BACKGROUND Bulked segregant analysis (BSA), coupled with next-generation sequencing, allows the rapid identification of both qualitative and quantitative trait loci (QTL), and this technique is referred to as BSA-Seq here. The current SNP index method and G-statistic method for BSA-Seq data analysis require relatively high sequencing coverage to detect significant single nucleotide polymorphism (SNP)-trait associations, which leads to high sequencing cost. RESULTS We developed a simple and effective algorithm for BSA-Seq data analysis and implemented it in Python; the program was named PyBSASeq. Using PyBSASeq, the significant SNPs (sSNPs), SNPs likely associated with the trait, were identified via Fisher's exact test, and then the ratio of the sSNPs to total SNPs in a chromosomal interval was used to detect the genomic regions that condition the trait of interest. The results obtained this way are similar to those generated via the current methods, but with more than five times higher sensitivity. This approach was termed the significant SNP method here. CONCLUSIONS The significant SNP method allows the detection of SNP-trait associations at much lower sequencing coverage than the current methods, leading to ~ 80% lower sequencing cost and making BSA-Seq more accessible to the research community and more applicable to the species with a large genome.

中文翻译：

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PyBSASeq：一种简单有效的算法，可用于全基因组测序数据的大量分离物分析。

背景技术批量隔离分析（BSA）与下一代测序相结合，可以快速识别定性和定量性状基因座（QTL），在此将其称为BSA-Seq。当前用于BSA-Seq数据分析的SNP索引方法和G统计方法需要相对较高的测序覆盖率才能检测到显着的单核苷酸多态性（SNP）-性状关联，从而导致较高的测序成本。结果我们为BSA-Seq数据分析开发了一种简单有效的算法，并在Python中实现了该算法。该程序名为PyBSASeq。使用PyBSASeq，通过Fisher精确检验确定了重要的SNP（sSNP），即可能与该性状相关的SNP，然后使用染色体区间中sSNPs与总SNPs的比率来检测调节目标性状的基因组区域。用这种方法获得的结果与通过当前方法产生的结果相似，但灵敏度高出五倍以上。这种方法在这里被称为重要的SNP方法。结论重大的SNP方法可在比目前方法低得多的测序覆盖率下检测SNP-性状关联，从而使测序成本降低约80％，并使BSA-Seq更易于为研究社区所用，并且更适用于具有BSA-Seq的物种。大基因组。这种方法在这里被称为重要的SNP方法。结论重大的SNP方法可在比目前方法低得多的测序覆盖率下检测SNP-性状关联，从而使测序成本降低约80％，并使BSA-Seq更易于为研究社区所用，并且更适用于具有BSA-Seq的物种。大基因组。这种方法在这里被称为重要的SNP方法。结论重大的SNP方法可在比目前方法低得多的测序覆盖率下检测SNP-性状关联，从而使测序成本降低约80％，并使BSA-Seq更易于为研究社区所用，并且更适用于具有BSA-Seq的物种。大基因组。