{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T19:37:50Z","timestamp":1776109070365,"version":"3.50.1"},"reference-count":89,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,7,3]],"date-time":"2020-07-03T00:00:00Z","timestamp":1593734400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,7,3]],"date-time":"2020-07-03T00:00:00Z","timestamp":1593734400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100005825","name":"National Institute of Food and Agriculture","doi-asserted-by":"publisher","award":["2013-67015-20951"],"award-info":[{"award-number":["2013-67015-20951"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005825","name":"National Institute of Food and Agriculture","doi-asserted-by":"publisher","award":["2016-67015-24886"],"award-info":[{"award-number":["2016-67015-24886"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005825","name":"National Institute of Food and Agriculture","doi-asserted-by":"publisher","award":["2019-67015-29321"],"award-info":[{"award-number":["2019-67015-29321"]}],"id":[{"id":"10.13039\/100005825","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006031","name":"United States - Israel Binational Agricultural Research and Development Fund","doi-asserted-by":"publisher","award":["US-4997-17"],"award-info":[{"award-number":["US-4997-17"]}],"id":[{"id":"10.13039\/100006031","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","award":["BBS\/E\/D\/10002070"],"award-info":[{"award-number":["BBS\/E\/D\/10002070"]}],"id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","award":["BBS\/E\/D\/30002275"],"award-info":[{"award-number":["BBS\/E\/D\/30002275"]}],"id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009187","name":"Medical Research Foundation","doi-asserted-by":"publisher","award":["MR\/P015514\/1"],"award-info":[{"award-number":["MR\/P015514\/1"]}],"id":[{"id":"10.13039\/501100009187","id-type":"DOI","asserted-by":"publisher"}]},{"name":"HDR-UK","award":["HDR-9004"],"award-info":[{"award-number":["HDR-9004"]}]},{"DOI":"10.13039\/100010665","name":"H2020 Marie Sk\u0142odowska-Curie Actions","doi-asserted-by":"publisher","award":["801215"],"award-info":[{"award-number":["801215"]}],"id":[{"id":"10.13039\/100010665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Biol"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues\/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance,<jats:italic>PIK3CG<\/jats:italic>, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle.<jats:italic>ICAM<\/jats:italic>, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Collectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12915-020-00792-6","type":"journal-article","created":{"date-parts":[[2020,7,3]],"date-time":"2020-07-03T13:07:50Z","timestamp":1593781670000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human"],"prefix":"10.1186","volume":"18","author":[{"given":"Shuli","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengli","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John B.","family":"Cole","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Albert","family":"Tenesa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tara G.","family":"McDaneld","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0192-6705","authenticated-orcid":false,"given":"George E.","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingzhao","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,7,3]]},"reference":[{"key":"792_CR1","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.ajhg.2011.11.029","volume":"90","author":"PM Visscher","year":"2012","unstructured":"Visscher PM, Brown MA, McCarthy MI, Yang J. Five years of GWAS discovery. Am J Hum Genet. 2012;90:7\u201324.","journal-title":"Am J Hum Genet"},{"key":"792_CR2","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.ajhg.2017.06.005","volume":"101","author":"PM Visscher","year":"2017","unstructured":"Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, et al. 10 years of GWAS discovery: biology, function, and translation. Am J Hum Genet. 2017;101:5\u201322.","journal-title":"Am J Hum Genet"},{"key":"792_CR3","doi-asserted-by":"crossref","first-page":"D701","DOI":"10.1093\/nar\/gky1084","volume":"47","author":"ZL Hu","year":"2019","unstructured":"Hu ZL, Park CA, Reecy JM. Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB. Nucleic Acids Res. 2019;47:D701\u201310.","journal-title":"Nucleic Acids Res"},{"key":"792_CR4","doi-asserted-by":"crossref","first-page":"1748","DOI":"10.1101\/gr.136127.111","volume":"22","author":"MA Schaub","year":"2012","unstructured":"Schaub MA, Boyle AP, Kundaje A, Batzoglou S, Snyder M. Linking disease associations with regulatory information in the human genome. Genome Res. 2012;22:1748\u201359.","journal-title":"Genome Res"},{"key":"792_CR5","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1038\/s41467-018-03133-y","volume":"9","author":"L Gao","year":"2018","unstructured":"Gao L, Uzun Y, Gao P, He B, Ma XK, Wang JH, et al. Identifying noncoding risk variants using disease-relevant gene regulatory networks. Nat Commun. 2018;9:702.","journal-title":"Nat Commun"},{"key":"792_CR6","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.1038\/s41380-018-0049-x","volume":"24","author":"SM Williams","year":"2018","unstructured":"Williams SM, An JY, Edson J, Watts M, Murigneux V, Whitehouse AJO, et al. An integrative analysis of non-coding regulatory DNA variations associated with autism spectrum disorder. Mol Psychiatry. 2018;24:1707\u201319.","journal-title":"Mol Psychiatry"},{"key":"792_CR7","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1016\/j.ajhg.2018.04.002","volume":"102","author":"MD Gallagher","year":"2018","unstructured":"Gallagher MD, Chen-Plotkin AS. The post-GWAS era: from association to function. Am J Hum Genet. 2018;102:717\u201330.","journal-title":"Am J Hum Genet"},{"key":"792_CR8","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/nature11247","volume":"489","author":"EP Consortium","year":"2012","unstructured":"Consortium EP. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57\u201374.","journal-title":"Nature"},{"key":"792_CR9","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1186\/gb-2012-13-8-418","volume":"13","author":"EC Mouse","year":"2012","unstructured":"Mouse EC, Stamatoyannopoulos JA, Snyder M, Hardison R, Ren B, Gingeras T, et al. An encyclopedia of mouse DNA elements (Mouse ENCODE). Genome Biol. 2012;13:418.","journal-title":"Genome Biol"},{"key":"792_CR10","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.1126\/science.1198374","volume":"330","author":"EC mod","year":"2010","unstructured":"mod EC, Roy S, Ernst J, Kharchenko PV, Kheradpour P, Negre N, et al. Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science. 2010;330:1787\u201397.","journal-title":"Science"},{"key":"792_CR11","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1038\/nature14248","volume":"518","author":"A Kundaje","year":"2015","unstructured":"Roadmap Epigenomics Consortium, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317\u201330.","journal-title":"Nature"},{"key":"792_CR12","doi-asserted-by":"crossref","first-page":"1228","DOI":"10.1038\/ng.3404","volume":"47","author":"HK Finucane","year":"2015","unstructured":"Finucane HK, Bulik-Sullivan B, Gusev A, Trynka G, Reshef Y, Loh PR, et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat Genet. 2015;47:1228\u201335.","journal-title":"Nat Genet"},{"key":"792_CR13","doi-asserted-by":"crossref","first-page":"e144","DOI":"10.1093\/nar\/gkw627","volume":"44","author":"Y Li","year":"2016","unstructured":"Li Y, Kellis M. Joint Bayesian inference of risk variants and tissue-specific epigenomic enrichments across multiple complex human diseases. Nucleic Acids Res. 2016;44:e144.","journal-title":"Nucleic Acids Res"},{"key":"792_CR14","doi-asserted-by":"crossref","first-page":"e1005947","DOI":"10.1371\/journal.pgen.1005947","volume":"12","author":"Q Lu","year":"2016","unstructured":"Lu Q, Powles RL, Wang Q, He BJ, Zhao H. Integrative tissue-specific functional annotations in the human genome provide novel insights on many complex traits and improve signal prioritization in genome wide association studies. PLoS Genet. 2016;12:e1005947.","journal-title":"PLoS Genet"},{"key":"792_CR15","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1186\/s13059-015-0622-4","volume":"16","author":"L Andersson","year":"2015","unstructured":"Andersson L, Archibald AL, Bottema CD, Brauning R, Burgess SC, Burt DW, et al. Coordinated international action to accelerate genome-to-phenome with FAANG, the Functional Annotation of Animal Genomes project. Genome Biol. 2015;16:57.","journal-title":"Genome Biol"},{"key":"792_CR16","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1186\/s12915-019-0687-8","volume":"17","author":"L Fang","year":"2019","unstructured":"Fang L, Liu S, Liu M, Kang X, Lin S, Li B, et al. Functional annotation of the cattle genome through systematic discovery and characterization of chromatin states