Section: Animal Science
Topic: Genetics/Genomics, Agricultural sciences

The big challenge for livestock genomics is to make sequence data pay

10.24072/pcjournal.300 - Peer Community Journal, Volume 3 (2023), article no. e67.

Get full text PDF Peer reviewed and recommended by PCI

This paper will argue that one of the biggest challenges for livestock genomics is to make whole-genome sequencing and functional genomics applicable to breeding practice. It discusses potential explanations for why it is so difficult to consistently improve the accuracy of genomic prediction by means of whole-genome sequence data, and three potential attacks on the problem.

Published online:
DOI: 10.24072/pcjournal.300
Type: Opinion, perspective
Keywords: genomics, animal breeding, genomic prediction, whole-genome sequence, quantitative genetics
Johnsson, Martin 1

1 Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Sweden
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights
@article{10_24072_pcjournal_300,
     author = {Johnsson, Martin},
     title = {The big challenge for livestock genomics is to make sequence data pay},
     journal = {Peer Community Journal},
     eid = {e67},
     publisher = {Peer Community In},
     volume = {3},
     year = {2023},
     doi = {10.24072/pcjournal.300},
     language = {en},
     url = {https://peercommunityjournal.org/articles/10.24072/pcjournal.300/}
}
TY  - JOUR
AU  - Johnsson, Martin
TI  - The big challenge for livestock genomics is to make sequence data pay
JO  - Peer Community Journal
PY  - 2023
VL  - 3
PB  - Peer Community In
UR  - https://peercommunityjournal.org/articles/10.24072/pcjournal.300/
DO  - 10.24072/pcjournal.300
LA  - en
ID  - 10_24072_pcjournal_300
ER  - 
%0 Journal Article
%A Johnsson, Martin
%T The big challenge for livestock genomics is to make sequence data pay
%J Peer Community Journal
%D 2023
%V 3
%I Peer Community In
%U https://peercommunityjournal.org/articles/10.24072/pcjournal.300/
%R 10.24072/pcjournal.300
%G en
%F 10_24072_pcjournal_300
Johnsson, Martin. The big challenge for livestock genomics is to make sequence data pay. Peer Community Journal, Volume 3 (2023), article  no. e67. doi : 10.24072/pcjournal.300. https://peercommunityjournal.org/articles/10.24072/pcjournal.300/

PCI peer reviews and recommendation, and links to data, scripts, code and supplementary information: 10.24072/pci.animsci.100192

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

[1] Abell, N. S.; DeGorter, M. K.; Gloudemans, M. J.; Greenwald, E.; Smith, K. S.; He, Z.; Montgomery, S. B. Multiple causal variants underlie genetic associations in humans, Science, Volume 375 (2022) no. 6586, pp. 1247-1254 | DOI

[2] van den Berg, I.; Bowman, P. J.; MacLeod, I. M.; Hayes, B. J.; Wang, T.; Bolormaa, S.; Goddard, M. E. Multi-breed genomic prediction using Bayes R with sequence data and dropping variants with a small effect, Genetics Selection Evolution, Volume 49 (2017) no. 1 | DOI

[3] van Binsbergen, R.; Calus, M. P. L.; Bink, M. C. A. M.; van Eeuwijk, F. A.; Schrooten, C.; Veerkamp, R. F. Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle, Genetics Selection Evolution, Volume 47 (2015) no. 1 | DOI

[4] Brard, S.; Ricard, A. Is the use of formulae a reliable way to predict the accuracy of genomic selection?, Journal of Animal Breeding and Genetics, Volume 132 (2015) no. 3, pp. 207-217 | DOI

[5] Brøndum, R.; Su, G.; Janss, L.; Sahana, G.; Guldbrandtsen, B.; Boichard, D.; Lund, M. Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction, Journal of Dairy Science, Volume 98 (2015) no. 6, pp. 4107-4116 | DOI

[6] Browning, B. L.; Browning, S. R. Efficient multilocus association testing for whole genome association studies using localized haplotype clustering, Genetic Epidemiology, Volume 31 (2007) no. 5, pp. 365-375 | DOI

[7] Browning, B. L.; Tian, X.; Zhou, Y.; Browning, S. R. Fast two-stage phasing of large-scale sequence data, The American Journal of Human Genetics, Volume 108 (2021) no. 10, pp. 1880-1890 | DOI

[8] Browning, B. L.; Zhou, Y.; Browning, S. R. A One-Penny Imputed Genome from Next-Generation Reference Panels, The American Journal of Human Genetics, Volume 103 (2018) no. 3, pp. 338-348 | DOI

[9] Butty, A. M.; Chud, T. C. S.; Miglior, F.; Schenkel, F. S.; Kommadath, A.; Krivushin, K.; Grant, J. R.; Häfliger, I. M.; Drögemüller, C.; Cánovas, A.; Stothard, P.; Baes, C. F. High confidence copy number variants identified in Holstein dairy cattle from whole genome sequence and genotype array data, Scientific Reports, Volume 10 (2020) no. 1 | DOI

[10] Calus, M. P. L.; Bouwman, A. C.; Schrooten, C.; Veerkamp, R. F. Efficient genomic prediction based on whole-genome sequence data using split-and-merge Bayesian variable selection, Genetics Selection Evolution, Volume 48 (2016) no. 1 | DOI

[11] Chen, L.; Pryce, J. E.; Hayes, B. J.; Daetwyler, H. D. Investigating the Effect of Imputed Structural Variants from Whole-Genome Sequence on Genome-Wide Association and Genomic Prediction in Dairy Cattle, Animals, Volume 11 (2021) no. 2 | DOI

[12] Chiang, C.; Scott, A. J.; Davis, J. R.; Tsang, E. K.; Li, X.; Kim, Y.; Hadzic, T.; Damani, F. N.; Ganel, L.; Montgomery, S. B.; Battle, A.; Conrad, D. F.; Hall, I. M. The impact of structural variation on human gene expression, Nature Genetics, Volume 49 (2017) no. 5, pp. 692-699 | DOI

[13] Clark, S. A.; Hickey, J. M.; van der Werf, J. H. Different models of genetic variation and their effect on genomic evaluation, Genetics Selection Evolution, Volume 43 (2011) no. 1 | DOI

[14] Conrad, D. F.; Hurles, M. E. The population genetics of structural variation, Nature Genetics, Volume 39 (2007) no. S7 | DOI

[15] Cuyabano, B. C.; Su, G.; Lund, M. S. Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population, BMC Genomics, Volume 15 (2014) no. 1 | DOI

[16] Cuyabano, B. C.; Su, G.; Lund, M. S. Selection of haplotype variables from a high-density marker map for genomic prediction, Genetics Selection Evolution, Volume 47 (2015) no. 1 | DOI

[17] Daetwyler, H. D.; Capitan, A.; Pausch, H.; Stothard, P.; van Binsbergen, R.; Brøndum, R. F.; Liao, X.; Djari, A.; Rodriguez, S. C.; Grohs, C.; Esquerré, D.; Bouchez, O.; Rossignol, M.-N.; Klopp, C.; Rocha, D.; Fritz, S.; Eggen, A.; Bowman, P. J.; Coote, D.; Chamberlain, A. J.; Anderson, C.; VanTassell, C. P.; Hulsegge, I.; Goddard, M. E.; Guldbrandtsen, B.; Lund, M. S.; Veerkamp, R. F.; Boichard, D. A.; Fries, R.; Hayes, B. J. Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle, Nature Genetics, Volume 46 (2014) no. 8, pp. 858-865 | DOI

