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. KEYWORDS genome; homology; Caenorhabditis elegans; human S TUDIES in Caenorhabditis elegans have illuminated many mechanisms relevant to human biology and disease. Forward genetic screens based on phenotype have identified genes homologous to human disease-associated genes, illuminating fundamental properties about their roles and mechanisms of action (e.g., Greenwald 2012; Sundaram 2013; Golden 2017; van der Bliek et al. 2017). Reverse genetic methods have expanded the repertoire of possible genetic approaches. These methods include the ability to phenocopy loss-of-function mutations by feeding worms bacteria expressing double-stranded RNA (Fire et al. 1998; Timmons and Fire 1998). The efficiency of RNA interference (RNAi) in C. elegans has allowed for genome-wide screens (Fraser et al. 2000; Kamath et al. 2003; O'Reilly et al. 2016), or screens targeted to specific conserved genes, such as human disease genes (e.g., Sin et al. 2014; Vahdati Nia et al. 2017; Nordquist et al. 2018) or those involved in fundamental biological processes (e.g., Balklava et al. 2007; Dunn et al. 2010; Firnhaber and Hammarlund 2013; Allen et al. 2014; Du et al. 2015). Other...