NAToRA, a relatedness-pruning method to minimize the loss of dataset size in genetic and omics analyses.

Genetic and omics analyses frequently require independent observations, which is not guaranteed in real datasets. When relatedness cannot be accounted for, solutions involve removing related individuals (or observations) and, consequently, a reduction of available data. We developed a network-based relatedness-pruning method that minimizes dataset reduction while removing unwanted relationships in a dataset. It uses node degree centrality metric to identify highly connected nodes (or individuals) and implements heuristics that approximate the minimal reduction of a dataset to allow its application to complex datasets. When compared with two other popular population genetics methodologies (PLINK and KING), NAToRA shows the best combination of removing all relatives while keeping the largest possible number of individuals in all datasets tested and also, with similar effects on the allele frequency spectrum and Principal Component Analysis than PLINK and KING. NAToRA is freely available, both as a standalone tool that can be easily incorporated as part of a pipeline, and as a graphical web tool that allows visualization of the relatedness networks. NAToRA also accepts a variety of relationship metrics as input, which facilitates its use. We also release a genealogies simulator software used for different tests performed in this study.

Human-SARS-CoV-2 interactome and human genetic diversity: TMPRSS2-rs2070788, associated with severe influenza, and its population genetics caveats in Native Americans.

For human/SARS-CoV-2 interactome genes ACE2, TMPRSS2 and BSG, there is a convincing evidence of association in Asians with influenza-induced SARS for TMPRSS2-rs2070788, tag-SNP of the eQTL rs383510. This case illustrates the importance of population genetics and of sequencing data in the design of genetic association studies in different human populations: the high linkage disequilibrium (LD) between rs2070788 and rs383510 is Asian-specific. Leveraging on a combination of genotyping and sequencing data for Native Americans (neglected in genetic studies), we show that while their frequencies of the Asian tag-SNP rs2070788 is, surprisingly, the highest worldwide, it is not in LD with the eQTL rs383510, that therefore, should be directly genotyped in genetic association studies of SARS in populations with Native American ancestry.