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Homologue engagement controls meiotic DNA break number and distribution

Nature volume 510, pages 241–246 (2014)Cite this article

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Abstract

Meiotic recombination promotes genetic diversification as well as pairing and segregation of homologous chromosomes, but the double-strand breaks (DSBs) that initiate recombination are dangerous lesions that can cause mutation or meiotic failure. How cells control DSBs to balance between beneficial and deleterious outcomes is not well understood. Here we test the hypothesis that DSB control involves a network of intersecting negative regulatory circuits. Using multiple complementary methods, we show that DSBs form in greater numbers in Saccharomyces cerevisiae cells lacking ZMM proteins, a suite of recombination-promoting factors traditionally regarded as acting strictly downstream of DSB formation. ZMM-dependent DSB control is genetically distinct from a pathway tying break formation to meiotic progression through the Ndt80 transcription factor. These counterintuitive findings suggest that homologous chromosomes that have successfully engaged one another stop making breaks. Genome-wide DSB maps uncover distinct responses by different subchromosomal domains to the ZMM mutation zip3 (also known as cst9), and show that Zip3 is required for the previously unexplained tendency of DSB density to vary with chromosome size. Thus, feedback tied to ZMM function contributes in unexpected ways to spatial patterning of recombination.

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Figure 1: More DSBs form in ZMM mutants.
Figure 2: Hyper-rec phenotype of ZMM mutants.
Figure 3: Separable effects of ndt80 and ZMM mutations.
Figure 4: Altered DSB distribution in zip3 mutants.

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Sequencing data were deposited at GEO under accession number GSE48299.

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Acknowledgements

We are grateful to S. Burgess, N. Hunter, N. Kleckner, K. Ohta, M. Rout and A. Shinohara for strains or epitope tagging constructs; F. Klein for sharing data; S. Shuman for gifts of T4 RNA ligase; A. Viale and the Memorial Sloan Kettering Cancer Center (MSKCC) Genomics Core Laboratory for sequencing; and N. Socci and the MSKCC Bioinformatics Core for assistance mapping Spo11 oligos. This work was supported by National Institutes of Health grant R01 GM058673. S.K. is an Investigator of the Howard Hughes Medical Institute.

Author information

Authors and Affiliations

  1. Molecular Biology Program, Memorial Sloan-Kettering Cancer Center, New York, 10065, New York, USA

    Drew Thacker, Neeman Mohibullah, Xuan Zhu & Scott Keeney

  2. Weill Graduate School of Medical Sciences of Cornell University, New York, 10065, New York, USA

    Drew Thacker, Xuan Zhu & Scott Keeney

  3. Howard Hughes Medical Institute, Memorial Sloan-Kettering Cancer Center, New York, 10065, New York, USA

    Neeman Mohibullah & Scott Keeney

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  1. Drew Thacker
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Contributions

D.T., N.M. and X.Z. performed experiments and analysed the data. N.M. optimized purification of the Spo11–protein A fusion, prepared the sequencing libraries to map DSBs and performed preliminary data analysis on sequencing reads. S.K. analysed sequencing data. D.T. and S.K. wrote the paper.

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Correspondence to Scott Keeney.

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Extended data figures and tables

Extended Data Figure 1 Chromosomal breaks in msh5 and zip1 mutants.

Representative pulsed-field gel Southern blots probed for chromosome IX are shown, labelled as in Fig. 1b.

Extended Data Figure 2 DSB formation appears normal in SPO11-Flag and SPO11-PrA strains.

a, Southern blots probed for chromosome III. High molecular weight chromosomal DNA was purified 6 h after transfer to sporulation medium from meiotic rad50S cultures carrying the indicated SPO11 alleles (in spo11-yf the catalytic tyrosine 135 is mutated to phenylalanine), then separated on pulsed-field electrophoresis gels. Samples from a rad50S spo11-HA strain are shown for comparison; haemagglutinin-tagged Spo11 has reduced DSB frequency. Each lane represents an independent culture (SPO11+ samples from the same cultures were run on both gels). PrA, protein A. b, Quantification of blots in panel a and separate blots (not shown) probed for chromosomes VII or VIII. Break frequencies are per cent of DNA in lane (mean ± s.d. of 3–4 cultures). Numbers in parentheses indicate values from each tagged strain relative to SPO11+ for the same chromosome. Relative DSB frequencies at the bottom are averages across the three chromosomes assayed.

Extended Data Figure 3 Spo11–oligo complexes in msh5 and zip1 mutants.

Representative time courses are shown.

Extended Data Figure 4 Analysis of recombination at three natural DSB hotspots.

a, b, Recombination reporters at the ERG1 (a) and GAT1 (b) hotspots. c–e, Representative Southern blots of parental and recombinant DNA molecules at CCT6 (c), ERG1 (d) and GAT1 (e). The arrowhead in e indicates a non-reproducible radiolabelled species. f, Local distribution of DSBs around recombination reporter locations is not altered in zip3 mutants. Spo11-oligo profiles (averages for wild type and zip3 mutant) are smoothed with 201-bp Hann window; zip3 values are offset to separate profiles.

Extended Data Figure 5 Direct analysis of DSB formation at natural hotspots.

a–d, Representative Southern blots of DNA separated on a conventional agarose gel and probed for GAT1 (a), CCT6 (b, c) and ERG1 (d). The arrowhead in a indicates signal from the CCT6 parental band that remained after stripping and reprobing for GAT1. e, Quantifications for b–d (mean ± s.d. for 3 cultures).

