Literature DB >> 21338774

Invited review: quantitative trait nucleotide determination in the era of genomic selection.

J I Weller1, M Ron.   

Abstract

Genome-wide association studies based on tens of thousands of single nucleotide polymorphisms have been completed for several dairy cattle populations. Methods have been proposed to directly incorporate genome scan data into breeding programs, chiefly by selection of young sires based on their genotypes for the genetic markers and pedigree without progeny test. Thus, the rate of genetic gain is increased by reduction of the mean generation interval. The methods developed so far for application of genomic selection do not require identification of the actual quantitative trait nucleotides (QTN) responsible for the observed variation of quantitative trait loci (QTL). To date, 2 QTN affecting milk production traits have been detected in dairy cattle: DGAT1 and ABCG2. This review will attempt to address the following questions based on the current state of bovine genomics and statistics. What are the pros and cons for QTN determination? How can data obtained from high-density, genome-wide scans be used most efficiently for QTN determination? Can the genome scan results already available and next-generation sequencing data be used to determine QTN? Should QTN be treated differently than markers at linkage disequilibrium with QTL in genetic evaluation programs? Data obtained by genome-wide association studies can be used to deduce QTL genotypes of sires via application of the a posteriori granddaughter design for concordance testing of putative QTN. This, together with next-generation sequencing technology, will dramatically reduce costs for QTN determination. By complete genome sequencing of 21 sires with many artificial insemination sons, it should be possible to determine concordance for all potential QTN, thus establishing the field of QTNomics.
Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21338774     DOI: 10.3168/jds.2010-3793

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


  16 in total

1.  Genomic Prediction of Complex Traits in Animal Breeding with Long Breeding History, the Dairy Cattle Case.

Authors:  Joel Ira Weller
Journal:  Methods Mol Biol       Date:  2022

2.  In silico mapping of quantitative trait loci (QTL) regulating the milk ionome in mice identifies a milk iron locus on chromosome 1.

Authors:  Darryl L Hadsell; Louise A Hadsell; Monique Rijnkels; Yareli Carcamo-Bahena; Jerry Wei; Peter Williamson; Michael A Grusak
Journal:  Mamm Genome       Date:  2018-08-02       Impact factor: 2.957

3.  Effect prediction of identified SNPs linked to fruit quality and chilling injury in peach [Prunus persica (L.) Batsch].

Authors:  Pedro J Martínez-García; Jonathan Fresnedo-Ramírez; Dan E Parfitt; Thomas M Gradziel; Carlos H Crisosto
Journal:  Plant Mol Biol       Date:  2012-11-25       Impact factor: 4.076

4.  CLIP Test: a new fast, simple and powerful method to distinguish between linked or pleiotropic quantitative trait loci in linkage disequilibria analysis.

Authors:  I David; J-M Elsen; D Concordet
Journal:  Heredity (Edinb)       Date:  2012-12-19       Impact factor: 3.821

5.  Polymorphism discovery and allele frequency estimation using high-throughput DNA sequencing of target-enriched pooled DNA samples.

Authors:  Michael P Mullen; Christopher J Creevey; Donagh P Berry; Matt S McCabe; David A Magee; Dawn J Howard; Aideen P Killeen; Stephen D Park; Paul A McGettigan; Matt C Lucy; David E Machugh; Sinead M Waters
Journal:  BMC Genomics       Date:  2012-01-11       Impact factor: 3.969

6.  A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.

Authors:  Massimo Bionaz; Kathiravan Periasamy; Sandra L Rodriguez-Zas; Walter L Hurley; Juan J Loor
Journal:  PLoS One       Date:  2012-03-16       Impact factor: 3.240

Review 7.  Genomic imprinting effects on complex traits in domesticated animal species.

Authors:  Alan M O'Doherty; David E MacHugh; Charles Spillane; David A Magee
Journal:  Front Genet       Date:  2015-04-24       Impact factor: 4.599

8.  Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows.

Authors:  Nina Melzer; Dörte Wittenburg; Dirk Repsilber
Journal:  PLoS One       Date:  2013-08-21       Impact factor: 3.240

9.  Genetic and Genome-Wide Association Analysis of Yearling Weight Gain in Israel Holstein Dairy Calves.

Authors:  Moran Gershoni; Joel Ira Weller; Ephraim Ezra
Journal:  Genes (Basel)       Date:  2021-05-10       Impact factor: 4.096

10.  Identification of male-specific amh duplication, sexually differentially expressed genes and microRNAs at early embryonic development of Nile tilapia (Oreochromis niloticus).

Authors:  Orly Eshel; Andrey Shirak; Lior Dor; Mark Band; Tatyana Zak; Michal Markovich-Gordon; Vered Chalifa-Caspi; Esther Feldmesser; Joel I Weller; Eyal Seroussi; Gideon Hulata; Micha Ron
Journal:  BMC Genomics       Date:  2014-09-09       Impact factor: 3.969

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.