[18] Dekkers, J. C. M. Commercial application of marker- and gene-assisted selection in livestock: Strategies and lessons1,2 , Journal of Animal Science, Volume 82 (2004) | DOI

[19] Delaneau, O.; Zagury, J.-F.; Robinson, M. R.; Marchini, J. L.; Dermitzakis, E. T. Accurate, scalable and integrative haplotype estimation, Nature Communications, Volume 10 (2019) no. 1 | DOI

[20] Derks, M.; Boshove, A.; Harlizius, B.; Sell-Kubiak, E.; Lopes, M.; Grindflek, E.; Knol, E.; Groenen, M.; Gjuvsland, A. 564. A pan-genome of commercial pig breeds, Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP) (2022) | DOI

[21] Dorshorst, B.; Molin, A.-M.; Rubin, C.-J.; Johansson, A. M.; Strömstedt, L.; Pham, M.-H.; Chen, C.-F.; Hallböök, F.; Ashwell, C.; Andersson, L. A Complex Genomic Rearrangement Involving the Endothelin 3 Locus Causes Dermal Hyperpigmentation in the Chicken, PLoS Genetics, Volume 7 (2011) no. 12 | DOI

[22] Durkin, K.; Coppieters, W.; Drögemüller, C.; Ahariz, N.; Cambisano, N.; Druet, T.; Fasquelle, C.; Haile, A.; Horin, P.; Huang, L.; Kamatani, Y.; Karim, L.; Lathrop, M.; Moser, S.; Oldenbroek, K.; Rieder, S.; Sartelet, A.; Sölkner, J.; Stålhammar, H.; Zelenika, D.; Zhang, Z.; Leeb, T.; Georges, M.; Charlier, C. Serial translocation by means of circular intermediates underlies colour sidedness in cattle, Nature, Volume 482 (2012) no. 7383, pp. 81-84 | DOI

[23] Ebert, P.; Audano, P. A.; Zhu, Q.; Rodriguez-Martin, B.; Porubsky, D.; Bonder, M. J.; Sulovari, A.; Ebler, J.; Zhou, W.; Serra Mari, R.; Yilmaz, F.; Zhao, X.; Hsieh, P.; Lee, J.; Kumar, S.; Lin, J.; Rausch, T.; Chen, Y.; Ren, J.; Santamarina, M.; Höps, W.; Ashraf, H.; Chuang, N. T.; Yang, X.; Munson, K. M.; Lewis, A. P.; Fairley, S.; Tallon, L. J.; Clarke, W. E.; Basile, A. O.; Byrska-Bishop, M.; Corvelo, A.; Evani, U. S.; Lu, T.-Y.; Chaisson, M. J. P.; Chen, J.; Li, C.; Brand, H.; Wenger, A. M.; Ghareghani, M.; Harvey, W. T.; Raeder, B.; Hasenfeld, P.; Regier, A. A.; Abel, H. J.; Hall, I. M.; Flicek, P.; Stegle, O.; Gerstein, M. B.; Tubio, J. M. C.; Mu, Z.; Li, Y. I.; Shi, X.; Hastie, A. R.; Ye, K.; Chong, Z.; Sanders, A. D.; Zody, M. C.; Talkowski, M. E.; Mills, R. E.; Devine, S. E.; Lee, C.; Korbel, J. O.; Marschall, T.; Eichler, E. E. Haplotype-resolved diverse human genomes and integrated analysis of structural variation, Science, Volume 372 (2021) no. 6537 | DOI

[24] Ebler, J.; Ebert, P.; Clarke, W. E.; Rausch, T.; Audano, P. A.; Houwaart, T.; Mao, Y.; Korbel, J. O.; Eichler, E. E.; Zody, M. C.; Dilthey, A. T.; Marschall, T. Pangenome-based genome inference allows efficient and accurate genotyping across a wide spectrum of variant classes, Nature Genetics, Volume 54 (2022) no. 4, pp. 518-525 | DOI

[25] Edriss, V.; Fernando, R. L.; Su, G.; Lund, M. S.; Guldbrandtsen, B. The effect of using genealogy-based haplotypes for genomic prediction, Genetics Selection Evolution, Volume 45 (2013) no. 1 | DOI

[26] Erbe, M.; Hayes, B.; Matukumalli, L.; Goswami, S.; Bowman, P.; Reich, C.; Mason, B.; Goddard, M. Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels, Journal of Dairy Science, Volume 95 (2012) no. 7, pp. 4114-4129 | DOI

[27] Falconer, D. S.; Mackay, T. F. C. Introduction to Quantitative Genetics. , Benjamin-Cummings Pub Co, Harlow, 1996

[28] Fernando, R.; Grossman, M. Marker assisted selection using best linear unbiased prediction, Genetics Selection Evolution, Volume 21 (1989) no. 4 | DOI

[29] Fragomeni, B. O.; Lourenco, D. A. L.; Masuda, Y.; Legarra, A.; Misztal, I. Incorporation of causative quantitative trait nucleotides in single-step GBLUP, Genetics Selection Evolution, Volume 49 (2017) no. 1 | DOI

[30] Geibel, J.; Praefke, N. P.; Weigend, S.; Simianer, H.; Reimer, C. Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations, BMC Genomics, Volume 23 (2022) no. 1 | DOI

[31] Geibel, J.; Reimer, C.; Pook, T.; Weigend, S.; Weigend, A.; Simianer, H. How imputation can mitigate SNP ascertainment Bias, BMC Genomics, Volume 22 (2021) no. 1 | DOI

[32] Georges, M.; Charlier, C.; Hayes, B. Harnessing genomic information for livestock improvement, Nature Reviews Genetics, Volume 20 (2019) no. 3, pp. 135-156 | DOI

[33] Giuffra, E.; Tuggle, C. K. Functional Annotation of Animal Genomes (FAANG): Current Achievements and Roadmap, Annual Review of Animal Biosciences, Volume 7 (2019) no. 1, pp. 65-88 | DOI

[34] Goddard, M. Genomic selection: prediction of accuracy and maximisation of long term response, Genetica, Volume 136 (2009) no. 2, pp. 245-257 | DOI

[35] Goddard, M.; Hayes, B.; Meuwissen, T. Using the genomic relationship matrix to predict the accuracy of genomic selection, Journal of Animal Breeding and Genetics, Volume 128 (2011) no. 6, pp. 409-421 | DOI

[36] Gunnarsson, U.; Kerje, S.; Bed’hom, B.; Sahlqvist, A.-S.; Ekwall, O.; Tixier-Boichard, M.; Kämpe, O.; Andersson, L. The Dark brown plumage color in chickens is caused by an 8.3-kb deletion upstream of SOX10, Pigment Cell & Melanoma Research, Volume 24 (2011) no. 2, pp. 268-274 | DOI

[37] Habier, D.; Fernando, R. L.; Dekkers, J. C. M. The Impact of Genetic Relationship Information on Genome-Assisted Breeding Values, Genetics, Volume 177 (2007) no. 4, pp. 2389-2397 | DOI

[38] Habier, D.; Fernando, R. L.; Garrick, D. J. Genomic BLUP Decoded: A Look into the Black Box of Genomic Prediction, Genetics, Volume 194 (2013) no. 3, pp. 597-607 | DOI

