Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.
Determining the full complement of protein-coding genes is a key goal of genome annotation. The most powerful approach for confirming protein-coding potential is the detection of cellular protein expression through peptide mass spectrometry (MS) experiments. Here, we mapped peptides detected in seven large-scale proteomics studies to almost 60% of the protein-coding genes in the GENCODE annotation of the human genome. We found a strong relationship between detection in proteomics experiments and both gene family age and cross-species conservation. Most of the genes for which we detected peptides were highly conserved. We found peptides for >96% of genes that evolved before bilateria. At the opposite end of the scale, we identified almost no peptides for genes that have appeared since primates, for genes that did not have any protein-like features or for genes with poor cross-species conservation. These results motivated us to describe a set of 2001 potential non-coding genes based on features such as weak conservation, a lack of protein features, or ambiguous annotations from major databases, all of which correlated with low peptide detection across the seven experiments. We identified peptides for just 3% of these genes. We show that many of these genes behave more like non-coding genes than protein-coding genes and suggest that most are unlikely to code for proteins under normal circumstances. We believe that their inclusion in the human protein-coding gene catalogue should be revised as part of the ongoing human genome annotation effort.
The Zoonomia Project is investigating the genomics of shared and specialized traits in eutherian mammals. Here we provide genome assemblies for 131 species, of which all but 9 are previously uncharacterized, and describe a whole-genome alignment of 240 species of considerable phylogenetic diversity, comprising representatives from more than 80% of mammalian families. We find that regions of reduced genetic diversity are more abundant in species at a high risk of extinction, discern signals of evolutionary selection at high resolution and provide insights from individual reference genomes. By prioritizing phylogenetic diversity and making data available quickly and without restriction, the Zoonomia Project aims to support biological discovery, medical research and the conservation of biodiversity.
INTRODUCTION: Improved understanding of how the developing human nervous system differs from that of closely related nonhuman primates is fundamental for teasing out human-specific aspects of behavior, cognition, and disorders. RATIONALE: The shared and unique functional properties of the human nervous system are rooted in the complex transcriptional programs governing the development of distinct cell types, neural circuits, and regions. However, the precise molecular mechanisms underlying shared and unique features of the developing human nervous system have been only minimally characterized. RESULTS: We generated complementary tissue-level and single-cell transcriptomic datasets from up to 16 brain regions covering prenatal and postnatal development in humans and rhesus macaques ( Macaca mulatta ), a closely related species and the most commonly studied nonhuman primate. We created and applied TranscriptomeAge and TempShift algorithms to age-match developing specimens between the species and to more rigorously identify temporal differences in gene expression within and across the species. By analyzing regional and temporal patterns of gene expression in both the developing human and macaque brain, and comparing these patterns to a complementary dataset that included transcriptomic information from the adult chimpanzee, we identified shared and divergent transcriptomic features of human brain development. Furthermore, integration with single-cell and single-nucleus transcriptomic data covering prenatal and adult periods of both species revealed that the developmental divergence between humans and macaques can be traced to distinct cell types enriched in different developmental times and brain regions, including the prefrontal cortex, a region of the brain associated with distinctly human aspects of cognition and behavior. We found two phases of prominent species differences: embryonic to late midfetal development and adolescence/young adulthood. This evolutionary cup-shaped or hourglass-like pattern, with high divergence in prenatal development and adolescence/young adulthood and lower divergence in early postnatal development, resembles the developmental cup-shaped pattern described in the accompanying study by Li et al . Even though the developmental (ontogenetic) and evolutionary (phylogenetic) patterns have similar profiles, the overlap of genes driving these two patterns is not substantial, indicating the existence of different molecular mechanisms and constraints for regional specification and species divergence. Notably, we also identified numerous genes and gene coexpression modules exhibiting human-distinct patterns in either temporal (heterochronic) or spatial (heterotopic) gene expression, as well as genes with human-distinct developmental expression, linked to autism spectrum disorder, schizophrenia, and other neurological or psychiatric diseases. This finding potentially suggests mechanistic underpinnings of these disorders. CONCLUSION: Our study provides insights into the evolution of gene expression in the developing human brain and may shed some light on potentially human-specific underpinnings of certain neuropsychiatric disorders. Concerted ontogenetic and phylogenetic transcriptomic divergence in human and macaque brain.: Left: Human and macaque brain regions spanning both prenatal and postnatal development were age-matched using TranscriptomeAge. Right: Phylogenetic transcriptomic divergence between humans and macaques resembles the developmental (ontogenetic) cup-shaped pattern of each species, with high divergence in prenatal development and adolescence/young adulthood and lower divergence during the early postnatal period (from perinatal to adolescence). Single-cell transcriptomics revealed shared and divergent transcriptomic features of distinct cell types.
The rich diversity of morphology and behavior displayed across primate species provides an informative context in which to study the impact of genomic diversity on fundamental biological processes. Analysis of that diversity provides insight into long-standing questions in evolutionary and conservation biology and is urgent given severe threats these species are facing. Here, we present high-coverage whole-genome data from 233 primate species representing 86% of genera and all 16 families. This dataset was used, together with fossil calibration, to create a nuclear DNA phylogeny and to reassess evolutionary divergence times among primate clades. We found within-species genetic diversity across families and geographic regions to be associated with climate and sociality, but not with extinction risk. Furthermore, mutation rates differ across species, potentially influenced by effective population sizes. Lastly, we identified extensive recurrence of missense mutations previously thought to be human specific. This study will open a wide range of research avenues for future primate genomic research.