Literature DB >> 17085728

Technical note: Use of marker-based relationships with multiple-trait derivative-free restricted maximal likelihood.

Z Zhang1, R J Todhunter, E S Buckler, L D Van Vleck.   

Abstract

The widespread use of the set of multiple-trait derivative-free REML programs for prediction of breeding values and estimation of variance components has led to significant improvement in traits of economic importance. The initial version of this software package, however, was generally limited to pedigree-based relationships. With continued advances in genomic research and the increased availability of genotyping, relationships based on molecular markers are obtainable and desirable. The addition of a new program to the set of multiple-trait derivative-free REML programs is described that allows users the flexibility to calculate relationships using standard pedigree files or an arbitrary relationship matrix based on genetic marker information. The strategy behind this modification and its design is described. An application is illustrated in a QTL association study for canine hip dysplasia.

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Year:  2006        PMID: 17085728     DOI: 10.2527/jas.2006-656

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  15 in total

1.  Marker-based estimation of the coefficient of coancestry in hybrid breeding programmes.

Authors:  S Maenhout; B De Baets; G Haesaert
Journal:  Theor Appl Genet       Date:  2009-02-18       Impact factor: 5.699

2.  Impact of reduced marker set estimation of genomic relationship matrices on genomic selection for feed efficiency in Angus cattle.

Authors:  Megan M Rolf; Jeremy F Taylor; Robert D Schnabel; Stephanie D McKay; Matthew C McClure; Sally L Northcutt; Monty S Kerley; Robert L Weaber
Journal:  BMC Genet       Date:  2010-04-19       Impact factor: 2.797

3.  Comparison of methods for estimation of genetic covariance matrix from SNP or pedigree data utilised to predict breeding value.

Authors:  Sebastian Mucha; Anna Wolc; Tomasz Strabel
Journal:  BMC Proc       Date:  2010-03-31

4.  Genome-wide association mapping of canopy wilting in diverse soybean genotypes.

Authors:  Avjinder S Kaler; Jeffery D Ray; William T Schapaugh; C Andy King; Larry C Purcell
Journal:  Theor Appl Genet       Date:  2017-07-20       Impact factor: 5.699

5.  Identification and validation of risk loci for osteochondrosis in standardbreds.

Authors:  Annette M McCoy; Samantha K Beeson; Rebecca K Splan; Sigrid Lykkjen; Sarah L Ralston; James R Mickelson; Molly E McCue
Journal:  BMC Genomics       Date:  2016-01-12       Impact factor: 3.969

6.  A SUPER powerful method for genome wide association study.

Authors:  Qishan Wang; Feng Tian; Yuchun Pan; Edward S Buckler; Zhiwu Zhang
Journal:  PLoS One       Date:  2014-09-23       Impact factor: 3.240

7.  Alternative parameterizations of relatedness in whole genome association analysis of pre-weaning traits of Nelore-Angus calves.

Authors:  David G Riley; Clare A Gill; Andy D Herring; Penny K Riggs; Jason E Sawyer; James O Sanders
Journal:  Genet Mol Biol       Date:  2014-09       Impact factor: 1.771

8.  Genomic prediction of survival time in a population of brown laying hens showing cannibalistic behavior.

Authors:  Setegn W Alemu; Mario P L Calus; William M Muir; Katrijn Peeters; Addie Vereijken; Piter Bijma
Journal:  Genet Sel Evol       Date:  2016-09-13       Impact factor: 4.297

9.  Expanding the BLUP alphabet for genomic prediction adaptable to the genetic architectures of complex traits.

Authors:  Jiabo Wang; Zhengkui Zhou; Zhe Zhang; Hui Li; Di Liu; Qin Zhang; Peter J Bradbury; Edward S Buckler; Zhiwu Zhang
Journal:  Heredity (Edinb)       Date:  2018-05-16       Impact factor: 3.821

10.  Evaluation of the Potential for Genomic Selection to Improve Spring Wheat Resistance to Fusarium Head Blight in the Pacific Northwest.

Authors:  Haixiao Dong; Rui Wang; Yaping Yuan; James Anderson; Michael Pumphrey; Zhiwu Zhang; Jianli Chen
Journal:  Front Plant Sci       Date:  2018-07-03       Impact factor: 5.753

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