[39] Haley, C.; Visscher, P. Strategies to Utilize Marker-Quantitative Trait Loci Associations, Journal of Dairy Science, Volume 81 (1998), pp. 85-97 | DOI

[40] 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.; Zhou, H.; Ross, P. J. A comparative analysis of chromatin accessibility in cattle, pig, and mouse tissues, BMC Genomics, Volume 21 (2020) no. 1 | DOI

[41] Hayes, B. J.; Daetwyler, H. D. 1000 Bull Genomes Project to Map Simple and Complex Genetic Traits in Cattle: Applications and Outcomes, Annual Review of Animal Biosciences, Volume 7 (2019) no. 1, pp. 89-102 | DOI

[42] Hickey, J. M. Sequencing millions of animals for genomic selection 2.0, Journal of Animal Breeding and Genetics, Volume 130 (2013) no. 5, pp. 331-332 | DOI

[43] Hickey, J. M.; Chiurugwi, T.; Mackay, I.; Powell, W. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery, Nature Genetics, Volume 49 (2017) no. 9, pp. 1297-1303 | DOI

[44] Hickey, G.; Heller, D.; Monlong, J.; Sibbesen, J. A.; Sirén, J.; Eizenga, J.; Dawson, E. T.; Garrison, E.; Novak, A. M.; Paten, B. Genotyping structural variants in pangenome graphs using the vg toolkit, Genome Biology, Volume 21 (2020) no. 1 | DOI

[45] Hickey, J.; Kinghorn, B.; Tier, B.; Clark, S.; van der Werf, J.; Gorjanc, G. Genomic evaluations using similarity between haplotypes, Journal of Animal Breeding and Genetics, Volume 130 (2013) no. 4, pp. 259-269 | DOI

[46] Ilska, J. J. Understanding genomic prediction in chickens, Royal (Dick) School of Veterinary Studies thesis and dissertation collection (2015) (http://hdl.handle.net/1842/15876)

[47] Imsland, F.; Feng, C.; Boije, H.; Bed'hom, B.; Fillon, V.; Dorshorst, B.; Rubin, C.-J.; Liu, R.; Gao, Y.; Gu, X.; Wang, Y.; Gourichon, D.; Zody, M. C.; Zecchin, W.; Vieaud, A.; Tixier-Boichard, M.; Hu, X.; Hallböök, F.; Li, N.; Andersson, L. The Rose-comb Mutation in Chickens Constitutes a Structural Rearrangement Causing Both Altered Comb Morphology and Defective Sperm Motility, PLoS Genetics, Volume 8 (2012) no. 6 | DOI

[48] Jang, S.; Tsuruta, S.; Leite, N. G.; Misztal, I.; Lourenco, D. Dimensionality of genomic information and its impact on genome-wide associations and variant selection for genomic prediction: a simulation study, Genetics Selection Evolution, Volume 55 (2023) no. 1 | DOI

[49] Kadri, N. K.; Sahana, G.; Charlier, C.; Iso-Touru, T.; Guldbrandtsen, B.; Karim, L.; Nielsen, U. S.; Panitz, F.; Aamand, G. P.; Schulman, N.; Georges, M.; Vilkki, J.; Lund, M. S.; Druet, T. A 660-Kb Deletion with Antagonistic Effects on Fertility and Milk Production Segregates at High Frequency in Nordic Red Cattle: Additional Evidence for the Common Occurrence of Balancing Selection in Livestock, PLoS Genetics, Volume 10 (2014) no. 1 | DOI

[50] Kelleher, J.; Wong, Y.; Wohns, A. W.; Fadil, C.; Albers, P. K.; McVean, G. Inferring whole-genome histories in large population datasets, Nature Genetics, Volume 51 (2019) no. 9, pp. 1330-1338 | DOI

[51] Kern, C.; Wang, Y.; Xu, X.; Pan, Z.; Halstead, M.; Chanthavixay, G.; Saelao, P.; Waters, S.; Xiang, R.; Chamberlain, A.; Korf, I.; Delany, M. E.; Cheng, H. H.; Medrano, J. F.; Van Eenennaam, A. L.; Tuggle, C. K.; Ernst, C.; Flicek, P.; Quon, G.; Ross, P.; Zhou, H. Functional annotations of three domestic animal genomes provide vital resources for comparative and agricultural research, Nature Communications, Volume 12 (2021) no. 1 | DOI

[52] Knol, E. F.; Nielsen, B.; Knap, P. W. Genomic selection in commercial pig breeding, Animal Frontiers, Volume 6 (2016) no. 1, pp. 15-22 | DOI

[53] Lande, R.; Thompson, R. Efficiency of marker-assisted selection in the improvement of quantitative traits., Genetics, Volume 124 (1990) no. 3, pp. 743-756 | DOI

[54] Legarra, A.; Garcia-Baccino, C. A.; Wientjes, Y. C. J.; Vitezica, Z. G. The correlation of substitution effects across populations and generations in the presence of nonadditive functional gene action, Genetics, Volume 219 (2021) no. 4 | DOI

[55] Leonard, A. S.; Crysnanto, D.; Fang, Z.-H.; Heaton, M. P.; Vander Ley, B. L.; Herrera, C.; Bollwein, H.; Bickhart, D. M.; Kuhn, K. L.; Smith, T. P. L.; Rosen, B. D.; Pausch, H. Structural variant-based pangenome construction has low sensitivity to variability of haplotype-resolved bovine assemblies, Nature Communications, Volume 13 (2022) no. 1 | DOI

[56] Littlejohn, M.; Lopdell, T.; Trevarton, A.; Moody, J.; Tiplady, K.; Burborough, K.; Prowse-Wilkins, C.; Chamberlain, A.; Goddard, M.; Snell, R. 534. A massively parallel reporter assay to screen bovine regulatory variants, Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP) (2022) | DOI

[57] Liu, S.; Gao, Y.; Canela-Xandri, O.; Wang, S.; Yu, Y.; Cai, W.; Li, B.; Xiang, R.; Chamberlain, A. J.; Pairo-Castineira, E.; D’Mellow, K.; Rawlik, K.; Xia, C.; Yao, Y.; Navarro, P.; Rocha, D.; Li, X.; Yan, Z.; Li, C.; Rosen, B. D.; Van Tassell, C. P.; Vanraden, P. M.; Zhang, S.; Ma, L.; Cole, J. B.; Liu, G. E.; Tenesa, A.; Fang, L. A multi-tissue atlas of regulatory variants in cattle, Nature Genetics, Volume 54 (2022) no. 9, pp. 1438-1447 | DOI

[58] Liu, L.; Sanderford, M. D.; Patel, R.; Chandrashekar, P.; Gibson, G.; Kumar, S. Biological relevance of computationally predicted pathogenicity of noncoding variants, Nature Communications, Volume 10 (2019) no. 1 | DOI

[59] Lowe, J. W. E.; Bruce, A. Genetics without genes? The centrality of genetic markers in livestock genetics and genomics, History and Philosophy of the Life Sciences, Volume 41 (2019) no. 4 | DOI

[60] MacLeod, I. M.; Hayes, B. J.; Goddard, M. E. The Effects of Demography and Long-Term Selection on the Accuracy of Genomic Prediction with Sequence Data, Genetics, Volume 198 (2014) no. 4, pp. 1671-1684 | DOI

[61] Meuwissen, T.; van den Berg, I.; Goddard, M. On the use of whole-genome sequence data for across-breed genomic prediction and fine-scale mapping of QTL, Genetics Selection Evolution, Volume 53 (2021) no. 1 | DOI

