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1. Leveraging base-pair mammalian constraint to understand genetic variation and human disease

   https://doi.org/10.1126/science.abn2937  

   Sullivan, Patrick F. ; Meadows, Jennifer R. ; Gazal, Steven ; Phan, BaDoi N. ; Li, Xue ; Genereux, Diane P. ; Dong, Michael X. ; Bianchi, Matteo ; Andrews, Gregory ; Sakthikumar, Sharadha ; et al ( April 2023 , Science)

   INTRODUCTION Thousands of genetic variants have been associated with human diseases and traits through genome-wide association studies (GWASs). Translating these discoveries into improved therapeutics requires discerning which variants among hundreds of candidates are causally related to disease risk. To date, only a handful of causal variants have been confirmed. Here, we leverage 100 million years of mammalian evolution to address this major challenge. RATIONALE We compared genomes from hundreds of mammals and identified bases with unusually few variants (evolutionarily constrained). Constraint is a measure of functional importance that is agnostic to cell type or developmental stage. It can be applied to investigate any heritable disease or trait and is complementary to resources using cell type– and time point–specific functional assays like Encyclopedia of DNA Elements (ENCODE) and Genotype-Tissue Expression (GTEx). RESULTS Using constraint calculated across placental mammals, 3.3% of bases in the human genome are significantly constrained, including 57.6% of coding bases. Most constrained bases (80.7%) are noncoding. Common variants (allele frequency ≥ 5%) and low-frequency variants (0.5% ≤ allele frequency < 5%) are depleted for constrained bases (1.85 versus 3.26% expected by chance, P < 2.2 × 10 −308 ). Pathogenic ClinVar variants are more constrained than benign variants ( P < 2.2 × 10 −16 ). The most constrained common variants are more enriched for disease single-nucleotide polymorphism (SNP)–heritability in 63 independent GWASs. The enrichment of SNP-heritability in constrained regions is greater (7.8-fold) than previously reported in mammals and is even higher in primates (11.1-fold). It exceeds the enrichment of SNP-heritability in nonsynonymous coding variants (7.2-fold) and fine-mapped expression quantitative trait loci (eQTL)–SNPs (4.8-fold). The enrichment peaks near constrained bases, with a log-linear decrease of SNP-heritability enrichment as a function of the distance to a constrained base. Zoonomia constraint scores improve functionally informed fine-mapping. Variants at sites constrained in mammals and primates have greater posterior inclusion probabilities and higher per-SNP contributions. In addition, using both constraint and functional annotations improves polygenic risk score accuracy across a range of traits. Finally, incorporating constraint information into the analysis of noncoding somatic variants in medulloblastomas identifies new candidate driver genes. CONCLUSION Genome-wide measures of evolutionary constraint can help discern which variants are functionally important. This information may accelerate the translation of genomic discoveries into the biological, clinical, and therapeutic knowledge that is required to understand and treat human disease. Using evolutionary constraint in genomic studies of human diseases. ( A ) Constraint was calculated across 240 mammal species, including 43 primates (teal line). ( B ) Pathogenic ClinVar variants ( N = 73,885) are more constrained across mammals than benign variants ( N = 231,642; P < 2.2 × 10 −16 ). ( C ) More-constrained bases are more enriched for trait-associated variants (63 GWASs). ( D ) Enrichment of heritability is higher in constrained regions than in functional annotations (left), even in a joint model with 106 annotations (right). ( E ) Fine-mapping (PolyFun) using a model that includes constraint scores identifies an experimentally validated association at rs1421085. Error bars represent 95% confidence intervals. BMI, body mass index; LF, low frequency; PIP, posterior inclusion probability. 

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2. A genomic timescale for placental mammal evolution

   https://doi.org/10.1126/science.abl8189  

   Foley, Nicole M. ; Mason, Victor C. ; Harris, Andrew J. ; Bredemeyer, Kevin R. ; Damas, Joana ; Lewin, Harris A. ; Eizirik, Eduardo ; Gatesy, John ; Karlsson, Elinor K. ; Lindblad-Toh, Kerstin ; et al ( April 2023 , Science)

