Biodiversity Institute and Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, USA.
California Academy of Sciences, San Francisco, California, USA.
Mol Ecol Resour. 2022 Apr;22(3):1100-1119. doi: 10.1111/1755-0998.13517. Epub 2021 Oct 12.
Despite the prevalence of high-throughput sequencing in phylogenetics, many relationships remain difficult to resolve because of conflicting signal among genomic regions. Selection of different types of molecular markers from different genomic regions is required to overcome these challenges. For evolutionary studies in frogs, we introduce the publicly available FrogCap suite of genomic resources, which is a large collection of ~15,000 markers that unifies previous genetic sequencing efforts. FrogCap is designed to be modular, such that subsets of markers and SNPs can be selected based on the desired phylogenetic scale. FrogCap uses a variety of marker types that include exons and introns, ultraconserved elements, and previously sequenced Sanger markers, which span up to 10,000 bp in alignment lengths; in addition, we demonstrate potential for SNP-based analyses. We tested FrogCap using 121 samples distributed across five phylogenetic scales, comparing probes designed using a consensus- or exemplar genome-based approach. Using the consensus design is more resilient to issues with sensitivity, specificity, and missing data than picking an exemplar genome sequence. We also tested the impact of different bait kit sizes (20,020 vs. 40,040) on depth of coverage and found triple the depth for the 20,020 bait kit. We observed sequence capture success (i.e., missing data, sequenced markers/bases, marker length, and informative sites) across phylogenetic scales. The incorporation of different marker types is effective for deep phylogenetic relationships and shallow population genetics studies. Having demonstrated FrogCap's utility and modularity, we conclude that these new resources are efficacious for high-throughput sequencing projects across variable timescales.
尽管高通量测序在系统发育学中很普遍,但由于基因组区域之间存在冲突的信号,许多关系仍然难以解决。需要从不同的基因组区域选择不同类型的分子标记,以克服这些挑战。对于青蛙的进化研究,我们引入了公开可用的 FrogCap 基因组资源套件,这是一个包含约 15000 个标记的大型集合,统一了以前的遗传测序工作。FrogCap 被设计为模块化的,因此可以根据所需的系统发育尺度选择标记和 SNP 的子集。FrogCap 使用多种标记类型,包括外显子和内含子、超保守元件和以前测序的 Sanger 标记,这些标记在比对长度上可达 10000bp;此外,我们还展示了基于 SNP 分析的潜力。我们使用分布在五个系统发育尺度上的 121 个样本测试了 FrogCap,比较了基于共识或范例基因组的探针设计。与选择范例基因组序列相比,使用共识设计对灵敏度、特异性和缺失数据的问题更具弹性。我们还测试了不同诱饵试剂盒大小(20020 与 40040)对覆盖深度的影响,发现 20020 诱饵试剂盒的深度是前者的三倍。我们观察到不同系统发育尺度上的序列捕获成功率(即缺失数据、测序标记/碱基、标记长度和信息位点)。不同标记类型的结合对于深入的系统发育关系和浅层的群体遗传学研究是有效的。证明了 FrogCap 的实用性和模块化之后,我们得出结论,这些新资源对于跨越不同时间尺度的高通量测序项目是有效的。