Cole T Jeffrey, Brewer Michael S
Department of Biology, East Carolina University, Greenville, NC, United States of America.
PeerJ. 2018 Jan 17;6:e4234. doi: 10.7717/peerj.4234. eCollection 2018.
The recent proliferation of large amounts of biodiversity transcriptomic data has resulted in an ever-expanding need for scalable and user-friendly tools capable of answering large scale molecular evolution questions. FUSTr identifies gene families involved in the process of adaptation. This is a tool that finds genes in transcriptomic datasets under strong positive selection that automatically detects isoform designation patterns in transcriptome assemblies to maximize phylogenetic independence in downstream analysis.
When applied to previously studied spider transcriptomic data as well as simulated data, FUSTr successfully grouped coding sequences into proper gene families as well as correctly identified those under strong positive selection in relatively little time.
FUSTr provides a useful tool for novice bioinformaticians to characterize the molecular evolution of organisms throughout the tree of life using large transcriptomic biodiversity datasets and can utilize multi-processor high-performance computational facilities.
近期大量生物多样性转录组数据的激增，导致对能够回答大规模分子进化问题的可扩展且用户友好的工具的需求不断增加。FUSTr可识别参与适应过程的基因家族。该工具能在转录组数据集中找到处于强正选择下的基因，自动检测转录组组装中的异构体指定模式，以在下游分析中最大化系统发育独立性。
当应用于先前研究的蜘蛛转录组数据以及模拟数据时，FUSTr在相对较短的时间内成功将编码序列分组到合适的基因家族中，并正确识别出处于强正选择下的序列。
FUSTr为新手生物信息学家提供了一个有用的工具，可利用大型转录组生物多样性数据集来表征整个生命之树中生物体的分子进化，并且可以利用多处理器高性能计算设施。
