ArticleGigaScience2018
Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics, and epigenetics data.
Article in GigaScience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Sequence-based GWAS meta-analyses for beef production traits.Genetics, selection, evolution : GSE · 2023Pooled it
- Identification of cis-regulatory elements provides insights into tissue-specific gene regulation in the sheep genome.Nature communications · 2026Article
- A Graph-based Goat Pangenome Reveals Structural Variations Involved in Domestication and Adaptation.Molecular biology and evolution · 2024Article
- Review
- Identification of transcriptional regulatory variants in pig duodenum, liver, and muscle tissues.GigaScience · 2022Article
- RGD v2.0: a major update of the ruminant functional and evolutionary genomics database.Nucleic acids research · 2022Article
- Chromatin accessibility and regulatory vocabulary across indicine cattle tissues.Genome biology · 2021Article
- Epstein-Barr virus inactivates the transcriptome and disrupts the chromatin architecture of its host cell in the first phase of lytic reactivation.Nucleic acids research · 2021Article
- Putative Causal Variants Are Enriched in Annotated Functional Regions From Six Bovine Tissues.Frontiers in genetics · 2021Article
- Comparative Enhancer Map of Cattle Muscle Genome Annotated by ATAC-Seq.Frontiers in veterinary science · 2021Article
- Selection signatures in tropical cattle are enriched for promoter and coding regions and reveal missense mutations in the damage response gene HELB.Genetics, selection, evolution : GSE · 2020Article
- Genome-Wide Histone Modifications and CTCF Enrichment Predict Gene Expression in Sheep Macrophages.Frontiers in genetics · 2020Article
- Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattle.Genetics, selection, evolution : GSE · 2019Article
- Putative bovine topological association domains and CTCF binding motifs can reduce the search space for causative regulatory variants of complex traits.BMC genomics · 2018Article
- Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics, and epigenetics data.GigaScience · 2018Article
- Integrating Selection Mapping With Genetic Mapping and Functional Genomics.Frontiers in genetics · 2018Review
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome sequences for hundreds of mammalian species are available, but an understanding of their genomic regulatory regions, which control gene expression, is only beginning. A comprehensive prediction of potential active regulatory regions is necessary to functionally study the roles of the majority of genomic variants in evolution, domestication, and animal production. We developed a computational method to predict regulatory DNA sequences (promoters, enhancers, and transcription factor binding sites) in production animals (cows and pigs) and extended its broad applicability to other mammals. The method utilizes human regulatory features identified from thousands of tissues, cell lines, and experimental assays to find homologous regions that are conserved in sequences and genome organization and are enriched for regulatory elements in the genome sequences of other mammalian species. Importantly, we developed a filtering strategy, including a machine learning classification method, to utilize a very small number of species-specific experimental datasets available to select for the likely active regulatory regions. The method finds the optimal combination of sensitivity and accuracy to unbiasedly predict regulatory regions in mammalian species. Furthermore, we demonstrated the utility of the predicted regulatory datasets in cattle for prioritizing variants associated with multiple production and climate change adaptation traits and identifying potential genome editing targets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.