GEneSTATION 1.0: A Synthetic Resource of Diverse Evolutionary and Functional Genomic Data for Studying The Evolution of Pregnancy-Associated Tissues and Phenotypes

Mammalian gestation and pregnancy are fast evolving processes that involve the interaction of the fetal, maternal and paternal genomes. Version 1.0 of the GEneSTATION database (http://genestation.org) integrates diverse types of omics data across mammals to advance understanding of the genetic basis of gestation and pregnancy-associated phenotypes and to accelerate the translation of discoveries from model organisms to humans. GEneSTATION is built using tools from the Generic Model Organism Database project, including the biology-aware database CHADO, new tools for rapid data integration, and algorithms that streamline synthesis and user access. GEneSTATION contains curated life history information on pregnancy and reproduction from 23 high-quality mammalian genomes. For every human gene, GEneSTATION contains diverse evolutionary (e.g. gene age, population genetic and molecular evolutionary statistics), organismal (e.g. tissue-specific gene and protein expression, differential gene expression, disease phenotype), and molecular data types (e.g. Gene Ontology Annotation, protein interactions), as well as links to many general (e.g. Entrez, PubMed) and pregnancy disease-specific (e.g. PTBgene, dbPTB) databases. By facilitating the synthesis of diverse functional and evolutionary data in pregnancy-associated tissues and phenotypes and enabling their quick, intuitive, accurate and customized meta-analysis, GEneSTATION provides a novel platform for comprehensive investigation of the function and evolution of mammalian pregnancy

Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.</p

Global Biobank Meta-analysis Initiative:Powering genetic discovery across human disease

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.</p

Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics

The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor—the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.publishedVersionPeer reviewe

Best practices for multi-ancestry, meta-analytic transcriptome-wide association studies: Lessons from the Global Biobank Meta-analysis Initiative.

The Global Biobank Meta-analysis Initiative (GBMI), through its diversity, provides a valuable opportunity to study population-wide and ancestry-specific genetic associations. However, with multiple ascertainment strategies and multi-ancestry study populations across biobanks, GBMI presents unique challenges in implementing statistical genetics methods. Transcriptome-wide association studies (TWASs) boost detection power for and provide biological context to genetic associations by integrating genetic variant-to-trait associations from genome-wide association studies (GWASs) with predictive models of gene expression. TWASs present unique challenges beyond GWASs, especially in a multi-biobank, meta-analytic setting. Here, we present the GBMI TWAS pipeline, outlining practical considerations for ancestry and tissue specificity, meta-analytic strategies, and open challenges at every step of the framework. We advise conducting ancestry-stratified TWASs using ancestry-specific expression models and meta-analyzing results using inverse-variance weighting, showing the least test statistic inflation. Our work provides a foundation for adding transcriptomic context to biobank-linked GWASs, allowing for ancestry-aware discovery to accelerate genomic medicine

Effects of Natural Selection and Gene Conversion on the Evolution of Human Glycophorins Coding for MNS Blood Polymorphisms in Malaria-Endemic African Populations

Malaria has been a very strong selection pressure in recent human evolution, particularly in Africa. Of the one million deaths per year due to malaria, more than 90% are in sub-Saharan Africa, a region with high levels of genetic variation and population substructure. However, there have been few studies of nucleotide variation at genetic loci that are relevant to malaria susceptibility across geographically and genetically diverse ethnic groups in Africa. Invasion of erythrocytes by Plasmodium falciparum parasites is central to the pathology of malaria. Glycophorin A (GYPA) and B (GYPB), which determine MN and Ss blood types, are two major receptors that are expressed on erythrocyte surfaces and interact with parasite ligands. We analyzed nucleotide diversity of the glycophorin gene family in 15 African populations with different levels of malaria exposure. High levels of nucleotide diversity and gene conversion were found at these genes. We observed divergent patterns of genetic variation between these duplicated genes and between different extracellular domains of GYPA. Specifically, we identified fixed adaptive changes at exons 3-4 of GYPA. By contrast, we observed an allele frequency spectrum skewed toward a significant excess of intermediate-frequency alleles at GYPA exon 2 in many populations; the degree of spectrum distortion is correlated with malaria exposure, possibly because of the joint effects of gene conversion and balancing selection. We also identified a haplotype causing three amino acid changes in the extracellular domain of glycophorin B. This haplotype might have evolved adaptively in five populations with high exposure to malaria

Genetic origins of lactase persistence and the spread of pastoralism in africa

In humans, the ability to digest lactose, the sugar in milk, declines after weaning because of decreasing levels of the enzyme lactase-phlorizin hydrolase, encoded by LCT. However, some individuals maintain high enzyme amounts and are able to digest lactose into adulthood (i.e., they have the lactase-persistence [LP] trait). It is thought that selection has played a major role in maintaining this genetically determined phenotypic trait in different human populations that practice pastoralism. To identify variants associated with the LP trait and to study its evolutionary history in Africa, we sequenced MCM6 introns 9 and 13 and ∼2 kb of the LCT promoter region in 819 individuals from 63 African populations and in 154 non-Africans from nine populations. We also genotyped four microsatellites in an ∼198 kb region in a subset of 252 individuals to reconstruct the origin and spread of LP-associated variants in Africa. Additionally, we examined the association between LP and genetic variability at candidate regulatory regions in 513 individuals from eastern Africa. Our analyses confirmed the association between the LP trait and three common variants in intron 13 (C-14010, G-13907, and G-13915). Furthermore, we identified two additional LP-associated SNPs in intron 13 and the promoter region (G-12962 and T-956, respectively). Using neutrality tests based on the allele frequency spectrum and long-range linkage disequilibrium, we detected strong signatures of recent positive selection in eastern African populations and the Fulani from central Africa. In addition, haplotype analysis supported an eastern African origin of the C-14010 LP-associated mutation in southern Africa

African evolutionary history inferred from whole genome sequence data of 44 indigenous African populations

Abstract Background Africa is the origin of modern humans within the past 300 thousand years. To infer the complex demographic history of African populations and adaptation to diverse environments, we sequenced the genomes of 92 individuals from 44 indigenous African populations. Results Genetic structure analyses indicate that among Africans, genetic ancestry is largely partitioned by geography and language, though we observe mixed ancestry in many individuals, consistent with both short- and long-range migration events followed by admixture. Phylogenetic analysis indicates that the San genetic lineage is basal to all modern human lineages. The San and Niger-Congo, Afroasiatic, and Nilo-Saharan lineages were substantially diverged by 160 kya (thousand years ago). In contrast, the San and Central African rainforest hunter-gatherer (CRHG), Hadza hunter-gatherer, and Sandawe hunter-gatherer lineages were diverged by ~ 120–100 kya. Niger-Congo, Nilo-Saharan, and Afroasiatic lineages diverged more recently by ~ 54–16 kya. Eastern and western CRHG lineages diverged by ~ 50–31 kya, and the western CRHG lineages diverged by ~ 18–12 kya. The San and CRHG populations maintained the largest effective population size compared to other populations prior to 60 kya. Further, we observed signatures of positive selection at genes involved in muscle development, bone synthesis, reproduction, immune function, energy metabolism, and cell signaling, which may contribute to local adaptation of African populations. Conclusions We observe high levels of genomic variation between ethnically diverse Africans which is largely correlated with geography and language. Our study indicates ancient population substructure and local adaptation of Africans