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  • 11
    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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  • 12
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 367, No. 6473 ( 2020-01-03), p. 64-67
    Abstract: A quantum anomalous Hall (QAH) insulator coupled to an s-wave superconductor is predicted to harbor chiral Majorana modes. A recent experiment interprets the half-quantized two-terminal conductance plateau as evidence for these modes in a millimeter-size QAH-niobium hybrid device. However, non-Majorana mechanisms can also generate similar signatures, especially in disordered samples. Here, we studied similar hybrid devices with a well-controlled and transparent interface between the superconductor and the QAH insulator. When the devices are in the QAH state with well-aligned magnetization, the two-terminal conductance is always half-quantized. Our experiment provides a comprehensive understanding of the superconducting proximity effect observed in QAH-superconductor hybrid devices and shows that the half-quantized conductance plateau is unlikely to be induced by chiral Majorana fermions in samples with a highly transparent interface.
    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: 2020
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  • 13
    In: Information Sciences, Elsevier BV, Vol. 568 ( 2021-08), p. 427-447
    Type of Medium: Online Resource
    ISSN: 0020-0255
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
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  • 14
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 14 ( 2022-04-05)
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 14 ( 2022-04-05)
    Abstract: Metformin, the frontline antidiabetic drug, has gained increasing attention for the prevention and treatment of aging, cancer, and cardiovascular disease. Yet a clear mechanistic understanding of its action is still lacking, largely due to the suprapharmacological concentrations of metformin used in most studies. Here, we report an inhibition of glucose production by primary hepatocytes from dietary and genetic mouse models of type 2 diabetes (T2D) using metformin at clinically relevant concentrations. Mechanistically, metformin up-regulates microRNA let-7 that in turn down-regulates TET3, evoking a change in the ratio of hepatocyte nuclear factor 4 alpha (HNF4α) isoforms and subsequent inhibition of key gluconeogenic genes. Importantly, this let-7–mediated mechanism is faithfully recapitulated in mice with T2D chronically treated with therapeutic doses of metformin. Furthermore, hepatic delivery of let-7 ameliorates hyperglycemia and improves glucose homeostasis in diabetic mice, whereas liver-specific inhibition of let-7 abrogates these beneficial effects of metformin. Moreover, let-7 overexpression decreases glucose production from primary hepatocytes from obese humans. Thus, we propose the reactivation of a let-7–dependent pathway that is pathologically repressed in the liver of diabetes as a major mechanism of metformin action and that liver-specific delivery of let-7 represents a potential therapeutic for T2D. Our findings are also pertinent to the development of therapeutic strategies for other chronic diseases.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
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  • 15
    Online Resource
    Online Resource
    Walter de Gruyter GmbH ; 2022
    In:  International Review of Applied Linguistics in Language Teaching Vol. 0, No. 0 ( 2022-10-28)
    In: International Review of Applied Linguistics in Language Teaching, Walter de Gruyter GmbH, Vol. 0, No. 0 ( 2022-10-28)
    Abstract: This study proposes two collaborative concept mapping-based prewriting strategies to help Chinese EFL learners with a reading-to-write task—reading an unfinished story and then writing its ending. Collaborative concept mapping enables students to visualize the storyline with the help of peer scaffolding. The two proposed strategies used collaborative fill-in-the-blanks concept maps (CFCM) and collaboratively constructed concept maps (CCCM). Classes 1 ( N  = 48) and 2 ( N  = 47) participated in the experiment and respectively learned the strategies of CFCM and CCCM. The collected data included students’ concept maps, reading-to-write products, responses to questionnaires on attitudes and motivation, and learning journals, which were analyzed by t tests, path analysis, and qualitative coding. The results indicated that students using CCCM showed more positive attitudes and higher motivation than those using CFCM; however, the two strategies shared similar effectiveness in developing students’ reading-to-write abilities. Students found the proposed strategies effective in helping them write the story ending.
    Type of Medium: Online Resource
    ISSN: 0019-042X , 1613-4141
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    Language: English
    Publisher: Walter de Gruyter GmbH
    Publication Date: 2022
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  • 16
    Online Resource
    Online Resource
    IOP Publishing ; 2014
    In:  EPL (Europhysics Letters) Vol. 107, No. 3 ( 2014-08-01), p. 34007-
    In: EPL (Europhysics Letters), IOP Publishing, Vol. 107, No. 3 ( 2014-08-01), p. 34007-
    Type of Medium: Online Resource
    ISSN: 0295-5075 , 1286-4854
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2014
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  • 17
    Online Resource
    Online Resource
    IOP Publishing ; 2010
    In:  EPL (Europhysics Letters) Vol. 89, No. 5 ( 2010-03-01), p. 58002-
    In: EPL (Europhysics Letters), IOP Publishing, Vol. 89, No. 5 ( 2010-03-01), p. 58002-
    Type of Medium: Online Resource
    ISSN: 0295-5075 , 1286-4854
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2010
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  • 18
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6648 ( 2023-06-02)
    Abstract: There is increasing evidence pointing to a close relationship between heart health and brain health, with cardiovascular diseases potentially leading to brain diseases such as stroke, dementia, and cognitive impairment. Magnetic resonance imaging (MRI) is a valuable tool that can be used to assess both the heart and brain, generating biomarkers and endophenotypes for various clinical outcomes. However, although recent large-scale analyses have been conducted on heart and brain MRI-derived traits separately, few studies have explored the potential for multiorgan MRI to examine heart-brain connections and identify shared genetic effects. The structural and functional links between the heart and the brain remain unclear. RATIONALE Using multiorgan MRI and genetic data from 〉 40,000 subjects, we aimed to quantify interorgan connections between the heart and brain and identify the underlying genetic variants. Specifically, we analyzed 82 cardiac and aortic MRI-derived traits across six categories: left and right ventricles, left and right atria, and ascending and descending aortas, as well as 458 brain