Extended Data Figure 6 Spo11–oligo complexes in msh5 ndt80 double mutant.

Representative time courses are shown.

Extended Data Figure 7 Effects of dmc1 deletion or spo11 hypomorphic mutation on ZMM mutant phenotypes.

a, b, ZMM status is irrelevant in a dmc1 background. Broken chromosomes accumulate to similar levels in a dmc1 single mutant and dmc1 zmm double mutants. Representative pulsed-field gel Southern blots probed for chromosome IX are in a and Poisson-corrected quantification of DSBs is in b (mean ± s.d., 3 cultures). c, Reducing Spo11 activity in a zip3 mutant partially alleviates the prophase I delay/arrest. Meiotic progression was assessed by staining with DAPI (4′,6-diamidino-2-phenylindole) and measuring the percentage of cells that had completed meiosis I (MI) with or without completing meiosis II ( ± MII). Data are means ± s.d. for 3 cultures, except wild type and spo11-HA, each analysed once.

Extended Data Figure 8 Spo11-oligo mapping in wild type and zip3 mutant.

a, b, Quantitative reproducibility of Spo11-oligo maps. In a, comparisons are shown for individual wild type (WT) or zip3 data sets from the present study, or the previously published spo11-HA data (from ref. 11). Uniquely mapped Spo11 oligos were summed in non-overlapping 5-kb bins and expressed as RPM per kb (plotted on a log scale). In b, pairwise correlation coefficients for the data sets from the current study are shown (Pearson’s r; box colours scaled from blue to red proportional to strength of correlation). For the comparison of this study’s wild-type average with data from Pan et al., r = 0.949. Note that Pan et al. used a different strain background with different auxotrophies, which may alter DSB distributions51,52, and a hypomorphic spo11 allele (spo11-HA), which may affect DSBs to different extents at different locations53. Note that biological replicates (WT-1 versus WT-2 or zip3-1 versus zip3-2) agreed better than comparisons between cultures of different genotype. c, DSBs form at the same hotspots and with similar distribution within and between hotspots in wild type and zip3. Unsmoothed Spo11-oligo maps are shown in the vicinity of the well-characterized ARE1 (YCR048w) hotspot.

Extended Data Figure 9 Changes in the DSB landscape in zip3 mutant.

a, Change in Spo11-oligo counts in hotspots grouped by chromosomal context. Tel, within 20 kb of telomeres; Cen, within ± 10 kb of centromeres; rDNA, from 60 kb leftward to 30 kb rightward of rDNA; Interstitial, all others. Dashed lines mark values assumed as no change and average change (1.8-fold). Boxes indicate median and interquartile range; whiskers indicate the most extreme data points which are ≤1.5 times the interquartile range from the box; individual points are outliers. Subtelomeric and pericentric zones show less increase in zip3 on average, thus, ZMM-dependent feedback contributes less than other, unknown factors to suppressing DSBs in these regions. The zone near the rDNA showed no increase or was even decreased; thus, zip3 mutants are competent for this region’s DSB suppression, which is dependent on the ATPase Pch2 and the replication factor Orc1 (ref. 54). Note that the remaining interstitial hotspots showed highly variable response to zip3 mutation (>20 fold). b, Correlation between log-fold change in Spo11-oligo counts in zip3 and the binding of the indicated proteins, binned in non-overlapping windows of varying size. Closed symbols, P < 0.05. ChIP data are from ref. 38. c, Average ChIP profiles around interstitial hotspots divided into three equal-sized groups according to the average fold change in zip3. Top, the box and whisker plot (as described for a) shows the distribution of fold changes for the three groups. Bottom, ChIP profiles for each of the indicated proteins. Note that the profiles lie atop one another for Rec102 and Rec104. Dashed arrows indicate direction of the change in the average profiles with increasing fold change in zip3. ChIP data are from refs 38 and 39. d, High degree of colinearity of log2-transformed ChIP data38 for Rec114, Mei4 and Mer2 (which are essential for DSB formation) and Hop1 and Red1 (axis proteins that promote normal DSB formation). More than 90% of the variance for this combination of ChIP data is captured in the first principal component (PC1). The high degree of correlation between these proteins was described previously38. e, Correlations between the fold change in zip3 (zip3 FC, log2 and assuming 1.8-fold increase genome-wide) and various chromosomal features: principal component 1 for Rec114, Mei4, Mer2, Hop1 and Red1 ChIP data (same as in d); chromosome size (loge(bp)); G+C content (%); and ChIP data for the indicated proteins (log2). In d and e, top right panels show pairwise scatter plots and bottom left panels show corresponding correlation coefficients (Pearson’s r) for data for interstitial regions binned in 35-kb non-overlapping windows. Essentially identical results were obtained with different window sizes (20–40 kb) or with varying placement of windows (data not shown). f, Essentially no correlation between DSB activity in wild type and change in zip3, whether considering interstitial regions divided into non-overlapping 35-kb bins (upper panel) or interstitial hotspots (lower panel). A 1.8-fold increase genome-wide in zip3 is assumed. Note: fold change is labelled according to a linear scale but plotted in a log scale in panels a, c, f.

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This file contains a Supplementary Discussion, Supplementary References and Supplementary Tables 1-3 and 5-6 (see separate file for Supplementary Table 4). (PDF 683 kb)

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Thacker, D., Mohibullah, N., Zhu, X. et al. Homologue engagement controls meiotic DNA break number and distribution. Nature 510, 241–246 (2014). https://doi.org/10.1038/nature13120

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