Literature DB >> 28843688

The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows.

L C Hardie1, M J VandeHaar2, R J Tempelman2, K A Weigel3, L E Armentano3, G R Wiggans4, R F Veerkamp5, Y de Haas5, M P Coffey6, E E Connor4, M D Hanigan7, C Staples8, Z Wang9, J C M Dekkers10, D M Spurlock10.   

Abstract

The objective of this study was to identify genomic regions and candidate genes associated with feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 single nucleotide polymorphisms having individual feed intake, milk yield, milk composition, and body weight records were used in this study. Cows were from research herds located in the United States, Canada, the Netherlands, and the United Kingdom. Feed efficiency, defined as residual feed intake (RFI), was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed considering each trait as a separate trait within parity group to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method with a prior assumption that 1% of single nucleotide polymorphisms have a nonzero effect. One-megabase windows with greatest percentage of the total genetic variation explained by the markers (TGVM) were identified, and adjacent windows with large proportion of the TGVM were combined and reanalyzed. Heritability estimates for RFI were 0.14 (±0.03; ±SE) in primiparous cows and 0.13 (±0.03) in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW, and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, after combining windows, significance was met on Bos taurus autosome 27 in primiparous cows, and nearly reached on Bos taurus autosome 4 in multiparous cows. Among other genes, these regions contain β-3 adrenergic receptor and the physiological candidate gene, leptin, respectively. Between the 2 parity groups, 3 of the 10 windows with the largest effects on DMI neighbored windows affecting RFI, but were not in the top 10 regions for MilkE or MBW. This result suggests a genetic basis for feed intake that is unrelated to energy consumption required for milk production or expected maintenance as determined by MBW. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.
Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  dairy; feed efficiency; genome-wide association study; residual feed intake

Mesh:

Year:  2017        PMID: 28843688     DOI: 10.3168/jds.2017-12604

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  16 in total

1.  Genetic parameters and genome-wide association study regarding feed efficiency and slaughter traits in Charolais cows.

Authors:  Pauline Martin; Sébastien Taussat; Aurélie Vinet; Daniel Krauss; David Maupetit; Gilles Renand
Journal:  J Anim Sci       Date:  2019-09-03       Impact factor: 3.159

2.  Genome-wide association and genotype by environment interactions for growth traits in U.S. Red Angus cattle.

Authors:  Johanna L Smith; Miranda L Wilson; Sara M Nilson; Troy N Rowan; Robert D Schnabel; Jared E Decker; Christopher M Seabury
Journal:  BMC Genomics       Date:  2022-07-16       Impact factor: 4.547

3.  Can We Observe Expected Behaviors at Large and Individual Scales for Feed Efficiency-Related Traits Predicted Partly from Milk Mid-Infrared Spectra?

Authors:  Lei Zhang; Nicolas Gengler; Frédéric Dehareng; Frédéric Colinet; Eric Froidmont; Hélène Soyeurt
Journal:  Animals (Basel)       Date:  2020-05-18       Impact factor: 2.752

4.  Copy Number Variation Mapping and Genomic Variation of Autochthonous and Commercial Turkey Populations.

Authors:  Maria G Strillacci; Erica Gorla; Angel Ríos-Utrera; Vicente E Vega-Murillo; Moises Montaño-Bermudez; Adriana Garcia-Ruiz; Silvia Cerolini; Sergio I Román-Ponce; Alessandro Bagnato
Journal:  Front Genet       Date:  2019-10-29       Impact factor: 4.599

5.  Effects of Incorporating Dry Matter Intake and Residual Feed Intake into a Selection Index for Dairy Cattle Using Deterministic Modeling.

Authors:  Kerry Houlahan; Flavio S Schenkel; Dagnachew Hailemariam; Jan Lassen; Morten Kargo; John B Cole; Erin E Connor; Silvia Wegmann; Oliveira Junior; Filippo Miglior; Allison Fleming; Tatiane C S Chud; Christine F Baes
Journal:  Animals (Basel)       Date:  2021-04-17       Impact factor: 2.752

Review 6.  Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle.

Authors:  Cori J Siberski-Cooper; James E Koltes
Journal:  Animals (Basel)       Date:  2021-12-22       Impact factor: 2.752

7.  Impact of merging commercial breeding lines on the genetic diversity of Landrace pigs.

Authors:  Ina Hulsegge; Mario Calus; Rita Hoving-Bolink; Marcos Lopes; Hendrik-Jan Megens; Kor Oldenbroek
Journal:  Genet Sel Evol       Date:  2019-10-29       Impact factor: 4.297

8.  Genomic analyses reveal distinct genetic architectures and selective pressures in buffaloes.

Authors:  Ting Sun; Jiafei Shen; Alessandro Achilli; Ningbo Chen; Qiuming Chen; Ruihua Dang; Zhuqing Zheng; Hucai Zhang; Xiaoming Zhang; Shaoqiang Wang; Tao Zhang; Hongzhao Lu; Yun Ma; Yutang Jia; Marco Rosario Capodiferro; Yongzhen Huang; Xianyong Lan; Hong Chen; Yu Jiang; Chuzhao Lei
Journal:  Gigascience       Date:  2020-02-01       Impact factor: 6.524

9.  Genome Wide Association Study of Beef Traits in Local Alpine Breed Reveals the Diversity of the Pathways Involved and the Role of Time Stratification.

Authors:  Enrico Mancin; Beniamino Tuliozi; Sara Pegolo; Cristina Sartori; Roberto Mantovani
Journal:  Front Genet       Date:  2022-01-04       Impact factor: 4.599

10.  Unraveling Admixture, Inbreeding, and Recent Selection Signatures in West African Indigenous Cattle Populations in Benin.

Authors:  Sèyi Fridaïus Ulrich Vanvanhossou; Tong Yin; Carsten Scheper; Ruedi Fries; Luc Hippolyte Dossa; Sven König
Journal:  Front Genet       Date:  2021-12-08       Impact factor: 4.599

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