and butyrate-induced variations. BMC Biol. 2019;17:68.","journal-title":"BMC Biol"},{"key":"792_CR17","doi-asserted-by":"crossref","first-page":"8204","DOI":"10.1093\/nar\/gkv693","volume":"43","author":"I Hernando-Herraez","year":"2015","unstructured":"Hernando-Herraez I, Heyn H, Fernandez-Callejo M, Vidal E, Fernandez-Bellon H, Prado-Martinez J, et al. The interplay between DNA methylation and sequence divergence in recent human evolution. Nucleic Acids Res. 2015;43:8204\u201314.","journal-title":"Nucleic Acids Res"},{"key":"792_CR18","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1038\/s41588-018-0056-5","volume":"50","author":"AC Bouwman","year":"2018","unstructured":"Bouwman AC, Daetwyler HD, Chamberlain AJ, Ponce CH, Sargolzaei M, Schenkel FS, et al. Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals. Nat Genet. 2018;50:362\u20137.","journal-title":"Nat Genet"},{"key":"792_CR19","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1016\/j.cell.2012.04.029","volume":"149","author":"S Xiao","year":"2012","unstructured":"Xiao S, Xie D, Cao X, Yu P, Xing X, Chen CC, et al. Comparative epigenomic annotation of regulatory DNA. Cell. 2012;149:1381\u201392.","journal-title":"Cell."},{"key":"792_CR20","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1038\/nature13972","volume":"515","author":"AB Stergachis","year":"2014","unstructured":"Stergachis AB, Neph S, Sandstrom R, Haugen E, Reynolds AP, Zhang M, et al. Conservation of trans-acting circuitry during mammalian regulatory evolution. Nature. 2014;515:365\u201370.","journal-title":"Nature."},{"key":"792_CR21","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.cmet.2016.11.001","volume":"25","author":"M von Scheidt","year":"2017","unstructured":"von Scheidt M, Zhao Y, Kurt Z, Pan C, Zeng L, Yang X, et al. Applications and limitations of mouse models for understanding human atherosclerosis. Cell Metab. 2017;25:248\u201361.","journal-title":"Cell Metab"},{"key":"792_CR22","doi-asserted-by":"crossref","first-page":"724","DOI":"10.1186\/s12864-017-4115-6","volume":"18","author":"J Zhou","year":"2017","unstructured":"Zhou J, Sears RL, Xing X, Zhang B, Li D, Rockweiler NB, et al. Tissue-specific DNA methylation is conserved across human, mouse, and rat, and driven by primary sequence conservation. BMC Genomics. 2017;18:724.","journal-title":"BMC Genomics"},{"key":"792_CR23","doi-asserted-by":"publisher","unstructured":"Ebert P, Lengauer T, Bock C. Epigenome-based prediction of gene expression across species. bioRxiv. 2018. https:\/\/doi.org\/10.1101\/371146.","DOI":"10.1101\/371146"},{"key":"792_CR24","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1038\/s42003-019-0454-y","volume":"2","author":"J Jiang","year":"2019","unstructured":"Jiang J, Cole JB, Freebern E, Da Y, VanRaden PM, Ma L. Functional annotation and Bayesian fine-mapping reveals candidate genes for important agronomic traits in Holstein bulls. Commun Biol. 2019;2:212.","journal-title":"Commun Biol"},{"key":"792_CR25","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1186\/gb-2012-13-4-244","volume":"13","author":"KE Kemper","year":"2012","unstructured":"Kemper KE, Visscher PM, Goddard ME. Genetic architecture of body size in mammals. Genome Biol. 2012;13:244.","journal-title":"Genome Biol"},{"key":"792_CR26","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1080\/15592294.2019.1582217","volume":"14","author":"LZ Fang","year":"2019","unstructured":"Fang LZ, Zhou Y, Liu SL, Jiang JC, Bickhart DM, Null DJ, et al. Comparative analyses of sperm DNA methylomes among human, mouse and cattle provide insights into epigenomic evolution and complex traits. Epigenetics. 2019;14:260\u201376.","journal-title":"Epigenetics."},{"key":"792_CR27","doi-asserted-by":"crossref","unstructured":"Ma L, Sonstegard TS, Cole JB, VanTassell CP, Wiggans GR, Crooker BA, et al. Genome changes due to artificial selection in US Holstein cattle. BMC Genomics. 2019;20:128.","DOI":"10.1186\/s12864-019-5459-x"},{"key":"792_CR28","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1146\/annurev-animal-020518-115024","volume":"7","author":"BJ Hayes","year":"2019","unstructured":"Hayes BJ, Daetwyler HD. 1000 Bull Genomes Project to map simple and complex genetic traits in cattle: applications and outcomes. Annu Rev Anim Biosci. 