MRI traits that measured structure and function. RESULTS After controlling for various covariates, we found that heart MRI traits were clearly associated with the brain across all imaging modalities studied. We observed multiple patterns of association for brain gray matter morphometry, white matter microstructure, and functional networks. For example, we found that the left ventricle of the heart showed the strongest correlations with microstructure metrics of cerebral white matter tracts, suggesting that adverse heart features were associated with poorer white matter microstructure. Our genome-wide association analysis of heart MRI traits identified 80 associated genomic loci ( P 〈 6.09 × 10 −10 ). We performed sex-specific analysis and found that the genetic effects on heart structure and function were highly consistent between both sexes. Further, we conducted a systematic search of previously reported genetic results in these genomic loci and found that heart MRI traits had shared genetic influences and colocalized with heart and brain diseases and complex traits. We identified genetic correlations between heart MRI traits and various brain complex traits and diseases such as stroke, eating disorders, schizophrenia, cognitive function, and mental health traits. For example, adverse myocardial wall thickness condition was positively genetically correlated with stroke. We further used two-sample Mendelian randomization to explore causal genetic links between the heart and brain, and our findings suggest that adverse heart features have genetic causal effects on several brain diseases such as psychiatric disorders and depression. CONCLUSION This study deepened our understanding of heart-brain links and their genetic basis. We observed that MRI measurements of the two organs were associated with each other, and this was independent of a wide variety of body measures, shared risk factors, and imaging confounders. We also uncovered genetic colocalizations and correlations between heart structure and function and brain clinical end points, suggesting that adverse heart metrics may have implications for brain abnormalities and the risk of brain diseases. By understanding human health from a multiorgan perspective, we may be able to improve disease risk prediction and prevention and mitigate the negative effects of one organ disease on other organs that may be at risk. Heart-brain connections revealed by multiorgan imaging genetics. Top left: Quantifying the heart and brain structure and function in MRI. Top right: Examples of associations between heart MRI traits and brain white matter tracts. Bottom left: Genomic loci associated with heart MRI traits that overlapped with traits and disorders of the heart and/or brain. Bottom right: Selected genetic correlations between heart MRI traits and brain disorders.
    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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  • 19
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6643 ( 2023-04-28)
    Abstract: Human accelerated regions (HARs) are evolutionarily conserved sequences that acquired an unexpectedly high number of nucleotide substitutions in the human genome since divergence from our common ancestor with chimpanzees. Prior work has established that many HARs are gene regulatory enhancers that function during embryonic development, particularly in neurodevelopment, and that most HARs show signatures of positive selection. However, the events that caused the sudden change in selective pressures on HARs remain a mystery. RATIONALE Because HARs acquired many substitutions in our ancestors after millions of years of extreme constraint across diverse mammals, we reasoned that their conserved roles in regulating development of the brain and other organs must have changed during human evolution. One mechanism that could drive such a functional shift is enhancer hijacking, whereby the target gene repertoire of a noncoding sequence is changed through alterations in three-dimensional genome folding. The regulatory information encoded in a hijacked enhancer would likely need to change to avoid deleterious expression of the altered target gene while also possibly supporting modified expression patterns. Structural variants—large genomic insertions, deletions, and rearrangements—are the greatest sources of sequence differences between the human and chimpanzee genomes, and they have the potential to affect how a region of the genome folds and localizes in the nucleus. We therefore hypothesized that some HARs were generated through enhancer hijacking triggered by nearby human-specific structural variants (hsSVs). RESULTS We leveraged an alignment of hundreds of mammalian genomes plus a Nextflow pipeline that we wrote for automating the detection of lineage-specific accelerated regions to identify 312 high-confidence HARs (zooHARs). Through massively parallel reporter assays and machine learning integration of hundreds of epigenomic datasets, we showed that many zooHARs function as neurodevelopmental enhancers and that their human substitutions alter transcription factor binding sites, consistent with previous studies. We further mapped zooHARs to specific cell types and tissues using single-cell open chromatin and gene expression data, and we found that they represent a more diverse set of neurodevelopmental processes than a parallel set of chimpanzee accelerated regions. To test the enhancer hijacking hypothesis, we first examined the three-dimensional neighborhoods of zooHARs using publicly available chromatin capture (Hi-C) data, finding a significant enrichment of zooHARs in domains with hsSVs. This motivated us to use deep learning to predict how hsSVs changed genome folding in the human versus the chimpanzee genomes. We found that 30% of zooHARs occur within 500 kb of an hsSV that substantially alters local chromatin interactions, and we confirmed this association in Hi-C data that we generated in human and chimpanzee neural progenitor cells. Finally, we showed that chromatin domains containing zooHARs and hsSVs are enriched for genes differentially expressed in human versus chimpanzee neurodevelopment. CONCLUSION The origin of many HARs may be explained by human-specific structural variants that altered three-dimensional genome folding, causing evolutionarily conserved enhancers to adapt to different target genes and regulatory domains. Example of HAR enhancer hijacking. The HAR is nearby and regulates gene A, but not gene B, as the chimpanzee genome folds. An insertion in the human genome brings the HAR closer to gene B, causing expression of gene B. The HAR adapts to being in gene B’s regulatory domain through substitutions to previously conserved nucleotides.
    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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  • 20
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 380, No. 6643 ( 2023-04-28)
    Abstract: 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.
    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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