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  • 1
    In: Nature, Springer Science and Business Media LLC, Vol. 583, No. 7814 ( 2020-07-02), p. 96-102
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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    SSG: 11
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  • 2
    In: Biological Psychiatry, Elsevier BV, ( 2024-4)
    Type of Medium: Online Resource
    ISSN: 0006-3223
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
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    SSG: 12
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  • 3
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6643 ( 2023-04-28)
    Abstract: A major challenge in genomics is discerning which bases among billions alter organismal phenotypes and affect health and disease risk. Evidence of past selective pressure on a base, whether highly conserved or fast evolving, is a marker of functional importance. Bases that are unchanged in all mammals may shape phenotypes that are essential for organismal health. Bases that are evolving quickly in some species, or changed only in species that share an adaptive trait, may shape phenotypes that support survival in specific niches. Identifying bases associated with exceptional capacity for cellular recovery, such as in species that hibernate, could inform therapeutic discovery. RATIONALE The power and resolution of evolutionary analyses scale with the number and diversity of species compared. By analyzing genomes for hundreds of placental mammals, we can detect which individual bases in the genome are exceptionally conserved (constrained) and likely to be functionally important in both coding and noncoding regions. By including species that represent all orders of placental mammals and aligning genomes using a method that does not require designating humans as the reference species, we explore unusual traits in other species. RESULTS Zoonomia’s mammalian comparative genomics resources are the most comprehensive and statistically well-powered produced to date, with a protein-coding alignment of 427 mammals and a whole-genome alignment of 240 placental mammals representing all orders. We estimate that at least 10.7% of the human genome is evolutionarily conserved relative to neutrally evolving repeats and identify about 101 million significantly constrained single bases (false discovery rate 〈 0.05). We cataloged 4552 ultraconserved elements at least 20 bases long that are identical in more than 98% of the 240 placental mammals. Many constrained bases have no known function, illustrating the potential for discovery using evolutionary measures. Eighty percent are outside protein-coding exons, and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Constrained bases tend to vary less within human populations, which is consistent with purifying selection. Species threatened with extinction have few substitutions at constrained sites, possibly because severely deleterious alleles have been purged from their small populations. By pairing Zoonomia’s genomic resources with phenotype annotations, we find genomic elements associated with phenotypes that differ between species, including olfaction, hibernation, brain size, and vocal learning. We associate genomic traits, such as the number of olfactory receptor genes, with physical phenotypes, such as the number of olfactory turbinals. By comparing hibernators and nonhibernators, we implicate genes involved in mitochondrial disorders, protection against heat stress, and longevity in this physiologically intriguing phenotype. Using a machine learning–based approach that predicts tissue-specific cis - regulatory activity in hundreds of species using data from just a few, we associate changes in noncoding sequence with traits for which humans are exceptional: brain size and vocal learning. CONCLUSION Large-scale comparative genomics opens new opportunities to explore how genomes evolved as mammals adapted to a wide range of ecological niches and to discover what is shared across species and what is distinctively human. High-quality data for consistently defined phenotypes are necessary to realize this potential. Through partnerships with researchers in other fields, comparative genomics can address questions in human health and basic biology while guiding efforts to protect the biodiversity that is essential to these discoveries. Comparing genomes from 240 species to explore the evolution of placental mammals. Our new phylogeny (black lines) has alternating gray and white shading, which distinguishes mammalian orders (labeled around the perimeter). Rings around the phylogeny annotate species phenotypes. Seven species with diverse traits are illustrated, with black lines marking their branch in the phylogeny. Sequence conservation across species is described at the top left. IMAGE CREDIT: K. MORRILL
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2023
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  • 4
    In: Mammalian Biology, Springer Science and Business Media LLC, Vol. 102, No. 1 ( 2022-02), p. 235-249
    Abstract: A new and uniquely structured matrix of mammalian phenotypes, MaTrics ( Ma mmalian Tr aits for Comparative Genom ics ) in a digital form is presented. By focussing on mammalian species for which genome assemblies are available, MaTrics provides an interface between mammalogy and comparative genomics. MaTrics was developed within a project aimed to find genetic causes of phenotypic traits of mammals using Forward Genomics. This approach requires genomes and comprehensive and recorded information on homologous phenotypes that are coded as discrete categories in a matrix. MaTrics is an evolving online resource providing information on phenotypic traits in numeric code; traits are coded either as absent/present or with several states as multistate. The state record for each species is linked to at least one reference (e.g., literature, photographs, histological sections, CT scans, or museum specimens) and so MaTrics contributes to digitalization of museum collections. Currently, MaTrics covers 147 mammalian species and includes 231 characters related to structure, morphology, physiology, ecology, and ethology and available in a machine actionable NEXUS-format*. Filling MaTrics revealed substantial knowledge gaps, highlighting the need for phenotyping efforts. Studies based on selected data from MaTrics and using Forward Genomics identified associations between genes and certain phenotypes ranging from lifestyles (e.g., aquatic) to dietary specializations (e.g., herbivory, carnivory). These findings motivate the expansion of phenotyping in MaTrics by filling research gaps and by adding taxa and traits. Only databases like MaTrics will provide machine actionable information on phenotypic traits, an important limitation to genomics. MaTrics is available within the data repository Morph·D·Base ( www.morphdbase.de ).