[62] Meuwissen, T.; Goddard, M. Accurate Prediction of Genetic Values for Complex Traits by Whole-Genome Resequencing, Genetics, Volume 185 (2010) no. 2, pp. 623-631 | DOI

[63] Meuwissen, T. H. E.; Hayes, B. J.; Goddard, M. E. Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps, Genetics, Volume 157 (2001) no. 4, pp. 1819-1829 | DOI

[64] Mishra, N. A.; Drögemüller, C.; Jagannathan, V.; Keller, I.; Wüthrich, D.; Bruggmann, R.; Beck, J.; Schütz, E.; Brenig, B.; Demmel, S.; Moser, S.; Signer-Hasler, H.; Pieńkowska-Schelling, A.; Schelling, C.; Sande, M.; Rongen, R.; Rieder, S.; Kelsh, R. N.; Mercader, N.; Leeb, T. A structural variant in the 5’-flanking region of the TWIST2 gene affects melanocyte development in belted cattle, PLOS ONE, Volume 12 (2017) no. 6 | DOI

[65] Misztal, I.; Lourenco, D.; Legarra, A. Current status of genomic evaluation, Journal of Animal Science, Volume 98 (2020) no. 4 | DOI

[66] Misztal, I.; Steyn, Y.; Lourenco, D. Genomic evaluation with multibreed and crossbred data, JDS Communications, Volume 3 (2022) no. 2, pp. 156-159 | DOI

[67] Moghaddar, N.; Khansefid, M.; van der Werf, J. H. J.; Bolormaa, S.; Duijvesteijn, N.; Clark, S. A.; Swan, A. A.; Daetwyler, H. D.; MacLeod, I. M. Genomic prediction based on selected variants from imputed whole-genome sequence data in Australian sheep populations, Genetics Selection Evolution, Volume 51 (2019) no. 1 | DOI

[68] Mullen, M. P.; McClure, M. C.; Kearney, J. F.; Waters, S. M.; Weld, R.; Flynn, P.; Creevey, C. J.; Cromie, A. R.; Berry, D. P. Development of a custom SNP chip for dairy and beef cattle breeding, parentage and research, Interbull Bulletin (2013)

[69] Nejati-Javaremi, A.; Smith, C.; Gibson, J. P. Effect of total allelic relationship on accuracy of evaluation and response to selection., Journal of Animal Science, Volume 75 (1997) no. 7 | DOI

[70] Nguyen, T. V.; Vander Jagt, C. J.; Wang, J.; Daetwyler, H. D.; Xiang, R.; Goddard, M. E.; Nguyen, L. T.; Ross, E. M.; Hayes, B. J.; Chamberlain, A. J.; MacLeod, I. M. In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants, Genetics Selection Evolution, Volume 55 (2023) no. 1 | DOI

[71] Oppong, R. F.; Boutin, T.; Campbell, A.; McIntosh, A. M.; Porteous, D.; Hayward, C.; Haley, C. S.; Navarro, P.; Knott, S. SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): Joint Mapping of Common and Rare Variation Affecting Complex Traits, Frontiers in Genetics, Volume 12 (2022) | DOI

[72] Pérez-Enciso, M.; Rincón, J. C.; Legarra, A. Sequence- vs. chip-assisted genomic selection: accurate biological information is advised, Genetics Selection Evolution, Volume 47 (2015) no. 1 | DOI

[73] Pocrnic, I.; Lourenco, D. A. L.; Masuda, Y.; Legarra, A.; Misztal, I. The Dimensionality of Genomic Information and Its Effect on Genomic Prediction, Genetics, Volume 203 (2016) no. 1, pp. 573-581 | DOI

[74] Pocrnic, I.; Lourenco, D. A. L.; Masuda, Y.; Misztal, I. Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species, Genetics Selection Evolution, Volume 48 (2016) no. 1 | DOI

[75] Pocrnic, I.; Lourenco, D. A. L.; Masuda, Y.; Misztal, I. Accuracy of genomic BLUP when considering a genomic relationship matrix based on the number of the largest eigenvalues: a simulation study, Genetics Selection Evolution, Volume 51 (2019) no. 1 | DOI

[76] Pook, T.; Freudenthal, J.; Korte, A.; Simianer, H. Using Local Convolutional Neural Networks for Genomic Prediction, Frontiers in Genetics, Volume 11 (2020) | DOI

[77] Pook, T.; Schlather, M.; de los Campos, G.; Mayer, M.; Schoen, C. C.; Simianer, H. HaploBlocker: Creation of Subgroup-Specific Haplotype Blocks and Libraries, Genetics, Volume 212 (2019) no. 4, pp. 1045-1061 | DOI

[78] Prowse-Wilkins, C. P.; Lopdell, T. J.; Xiang, R.; Vander Jagt, C. J.; Littlejohn, M. D.; Chamberlain, A. J.; Goddard, M. E. Genetic variation in histone modifications and gene expression identifies regulatory variants in the mammary gland of cattle, BMC Genomics, Volume 23 (2022) no. 1 | DOI

[79] Pszczoła, M. The price of sequencing the livestock genomics, Peer Community in Animal Science (2023) | DOI

[80] Ragoussis, J. Genotyping Technologies for Genetic Research, Annual Review of Genomics and Human Genetics, Volume 10 (2009) no. 1, pp. 117-133 | DOI

[81] Raymond, B.; Bouwman, A. C.; Schrooten, C.; Houwing-Duistermaat, J.; Veerkamp, R. F. Utility of whole-genome sequence data for across-breed genomic prediction, Genetics Selection Evolution, Volume 50 (2018) no. 1 | DOI

[82] Raymond, B.; Bouwman, A. C.; Wientjes, Y. C. J.; Schrooten, C.; Houwing-Duistermaat, J.; Veerkamp, R. F. Genomic prediction for numerically small breeds, using models with pre-selected and differentially weighted markers, Genetics Selection Evolution, Volume 50 (2018) no. 1 | DOI

[83] Ros-Freixedes, R.; Battagin, M.; Johnsson, M.; Gorjanc, G.; Mileham, A. J.; Rounsley, S. D.; Hickey, J. M. Impact of index hopping and bias towards the reference allele on accuracy of genotype calls from low-coverage sequencing, Genetics Selection Evolution, Volume 50 (2018) no. 1 | DOI

[84] Ros-Freixedes, R.; Johnsson, M.; Whalen, A.; Chen, C.-Y.; Valente, B. D.; Herring, W. O.; Gorjanc, G.; Hickey, J. M. Genomic prediction with whole-genome sequence data in intensely selected pig lines, Genetics Selection Evolution, Volume 54 (2022) no. 1 | DOI

[85] Ros-Freixedes, R.; Valente, B. D.; Chen, C.-Y.; Herring, W. O.; Gorjanc, G.; Hickey, J. M.; Johnsson, M. Rare and population-specific functional variation across pig lines, Genetics Selection Evolution, Volume 54 (2022) no. 1 | DOI

[86] Ros-Freixedes, R.; Whalen, A.; Chen, C.-Y.; Gorjanc, G.; Herring, W. O.; Mileham, A. J.; Hickey, J. M. Accuracy of whole-genome sequence imputation using hybrid peeling in large pedigreed livestock populations, Genetics Selection Evolution, Volume 52 (2020) no. 1 | DOI

