Literature DB >> 33099757

Marker-assisted selection vis-à-vis bull fertility: coming full circle-a review.

Varinder Singh Raina1, Aneet Kour2, Atish Kumar Chakravarty2, Vikas Vohra2.   

Abstract

Bull fertility is considered an indispensable trait, as far as farm economics is concerned since it is the successful conception in a cow that provides calf crop, along with the ensuing lactation. This ensures sustainability of a dairy farm. Traditionally, bull fertility did not receive much attention by the farm managers and breeding animals were solely evaluated based on phenotypic predictors, namely, sire conception rate and seminal parameters in bull. With the advent of the molecular era in animal breeding, attempts were made to unravel the genetic complexity of bull fertility by the identification of genetic markers related to the trait. Marker-Assisted Selection (MAS) is a methodology that aims at utilizing the genetic information at markers and selecting improved populations for important traits. Traditionally, MAS was pursued using a candidate gene approach for identifying markers related to genes that are already known to have a physiological function related to the trait but this approach had certain shortcomings like stringent criteria for significance testing. Now, with the availability of genome-wide data, the number of markers identified and variance explained in relation to bull fertility has gone up. So, this presents a unique opportunity to revisit MAS by selection based on the information of a large number of genome-wide markers and thus, improving the accuracy of selection.

Entities:  

Keywords:  Bull fertility; Genetic markers; Genome-wide data; Marker-assisted selection

Mesh:

Year:  2020        PMID: 33099757     DOI: 10.1007/s11033-020-05919-0

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


  68 in total

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Journal:  Genome Res       Date:  2000-02       Impact factor: 9.043

2.  Detection of quantitative trait loci affecting milk production, health, and reproductive traits in Holstein cattle.

Authors:  M S Ashwell; D W Heyen; T S Sonstegard; C P Van Tassell; Y Da; P M VanRaden; M Ron; J I Weller; H A Lewin
Journal:  J Dairy Sci       Date:  2004-02       Impact factor: 4.034

Review 3.  Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons.

Authors:  J C M Dekkers
Journal:  J Anim Sci       Date:  2004       Impact factor: 3.159

4.  Selection indices in Holstein cattle of various countries.

Authors:  F Miglior; B L Muir; B J Van Doormaal
Journal:  J Dairy Sci       Date:  2005-03       Impact factor: 4.034

Review 5.  Marker-assisted selection to improve drought adaptation in maize: the backcross approach, perspectives, limitations, and alternatives.

Authors:  Jean-Marcel Ribaut; Michel Ragot
Journal:  J Exp Bot       Date:  2006-12-06       Impact factor: 6.992

6.  A second-generation linkage map of the bovine genome.

Authors:  S M Kappes; J W Keele; R T Stone; R A McGraw; T S Sonstegard; T P Smith; N L Lopez-Corrales; C W Beattie
Journal:  Genome Res       Date:  1997-03       Impact factor: 9.043

7.  Genome to Phenome: Improving Animal Health, Production, and Well-Being - A New USDA Blueprint for Animal Genome Research 2018-2027.

Authors:  Caird Rexroad; Jeffrey Vallet; Lakshmi Kumar Matukumalli; James Reecy; Derek Bickhart; Harvey Blackburn; Mark Boggess; Hans Cheng; Archie Clutter; Noelle Cockett; Catherine Ernst; Janet E Fulton; John Liu; Joan Lunney; Holly Neibergs; Catherine Purcell; Timothy P L Smith; Tad Sonstegard; Jerry Taylor; Bhanu Telugu; Alison Van Eenennaam; Curtis P Van Tassell; Kevin Wells
Journal:  Front Genet       Date:  2019-05-16       Impact factor: 4.599

Review 8.  Reproductive loss in high-producing dairy cattle: where will it end?

Authors:  M C Lucy
Journal:  J Dairy Sci       Date:  2001-06       Impact factor: 4.034

9.  Genome-wide association study for semen traits of the bulls in Chinese Holstein.

Authors:  Chunhua Qin; Hongwei Yin; Xu Zhang; Dongxiao Sun; Qin Zhang; Jianfeng Liu; Xiangdong Ding; Yi Zhang; Shengli Zhang
Journal:  Anim Genet       Date:  2016-09-09       Impact factor: 3.169

10.  Trends for conception rate of Holsteins over time in the southeastern United States.

Authors:  C Huang; S Tsuruta; J K Bertrand; I Misztal; T J Lawlor; J S Clay
Journal:  J Dairy Sci       Date:  2009-09       Impact factor: 4.034

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  1 in total

1.  A High-Density Genetic Map and QTL Fine Mapping for Growth- and Sex-Related Traits in Red Swamp Crayfish (Procambarus clarkii).

Authors:  Xin-Fen Guo; Yu-Lin Zhou; Min Liu; Zhi Li; Li Zhou; Zhong-Wei Wang; Jian-Fang Gui
Journal:  Front Genet       Date:  2022-02-15       Impact factor: 4.599

  1 in total

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