Mismatch repair disturbs meiotic crossover control: data and code

Data and code for the manuscript "Mismatch repair disturbs meiotic crossover control"Data from experiments in <i>S. cerevisiae</i>Includes positions of crossover and noncrossover events detected in sequencing dataIncludes simulator used to model crossover interference, along with code used to plot the figures of the paper.Abstract:Crossover formation during meiosis generates genetic diversity. In many species most crossovers display interference, meaning they are spaced more evenly than expected by chance, and are called class I crossovers. Class II crossovers, a minority pathway, are believed to lack substantial interference. Here, using whole-genome recombination maps, we examine the impact of mismatch repair (MMR) on the formation and distribution of crossovers in <i>Saccharomyces cerevisiae</i>. Loss of the MMR protein Msh2 increases the uniformity of crossover distributions—an effect that is independent of changes in crossover frequency. Simulations indicate that this effect is driven by increases in the class I crossover proportion without any change in interference strength. Consistent with this view, distributions of Zip3 foci, specific markers of class I crossovers, are unchanged by <i>MSH2 </i>deletion. Notably, in wild-type cells, fewer crossovers arise in regions of higher polymorphism density—a skew that depends on both Msh2 and Zip3. Taken together, our results indicate an unexpected influence of Msh2 on recombination: suppression of class I crossovers in regions of higher polymorphism density, whilst promoting class II crossover formation. Our findings highlight how MMR shapes the landscape of genetic exchange, and links recombination to sequence divergence and its role in speciation.##how to use##Figures_script, Density_COs_DSBs and Migration_testing R scripts:1. Ensure data folder is present in same directory as script, along with a folder titled "Output" (as provided here)2. Run the script. The scripts will search for the required R packages and install them if any are not installed.<br>COsim:1. Load the COsim script2. Run the script. This will store COsim() as a function in the R environment3. Call COsim() with the desired parameters. See the description at the top of the script for more details.<br>###Contents###<br>#ScriptsCOsim- The crossover interference simulatorFigures_script- script used to produce figures used in the studyMigration_testing- script used to displace crossovers randomly using user-defined parametersDensity_COs_DSBs- script used to test effects of possible confounders on observed crossover distributions<br>#DataChrSizesS288cH4L2_L2HG_edited.txt- sizes of S. cerevisiae chromosomes (in S288c strain)fail_fits- results of Kolmogorov-Smirnov tests between different genotypes and simulated data with variable class II crossover fractions and class I crossover failure ratesfail_sim- example output of COsim, used to plot some panels of the figuresfail_sim_model_parameters.csv- results of fitting gamma models to synthetic crossover distributions.gamma_sampling_simplemix.csv- tests of mixed gamma models on sampled gamma distributionsICDs_calc_CO+NCO.csv- inter-CO and NCO distances calculated from file SK1_Crawford&amp;Llorente_MasterEventTable1500NEW.csvICDs_calc_NCO.csv- inter-NCO distances calculated from file SK1_Crawford&amp;Llorente_MasterEventTable1500NEW.csvICDs_calc_YJM_CO+NCO.csv- inter-CO and NCO distances calculated from file YJM_Fung&amp;Mancera_MasterEventTable1500NEW.txtICDs_calc_YJM_NCO.csv- inter-NCO distances calculated from file YJM_Fung&amp;Mancera_MasterEventTable1500NEW.txtICDs_calc_YJM.csv- inter-CO distances calculated from file YJM_Fung&amp;Mancera_MasterEventTable1500NEW.txtICDs_calc.csv- inter-CO distances calculated from file SK1_Crawford&amp;Llorente_MasterEventTable1500NEW.csvIF_3_scale_380_105CO- example simulated ICDs from simulator, 105COs to match SK1 msh2 dataminority_models- results of fitting gamma models to simulations of two independent, interfering classes of crossoverPan.Hotspots.IGR.SacCer3_2016.08.10.txt- DSB hotspot data from Pan et al. 2011, used as control to asses polymorphism densities around COs and NCOspolymorphism_density- results of tests of polymorphism density around COs and NCOsshape_fits- results of testing simulations which vary strength of interference and class II CO proportion on biological datashape_sim- example simulation where strength of interference and class II CO proportion are allowed to varyshape_sim_model_parameters.csv- results of fitting gamma models to simulations in which strength of interference and class II CO proportion are allowed to varySK1_Crawford&amp;Llorente_MasterEventTable1500NEW.csv- crossover and non crossover positions in SK1 strains (Crawford et al 2024)VariantTable_SK1.txt- list of polymorphisms between SK1 and S288c cerevisiae backgroundsYJM_Fung&amp;Mancera_MasterEventTable1500NEW.txt- crossover and non crossover positions in YJM strains (Mancera et al 2008)zip3_event_fits- results of testing simulations on zip3D biological datazip3_microscopy- data processed from images of zip1 and zip3-stained cells<br>#OutputEach file in this folder is a separate panel from the study. Running the scripts Figures_script, Migration_testing and Density_COs_DSBs will reproduce these files.

