9.9
CiteScore
7.1
Impact Factor
Volume 52 Issue 12
Dec.  2025
Turn off MathJax
Article Contents

Annotation and assessment of functional variants in livestock through epigenomic data

doi: 10.1016/j.jgg.2025.03.013
Funds:

This work was supported by the National Natural Science Foundation of China (32341051), the grant from Department of Agriculture and Rural Affairs of Hubei Province (HBZY2023B006-02), the National Funding (2023ZD04050), the National Natural Science Foundation of China Outstanding Youth (32125035) , and the National Key R&

D Young Scientists Project (2022YFD1302000).

  • Received Date: 2024-12-10
  • Accepted Date: 2025-03-24
  • Rev Recd Date: 2025-03-22
  • Publish Date: 2025-12-31
  • Understanding genetic variant functionality is essential for advancing animal genomics and precision breeding. However, the lack of comprehensive functional genomic annotations in animals limits the effectiveness of most variant function assessment methods. In this study, we gather 1030 raw epigenomic datasets from 10 animal species and systematically annotate 7 types of key regulatory regions, creating a comprehensive functional annotation map of animal genomic variants. Our findings demonstrate that integrating variants with regulatory annotations can identify tissues and cell types underlying economic traits, underscoring the utility of these annotations in functional variant discovery. Using our functional annotations, we rank the functional potential of genetic variants and classify over 127 million candidate variants into 5 functional confidence categories, with high-confidence variants significantly enriched in eQTLs and trait-associated SNPs. Incorporating these variants into genomic prediction models can improve estimated breeding value accuracy, demonstrating their practical utility in breeding programs. To facilitate the use of our results, we develop the Integrated Functional Mutation (IFmut: http://www.ifmutants.com:8212) platform, enabling researchers to explore regulatory annotations and assess the functional potential of animal variants efficiently. Our study provides a robust framework for functional genomic annotations in farm animals, enhancing variant function assessment and breeding precision.
  • loading
  • Arthur, T.D., Nguyen, J.P., Henson, B.A., D’Antonio-Chronowska, A., Jaureguy, J., Silva, N., i, P.C., Panopoulos, A.D., Izpisua Belmonte, J.C., D’Antonio, M., McVicker, G., Frazer, K.A., 2025. Multiomic QTL mapping reveals phenotypic complexity of GWAS loci and prioritizes putative causal variants. Cell Genom. 5 (3), 100775.
    Blackledge, N.P., Klose, R.J., 2021. The molecular principles of gene regulation by Polycomb repressive complexes. Nat. Rev. Mol. Cell Biol. 22, 815-833.
    Boix, C.A., James, B.T., Park, Y.P., Meuleman, W., Kellis, M., 2021. Regulatory genomic circuitry of human disease loci by integrative epigenomics. Nature 590, 300-307.
    Boyle, A.P., Davis, S., Shulha, H.P., Meltzer, P., Margulies, E.H., Weng, Z., Furey, T.S., Crawford, G.E., 2008. High-resolution mapping and characterization of open chromatin across the genome. Cell 132, 311-322.
    Boyle, A.P., Hong, E.L., Hariharan, M., Cheng, Y., Schaub, M.A., Kasowski, M., Karczewski, K.J., Park, J., Hitz, B.C., Weng, S., et al., 2012. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22, 1790-1797.
    Brito, L.F., Clarke, S.M., McEwan, J.C., Miller, S.P., Pickering, N.K., Bain, W.E., Dodds, K.G., Sargolzaei, M., Schenkel, F.S., 2017. Prediction of genomic breeding values for growth, carcass and meat quality traits in a multi-breed sheep population using a HD SNP chip. BMC Genet. 18, 7.
    Buenrostro, J.D., Giresi, P.G., Zaba, L.C., Chang, H.Y., Greenleaf, W.J., 2013. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213-1218.
    Calus, M.P., 2010. Genomic breeding value prediction: methods and procedures. Animal 4, 157-164.