[87] Rubin, C.-J.; Megens, H.-J.; Barrio, A. M.; Maqbool, K.; Sayyab, S.; Schwochow, D.; Wang, C.; Carlborg, Ö.; Jern, P.; Jørgensen, C. B.; Archibald, A. L.; Fredholm, M.; Groenen, M. A. M.; Andersson, L. Strong signatures of selection in the domestic pig genome, Proceedings of the National Academy of Sciences, Volume 109 (2012) no. 48, pp. 19529-19536 | DOI

[88] Salavati, M.; Woolley, S. A.; Cortés Araya, Y.; Halstead, M. M.; Stenhouse, C.; Johnsson, M.; Ashworth, C. J.; Archibald, A. L.; Donadeu, F. X.; Hassan, M. A.; Clark, E. L. Profiling of open chromatin in developing pig (Sus scrofa) muscle to identify regulatory regions, G3 Genes|Genomes|Genetics, Volume 12 (2022) no. 2 | DOI

[89] Schütz, E.; Scharfenstein, M.; Brenig, B. Implication of Complex Vertebral Malformation and Bovine Leukocyte Adhesion Deficiency DNA-Based Testing on Disease Frequency in the Holstein Population, Journal of Dairy Science, Volume 91 (2008) no. 12, pp. 4854-4859 | DOI

[90] Selle, M. L.; Steinsland, I.; Lindgren, F.; Brajkovic, V.; Cubric-Curik, V.; Gorjanc, G. Hierarchical Modelling of Haplotype Effects on a Phylogeny, Frontiers in Genetics, Volume 11 (2021) | DOI

[91] Smith, C. Improvement of metric traits through specific genetic loci, Animal Science, Volume 9 (1967) no. 3, pp. 349-358 | DOI

[92] Snelling, W. M.; Hoff, J. L.; Li, J. H.; Kuehn, L. A.; Keel, B. N.; Lindholm-Perry, A. K.; Pickrell, J. K. Assessment of Imputation from Low-Pass Sequencing to Predict Merit of Beef Steers, Genes, Volume 11 (2020) no. 11 | DOI

[93] Soller, M. The use of loci associated with quantitative effects in dairy cattle improvement, Animal Science, Volume 27 (1978) no. 2, pp. 133-139 | DOI

[94] Stam, P. The distribution of the fraction of the genome identical by descent in finite random mating populations, Genetical Research, Volume 35 (1980) no. 2, pp. 131-155 | DOI

[95] Sudmant, P. H.; Rausch, T.; Gardner, E. J.; Handsaker, R. E.; Abyzov, A.; Huddleston, J.; Zhang, Y.; Ye, K.; Jun, G.; Hsi-Yang Fritz, M.; Konkel, M. K.; Malhotra, A.; Stütz, A. M.; Shi, X.; Paolo Casale, F.; Chen, J.; Hormozdiari, F.; Dayama, G.; Chen, K.; Malig, M.; Chaisson, M. J. P.; Walter, K.; Meiers, S.; Kashin, S.; Garrison, E.; Auton, A.; Lam, H. Y. K.; Jasmine Mu, X.; Alkan, C.; Antaki, D.; Bae, T.; Cerveira, E.; Chines, P.; Chong, Z.; Clarke, L.; Dal, E.; Ding, L.; Emery, S.; Fan, X.; Gujral, M.; Kahveci, F.; Kidd, J. M.; Kong, Y.; Lameijer, E.-W.; McCarthy, S.; Flicek, P.; Gibbs, R. A.; Marth, G.; Mason, C. E.; Menelaou, A.; Muzny, D. M.; Nelson, B. J.; Noor, A.; Parrish, N. F.; Pendleton, M.; Quitadamo, A.; Raeder, B.; Schadt, E. E.; Romanovitch, M.; Schlattl, A.; Sebra, R.; Shabalin, A. A.; Untergasser, A.; Walker, J. A.; Wang, M.; Yu, F.; Zhang, C.; Zhang, J.; Zheng-Bradley, X.; Zhou, W.; Zichner, T.; Sebat, J.; Batzer, M. A.; McCarroll, S. A.; Mills, R. E.; Gerstein, M. B.; Bashir, A.; Stegle, O.; Devine, S. E.; Lee, C.; Eichler, E. E.; Korbel, J. O. An integrated map of structural variation in 2,504 human genomes, Nature, Volume 526 (2015) no. 7571, pp. 75-81 | DOI

[96] Sved, J. Linkage disequilibrium and homozygosity of chromosome segments in finite populations, Theoretical Population Biology, Volume 2 (1971) no. 2, pp. 125-141 | DOI

[97] Talenti, A.; Powell, J.; Hemmink, J. D.; Cook, E. A. J.; Wragg, D.; Jayaraman, S.; Paxton, E.; Ezeasor, C.; Obishakin, E. T.; Agusi, E. R.; Tijjani, A.; Amanyire, W.; Muhanguzi, D.; Marshall, K.; Fisch, A.; Ferreira, B. R.; Qasim, A.; Chaudhry, U.; Wiener, P.; Toye, P.; Morrison, L. J.; Connelley, T.; Prendergast, J. G. D. A cattle graph genome incorporating global breed diversity, Nature Communications, Volume 13 (2022) no. 1 | DOI

[98] The FarmGTEx-PigGTEx Consortium,; Teng, J.; Gao, Y.; Yin, H.; Bai, Z.; Liu, S.; Zeng, H.; Bai, L.; Cai, Z.; Zhao, B.; Li, X.; Xu, Z.; Lin, Q.; Pan, Z.; Yang, W.; Yu, X.; Guan, D.; Hou, Y.; Keel, B. N.; Rohrer, G. A.; Lindholm-Perry, A. K.; Oliver, W. T.; Ballester, M.; Crespo-Piazuelo, D.; Quintanilla, R.; Canela-Xandri, O.; Rawlik, K.; Xia, C.; Yao, Y.; Zhao, Q.; Yao, W.; Yang, L.; Li, H.; Zhang, H.; Liao, W.; Chen, T.; Karlskov-Mortensen, P.; Fredholm, M.; Amills, M.; Clop, A.; Giuffra, E.; Wu, J.; Cai, X.; Diao, S.; Pan, X.; Wei, C.; Li, J.; Cheng, H.; Wang, S.; Su, G.; Sahana, G.; Lund, M.; Dekkers, J. C. M.; Kramer, L.; Tuggle, C. K.; Corbett, R.; Groenen, M. A. M.; Madsen, O.; Gòdia, M.; Rocha, D.; Charles, M.; Li, C.; Pausch, H.; Hu, X.; Frantz, L.; Luo, Y.; Lin, L.; Zhou, Z.; Zhang, Z.; Chen, Z.; Cui, L.; Xiang, R.; Shen, X.; Li, P.; Huang, R.; Tang, G.; Li, M.; Zhao, Y.; Yi, G.; Tang, Z.; Jiang, J.; Zhao, F.; Yuan, X.; Liu, X.; Chen, Y.; Xu, X.; Zhao, S.; Zhao, P.; Haley, C.; Zhou, H.; Wang, Q.; Pan, Y.; Ding, X.; Ma, L.; Li, J.; Navarro, P.; Zhang, Q.; Li, B.; Tenesa, A.; Li, K.; Liu, G.; Zhang, Z.; Fang, L. A compendium of genetic regulatory effects across pig tissues, bioRxiv (2022) | DOI

