TY - JOUR
T1 - The Resilient Dairy Genome Project
T2 - a general overview of methods and objectives related to feed efficiency and methane emissions
AU - van Staaveren, Nienke
AU - de Oliveira, Hinayah
AU - Houlahan, Kerry
AU - Chud, Tatiane
AU - Oliveira, Gerson
AU - Hailemariam, Dagnachew
AU - Kistemaker, Gerrit
AU - Miglior, Filippo
AU - Plastow, Graham
AU - Schenkel, Flavio S.
AU - Cerri, Ronaldo
AU - Sirard, Marc-André
AU - Stothard, Paul
AU - Pryce, Jennie
AU - Butty, Adrien
AU - Stratz, Patrick
AU - Abdalla, Emhimad
AU - Segelke, Dierck
AU - Stamer, Eckhard
AU - Thaller, Georg
AU - Lassen, Jan
AU - Manzanilla Pech, Coralia Ines V
AU - Stephansen, Rasmus Bak
AU - Charfeddine, Noureddine
AU - Garcia-Rodriguez, Aser
AU - González-Recio, Oscar
AU - López-Paredes, Javier
AU - Baldwin, Ransom
AU - Burchard, Javier
AU - Gaddis, Kristen
AU - Koltes, James
AU - Peñagaricano, Francisco
AU - Santos, José Eduardo
AU - Tempelman, Robert J.
AU - VandeHaar, Michael
AU - Weigel, Kent
AU - White, Heather
AU - Baes, Christine F.
PY - 2024/3
Y1 - 2024/3
N2 - The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries, i.e., Australia [AUS], Canada [CAN], Denmark [DNK], Germany [DEU], Spain [ESP], Switzerland [CHE], and United States of America [USA] contribute with genotypes and phenotypes including DMI and CH4. However, combining data is challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.
AB - The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries, i.e., Australia [AUS], Canada [CAN], Denmark [DNK], Germany [DEU], Spain [ESP], Switzerland [CHE], and United States of America [USA] contribute with genotypes and phenotypes including DMI and CH4. However, combining data is challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.
KW - dairy cattle breeding
KW - dry matter intake
KW - feed efficiency
KW - methane
KW - resilience
UR - http://www.scopus.com/inward/record.url?scp=85180113500&partnerID=8YFLogxK
U2 - 10.3168/jds.2022-22951
DO - 10.3168/jds.2022-22951
M3 - Journal article
C2 - 37690718
SN - 0022-0302
VL - 107
SP - 1510
EP - 1522
JO - Journal of Dairy Science
JF - Journal of Dairy Science
IS - 3
ER -