    Cappelloni, M., Gallo, M., Cesarani, A., 2022. Use of threshold and linear models to estimate variance components and breeding values for disease resistance in Italian heavy pigs. Italian Journal of Animal Science 21, 488-492.
    Chen, Y., Zhang, Z., Yang, K., Du, J., Xu, Y., Liu, S., 2015. Myeloid zinc-finger 1 (MZF-1) suppresses prostate tumor growth through enforcing ferroportin-conducted iron egress. Oncogene 34, 3839-3847.
    Cherry, T.J., Yang, M.G., Harmin, D.A., Tao, P., Timms, A.E., Bauwens, M., Allikmets, R., Jones, E.M., Chen, R., De Baere, E., et al., 2020. Mapping the cis-regulatory architecture of the human retina reveals noncoding genetic variation in disease. Proc. Natl. Acad. Sci. U. S. A. 117, 9001-9012.
    Cingolani, P., 2022. Variant annotation and functional prediction: SnpEff. Methods Mol. Biol. 2493, 289-314.
    Coetzee, S.G., Coetzee, G.A., Hazelett, D.J., 2015. motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites. Bioinformatics 31, 3847-3849.
    Cohen, J.C., Pertsemlidis, A., Fahmi, S., Esmail, S., Vega, G.L., Grundy, S.M., Hobbs, H.H., 2006. Multiple rare variants in NPC1L1 associated with reduced sterol absorption and plasma low-density lipoprotein levels. Proc. Natl. Acad. Sci. U. S. A. 103, 1810-1815.
    Collins, F.S., Fink, L., 1995. The Human Genome Project. Alcohol Health Res. World 19, 190-195.
    Consortium, E.P., 2004. The ENCODE (ENCyclopedia Of DNA Elements) Project. Science 306, 636-640.
    Consortium, IGVF, 2024. Deciphering the impact of genomic variation on function. Nature 633, 47-57.
    Cooper, G.M., Stone, E.A., Asimenos, G., Green, E.D., Batzoglou, S., Sidow, A., 2005. Distribution and intensity of constraint in mammalian genomic sequence. Genome Res. 15, 901-913.
    da Silva Lima, F., da Silva Goncalves, C.E., Fock, R.A., 2023. A review of the role of zinc finger proteins on hematopoiesis. J. Trace Elem. Med. Biol. 80, 127290.
    Devuyst, O., 2015. The 1000 Genomes Project: Welcome to a New World. Perit Dial Int. 35, 676-677.
    Eichler, E.E., 2019. Genetic variation, comparative genomics, and the diagnosis of disease. N. Engl. J. Med. 381, 64-74.
    Fang, L., Cai, W., Liu, S., Canela-Xandri, O., Gao, Y., Jiang, J., Rawlik, K., Li, B., Schroeder, S.G., Rosen, B.D., 2020. Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle. Genome Res. 30, 790-801.
    Foissac, S., Djebali, S., Munyard, K., Vialaneix, N., Giuffra, E., 2019. Multi-species annotation of transcriptome and chromatin structure in domesticated animals. BMC Biol. 17, 108.
    Fu, Y., Xu, J., Tang, Z., Wang, L., Yin, D., Fan, Y., Zhang, D., Deng, F., Zhang, Y., Zhang, H., et al., 2020. A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model. Commun. Biol. 3, 502.
    Fu, Y.H., Liu, H., Dou, J.W., Wang, Y., Liao, Y., Huang, X., Tang, Z.S., Xu, J.Y., Yin, D., Zhu, S.L., et al., 2022. IAnimal: a cross-species omics knowledgebase for animals. Nucleic Acids Res. 51, D1312-D1324.
    Giral, H., Landmesser, U., Kratzer, A., 2018. Into the wild: GWAS exploration of non-coding RNAs. Front Cardiovasc Med. 5, 181.
    Gross, C., Bortoluzzi, C., de Ridder, D., Megens, H.-J., Groenen, M.A., Reinders, M., Bosse, M., 2020a. Prioritizing sequence variants in conserved non-coding elements in the chicken genome using chCADD. PLoS Genet. 16, e1009027.
