Optimized double-digest genotyping by sequencing (ddGBS) method with high-density SNP markers and high genotyping accuracy for chickens
收藏Figshare2017-06-10 更新2026-04-29 收录
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https://figshare.com/articles/dataset/Optimized_double-digest_genotyping_by_sequencing_ddGBS_method_with_high-density_SNP_markers_and_high_genotyping_accuracy_for_chickens/5098360
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High-density single nucleotide polymorphism (SNP) markers are crucial to improve the resolution and accuracy of genome-wide association study (GWAS) and genomic selection (GS). Numerous approaches, including whole genome sequencing, genome sampling sequencing, and SNP chips are able to discover or genotype markers at different densities and costs. Achieving an optimal balance between sequencing resolution and budgets, especially in large-scale population genetics research, constitutes a major challenge. Here, we performed improved double-enzyme digestion genotyping by sequencing (ddGBS) on chicken. We evaluated eight double-enzyme digestion combinations, and EcoR I- Mse I was chosen as the optimal combination for the chicken genome. We firstly proposed that two parameters, optimal read-count point (ORP) and saturated read-count point (SRP), could be utilized to determine the optimal sequencing volume. A total of 291,772 high-density SNPs from 824 animals were identified. By validation using the SNP chip, we found that the consistency between ddGBS data and the SNP chip is over 99%. The approach that we developed in chickens, which is high-quality, high-density, cost-effective (300 K, $30/sample), and time-saving (within 48 h), will have broad applications in animal breeding programs.
高密度单核苷酸多态性(single nucleotide polymorphism,SNP)标记对于提升全基因组关联分析(genome-wide association study,GWAS)和基因组选择(genomic selection,GS)的分辨率与准确性至关重要。目前已有多种方法可实现不同密度、不同成本下的标记发掘与基因分型,包括全基因组测序(whole genome sequencing)、基因组抽样测序(genome sampling sequencing)以及SNP芯片(SNP chip)。在测序分辨率与预算之间实现最优平衡,尤其是在大规模群体遗传学研究中,仍是一项重大挑战。
本研究针对鸡开展了改进型双酶切测序分型(double-enzyme digestion genotyping by sequencing,ddGBS)实验,共评估了8种双酶切组合,最终选定EcoR I-Mse I作为适配鸡基因组的最优酶切组合。本研究首次提出可通过最优读取计数点(optimal read-count point,ORP)与饱和读取计数点(saturated read-count point,SRP)两个参数,确定最优测序量。本研究共从824份鸡样本中鉴定出291,772个高密度SNP标记;通过SNP芯片验证发现,ddGBS数据与SNP芯片数据的一致性超过99%。
本研究在鸡中开发的这套方法兼具高质量、高密度、高性价比(单样本30美元,覆盖300K位点)且耗时短(48小时内完成)的优势,将在动物育种项目中拥有广阔的应用前景。
创建时间:
2017-06-10