本数据集与配套代码源自论文《错配修复干扰减数分裂交叉调控》。数据来自酿酒酵母（<i>S. cerevisiae</i>）的实验，涵盖测序数据中检测到的交叉互换（crossover）与非交叉互换（noncrossover）事件的位点，同时包含用于模拟交叉干涉（crossover interference）的模拟器，以及论文配图的绘制代码。

摘要：减数分裂过程中的交叉互换形成可产生遗传多样性。在多数物种中，绝大多数交叉互换表现出干涉效应，即其分布比随机预期更为均匀，这类交叉互换被称为I型交叉互换（class I crossovers）。作为次要途径的II型交叉互换（class II crossovers）则被认为几乎不具备显著干涉效应。本研究利用全基因组重组图谱，探究了错配修复（mismatch repair, MMR）对酿酒酵母（Saccharomyces cerevisiae）交叉互换形成与分布的影响。错配修复蛋白Msh2的缺失会提升交叉互换分布的均匀性——这一效应独立于交叉互换频率的变化。模拟实验表明，该效应源于I型交叉互换占比的提升，而干涉强度未发生改变。与此观点一致的是，作为I型交叉互换特异性标记的Zip3焦点的分布，不受MSH2基因缺失的影响。值得注意的是，在野生型细胞中，多态性密度更高的区域产生的交叉互换更少——这一偏倚同时依赖于Msh2与Zip3。综合来看，我们的研究结果揭示了Msh2对重组过程的意外调控作用：在多态性密度更高的区域抑制I型交叉互换，同时促进II型交叉互换的形成。本研究结果阐明了错配修复如何塑造遗传交换的景观，并将重组过程与序列分化及其在物种形成中的作用联系起来。

## 使用方法
### R脚本（Figures_script、Density_COs_DSBs与Migration_testing）：
1. 确保数据文件夹与脚本位于同一目录下，同时存在如本数据集提供的名为"Output"的输出文件夹；
2. 运行脚本。脚本将自动检索所需的R包，若缺失则自动安装。

### COsim模拟器：
1. 加载COsim脚本；
2. 运行脚本，该操作会将COsim()以函数形式存储至R环境中；
3. 传入所需参数调用COsim()函数。更多细节请参阅脚本顶部的说明文档。

## 内容详情
### 脚本集
- COsim：交叉干涉模拟器
- Figures_script：本研究配图的生成脚本
- Migration_testing：可通过用户自定义参数随机重排交叉互换位点的脚本
- Density_COs_DSBs：用于检验潜在混杂因素对观测到的交叉互换分布影响的脚本

### 数据集文件
- ChrSizesS288cH4L2_L2HG_edited.txt：酿酒酵母（S. cerevisiae）S288c菌株的染色体大小信息
- fail_fits：不同基因型与可变II型交叉互换占比、I型交叉互换失败率的模拟数据之间的柯尔莫哥洛夫-斯米尔诺夫（Kolmogorov-Smirnov）检验结果
- fail_sim：COsim的示例输出结果，用于绘制部分论文插图
- fail_sim_model_parameters.csv：针对人工合成交叉互换分布拟合伽马模型的结果
- gamma_sampling_simplemix.csv：对采样得到的伽马分布进行混合伽马模型检验的结果
- ICDs_calc_CO+NCO.csv：基于文件SK1_Crawford&Llorente_MasterEventTable1500NEW.csv计算得到的交叉互换与非交叉互换的间隔距离
- ICDs_calc_NCO.csv：基于文件SK1_Crawford&Llorente_MasterEventTable1500NEW.csv计算得到的非交叉互换间隔距离
- ICDs_calc_YJM_CO+NCO.csv：基于文件YJM_Fung&Mancera_MasterEventTable1500NEW.txt计算得到的交叉互换与非交叉互换的间隔距离
- ICDs_calc_YJM_NCO.csv：基于文件YJM_Fung&Mancera_MasterEventTable1500NEW.txt计算得到的非交叉互换间隔距离
- ICDs_calc_YJM.csv：基于文件YJM_Fung&Mancera_MasterEventTable1500NEW.txt计算得到的交叉互换间隔距离
- ICDs_calc.csv：基于文件SK1_Crawford&Llorente_MasterEventTable1500NEW.csv计算得到的交叉互换间隔距离
- IF_3_scale_380_105CO：模拟器生成的示例模拟间隔距离数据，包含105个交叉互换位点以匹配SK1 msh2菌株的数据
- minority_models：针对两类独立且具有干涉效应的交叉互换的模拟数据拟合伽马模型的结果
- Pan.Hotspots.IGR.SacCer3_2016.08.10.txt：Pan等人2011年发表的双链断裂（double-strand break, DSB）热点数据，用作评估交叉互换与非交叉互换周围多态性密度的对照数据集
- polymorphism_density：交叉互换与非交叉互换周围多态性密度的检验结果
- shape_fits：在生物数据上测试改变干涉强度与II型交叉互换占比的模拟实验的结果
- shape_sim：允许改变干涉强度与II型交叉互换占比的示例模拟数据
- shape_sim_model_parameters.csv：针对允许改变干涉强度与II型交叉互换占比的模拟数据拟合伽马模型的结果
- SK1_Crawford&Llorente_MasterEventTable1500NEW.csv：SK1菌株的交叉互换与非交叉互换位点信息（Crawford等人2024年研究）
- VariantTable_SK1.txt：SK1菌株与S288c酿酒酵母背景之间的多态性位点列表
- YJM_Fung&Mancera_MasterEventTable1500NEW.txt：YJM菌株的交叉互换与非交叉互换位点信息（Mancera等人2008年研究）
- zip3_event_fits：针对zip3缺失型生物数据的模拟检验结果
- zip3_microscopy：经zip1与zip3染色的细胞图像处理得到的数据

### 输出文件夹
该文件夹内的每个文件对应本研究的一幅独立插图。运行Figures_script、Migration_testing与Density_COs_DSBs脚本即可复现这些文件。