[99] Tian, X.; Li, R.; Fu, W.; Li, Y.; Wang, X.; Li, M.; Du, D.; Tang, Q.; Cai, Y.; Long, Y.; Zhao, Y.; Li, M.; Jiang, Y. Building a sequence map of the pig pan-genome from multiple de novo assemblies and Hi-C data, Science China Life Sciences, Volume 63 (2019) no. 5, pp. 750-763 | DOI

[100] Van der Auwera, G. A.; Carneiro, M. O.; Hartl, C.; Poplin, R.; del Angel, G.; Levy‐Moonshine, A.; Jordan, T.; Shakir, K.; Roazen, D.; Thibault, J.; Banks, E.; Garimella, K. V.; Altshuler, D.; Gabriel, S.; DePristo, M. A. From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline, Current Protocols in Bioinformatics, Volume 43 (2013) no. 1 | DOI

[101] VanRaden, P. Efficient Methods to Compute Genomic Predictions, Journal of Dairy Science, Volume 91 (2008) no. 11, pp. 4414-4423 | DOI

[102] VanRaden, P. M.; Tooker, M. E.; O’Connell, J. R.; Cole, J. B.; Bickhart, D. M. Selecting sequence variants to improve genomic predictions for dairy cattle, Genetics Selection Evolution, Volume 49 (2017) no. 1 | DOI

[103] Veerkamp, R. F.; Bouwman, A. C.; Schrooten, C.; Calus, M. P. L. Genomic prediction using preselected DNA variants from a GWAS with whole-genome sequence data in Holstein–Friesian cattle, Genetics Selection Evolution, Volume 48 (2016) no. 1 | DOI

[104] Wang, M.; Hancock, T. P.; MacLeod, I. M.; Pryce, J. E.; Cocks, B. G.; Hayes, B. J. Putative enhancer sites in the bovine genome are enriched with variants affecting complex traits, Genetics Selection Evolution, Volume 49 (2017) no. 1 | DOI

[105] Wang, Z.; Qu, L.; Yao, J.; Yang, X.; Li, G.; Zhang, Y.; Li, J.; Wang, X.; Bai, J.; Xu, G.; Deng, X.; Yang, N.; Wu, C. An EAV-HP Insertion in 5′ Flanking Region of SLCO1B3 Causes Blue Eggshell in the Chicken, PLoS Genetics, Volume 9 (2013) no. 1 | DOI

[106] Whalen, A.; Ros-Freixedes, R.; Wilson, D. L.; Gorjanc, G.; Hickey, J. M. Hybrid peeling for fast and accurate calling, phasing, and imputation with sequence data of any coverage in pedigrees, Genetics Selection Evolution, Volume 50 (2018) no. 1 | DOI

[107] Wiedemar, N.; Tetens, J.; Jagannathan, V.; Menoud, A.; Neuenschwander, S.; Bruggmann, R.; Thaller, G.; Drögemüller, C. Independent Polled Mutations Leading to Complex Gene Expression Differences in Cattle, PLoS ONE, Volume 9 (2014) no. 3 | DOI

[108] Wientjes, Y. C.; Calus, M. P.; Goddard, M. E.; Hayes, B. J. Impact of QTL properties on the accuracy of multi-breed genomic prediction, Genetics Selection Evolution, Volume 47 (2015) no. 1 | DOI

[109] Wientjes, Y. C. J.; Veerkamp, R. F.; Calus, M. P. L. The Effect of Linkage Disequilibrium and Family Relationships on the Reliability of Genomic Prediction, Genetics, Volume 193 (2013) no. 2, pp. 621-631 | DOI

[110] Wiggans, G. R.; Cole, J. B.; Hubbard, S. M.; Sonstegard, T. S. Genomic Selection in Dairy Cattle: The USDA Experience, Annual Review of Animal Biosciences, Volume 5 (2017) no. 1, pp. 309-327 | DOI

[111] Wolc, A.; Kranis, A.; Arango, J.; Settar, P.; Fulton, J.; O'Sullivan, N.; Avendano, A.; Watson, K.; Hickey, J.; de los Campos, G.; Fernando, R.; Garrick, D.; Dekkers, J. Implementation of genomic selection in the poultry industry, Animal Frontiers, Volume 6 (2016) no. 1, pp. 23-31 | DOI

[112] Wright, D.; Boije, H.; Meadows, J. R. S.; Bed'hom, B.; Gourichon, D.; Vieaud, A.; Tixier-Boichard, M.; Rubin, C.-J.; Imsland, F.; Hallböök, F.; Andersson, L. Copy Number Variation in Intron 1 of SOX5 Causes the Pea-comb Phenotype in Chickens, PLoS Genetics, Volume 5 (2009) no. 6 | DOI

[113] Xiang, R.; Berg, I. v. d.; MacLeod, I. M.; Hayes, B. J.; Prowse-Wilkins, C. P.; Wang, M.; Bolormaa, S.; Liu, Z.; Rochfort, S. J.; Reich, C. M.; Mason, B. A.; Vander Jagt, C. J.; Daetwyler, H. D.; Lund, M. S.; Chamberlain, A. J.; Goddard, M. E. Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits, Proceedings of the National Academy of Sciences, Volume 116 (2019) no. 39, pp. 19398-19408 | DOI

[114] Xiang, R.; Fang, L.; Liu, S.; Liu, G. E.; Tenesa, A.; Gao, Y.; Mason, B. A.; Chamberlain, A. J.; Goddard, M. E. Genetic score omics regression and multi-trait meta-analysis detect widespread cis-regulatory effects shaping bovine complex traits, bioRxiv | DOI

[115] Xiang, R.; Fang, L.; Liu, S.; Macleod, I. M.; Liu, Z.; Breen, E. J.; Gao, Y.; Liu, G. E.; Tenesa, A.; Mason, B. A.; Chamberlain, A. J.; Wray, N. R.; Goddard, M. E. Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle, bioRxiv | DOI

[116] Xiang, R.; MacLeod, I. M.; Daetwyler, H. D.; de Jong, G.; O’Connor, E.; Schrooten, C.; Chamberlain, A. J.; Goddard, M. E. Genome-wide fine-mapping identifies pleiotropic and functional variants that predict many traits across global cattle populations, Nature Communications, Volume 12 (2021) no. 1 | DOI

[117] Xu, L.; Cole, J. B.; Bickhart, D. M.; Hou, Y.; Song, J.; VanRaden, P. M.; Sonstegard, T. S.; Van Tassell, C. P.; Liu, G. E. Genome wide CNV analysis reveals additional variants associated with milk production traits in Holsteins, BMC Genomics, Volume 15 (2014) no. 1 | DOI

[118] Yan, S. M.; Sherman, R. M.; Taylor, D. J.; Nair, D. R.; Bortvin, A. N.; Schatz, M. C.; McCoy, R. C. Local adaptation and archaic introgression shape global diversity at human structural variant loci, eLife, Volume 10 (2021) | DOI

