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Keywords = PANFIS

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14 pages, 4416 KiB  
Article
Genome-Wide Identification and Expression Analysis of the NF-Y Transcription Factor Family in Prunus armeniaca
by Jiangting Wu, Yanguang He, Lin Wang, Han Zhao, Nan Jiang, Tana Wuyun and Huimin Liu
Forests 2024, 15(11), 1986; https://doi.org/10.3390/f15111986 - 10 Nov 2024
Viewed by 796
Abstract
The nuclear factor Y (NF-Y) gene family plays important roles in regulating many of the biological processes of plants, including oil accumulation. The apricot (Prunus armeniaca) is one of the most commercially traded plants, and apricot kernel oil has a high [...] Read more.
The nuclear factor Y (NF-Y) gene family plays important roles in regulating many of the biological processes of plants, including oil accumulation. The apricot (Prunus armeniaca) is one of the most commercially traded plants, and apricot kernel oil has a high nutritional value owing to its richness in fatty acids and bioactive compounds. However, the systematic characterization of the PaNF-Y family in the apricot and the underlying regulatory mechanisms involved in oil biosynthesis remain unclear. In this study, a total of 28 PaNF-Y members from the apricot genome were identified and divided into three subfamilies (6 PaNF-YAs, 15 PaNF-YBs, and 7 PaNF-YCs) based on phylogenetic analysis results. The types and distributions of the gene structures and conserved motifs were similar in the clustered PaNF-Ys of the same subfamily. Gene duplication analysis results revealed that segmental duplication events were important for the expansion of the PaNF-Y family. Importantly, transcriptome data analysis results showed that most genes of the PaNF-YA subfamily and PaNF-YB4 of the PaNF-YB subfamily were specifically expressed in the apricot kernel. Furthermore, highly positive correlations were observed between apricot oil content and the transcript levels of PaNF-YA2, PaNF-YA6, and PaNF-YB4. In conclusion, our results provide insights into the molecular mechanisms of the key PaNF-Y genes regulating apricot oil biosynthesis. Full article
(This article belongs to the Section Genetics and Molecular Biology)
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Figure 1