2019;7:89\u2013102.","journal-title":"Annu Rev Anim Biosci"},{"key":"792_CR29","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1126\/science.1169588","volume":"324","author":"CG Elsik","year":"2009","unstructured":"Bovine Genome Sequencing and Analysis Consortium, Elsik CG, Tellam RL, Worley KC, Gibbs RA, Muzny DM, et al. The genome sequence of taurine cattle: a window to ruminant biology and evolution. Science. 2009;324:522\u20138.","journal-title":"Science"},{"key":"792_CR30","doi-asserted-by":"crossref","first-page":"e0115358","DOI":"10.1371\/journal.pone.0115358","volume":"10","author":"C Zhao","year":"2015","unstructured":"Zhao C, Carrillo JA, Tian F, Zan L, Updike SM, Zhao K, et al. Genome-wide H3K4me3 analysis in Angus cattle with divergent tenderness. PLoS One. 2015;10:e0115358.","journal-title":"PLoS One"},{"key":"792_CR31","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1016\/j.cell.2015.01.006","volume":"160","author":"D Villar","year":"2015","unstructured":"Villar D, Berthelot C, Aldridge S, Rayner TF, Lukk M, Pignatelli M, et al. Enhancer evolution across 20 mammalian species. Cell. 2015;160:554\u201366.","journal-title":"Cell."},{"key":"792_CR32","doi-asserted-by":"crossref","first-page":"2046","DOI":"10.1093\/bioinformatics\/btt343","volume":"29","author":"A Heger","year":"2013","unstructured":"Heger A, Webber C, Goodson M, Ponting CP, Lunter G. GAT: a simulation framework for testing the association of genomic intervals. Bioinformatics. 2013;29:2046\u20138.","journal-title":"Bioinformatics."},{"key":"792_CR33","doi-asserted-by":"publisher","unstructured":"Fang L, Cai W, Liu S, Canela-Xandri O, Gao Y, Jiang J, Rawlik K, Li B, Schroeder SG, Rosen BD et al. Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle. Genome Res. 2020. https:\/\/doi.org\/10.1101\/gr.250704.119. http:\/\/cattlegeneatlas.roslin.ed.ac.uk\/. Accessed 19 May 2020.","DOI":"10.1101\/gr.250704.119"},{"key":"792_CR34","doi-asserted-by":"crossref","unstructured":"Namwanje M, Brown CW. Activins and inhibins: roles in development, physiology, and disease. Cold Spring Harb Perspect Biol. 2016;8:a021881.","DOI":"10.1101\/cshperspect.a021881"},{"key":"792_CR35","doi-asserted-by":"crossref","first-page":"462","DOI":"10.18632\/oncotarget.497","volume":"3","author":"D Jjingo","year":"2012","unstructured":"Jjingo D, Conley AB, Yi SV, Lunyak VV, Jordan IK. On the presence and role of human gene-body DNA methylation. Oncotarget. 2012;3:462\u201374.","journal-title":"Oncotarget."},{"key":"792_CR36","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1016\/j.ajhg.2019.02.008","volume":"104","author":"MLA Hujoel","year":"2019","unstructured":"Hujoel MLA, Gazal S, Hormozdiari F, van de Geijn B, Price AL. Disease heritability enrichment of regulatory elements is concentrated in elements with ancient sequence age and conserved function across species. Am J Hum Genet. 2019;104:611\u201324.","journal-title":"Am J Hum Genet"},{"key":"792_CR37","first-page":"19","volume":"2","author":"C Pimentel Eda","year":"2011","unstructured":"Pimentel Eda C, Erbe M, Konig S, Simianer H. Genome partitioning of genetic variation for milk production and composition traits in Holstein cattle. Front Genet. 2011;2:19.","journal-title":"Front Genet"},{"key":"792_CR38","doi-asserted-by":"crossref","first-page":"e1007186","DOI":"10.1371\/journal.pgen.1007186","volume":"14","author":"X Hao","year":"2018","unstructured":"Hao X, Zeng P, Zhang S, Zhou X. Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies. PLoS Genet. 2018;14:e1007186.","journal-title":"PLoS Genet"},{"key":"792_CR39","doi-asserted-by":"crossref","first-page":"1284","DOI":"10.1016\/j.fertnstert.2017.04.009","volume":"107","author":"MM Hviid","year":"2017","unstructured":"Hviid MM, Macklon N. Immune modulation treatments-where is the evidence? Fertil Steril. 2017;107:1284\u201393.","journal-title":"Fertil Steril"},{"key":"792_CR40","doi-asserted-by":"crossref","first-page":"2103","DOI":"10.3168\/jds.S0022-0302(94)77153-8","volume":"77","author":"RJ Harmon","year":"1994","unstructured":"Harmon RJ. Physiology of mastitis and factors affecting somatic cell counts. J Dairy Sci. 1994;77:2103\u201312.","journal-title":"J Dairy Sci"},{"key":"792_CR41","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1111\/j.1365-2826.2008.01735.x","volume":"20","author":"PJ Brunton","year":"2008","unstructured":"Brunton PJ, Russell JA, Douglas AJ. Adaptive responses of the maternal hypothalamic-pituitary-adrenal axis during pregnancy and lactation. J Neuroendocrinol. 