[119] Yengo, L.; Vedantam, S.; Marouli, E.; Sidorenko, J.; Bartell, E.; Sakaue, S.; Graff, M.; Eliasen, A. U.; Jiang, Y.; Raghavan, S.; Miao, J.; Arias, J. D.; Graham, S. E.; Mukamel, R. E.; Spracklen, C. N.; Yin, X.; Chen, S.-H.; Ferreira, T.; Highland, H. H.; Ji, Y.; Karaderi, T.; Lin, K.; Lüll, K.; Malden, D. E.; Medina-Gomez, C.; Machado, M.; Moore, A.; Rüeger, S.; Sim, X.; Vrieze, S.; Ahluwalia, T. S.; Akiyama, M.; Allison, M. A.; Alvarez, M.; Andersen, M. K.; Ani, A.; Appadurai, V.; Arbeeva, L.; Bhaskar, S.; Bielak, L. F.; Bollepalli, S.; Bonnycastle, L. L.; Bork-Jensen, J.; Bradfield, J. P.; Bradford, Y.; Braund, P. S.; Brody, J. A.; Burgdorf, K. S.; Cade, B. E.; Cai, H.; Cai, Q.; Campbell, A.; Cañadas-Garre, M.; Catamo, E.; Chai, J.-F.; Chai, X.; Chang, L.-C.; Chang, Y.-C.; Chen, C.-H.; Chesi, A.; Choi, S. H.; Chung, R.-H.; Cocca, M.; Concas, M. P.; Couture, C.; Cuellar-Partida, G.; Danning, R.; Daw, E. W.; Degenhard, F.; Delgado, G. E.; Delitala, A.; Demirkan, A.; Deng, X.; Devineni, P.; Dietl, A.; Dimitriou, M.; Dimitrov, L.; Dorajoo, R.; Ekici, A. B.; Engmann, J. E.; Fairhurst-Hunter, Z.; Farmaki, A.-E.; Faul, J. D.; Fernandez-Lopez, J.-C.; Forer, L.; Francescatto, M.; Freitag-Wolf, S.; Fuchsberger, C.; Galesloot, T. E.; Gao, Y.; Gao, Z.; Geller, F.; Giannakopoulou, O.; Giulianini, F.; Gjesing, A. P.; Goel, A.; Gordon, S. D.; Gorski, M.; Grove, J.; Guo, X.; Gustafsson, S.; Haessler, J.; Hansen, T. F.; Havulinna, A. S.; Haworth, S. J.; He, J.; Heard-Costa, N.; Hebbar, P.; Hindy, G.; Ho, Y.-L. A.; Hofer, E.; Holliday, E.; Horn, K.; Hornsby, W. E.; Hottenga, J.-J.; Huang, H.; Huang, J.; Huerta-Chagoya, A.; Huffman, J. E.; Hung, Y.-J.; Huo, S.; Hwang, M. Y.; Iha, H.; Ikeda, D. D.; Isono, M.; Jackson, A. U.; Jäger, S.; Jansen, I. E.; Johansson, I.; Jonas, J. B.; Jonsson, A.; Jørgensen, T.; Kalafati, I.-P.; Kanai, M.; Kanoni, S.; Kårhus, L. L.; Kasturiratne, A.; Katsuya, T.; Kawaguchi, T.; Kember, R. L.; Kentistou, K. A.; Kim, H.-N.; Kim, Y. J.; Kleber, M. E.; Knol, M. J.; Kurbasic, A.; Lauzon, M.; Le, P.; Lea, R.; Lee, J.-Y.; Leonard, H. L.; Li, S. A.; Li, X.; Li, X.; Liang, J.; Lin, H.; Lin, S.-Y.; Liu, J.; Liu, X.; Lo, K. S.; Long, J.; Lores-Motta, L.; Luan, J.; Lyssenko, V.; Lyytikäinen, L.-P.; Mahajan, A.; Mamakou, V.; Mangino, M.; Manichaikul, A.; Marten, J.; Mattheisen, M.; Mavarani, L.; McDaid, A. F.; Meidtner, K.; Melendez, T. L.; Mercader, J. M.; Milaneschi, Y.; Miller, J. E.; Millwood, I. Y.; Mishra, P. P.; Mitchell, R. E.; Møllehave, L. T.; Morgan, A.; Mucha, S.; Munz, M.; Nakatochi, M.; Nelson, C. P.; Nethander, M.; Nho, C. W.; Nielsen, A. A.; Nolte, I. M.; Nongmaithem, S. S.; Noordam, R.; Ntalla, I.; Nutile, T.; Pandit, A.; Christofidou, P.; Pärna, K.; Pauper, M.; Petersen, E. R. B.; Petersen, L. V.; Pitkänen, N.; Polašek, O.; Poveda, A.; Preuss, M. H.; Pyarajan, S.; Raffield, L. M.; Rakugi, H.; Ramirez, J.; Rasheed, A.; Raven, D.; Rayner, N. W.; Riveros, C.; Rohde, R.; Ruggiero, D.; Ruotsalainen, S. E.; Ryan, K. A.; Sabater-Lleal, M.; Saxena, R.; Scholz, M.; Sendamarai, A.; Shen, B.; Shi, J.; Shin, J. H.; Sidore, C.; Sitlani, C. M.; Slieker, R. C.; Smit, R. A. J.; Smith, A. V.; Smith, J. A.; Smyth, L. J.; Southam, L.; Steinthorsdottir, V.; Sun, L.; Takeuchi, F.; Tallapragada, D. S. P.; Taylor, K. D.; Tayo, B. O.; Tcheandjieu, C.; Terzikhan, N.; Tesolin, P.; Teumer, A.; Theusch, E.; Thompson, D. J.; Thorleifsson, G.; Timmers, P. R. H. J.; Trompet, S.; Turman, C.; Vaccargiu, S.; van der Laan, S. W.; van der Most, P. J.; van Klinken, J. B.; van Setten, J.; Verma, S. S.; Verweij, N.; Veturi, Y.; Wang, C. A.; Wang, C.; Wang, L.; Wang, Z.; Warren, H. R.; Bin Wei, W.; Wickremasinghe, A. R.; Wielscher, M.; Wiggins, K. L.; Winsvold, B. S.; Wong, A.; Wu, Y.; Wuttke, M.; Xia, R.; Xie, T.; Yamamoto, K.; Yang, J.; Yao, J.; Young, H.; Yousri, N. A.; Yu, L.; Zeng, L.; Zhang, W.; Zhang, X.; Zhao, J.-H.; Zhao, W.; Zhou, W.; Zimmermann, M. E.; Zoledziewska, M.; Adair, L. S.; Adams, H. H. H.; Aguilar-Salinas, C. A.; Al-Mulla, F.; Arnett, D. K.; Asselbergs, F. W.; Åsvold, B. O.; Attia, J.; Banas, B.; Bandinelli, S.; Bennett, D. A.; Bergler, T.; Bharadwaj, D.; Biino, G.; Bisgaard, H.; Boerwinkle, E.; Böger, C. A.; Bønnelykke, K.; Boomsma, D. I.; Børglum, A. D.; Borja, J. B.; Bouchard, C.; Bowden, D. W.; Brandslund, I.; Brumpton, B.; Buring, J. E.; Caulfield, M. J.; Chambers, J. C.; Chandak, G. R.; Chanock, S. J.; Chaturvedi, N.; Chen, Y.-D. I.; Chen, Z.; Cheng, C.