Figure 1
<p>Phylogenetic analysis of the NF-Y gene family in <span class="html-italic">P. armeniaca</span> (Pa) and <span class="html-italic">A. thaliana</span> (At). The red and blue dots represent the genes from the genome of <span class="html-italic">P. armeniaca</span> and <span class="html-italic">A. thaliana</span>, respectively. Orange, purple, and green branches represent NF-YAs, NF-YBs, and NF-YCs, respectively. The accession numbers of NF-Y genes are listed in <a href="#app1-forests-15-01986" class="html-app">Table S3</a>.</p> Full article ">Figure 2
<p>Schematic diagram of the gene structure and conserved motifs of the PaNF-Y gene family in <span class="html-italic">P. armeniaca</span>. (<b>A</b>) The phylogenetic tree of PaNF-Y proteins based on amino acid sequences. Orange, purple, and green branches represent PaNF-YAs, PaNF-YBs, and PaNF-YCs, respectively. (<b>B</b>) The exon/intron structure of the <span class="html-italic">PaNF-Y</span> genes. UTRs, exons, and introns are shown in blue boxes, yellow boxes, and gray lines, respectively. (<b>C</b>) The conserved motifs of PaNF-Y proteins were identified using MEME. Different colored boxes represent the different motifs of proteins. The scales at the bottom in panels (<b>B</b>,<b>C</b>) indicate the sequence lengths. The conserved motifs are listed in <a href="#app1-forests-15-01986" class="html-app">Table S4</a>.</p> Full article ">Figure 3
<p>Chromosomal locations of <span class="html-italic">PaNF-Y</span> genes on eight apricot chromosomes. The different colors represent gene density on the chromosomes, with red representing high gene density and blue representing low gene density. The scale on the left represents the lengths of the <span class="html-italic">P. armeniaca</span> chromosomes.</p> Full article ">Figure 4
<p>Synteny analysis of <span class="html-italic">PaNF-Y</span> genes. (<b>A</b>) Synteny analysis of <span class="html-italic">PaNF-Y</span> genes in <span class="html-italic">P. armeniaca</span>. The lines and heatmaps along the rectangles represent gene density on the chromosomes. The gray lines indicate synteny blocks in the apricot genome, while the red lines between chromosomes delineate segmental duplicated gene pairs. (<b>B</b>) Synteny analysis of <span class="html-italic">PaNF-Y</span> genes between the genome of <span class="html-italic">P. armeniaca</span> and that of <span class="html-italic">A. thaliana</span>. The gray lines represent the collinear blocks between the apricot and <span class="html-italic">Arabidopsis</span>. The syntenic <span class="html-italic">NF-Y</span> gene pairs are shown to be connected by the red lines.</p> Full article ">Figure 5
<p>Cis-elements of <span class="html-italic">PaNF-Y</span> genes in the genome of <span class="html-italic">P. armeniaca. PaNF-Y</span> genes are listed on the Y axis; orange, purple, and green represent different clades of the <span class="html-italic">PaNF-Y</span> family. The regulatory elements on the promoter regions of <span class="html-italic">PaNF-Y</span> genes are listed on the X axis. The different intensity colors and figures of the grids indicate the number of elements.</p> Full article ">Figure 6
<p>Expression patterns of the <span class="html-italic">PaNF-Y</span> gene family in different tissues of <span class="html-italic">P. armeniaca</span>. (<b>A</b>) Heatmaps showing the gene expression profiles of <span class="html-italic">PaNF-Ys</span> in the kernel, fruit, flower, flower bud, and leaf. The heatmaps were generated in the R package based on normalized FPKM values. Blue, white, and red represent low, medium, and high expression, respectively. K1–K5: kernels from different developmental stages. F1–F8: flesh from different stages. FL: flower. FB: flower bud. (<b>B</b>–<b>H</b>) Reverse transcription–quantitative polymerase chain reaction analysis of the selected <span class="html-italic">PaNF-Y</span> genes in the different developmental stages of apricot kernels. The bars in each panel indicate the means ± SE (n = 3). Different letters on the bars indicate significant differences between the groups.</p> Full article ">
21 pages, 4397 KiB  
Article
Parsimonious Network Based on a Fuzzy Inference System (PANFIS) for Time Series Feature Prediction of Low Speed Slew Bearing Prognosis
by Wahyu Caesarendra, Mahardhika Pratama, Buyung Kosasih, Tegoeh Tjahjowidodo and Adam Glowacz
Appl. Sci. 2018, 8(12), 2656; https://doi.org/10.3390/app8122656 - 17 Dec 2018
Cited by 53 | Viewed by 3812
Abstract
In recent years, the utilization of rotating parts, e.g., bearings and gears, has been continuously supporting the manufacturing line to produce a consistent output quality. Due to their critical role, the breakdown of these components might significantly impact the production rate. Prognosis, which [...] Read more.
In recent years, the utilization of rotating parts, e.g., bearings and gears, has been continuously supporting the manufacturing line to produce a consistent output quality. Due to their critical role, the breakdown of these components might significantly impact the production rate. Prognosis, which is an approach that predicts the machine failure, has attracted significant interest in the last few decades. In this paper, the prognostic approaches are described briefly and advanced predictive analytics, namely a parsimonious network based on a fuzzy inference system (PANFIS), is proposed and tested for low speed slew bearing data. PANFIS differs itself from conventional prognostic approaches, supporting online lifelong prognostics without the requirement of a retraining or reconfiguration phase. The PANFIS method is applied to normal-to-failure bearing vibration data collected for 139 days to predict the time-domain features of vibration slew bearing signals. The performance of the proposed method is compared to some established methods, such as ANFIS, eTS, and Simp_eTS. From the results, it is suggested that PANFIS offers an outstanding performance compared to those methods. Full article
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Figure 1

Figure 1
<p>(<b>a</b>) Slew bearing rig picture; (<b>b</b>) Schematic of laboratory slew bearing rig showing a slew bearing attached in the drive ring and the applied load from the hydraulic.</p> Full article ">Figure 2
<p>A detailed sketch of the location of four accelerometers and two AE sensors on slew bearing.</p> Full article ">Figure 3
<p>Slew bearing vibration signal on 30 August 2007: (<b>a</b>) 1 min duration signal; (<b>b</b>) FFT.</p> Full article ">Figure 4
<p>Time-domain feature extraction results (139 days).</p> Full article ">Figure 5
<p>An architectural scheme of the PANFIS method.</p> Full article ">Figure 6
<p>A schematic diagram of direct mode prediction.</p> Full article ">Figure 7
<p>PANFIS prediction of kurtosis feature.</p> Full article ">Figure 8
<p>Fuzzy rule evolution of kurtosis feature.</p> Full article ">Figure 9
<p>A schematic diagram of time series mode prediction.</p> Full article ">Figure 10
<p>PANFIS prediction of variance feature.</p> Full article ">Figure 11
<p>Fuzzy rule evolution of variance feature.</p> Full article ">Figure 12
<p>PANFIS prediction of histogram lower feature.</p> Full article ">Figure 13
<p>Fuzzy rule evolution of histogram lower feature.</p> Full article ">
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