Iguanian lizards Raw sequence reads

Targeted sequence capture is becoming a widespread tool for generating large phylogenomic datasets to address difficult phylogenetic problems. However, this methodology often generates datasets in which increasing the number of taxa and loci increases amounts of missing data. Thus, a fundamental (but still unresolved) question is whether sampling should be designed to maximize sampling of taxa or genes, or minimize the inclusion of missing data cells. Here, we explore this question for an ancient, rapid radiation of lizards, the pleurodont iguanians. Pleurodonts include many well-known clades (e.g. anoles, basilisks, iguanas, spiny lizards) but relationships among pleurodont families have proven difficult to resolve strongly and consistently using traditional sequencing approaches. We generated up to 4,921 ultraconserved elements with sampling strategies including 16, 29, and 44 taxa, from 1,179 to ~2.4 million characters, and ~30% to 60% total missing data.

靶向序列捕获（targeted sequence capture）正成为构建大型系统发育组数据集以解决疑难系统发育问题的通用工具。然而，该方法常导致其产出的数据集存在如下固有问题：随着类群（taxa）与基因座（loci）数量的增加，缺失数据的占比也会随之升高。因此，一个核心但尚未解决的科学问题是：采样策略应当优先最大化类群或基因的采样量，还是尽可能减少缺失数据单元格的占比。本研究针对一类古老且经历快速辐射演化的蜥蜴类群——侧齿鬣蜥类（pleurodont iguanians），探讨了这一问题。侧齿鬣蜥类包含多个广为人知的演化支（clade），例如安乐蜥、蛇怪蜥、鬣蜥与棘蜥，但采用传统测序方法，难以强力且一致地解析该类群各科之间的系统发育关系。本研究通过设置16、29和44个分类单元的三种采样策略，构建了最多4921个超保守元件（ultraconserved elements），对应序列长度范围为1179至约240万个字符，总缺失数据占比介于30%至60%之间。