   INTRODUCTION Resolving the role that different environmental forces may have played in the apparent explosive diversification of modern placental mammals is crucial to understanding the evolutionary context of their living and extinct morphological and genomic diversity. RATIONALE Limited access to whole-genome sequence alignments that sample living mammalian biodiversity has hampered phylogenomic inference, which until now has been limited to relatively small, highly constrained sequence matrices often representing <2% of a typical mammalian genome. To eliminate this sampling bias, we used an alignment of 241 whole genomes to comprehensively identify and rigorously analyze noncoding, neutrally evolving sequence variation in coalescent and concatenation-based phylogenetic frameworks. These analyses were followed by validation with multiple classes of phylogenetically informative structural variation. This approach enabled the generation of a robust time tree for placental mammals that evaluated age variation across hundreds of genomic loci that are not restricted by protein coding annotations. RESULTS Coalescent and concatenation phylogenies inferred from multiple treatments of the data were highly congruent, including support for higher-level taxonomic groupings that unite primates+colugos with treeshrews (Euarchonta), bats+cetartiodactyls+perissodactyls+carnivorans+pangolins (Scrotifera), all scrotiferans excluding bats (Fereuungulata), and carnivorans+pangolins with perissodactyls (Zooamata). However, because these approaches infer a single best tree, they mask signatures of phylogenetic conflict that result from incomplete lineage sorting and historical hybridization. Accordingly, we also inferred phylogenies from thousands of noncoding loci distributed across chromosomes with historically contrasting recombination rates. Throughout the radiation of modern orders (such as rodents, primates, bats, and carnivores), we observed notable differences between locus trees inferred from the autosomes and the X chromosome, a pattern typical of speciation with gene flow. We show that in many cases, previously controversial phylogenetic relationships can be reconciled by examining the distribution of conflicting phylogenetic signals along chromosomes with variable historical recombination rates. Lineage divergence time estimates were notably uniform across genomic loci and robust to extensive sensitivity analyses in which the underlying data, fossil constraints, and clock models were varied. The earliest branching events in the placental phylogeny coincide with the breakup of continental landmasses and rising sea levels in the Late Cretaceous. This signature of allopatric speciation is congruent with the low genomic conflict inferred for most superordinal relationships. By contrast, we observed a second pulse of diversification immediately after the Cretaceous-Paleogene (K-Pg) extinction event superimposed on an episode of rapid land emergence. Greater geographic continuity coupled with tumultuous climatic changes and increased ecological landscape at this time provided enhanced opportunities for mammalian diversification, as depicted in the fossil record. These observations dovetail with increased phylogenetic conflict observed within clades that diversified in the Cenozoic. CONCLUSION Our genome-wide analysis of multiple classes of sequence variation provides the most comprehensive assessment of placental mammal phylogeny, resolves controversial relationships, and clarifies the timing of mammalian diversification. We propose that the combination of Cretaceous continental fragmentation and lineage isolation, followed by the direct and indirect effects of the K-Pg extinction at a time of rapid land emergence, synergistically contributed to the accelerated diversification rate of placental mammals during the early Cenozoic. The timing of placental mammal evolution. Superordinal mammalian diversification took place in the Cretaceous during periods of continental fragmentation and sea level rise with little phylogenomic discordance (pie charts: left, autosomes; right, X chromosome), which is consistent with allopatric speciation. By contrast, the Paleogene hosted intraordinal diversification in the aftermath of the K-Pg mass extinction event, when clades exhibited higher phylogenomic discordance consistent with speciation with gene flow and incomplete lineage sorting. 

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3. Olfactory receptor gene evolution is unusually rapid across Tetrapoda and outpaces chemosensory phenotypic change

   https://doi.org/10.1093/cz/zoaa051  

   Yohe, Laurel R ; Fabbri, Matteo ; Hanson, Michael ; Bhullar, Bhart-Anjan S ( September 2020 , Current Zoology)

   Muñoz, Martha (Ed.)

   Abstract Chemosensation is the most ubiquitous sense in animals, enacted by the products of complex gene families that detect environmental chemical cues and larger-scale sensory structures that process these cues. While there is a general conception that olfactory receptor (OR) genes evolve rapidly, the universality of this phenomenon across vertebrates, and its magnitude, are unclear. The supposed correlation between molecular rates of chemosensory evolution and phenotypic diversity of chemosensory systems is largely untested. We combine comparative genomics and sensory morphology to test whether OR genes and olfactory phenotypic traits evolve at faster rates than other genes or traits. Using published genomes, we identified ORs in 21 tetrapods, including amphibians, reptiles, birds, and mammals and compared their rates of evolution to those of orthologous non-OR protein-coding genes. We found that, for all clades investigated, most OR genes evolve nearly an order of magnitude faster than other protein-coding genes, with many OR genes showing signatures of diversifying selection across nearly all taxa in this study. This rapid rate of evolution suggests that chemoreceptor genes are in “evolutionary overdrive,” perhaps evolving in response to the ever-changing chemical space of the environment. To obtain complementary morphological data, we stained whole fixed specimens with iodine, µCT-scanned the specimens, and digitally segmented chemosensory and nonchemosensory brain regions. We then estimated phenotypic variation within traits and among tetrapods. While we found considerable variation in chemosensory structures, they were no more diverse than nonchemosensory regions. We suggest chemoreceptor genes evolve quickly in reflection of an ever-changing chemical space, whereas chemosensory phenotypes and processing regions are more conserved because they use a standardized or constrained architecture to receive and process a range of chemical cues. 

