Literature DB >> 22153268

Impact of genomic selection of AI dairy sires on their likely utilization and methods to estimate fertility: a paradigm shift.

R P Amann1, J M DeJarnette.   

Abstract

Breeding of dairy cattle is undergoing a paradigm shift to genomic selection of potential sires and dams. This undoubtedly will affect how bulls are managed in an artificial insemination (AI) center and impact methods to estimate their 'fertility'. Our goal is to help decision-makers understand the contents of a straw of semen, current estimates of sire fertility, and how estimates might evolve in a genomic era. Sire fertility is estimated from outcome (pregnant or not) after 300 to > 2,000 inseminations and reported in units (U) as a sire's deviation from a population (> 500 bulls) average pregnancy rate (PR). Too often users do not recognize that imprecision of an estimate encompasses a 3-U range, or more. 'True fertility' of the sire whose semen is inseminated influences outcome far less than 'true fertility' of each female and a myriad of microenvironment and management factors. Further, AI centers discard substandard collections and intentionally adjust number of sperm per straw so that differences in pregnancy rates achieved by different sires are minimized! For > 80% of Holstein bulls, estimated 'sire conception rates' are within a 5.4-U range. In the future, most sires will be 15 to 40 mo old and services will accumulate at > 1,000/mo. Estimated sire conception rates still will be a deviation from the population mean, but should be based on records for the most recent 6 or 12 mo, rather than 48 or 60 mo. Repeated 'snap shots' every 2 mo would allow AI centers to adjust number of sperm per AI straw from genomic-sires in a timely manner, to maintain high pregnancy rates, and to meet market demands with sires producing ∼40% as many sperm as mature 'proven sires' of yesteryear.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22153268     DOI: 10.1016/j.theriogenology.2011.09.002

Source DB:  PubMed          Journal:  Theriogenology        ISSN: 0093-691X            Impact factor:   2.740


  11 in total

1.  Sperm proteins ODF2 and PAWP as markers of fertility in breeding bulls.

Authors:  Abdullah Kaya; Sule Dogan; Peter Vargovic; Naseer Ahmad Kutchy; Pablo Ross; Einko Topper; Richard Oko; Frans van der Hoorn; Peter Sutovsky; Erdogan Memili
Journal:  Cell Tissue Res       Date:  2021-11-11       Impact factor: 5.249

2.  ProAKAP4 Semen Concentrations as a Valuable Marker Protein of Post-Thawed Semen Quality and Bull Fertility: A Retrospective Study.

Authors:  Marta Dordas-Perpinyà; Nicolas Sergeant; Isabelle Ruelle; Jean-François Bruyas; Frédéric Charreaux; Sandrine Michaud; Sara Carracedo; Jaime Catalán; Jordi Miró; Maryse Delehedde; Lamia Briand-Amirat
Journal:  Vet Sci       Date:  2022-05-06

3.  Copy number variations of the extensively amplified Y-linked genes, HSFY and ZNF280BY, in cattle and their association with male reproductive traits in Holstein bulls.

Authors:  Xiang-Peng Yue; Chad Dechow; Ti-Cheng Chang; James Melton DeJarnette; Clifton Eugene Marshall; Chu-Zhao Lei; Wan-Sheng Liu
Journal:  BMC Genomics       Date:  2014-02-08       Impact factor: 3.969

4.  Unravelling the genomic architecture of bull fertility in Holstein cattle.

Authors:  Yi Han; Francisco Peñagaricano
Journal:  BMC Genet       Date:  2016-11-14       Impact factor: 2.797

5.  A dual targeted β-defensin and exome sequencing approach to identify, validate and functionally characterise genes associated with bull fertility.

Authors:  Ronan Whiston; Emma K Finlay; Matthew S McCabe; Paul Cormican; Paul Flynn; Andrew Cromie; Peter J Hansen; Alan Lyons; Sean Fair; Patrick Lonergan; Cliona O' Farrelly; Kieran G Meade
Journal:  Sci Rep       Date:  2017-09-25       Impact factor: 4.379

6.  Uncovering sperm metabolome to discover biomarkers for bull fertility.

Authors:  E B Menezes; A L C Velho; F Santos; T Dinh; A Kaya; E Topper; A A Moura; E Memili
Journal:  BMC Genomics       Date:  2019-09-18       Impact factor: 3.969

7.  Influence of the temperature and the genotype of the HSP90AA1 gene over sperm chromatin stability in Manchega Rams.

Authors:  Manuel Ramón; Judit Salces-Ortiz; Carmen González; M Dolores Pérez-Guzmán; J Julián Garde; Olga García-Álvarez; Alejandro Maroto-Morales; Jorge H Calvo; M Magdalena Serrano
Journal:  PLoS One       Date:  2014-01-21       Impact factor: 3.240

8.  Whole-genome scan reveals significant non-additive effects for sire conception rate in Holstein cattle.

Authors:  Paula Nicolini; Rocío Amorín; Yi Han; Francisco Peñagaricano
Journal:  BMC Genet       Date:  2018-02-27       Impact factor: 2.797

9.  Genetic dissection of bull fertility in US Jersey dairy cattle.

Authors:  F M Rezende; G O Dietsch; F Peñagaricano
Journal:  Anim Genet       Date:  2018-08-14       Impact factor: 3.169

10.  Association of α/β-Hydrolase D16B with Bovine Conception Rate and Sperm Plasma Membrane Lipid Composition.

Authors:  Shuwen Shan; Fangzheng Xu; Martina Bleyer; Svenja Becker; Torben Melbaum; Wilhelm Wemheuer; Marc Hirschfeld; Christin Wacker; Shuhong Zhao; Ekkehard Schütz; Bertram Brenig
Journal:  Int J Mol Sci       Date:  2020-01-17       Impact factor: 5.923

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