    Type of Medium: Online Resource
    ISSN: 1616-5047 , 1618-1476
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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    detail.hit.zdb_id: 2072973-X
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  • 5
    In: Nature Biotechnology, Springer Science and Business Media LLC, Vol. 40, No. 6 ( 2022-06), p. 817-820
    Type of Medium: Online Resource
    ISSN: 1087-0156 , 1546-1696
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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    detail.hit.zdb_id: 1311932-1
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  • 6
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6643 ( 2023-04-28)
    Abstract: 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]
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2023
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  • 7
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 377, No. 6609 ( 2022-08-26), p. 982-987
    Abstract: Two pulses of migration appear to have contributed to the early farmers of Anatolia.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2022
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  • 8
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6643 ( 2023-04-28)
    Abstract: Mammals, including humans, achieve high levels of organismal complexity largely due to how their proteins are regulated; characterizing the regulatory landscape of the human genome is a longstanding goal of modern biology. Contemporary approaches measure genome-wide biochemical signals, including chromatin accessibility, histone modifications, DNA methylation, and binding of ~1600 transcription factors (TFs) by the human genome. Using these methods, the ENCODE consortium defined almost one million candidate cis-regulatory elements (cCREs). Another approach uses evolutionary conservation to identify potential regulatory regions. We combine these approaches, examining how different functional classes of regulatory elements respond to evolutionary pressures. RATIONALE cCREs tend to be conserved and cCRE classes exhibit varying levels of conservation, suggesting interesting evolutionary dynamics. We examine these dynamics in placental mammals using tools developed by the Zoonomia project: the evolutionary constraint in placental mammals and the reference-free 241-genome alignment. We identify the human cCREs and transcription factor binding sites (TFBSs) conserved in the mammalian lineage, characterize the evolutionary histories of cCREs and TFBSs and identify the driving forces behind their gains and losses and—using biochemical and epigenomic data—assess the likelihood that conserved cCREs and TFBSs are functional in humans and other mammals. RESULTS We explored the ENCODE cCREs derived from epigenomic data and the binding sites of 367 TFs from chromatin immunoprecipitation data. We found a spectrum of mammalian conservation for regulatory elements: on one end lies the highly conserved cCREs and constrained TFBSs, and on the other are primate-specific cCREs and TFBSs overlapping transposable elements (TEs). Conserved elements predominate near genes that function in fundamental cellular processes (metabolism, development) and tend to be functional in other mammalian genomes whereas unconstrained elements lie near genes involved in interaction with the environment. We identified ~439 thousand deeply conserved cCREs (47.5% of cCREs and 4% of the human genome) and 2 million TFBSs (0.8% of the human genome) under mammalian constraint. Using a panel of 69 genome-wide association studies, we found that conserved cCREs and constrained TFBSs achieved high heritability enrichment, demonstrating their utility for functional interpretation of human genetic variants. Meanwhile, more than 85% of primate-specific TFBSs—representing more than 20% of all TFBSs—are derived from TEs. Phylogenetic analysis revealed a staggering number of TFBS clusters sharing patterns of presence and absence across primate genomes and enrichment in specific TE families, suggesting that multiple waves of TE insertion spread these TFBSs during primate evolution. CONCLUSION We charted the evolutionary landscapes of cCREs and TFBSs among placental mammals, identifying a subset of elements under purifying selection in the mammalian lineage. These elements are highly enriched in the human genetic variants associated with a panel of diverse, complex traits, with heritability enrichment contributed by both nucleotides under mammalian and nucleotides under primate constraint. Mammalian evolution of the human regulatory landscape. ( A ) Distribution of human cCREs by the number of genomes they align. ( B ) Projection of cCREs by alignments to the other 240 mammalian genomes. ( C ) Project of HNF4A sites (constrained, red; unconstrained, blue). ( D ) Heritability enrichment for 69 human traits in partitions of TFBSs ordered by evolutionary constraint. ( E ) Heritability enrichment for human traits by subsets of TFBSs.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2023
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    detail.hit.zdb_id: 2066996-3
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    SSG: 11
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  • 9