-Y.; Christophersen, I. E.; Ciullo, M.; Cole, J. W.; Collins, F. S.; Cooper, R. S.; Cruz, M.; Cucca, F.; Cupples, L. A.; Cutler, M. J.; Damrauer, S. M.; Dantoft, T. M.; de Borst, G. J.; de Groot, L. C. P. G. M.; De Jager, P. L.; de Kleijn, D. P. V.; Janaka de Silva, H.; Dedoussis, G. V.; den Hollander, A. I.; Du, S.; Easton, D. F.; Elders, P. J. M.; Eliassen, A. H.; Ellinor, P. T.; Elmståhl, S.; Erdmann, J.; Evans, M. K.; Fatkin, D.; Feenstra, B.; Feitosa, M. F.; Ferrucci, L.; Ford, I.; Fornage, M.; Franke, A.; Franks, P. W.; Freedman, B. I.; Gasparini, P.; Gieger, C.; Girotto, G.; Goddard, M. E.; Golightly, Y. M.; Gonzalez-Villalpando, C.; Gordon-Larsen, P.; Grallert, H.; Grant, S. F. A.; Grarup, N.; Griffiths, L.; Gudnason, V.; Haiman, C.; Hakonarson, H.; Hansen, T.; Hartman, C. A.; Hattersley, A. T.; Hayward, C.; Heckbert, S. R.; Heng, C.-K.; Hengstenberg, C.; Hewitt, A. W.; Hishigaki, H.; Hoyng, C. B.; Huang, P. L.; Huang, W.; Hunt, S. C.; Hveem, K.; Hyppönen, E.; Iacono, W. G.; Ichihara, S.; Ikram, M. A.; Isasi, C. R.; Jackson, R. D.; Jarvelin, M.-R.; Jin, Z.-B.; Jöckel, K.-H.; Joshi, P. K.; Jousilahti, P.; Jukema, J. W.; Kähönen, M.; Kamatani, Y.; Kang, K. D.; Kaprio, J.; Kardia, S. L. R.; Karpe, F.; Kato, N.; Kee, F.; Kessler, T.; Khera, A. V.; Khor, C. C.; Kiemeney, L. A. L. M.; Kim, B.-J.; Kim, E. K.; Kim, H.-L.; Kirchhof, P.; Kivimaki, M.; Koh, W.-P.; Koistinen, H. A.; Kolovou, G. D.; Kooner, J. S.; Kooperberg, C.; Köttgen, A.; Kovacs, P.; Kraaijeveld, A.; Kraft, P.; Krauss, R. M.; Kumari, M.; Kutalik, Z.; Laakso, M.; Lange, L. A.; Langenberg, C.; Launer, L. J.; Le Marchand, L.; Lee, H.; Lee, N. R.; Lehtimäki, T.; Li, H.; Li, L.; Lieb, W.; Lin, X.; Lind, L.; Linneberg, A.; Liu, C.-T.; Liu, J.; Loeffler, M.; London, B.; Lubitz, S. A.; Lye, S. J.; Mackey, D. A.; Mägi, R.; Magnusson, P. K. E.; Marcus, G. M.; Vidal, P. M.; Martin, N. G.; März, W.; Matsuda, F.; McGarrah, R. W.; McGue, M.; McKnight, A. J.; Medland, S. E.; Mellström, D.; Metspalu, A.; Mitchell, B. D.; Mitchell, P.; Mook-Kanamori, D. O.; Morris, A. D.; Mucci, L. A.; Munroe, P. B.; Nalls, M. A.; Nazarian, S.; Nelson, A. E.; Neville, M. J.; Newton-Cheh, C.; Nielsen, C. S.; Nöthen, M. M.; Ohlsson, C.; Oldehinkel, A. J.; Orozco, L.; Pahkala, K.; Pajukanta, P.; Palmer, C. N. A.; Parra, E. J.; Pattaro, C.; Pedersen, O.; Pennell, C. E.; Penninx, B. W. J. H.; Perusse, L.; Peters, A.; Peyser, P. A.; Porteous, D. J.; Posthuma, D.; Power, C.; Pramstaller, P. P.; Province, M. A.; Qi, Q.; Qu, J.; Rader, D. J.; Raitakari, O. T.; Ralhan, S.; Rallidis, L. S.; Rao, D. C.; Redline, S.; Reilly, D. F.; Reiner, A. P.; Rhee, S. Y.; Ridker, P. M.; Rienstra, M.; Ripatti, S.; Ritchie, M. D.; Roden, D. M.; Rosendaal, F. R.; Rotter, J. I.; Rudan, I.; Rutters, F.; Sabanayagam, C.; Saleheen, D.; Salomaa, V.; Samani, N. J.; Sanghera, D. K.; Sattar, N.; Schmidt, B.; Schmidt, H.; Schmidt, R.; Schulze, M. B.; Schunkert, H.; Scott, L. J.; Scott, R. J.; Sever, P.; Shiroma, E. J.; Shoemaker, M. B.; Shu, X.-O.; Simonsick, E. M.; Sims, M.; Singh, J. R.; Singleton, A. B.; Sinner, M. F.; Smith, J. G.; Snieder, H.; Spector, T. D.; Stampfer, M. J.; Stark, K. J.; Strachan, D. P.; ‘t Hart, L. M.; Tabara, Y.; Tang, H.; Tardif, J.-C.; Thanaraj, T. A.; Timpson, N. J.; Tönjes, A.; Tremblay, A.; Tuomi, T.; Tuomilehto, J.; Tusié-Luna, M.-T.; Uitterlinden, A. G.; van Dam, R. M.; van der Harst, P.; Van der Velde, N.; van Duijn, C. M.; van Schoor, N. M.; Vitart, V.; Völker, U.; Vollenweider, P.; Völzke, H.; Wacher-Rodarte, N. H.; Walker, M.; Wang, Y. X.; Wareham, N. J.; Watanabe, R. M.; Watkins, H.; Weir, D. R.; Werge, T. M.; Widen, E.; Wilkens, L. R.; Willemsen, G.; Willett, W. C.; Wilson, J. F.; Wong, T.-Y.; Woo, J.-T.; Wright, A. F.; Wu, J.-Y.; Xu, H.; Yajnik, C. S.; Yokota, M.; Yuan, J.-M.; Zeggini, E.; Zemel, B. S.; Zheng, W.; Zhu, X.; Zmuda, J. M.; Zonderman, A. B.; Zwart, J.-A.; Partida, G. C.; Sun, Y.; Croteau-Chonka, D.; Vonk, J. M.; Chanock, S.; Le Marchand, L.; Chasman, D. I.; Cho, Y. S.; Heid, I. M.; McCarthy, M. I.; Ng, M. C. Y.; O’Donnell, C. J.; Rivadeneira, F.; Thorsteinsdottir, U.; Sun, Y. V.; Tai, E. S.; Boehnke, M.; Deloukas, P.; Justice, A. E.; Lindgren, C. M.; Loos, R. J. F.; Mohlke, K. L.; North, K. E.; Stefansson, K.; Walters, R. G.; Winkler, T. W.; Young, K. L.; Loh, P.-R.; Yang, J.; Esko, T.; Assimes, T. L.; Auton, A.; Abecasis, G. R.; Willer, C. J.; Locke, A. E.; Berndt, S. I.; Lettre, G.; Frayling, T. M.; Okada, Y.; Wood, A. R.; Visscher, P. M.; Hirschhorn, J. N. A saturated map of common genetic variants associated with human height, Nature, Volume 610 (2022) no. 7933, pp. 704-712 | DOI

[120] Zhao, Y.; Hou, Y.; Xu, Y.; Luan, Y.; Zhou, H.; Qi, X.; Hu, M.; Wang, D.; Wang, Z.; Fu, Y.; Li, J.; Zhang, S.; Chen, J.; Han, J.; Li, X.; Zhao, S. A compendium and comparative epigenomics analysis of cis-regulatory elements in the pig genome, Nature Communications, Volume 12 (2021) no. 1 | DOI

Cited by Sources: