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Genes, Volume 13, Issue 7 (July 2022) – 190 articles

Cover Story (view full-size image): Environmental and genetic risk factors are often associated with each other, as evidenced in established gene–environment correlation (rGE) findings. It is understood that this correlation becomes stronger throughout development as individuals become more able to select their environments (influenced by their genetic characteristics). Using data from three British longitudinal cohorts, we investigated whether rGE patterns between polygenic risk scores for schizophrenia as well as major depression and environmental risk factors change across childhood and adulthood. Overall, the majority of rGEs remained relatively stable across time. The few detected rGE changes differed between schizophrenia and major depression and are likely the result of changes in environmental risk factors, with genetic susceptibility to schizophrenia and major depression likely playing a less significant role. View this paper
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17 pages, 1404 KiB  
Article
Identification of New Toxicity Mechanisms in Drug-Induced Liver Injury through Systems Pharmacology
by Aurelio A. Moya-García, Andrés González-Jiménez, Fernando Moreno, Camilla Stephens, María Isabel Lucena and Juan A. G. Ranea
Genes 2022, 13(7), 1292; https://doi.org/10.3390/genes13071292 - 21 Jul 2022
Cited by 1 | Viewed by 2391
Abstract
Among adverse drug reactions, drug-induced liver injury presents particular challenges because of its complexity, and the underlying mechanisms are still not completely characterized. Our knowledge of the topic is limited and based on the assumption that a drug acts on one molecular target. [...] Read more.
Among adverse drug reactions, drug-induced liver injury presents particular challenges because of its complexity, and the underlying mechanisms are still not completely characterized. Our knowledge of the topic is limited and based on the assumption that a drug acts on one molecular target. We have leveraged drug polypharmacology, i.e., the ability of a drug to bind multiple targets and thus perturb several biological processes, to develop a systems pharmacology platform that integrates all drug–target interactions. Our analysis sheds light on the molecular mechanisms of drugs involved in drug-induced liver injury and provides new hypotheses to study this phenomenon. Full article
(This article belongs to the Special Issue Feature Papers in Technologies and Resources for Genetics)
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<p>Integration of domain and protein data in a drug similarity network. (<b>A</b>) Drugs <span class="html-italic">i</span> and <span class="html-italic">j</span> are associated if they target the same domains or the same proteins; (<b>B</b>) hypergeometric indices measuring the similarity of the domains profiles between <span class="html-italic">i</span> and <span class="html-italic">j</span> (pink) and the similarity of the protein profiles (yellow) are represented as a vector; (<b>C</b>) drug similarity matrix obtained from the modules (α) of the hypergeometric indices and distribution of the angles of the vectors obtained for all drug pairs; (<b>D</b>) the drug similarity network is built from the drug similarity matrix.</p>
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<p>Distribution of drug similarity vectors. The angle (γ) of the vectors formed by the similarities of the drug profiles depends on the threshold used for the hypergeometric index.</p>
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<p>Degree distribution of the drug similarity network. The degree distribution of the drug similarity network (full line) is compared with a scale-free model of the same size (dashed line).</p>
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<p>Assortative mixing of the drug similarity network. Nodes of different types are represented in green and orange circles (<b>A</b>) Assortative mixing of a network model in the low end of the assortativity range. (<b>B</b>) Assortative mixing of the drug similarity network. (<b>C</b>) Assortativity mixing of a network model in the upper end of the assortativity range.</p>
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<p>Modularity of the drug similarity network. The modularity (<span class="html-italic">M</span>) of the drug similarity network (<b>A</b>) is compared with a network model in the low end of the modularity range (<b>B</b>) and with a network model in the upper end of the modularity range (<b>C</b>).</p>
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14 pages, 1997 KiB  
Article
Further Insights on RNA Expression and Sperm Motility
by Carolina Silva, Paulo Viana, Alberto Barros, Rosália Sá, Mário Sousa and Rute Pereira
Genes 2022, 13(7), 1291; https://doi.org/10.3390/genes13071291 - 21 Jul 2022
Cited by 7 | Viewed by 3377
Abstract
Asthenozoospermia is one of the main causes of male infertility and it is characterized by reduced sperm motility. Several mutations in genes that code for structural or functional constituents of the sperm have already been identified as known causes of asthenozoospermia. In contrast, [...] Read more.
Asthenozoospermia is one of the main causes of male infertility and it is characterized by reduced sperm motility. Several mutations in genes that code for structural or functional constituents of the sperm have already been identified as known causes of asthenozoospermia. In contrast, the role of sperm RNA in regulating sperm motility is still not fully understood. Consequently, here we aim to contribute to the knowledge regarding the expression of sperm RNA, and ultimately, to provide further insights into its relationship with sperm motility. We investigated the expression of a group of mRNAs by using real-time PCR (CATSPER3, CFAP44, CRHR1, HIP1, IQCG KRT34, LRRC6, QRICH2, RSPH6A, SPATA33 and TEKT2) and the highest score corresponding to the target miRNA for each mRNA in asthenozoospermic and normozoospermic individuals. We observed a reduced expression of all mRNAs and miRNAs in asthenozoospermic patients compared to controls, with a more accentuated reduction in patients with progressive sperm motility lower than 15%. Our work provides further insights regarding the role of RNA in regulating sperm motility. Further studies are required to determine how these genes and their corresponding miRNA act regarding sperm motility, particularly KRT34 and CRHR1, which have not previously been seen to play a significant role in regulating sperm motility. Full article
(This article belongs to the Section RNA)
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<p>The presence of <span class="html-italic">SPATA33</span>, <span class="html-italic">RSPH6A</span>, <span class="html-italic">KRT34</span>, <span class="html-italic">CRHR1</span>, <span class="html-italic">CATSPER3</span> (<b>in the upper gel</b>), <span class="html-italic">HIP1</span>, <span class="html-italic">IQCG</span>, <span class="html-italic">LRCC6</span>, <span class="html-italic">QRICH2</span>, <span class="html-italic">TEKT2</span> and <span class="html-italic">CFAP44</span> (<b>in the lower gel</b>) transcripts in human ejaculated spermatozoa identified by PCR and running on a 1.5% agarose gel. <span class="html-italic">B2M</span> was used as control for the different tissues. L, DNA Ladder; B, blood; C, ciliated cells; T, testis; SZ, purified spermatozoa; NC, negative control.</p>
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<p>Box plot of CT values of <span class="html-italic">B2M</span> and <span class="html-italic">GAPDH</span> genes.</p>
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<p>Log of fold change of the mRNA expression levels in spermatozoa from patients with RPM &lt; 15% and RPM between 15–25%. Statistical significance was determined using the Kruskal–Wallis test, with α &lt; 0.05. ** <span class="html-italic">p</span> &lt; 0.01, and **** <span class="html-italic">p</span> &lt; 0.0001. <span class="html-italic">B2M</span> was used as reference gene.</p>
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<p>Log of fold change of the miRNA expression levels in spermatozoa from patients with RPM &lt; 15% and RPM between 15–25%. Statistical significance was determined using the Kruskal–Wallis test, with α &lt; 0.05. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001. <span class="html-italic">miR-30a-5p</span> (<b>left</b>) and <span class="html-italic">miR-100-5p</span> (<b>right</b>) were used as reference genes.</p>
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9 pages, 380 KiB  
Review
BK Virus Infection and BK-Virus-Associated Nephropathy in Renal Transplant Recipients
by Margherita Borriello, Diego Ingrosso, Alessandra Fortunata Perna, Angela Lombardi, Paolo Maggi, Lucia Altucci and Michele Caraglia
Genes 2022, 13(7), 1290; https://doi.org/10.3390/genes13071290 - 21 Jul 2022
Cited by 27 | Viewed by 7795
Abstract
Poliomavirus BK virus (BKV) is highly infective, causing asymptomatic infections during childhood. After the initial infection, a stable state of latent infection is recognized in kidney tubular cells and the uroepithelium with negligible clinical consequences. BKV is an important risk factor for BKV-associated [...] Read more.
Poliomavirus BK virus (BKV) is highly infective, causing asymptomatic infections during childhood. After the initial infection, a stable state of latent infection is recognized in kidney tubular cells and the uroepithelium with negligible clinical consequences. BKV is an important risk factor for BKV-associated diseases, and, in particular, for BKV-associated nephropathy (BKVN) in renal transplanted recipients (RTRs). BKVN affects up to 10% of renal transplanted recipients, and results in graft loss in up to 50% of those affected. Unfortunately, treatments for BK virus infection are restricted, and there is no efficient prophylaxis. In addition, consequent immunosuppressive therapy reduction contributes to immune rejection. Increasing surveillance and early diagnosis based upon easy and rapid analyses are resulting in more beneficial outcomes. In this report, the current status and perspectives in the diagnosis and treatment of BKV in RTRs are reviewed. Full article
(This article belongs to the Special Issue Genetic Markers and Liquid Biopsy for Kidney Diseases)
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<p>Graphical Sketch of BKV Genome. Early Genes Region: T-Ag (Large T antigen), T’-Ag (alternatively-spliced T-Ag), t-Ag (small T antigen); NCCR: Non-Coding Control Region; Late Genes Region: Agno (Agnoprotein), VP1–3 (viral capsid proteins).</p>
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27 pages, 1257 KiB  
Review
The Epitranscriptome in miRNAs: Crosstalk, Detection, and Function in Cancer
by Daniel del Valle-Morales, Patricia Le, Michela Saviana, Giulia Romano, Giovanni Nigita, Patrick Nana-Sinkam and Mario Acunzo
Genes 2022, 13(7), 1289; https://doi.org/10.3390/genes13071289 - 21 Jul 2022
Cited by 12 | Viewed by 4401
Abstract
The epitranscriptome encompasses all post-transcriptional modifications that occur on RNAs. These modifications can alter the function and regulation of their RNA targets, which, if dysregulated, result in various diseases and cancers. As with other RNAs, miRNAs are highly modified by epitranscriptomic modifications such [...] Read more.
The epitranscriptome encompasses all post-transcriptional modifications that occur on RNAs. These modifications can alter the function and regulation of their RNA targets, which, if dysregulated, result in various diseases and cancers. As with other RNAs, miRNAs are highly modified by epitranscriptomic modifications such as m6A methylation, 2′-O-methylation, m5C methylation, m7G methylation, polyuridine, and A-to-I editing. miRNAs are a class of small non-coding RNAs that regulates gene expression at the post-transcriptional level. miRNAs have gathered high clinical interest due to their role in disease, development, and cancer progression. Epitranscriptomic modifications alter the targeting, regulation, and biogenesis of miRNAs, increasing the complexity of miRNA regulation. In addition, emerging studies have revealed crosstalk between these modifications. In this review, we will summarize the epitranscriptomic modifications—focusing on those relevant to miRNAs—examine the recent crosstalk between these modifications, and give a perspective on how this crosstalk expands the complexity of miRNA biology. Full article
(This article belongs to the Special Issue Epitranscriptomics and Non-coding RNAs in Cancer)
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<p>Epitranscriptomic modifications regulate the maturation and downstream targeting of miRNAs. A-to-I editing interferes with Drosha processing, inhibiting the processing of pri-miRNAs to pre-miRNAs (brown arrows). m<sup>7</sup>G (grey arrows) disrupts the formation of inhibitory G-quadruplexes in the pri-miRNA and facilitates miRNA processing. A group of m<sup>7</sup>G-capped miRNAs undergo a non-canonical biogenesis pathway, bypassing Drosha processing and being exported by exportin-1. m<sup>6</sup>A enhances DCGR8 binding to pri-miRNAs to enhance miRNA processing (blue arrows). m<sup>5</sup>C impairs mRNA/miRNA complex formation, affecting miRNA targeting (purple arrows). Poly-U blocks Dicer cleavage and marks the pre-miRNA for degradation (pink arrows). Poly-U is added to the miRNA-directed cleaved mRNA for 5′ degradation. 2′-O-methyl protects the 3′ end of miRNA from degradation and enhances AGO2 binding, increasing target repression by miRNAs (green arrows).</p>
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<p>Crosstalk between epitranscriptomic modifications. (<b>A</b>) m<sup>6</sup>A regulation of ADAR1. The mRNA of ADAR1 is methylated by METTL3/METTL14 near the stop codon. This m<sup>6</sup>A mark recruits YTHDF1, which increases the protein translation of ADAR1. (<b>B</b>) m<sup>6</sup>Am modification at the first nucleotide. If the first nucleotide of an mRNA is adenine, the adenine can be methylated by m<sup>6</sup>A and 2′-O-methyl (m<sup>6</sup>Am). m<sup>6</sup>Am reduces the decapping activity of DCP2, thus rendering the mRNA resistant to miRNA-mediated degradation. (<b>C</b>) Cooperative interaction between m<sup>6</sup>A and m<sup>5</sup>C. m<sup>6</sup>A and m<sup>5</sup>C can cooperatively enhance the addition of each other to the 3′UTR of mRNAs. Both modifications occur close to the miRNA and AGO binding site. Their role in miRNA binding is speculative. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 17 February 2022).</p>
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15 pages, 1354 KiB  
Article
Haemolysis Detection in MicroRNA-Seq from Clinical Plasma Samples
by Melanie D. Smith, Shalem Y. Leemaqz, Tanja Jankovic-Karasoulos, Dale McAninch, Dylan McCullough, James Breen, Claire T. Roberts and Katherine A. Pillman
Genes 2022, 13(7), 1288; https://doi.org/10.3390/genes13071288 - 21 Jul 2022
Cited by 10 | Viewed by 2783
Abstract
The abundance of cell-free microRNA (miRNA) has been measured in blood plasma and proposed as a source of novel, minimally invasive biomarkers for several diseases. Despite improvements in quantification methods, there is no consensus regarding how haemolysis affects plasma miRNA content. We propose [...] Read more.
The abundance of cell-free microRNA (miRNA) has been measured in blood plasma and proposed as a source of novel, minimally invasive biomarkers for several diseases. Despite improvements in quantification methods, there is no consensus regarding how haemolysis affects plasma miRNA content. We propose a method for haemolysis detection in miRNA high-throughput sequencing (HTS) data from libraries prepared using human plasma. To establish a miRNA haemolysis signature we tested differential miRNA abundance between plasma samples with known haemolysis status. Using these miRNAs with statistically significant higher abundance in our haemolysed group, we further refined the set to reveal high-confidence haemolysis association. Given our specific context, i.e., women of reproductive age, we also tested for significant differences between pregnant and non-pregnant groups. We report a novel 20-miRNA signature used to identify the presence of haemolysis in silico in HTS miRNA-sequencing data. Further, we validated the signature set using firstly an all-male cohort (prostate cancer) and secondly a mixed male and female cohort (radiographic knee osteoarthritis). Conclusion: Given the potential for haemolysis contamination, we recommend that assays for haemolysis detection become standard pre-analytical practice and provide here a simple method for haemolysis detection. Full article
(This article belongs to the Special Issue Small RNA Bioinformatics)
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<p>The number of mature miRNA species identified in an individual sample increases with read depth for both haemolysed (dark red) and non-haemolysed (blue) samples. However, the number of mature miRNA species identified for a given read depth is significantly lower (ANOVA, <span class="html-italic">p</span>-value = 1.68 × 10-9) in samples affected by haemolysis when compared to a non-haemolysed sample of equal read depth (<span class="html-italic">n</span> = 121).</p>
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<p>(<b>a</b>) A comparison of the derived haemolysis metric and the ΔCq measure of haemolysis shows a clear correlation. We identified 13 samples (named) that we suggest should be discarded or used with caution in further analysis. (<b>b</b>) Histogram of haemolysis metric values from the 121 samples in our experiment, coloured according to their ΔCq (miR-23a-3p-miR-451a) classification, indicate a minimum haemolysis metric of ≥ 1.9 for samples previously identified as haemolysed.</p>
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13 pages, 1904 KiB  
Article
The Complete Mitochondrial Genome of Ophioglossum vulgatum L. Is with Highly Repetitive Sequences: Intergenomic Fragment Transfer and Phylogenetic Analysis
by Jing Hao, Yingyi Liang, Yingjuan Su and Ting Wang
Genes 2022, 13(7), 1287; https://doi.org/10.3390/genes13071287 - 21 Jul 2022
Cited by 11 | Viewed by 2393
Abstract
Many plant mitochondrial (mt) genomes have been sequenced but few in ferns. Ophioglossum vulgatum represents a typical species of fern genus Ophioglossum with medicinal and scientific value. However, its mt genome structure remains to be characterized. This study assembled and annotated the complete [...] Read more.
Many plant mitochondrial (mt) genomes have been sequenced but few in ferns. Ophioglossum vulgatum represents a typical species of fern genus Ophioglossum with medicinal and scientific value. However, its mt genome structure remains to be characterized. This study assembled and annotated the complete O. vulgatum mt genome and presented its structural characters and repeat sequences firstly. Its mt and chloroplast (cp) transfer sequences were explored, and the phylogenetic significance of both mt and cp genomes was also evaluated at the family level. Our results showed that the complete mt genome of O. vulgatum is a single circular genome of 369,673 bp in length, containing 5000 dispersed repetitive sequences. Phylogenetic trees reconstructed from cp and mt genomes displayed similar topologies, but also showed subtle differences at certain nodes. There exist 4818 bp common gene fragments between cp and mt genomes, of which more than 70% are located in tRNA intergenic regions (in mt). In conclusion, we assembled the complete mt genome of O. vulgatum, identified its remarkable structural characters, and provided new insights on ferns. The complementary results derived from mt and cp phylogeny highlighted that some higher taxonomic-level phylogenetic relationships among ferns remain to be resolved. Full article
(This article belongs to the Special Issue Advances in Evolution of Plant Organelle Genome)
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Graphical abstract

Graphical abstract
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<p>Mitochondrial genome map of <span class="html-italic">O. vulgatum</span>. The total length of the mitochondrial genome is 369,673 bp. Genes shown on the inside of the circle are transcribed clockwise, whereas those on the outside are transcribed counter-clockwise. Genes containing introns are marked by an asterisk (*).</p>
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<p>Hypervariable regions between <span class="html-italic">O. vulgatum</span> and <span class="html-italic">O. californicum</span>. The horizontal axis shows the location information for <span class="html-italic">O. vulgatum</span> mitochondrial genome, and the vertical axis shows the Pi values.</p>
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<p>Maximum likelihood (ML) trees reconstructed by using concatenated datasets of common mitochondrial (left) and chloroplast (right) genes of representative species. Red numbers below the branches are bootstrap values. Values above the branches are branch lengths. The boxes with different colors represent different plant groups (the bryophytes, ferns, gymnosperms, monocots, and dicots).</p>
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<p>Locations of the transferred fragments between mitochondrial and chloroplast genomes. Green circle represents mitochondrial genome, and orange circle chloroplast genome. Blue and red lines inside the circle correspond to fragment lengths more or less than 100 bp, respectively. Ends of the same line indicate the location of common gene fragments.</p>
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<p>Simple sequence repeats (SSRs) and dispersed repetitive sequences in the mitochondrial genome of <span class="html-italic">O. vulgatum</span>. Black lines on the blue circle indicate the SSR locations. Lines inside the circle show the distribution of dispersed repetitive sequences; green lines represent forward (F) repeats, and orange lines represent palindromic (P) repeats (light green and orange lines correspond to lengths less than 200 bp).</p>
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<p>Simple sequence repeats (SSRs) characteristic of 18 representative species and their association with phylogeny. P1, p2, p3, p4, p5, p6, and c (*) represent mono-, di-, tri-, tetra-, penta-, hexa-, and compound SSRs, respectively. Clades in the tree are highlighted with color boxes. Horizontal axis in the right figure presents the number of different SSR types.</p>
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20 pages, 6167 KiB  
Article
Germline Testing in a Cohort of Patients at High Risk of Hereditary Cancer Predisposition Syndromes: First Two-Year Results from South Italy
by Francesco Paduano, Emma Colao, Fernanda Fabiani, Valentina Rocca, Francesca Dinatolo, Adele Dattola, Lucia D’Antona, Rosario Amato, Francesco Trapasso, Francesco Baudi, Nicola Perrotti and Rodolfo Iuliano
Genes 2022, 13(7), 1286; https://doi.org/10.3390/genes13071286 - 21 Jul 2022
Cited by 9 | Viewed by 3702
Abstract
Germline pathogenic variants (PVs) in oncogenes and tumour suppressor genes are responsible for 5 to 10% of all diagnosed cancers, which are commonly known as hereditary cancer predisposition syndromes (HCPS). A total of 104 individuals at high risk of HCPS were selected by [...] Read more.
Germline pathogenic variants (PVs) in oncogenes and tumour suppressor genes are responsible for 5 to 10% of all diagnosed cancers, which are commonly known as hereditary cancer predisposition syndromes (HCPS). A total of 104 individuals at high risk of HCPS were selected by genetic counselling for genetic testing in the past 2 years. Most of them were subjects having a personal and family history of breast cancer (BC) selected according to current established criteria. Genes analysis involved in HCPS was assessed by next-generation sequencing (NGS) using a custom cancer panel with high- and moderate-risk susceptibility genes. Germline PVs were identified in 17 of 104 individuals (16.3%) analysed, while variants of uncertain significance (VUS) were identified in 21/104 (20.2%) cases. Concerning the germline PVs distribution among the 13 BC individuals with positive findings, 8/13 (61.5%) were in the BRCA1/2 genes, whereas 5/13 (38.4%) were in other high- or moderate-risk genes including PALB2, TP53, ATM and CHEK2. NGS genetic testing showed that 6/13 (46.1%) of the PVs observed in BC patients were detected in triple-negative BC. Interestingly, the likelihood of carrying the PVs in the moderate-to-high-risk genes calculated by the cancer risk model BOADICEA was significantly higher in pathogenic variant carriers than in negative subjects. Collectively, this study shows that multigene panel testing can offer an effective diagnostic approach for patients at high risk of hereditary cancers. Full article
(This article belongs to the Special Issue Feature Papers: Molecular Genetics and Genomics)
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<p>Study flow chart. PVs, pathogenic variants; VUS, variants of uncertain significance; BC, breast cancer; HBOC, hereditary breast and ovarian cancer syndrome.</p>
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<p>Distribution of patients selected for NGS genetic testing concerning inclusion criteria. (1) Women with BC and OC; males with BC; women with triple-negative breast cancer (TNBC) &lt; 60 years; women with BC &lt; 36 years; women with bilateral BC &lt; 50 years; not mucinous and not borderline OC at any age; metastatic pancreatic adenocarcinoma; metastatic prostatic carcinoma. (2) Personal history of breast cancer diagnosed &lt; 50 years and at least one first-degree relative with nonmucinous and nonborderline OC at any age; BC &lt; 50 years; male BC; bilateral BC; metastatic pancreatic adenocarcinoma and metastatic prostatic carcinoma. (3) Personal history of BC &gt; 50 years and family history of breast, ovarian cancer, metastatic prostatic carcinoma and metastatic pancreatic adenocarcinoma in 2 or more first-degree relatives (one of which in the first degree with the proband). (4) Presence of personal and family history that did not meet AIOM criteria. (5) Patients that were not affected by tumours described by AIOM criteria.</p>
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<p>Characteristics of study participants. (<b>A</b>) Sex distribution. (<b>B</b>) Age of diagnosis. (<b>C</b>) Type of tumours. (<b>D</b>) BC histology. (<b>E</b>) BC molecular subtype. (<b>F</b>) Family cancer history; BC: breast cancer; BOC: breast and ovarian cancer; PC: prostate cancer; OC: ovarian cancer; TN: triple-negative; CDI: invasive ductal carcinoma; CLI: invasive lobular carcinoma; DCIS: ductal carcinoma in situ; LUM: luminal; LFS: Li–Fraumeni syndrome.</p>
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<p>Likelihood of carrying PVs in the moderate-to-high-risk genes in eighty-eight BC, five OC and three PC (n = 96) patients using a 10% pretest probability threshold. (<b>A</b>) Number of patients having BOADICEA &gt;10% and ≤10%. (<b>B</b>) Patient’s risk in the well-known high-penetrance alleles <span class="html-italic">BRCA1</span> and <span class="html-italic">BRCA2</span> with respect to other moderate-penetrance alleles including <span class="html-italic">PALB2</span>, <span class="html-italic">CHEK2, ATM, BARD1, RAD51D, RAD51C</span> and <span class="html-italic">BRIP1</span>.</p>
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<p>(<b>A</b>) Overall results of NGS panel testing. Importantly, the VUS rate does not include VUS detected in patients with P/LP variants. (<b>B</b>) Outcomes of panel testing for the 104 individuals tested. (<b>C</b>) Distribution of PVs concerning enrolling criteria. (<b>D</b>) Distribution of PVs among tumours. (<b>E</b>) Distribution of PVs among genes. (<b>F</b>) Distribution of 17 pathogenic variants by effect.</p>
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<p>(<b>A</b>) Distribution of molecular subtypes in the study cohort. (<b>B</b>) Prevalence of molecular subtypes in positive <span class="html-italic">BRCA1</span>- and <span class="html-italic">BRCA2</span>- breast cancer patients.</p>
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<p>BOADICEA scores in LP/P variant-positive HBOC and prostate cancer patients versus negative and patients carrying VUS. (<b>A</b>) Distribution of total % BOADICEA score (likelihood of carrying PVs, sum of <span class="html-italic">BRCA1</span>, <span class="html-italic">BRCA2</span>, <span class="html-italic">PALB2, CHEK2, ATM</span>, <span class="html-italic">BARD1</span>, <span class="html-italic">RAD51D, RAD51C</span> and <span class="html-italic">BRIP1</span>) for each patient. (<b>B</b>) BOADICEA scores between groups of patients depending on variant status (VUS, LP/P and negative). Differences between groups were assessed by the Mann–Whitney test; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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17 pages, 15098 KiB  
Article
Transcriptomic and Metabolomic Analyses Provide Insights into the Formation of the Peach-like Aroma of Fragaria nilgerrensis Schlecht. Fruits
by Ai-Hua Wang, Hong-Ye Ma, Bao-Hui Zhang, Chuan-Yuan Mo, En-Hong Li and Fei Li
Genes 2022, 13(7), 1285; https://doi.org/10.3390/genes13071285 - 20 Jul 2022
Cited by 12 | Viewed by 2758
Abstract
Fragaria nilgerrensis Schlecht. is a wild diploid strawberry species. The intense peach-like aroma of its fruits makes F. nilgerrensis an excellent resource for strawberry breeding programs aimed at enhancing flavors. However, the formation of the peach-like aroma of strawberry fruits has not been [...] Read more.
Fragaria nilgerrensis Schlecht. is a wild diploid strawberry species. The intense peach-like aroma of its fruits makes F. nilgerrensis an excellent resource for strawberry breeding programs aimed at enhancing flavors. However, the formation of the peach-like aroma of strawberry fruits has not been comprehensively characterized. In this study, fruit metabolome and transcriptome datasets for F. nilgerrensis (HA; peach-like aroma) and its interspecific hybrids PA (peach-like aroma) and NA (no peach-like aroma; control) were compared. In total, 150 differentially accumulated metabolites were detected. The K-means analysis revealed that esters/lactones, including acetic acid, octyl ester, δ-octalactone, and δ-decalactone, were more abundant in HA and PA than in NA. These metabolites may be important for the formation of the peach-like aroma of F. nilgerrensis fruits. The significantly enriched gene ontology terms assigned to the differentially expressed genes (DEGs) were fatty acid metabolic process and fatty acid biosynthetic process. Twenty-seven DEGs were predicted to be associated with ester and lactone biosynthesis, including AAT, LOX, AOS, FAD, AIM1, EH, FAH, ADH, and cytochrome P450 subfamily genes. Thirty-five transcription factor genes were predicted to be associated with aroma formation, including bHLH, MYB, bZIP, NAC, AP2, GATA, and TCPfamily members. Moreover, we identified differentially expressed FAD, AOS, and cytochrome P450 family genes and NAC, MYB, and AP2 transcription factor genes that were correlated with δ-octalactone and δ-decalactone. These findings provide key insights into the formation of the peach-like aroma of F. nilgerrensis fruits, with implications for the increased use of wild strawberry resources. Full article
(This article belongs to the Section Plant Genetics and Genomics)
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<p>Analysis of all metabolites. Metabolite types (<b>a</b>). Two-dimensional principal component analysis plot (<b>b</b>). Heatmap for the hierarchical clustering analysis (<b>c</b>).</p>
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<p>Metabolomics profiling. Orthogonal partial least squares-discriminant analysis (OPLS-DA) of NA vs. HA (<b>a</b>) and NA vs. PA (<b>b</b>). The 200-response sorting tests of the OPLS-DA model for NA vs. HA (<b>a′</b>) and NA vs. PA (<b>b′</b>). Q<sup>2</sup> is an important parameter for evaluating the OPLS-DA model. R<sup>2</sup>X and R<sup>2</sup>Y represent the percentage of the OPLS-DA model that can explain the X and Y matrix information, respectively.</p>
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<p>Venn diagram (<b>a</b>) and K-means (<b>b</b>) analyses of differentially abundant metabolites.</p>
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<p>Venn diagram analysis of differentially expressed genes.</p>
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<p>GO analysis of differentially expressed genes (<b>a</b>,<b>b</b>).</p>
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<p>KEGG analysis of differentially expressed genes (<b>a</b>,<b>b</b>).</p>
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<p>Relative expression levels of the structural DEGs related to ester and lactone biosynthesis. Significant differences in expression levels are indicated by an asterisk.</p>
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<p>Expression patterns of genes encoding TFs are involved in the regulation of aroma formation.</p>
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<p>Analyses of the correlation between 27 key structural genes and 29 key metabolites (<b>a</b>) and between 35 key TFs and 29 key metabolites (<b>b</b>).</p>
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<p>Analyses of the correlation between key structural genes and two key lactones (<b>a</b>) and between TFs and two key lactones (<b>b</b>). Blue circles represent the differentially expressed genes and TFs, whereas red circles represent the two key lactones. The solid and dotted lines indicate positive and negative correlations, respectively.</p>
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14 pages, 1555 KiB  
Systematic Review
Genetic Biomarkers as Predictors of Response to Tocilizumab in Rheumatoid Arthritis: A Systematic Review and Meta-Analysis
by Sivakami Janahiraman, Chun Lai Too, Kai Wei Lee, Nor Shuhaila Shahril and Chee Onn Leong
Genes 2022, 13(7), 1284; https://doi.org/10.3390/genes13071284 - 20 Jul 2022
Cited by 7 | Viewed by 3216
Abstract
Rheumatoid arthritis (RA) is a lifelong, debilitating disease which incredibly impacts a patient’s quality of life if not treated to the optimal target. The clinical response of tocilizumab, an interleukin-6 (IL-6) inhibitor, is associated with several gene polymorphisms, particularly targeting the IL-6 pathway. [...] Read more.
Rheumatoid arthritis (RA) is a lifelong, debilitating disease which incredibly impacts a patient’s quality of life if not treated to the optimal target. The clinical response of tocilizumab, an interleukin-6 (IL-6) inhibitor, is associated with several gene polymorphisms, particularly targeting the IL-6 pathway. This systematic review and meta-analysis seeks to investigate genetic biomarkers that predict the treatment outcome of tocilizumab therapy in RA patients. After evaluating the quality of retrieved records, five studies were chosen to carry out a quantitative synthesis involving 591 participants. We analysed genetic markers of IL-6R single nucleotide polymorphism (SNP)s rs12083537, rs2228145 and rs4329505, FCGR3A, CD69, GALNT18 and FCGR2A. A plausible finding based on meta-analysis revealed that RA patients with homozygous AA genotype for rs12083537 polymorphism of the IL-6R gene demonstrate a better response to TCZ treatment as opposed to homozygous and heterozygous patients with the G allele. Nonetheless, limitations in evaluating the available studies by meta-analysis include a lack of studies with dissimilarities in study design and outcome definitions, small sample sizes with low statistical power and heterogeneity of cohorts, a restricted the number of tested SNPs and small effects for the selected variants. Inconsistent finding remains as a great challenge to forge ahead towards personalised medicine for RA management. Full article
(This article belongs to the Section Pharmacogenetics)
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<p>PRISMA flow diagram of study selection process.</p>
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<p>Forest plot of IL-6R rs 12083537 (genotype AA as control vs. genotype GG as testing/risk genotype) and response to TCZ treatment [<a href="#B22-genes-13-01284" class="html-bibr">22</a>,<a href="#B23-genes-13-01284" class="html-bibr">23</a>] (Ev/Trt refers to number of participants not responding to the treatment in the cohort of GG genotype carrier. Ev/Ctrl refers to number of participants not responding to the treatment in the cohort of AA genotype carrier).</p>
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<p>Forest plot of IL-6R rs 12083537 (genotype AA as control vs. genotype AG as testing/risk genotype) and response to TCZ treatment [<a href="#B20-genes-13-01284" class="html-bibr">20</a>,<a href="#B22-genes-13-01284" class="html-bibr">22</a>,<a href="#B23-genes-13-01284" class="html-bibr">23</a>] (Ev/Trt refers to number of participants not responding to the treatment in the cohort of AG genotype carrier. Ev/Ctrl refers to number of participants not responding to the treatment in the cohort of AA genotype carrier).</p>
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<p>Forest plot of IL-6R rs 12083537 (allele A as control vs. allele G as risk allele) and response to TCZ treatment [<a href="#B20-genes-13-01284" class="html-bibr">20</a>,<a href="#B22-genes-13-01284" class="html-bibr">22</a>,<a href="#B23-genes-13-01284" class="html-bibr">23</a>] (Ev/Trt refers to number of participants not responding to the treatment in the cohort of G allele carrier. Ev/Ctrl refers to number of participants not responding to the treatment in the cohort of A allele carrier).</p>
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6 pages, 777 KiB  
Article
Clinical Features and Novel Genetic Variants Associated with Hermansky-Pudlak Syndrome
by Chonglin Chen, Ruixin Wang, Yongguang Yuan, Jun Li and Xinping Yu
Genes 2022, 13(7), 1283; https://doi.org/10.3390/genes13071283 - 20 Jul 2022
Cited by 5 | Viewed by 2264
Abstract
Hermansky-Pudlak syndrome (HPS) is a rare autosomal recessive syndromic form of albinism, characterized by oculocutaneous albinism (OCA) and other systemic complications. The purpose of this study was to investigate patients with HPS-associated gene mutations and describe associated ocular and extraocular phenotypes. Fifty-four probands [...] Read more.
Hermansky-Pudlak syndrome (HPS) is a rare autosomal recessive syndromic form of albinism, characterized by oculocutaneous albinism (OCA) and other systemic complications. The purpose of this study was to investigate patients with HPS-associated gene mutations and describe associated ocular and extraocular phenotypes. Fifty-four probands clinically diagnosed as albinism were enrolled. Ophthalmic examinations and genetic testing were performed in all subjects. The phenotypic and genetic features were evaluated. HPS-associated gene mutation was identified in four of the patients with albinism phenotype. Clinically, photophobia, and nystagmus was detected in all (4/4) patients, and strabismus was found in one (1/4) patient. Fundus examination revealed fundus hypopigmentation and foveal hypoplasia in all (8/8) eyes. Eight novel causative mutations were detected in these four HPS probands. Five (62.5%, 5/8) of the mutations were nonsense, two of the mutations were missense (25%, 2/8), and one of the mutations was frameshift (12.5%, 1/8). All patients in our study carried compound heterozygous variants, and all these pathogenic variants were identified to be novel, with most (62.5%, 5/8) of the mutations being nonsense. Our results improved the understanding of clinical ocular features, and expanded the spectrum of known variants and the genetic background of HPS. Full article
(This article belongs to the Special Issue Genetics and Pathogenesis of Inherited Eye Diseases)
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<p>Representative clinical findings in patients with causative <span class="html-italic">HPS6</span> mutation. Figure shows a 5-year-old patient who carried compound heterozygous variants in <span class="html-italic">HPS6</span> NM_024747, c.1021C&gt;T (p.Gln341*) and c.1146_1147delTC (p.Gly382Glyfs*13). His hair color is brown (<b>A</b>) and iris color is brownish-black (<b>B</b>). Hypopigmentation was detected in the fundus (<b>C</b>) and foveal hypoplasia was shown in the OCT (<b>D</b>).</p>
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<p>Schematic pedigrees of the families with causative HPS-associated gene mutations. Arrows indicate proband; filled symbols indicate compound heterozygous; Half-filled areas indicate heterozygous and unfilled indicate unaffected individuals.</p>
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16 pages, 7504 KiB  
Article
Comprehensive Analysis of HMCN1 Somatic Mutation in Clear Cell Renal Cell Carcinoma
by Ziqi Gong, Xiaowen Wu, Qian Guo, Haizhen Du, Fenghao Zhang and Yan Kong
Genes 2022, 13(7), 1282; https://doi.org/10.3390/genes13071282 - 20 Jul 2022
Cited by 6 | Viewed by 2831
Abstract
Background: Renal cell carcinoma (RCC) is a common malignancy of the genitourinary system and clear cell renal cell carcinoma (ccRCC) is the most representative subtype. The morbidity and mortality of ccRCC have gradually risen during recent years; however, the pathogenesis and potential biomarkers [...] Read more.
Background: Renal cell carcinoma (RCC) is a common malignancy of the genitourinary system and clear cell renal cell carcinoma (ccRCC) is the most representative subtype. The morbidity and mortality of ccRCC have gradually risen during recent years; however, the pathogenesis and potential biomarkers remain unclear. The purpose of our study was to find out prognostic genes correlated with somatic mutation and the underlying mechanisms of HMCN1 mutation in ccRCC. Methods: Somatic mutation data of two ccRCC cohorts were acquired from TCGA and cBioPortal. Genes frequently mutated in both datasets were extracted, from which tumor mutation burden and survival analysis revealed three prognostic genes. Further comprehensive analysis of HMCN1 mutation was carried out to identify differentially expressed genes and apply functional annotations. The correlation of HMCN1 mutation and tumor immunity was also evaluated. Results: HMCN1, SYNE1, and BAP1 mutations were associated with both tumor mutation burden and clinical prognosis in ccRCC. Gene enrichment analysis suggested the effects of HMCN1 mutation on biological processes and pathways linked to energy metabolism. HMCN1 mutation was also correlated with anti-tumor immunity. There were several limitations in the sample size and cohort availability of the present computational study. Conclusions: The present results inferred that HMCN1 mutation might have an important clinical significance for ccRCC patients by regulating metabolism and the immune microenvironment. Full article
(This article belongs to the Special Issue Bioinformatic Analysis of NGS Data)
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<p>Workflow chart of the analysis process.</p>
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<p>Profile of frequently mutated genes in KIRC. (<b>A</b>) Waterfall plot illustrating the top 30 genes in TCGA cohort. (<b>B</b>) Waterfall plot demonstrating the top 30 genes in UTokyo cohort.</p>
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<p>TMB-related gene mutations. (<b>A</b>) Venn diagram figures out 12 frequently mutated genes included in both two cohorts. (<b>B</b>) Boxplot reveals the correlation of gene mutation and TMB. *: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.01; ***: <span class="html-italic">p</span> &lt; 0.001; ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>Gene mutations associated with prognosis. Kaplan–Meier survival curves of three gene mutations significantly correlated with clinical prognosis. (<b>A</b>): <span class="html-italic">HMCN1</span> mutation is associated with poorer prognosis; (<b>B</b>): <span class="html-italic">BAP1</span> mutation is associated with poorer prognosis; (<b>C</b>): <span class="html-italic">SYNE1</span> mutation is associated with poorer prognosis.</p>
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<p>Univariate (<b>A</b>) and multivariate (<b>B</b>) Cox regression model of KIRC.</p>
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<p>Differentially expressed genes analysis. (<b>A</b>) Volcano map of DEGs. Red: significantly upregulated genes; Green: significantly down-regulated genes. (<b>B</b>) Heatmap of DEGs. (<b>C</b>) <span class="html-italic">HMCN1</span> mutation types and sites in KIRC. Green: von Willebrand factor type A domain; Red: Immunoglobulin I-set domain; Blue: Thrombospondin type 1 domain; Yellow: G2F domain; Purple: Calcium-binding EGF domain; Orange: Complement Clr-like EGF-like.</p>
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<p>GO and KEGG analysis. (<b>A</b>) Bar graph of gene ontology functional annotations. (<b>B</b>) Bar graph of KEGG pathway enrichment analysis.</p>
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<p><span class="html-italic">HMCN1</span> mutation-related pathways. (<b>A</b>) Multigene enrichment plot shows gene sets enriched in <span class="html-italic">HMCN1</span>-mutant cases. (<b>B</b>) Multigene enrichment plot shows gene sets enriched in wild-type cases. (<b>C</b>) Several enrichment plots displaying a series of metabolism-related pathways.</p>
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<p>The PPI network and two submodules. (<b>A</b>) PPI network of the DEGs. (<b>B</b>) Stacked bar chart of top 30 hub genes. (<b>C</b>) PPI network of module 1. (<b>D</b>) PPI network of module 2.</p>
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<p><span class="html-italic">HMCN1</span> mutation is related to tumor immune microenvironment. (<b>A</b>) The composition of 22 types of immune cells. (<b>B</b>) The correlation graph of immune cells. (<b>C</b>) The difference of immune cell proportion between mutant and wild-type samples. (<b>D</b>) Representative immune check point genes expression in mutant and wild-type samples.</p>
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8 pages, 610 KiB  
Article
MicroRNA Processing Pathway-Based Polygenic Score for Clear Cell Renal Cell Carcinoma in the Volga-Ural Region Populations of Eurasian Continent
by Elizaveta Ivanova, Irina Gilyazova, Valentin Pavlov, Adel Izmailov, Galiya Gimalova, Alexandra Karunas, Inga Prokopenko and Elza Khusnutdinova
Genes 2022, 13(7), 1281; https://doi.org/10.3390/genes13071281 - 20 Jul 2022
Cited by 2 | Viewed by 1996
Abstract
The polygenic scores (PGSs) are developed to help clinicians in distinguishing individuals at high risk of developing disease outcomes from the general population. Clear cell renal cell carcinoma (ccRCC) is a complex disorder that involves numerous biological pathways, one of the most important [...] Read more.
The polygenic scores (PGSs) are developed to help clinicians in distinguishing individuals at high risk of developing disease outcomes from the general population. Clear cell renal cell carcinoma (ccRCC) is a complex disorder that involves numerous biological pathways, one of the most important of which is responsible for the microRNA biogenesis machinery. Here, we defined the biological-pathway-specific PGS in a case-control study of ccRCC in the Volga-Ural region of the Eurasia continent. We evaluated 28 DNA SNP variants, located in microRNA biogenesis genes, in 464 individuals with clinically diagnosed ccRCC and 1042 individuals without the disease. Individual genetic risks were defined using the SNP-variant effects derived from the ccRCC association analysis. The final weighted and unweighted PGS models were based on 21 SNPs, and 7 SNPs were excluded due to high LD. In our dataset, microRNA-machinery-weighted PGS revealed 1.69-fold higher odds (95% CI [1.51–1.91]) for ccRCC risk in individuals with ccRCC compared with controls with a p-value of 2.0 × 10−16. The microRNA biogenesis pathway weighted PGS predicted the risk of ccRCC with an area under the curve (AUC) = 0.642 (95%nCI [0.61–0.67]). Our findings indicate that DNA variants of microRNA machinery genes modulate the risk of ccRCC in Volga-Ural populations. Moreover, larger powerful genome-wide association studies are needed to reveal a wider range of genetic variants affecting microRNA processing. Biological-pathway-based PGSs will advance the development of innovative screening systems for future stratified medicine approaches in ccRCC. Full article
(This article belongs to the Special Issue Feature Papers: Molecular Genetics and Genomics)
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<p>ROC curves assessing the discriminative power of the weighted PGS model for the ccRCC risk. The best predictive point is shown with the ideal cut-off for the PGS and with estimates for specificity and sensitivity at that point. AUC, area under the curve.</p>
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16 pages, 13190 KiB  
Article
Plastid Phylogenomics and Plastomic Diversity of the Extant Lycophytes
by Sisi Chen, Ting Wang, Jiangping Shu, Qiaoping Xiang, Tuo Yang, Xianchun Zhang and Yuehong Yan
Genes 2022, 13(7), 1280; https://doi.org/10.3390/genes13071280 - 19 Jul 2022
Cited by 6 | Viewed by 2927
Abstract
Although extant lycophytes represent the most ancient surviving lineage of early vascular plants, their plastomic diversity has long been neglected. The ancient evolutionary history and distinct genetic diversity patterns of the three lycophyte families, each with its own characteristics, provide an ideal opportunity [...] Read more.
Although extant lycophytes represent the most ancient surviving lineage of early vascular plants, their plastomic diversity has long been neglected. The ancient evolutionary history and distinct genetic diversity patterns of the three lycophyte families, each with its own characteristics, provide an ideal opportunity to investigate the interfamilial relationships of lycophytes and their associated patterns of evolution. To compensate for the lack of data on Lycopodiaceae, we sequenced and assembled 14 new plastid genomes (plastomes). Combined with other lycophyte plastomes available online, we reconstructed the phylogenetic relationships of the extant lycophytes based on 93 plastomes. We analyzed, traced, and compared the plastomic diversity and divergence of the three lycophyte families (Isoëtaceae, Lycopodiaceae, and Selaginellaceae) in terms of plastomic diversity by comparing their plastome sizes, GC contents, substitution rates, structural rearrangements, divergence times, ancestral states, RNA editings, and gene losses. Comparative analysis of plastid phylogenomics and plastomic diversity of three lycophyte families will set a foundation for further studies in biology and evolution in lycophytes and therefore in vascular plants. Full article
(This article belongs to the Special Issue Advances in Evolution of Plant Organelle Genome)
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<p>Phylogenetic tree inferred by the maximum likelihood (ML) and Bayesian methods based on 84 CDSs from 93 plastomes of 81 lycophytes and 12 outgroup species. ML bootstrap (BS) and Bayesian posterior probability (PP) support values are separated by ‘/’ and marked on each branch (* indicates BS = 100 or PP = 1). (<b>A</b>) <span class="html-italic">Phlegmariurus petiolatus</span> [Photos: XL Zhou], (<b>B</b>) <span class="html-italic">Huperzia javanica</span> [Photos: SS Chen], (<b>C</b>) Palhinhaea cernua [Photos: YH Yan], (<b>D</b>) <span class="html-italic">L. japonicum</span> [Photos: YH Yan], (<b>E</b>) <span class="html-italic">Isoëtes sinensis</span> [Photos: YF Gu], (<b>F</b>) <span class="html-italic">Selaginella tamariscina</span> [Photos: JP Shu], and (<b>G</b>) <span class="html-italic">Selaginella biformis</span> [Photos: YH Yan].</p>
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<p>Sliding window analysis of GC content of 8 representative lycophyte plastomes. Each large figure represents the GC content distribution along a plastome. The yellow, green, red, and orange blocks at the bottom of the blue plots represent genes, CDSs, tRNA, and rRNA genes, and the two repeat regions, respectively. The middle panels represent the GC content of one of the repeat regions, connected to the corresponding species by black crossed lines. All sliding window sizes were 100 bp.</p>
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<p>Overall substitution rates (OSRs) of noncoding sequences in repeat regions, SC regions, and rRNA regions; synonymous substitution rates (dS), nonsynonymous substitution rates (dN) of all coding sequences (CDS).</p>
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<p>The numbers and types of predicted RNA-editing sites in the CDSs of lycophyte plastomes.</p>
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<p>Ancestral state reconstruction of gene numbers (<b>left</b>) and GC content (<b>right</b>) along the divergence time tree of the lycophytes inferred from MCMCTree. The full posterior distributions were displayed on nodes (<b>left</b>), and the positions of fossil node calibrations were marked by colored circles (<b>right</b>).</p>
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23 pages, 8473 KiB  
Article
Comparative Analysis of the Complete Chloroplast Genomes in Allium Section Bromatorrhiza Species (Amaryllidaceae): Phylogenetic Relationship and Adaptive Evolution
by Junpei Chen, Dengfeng Xie, Xingjin He, Yi Yang and Xufeng Li
Genes 2022, 13(7), 1279; https://doi.org/10.3390/genes13071279 - 19 Jul 2022
Cited by 13 | Viewed by 3216
Abstract
With the development of molecular sequencing approaches, many taxonomic and phylogenetic problems of the genus Allium L. have been solved; however, the phylogenetic relationships of some subgenera or sections, such as section Bromatorrhiza, remain unresolved, which has greatly impeded our full understanding [...] Read more.
With the development of molecular sequencing approaches, many taxonomic and phylogenetic problems of the genus Allium L. have been solved; however, the phylogenetic relationships of some subgenera or sections, such as section Bromatorrhiza, remain unresolved, which has greatly impeded our full understanding of the species relationships among the major clades of Allium. In this study, the complete chloroplast (cp) genomes of nine species in the Allium sect. Bromatorrhiza were determined using the Illumina paired-end sequencing, the NOVOPlasty de novo assembly strategy, and the PGA annotation method. The results showed that the cp genome exhibited high conservation and revealed a typical circular tetrad structure. Among the sect. Bromatorrhiza species, the gene content, SSRs, codon usage, and RNA editing site were similar. The genome structure and IR regions’ fluctuation were investigated while genes, CDSs, and non-coding regions were extracted for phylogeny reconstruction. Evolutionary rates (Ka/Ks values) were calculated, and positive selection analysis was further performed using the branch-site model. Five hypervariable regions were identified as candidate molecular markers for species authentication. A clear relationship among the sect. Bromatorrhiza species were detected based on concatenated genes and CDSs, respectively, which suggested that sect. Bromatorrhiza is monophyly. In addition, there were three genes with higher Ka/Ks values (rps2, ycf1, and ycf2), and four genes (rpoC2, atpF, atpI, and rpl14) were further revealed to own positive selected sites. These results provide new insights into the plastome component, phylogeny, and evolution of Allium species. Full article
(This article belongs to the Special Issue Genetics of Abiotic Stress Tolerance in Plants)
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<p>Maps of nine sect. <span class="html-italic">Bromatorrhiza</span> plastomes. The outer circle shows genes transcribed counterclockwise while the inner ones are those transcribed clockwise. Colored bars indicate the different functional regions. The dark grey area in the inner circle indicates the GC content while the light grey area represents the AT content. LSC: large single-copy region; SSC: small single-copy region; IR: inverted repeat region.</p>
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<p>MAUVE alignment of chloroplast genomes of nine sect. <span class="html-italic">Bromatorrhiza</span> species and their relatives using Geneious R11. Local collinear blocks are represented by blocks of the same color and linked within each of the alignments. Box in red is for sect. <span class="html-italic">Bromatorrhiza</span> species.</p>
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<p>Comparison of the LSC, SSC, and IR junction of plastid genomes between the nine sect. <span class="html-italic">Bromatorrhiza</span> species and their relatives. JLB indicates the junction line between LSC and IRb; JSB indicates the junction line between SSC and IRb; JSA indicates the junction line between SSC and IRa; JLA indicates the junction line between LSC and IRa. Box in red is for sect. <span class="html-italic">Bromatorrhiza</span> species.</p>
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<p>Analyses of the simple sequence repeats (SSRs) in 15 plastomes: (<b>A</b>) proportion of different repeat types in the plastid, (<b>B</b>) numbers of different repeat types, (<b>C</b>) presence of SSRs in LSC, SSC, and IR. Boxes in red are for sect. <span class="html-italic">Bromatorrhiza</span> species.</p>
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<p>Variation in the distribution of forward (F), reverse (R), complementary (C), and palindromic (P) repeats and the number of different repeats in the chloroplast genome of 15 plastomes. Box in red is for sect. <span class="html-italic">Bromatorrhiza</span> species.</p>
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<p>Codon content of 20 amino acids and stop codons in the 9 sect. <span class="html-italic">Bromatorrhiza</span> species.</p>
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<p>The RSCU values of all merged protein-coding genes for 15 plastomes. In the colored boxes, higher values in red indicate higher RSCU values and, conversely, higher values in blue indicate lower RSCU values. Box in red is for sect. <span class="html-italic">Bromatorrhiza</span> species.</p>
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<p>VISTA-based sequence identity plot of 15 chloroplast genomes with <span class="html-italic">A. wallichii</span> as a reference. The percentage identity ranging from 50 to 100% is represented by the vertical scale. Coding and non-coding regions are colored in purple and pink, respectively. Box in red is for sect. <span class="html-italic">Bromatorrhiza</span> species.</p>
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<p>The nucleotide diversity of the plastid genome of (<b>A</b>) the 9 sect. <span class="html-italic">Bromatorrhiza</span> species and (<b>B</b>) 15 allied species in <span class="html-italic">Allium</span>. Ten regions with the highest Pi values were labeled. LSC indicates the large single-copy region; IR indicates the inverted repeat region; SSC indicates the small single-copy region.</p>
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<p>Phylogeny of the 45 taxa inferred from maximum likelihood (ML) and Bayesian inference (BI) analyses based on shared genes and non-coding regions. The numbers to the left of the slashes on the branches show the posterior probabilities (PPs) according to Bayesian inference, and those to the right show the bootstrap values (BS) obtained by maximum likelihood analyses. * Maximum support of 1.00/100—no statistical support. Three evolutionary lineages (Clade 1–3) are marked with different colors: Clade 1, red; Clade 2, green; Clade 3, purple. The nine sect. <span class="html-italic">Bromatorrhiza</span> species are located in the black dotted box, and the other six species compared above are shaded in yellow.</p>
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<p>Selective pressure of 80 protein-coding genes in the 9 sect. <span class="html-italic">Bromatorrhiza</span> species. Ka: rate of non-synonymous substitution; Ks: rate of synonymous substitution. Ka/Ks values &gt; 0.5 with red boxes.</p>
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6 pages, 2824 KiB  
Communication
Human Fetal Liver Parenchyma CD71+ Cells Have AIRE and Tissue-Specific Antigen Gene Expression
by Roman Perik-Zavodskii, Olga Perik-Zavodskaya, Yulia Shevchenko, Saleh Alrhmoun, Marina Volynets, Konstantin Zaitsev and Sergey Sennikov
Genes 2022, 13(7), 1278; https://doi.org/10.3390/genes13071278 - 19 Jul 2022
Viewed by 1703
Abstract
Autoimmune regulator (AIRE) is a multifunctional protein that is capable of inducing tissue-specific antigens’ (TSAs) gene expression, a key event in the induction of self-tolerance, that is usually expressed and functions in the thymus. However, its expression has been detected outside the thymus [...] Read more.
Autoimmune regulator (AIRE) is a multifunctional protein that is capable of inducing tissue-specific antigens’ (TSAs) gene expression, a key event in the induction of self-tolerance, that is usually expressed and functions in the thymus. However, its expression has been detected outside the thymus and cells expressing the gene have been named extra-thymic AIRE expressing cells (eTACs). Here, we discuss the finding of AIRE and TSAs gene expression in CD71+ cells from human fetal liver parenchyma, which are mostly represented by CD71+ erythroid cells. Full article
(This article belongs to the Section Genes & Environments)
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<p>Human fetal liver parenchyma CECs’ purity assessment by flow cytometry.</p>
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<p>(<b>a</b>) Melt curve plot for <span class="html-italic">AIRE</span> cDNA amplicons. (<b>b</b>) Melt curve plot for <span class="html-italic">GCG</span> cDNA amplicons. (<b>c</b>) Melt curve plot for <span class="html-italic">INS</span> cDNA amplicons. (<b>d</b>) Melt curve plot for <span class="html-italic">TFF3</span> cDNA amplicons. Melt curve plots for <span class="html-italic">AIRE</span>, <span class="html-italic">GCG</span>, <span class="html-italic">INS</span> and <span class="html-italic">TFF3</span> cDNA amplicons.</p>
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<p>(<b>a</b>) Melt curve plot for <span class="html-italic">AIRE</span> cDNA amplicons. (<b>b</b>) Melt curve plot for <span class="html-italic">GCG</span> cDNA amplicons. (<b>c</b>) Melt curve plot for <span class="html-italic">INS</span> cDNA amplicons. (<b>d</b>) Melt curve plot for <span class="html-italic">TFF3</span> cDNA amplicons. Melt curve plots for <span class="html-italic">AIRE</span>, <span class="html-italic">GCG</span>, <span class="html-italic">INS</span> and <span class="html-italic">TFF3</span> cDNA amplicons.</p>
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<p>Agarose gel-electrophoresis.</p>
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9 pages, 1309 KiB  
Article
Novel Exon-Skipping Therapeutic Approach for the DMD Gene Based on Asymptomatic Deletions of Exon 49
by Mario Abaji, Svetlana Gorokhova, Nathalie Da Silva, Tiffany Busa, Maude Grelet, Chantal Missirian, Sabine Sigaudy, Nicole Philip, France Leturcq, Nicolas Lévy, Martin Krahn and Marc Bartoli
Genes 2022, 13(7), 1277; https://doi.org/10.3390/genes13071277 - 19 Jul 2022
Cited by 2 | Viewed by 3419
Abstract
Exon skipping is a promising therapeutic approach. One important condition for this approach is that the exon-skipped form of the gene can at least partially perform the required function and lead to improvement of the phenotype. It is therefore critical to identify the [...] Read more.
Exon skipping is a promising therapeutic approach. One important condition for this approach is that the exon-skipped form of the gene can at least partially perform the required function and lead to improvement of the phenotype. It is therefore critical to identify the exons that can be skipped without a significant deleterious effect on the protein function. Pathogenic variants in the DMD gene are responsible for Duchenne muscular dystrophy (DMD). We report for the first time a deletion of the in-frame exon 49 associated with a strikingly normal muscular phenotype. Based on this observation, and on previously known therapeutic approaches using exon skipping in DMD for other single exons, we aimed to extend the clinical use of exon skipping for patients carrying truncating mutations in exon 49. We first determined the precise genomic position of the exon 49 deletion in our patients. We then demonstrated the feasibility of skipping exon 49 using an in vitro AON (antisense oligonucleotide) approach in human myotubes carrying a truncating pathogenic variant as well as in healthy ones. This work is a proof of concept aiming to expand exon-skipping approaches for DMD exon 49. Full article
(This article belongs to the Special Issue Genetics of Muscular Disorders)
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<p>(<b>a</b>) Schematic representation of dystrophin (violet), a rod-shaped protein containing four main functional domains: an actin-binding amino-terminal domain (ABD1); a central rod domain composed of 24 spectrin-like repeats (R1–R24, represented by circles) interrupted by four proline-rich parts (H1–H4) which gives it more flexibility (represented by diamonds); a cysteine-rich domain; a carboxy-terminal domain. A second actin-binding domain (ABD2) extends from R11 to R17. Dystrophin has two membrane lipid-binding domains (LBD), the first one comprises the repeats R1 to R3 whereas the second one (LBD2) comprises repeats R4 to R19. This places dystrophin very near the sarcolemma with a large part of its central rod domain lying along the phospholipid membrane. R19 (LBD2), which is coded partially by exon 49, is represented by a dashed white circle. In the cellular context, dystrophin forms a complex with other proteins (DG: dystroglycans, SGC/SPN: sarcoglycan–sarcospan complex, DB: dystrobrevin, SYN: syntrophins). This complex plays an important role in signal transduction in addition to its mechano-protective role, which is indispensable for contractions and proper muscle function [<a href="#B3-genes-13-01277" class="html-bibr">3</a>]. (DGC: dystrophin glycoproteins complex, ECM: extracellular matrix); (<b>b</b>) Schematic representation of exons 50, 49 and 48 in <span class="html-italic">DMD</span> (rectangles). The identified genomic deletion of exon 49 is represented by the dashed horizontal line. Genomic positions are mentioned using (hg19/GRCH37).</p>
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<p>Long-range PCR results showing the amplified fragment containing the breakpoint junction of the exon 49 deletion, using Q5 High-Fidelity DNA Polymerase. We note that we have the same 750 bp fragments for the 5 individuals. All patients are identified by the same letter as in the text. (-) signs mark the negative control lanes (PCR amplification without DNA). For patient D (daughter of patient E), PCR had to be redone using a new source of DNA because of the degradation of the first source.</p>
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<p>(<b>a</b>) Schematic representation of exon 49 DNA sequence in a DMD patient carrying a frameshift variant (asterisk). AON A and B, transfected in WT and mutated myotubes, are represented in grey and black respectively and hybridized to their complementary sequence. AON A masks the canonical (ag) splice site (red), AON B masks a region rich in ESE (exonic splicing enhancer), represented by horizontal lines (color reflects density of ESE presence); (<b>b</b>) Results of AON transfection into WT and mutated myotubes are presented. In the dashed rectangle: RT-PCR results after RNA extraction from transfected WT myotubes are shown on electrophoresis migration gel; primers located in exons 47 and 51 were used. In WT, myotubes bands without exon 49 represent 11.68% with AON A alone, 16.87% with AON B alone and 24.42% using AON A plus B. The second migration gel represents the results of transfected myotubes carrying the c.7186_7187insT pathogenic variant (RT-PCR). Exon skipping was done using AON B alone (first lane) and compared to the control (second lane). The band without exon 49 represents 63.28% of all amplified bands. The sequence of represented bands is shown with their respective chromatograms. (ES: Exon skipping, WT: Wild type).</p>
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16 pages, 3252 KiB  
Article
Identification of Differential Expression Genes between Volume and Pressure Overloaded Hearts Based on Bioinformatics Analysis
by Yuanfeng Fu, Di Zhao, Yufei Zhou, Jing Lu, Le Kang, Xueli Jiang, Ran Xu, Zhiwen Ding and Yunzeng Zou
Genes 2022, 13(7), 1276; https://doi.org/10.3390/genes13071276 - 19 Jul 2022
Cited by 1 | Viewed by 4378
Abstract
Volume overload (VO) and pressure overload (PO) are two common pathophysiological conditions associated with cardiac disease. VO, in particular, often occurs in a number of diseases, and no clinically meaningful molecular marker has yet been established. We intend to find the main differential [...] Read more.
Volume overload (VO) and pressure overload (PO) are two common pathophysiological conditions associated with cardiac disease. VO, in particular, often occurs in a number of diseases, and no clinically meaningful molecular marker has yet been established. We intend to find the main differential gene expression using bioinformatics analysis. GSE97363 and GSE52796 are the two gene expression array datasets related with VO and PO, respectively. The LIMMA algorithm was used to identify differentially expressed genes (DEGs) of VO and PO. The DEGs were divided into three groups and subjected to functional enrichment analysis, which comprised GO analysis, KEGG analysis, and the protein–protein interaction (PPI) network. To validate the sequencing data, cardiomyocytes from AR and TAC mouse models were used to extract RNA for qRT-PCR. The three genes with random absolute values of LogFC and indicators of heart failure (natriuretic peptide B, NPPB) were detected: carboxylesterase 1D (CES1D), whirlin (WHRN), and WNK lysine deficient protein kinase 2 (WNK2). The DEGs in VO and PO were determined to be 2761 and 1093, respectively, in this study. Following the intersection, 305 genes were obtained, 255 of which expressed the opposing regulation and 50 of which expressed the same regulation. According to the GO and pathway enrichment studies, DEGs with opposing regulation are mostly common in fatty acid degradation, propanoate metabolism, and other signaling pathways. Finally, we used Cytoscape’s three techniques to identify six hub genes by intersecting 255 with the opposite expression and constructing a PPI network. Peroxisome proliferator-activated receptor (PPARα), acyl-CoA dehydrogenase medium chain (ACADM), patatin-like phospholipase domain containing 2 (PNPLA2), isocitrate dehydrogenase 3 (IDH3), heat shock protein family D member 1 (HSPD1), and dihydrolipoamide S-acetyltransferase (DLAT) were identified as six potential genes. Furthermore, we predict that the hub genes PPARα, ACADM, and PNPLA2 regulate VO myocardial changes via fatty acid metabolism and acyl-Coa dehydrogenase activity, and that these genes could be employed as basic biomarkers for VO diagnosis and treatment. Full article
(This article belongs to the Special Issue Genetics and Mechanistic Basis of Cardiomyopathies)
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<p>Flowchart of data analysis. VO: volume overload; PO: pressure overload.</p>
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<p>The volcano plot, heatmap, and qPCR of DEGs. The gradient color from blue to red represents the gene expression value ((<b>A</b>): VO group/sham group; (<b>B</b>): TAC group/sham group) from down-regulation to up-regulation, respectively. DEGs: differentially expressed genes. The volcano plot of DEGs: red and blue dots represent up-regulated and down-regulated genes, respectively. (<b>C</b>) is VO group vs. sham group; (<b>D</b>) is TAC group vs. sham group. (<b>E</b>) is the Venn analysis of VO and TAC. (<b>F</b>) is qPCR results of RNA from mice that received AR or TAC. ****: <span class="html-italic">p</span>-value &lt; 0.0001.</p>
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<p>GO and pathway analysis of DEGs in VO group. (<b>A</b>) is an up-regulated differential gene, and (<b>B</b>) is a down-regulated differential gene. DEGs were divided into KEGG pathway and 3 functional groups, including BP, CC, and MF. KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene Ontology; BP: biological process; CC: cellular component; MF: molecular function; DEGs: differentially expressed genes.</p>
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<p>GO and pathway analysis of DEGs in PO group. (<b>A</b>) is the figure of up-regulated differential gene, and (<b>B</b>) is the figure of down-regulated differential gene. DEGs were divided into KEGG pathway and 3 functional groups, including BP, CC, and MF. KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene Ontology; BP: biological process; CC: cellular component; MF: molecular function; DEGs: differentially expressed genes.</p>
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<p>GO and pathway analysis of DEGs in VO and TAC groups with same regulation, opposite regulation, and no interaction. DEGs were divided into two functional groups, including BP and CC. GO: Gene Ontology; BP: biological process; CC: cellular component; KEGG: Kyoto Encyclopedia of Genes and Genomes; DEGs: differentially expressed genes. (<b>A</b>) is GO analysis of DEGs with same regulation. (<b>B</b>) is GO analysis of DEGs with opposite regulation. (<b>C</b>) is GO analysis of DEGs with no interaction.</p>
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<p>PPI network. (<b>A</b>) is Venn analysis with three algorithms. (<b>B</b>) is PPI network construction. Each circle represents a gene node. The transition from yellow to purple and the changes in the diameter of the circle indicate an increase in the sum of the absolute values of logFC. The genes with the 6 circles in the center represent the 6 genes with the intersection of the three algorithms.</p>
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11 pages, 251 KiB  
Article
Atypical, Composite, or Blended Phenotypes: How Different Molecular Mechanisms Could Associate in Double-Diagnosed Patients
by Erica Rosina, Lidia Pezzani, Laura Pezzoli, Daniela Marchetti, Matteo Bellini, Alba Pilotta, Olga Calabrese, Emanuele Nicastro, Francesco Cirillo, Anna Cereda, Agnese Scatigno, Donatella Milani and Maria Iascone
Genes 2022, 13(7), 1275; https://doi.org/10.3390/genes13071275 - 19 Jul 2022
Cited by 19 | Viewed by 2223
Abstract
In the last few years, trio-Whole Exome Sequencing (WES) analysis has revolutionized the diagnostic process for patients with rare genetic syndromes, demonstrating its potential even in non-specific clinical pictures and in atypical presentations of known diseases. Multiple disorders in a single patient have [...] Read more.
In the last few years, trio-Whole Exome Sequencing (WES) analysis has revolutionized the diagnostic process for patients with rare genetic syndromes, demonstrating its potential even in non-specific clinical pictures and in atypical presentations of known diseases. Multiple disorders in a single patient have been estimated to occur in approximately 2–7.5% of diagnosed cases, with higher frequency in consanguineous families. Here, we report the clinical and molecular characterisation of eight illustrative patients for whom trio-WES allowed for identifing more than one genetic condition. Double homozygosity represented the causal mechanism in only half of them, whereas the other half showed peculiar multilocus combinations. The paper takes into consideration difficulties and learned lessons from our experience and therefore supports the powerful role of wide analyses for ascertaining multiple genetic diseases in complex patients, especially when a clinical suspicion could account for the majority of clinical signs. It finally makes clear how a patient’s “deep phenotyping” might not be sufficient to suggest the presence of multiple genetic diagnoses but remains essential to validate an unexpected multilocus result from genetic tests. Full article
11 pages, 299 KiB  
Article
Powdery Mildew Resistance Genes in European Barley Cultivars Registered in the Czech Republic from 2016 to 2020
by Antonín Dreiseitl
Genes 2022, 13(7), 1274; https://doi.org/10.3390/genes13071274 - 18 Jul 2022
Cited by 11 | Viewed by 1824
Abstract
Barley is an important crop grown annually on about 55 Mha and intensively cultivated in Europe. In central and north-western Europe, spring and winter barley can be grown in similar environments which creates suitable conditions for the development of barley pathogens, including Blumeria [...] Read more.
Barley is an important crop grown annually on about 55 Mha and intensively cultivated in Europe. In central and north-western Europe, spring and winter barley can be grown in similar environments which creates suitable conditions for the development of barley pathogens, including Blumeria graminis f. sp. hordei, the causal agent of powdery mildew. Apart from pesticide application, it can be controlled by inexpensive and environmentally-friendly genetic resistance. In this contribution, results of the resistance gene identification in 58 barley cultivars to powdery mildew are presented. In 56 of them their resistances were postulated and in two hybrid cultivars a recently developed method of gene identification was used. In total, 18 known resistance genes were found and several unknown genes were detected. In spring barley, a gene of durable resistance mlo is still predominant. MlVe found in winter SU Celly was the only new resistance gene recorded in barley cultivars registered in the Czech Republic in this time span. Since 2001 eight new genes of specific resistance have been identified in cultivars registered in the country and their response under field conditions is discussed, including the corresponding responses of the pathogen population due to directional selection. Different strategies for breeding spring and winter barley are recommended. Full article
(This article belongs to the Section Plant Genetics and Genomics)
19 pages, 7128 KiB  
Article
Insights into the Deep Phylogeny and Novel Divergence Time Estimation of Patellogastropoda from Complete Mitogenomes
by Jiantong Feng, Jing Miao, Yingying Ye, Jiji Li, Kaida Xu, Baoying Guo and Xiaojun Yan
Genes 2022, 13(7), 1273; https://doi.org/10.3390/genes13071273 - 18 Jul 2022
Cited by 2 | Viewed by 2610
Abstract
To further understand the origin and evolution of Patellogastropoda, we determined the mitochondrial genome sequence of Cellana toreuma, and compared its mitogenome characteristics with the other four limpets of Nacellidae. The ratio of Ka and Ks indicated that these Nacellidae species were [...] Read more.
To further understand the origin and evolution of Patellogastropoda, we determined the mitochondrial genome sequence of Cellana toreuma, and compared its mitogenome characteristics with the other four limpets of Nacellidae. The ratio of Ka and Ks indicated that these Nacellidae species were suffering a purifying selection, with exception of the atp6 gene. The gene sequence is basically consistent among families, while there are great differences among Lottidae species. According to the mitogenome sequences of selected gastropod species, we reconstructed a new phylogenetic tree with two methods. The data complement the mitogenome database of limpets and is a favorable research tool for the phylogenetic analysis of Gastropoda. It is found that there is a long-branch attraction (LBA) artefact in the family Lottiidae of Patellogastropoda. Therefore, the Patellogastropoda was separated by Heterobranchia, and Lottiidae is located at the root of the whole phylogenetic tree. Furthermore, we constructed the divergence time tree according to the Bayesian method and discussed the internal historical dynamics, and divergence differences among the main lineages of 12 Patellogastropoda under an uncorrelated relaxed molecular clock. In turn, we made a more comprehensive discussion on the divergence time of limpets at the molecular level. Full article
(This article belongs to the Special Issue Genetic Breeding and Genomics of Marine Shellfish)
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<p>Gene map of the complete mitogenomes for <span class="html-italic">Cellana toreuma</span> (GenBank accession No. MZ329338). The ring indicates gene arrangement and distribution.</p>
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<p>Percentage of each amino acid for proteins coded by PCGs in the five mitochondrial genomes of Nacellidae.</p>
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<p>The relative synonymous codon usage (RSCU) in the mitochondrial genomes of five Nacellidae species.</p>
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<p>Selective pressure analysis for 13 PCGs among 5 Nacellidae mitochondrial genomes. Species of Nacellidae are shown in <a href="#genes-13-01273-t001" class="html-table">Table 1</a>. The purple and blue boxes indicate the number of nonsynonymous substitutions per nonsynonymous sites (Ka) and the number of synonymous substitutions per synonymous sites (Ks), respectively. The orange line indicates the mean of pairwise divergence of the Ka/Ks ratio.</p>
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<p>Comparison of mitochondrial gene order of the family Nacellidae in Patellogastropoda.</p>
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<p>Phylogenetic tree inferred using maximum likelihood (ML) and Bayesian inference (BI) methods based on concatenated sequences of 13 PCGs from 88 gastropod mitogenomes. The sequences of two bivalves were chosen as the outgroups. The purple dots indicate <span class="html-italic">C</span><span class="html-italic">. toreuma</span> sequenced in this study. The number at each node is the bootstrap probability.</p>
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<p>Divergence time estimation analysis of Nacellidae inferred via Bayesian relaxed dating methods (BEAST) based on the nucleotide sequences of 13 PCGs. Fossil samples used to calibrate internal nodes are represented by an asterisk. A total of 95% HPD is reported as blue bars, and Bayesian posterior probabilities are reported for each node.</p>
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Article
An Intron c.103-3T>C Variant of the AMELX Gene Causes Combined Hypomineralized and Hypoplastic Type of Amelogenesis Imperfecta: Case Series and Review of the Literature
by Tina Leban, Katarina Trebušak Podkrajšek, Jernej Kovač, Aleš Fidler and Alenka Pavlič
Genes 2022, 13(7), 1272; https://doi.org/10.3390/genes13071272 - 18 Jul 2022
Cited by 6 | Viewed by 3260
Abstract
Amelogenesis imperfecta (AI) is a heterogeneous group of genetic disorders of dental enamel. X-linked AI results from disease-causing variants in the AMELX gene. In this paper, we characterise the genetic aetiology and enamel histology of female AI patients from two unrelated families with [...] Read more.
Amelogenesis imperfecta (AI) is a heterogeneous group of genetic disorders of dental enamel. X-linked AI results from disease-causing variants in the AMELX gene. In this paper, we characterise the genetic aetiology and enamel histology of female AI patients from two unrelated families with similar clinical and radiographic findings. All three probands were carefully selected from 40 patients with AI. In probands from both families, scanning electron microscopy confirmed hypoplastic and hypomineralised enamel. A neonatal line separated prenatally and postnatally formed enamel of distinctly different mineralisation qualities. In both families, whole exome analysis revealed the intron variant NM_182680.1: c.103-3T>C, located three nucleotides before exon 4 of the AMELX gene. In family I, an additional variant, c.2363G>A, was found in exon 5 of the FAM83H gene. This report illustrates a variant in the AMELX gene that was not previously reported to be causative for AI as well as an additional variant in the FAM83H gene with probably limited clinical significance. Full article
(This article belongs to the Special Issue Advances in Genetic Diseases of Teeth)
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<p>Clinical photographs, panoramic radiograph, and pedigree of the girl from family I. (<b>A</b>–<b>C</b>) Mixed dentition of the 9-year-and-10-month-old probed (III.6) reveal the chalky-white to yellowish hyperplastic enamel of all deciduous and permanent teeth. On the occlusal surfaces of upper and lower deciduous molars and permanent first molars, profound attrition is observed. Permanent first molars are covered with extensive glass ionomer fillings. All first deciduous molars and the lower right second deciduous molar were extracted. Both upper lateral permanent incisors are erupting ectopically. (<b>D</b>) Panoramic radiograph shows the presence of all permanent germs (wisdom teeth included). Those teeth that have developing tooth crowns not erupted exhibited normal anatomy, with enamel of normal thickness but lacking contrast between enamel and dentine. (<b>E</b>) Pedigree of family I shows the presence of an X-linked mode of inheritance. The arrow indicates the girl described (III.6); the symbol (*) indicates participating individuals; NA indicates not-available family members.</p>
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<p>Clinical photographs, panoramic radiographs, and pedigree of the girls from family II. (<b>A</b>–<b>C</b>) Hypomineralised mixed dentition of the 11-year-and-6-month-old girl (IV.4) also exhibits some hypoplastic areas on all tooth crowns. Teeth are whitish with diffuse chalky-like patches, in some areas altering to yellow-brownish. All permanent incisors are restored with composite resins and all premolars and molars with glass ionomers. (<b>E</b>–<b>G</b>) The enamel of the 6-year-and-9-month-old sister (IV.5) is similarly altered, of chalky to yellowish colour. All deciduous and permanent molars are covered with extensive temporary fillings. (<b>D</b>,<b>H</b>) The panoramic radiographs show the enamel of adequate thickness, but with radiopacity, similar to dentine. (<b>I</b>) The filled symbols denote individuals of four generations of family II who have similarly affected enamel. Arrows indicate both girls examined (IV.4 and IV.5), the symbol (*) indicates family members who participated in the study, and NA indicates non-available family members.</p>
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<p>Images of (<b>A</b>–<b>C</b>) an exfoliated and etched lower deciduous first molar (tooth 74) of the girl (III.6) from family I and (<b>D</b>–<b>F</b>) a non-etched upper deciduous second molar (tooth 65) of the older girl (IV.4) from family II. (<b>A</b>,<b>D</b>) Light microscopy reveals a pitted enamel surface (yellow arrows) that is also missing in some areas due to attrition (white arrows). Two layers of enamel are visible, with the inner layer (asterisks) being better mineralised (etched, ×60 and non-etched, ×100, respectively). (<b>B</b>,<b>E</b>) Scanning electron microscopic (SEM) images of these same surfaces of both affected teeth show rather normal structures in the inner enamel layer and irregular histology with numerous voids and amorphous artefacts in the outer layer (etched, ×150, SEI and non-etched, ×120, SEI, respectively). (<b>C</b>,<b>F</b>) Under higher magnification, we see profoundly porous enamel and a reduced number of enamel prisms with increased inter-prism space in the outer layer (etched, ×800, SEI and non-etched, ×850, SEI).</p>
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<p>Diagram showing disease-causing variants, named according to the reference sequence NM_198488.5, identified in reported families with hypocalcified AI. The <span class="html-italic">FAM83H</span> domains are shown in coloured boxes. The bottom line shows the range of amino acids in particular domains (blue: highly conserved N-terminus domain encompassing amino acids 17–281; yellow: intermediate region encompassing amino acids 282–675; green: highly conserved C-terminus domain encompassing amino acids 676–1179). The disease-causing variants shown in black are associated with the generalised phenotype, those in green with the localised phenotype, and those in blue with the attenuated phenotype. The variant identified in this study is shown in red.</p>
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<p>Diagram showing disease-causing variants, named according to the reference sequence NM_182680.1, identified in reported families with the <span class="html-italic">AMELX</span> phenotype. The amelogenin protein has several structural domains shown in coloured boxes (adapted from [<a href="#B75-genes-13-01272" class="html-bibr">75</a>,<a href="#B76-genes-13-01272" class="html-bibr">76</a>]). The bottom line shows the range of amino acids in particular domains (TRAP represents tyrosine-rich amelogenin protein, LRAP leucine-rich amelogenin protein, and TLE telopeptide). The disease-causing variant identified in this study is shown in red. * Disease-causing variants with no product are not labelled ([<a href="#B57-genes-13-01272" class="html-bibr">57</a>,<a href="#B58-genes-13-01272" class="html-bibr">58</a>,<a href="#B74-genes-13-01272" class="html-bibr">74</a>]).</p>
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13 pages, 2075 KiB  
Article
Genome-Wide Analysis Identifies Candidate Genes Encoding Beak Color of Duck
by Qixin Guo, Yong Jiang, Zhixiu Wang, Yulin Bi, Guohong Chen, Hao Bai and Guobin Chang
Genes 2022, 13(7), 1271; https://doi.org/10.3390/genes13071271 - 18 Jul 2022
Cited by 10 | Viewed by 3054
Abstract
Beak color diversity is a broadly occurring phenomenon in birds. Here, we used ducks to identify candidate genes for yellow, black, and spotted beaks. For this, an F2 population consisting of 275 ducks was genotyped using whole genome resequencing containing 12.6 M [...] Read more.
Beak color diversity is a broadly occurring phenomenon in birds. Here, we used ducks to identify candidate genes for yellow, black, and spotted beaks. For this, an F2 population consisting of 275 ducks was genotyped using whole genome resequencing containing 12.6 M single-nucleotide polymorphisms (SNPs) and three beak colors. Genome-wide association studies (GWAS) was used to identify the candidate and potential SNPs for three beak colors in ducks (yellow, spotted, and black). The results showed that 2753 significant SNPs were associated with black beaks, 7462 with yellow, and 17 potential SNPs with spotted beaks. Based on SNP annotation, MITF, EDNRB2, members of the POU family, and the SLC superfamily were the candidate genes regulating pigmentation. Meanwhile, isoforms MITF-M and EDNRB2 were significantly different between black and yellow beaks. MITF and EDNRB2 likely play a synergistic role in the regulation of melanin synthesis, and their mutations contribute to phenotypic differences in beak melanin deposition among individuals. This study provides new insights into genetic factors that may influence the diversity of beak color. Full article
(This article belongs to the Section Animal Genetics and Genomics)
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<p>Beak color and sex correlation analysis (<b>a</b>); population structure analysis (<b>b</b>).</p>
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<p>Quantile–quantile (Q–Q) from GWAS for beak color trait in duck. Q–Q plot showing the late separation between observed and expected values. The red lines indicate the null hypothesis of no true association. Deviation from the expected <span class="html-italic">p</span>-value distribution is evident only in the tail area for each trait, indicating that population stratification was properly controlled. BB refers to black beak; BS refers to spotted beak; BY refers to yellow beak.</p>
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<p>Manhattan plots showing the significance of genetic effects on the beak color according to the GWAS.</p>
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<p>Venn analysis of all beak colors showing overlap of significant SNPs.</p>
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<p>Functional enrichment analysis of the beak color candidate genes. (<b>a</b>) KEGG (left) and GO (right) enrichment of black beak candidate genes; (<b>b</b>) KEGG (left) and GO (right) enrichment of spotted beak candidate genes; (<b>c</b>) KEGG (left) and GO (right) enrichment of yellow beak candidate genes.</p>
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<p>Expression differences in <span class="html-italic">EDNRB2</span> and <span class="html-italic">MITF</span> on three exon junctions between black and yellow beaks according to RT-qPCR. (<b>a</b>) Information on the <span class="html-italic">MITF</span> isoform. The red triangle represents the intronic insertion on chromosome 13 in Pekin ducks. Exon 1M is specific for the MITF-M transcript, while exon 1B is specific for the MITF-B transcript. (<b>b</b>) <span class="html-italic">EDNRB2</span> and <span class="html-italic">MITF</span> on three exon junctions between black and yellow beaks. Each exon junction was assayed in six biological replicates with three technical replicates. The indicated <span class="html-italic">p</span>-values were based on one-way ANOVA. NS, nonsignificant; **, extremely significant.</p>
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16 pages, 4072 KiB  
Article
A Chromosome-Length Assembly of the Hawaiian Monk Seal (Neomonachus schauinslandi): A History of “Genetic Purging” and Genomic Stability
by David W. Mohr, Stephen J. Gaughran, Justin Paschall, Ahmed Naguib, Andy Wing Chun Pang, Olga Dudchenko, Erez Lieberman Aiden, Deanna M. Church and Alan F. Scott
Genes 2022, 13(7), 1270; https://doi.org/10.3390/genes13071270 - 18 Jul 2022
Cited by 4 | Viewed by 3366
Abstract
The Hawaiian monk seal (HMS) is the single extant species of tropical earless seals of the genus Neomonachus. The species survived a severe bottleneck in the late 19th century and experienced subsequent population declines until becoming the subject of a NOAA-led species recovery [...] Read more.
The Hawaiian monk seal (HMS) is the single extant species of tropical earless seals of the genus Neomonachus. The species survived a severe bottleneck in the late 19th century and experienced subsequent population declines until becoming the subject of a NOAA-led species recovery effort beginning in 1976 when the population was fewer than 1000 animals. Like other recovering species, the Hawaiian monk seal has been reported to have reduced genetic heterogeneity due to the bottleneck and subsequent inbreeding. Here, we report a chromosomal reference assembly for a male animal produced using a variety of methods. The final assembly consisted of 16 autosomes, an X, and portions of the Y chromosomes. We compared variants in this animal to other HMS and to a frequently sequenced human sample, confirming about 12% of the variation seen in man. To confirm that the reference animal was representative of the HMS, we compared his sequence to that of 10 other individuals and noted similarly low variation in all. Variation in the major histocompatibility (MHC) genes was nearly absent compared to the orthologous human loci. Demographic analysis predicts that Hawaiian monk seals have had a long history of small populations preceding the bottleneck, and their current low levels of heterozygosity may indicate specialization to a stable environment. When we compared our reference assembly to that of other species, we observed significant conservation of chromosomal architecture with other pinnipeds, especially other phocids. This reference should be a useful tool for future evolutionary studies as well as the long-term management of this species. Full article
(This article belongs to the Special Issue Feature Papers: Molecular Genetics and Genomics)
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<p>Montage of “Benny” (RE74). (<b>a</b>) Asleep on east Oahu in 2009, (<b>b</b>) In distress after swallowing a fishing hook and line (2015), (<b>c</b>) X-ray prior to surgery and (<b>d</b>) post-surgery. Images courtesy of NOAA. RE74 died of undetermined causes on 17 June 2022 at the age of 19 (<a href="https://www.fisheries.noaa.gov/pacific-islands/endangered-species-conservation/hawaiian-monk-seal-updates#saying-a-final-aloha-to-re74%C2%A0&#x2013;&#x201C;benny&#x201D;" target="_blank">https://www.fisheries.noaa.gov/pacific-islands/endangered-species-conservation/hawaiian-monk-seal-updates#saying-a-final-aloha-to-re74%C2%A0–“benny”</a>, accessed on 22 June 2022).</p>
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<p>QUAST plot showing the improvement of assembly metrics from version 1 (NCBI ASM220157v1) to version 2 (NCBI ASM220157v2) and the small contribution of unplaced scaffolds in v2. The green line represents scaffolds remaining after the second optical genome mapping.</p>
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<p>D-GENIES plots of HMS aligned to other pinnipeds for which chromosome-length assemblies are available as well as the domestic cat. The specific genomes compared are listed in <a href="#app1-genes-13-01270" class="html-app">Supplemental Table S2</a>. As chromosome orientations are arbitrarily based on their order in NCBI, we reverse-complemented chromosomes in some species prior to alignment so that the chromosomes are in the same direction relative to HMS. Phocidae (earless seals), Otariidae (eared seals), Odobenidae (walrus), Felidae (felines). Enlarged individual alignments are shown in <a href="#app1-genes-13-01270" class="html-app">Supplement Figure S3</a>. D-GENIES filtering was adjusted individually for each plot to maximize sequence identity but minimize small matches.</p>
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<p>Absence of heterozygosity in RE74 at loci orthologous to human DQA1 and B1. Comparison of phased variants in NA12878 HLA DQA1 and B1 genes visualized in the Loupe viewer (10X genomics) compared to orthologous RE74 genes [<a href="#B26-genes-13-01270" class="html-bibr">26</a>] LOC110575557 and LOC110575559. The figures were adjusted to the same scale (the blue bar represents 20 kb). Blue dots represent SNPs and yellow dots are indels. Blue squares represent multiple SNPs that are not resolved at this scale. One low quality intergenic SNV was observed in RE74.</p>
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<p>(<b>a</b>) Heterozygosity at positions flanking the MHC class II loci DMA DMB, DOA and DOB among human samples in comparison to RE74 and ten other HMS genomes as visualized in IGV. Human genomes are CEPH NA12891 and 12892, the parents of NA12878 and NA12889 and NA12890, her unrelated in-laws. A seal SNV occurs at only one position. (<b>b</b>) Comparisons of NA12889-12892 for HLA DOA and DOB (the human genes are split into two panels due to their larger intergenic sequence). Seal SNVs occur at a single position for all 10 animals for both regions. Panel width is 22 kb for all compared regions.</p>
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<p>MSMC plot showing small and declining Ne over the last 200,000 years.</p>
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17 pages, 4048 KiB  
Article
Genomic Characterization by Whole-Exome Sequencing of Hypermobility Spectrum Disorder
by Gerardo J. Alanis-Funes, Saúl Lira-Albarrán, Jesús Hernández-Pérez, Mario A. Garza-Elizondo, Rocío Ortíz-López, César V. Elizondo, Augusto Rojas-Martinez, Rocío A. Chávez-Santoscoy and Claudia Rangel-Escareño
Genes 2022, 13(7), 1269; https://doi.org/10.3390/genes13071269 - 18 Jul 2022
Cited by 4 | Viewed by 5242
Abstract
No genetic basis is currently established that differentiates hypermobility spectrum disorders (HSD) from hypermobile Ehlers–Danlos syndrome (hEDS). Diagnosis is entirely based on clinical parameters with high overlap, leading to frequent misdiagnosis of these two phenotypes. This study presents a landscape of DNA mutations [...] Read more.
No genetic basis is currently established that differentiates hypermobility spectrum disorders (HSD) from hypermobile Ehlers–Danlos syndrome (hEDS). Diagnosis is entirely based on clinical parameters with high overlap, leading to frequent misdiagnosis of these two phenotypes. This study presents a landscape of DNA mutations through whole-exome sequencing of patients clinically diagnosed with generalized HSD. In this study, three genes (MUC3A, RHBG, and ZNF717) were mutated in all five patients evaluated. The functional enrichment analysis on all 1162 mutated genes identified the extracellular matrix (ECM) structural constituent as the primary overrepresented molecular function. Ingenuity pathway analysis identified relevant bio-functions, such as the organization of ECM and hereditary connective tissue disorders. A comparison with the matrisome revealed 55 genes and highlighted MUC16 and FREM2. We also contrasted the list of mutated genes with those from a transcriptomic analysis on data from Gene Expression Omnibus, with only 0.5% of the genes at the intersection of both approaches supporting the hypothesis of two different diseases that inevitably share a common genetic background but are not the same. Potential biomarkers for HSD include the five genes presented. We conclude the study by describing five potential biomarkers and by highlighting the importance of genetic/genomic approaches that, combined with clinical data, may result in an accurate diagnosis and better treatment. Full article
(This article belongs to the Section Human Genomics and Genetic Diseases)
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<p>The continuous struggle to characterize joint hypermobility from 1998 to the current nosology established in 2017, in which two phenotypes are recognized. Hypothesis A identifies two diseases that have overlapping symptoms but are genetically different, while Hypothesis B presents two diseases with overlapping symptoms and common genetic backgrounds.</p>
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<p>Whole-exome sequencing analysis workflow.</p>
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<p>Mutation summary by variant classification, type of variant, and class (<b>top plots</b>). The number of mutations per sample, boxplots for variant classification, and the top 10 mutated genes (<b>bottom plots</b>). Color representations are green for missense mutations, red for nonsense mutations, purple for frameshift insertions, blue for frameshift deletions, yellow for in-frame deletions, dark pink for in-frame insertions, cyan for nonstop mutations and orange for translation start site. The red dotted line in the variants per sample plot indicates the median of variants for all samples.</p>
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<p>Mutation characterization of most mutated genes. Each column represents a patient; rows are genes. Here, green represents missense mutations, purple represents frameshift insertions, red represents nonsense mutations, and black represents multi-hit mutations. Gray is interpreted as no mutations found.</p>
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<p>Ehlers–Danlos syndrome network of genes highly associated with the disease. Molecules are classified by shape (see legend) and colored to make them easier to follow.</p>
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<p>HSD network of genes known to be associated with HS according to the IPA database.</p>
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<p>Heat map results from an unsupervised hierarchical clustering algorithm. The green bar on top represents hEDS/JHS patients and the blue bar represents the controls.</p>
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<p>Venn diagram showing the intersection level between the list of genes found to be significant in both approaches: WES mutated genes and differentially expressed genes (DEGs). Genes at the intersection are <span class="html-italic">LIMCH1, ACSL5, FLG, DSP, EDIL3, PRUNE2</span>, and <span class="html-italic">ZFPM2</span>.</p>
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15 pages, 5281 KiB  
Article
A Novel Hypothesis on Choroideremia-Manifesting Female Carriers: Could CHM In-Frame Variants Exert a Dominant Negative Effect? A Case Report
by Niccolò Di Giosaffatte, Michele Valiante, Stefano Tricarico, Giulia Parise, Anna Maria De Negri, Guido Ricciotti, Lara Florean, Alessandro Paiardini, Irene Bottillo and Paola Grammatico
Genes 2022, 13(7), 1268; https://doi.org/10.3390/genes13071268 - 17 Jul 2022
Cited by 5 | Viewed by 2324
Abstract
Choroideremia is an X-linked recessive condition presenting in males, with progressive degeneration of retinal and choroidal tissues leading to progressive visual loss. Its pathological mechanism is due to alterations in the CHM gene that encodes for REP1, a protein required for prenylation of [...] Read more.
Choroideremia is an X-linked recessive condition presenting in males, with progressive degeneration of retinal and choroidal tissues leading to progressive visual loss. Its pathological mechanism is due to alterations in the CHM gene that encodes for REP1, a protein required for prenylation of Rab by the Rab geranylgeranyl transferase (RGGT). Even though female carriers are predicted to be not affected by the disease, a wide phenotypic spectrum ranging from mild to severe cases has been reported in women. The reason why Choroideremia manifests in female carriers remains elusive. While X chromosome inactivation (XCI) skewing has been proposed as a leading putative mechanism, emerging evidence has shown that CHM could variably escape from XCI. We described a family with an initial clinical suspicion of Retinitis Pigmentosa in which a novel CHM pathogenic splicing variant was found by exome sequencing. The variant, initially found in the 63-year-old female presenting with impaired visual acuity and severe retinal degeneration, segregated in the 31-year-old daughter and the 37-year-old son, both presenting with fundus anomalies. mRNA studies revealed a shorter in-frame CHM isoform lacking exon 10. Molecular modeling of the ternary REP1/Rab/RGGT protein complex predicted significant impairing of REP1/Rab binding without alteration of REP1/RGGT interaction. We suggest that, in our female cases, the biallelic expression of CHM may have led to the production of both the mutant and wild type REP1. The mutant isoform, sequestrating RGGT, could reduce its available amount for Rab prenylation, thus exerting a dominant-negative effect. If confirmed with further studies and in large cohorts of female carriers, the here proposed molecular mechanism could help to explain the complexity of manifestation of Choroideremia in females. Full article
(This article belongs to the Special Issue Study of Inherited Retinal Diseases)
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<p>Models of REP1 mediated prenylation of Rab proteins. (Upper panel). Traditional model: (1) REP1 binds Rab; (2) Rab/REP1 complex binds RGGT/GGDP; (3) RGGT mediates two cycles of geranylation of Rab using two molecules of GGDP; (4) REP1 detaches from RGGT and escorts RabGG to membranes. (Lower panel). Alternative model: (1) REP1 binds RGGT/GGDP; (2) Rab binds REP1/RGGT/GGDP complex; (3) RGGT mediates two cycles of geranylation of Rab using two molecules of GGDP; (4) REP1 detaches from RGGT and escorts RabGG to membranes.</p>
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<p>(<b>A</b>) Family pedigree. The phenotype of each patient is shown with different filling motifs. <span class="html-italic">CHM</span> genotypes are provided under each case’s symbol. The clinical legend is provided under the pedigree. YoB: year of birth. (<b>B</b>) cDNA analysis of cases II:2 and a control. The gel electrophoresis of the PCR products amplified with primers from exon 8 to exon 13 is shown on the top. The Sanger sequencing electropherogram from cDNA of case II:2 is shown on the bottom. M: molecular weight marker 50 (Experteam, Venezia, Italy).</p>
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<p>Multimodal imaging of both eyes of Patient I:2. (<b>A</b>,<b>B</b>) Color fundus photography of both eyes showed a large bilateral chorioretinal atrophy; (<b>C</b>,<b>D</b>) SD-OCT of both eyes showed an extensive chorioretinal atrophy and retinal thinning in the right eye and a residual central island of preserved Ellipsoid Zone (EZ) area in the left eye; (<b>E</b>,<b>F</b>) IR images showed areas of residual RPE in the left eye; (<b>G</b>,<b>H</b>) FAF showed generalized decreased autofluorescence, with residual areas of autofluorescence in the central macular area in the right eye and also in the temporal macular area in the left eye. (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>): right eye; (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>): left eye.</p>
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<p>Multimodal imaging of both eyes of patient II:1. (<b>A</b>,<b>B</b>) Color fundus photography of both eyes showed large peripapillary and temporal retinal atrophy; (<b>C</b>,<b>D</b>) SD-OCT of both eyes showed peripapillary chorioretinal atrophy with retinal thinning and hyper-transmission posterior to the RPE. In the foveal and iuxtafoveal area, the Ellipsoid zone (EZ), RPE and all retinal layers were well-detectable; (<b>E</b>,<b>F</b>) IR images showed the transition of the intact RPE under the fovea to the atrophic area; (<b>G</b>,<b>H</b>). FAF showed central island of preserved autofluorescence. (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>): right eye; (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>): left eye.</p>
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<p>Multimodal imaging of both eyes of Patient II:2. (<b>A</b>,<b>B</b>) Color fundus photography of both eyes showed mild peripapillary atrophy, areas of hyper-pigmentation in the perifoveal area and pigmentary changes at the level of the vascular arcades; (<b>C</b>,<b>D</b>) SD-OCT of both eyes showed thinning of the ONL in the perimacular zone. IZ-EZ and the RPE–Bruch’s complex were irregular, with spot of hyper-transmission posterior to the RPE-Bruch’s membrane; (<b>E</b>,<b>F</b>) IR images showed normal aspect of the macular area and hypo-reflective areas among the vascular arcades; (<b>G</b>,<b>H</b>) normal autofluorescence of the macular area and a generalized hypo-fluorescence of the vascular arcade area. (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>): right eye; (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>): left eye.</p>
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<p>(<b>A</b>) The structure of wild type REP1 is shown in grey, with the peptide codified by exon 10 colored in magenta. The interacting RGGT is shown as a deep purple surface, while Rab7 is shown as a pink surface. (<b>B</b>) The image shows the interaction lost due to the lack of exon 10 in mutated REP1 (green illustration), while the interaction with RGGT is presumably conserved, given the invariant interaction interface. (<b>C</b>) A zoomed view of the interaction with Rab7 (pink illustrations and transparent surface) showing the different interaction interface affecting the binding of Rab7 due to the different conformation of REP1, lacking exon 10 (magenta).</p>
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<p>Proposed pathogenic molecular mechanisms for Choroideremia considering <span class="html-italic">CHM</span> biallelic (“a” allele and “b” allele) expression in females, following the alternative model (see <a href="#genes-13-01268-f001" class="html-fig">Figure 1</a>). The level of REP1a and REP1b expression would depend upon <span class="html-italic">CHM</span>a/<span class="html-italic">CHM</span>b position on Xa or Xi and the levels of expression of <span class="html-italic">CHM</span> allele from Xi. Legend: wt = wild type allele, mut = mutant allele, NMD= Nonsense RNA Mediated Decay.</p>
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12 pages, 1791 KiB  
Article
Microsatellite Characteristics of Silver Carp (Hypophthalmichthysmolitrix) Genome and Genetic Diversity Analysis in Four Cultured Populations
by Yajun Wang, Hang Sha, Xiaohui Li, Tong Zhou, Xiangzhong Luo, Guiwei Zou, Yi Chai and Hongwei Liang
Genes 2022, 13(7), 1267; https://doi.org/10.3390/genes13071267 - 16 Jul 2022
Cited by 5 | Viewed by 2534
Abstract
Hypophthalmichthys molitrix is one of the four most important fish in China and has high breeding potential. However, simple sequence repeat (SSR) markers developed on H. molitrix genome level for genetic diversity analysis are limited. In this study, the distribution characteristics of SSRs [...] Read more.
