Genetic Variation in Human Gene Regulatory Factors Uncovers Regulatory Roles in Local Adaptation and Disease

Abstract

Differences in gene regulation have been suggested to play essential roles in the evolution of phenotypic changes. Although DNA changes in cis-regulatory elements affect only the regulation of its corresponding gene, variations in gene regulatory factors (trans) can have a broader effect, because the expression of many target genes might be affected. Aiming to better understand how natural selection may have shaped the diversity of gene regulatory factors in human, we assembled a catalog of all proteins involved in controlling gene expression. We found that at least five DNA-binding transcription factor classes are enriched among genes located in candidate regions for selection, suggesting that they might be relevant for understanding regulatory mechanisms involved in human local adaptation. The class of KRAB-ZNFs, zinc-finger (ZNF) genes with a Krüppel-associated box, stands out by first, having the most genes located on candidate regions for positive selection. Second, displaying most nonsynonymous single nucleotide polymorphisms (SNPs) with high genetic differentiation between populations within these regions. Third, having 27 KRAB-ZNF gene clusters with high extended haplotype homozygosity. Our further characterization of nonsynonymous SNPs in ZNF genes located within candidate regions for selection, suggests regulatory modifications that might influence the expression of target genes at population level. Our detailed investigation of three candidate regions revealed possible explanations for how SNPs may influence the prevalence of schizophrenia, eye development, and fertility in humans, among other phenotypes. The genetic variation we characterized here may be responsible for subtle to rough regulatory changes that could be important for understanding human adaptation.

Whole transcriptomic network analysis using Co-expression Differential Network Analysis (CoDiNA)

“…To this end, we calculated the wTO network [ 54 – 56 ] of the TFs for each tumor. We computed the wTO network for each cancer dataset and the controls separately using only the set of 3, 229 unique TF symbols from the Gene Regulatory Factors (GRF)-Catalogue [ 12 , 57 ], filtered by genes with proteins that also are included in the ENSEMBL protein dataset. For that, wTO package was used, similarly to the previous example, using the same parameters: Pearson Correlation and a 1000 bootstraps.…”

Functional Genomics Analysis to Disentangle the Role of Genetic Variants in Major Depression

“…This study aims to unravel the role of MD GVs in genetic regulation by focusing on regulatory variation following two complementary approaches: cis-eQTLs and TF binding alterations. Both are key to identifying potentially causal genes and understanding gene expression regulation [ 6 , 8 ], as reported by supporting evidence for its association with other mental disorders [ 53 , 54 , 55 ] and with MD in particular [ 56 , 57 , 58 ]. The regulatory variation analysis pipelines we have implemented involve fine-mapping, cis-eQTL colocalization, transcription factor binding analysis, and chromatin accessibility data, specially designed to perform well when full-genome summary statistics are not available [ 59 ].…”

“…A necessary step forward to disentangle the role of GVs identified in GWAS requires the evaluation of functional regulatory variation. Here, we have pursued two complementary analytical approaches geared toward the use of index GVs: (1) identification of candidate susceptibility genes using expression quantitative trait loci in cis (cis-eQTLs), which are enriched among disease-associated loci [ 6 ], and (2) characterization of transcription factor (TF) binding sites modified by GVs, which are key to understanding their potential impact on regulatory mechanisms [ 6 , 7 , 8 ].…”

Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution

“…Starting with the list of Ensembl IDs of human GRFs (Supplementary Data 1 from Perdomo-Sabogal and Nowick, 2019), the orthologous coding sequences from 27 primate genomes, including human, available at Ensembl/Compara (Vilella et al, 2009) and NCBI GenBank were downloaded using biomaRt (Durinck et al, 2005) and rentrez (Winter, 2017) R packages. Thus all gene sequences were from the Ensembl release 100 1 (Yates et al, 2020) and NCBI GenBank Release 237 2 , both from April 2020.…”

“…There are several lists or databases that compile regulatory factors (e.g., Ravasi et al, 2010;Tripathi et al, 2013;Lambert et al, 2018). For this study we chose 3,344 genes from a published human GRF catalog (Perdomo-Sabogal and Nowick, 2019), which we consider to be the most comprehensive GRF catalog to date. Interestingly, positive selection of some of the GRFs from that catalog has been previously proposed among primate species (for instance, 3 of 36 genes in Nielsen et al, 2005; 35 of 187 genes in Su et al, 2016), albeit with fewer species included in the analyses, and at population level within humans (Perdomo-Sabogal and Nowick, 2019).…”