2008;20:764\u201376.","journal-title":"J Neuroendocrinol"},{"key":"792_CR42","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1530\/EJE-09-0923","volume":"162","author":"Z Karaca","year":"2010","unstructured":"Karaca Z, Tanriverdi F, Unluhizarci K, Kelestimur F. Pregnancy and pituitary disorders. Eur J Endocrinol. 2010;162:453\u201375.","journal-title":"Eur J Endocrinol"},{"key":"792_CR43","doi-asserted-by":"crossref","first-page":"19398","DOI":"10.1073\/pnas.1904159116","volume":"116","author":"R Xiang","year":"2019","unstructured":"Xiang R, Berg IVD, MacLeod IM, Hayes BJ, Prowse-Wilkins CP, et al. Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits. Proc Natl Acad Sci U S A. 2019;116:19398\u2013408.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"792_CR44","unstructured":"Brown C. When\u2019s She \u201cGonna\u201d Calve? https:\/\/www.canadiancattlemen.ca\/features\/whens-she-gonna-calve\/. Accessed 1 Oct 2019."},{"key":"792_CR45","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1210\/jc.2008-1288","volume":"94","author":"A Stagnaro-Green","year":"2009","unstructured":"Stagnaro-Green A. Maternal thyroid disease and preterm delivery. J Clin Endocrinol Metab. 2009;94:21\u20135.","journal-title":"J Clin Endocrinol Metab"},{"key":"792_CR46","doi-asserted-by":"crossref","first-page":"R87","DOI":"10.1530\/JOE-14-0025","volume":"221","author":"AJ Forhead","year":"2014","unstructured":"Forhead AJ, Fowden AL. Thyroid hormones in fetal growth and prepartum maturation. J Endocrinol. 2014;221:R87\u2013103.","journal-title":"J Endocrinol"},{"key":"792_CR47","doi-asserted-by":"crossref","first-page":"2113","DOI":"10.3168\/jds.S0022-0302(94)77154-X","volume":"77","author":"MM Schutz","year":"1994","unstructured":"Schutz MM. Genetic evaluation of somatic cell scores for United States dairy cattle. J Dairy Sci. 1994;77:2113\u201329.","journal-title":"J Dairy Sci"},{"key":"792_CR48","doi-asserted-by":"crossref","first-page":"1667","DOI":"10.1016\/j.cgh.2014.01.039","volume":"12","author":"AP Thrift","year":"2014","unstructured":"Thrift AP, Risch HA, Onstad L, Shaheen NJ, Casson AG, Bernstein L, et al. Risk of esophageal adenocarcinoma decreases with height, based on consortium analysis and confirmed by Mendelian randomization. Clin Gastroenterol Hepatol. 2014;12:1667\u201376.","journal-title":"Clin Gastroenterol Hepatol"},{"key":"792_CR49","doi-asserted-by":"crossref","first-page":"59","DOI":"10.5194\/aab-50-59-2007","volume":"50","author":"R Pfuhl","year":"2007","unstructured":"Pfuhl R, Bellmann O, K\u00fchn C, Teuscher F, Ender K, Wegner J. Beef versus dairy cattle: a comparison of feed conversion, carcass composition, and meat quality. Arch Anim Breed. 2007;50:59\u201370.","journal-title":"Arch Anim Breed"},{"key":"792_CR50","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.cellimm.2015.01.018","volume":"294","author":"S Kovats","year":"2015","unstructured":"Kovats S. Estrogen receptors regulate innate immune cells and signaling pathways. Cell Immunol. 2015;294:63\u20139.","journal-title":"Cell Immunol"},{"key":"792_CR51","doi-asserted-by":"crossref","first-page":"e0199931","DOI":"10.1371\/journal.pone.0199931","volume":"13","author":"A Marete","year":"2018","unstructured":"Marete A, Lund MS, Boichard D, Ramayo-Caldas Y. A system-based analysis of the genetic determinism of udder conformation and health phenotypes across three French dairy cattle breeds. PLoS One. 2018;13:e0199931.","journal-title":"PLoS One"},{"key":"792_CR52","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1038\/s41588-018-0081-4","volume":"50","author":"HK Finucane","year":"2018","unstructured":"Finucane HK, Reshef YA, Anttila V, Slowikowski K, Gusev A, Byrnes A, et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat Genet. 2018;50:621\u20139.","journal-title":"Nat Genet"},{"key":"792_CR53","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1038\/ng.377","volume":"41","author":"A K\u00f6ttgen","year":"2009","unstructured":"K\u00f6ttgen A, Glazer NL, Dehghan A, Hwang S-J, Katz R, Li M, et al. Multiple loci associated with indices of renal function and chronic kidney disease. Nat Genet. 2009;41:712\u20137.","journal-title":"Nat Genet"},{"key":"792_CR54","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1177\/2042018810380214","volume":"1","author":"S Chan","year":"2010","unstructured":"Chan S, Debono M. Replication of cortisol circadian rhythm: new advances in hydrocortisone replacement therapy. Ther Adv Endocrinol Metab. 