Animal Molecular Breeding 2024, Vol.14, No.2, 141-153 http://animalscipublisher.com/index.php/amb 152 Ma A.J., McDermaid A., Xu J.Z., Chang Y.Z., and Ma Q., 2020, Integrative methods and practical challenges for single-cell multi-omics, Trends in Biotechnology, 38(9): 1007-1022. https://doi.org/10.1016/j.tibtech.2020.02.013 PMID: 32818441 PMCID: PMC7442857 Mahmood U., Li X.D., Fan Y.H., Chang W., Niu Y., Li J.N., Qu C.M., and Lu K., 2022, Multi-omics revolution to promote plant breeding efficiency, Frontiers in Plant Science, 13: 1062952. https://doi.org/10.3389/fpls.2022.1062952 PMID: 36570904 PMCID: PMC9773847 Meuwissen T., Hayes B., and Goddard M., 2013, Accelerating improvement of livestock with genomic selection, Annual Review of Animal Biosciences, 1: 221-237 https://doi.org/10.1146/annurev-animal-031412-103705 PMID: 25387018 Meuwissen T., Hayes B., and Goddard M., 2016, Genomic selection: a paradigm shift in animal breeding, Animal Frontiers, 6(1): 6-14. https://doi.org/10.2527/AF.2016-0002 Mote R.S., and Filipov N.M., 2020, Use of integrative interactomics for improvement of farm animal health and welfare: an example with fescue toxicosis, Toxins, 12(10): 633. https://doi.org/10.3390/toxins12100633 PMCID: PMC7600642 PMID: 33019560 Mutenje M., Chipfupa U., Mupangwa W., Nyagumbo I., Manyawu G., Chakoma I., and Gwiriri L., 2020, Understanding breeding preferences among small-scale cattle producers: implications for livestock improvement programmes, Animal, 14(8): 1757-1767. https://doi.org/10.1017/S1751731120000592 PMID: 32252847 Pazhamala L.T., Kudapa H., Weckwerth W., Millar A.H., and Varshney R.K., 2021, Systems biology for crop improvement, The Plant Genome, 14(2): e20098. https://doi.org/10.1002/tpg2.20098 PMID: 33949787 Picard B., Berri C., Lefaucheur L., Molette C., Sayd T., and Terlouw C., 2010, Skeletal muscle proteomics in livestock production, Briefings in Functional Genomics, 9(3): 259-278. https://doi.org/10.1093/bfgp/elq005 PMID: 20308039 Qin J., Yan B., Hu Y.H., Wang P.W., and Wang J.W., 2016, Applications of integrative OMICs approaches to gene regulation studies, Quantitative Biology, 4: 283-301. https://doi.org/10.1007/s40484-016-0085-y Raza A., 2020, Metabolomics: a systems biology approach for enhancing heat stress tolerance in plants, Plant Cell Reports, 41(3): 741-763. https://doi.org/10.1007/s00299-020-02635-8 Ribeiro D.M., Salama A., Vítor A., Arguello A., Moncau C., Santos E., Caja G., Oliveira J., Balieiro J., Hernández-Castellano L., Zachut M., Poleti M., Castro N., Alves S., and Almeida A., 2020, The application of omics in ruminant production: a review in the tropical and sub-tropical animal production context, Journal of Proteomics, 227: 103905. https://doi.org/10.1016/j.jprot.2020.103905 Stanberry L., Mias G.I., Haynes W., Higdon R., Snyder M., and Kolker E., 2013, Integrative analysis of longitudinal metabolomics data from a personal multi-omics profile, Metabolites, 3(3): 741-760. https://doi.org/10.3390/metabo3030741 PMID: 24958148 PMCID: PMC3901289 Stella A., Ajmone-Marsan P., Lazzari B., and Boettcher P., 2010, Identification of selection signatures in cattle breeds selected for dairy production, Genetics, 185(4): 1451-1461. https://doi.org/10.1534/genetics.110.116111 PMID: 20479146 PMCID: PMC2927769 Subramanian I., Verma S., Kumar S., Jere A., and Anamika K., 2020, Multi-omics data integration, interpretation, and its application, Bioinformatics and Biology Insights, 14: 1177932219899051. https://doi.org/10.1177/1177932219899051 PMID: 32076369 PMCID: PMC7003173 Suravajhala P., Kogelman L.J.A., and Kadarmideen H.N., 2016, Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare, Genetics Selection Evolution, 48(1): 38. https://doi.org/10.1186/s12711-016-0217-x PMID: 27130220 PMCID: PMC4850674 Verardo L.L., Brito L.F., Carolino N., and Magalhães A.F.B., 2023, Editorial: omics applied to livestock genetics, Frontiers in Genetics, 14: 1155611. https://doi.org/10.3389/fgene.2023.1155611 PMID: 36873944 PMCID: PMC9978907
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