    In: Journal of Evolutionary Biology, Wiley, Vol. 35, No. 2 ( 2022-02), p. 225-239
    Abstract: The inactivation of ancestral protein‐coding genes (gene loss) can be associated with phenotypic modifications. Within placental mammals, repeated losses of PNLIPRP1 (gene inhibiting fat digestion) occurred preferentially in strictly herbivorous species, whereas repeated NR1I3 losses (gene involved in detoxification) occurred preferentially in strictly carnivorous species. It was hypothesized that lower fat contents of herbivorous diets and lower toxin contents of carnivorous diets cause relaxed selection pressure on these genes, resulting in the accumulation of mutations and ultimately to convergent gene losses. However, because herbivorous and carnivorous diets differ vastly in their composition, a fine‐grained analysis is required for hypothesis testing. We generated a trait matrix recording diet and semi‐quantitative estimates of fat and toxin consumption for 52 placental species. By including data from 31 fossil taxa, we reconstructed the ancestral diets in major lineages ( grundplan reconstruction). We found support that PNLIPRP1 loss is primarily associated with low levels of fat intake and not simply with herbivory/carnivory. In particular, PNLIPRP1 loss also occurred in carnivorous lineages feeding on a fat‐poor diet, suggesting that the loss of this gene may be beneficial for occupying ecological niches characterized by fat‐poor food resources. Similarly, we demonstrated that carnivorous species are indeed less exposed to diet‐related toxins, suggesting that the loss of NR1I3 and related genes ( NR1I2 and UGT1A6 ) resulted from relaxed selection pressure. This study illustrates the need of detailed phenotype studies to obtain a deeper understanding of factors underlying gene losses and to progress in understanding genomic causes of phenotypic variation in mammals.
    Type of Medium: Online Resource
    ISSN: 1010-061X , 1420-9101
    URL: Issue
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    Language: English
    Publisher: Wiley
    Publication Date: 2022
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    detail.hit.zdb_id: 1465318-7
    SSG: 12
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  • 10
    In: BMC Microbiology, Springer Science and Business Media LLC, Vol. 20, No. 1 ( 2020-12)
    Abstract: The human colon is colonised by a dense microbial community whose species composition and metabolism are linked to health and disease. The main energy sources for colonic bacteria are dietary polysaccharides and oligosaccharides. These play a major role in modulating gut microbial composition and metabolism, which in turn can impact on health outcomes. Results We investigated the influence of wheat bran arabinoxylan oligosaccharides (AXOS) and maltodextrin supplements in modulating the composition of the colonic microbiota and metabolites in healthy adults over the age of 60. Male and female volunteers, ( n  = 21, mean BMI 25.2 ± 0.7 kg/m 2 ) participated in the double-blind, cross over supplement study. Faecal samples were collected for analysis of microbiota, short chain fatty acids levels and calprotectin. Blood samples were collected to measure glucose, cholesterol and triglycerides levels. There was no change in these markers nor in calprotectin levels in response to the supplements. Both supplements were well-tolerated by the volunteers. Microbiota analysis across the whole volunteer cohort revealed a significant increase in the proportional abundance of faecal Bifidobacterium species ( P  ≤ 0.01) in response to AXOS, but not maltodextrin, supplementation. There was considerable inter-individual variation in the other bacterial taxa that responded, with a clear stratification of volunteers as either Prevotella -plus ( n  = 8; 〉  0.1% proportional abundance) or Prevotella -minus ( n  = 13; ≤0.1% proportional abundance) subjects founded on baseline sample profiles. There was a significant increase in the proportional abundance of both faecal Bifidobacterium ( P  ≤ 0.01) and Prevotella species ( P  ≤ 0.01) in Prevotella -plus volunteers during AXOS supplementation, while Prevotella and Bacteroides relative abundances showed an inverse relationship. Proportional abundance of 26 OTUs, including bifidobacteria and Anaerostipes hadrus, differed significantly between baseline samples of Prevotella -plus compared to Prevotella -minus individuals. Conclusions The wheat bran AXOS supplementation was bifidogenic and resulted in changes in human gut microbiota composition that depended on the initial microbiota profile, specifically the presence or absence of Prevotella spp. as a major component of the microbiota. Our data therefore suggest that initial profiling of individuals through gut microbiota analysis should be considered important when contemplating nutritional interventions that rely on prebiotics. Trial registration Clinical trial registration number: NCT02693782 . Registered 29 February 2016 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02693782?term=NCT02693782 & rank=1
    Type of Medium: Online Resource
    ISSN: 1471-2180
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2041505-9
    SSG: 12
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