OrthoList 2: A New Comparative Genomic Analysis of Human and Caenorhabditis elegans Genes
OrthoList 2: A New Comparative Genomic Analysis of Human and Caenorhabditis elegans Genes
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DOI：
10.1534/genetics.118.301307
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发表时间：
2018-10-01
期刊：
影响因子：
3.3
通讯作者：
Shaye, Daniel D.
中科院分区：
文献类型：
--
作者：
Kim, Woojin;Underwood, Ryan S.;Shaye, Daniel D.
OrthoList是2011年通过对四种正畸预测方法的荟萃分析编制的秀丽线虫基因与人类同源物的概要，一直是识别保守基因的流行工具，用于生物学和疾病机制的研究。然而，正畸预测的有效性取决于基因模型预测的准确性，这是一个持续的过程，而且正畸预测算法也随着时间的推移而更新。在这里，我们提出了OrthoList 2(OL2)，这是一种新的线虫和人类之间的比较基因组分析，并首次评估了随着时间的变化如何影响两个物种之间预测的直系物的景观。尽管我们发现，正交学预测方法的更新显著改变了单个程序预测的线虫-人类同源物的图景，并且-出人意料地-减少了它们之间的一致性，但我们也表明，我们的荟萃分析方法对基因含量的变化具有缓冲作用。我们表明，添加来自更多程序的结果并不会导致列表中增加许多结果，并讨论了避免基于单个正畸预测程序的支持来分配“分数”的原因；这些程序不再预测的“遗留”基因的处理；以及由于遇到不建议使用、更改或停用的基因识别符而更新的实际困难。此外，我们还考虑了哪些其他标准可以支持矫形学的主张，以及寻找潜在的直系同源基因的替代方法，这些潜在的直系同源基因无法通过这些程序进行识别。最后，我们创建了一个新的基于网络的工具，允许通过基因识别符、蛋白质结构域[InterPro和SMART(简单模块化结构研究工具)或人类疾病关联[OMIM(人类在线孟德尔遗传)]快速搜索OL2，还包括可用的RNA干扰资源，以促进潜在的跨物种翻译研究。
OrthoList, a compendium of Caenorhabditis elegans genes with human orthologs compiled in 2011 by a meta-analysis of four orthology-prediction methods, has been a popular tool for identifying conserved genes for research into biological and disease mechanisms. However, the efficacy of orthology prediction depends on the accuracy of gene-model predictions, an ongoing process, and orthology-prediction algorithms have also been updated over time. Here we present OrthoList 2 (OL2), a new comparative genomic analysis between C. elegans and humans, and the first assessment of how changes over time affect the landscape of predicted orthologs between two species. Although we find that updates to the orthology-prediction methods significantly changed the landscape of C. elegans-human orthologs predicted by individual programs and-unexpectedly-reduced agreement among them, we also show that our meta-analysis approach "buffered" against changes in gene content. We show that adding results from more programs did not lead to many additions to the list and discuss reasons to avoid assigning "scores" based on support by individual orthology-prediction programs; the treatment of "legacy" genes no longer predicted by these programs; and the practical difficulties of updating due to encountering deprecated, changed, or retired gene identifiers. In addition, we consider what other criteria may support claims of orthology and alternative approaches to find potential orthologs that elude identification by these programs. Finally, we created a new web-based tool that allows for rapid searches of OL2 by gene identifiers, protein domains [InterPro and SMART (Simple Modular Architecture Research Tool], or human disease associations ([OMIM (Online Mendelian Inheritence in Man], and also includes available RNA-interference resources to facilitate potential translational cross-species studies.