Variant Calls for the Inbred Nachman Mouse Strains

SNV calling: Reads were mapped to the GRCm39 reference sequence using minimap2 invoking the “HIFI” preset. Per sample single nucleotide calling was performed using DeepVariant (v1.2.0) under the “PACBIO” model. Per sample gVCF files were then merged using glnexus (v1.2.7) under the DeepVariantWGS configuration to produce a joint call set. Sites with missing data, genotype quality <30, and indels were subsequently filtered using bcftools (v 0.1.19). We further eliminated sites with heterozygous calls as these sites are potentially enriched for false positives given our modest sequencing coverage. Variant effects were predicted using the Variant Effect Predictor (Ensembl release 109.3) using the GRCm39 Mus musculus assembly. Unfiltered SNV calls: hifi.deepvariant.jointGenotyping.vcf.gz Filtered and annotated SNV calls: hifi.deepvariant.jointGenotyping.filtered.vep.vcf.gz SV calling: We identified SVs in the Nachman wild-derived inbred strain genomes using both pbsv (https://github.com/PacificBiosciences/pbsv) and sniffles2 (v. 2.0.7). pbsv was first run on each sample in discover mode to identify read signatures consistent with possible SVs. SVs where then called and samples jointly genotyped by executing pbsv in call mode. Tandem repeats in the GRCm39 assembly were identified using the findTandemRepeats.py script (https://github.com/PacificBiosciences/pbsv/commit/bcec7d382f3ea40158ed9cca3c5fef9686a76641) and supplied when executing sniffles2 to improve the accuracy of calls in repetitive regions. Per sample SV calls generated by sniffles2 were merged and filtered to include only autosomal calls using bcftools merge (v. 0.1.19). Calls with close or overlapping breakpoints across samples were collapsed using truvari (v4.0.0), with the following parameters specified: -pctsize 0.75 –pctovl 0.5 –pctseq 0.7 -s 20 -S 10000000 -k common --chain. We then intersected pbsv and sniffles2 SV calls using truvari bench to produce a higher confidence call set. We used the pbsv callset as the “truth” set and invoked the following command line parameters: -pctsize 0.75 –pctovl 0.5 –pctseq 0.7 –dup-to-ins –passonly -sizemin 20. SVs were annotated using the Ensembl Variant Effect Predictor (release 109.3) and gene model annotations from the GRCm39 assembly. pbsv calls: NachmanInbred.pbsv.filtered.vcf.gz sniffles2 SV calls: NachmanSV.sniffles.vcf.gz pbsv - sniffles2 merged SV calls, with VEP annotations: Nachman.pbsv.sniffles.mergeSet.vep.vcf.gz单核苷酸变异（SNV, Single Nucleotide Variant）调用： 测序读段通过minimap2并启用“HIFI”预设模式，比对至GRCm39参考基因组序列。采用DeepVariant（v1.2.0）在“PACBIO”模型下对每个样本进行单核苷酸变异调用。随后使用glnexus（v1.2.7）以DeepVariantWGS配置合并各样本的gVCF（基因组变异调用格式，genomic Variant Call Format）文件，生成联合变异调用集。使用bcftools（v0.1.19）过滤掉存在数据缺失、基因型质量值低于30以及插入缺失（Indel, Insertion/Deletion）的位点。由于本次测序覆盖度有限，杂合基因型位点可能富集假阳性结果，因此进一步移除所有杂合调用位点。变异效应预测通过变异效应预测器（Variant Effect Predictor，Ensembl版本109.3）完成，所用基因组组装版本为GRCm39小家鼠（Mus musculus）参考序列。 未过滤的SNV调用结果：hifi.deepvariant.jointGenotyping.vcf.gz 过滤并注释的SNV调用结果：hifi.deepvariant.jointGenotyping.filtered.vep.vcf.gz 结构变异（SV, Structural Variant）调用： 本研究针对Nachman野生来源近交系菌株的基因组，分别采用pbsv和sniffles2（v2.0.7）两种工具鉴定结构变异。首先以发现模式（discover mode）对每个样本运行pbsv，以识别与潜在结构变异相符的读段特征；随后以调用模式（call mode）运行pbsv，完成结构变异调用并对所有样本进行联合基因分型。使用findTandemRepeats.py脚本（来源：https://github.com/PacificBiosciences/pbsv/commit/bcec7d382f3ea40158ed9cca3c5fef9686a76641）鉴定GRCm39参考组装版本中的串联重复序列，并在运行sniffles2时提供该注释信息，以提升重复区域的变异调用准确性。使用bcftools merge（v0.1.19）合并sniffles2生成的各样本结构变异调用结果，并过滤仅保留常染色体上的变异位点。使用truvari（v4.0.0）对跨样本的断点相近或重叠的变异调用进行聚类合并，指定参数为：-pctsize 0.75 –pctovl 0.5 –pctseq 0.7 -s 20 -S 10000000 -k common --chain。随后通过truvari bench工具对pbsv和sniffles2的结构变异调用结果取交集，以生成更高置信度的联合调用集，其中以pbsv调用集作为“真值集”，并使用以下命令行参数：-pctsize 0.75 –pctovl 0.5 –pctseq 0.7 –dup-to-ins –passonly -sizemin 20。采用Ensembl变异效应预测器（版本109.3）及GRCm39参考组装的基因模型注释信息，完成结构变异的注释。 pbsv调用结果：NachmanInbred.pbsv.filtered.vcf.gz sniffles2 SV调用结果：NachmanSV.sniffles.vcf.gz pbsv - sniffles2合并SV调用结果（含VEP注释）：Nachman.pbsv.sniffles.mergeSet.vep.vcf.gz