Hypophthalmichthys molitrix is one of the four most important fish in China and has high breeding potential. However, simple sequence repeat (SSR) markers developed on H. molitrix genome level for genetic diversity analysis are limited. In this study, the distribution characteristics of SSRs in the assembled H. molitrix genome were analyzed, and new markers were developed to preliminarily evaluate the genetic diversity of the four breeding populations. A total of 368,572 SSRs were identified from the H. molitrix genome. The total length of SSRs was 6,492,076 bp, accounting for 0.77% of the total length of the genome sequence. The total frequency and total density were 437.73 loci/Mb and 7713.16 bp/Mb, respectively. Among the 2–6 different nucleotide repeat types, SSRs were dominated by di-nucleotide repeats (204,873, 55.59%), and AC/GT was the most abundant motif. The number of SSRs on each chromosome was positively correlated with the length. The 13 pairs of markers developed were used to analyze the genetic diversity of four cultivated populations in Hubei Province. The results showed that the genetic diversity of the four populations was low, and the ranges of alleles (Na), effective alleles (Ne), observed heterozygosity (Ho), and Shannon’s index information (I) were 3.538–4.462, 2.045–2.461, 0.392–0.450, and 0.879–0.954, respectively. Genetic variation occurs mainly among individuals within populations (95.35%). UPGMA tree and Bayesian analysis showed that four populations could be divided into two different branches. Therefore, the genome-wide SSRs were effectively in genetic diversity analysis on H. molitrix. Full article
(This article belongs to the Special Issue Genetic Breeding of Aquaculture)
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<p>Motif proportions of different repeat types in <span class="html-italic">H. molitrix</span> genome. (<b>a</b>) The most abundant SSRs motifs in the <span class="html-italic">H. molitrix</span> genome; (<b>b</b>) mono-nucleotide repeat types, (<b>c</b>) tri-nucleotide repeat types, (<b>d</b>) tera-nucleotide repeat types, (<b>e</b>) penta-nucleotide repeat types, and (<b>f</b>) hexa-nucleotide repeat types.</p>
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<p>Different copy number distribution of <span class="html-italic">H. molitrix</span> SSRs.</p>
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<p>Analysis of SSR frequencies on <span class="html-italic">H. molitrix</span> chromosomes: (<b>a</b>) number of SSRs, (<b>b</b>) length of SSRs, (<b>c</b>) frequency of SSRs, and (<b>d</b>) density of SSRs.</p>
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<p>UPGMA tree based on the genetic distance among four <span class="html-italic">H. molitrix</span> populations.</p>
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<p>Structure analysis of <span class="html-italic">H. molitrix</span> populations using genotype data from 13 SSR sites. (K = 2).</p>
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12 pages, 1380 KiB  
Article
Differences and Similarities in Adaptive Functioning between Children with Autism Spectrum Disorder and Williams–Beuren Syndrome: A Longitudinal Study
by Paolo Alfieri, Francesco Scibelli, Federica Alice Maria Montanaro, Maria Cristina Digilio, Lucilla Ravà, Giovanni Valeri and Stefano Vicari
Genes 2022, 13(7), 1266; https://doi.org/10.3390/genes13071266 - 16 Jul 2022
Cited by 5 | Viewed by 3410
Abstract
Background: The last decade has seen a growing number of comparative studies on adaptive profiles between individuals with autism spectrum disorder (ASD) and Williams–Beuren syndrome (WBS), showing shared and syndrome-specific adaptive trajectories. Studies have revealed similarities in global adaptive profiles across conditions, while [...] Read more.
Background: The last decade has seen a growing number of comparative studies on adaptive profiles between individuals with autism spectrum disorder (ASD) and Williams–Beuren syndrome (WBS), showing shared and syndrome-specific adaptive trajectories. Studies have revealed similarities in global adaptive profiles across conditions, while some differences have been found in preschoolers on the specific sub-domains of communication and socialization. However, the majority of studies that have focused on the differences in adaptive functioning across these two conditions used a cross-sectional design. To the best of our knowledge, there are no studies exploring the differences and similarities of adaptive functioning over time. Methods: We compared longitudinal data of adaptive functioning measured by Vineland Adaptive Behavior Scales (VABS) between two samples of children and adolescents with ASD and WBS, matched for chronological age and cognitive/developmental level at the time of the first evaluation. Results and Conclusions: We did not find any difference on the global adaptive level, both at the first evaluation and over time. However, significant differences emerged on the socialization and communication levels at the time of recruitment. Longitudinal data show that only the socialization domain remains different over time, with individuals with WBS having better functioning than those with ASD. The results on shared and distinct patterns of adaptive functioning between disorders are discussed from a developmental perspective, thus contributing to the implementation of age-specific interventions. Full article
(This article belongs to the Special Issue Advances in Genetics of Psychiatric Disorders)
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<p>Data collection distribution for each patients’ group.</p>
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<p>(<b>a</b>) VABS communication domain’s developmental trajectories, (<b>b</b>) VABS daily living skills domain’s developmental trajectories, (<b>c</b>) VABS socialization domain’s developmental trajectories, (<b>d</b>) VABS-ABC domain’s developmental trajectories.</p>
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<p>(<b>a</b>) VABS communication domain’s developmental trajectories, (<b>b</b>) VABS daily living skills domain’s developmental trajectories, (<b>c</b>) VABS socialization domain’s developmental trajectories, (<b>d</b>) VABS-ABC domain’s developmental trajectories.</p>
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<p>(<b>a</b>) VABS communication domain’s developmental trajectories, (<b>b</b>) VABS daily living skills domain’s developmental trajectories, (<b>c</b>) VABS socialization domain’s developmental trajectories, (<b>d</b>) VABS-ABC domain’s developmental trajectories.</p>
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13 pages, 1864 KiB  
Article
HSPA8 Single-Nucleotide Polymorphism Is Associated with Serum HSC70 Concentration and Carotid Artery Atherosclerosis in Nonalcoholic Fatty Liver Disease
by Wenli Zhao, Hitoe Mori, Yuki Tomiga, Kenichi Tanaka, Rasheda Perveen, Keiichiro Mine, Chika Inadomi, Wataru Yoshioka, Yoshihito Kubotsu, Hiroshi Isoda, Takuya Kuwashiro, Satoshi Oeda, Takumi Akiyama, Ye Zhao, Iwata Ozaki, Seiho Nagafuchi, Atsushi Kawaguchi, Shinichi Aishima, Keizo Anzai and Hirokazu Takahashi
Genes 2022, 13(7), 1265; https://doi.org/10.3390/genes13071265 - 16 Jul 2022
Cited by 5 | Viewed by 2985
Abstract
There is an association between nonalcoholic fatty liver disease (NAFLD) and atherosclerosis, but the genetic risk of atherosclerosis in NAFLD remains unclear. Here, a single-nucleotide polymorphism (SNP) of the heat shock 70 kDa protein 8 (HSPA8) gene was analyzed in 123 [...] Read more.
There is an association between nonalcoholic fatty liver disease (NAFLD) and atherosclerosis, but the genetic risk of atherosclerosis in NAFLD remains unclear. Here, a single-nucleotide polymorphism (SNP) of the heat shock 70 kDa protein 8 (HSPA8) gene was analyzed in 123 NAFLD patients who had been diagnosed using a liver biopsy, and the NAFLD phenotype including the maximum intima–media thickness (Max-IMT) of the carotid artery was investigated. Patients with the minor allele (A/G or G/G) of rs2236659 showed a lower serum heat shock cognate 71 kDa protein concentration than those with the major A/A allele. Compared with the patients with the major allele, those with the minor allele showed a higher prevalence of hypertension and higher Max-IMT in men. No significant associations between the HSPA8 genotype and hepatic pathological findings were identified. In decision-tree analysis, age, sex, liver fibrosis, and HSPA8 genotype were individually associated with severe carotid artery atherosclerosis (Max-IMT ≥ 1.5 mm). Noncirrhotic men aged ≥ 65 years were most significantly affected by the minor allele of HSPA8. To predict the risk of atherosclerosis and cardiovascular disease, HSPA8 SNP genotyping might be useful, particularly for older male NAFLD patients. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Vascular Disease)
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<p>Comparison of serum HSC70 concentration and Max-IMT between <span class="html-italic">HSPA8</span> genotypes. (<b>A</b>,<b>B</b>) HSC70 concentration (<b>A</b>) and Max-IMT (<b>B</b>) were compared between the patients homozygous for the major allele and those with at least one copy of the minor allele in the patients overall. The middle bar represents the median and the upper/lower bars represent the 95% confidence interval. * <span class="html-italic">p</span> &lt; 0.05. HSC70, heat shock cognate 71 kDa protein; Max-IMT, maximum intima–media thickness.</p>
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<p>Sex differences in the association of Max-IMT and <span class="html-italic">HSPA8</span> genotypes. (<b>A</b>) Comparison of Max-IMT between the <span class="html-italic">HSPA8</span> genotypes stratified by sex. The middle bar represents the median and the upper/lower bars represent the 95% confidence interval. (<b>B</b>–<b>D</b>) <span class="html-italic">HSPA8</span> genotype prevalence in the individual Max-IMT categories overall (<b>B</b>) and in female patients (<b>C</b>) and male patients (<b>D</b>). * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01. Max-IMT, maximum intima–media thickness; <span class="html-italic">HSPA8</span>, heat shock 70 kDa protein 8.</p>
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<p>Max-IMT and <span class="html-italic">PNPLA3</span> genotypes. (<b>A</b>) Max-IMT was compared among three <span class="html-italic">PNPLA3</span> genotypes. (<b>B</b>) Comparison of Max-IMT between the two <span class="html-italic">PNPLA3</span> genotype groups stratified by sex. The middle bar represents the median and the upper/lower bars represent the 95% confidence interval. Max-IMT, maximum intima–media thickness; <span class="html-italic">PNPLA3</span>, patatin-like phospholipase domain-containing protein 3.</p>
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<p>Association among age, liver fibrosis, and Max-IMT. (<b>A</b>) Correlation between age and Max-IMT. (<b>B</b>) Max-IMT at each hepatic fibrosis stage. The middle bar represents the median and the upper/lower bars represent the 95% confidence interval. (<b>C</b>) Association between hypertension and hepatic fibrosis stage. * <span class="html-italic">p</span> &lt; 0.05. Max-IMT, maximum intima–media thickness.</p>
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<p>Decision-tree analysis to identify the factors associated with significant Max-IMT. Max-IMT, maximum intima–media thickness.</p>
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27 pages, 6120 KiB  
Article
Photosynthetic, Respirational, and Growth Responses of Six Benthic Diatoms from the Antarctic Peninsula as Functions of Salinity and Temperature Variations
by Lara R. Prelle, Ina Schmidt, Katherina Schimani, Jonas Zimmermann, Nelida Abarca, Oliver Skibbe, Desiree Juchem and Ulf Karsten
Genes 2022, 13(7), 1264; https://doi.org/10.3390/genes13071264 - 16 Jul 2022
Cited by 11 | Viewed by 2903
Abstract
Temperature and salinity are some of the most influential abiotic parameters shaping biota in aquatic ecosystems. In recent decades, climate change has had a crucial impact on both factors—especially around the Antarctic Peninsula—with increasing air and water temperature leading to glacial melting and [...] Read more.
