10
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Predicting Archaic Hominin Phenotypes from Genomic Data

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Ancient DNA provides a powerful window into the biology of extant and extinct species, including humans’ closest relatives: Denisovans and Neanderthals. Here, we review what is known about archaic hominin phenotypes from genomic data and how those inferences have been made. We contend that understanding the influence of variants on lower-level molecular phenotypes—such as gene expression and protein function—is a promising approach to using ancient DNA to learn about archaic hominin traits. Molecular phenotypes have simpler genetic architectures than organism-level complex phenotypes, and this approach enables moving beyond association studies by proposing hypotheses about the effects of archaic variants that are testable in model systems. The major challenge to understanding archaic hominin phenotypes is broadening our ability to accurately map genotypes to phenotypes, but ongoing advances ensure that there will be much more to learn about archaic hominin phenotypes from their genomes.

          Related collections

          Most cited references145

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          An Integrated Encyclopedia of DNA Elements in the Human Genome

          Summary The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure, and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall the project provides new insights into the organization and regulation of our genes and genome, and an expansive resource of functional annotations for biomedical research.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The GTEx Consortium atlas of genetic regulatory effects across human tissues

            (2020)
            The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Integrative analysis of 111 reference human epigenomes

              The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but a similar reference has lacked for epigenomic studies. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection to-date of human epigenomes for primary cells and tissues. Here, we describe the integrative analysis of 111 reference human epigenomes generated as part of the program, profiled for histone modification patterns, DNA accessibility, DNA methylation, and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically-relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation, and human disease.
                Bookmark

                Author and article information

                Journal
                100911346
                26795
                Annu Rev Genomics Hum Genet
                Annu Rev Genomics Hum Genet
                Annual review of genomics and human genetics
                1527-8204
                1545-293X
                3 June 2023
                31 August 2022
                19 April 2022
                09 June 2023
                : 23
                : 591-612
                Affiliations
                [1 ]Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
                [2 ]Bakar Computational Health Sciences Institute, University of California, San Francisco, California, USA
                [3 ]Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
                Author notes
                Article
                NIHMS1899886
                10.1146/annurev-genom-111521-121903
                10250142
                35440148
                ec5157a4-fa0d-498d-afcd-094c9a27e215

                This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See credit lines of images or other third-party material in this article for license information

                History
                Categories
                Article

                ancient dna,archaic hominin,denisovan,neanderthal,phenotype prediction

                Comments

                Comment on this article