    Gross, C., Derks, M., Megens, H.-J., Bosse, M., Groenen, M.A., Reinders, M., De Ridder, D., 2020b. pCADD: SNV prioritisation in Sus scrofa. Genetics Selection Evolution 52, 1-15.
    Gulko, B., Hubisz, M.J., Gronau, I., Siepel, A., 2015. A method for calculating probabilities of fitness consequences for point mutations across the human genome. Nature Genet. 47, 276-283.
    Halstead, M.M., Kern, C., Saelao, P., Wang, Y., Chanthavixay, G., Medrano, J.F., Van Eenennaam, A.L., Korf, I., Tuggle, C.K., Ernst, C.W., et al., 2020. A comparative analysis of chromatin accessibility in cattle, pig, and mouse tissues. BMC Genomics 21, 698.
    Hao, Y., Stuart, T., Kowalski, M.H., Choudhary, S., Hoffman, P., Hartman, A., Srivastava, A., Molla, G., Madad, S., Fernandez-Granda, C., 2024. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nature Biotech. 42, 293-304.
    Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y.C., Laslo, P., Cheng, J.X., Murre, C., Singh, H., Glass, C.K., 2010. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576-589.
    Hu, C., Li, T., Xu, Y., Zhang, X., Li, F., Bai, J., Chen, J., Jiang, W., Yang, K., Ou, Q., 2023. CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data. Nucleic acids Res. 51, D870-D876.
    Hu, Z.-L., Park, C.A., Reecy, J.M., 2022. Bringing the animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services. Nucleic acids Res. 50, D956-D961.
    Hugot, J.-P., Chamaillard, M., Zouali, H., Lesage, S., Cezard, J.-P., Belaiche, J., Almer, S., Tysk, C., O'Morain, C.A., Gassull, M., 2001. Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease. Nature 411, 599-603.
    Joslin, A.C., Sobreira, D.R., Hansen, G.T., Sakabe, N.J., Aneas, I., Montefiori, L.E., Farris, K.M., Gu, J., Lehman, D.M., Ober, C., 2021. A functional genomics pipeline identifies pleiotropy and cross-tissue effects within obesity-associated GWAS loci. Nature Commun. 12, 5253.
    Kern, C., Wang, Y., Xu, X., Pan, Z., Zhou, H., 2021. Functional annotations of three domestic animal genomes provide vital resources for comparative and agricultural research. Nature Commun. 12, 1821.
    Khan, A., Fornes, O., Stigliani, A., Gheorghe, M., Castro-Mondragon, J.A., van der Lee, R., Bessy, A., Cheneby, J., Kulkarni, S.R., Tan, G., et al., 2018. JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework. Nucleic Acids Res. 46, D1284.
    Lee, T.I., Young, R.A., 2013. Transcriptional regulation and its misregulation in disease. Cell 152, 1237-1251.
    Leinonen, R., Sugawara, H., Shumway, M., C, I.N.S.D., 2011. The Sequence Read Archive. Nucleic Acids Res. 39, D19-D21.
    Li, H., Durbin, R., 2009. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754-1760.
    Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., Genome Project Data Processing, S., 2009. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079.
    Li, Z., Kuo, C.C., Ticconi, F., Shaigan, M., Gehrmann, J., Gusmao, E.G., Allhoff, M., Manolov, M., Zenke, M., Costa, I.G., 2023. RGT: a toolbox for the integrative analysis of high throughput regulatory genomics data. BMC Bioinformatics 24, 79.
    Liu, T., 2014. Use model-based Analysis of ChIP-Seq (MACS) to analyze short reads generated by sequencing protein-DNA interactions in embryonic stem cells. Methods Mol. Biol. 1150, 81-95.
    Lourenco, D.A.L., Fragomeni, B.O., Tsuruta, S., Aguilar, I., Zumbach, B., Hawken, R.J., Legarra, A., Misztal, I., 2015. Accuracy of estimated breeding values with genomic information on males, females, or both: an example on broiler chicken. Genetics Selection Evolution 47, 56.