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4. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

   https://doi.org/10.1126/science.abm7993  

   Kaplow, Irene M. ; Lawler, Alyssa J. ; Schäffer, Daniel E. ; Srinivasan, Chaitanya ; Sestili, Heather H. ; Wirthlin, Morgan E. ; Phan, BaDoi N. ; Prasad, Kavya ; Brown, Ashley R. ; Zhang, Xiaomeng ; et al ( April 2023 , Science)

   INTRODUCTION Diverse phenotypes, including large brains relative to body size, group living, and vocal learning ability, have evolved multiple times throughout mammalian history. These shared phenotypes may have arisen repeatedly by means of common mechanisms discernible through genome comparisons. RATIONALE Protein-coding sequence differences have failed to fully explain the evolution of multiple mammalian phenotypes. This suggests that these phenotypes have evolved at least in part through changes in gene expression, meaning that their differences across species may be caused by differences in genome sequence at enhancer regions that control gene expression in specific tissues and cell types. Yet the enhancers involved in phenotype evolution are largely unknown. Sequence conservation–based approaches for identifying such enhancers are limited because enhancer activity can be conserved even when the individual nucleotides within the sequence are poorly conserved. This is due to an overwhelming number of cases where nucleotides turn over at a high rate, but a similar combination of transcription factor binding sites and other sequence features can be maintained across millions of years of evolution, allowing the function of the enhancer to be conserved in a particular cell type or tissue. Experimentally measuring the function of orthologous enhancers across dozens of species is currently infeasible, but new machine learning methods make it possible to make reliable sequence-based predictions of enhancer function across species in specific tissues and cell types. RESULTS To overcome the limits of studying individual nucleotides, we developed the Tissue-Aware Conservation Inference Toolkit (TACIT). Rather than measuring the extent to which individual nucleotides are conserved across a region, TACIT uses machine learning to test whether the function of a given part of the genome is likely to be conserved. More specifically, convolutional neural networks learn the tissue- or cell type–specific regulatory code connecting genome sequence to enhancer activity using candidate enhancers identified from only a few species. This approach allows us to accurately associate differences between species in tissue or cell type–specific enhancer activity with genome sequence differences at enhancer orthologs. We then connect these predictions of enhancer function to phenotypes across hundreds of mammals in a way that accounts for species’ phylogenetic relatedness. We applied TACIT to identify candidate enhancers from motor cortex and parvalbumin neuron open chromatin data that are associated with brain size relative to body size, solitary living, and vocal learning across 222 mammals. Our results include the identification of multiple candidate enhancers associated with brain size relative to body size, several of which are located in linear or three-dimensional proximity to genes whose protein-coding mutations have been implicated in microcephaly or macrocephaly in humans. We also identified candidate enhancers associated with the evolution of solitary living near a gene implicated in separation anxiety and other enhancers associated with the evolution of vocal learning ability. We obtained distinct results for bulk motor cortex and parvalbumin neurons, demonstrating the value in applying TACIT to both bulk tissue and specific minority cell type populations. To facilitate future analyses of our results and applications of TACIT, we released predicted enhancer activity of >400,000 candidate enhancers in each of 222 mammals and their associations with the phenotypes we investigated. CONCLUSION TACIT leverages predicted enhancer activity conservation rather than nucleotide-level conservation to connect genetic sequence differences between species to phenotypes across large numbers of mammals. TACIT can be applied to any phenotype with enhancer activity data available from at least a few species in a relevant tissue or cell type and a whole-genome alignment available across dozens of species with substantial phenotypic variation. Although we developed TACIT for transcriptional enhancers, it could also be applied to genomic regions involved in other components of gene regulation, such as promoters and splicing enhancers and silencers. As the number of sequenced genomes grows, machine learning approaches such as TACIT have the potential to help make sense of how conservation of, or changes in, subtle genome patterns can help explain phenotype evolution. Tissue-Aware Conservation Inference Toolkit (TACIT) associates genetic differences between species with phenotypes. TACIT works by generating open chromatin data from a few species in a tissue related to a phenotype, using the sequences underlying open and closed chromatin regions to train a machine learning model for predicting tissue-specific open chromatin and associating open chromatin predictions across dozens of mammals with the phenotype. [Species silhouettes are from PhyloPic] 

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5. Phylogenomics and the Genetic Architecture of the Placental Mammal Radiation

   https://doi.org/10.1146/annurev-animal-061220-023149  

   Murphy, William J. ; Foley, Nicole M. ; Bredemeyer, Kevin R. ; Gatesy, John ; Springer, Mark S. ( February 2021 , Annual Review of Animal Biosciences)

   null (Ed.)

   The genomes of placental mammals are being sequenced at an unprecedented rate. Alignments of hundreds, and one day thousands, of genomes spanning the rich living and extinct diversity of species offer unparalleled power to resolve phylogenetic controversies, identify genomic innovations of adaptation, and dissect the genetic architecture of reproductive isolation. We highlight outstanding questions about the earliest phases of placental mammal diversification and the promise of newer methods, as well as remaining challenges, toward using whole genome data to resolve placental mammal phylogeny. The next phase of mammalian comparative genomics will see the completion and application of finished-quality, gapless genome assemblies from many ordinal lineages and closely related species. Interspecific comparisons between the most hypervariable genomic loci will likely reveal large, but heretofore mostly underappreciated, effects on population divergence, morphological innovation, and the origin of new species. 

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