Temperature and salinity are some of the most influential abiotic parameters shaping biota in aquatic ecosystems. In recent decades, climate change has had a crucial impact on both factors—especially around the Antarctic Peninsula—with increasing air and water temperature leading to glacial melting and the accompanying freshwater increase in coastal areas. Antarctic soft and hard bottoms are typically inhabited by microphytobenthic communities, which are often dominated by benthic diatoms. Their physiology and primary production are assumed to be negatively affected by increased temperatures and lower salinity. In this study, six representative benthic diatom strains were isolated from different aquatic habitats at King George Island, Antarctic Peninsula, and comprehensively identified based on molecular markers and morphological traits. Photosynthesis, respiration, and growth response patterns were investigated as functions of varying light availability, temperature, and salinity. Photosynthesis–irradiance curve measurements pointed to low light requirements, as light-saturated photosynthesis was reached at <70 µmol photons m−2 s−1. The marine isolates exhibited the highest effective quantum yield between 25 and 45 SA (absolute salinity), but also tolerance to lower and higher salinities at 1 SA and 55 SA, respectively, and in a few cases even <100 SA. In contrast, the limnic isolates showed the highest effective quantum yield at salinities ranging from 1 SA to 20 SA. Almost all isolates exhibited high effective quantum yields between 1.5 °C and 25 °C, pointing to a broad temperature tolerance, which was supported by measurements of the short-term temperature-dependent photosynthesis. All studied Antarctic benthic diatoms showed activity patterns over a broader environmental range than they usually experience in situ. Therefore, it is likely that their high ecophysiological plasticity represents an important trait to cope with climate change in the Antarctic Peninsula. Full article
(This article belongs to the Special Issue Polar Genomics)
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<p>Sampling points: (<b>A</b>) map of the Antarctic, (<b>B</b>) map of King George Island, and (<b>C</b>) sample points in the Potter Cove: limnic location APC18, brackish water location APC12, and marine locations APC06, APC14, and APC28. Basemap: Landsat image mosaic of Antarctica (LIMA).</p>
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<p>LM and SEM Image Set 1 (<b>A</b>–<b>U</b>): (<b>A</b>–<b>K</b>) <span class="html-italic">Navicula criophiliforma</span>. (<b>A</b>–<b>E</b>) LM pictures; development of auxospores led to size differences in the valves in the culture. (<b>F</b>–<b>K</b>) SEM pictures: (<b>F</b>) whole-valve internal view, (<b>G</b>) whole-valve external view, (<b>H</b>) external central raphe endings, (<b>I</b>) valve apex external view, (<b>J</b>) internal proximal raphe endings, (<b>K</b>) valve apex internal view. (<b>L</b>–<b>T</b>) <span class="html-italic">Chamaepinnularia gerlachei</span>, APC12 D294_006, and <span class="html-italic">Chamaepinnularia gerlachei</span>: (<b>L</b>,<b>M</b>) LM pictures of the strain <span class="html-italic">Chamaepinnularia gerlachei</span>, (<b>N</b>–<b>P</b>) LM pictures of the strain APC12 D294_006, (<b>Q</b>–<b>U</b>) SEM pictures of APC12 D294_006. (<b>Q</b>,<b>R</b>) whole-valve external view, hymenate occlusion of areolae partly corroded, (<b>S</b>) whole-valve internal view, (<b>T</b>) valve in girdle view, (<b>U</b>) valve apex internal view. Scale bars: (<b>A</b>–<b>G</b>) and (<b>L</b>–<b>P</b>) 10 µm, (<b>H</b>–<b>K</b>) and (<b>U</b>) 2 µm, and (<b>Q</b>–<b>T</b>) 5 µm.</p>
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<p>LM and SEM Image Set 2 (<b>A</b>–<b>U</b>): (<b>A</b>–<b>K</b>) <span class="html-italic">Navicula concordia</span>. (<b>A</b>–<b>E</b>) LM pictures. (<b>F</b>–<b>K</b>) SEM pictures: (<b>F</b>) whole-valve external view, (<b>G</b>) whole-valve internal view, (<b>H</b>) valve apex external view, (<b>I</b>) external proximal raphe endings, (<b>J</b>) valve apex internal view, (<b>K</b>) internal proximal raphe endings. (<b>L</b>–<b>U</b>) <span class="html-italic">Nitzschia annewillemsiana</span>: (<b>L</b>–<b>Q</b>) LM pictures. (<b>R</b>–<b>U</b>) SEM pictures: (<b>R</b>) valve apex external view, (<b>S</b>) valve apex internal view, (<b>T</b>) whole-valve internal view, (<b>U</b>) whole-valve external view. Scale bars: (<b>A</b>–<b>G</b>) and (<b>L</b>–<b>Q</b>) 10 µm, (<b>H</b>–<b>K</b>) and (<b>R</b>,<b>S</b>) 3 µm, and (<b>T</b>,<b>U</b>) 5 µm.</p>
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<p>LM and SEM Image Set 3: (<b>A</b>–<b>L</b>) <span class="html-italic">Planothidium</span> sp. (<b>A</b>–<b>E</b>) LM pictures. (<b>F</b>–<b>L</b>) SEM pictures: (<b>F</b>) whole-sternum-valve external view, (<b>G</b>) whole-raphe-valve external view, (<b>H</b>) valve in girdle view, (<b>I</b>) whole-sternum-valve internal view, (<b>J</b>) whole-raphe-valve internal view, (<b>K</b>) internal valve view of one stria with rows of areolae with hymenate occlusions, (<b>L</b>) internal valve view of one stria with rows of areolae. (<b>M</b>–<b>Z</b>) <span class="html-italic">Psammothidium papilio</span>: (<b>M</b>–<b>R</b>) LM pictures. (<b>T</b>–<b>Z</b>) SEM pictures: (<b>T</b>) whole-raphe-valve external view, (<b>U</b>) whole-sternum-valve external view, (<b>V</b>) whole-raphe-valve-internal view, (<b>W</b>) whole-sternum-valve internal view, (<b>X</b>) valves in girdle view, (<b>Y</b>) internal sternum valve view of areolae with hymenate occlusions, (<b>Z</b>) internal raphe valve view of areolae. Scale bars: (<b>A</b>–<b>E</b>), (<b>F</b>–<b>J</b>) and (<b>T</b>–<b>X</b>) 5 µm, (<b>K</b>,<b>L</b>) 1 µm, and (<b>Y</b>,<b>Z</b>) 2 µm.</p>
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<p>Effective quantum yield of photosystem II (Fv/Fm) as a function of salinity of six benthic diatom strains from Antarctica after 3 days of incubation (<b>A</b>–<b>F</b>). Data represent mean values ± SD (<span class="html-italic">n</span> = 6). Different lowercase letters indicate significant means (<span class="html-italic">p</span> &lt; 0.05; one-way ANOVA with post hoc Tukey’s test). (<b>A</b>) <span class="html-italic">Navicula criophiliforma</span>, (<b>B</b>) <span class="html-italic">Chamaepinnularia gerlachei</span>, (<b>C</b>) <span class="html-italic">Navicula concordia</span>, (<b>D</b>) <span class="html-italic">Nitzschia annewillemsiana</span>, (<b>E</b>) <span class="html-italic">Planothidium</span> sp., and (<b>F</b>) <span class="html-italic">Psammothidium papilio</span>.</p>
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<p>Effects of (<b>A</b>) salinity and (<b>B</b>) temperature on the effective quantum yield of photosystem II (Fv/Fm) of six benthic diatom strains from Antarctica. Dark blue symbols represent the range of the highest effective quantum yield at the 80th percentile and above, medium blue symbols are between the 20th and 80th percentiles, light blue symbols represent the 20th percentile and below, and white symbols were not tested. Data represent mean values (<span class="html-italic">n</span> = 6).</p>
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<p>Effective quantum yield of photosystem II (Fv/Fm) as a function of temperature of six benthic diatom strains from Antarctica after 0 days (blue) and 5 days (purple) of incubation (<b>A</b>–<b>F</b>). Data represent mean values ± SD (<span class="html-italic">n</span> = 6). Different capital (t<sub>0</sub>) and lowercase (t<sub>5</sub>) letters indicate significant means (<span class="html-italic">p</span> &lt; 0.05; one-way ANOVA with post hoc Tukey’s test). (<b>A</b>) <span class="html-italic">Navicula criophiliforma</span>, (<b>B</b>) <span class="html-italic">Chamaepinnularia gerlachei</span>, (<b>C</b>) <span class="html-italic">Navicula concordia</span>, (<b>D</b>) <span class="html-italic">Nitzschia annewillemsiana</span>, (<b>E</b>) <span class="html-italic">Planothidium</span> sp., and (<b>F</b>) <span class="html-italic">Psammothidium papilio</span>.</p>
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<p>Photosynthesis and respiration rates (μmol O<sub>2</sub> mg<sup>−1</sup> Chl <span class="html-italic">a</span> h<sup>−1</sup>) as a function of increasing photon flux density (μmol photons m<sup>−2</sup> s<sup>−1</sup>) of six benthic diatom strains from Antarctica kept at 8 °C in f/2 medium: 33 S<sub>A</sub> (<b>A</b>–<b>C</b>) and 1 S<sub>A</sub> (<b>D</b>–<b>F</b>). Data represent mean values ± SD (<span class="html-italic">n</span> = 3). Data points were fitted using the model of Walsby [<a href="#B50-genes-13-01264" class="html-bibr">50</a>]. (<b>A</b>) <span class="html-italic">Navicula criophiliforma</span>, (<b>B</b>) <span class="html-italic">Chamaepinnularia gerlachei</span>, (<b>C</b>) <span class="html-italic">Navicula concordia</span>, (<b>D</b>) <span class="html-italic">Nitzschia annewillemsiana</span>, (<b>E</b>) <span class="html-italic">Planothidium</span> sp., and (<b>F</b>) <span class="html-italic">Psammothidium papilio</span>.</p>
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<p>Photosynthetic (blue) oxygen production at 342 ± 40 µmol photons m<sup>−2</sup> s<sup>−1</sup> and respiratory (red) oxygen consumption in darkness of six benthic diatom strains from Antarctica, as a function of increasing temperature (<b>A</b>–<b>F</b>). The measured data were fitted using the model of Yan and Hunt [<a href="#B55-genes-13-01264" class="html-bibr">55</a>] (photosynthesis: blue dashed line; respiration: red dashed line). All cultures were kept in f/2 Baltic Sea media: 33 S<sub>A</sub> (<b>A</b>–<b>C</b>) and 1 S<sub>A</sub> (<b>D</b>–<b>F</b>). Data represent mean values ± SD (<span class="html-italic">n</span> = 3). Different lowercase (photosynthesis) and capital letters (respiration) indicate significant means (<span class="html-italic">p</span> &lt; 0.05; one-way ANOVA with post hoc Tukey’s test). (<b>A</b>) <span class="html-italic">Navicula criophiliforma</span>, (<b>B</b>) <span class="html-italic">Chamaepinnularia gerlachei</span>, (<b>C</b>) <span class="html-italic">Navicula concordia</span>, (<b>D</b>) <span class="html-italic">Nitzschia annewillemsiana</span>, (<b>E</b>) <span class="html-italic">Planothidium</span> sp., and (<b>F</b>) <span class="html-italic">Psammothidium papilio</span>.</p>
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<p>Growth rates (µ d<sup>−1</sup>) in relation to (<b>A</b>) temperature and (<b>B</b>) salinity of the respective diatom strains <span class="html-italic">Chamaepinnularia gerlachei</span> and <span class="html-italic">Psammothidium papilio</span>. Data represent mean values ± SD (<span class="html-italic">n</span> = 3). Different lowercase letters represent significance levels among all means, as calculated per temperature or salinity by one-way ANOVA (Tukey’s test, <span class="html-italic">p</span> &lt; 0.05). Please note the different salinity ranges for both species.</p>
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15 pages, 7528 KiB  
Article
Karyotypes of Manatees: New Insights into Hybrid Formation (Trichechus inunguis × Trichechus m. manatus) in the Amazon Estuary
by Renata C. R. Noronha, Bruno R. R. Almeida, Monique C. S. Chagas, Flávia S. Tavares, Adauto L. Cardoso, Carlos E. M. C. Bastos, Natalia K. N. Silva, Alex G. C. M. Klautau, Fábia O. Luna, Fernanda L. N. Attademo, Danielle S. Lima, Luiz A. Sabioni, Maria I. C. Sampaio, Jairo Moura Oliveira, Luís Adriano Santos do Nascimento, Cesar Martins, Marcelo R. Vicari, Cleusa Y. Nagamachi and Julio C. Pieczarka
Genes 2022, 13(7), 1263; https://doi.org/10.3390/genes13071263 - 16 Jul 2022
Cited by 8 | Viewed by 3076
Abstract
Great efforts have been made to preserve manatees. Recently, a hybrid zone was described between Trichechus inunguis (TIN) and the Trichechus manatus manatus (TMM) in the Amazon estuary. Cytogenetic data on these sirenians are limited, despite being fundamental to understanding the hybridization/introgression dynamics [...] Read more.
Great efforts have been made to preserve manatees. Recently, a hybrid zone was described between Trichechus inunguis (TIN) and the Trichechus manatus manatus (TMM) in the Amazon estuary. Cytogenetic data on these sirenians are limited, despite being fundamental to understanding the hybridization/introgression dynamics and genomic organization in Trichechus. We analyzed the karyotype of TMM, TIN, and two hybrid specimens (“Poque” and “Vitor”) by classical and molecular cytogenetics. G-band analysis revealed that TMM (2n = 48) and TIN (2n = 56) diverge by at least six Robertsonian translocations and a pericentric inversion. Hybrids had 2n = 50, however, with Autosomal Fundamental Number (FNA) = 88 in “Poque” and FNA = 74 in “Vitor”, and chromosomal distinct pairs in heterozygous; additionally, “Vitor” exhibited heteromorphisms and chromosomes whose pairs could not be determined. The U2 snDNA and Histone H3 multi genes are distributed in small clusters along TIN and TMM chromosomes and have transposable Keno and Helitron elements (TEs) in their sequences. The different karyotypes observed among manatee hybrids may indicate that they represent different generations formed by crossing between fertile hybrids and TIN. On the other hand, it is also possible that all hybrids recorded represent F1 and the observed karyotype differences must result from mechanisms of elimination. Full article
(This article belongs to the Special Issue Chromosome Evolution and Karyotype Analysis)
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Graphical abstract

Graphical abstract
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<p>Karyotype of TIN (<b>A</b>,<b>B</b>) and TMM (<b>C</b>,<b>D</b>), after G-banding (<b>A</b>,<b>C</b>) and C-banding (<b>B</b>,<b>D</b>). In (<b>A</b>,<b>C</b>), an ideogram shows the pattern of G bands next to each chromosome pair. Bar 10 µm.</p>
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<p>Comparative analysis by G-banding between TIN and TMM: (<b>A</b>) possible chromosomal homologies; and (<b>B</b>) possible chromosomal rearrangements. Bar 10 µm.</p>
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<p>G-banded karyotype of hybrid specimens of manatee: (<b>A</b>). “Poque”; (<b>B</b>). “Vitor”. The blue and red bars indicate probable homologies. The black bars show chromosomes whose pairs could not be determined by the banding pattern. Bar 10 µm.</p>
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<p>Fluorescent in situ hybridization with probes of telomeric sequences (<b>A</b>–<b>D</b>) and 45S rDNA (<b>E</b>–<b>H</b>): (<b>A</b>,<b>E</b>) <span class="html-italic">T. inunguis</span>; (<b>B</b>,<b>F</b>) <span class="html-italic">T. m. manatus</span>; (<b>C</b>,<b>G</b>) “Poque”; and (<b>D</b>,<b>H</b>) “Vitor”. Bar 10 µm.</p>
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<p>Chromosomal mapping of the transposable element LINE-1: (<b>A</b>) <span class="html-italic">T. inunguis</span>; (<b>B</b>) <span class="html-italic">T. m. manatus</span>; the insert indicates the pair 1 chromosome with a LINE-1 pattern similar to bands and compared to the pattern of G bands; and (<b>C</b>) “Poque”. Arrows indicate chromosomal regions in TIN and TMM karyotypes with low LINE-1 concentration. Bar 10 µm.</p>
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<p>FISH with probe of U2-snDNA (<b>A</b>,<b>B</b>) and H3 Histone (<b>C</b>–<b>F</b>) genes; (<b>A</b>–<b>C</b>) <span class="html-italic">T. m. manatus</span>; (<b>B</b>–<b>D</b>) <span class="html-italic">T. inunguis</span>; (<b>E</b>) “Poque”; and (<b>F</b>) “Vitor”. Bar 10 µm.</p>
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<p>Repetitive DNA sequences isolated from the <span class="html-italic">Trichechus</span> genome: (<b>A</b>) partial sequence of U2 snRNA with similarity to non-LTR Keno_1_SSa retrotransposon (blue); and (<b>B</b>) partial H3 sequence of Trichechus showing a segment similar (102–182 bp) to the Helitron 4N1_SMo transposon (blue).</p>
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<p>Hypothesis of hybrid formation in <span class="html-italic">Trichechus</span> in the Amazon estuary: (<b>A</b>) crosses between <span class="html-italic">T. inunguis</span> (2n = 56) and <span class="html-italic">T. m. manatus</span> (2n = 48) generate the F1 hybrid (2n = 52). Backcross between F1 hybrid and <span class="html-italic">T. m. manatus</span> generate F2 hybrid (2n = 50). In turn, interbreeding between F2 hybrids and <span class="html-italic">T. m. manatus</span> produces F3 hybrids (2n = 49); and (<b>B</b>) crosses between <span class="html-italic">T. inunguis</span> (2n = 56) and <span class="html-italic">T. m. manatus</span> (2n = 48) generate the F1 hybrids with distinct chromosome numbers (2n = 49, 50, 52) as consequence of chromosome elimination.</p>
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