    Ma, X., Christensen, O.F., Gao, H., Huang, R., Nielsen, B., Madsen, P., Jensen, J., Ostersen, T., Li, P., Shirali, M., et al., 2021. Prediction of breeding values for group-recorded traits including genomic information and an individually recorded correlated trait. Heredity (Edinb) 126, 206-217.
    Martin, M., 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 17, 10-12.
    Meuwissen, T.H.E., Hayes, B.J., Goddard, M.E., 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819-1829.
    Mi, B., Xiong, Y., Knoedler, S., Alfertshofer, M., Panayi, A.C., Wang, H., Lin, S., Li, G., Liu, G., 2024. Ageing-related bone and immunity changes: insights into the complex interplay between the skeleton and the immune system. Bone Res. 12, 42.
    Mitsis, T., Efthimiadou, A., Bacopoulou, F., Vlachakis, D., Chrousos, G.P., Eliopoulos, E., 2020. Transcription factors and evolution: an integral part of gene expression. World Academy of Sciences Journal 2, 3-8.
    Mrode, R.A., Thompson, R., 2005. Linear models for the prediction of animal breeding values. CABI publishing.
    Nik-Zainal, S., Davies, H., Staaf, J., Ramakrishna, M., Glodzik, D., Zou, X., Martincorena, I., Alexandrov, L.B., Martin, S., Wedge, D.C., et al., 2016. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature 534, 47-54.
    O'Haire, M., 2010. Companion animals and human health: Benefits, challenges, and the road ahead. Journal of Veterinary Behavior 5, 226-234.
    Okumura, N., Kurosawa, Y., Kobayashi, E., Watanobe, T., Ishiguro, N., Yasue, H., Mitsuhashi, T., 2001. Genetic relationship amongst the major non-coding regions of mitochondrial DNAs in wild boars and several breeds of domesticated pigs. Animal Genet. 32, 139-147.
    Per Madsen, J.J., 2013. A user’s guide to DMU. Version 6, release 5.2.
    Plaza, A., Merino, B., Sanchez-Pernaute, A., Torres-Garcia, A.J., Rubio-Herrera, M.A., Ruiz-Gayo, M., 2018. Expression analysis of a cholecystokinin system in human and rat white adipose tissue. Life sciences 206, 98-105.
    Quinlan, A.R., Hall, I.M., 2010. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842.
    Ramirez, F., Dundar, F., Diehl, S., Gruning, B.A., Manke, T., 2014. deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Res. 42, W187-191.
    Rao, S.S., Huntley, M.H., Durand, N.C., Stamenova, E.K., Bochkov, I.D., Robinson, J.T., Sanborn, A.L., Machol, I., Omer, A.D., Lander, E.S., 2014. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665-1680.
    Rentzsch, P., Witten, D., Cooper, G.M., Shendure, J., Kircher, M., 2019. CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic acids research 47, D886-D894.
    Ropka-Molik, K., Bereta, A., Tyra, M., Rozycki, M., Piorkowska, K., Szyndler-Nedza, M., Szmatola, T., 2014. Association of calpastatin gene polymorphisms and meat quality traits in pig. Meat Science 97, 143-150.
    Rubin, C.-J., Megens, H.-J., Barrio, A.M., Maqbool, K., Sayyab, S., Schwochow, D., Wang, C., Carlborg, O., Jern, P., Joergensen, C.B., 2012. Strong signatures of selection in the domestic pig genome. Proceedings of the National Academy of Sciences 109, 19529-19536.
    Servant, N., Varoquaux, N., Lajoie, B.R., Viara, E., Chen, C.J., Vert, J.P., Heard, E., Dekker, J., Barillot, E., 2015. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16, 259.
    Smigielski, E.M., Sirotkin, K., Ward, M., Sherry, S.T., 2000. dbSNP: a database of single nucleotide polymorphisms. Nucleic Acids Res. 28, 352-355.