2010;1:129\u201338.","journal-title":"Ther Adv Endocrinol Metab"},{"key":"792_CR55","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1016\/j.maturitas.2010.08.003","volume":"67","author":"CM Gameiro","year":"2010","unstructured":"Gameiro CM, Romao F, Castelo-Branco C. Menopause and aging: changes in the immune system--a review. Maturitas. 2010;67:316\u201320.","journal-title":"Maturitas."},{"key":"792_CR56","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1038\/ng.1051","volume":"44","author":"L Stolk","year":"2012","unstructured":"Stolk L, Perry JR, Chasman DI, He C, Mangino M, Sulem P, et al. Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways. Nat Genet. 2012;44:260\u20138.","journal-title":"Nat Genet"},{"key":"792_CR57","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.ypmed.2006.09.002","volume":"44","author":"JH Stubbe","year":"2007","unstructured":"Stubbe JH, de Moor MH, Boomsma DI, de Geus EJ. The association between exercise participation and well-being: a co-twin study. Prev Med. 2007;44:148\u201352.","journal-title":"Prev Med"},{"key":"792_CR58","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1160\/TH07-10-0632","volume":"99","author":"L Barberis","year":"2008","unstructured":"Barberis L, Hirsch E. Targeting phosphoinositide 3-kinase gamma to fight inflammation and more. Thromb Haemost. 2008;99:279\u201385.","journal-title":"Thromb Haemost"},{"key":"792_CR59","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1016\/j.cub.2005.02.020","volume":"15","author":"S Suire","year":"2005","unstructured":"Suire S, Coadwell J, Ferguson GJ, Davidson K, Hawkins P, Stephens L. p84, a new Gbetagamma-activated regulatory subunit of the type IB phosphoinositide 3-kinase p110gamma. Curr Biol. 2005;15:566\u201370.","journal-title":"Curr Biol"},{"key":"792_CR60","doi-asserted-by":"crossref","first-page":"260","DOI":"10.3389\/fgene.2014.00260","volume":"5","author":"EG Allen","year":"2014","unstructured":"Allen EG, Grus WE, Narayan S, Espinel W, Sherman SL. Approaches to identify genetic variants that influence the risk for onset of fragile X-associated primary ovarian insufficiency (FXPOI): a preliminary study. Front Genet. 2014;5:260.","journal-title":"Front Genet"},{"key":"792_CR61","unstructured":"Gene ATLAS. http:\/\/geneatlas.roslin.ed.ac.uk\/. Accessed 13 Dec 2019."},{"key":"792_CR62","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1086\/518569","volume":"170","author":"SS French","year":"2007","unstructured":"French SS, DeNardo DF, Moore MC. Trade-offs between the reproductive and immune systems: facultative responses to resources or obligate responses to reproduction? Am Nat. 2007;170:79\u201389.","journal-title":"Am Nat"},{"key":"792_CR63","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1530\/REP-10-0360","volume":"141","author":"JC Warning","year":"2011","unstructured":"Warning JC, McCracken SA, Morris JM. A balancing act: mechanisms by which the fetus avoids rejection by the maternal immune system. Reproduction. 2011;141:715.","journal-title":"Reproduction."},{"key":"792_CR64","first-page":"26","volume":"4","author":"GF Clark","year":"2013","unstructured":"Clark GF, Schust DJ. Manifestations of immune tolerance in the human female reproductive tract. Front Immunol. 2013;4:26.","journal-title":"Front Immunol"},{"key":"792_CR65","doi-asserted-by":"crossref","first-page":"1432","DOI":"10.1101\/gr.190603.115","volume":"25","author":"WL Lowe Jr","year":"2015","unstructured":"Lowe WL Jr, Reddy TE. Genomic approaches for understanding the genetics of complex disease. Genome Res. 2015;25:1432\u201341.","journal-title":"Genome Res"},{"key":"792_CR66","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1038\/s41467-017-02809-1","volume":"9","author":"M Naval-Sanchez","year":"2018","unstructured":"Naval-Sanchez M, Nguyen Q, McWilliam S, Porto-Neto LR, Tellam R, Vuocolo T, et al. Sheep genome functional annotation reveals proximal regulatory elements contributed to the evolution of modern breeds. Nat Commun. 2018;9:859.","journal-title":"Nat Commun"},{"key":"792_CR67","doi-asserted-by":"publisher","unstructured":"Jiang J, Cole JB, Da Y, VanRaden PM, Ma L. Fast Bayesian fine-mapping of 35 production, reproduction and body conformation traits in dairy cattle. bioRxiv. 2018. https:\/\/doi.org\/10.1101\/428227.","DOI":"10.1101\/428227"},{"key":"792_CR68","doi-asserted-by":"crossref","first-page":"2103","DOI":"10.2527\/jas.2007-0768","volume":"86","author":"GL Bennett","year":"2008","unstructured":"Bennett GL, Thallman RM, Snelling WM, Kuehn LA. Experimental selection for calving ease and postnatal growth in seven cattle populations. II. Phenotypic differences. J Anim Sci. 2008;86:2103\u201314.","journal-title":"J Anim Sci"},{"key":"792_CR69","doi-asserted-by":"crossref","first-page":"E3995","DOI":"10.1073\/pnas.1519061113","volume":"113","author":"A Garcia-Ruiz","year":"2016","unstructured":"Garcia-Ruiz A, Cole JB, VanRaden PM, Wiggans GR, Ruiz-Lopez FJ, Van Tassell CP. Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection. Proc Natl Acad Sci U S A. 2016;113:E3995\u20134004.","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"Suppl 1","key":"792_CR70","doi-asserted-by":"crossref","first-page":"1752","DOI":"10.1073\/pnas.0906182107","volume":"107","author":"A Eyre-Walker","year":"2010","unstructured":"Eyre-Walker A. Evolution in health and medicine Sackler colloquium: genetic architecture of a complex trait and its implications for fitness and genome-wide association studies. Proc Natl Acad Sci U S A. 2010;107(Suppl 1):1752\u20136.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"792_CR71","doi-asserted-by":"publisher","unstructured":"Romero IG, Gopalakrishnan S, Gilad Y. Widespread conservation of chromatin accessibility patterns and transcription factor binding in human and chimpanzee induced pluripotent stem cells. bioRxiv. 2018. https:\/\/doi.org\/10.1101\/466631.","DOI":"10.1101\/466631"},{"key":"792_CR72","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1038\/nature11082","volume":"485","author":"JR Dixon","year":"2012","unstructured":"Dixon JR, Selvaraj S, Yue F, Kim A, Li Y, Shen Y, et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature. 2012;485:376\u201380.","journal-title":"Nature."},{"key":"792_CR73","doi-asserted-by":"crossref","first-page":"1006","DOI":"10.1093\/bioinformatics\/btt730","volume":"30","author":"H Zhao","year":"2014","unstructured":"Zhao H, Sun ZF, Wang J, Huang HJ, Kocher JP, Wang LG. CrossMap: a versatile tool for coordinate conversion between genome assemblies. Bioinformatics. 2014;30:1006\u20137.","journal-title":"Bioinformatics."},{"key":"792_CR74","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1080\/10618600.1996.10474713","volume":"5","author":"R Ihaka","year":"1996","unstructured":"Ihaka R, Gentleman R. R: a language for data analysis and graphics. J Comput Graph Stat. 1996;5:299\u2013314.","journal-title":"J Comput Graph Stat"},{"key":"792_CR75","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1016\/j.tig.2012.10.012","volume":"28","author":"MD Schultz","year":"2012","unstructured":"Schultz MD, Schmitz RJ, Ecker JR. \u2018Leveling\u2019 the playing field for analyses of single-base resolution DNA methylomes. Trends Genet. 2012;28:583\u20135.","journal-title":"Trends Genet"},{"key":"792_CR76","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1186\/s12864-020-6461-z","volume":"21","author":"E Freebern","year":"2020","unstructured":"Freebern E, Santos DJ, Fang L, Jiang J, Parker Gaddis KL, Liu GE, et al. GWAS and fine-mapping of livability and six disease traits in Holstein cattle. BMC Genomics. 2020;21:41.","journal-title":"BMC Genomics"},{"key":"792_CR77","doi-asserted-by":"crossref","first-page":"11067","DOI":"10.3168\/jds.2019-16645","volume":"102","author":"B Li","year":"2019","unstructured":"Li B, Fang L, Null DJ, Hutchison JL, Connor EE, VanRaden PM, et al. High-density genome-wide association study for residual feed intake in Holstein dairy cattle. J Dairy Sci. 2019;102:11067\u201380.","journal-title":"J Dairy Sci"},{"key":"792_CR78","doi-asserted-by":"publisher","unstructured":"Rohde PD, S\u00f8rensen IF, S\u00f8rensen P. qgg: an R package for large-scale quantitative genetic analyses. Bioinformatics. 2019. https:\/\/doi.org\/10.1093\/bioinformatics\/btz955.","DOI":"10.1093\/bioinformatics\/btz955"},{"key":"792_CR79","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s12863-015-0322-9","volume":"17","author":"P Sarup","year":"2016","unstructured":"Sarup P, Jensen J, Ostersen T, Henryon M, Sorensen P. Increased prediction accuracy using a genomic feature model including prior information on quantitative trait locus regions in purebred Danish Duroc pigs. BMC Genet. 2016;17:11.","journal-title":"BMC Genet"},{"key":"792_CR80","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1186\/s12711-017-0319-0","volume":"49","author":"L Fang","year":"2017","unstructured":"Fang L, Sahana G, Ma P, Su G, Yu Y, Zhang S, et al. Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection. Genet Sel Evol. 2017;49:44.","journal-title":"Genet Sel Evol"},{"key":"792_CR81","doi-asserted-by":"crossref","first-page":"45560","DOI":"10.1038\/srep45560","volume":"7","author":"L Fang","year":"2017","unstructured":"Fang L, Sahana G, Su G, Yu Y, Zhang S, Lund MS, et al. Integrating sequence-based GWAS and RNA-Seq provides novel insights into the genetic basis of mastitis and milk production in dairy cattle. Sci Rep. 2017;7:45560.","journal-title":"Sci Rep"},{"key":"792_CR82","doi-asserted-by":"crossref","first-page":"9345","DOI":"10.1038\/s41598-018-27729-y","volume":"8","author":"L Fang","year":"2018","unstructured":"Fang L, Sorensen P, Sahana G, Panitz F, Su G, Zhang S, et al. MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle. Sci Rep. 2018;8:9345.","journal-title":"Sci Rep"},{"key":"792_CR83","doi-asserted-by":"crossref","first-page":"2413","DOI":"10.1038\/s41598-017-02281-3","volume":"7","author":"IF Sorensen","year":"2017","unstructured":"Sorensen IF, Edwards SM, Rohde PD, Sorensen P. Multiple trait covariance association test identifies gene ontology categories associated with chill coma recovery time in Drosophila melanogaster. Sci Rep. 2017;7:2413.","journal-title":"Sci Rep"},{"key":"792_CR84","doi-asserted-by":"crossref","first-page":"1901","DOI":"10.1534\/genetics.116.189498","volume":"203","author":"PD Rohde","year":"2016","unstructured":"Rohde PD, Demontis D, Cuyabano BC, Genomic Medicine for Schizophrenia Group, Borglum AD, Sorensen P. Covariance association test (CVAT) identifies genetic markers associated with schizophrenia in functionally associated biological processes. Genetics. 2016;203:1901\u201313.","journal-title":"Genetics"},{"key":"792_CR85","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1089\/omi.2011.0118","volume":"16","author":"G Yu","year":"2012","unstructured":"Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284\u20137.","journal-title":"OMICS."},{"key":"792_CR86","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1038\/ng.3286","volume":"47","author":"B Mifsud","year":"2015","unstructured":"Mifsud B, Tavares-Cadete F, Young AN, Sugar R, Schoenfelder S, Ferreira L, et al. Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C. Nat Genet. 2015;47:598\u2013606.","journal-title":"Nat Genet"},{"key":"792_CR87","doi-asserted-by":"crossref","first-page":"2511","DOI":"10.1093\/bioinformatics\/btw173","volume":"32","author":"EC Schofield","year":"2016","unstructured":"Schofield EC, Carver T, Achuthan P, Freire-Pritchett P, Spivakov M, Todd JA, et al. CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets. Bioinformatics. 2016;32:2511\u20133.","journal-title":"Bioinformatics."},{"key":"792_CR88","doi-asserted-by":"crossref","first-page":"1510","DOI":"10.1038\/s41598-018-37618-z","volume":"9","author":"AM O\u2019Doherty","year":"2019","unstructured":"O\u2019Doherty AM, Rue-Albrecht KC, Magee DA, Ahting S, Irwin RE, Hall TJ, et al. The bovine alveolar macrophage DNA methylome is resilient to infection with Mycobacterium bovis. Sci Rep. 2019;9:1510.","journal-title":"Sci Rep"},{"key":"792_CR89","doi-asserted-by":"crossref","unstructured":"Zhou Y, Connor EE, Bickhart DM, Li C, Baldwin RL, Schroeder SG, et al. Comparative whole genome DNA methylation profiling of cattle sperm and somatic tissues reveals striking hypomethylated patterns in sperm. Gigascience. 2018;7:giy039.","DOI":"10.1093\/gigascience\/giy039"}],"container-title":["BMC Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12915-020-00792-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12915-020-00792-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12915-020-00792-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T04:56:14Z","timestamp":1723179374000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbiol.biomedcentral.com\/articles\/10.1186\/s12915-020-00792-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,3]]},"references-count":89,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["792"],"URL":"https:\/\/doi.org\/10.1186\/s12915-020-00792-6","relation":{},"ISSN":["1741-7007"],"issn-type":[{"value":"1741-7007","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,3]]},"assertion":[{"value":"16 October 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 May 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 July 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Tissue samples from U.S. Holstein cattle were collected with approval of the US Department of Agriculture, Agriculture Research Service Institutional Animal Care and Use Committee under Protocol 16-016.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"80"}}