Efficient Methods to Compute Genomic Predictions
TLDR
Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and to estimate thousands of marker effects simultaneously, and a blend of first- and second-order Jacobi iteration using 2 separate relaxation factors converged well for allele frequencies and effects.About:
This article is published in Journal of Dairy Science.The article was published on 2008-11-01 and is currently open access. It has received 4196 citations till now. The article focuses on the topics: Best linear unbiased prediction & Allele frequency.read more
Citations
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Genomic dissection of maternal, additive and non-additive genetic effects for growth and carcass traits in Nile tilapia.
TL;DR: The benefit of including non-additive genetic effects for genetic evaluations in tilapia breeding schemes is not evident from these findings, but the observed inbreeding depression points to a role for reciprocal recurrent selection.
Polygenic methods and their application to psychiatric traits
Naomi R. Wray,S. Hong Lee,Divya Mehta,Anna A. E. Vinkhuyzen,Frank Dudbridge,Christel,M Middeldorp +6 more
TL;DR: In this paper, the authors provide mini-guides for polygenic methods of genomic profile (or polygenic) risk scoring and estimation of variance (or heritability) from common SNPs.
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Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS.
Sonia Sheoran,Sarika Jaiswal,Deepender Kumar,Nishu Raghav,Ruchika Sharma,Sushma Kumari Pawar,S. Paul,Mir Asif Iquebal,Akanksha Jaiswar,Pradeep Sharma,Rajender Singh,C P Singh,Arun Gupta,Neeraj Kumar,Ulavappa B. Angadi,Anil Rai,G. P. Singh,Dinesh Kumar,Ratan Tiwari +18 more
TL;DR: This study led to the discovery of hitherto unreported loci for some less explored traits besides the refined chromosomal regions of known loci associated with the traits, including leaf sheath wax, awn attitude, and glume pubescence.
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Predicting genomic selection efficiency to optimize calibration set and to assess prediction accuracy in highly structured populations.
TL;DR: It is illustrated that the generalized coefficient of determination (CD) theory criteria could be adapted to various prediction scenarios including inter and intra-family predictions, resulting in higher prediction accuracies.
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Accuracies of univariate and multivariate genomic prediction models in African cassava
Uche Godfrey Okeke,Deniz Akdemir,Ismail Y. Rabbi,Peter Kulakow,Jean-Luc Jannink,Jean-Luc Jannink +5 more
TL;DR: The use of multivariate mixed models (MT and ME) for cassava genetic evaluation is recommended and these models may be useful for other plant species.
References
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Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps
TL;DR: It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.
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Coefficients of Inbreeding and Relationship
TL;DR: The importance of having a coefficient by means of which the degree of inbreeding may be expressed has been brought out by Pearl' in a number of papers published between 1913 and 1917.
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Strategy for applying genome-wide selection in dairy cattle.
TL;DR: Genome-wide selection may become a popular tool for genetic improvement in livestock after a strategy that utilizes these advantages was compared with a traditional progeny testing strategy under a typical Canadian-like dairy cattle situation.
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Derivation, calculation, and use of national animal model information.
Paul M. VanRaden,G.R. Wiggans +1 more
TL;DR: New terms and definitions were developed to explain national USDA genetic evaluations computed by an animal model, whereiability is the squared correlation of predicted and true transmitting ability.
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Accuracy of Genomic Selection Using Different Methods to Define Haplotypes
TL;DR: It was concluded that genomic selection is considerably more accurate than traditional selection, especially for a low-heritability trait.