    Sun W.K., Chi, C., Liu, R., Chen, Y.H., Zeng, K., Chen, X.H., Gu, Y.H., Li, J.L., Lv, X.B., Gao, R., 2019. Expression patterns of GHRL, GHSR, LEP, LEPR, SST and CCK genes in the gastrointestinal tissues of Tibetan and Yorkshire pigs.
    and CCK genes in the gastrointestinal tissues of Tibetan and Yorkshire pigs.
    Takayanagi, H., 2007. Osteoimmunology: shared mechanisms and crosstalk between the immune and bone systems. Nat. Rev. Immun. 7, 292-304.
    Teng, J., Gao, Y., Yin, H., Bai, Z., Liu, S., Zeng, H., Consortium, P., Bai, L., Cai, Z., Zhao, B., 2024. A compendium of genetic regulatory effects across pig tissues. Nature genetics 56 (1), 112-123.
    Vives, V., Cres, G., Richard, C., Busson, M., Ferrandez, Y., Planson, A.-G., Zeghouf, M., Cherfils, J., Malaval, L., Blangy, A., 2015. Pharmacological inhibition of Dock5 prevents osteolysis by affecting osteoclast podosome organization while preserving bone formation. Nat. Commun. 6, 6218.
    Wang, J., Dai, X., Berry, L.D., Cogan, J.D., Liu, Q., Shyr, Y., 2019. HACER: an atlas of human active enhancers to interpret regulatory variants. Nucleic Acids Res. 47, D106-D112.
    Yates, A.D., Achuthan, P., Akanni, W., Allen, J., Allen, J., Alvarez-Jarreta, J., Amode, M.R., Armean, I.M., Azov, A.G., Bennett, R., et al., 2020. Ensembl 2020. Nucleic Acids Res. 48, D682-D688.
    Yonekura, S., Kitade, K., Furukawa, G., Takahashi, K., Katsumata, N., Katoh, K., Obara, Y., 2002. Effects of aging and weaning on mRNA expression of leptin and CCK receptors in the calf rumen and abomasum. Domes. Anim. Endocrinol. 22, 25-35.
    Yu, T., Fife, J.D., Bhat, V., Adzhubey, I., Sherwood, R., Cassa, C.A., 2024. FUSE: Improving the estimation and imputation of variant impacts in functional screening. Cell Genom. 4 (10), 100667.
    Zeng, H., Zhang, W., Lin, Q., Gao, Y., Teng, J., Xu, Z., Cai, X., Zhong, Z., Wu, J., Liu, Y., 2024. PigBiobank: a valuable resource for understanding genetic and biological mechanisms of diverse complex traits in pigs. Nucleic Acids Res. 52, D980-D989.
    Zhang, F., Gu, W., Hurles, M.E., Lupski, J.R., 2009. Copy number variation in human health, disease, and evolution. Annu. Rev. Genomics Hum. Genet. 10, 451-481.
    Zhang, F., Lupski, J.R., 2015. Non-coding genetic variants in human disease. Hum. Mol. Genet. 24, R102-110.
    Zhang, K., Liang, J., Fu, Y., Chu, J., Fu, L., Wang, Y., Li, W., Zhou, Y., Li, J., Yin, X., 2024. AGIDB: a versatile database for genotype imputation and variant decoding across species. Nucleic Acids Res. 52, D835-D849.
    Zhang, K., Yuan, Z., Bing, Y., Chen, X., Ding, X., Chen, D., 2007. Effects of active immunization against cholecystokinin 8 on performance, contents of serum hormones, and expressions of CCK gene and CCK receptor gene in pigs. Endocrine 32, 338-344.
    Zhang, Y., Liu, T., Meyer, C.A., Eeckhoute, J., Johnson, D.S., Bernstein, B.E., Nusbaum, C., Myers, R.M., Brown, M., Li, W., Liu, X.S., 2008. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137.
    Zhao, Y., Hou, Y., Xu, Y., Luan, Y., Zhou, H., Qi, X., Hu, M., Wang, D., Wang, Z., Fu, Y., et al., 2021. A compendium and comparative epigenomics analysis of cis-regulatory elements in the pig genome. Nat. Commun. 12, 2217.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (25) PDF downloads (0) Cited by ()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return