Single-step genomic prediction of Eucalyptus dunnii using different identity-by-descent and identity-by-state relationship matrices

Heredity ◽  
2021 ◽  
Author(s):  
Esteban J. Jurcic ◽  
Pamela V. Villalba ◽  
Pablo S. Pathauer ◽  
Dino A. Palazzini ◽  
Gustavo P. J. Oberschelp ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Single Step ◽  
Identity By Descent ◽  
Eucalyptus Dunnii ◽  
Identity By State

scholarly journals Genomic Prediction Using Alternative Strategies of Weighted Single-Step Genomic BLUP for Yearling Weight and Carcass Traits in Hanwoo Beef Cattle

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 266
Author(s):  
Hossein Mehrban ◽  
Masoumeh Naserkheil ◽  
Deuk Hwan Lee ◽  
Chungil Cho ◽  
Taejeong Choi ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Beef Cattle ◽  
Genomic Prediction ◽  
Quantitative Trait ◽  
Carcass Traits ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Linear Unbiased Prediction ◽  
Single Nucleotide ◽  
Best Linear Unbiased

The weighted single-step genomic best linear unbiased prediction (GBLUP) method has been proposed to exploit information from genotyped and non-genotyped relatives, allowing the use of weights for single-nucleotide polymorphism in the construction of the genomic relationship matrix. The purpose of this study was to investigate the accuracy of genetic prediction using the following single-trait best linear unbiased prediction methods in Hanwoo beef cattle: pedigree-based (PBLUP), un-weighted (ssGBLUP), and weighted (WssGBLUP) single-step genomic methods. We also assessed the impact of alternative single and window weighting methods according to their effects on the traits of interest. The data was comprised of 15,796 phenotypic records for yearling weight (YW) and 5622 records for carcass traits (backfat thickness: BFT, carcass weight: CW, eye muscle area: EMA, and marbling score: MS). Also, the genotypic data included 6616 animals for YW and 5134 for carcass traits on the 43,950 single-nucleotide polymorphisms. The ssGBLUP showed significant improvement in genomic prediction accuracy for carcass traits (71%) and yearling weight (99%) compared to the pedigree-based method. The window weighting procedures performed better than single SNP weighting for CW (11%), EMA (11%), MS (3%), and YW (6%), whereas no gain in accuracy was observed for BFT. Besides, the improvement in accuracy between window WssGBLUP and the un-weighted method was low for BFT and MS, while for CW, EMA, and YW resulted in a gain of 22%, 15%, and 20%, respectively, which indicates the presence of relevant quantitative trait loci for these traits. These findings indicate that WssGBLUP is an appropriate method for traits with a large quantitative trait loci effect.

scholarly journals Genomic prediction in a nuclear population of layers using single-step models

2018 ◽  
Vol 97 (2) ◽  
pp. 397-402 ◽  
Author(s):  
Yiyuan Yan ◽  
Guiqin Wu ◽  
Aiqiao Liu ◽  
Congjiao Sun ◽  
Wenpeng Han ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Single Step

scholarly journals Estimating relatedness between malaria parasites

2019 ◽  
Author(s):  
Aimee R. Taylor ◽  
Pierre E. Jacob ◽  
Daniel E. Neafsey ◽  
Caroline O. Buckee
Keyword(s):  
Genetic Epidemiology ◽  
Ad Hoc ◽  
Pathogen Transmission ◽  
Identity By Descent ◽  
Malaria Parasites ◽  
Data Set ◽  
Epidemiology Studies ◽  
Diverse Data ◽  
Prospective Study Design ◽  
Identity By State

1.AbstractUnderstanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. It remains unclear how to compare different studies, therefore, and which measures to use. Here, we systematically compare measures based on identity-by-state and identity-by-descent using a globally diverse data set of malaria parasites,Plasmodium falciparumandPlasmodium vivax, and provide marker requirements for estimates based on identity-by-descent. We formally show that the informativeness of polyallelic markers for relatedness inference is maximised when alleles are equifrequent. Estimates based on identity-by-state are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on identity-by-descent. To generate reliable estimates, we recommend approximately 200 biallelic or 100 polyallelic markers. Confidence intervals illuminate inference across studies based on different sets of markers. These marker requirements, unlike many thus far reported, are immediately applicable to haploid malaria parasites and other haploid eukaryotes. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology, and will provide a basis for statistically informed prospective study design and surveillance strategies.

scholarly journals The Accuracy and Bias of Single-Step Genomic Prediction for Populations Under Selection

2017 ◽  
Vol 7 (8) ◽  
pp. 2685-2694 ◽  
Author(s):  
Wan-Ling Hsu ◽  
Dorian J. Garrick ◽  
Rohan L. Fernando
Keyword(s):  
Genomic Prediction ◽  
Single Step

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

2005 ◽  
Vol 14 (4) ◽  
pp. 441-454 ◽  
Author(s):  
D. R. Jordan ◽  
Y. Z. Tao ◽  
I. D. Godwin ◽  
R. G. Henzell ◽  
M. Cooper ◽  
...  
Keyword(s):  
Breeding Program ◽  
Identity By Descent ◽  
Identity By State ◽  
Pedigree Breeding

scholarly journals The accuracy and bias of single-step genomic prediction for populations under selection

2016 ◽  
Author(s):  
Wan-Ling Hsu ◽  
Dorian J. Garrick ◽  
Rohan L. Fernando
Keyword(s):  
Genomic Prediction ◽  
Single Step ◽  
Alternative Analysis ◽  
Genomic Analyses ◽  
Causal Variants ◽  
Entire Matrix ◽  
C And N ◽  
The Mean ◽  
Missing Genotypes ◽  
Improved Accuracy

ABSTRACTIn single-step analyses, missing genotypes are explicitly or implicitly imputed, and this requires centering the observed genotypes, ideally using the mean of the unselected founders. If genotypes are only available on selected individuals, centering on the unselected founder mean is impossible. Here, computer simulation is used to study an alternative analysis that does not require centering genotypes but fits the mean µg of unselected individuals as a fixed effect. To improve numerical properties of the analysis, centering the entire matrix of observed and imputed genotypes, using their sample means can be done in addition to fitting µg. Starting with observed diplotypes from 721 cattle, a 5 generation population was simulated with sire selection to produce 40,000 individuals with phenotypes of which the 1,000 sires had genotypes. The next generation of 8,000 genotyped individuals was used for validation. Evaluations were undertaken: with (J) or without (N) µg when marker covariates were not centered; and with (JC) or without (C) µg when all marker covariates were centered. A pedigree based evaluation was less accurate than genomic analyses. Centering did not influence accuracy of genomic prediction, but fitting µg did. Accuracies were improved when the panel comprised only QTL, models JC and J had accuracies of 99.2%; and models C and N had accuracies of 85.6%. When only markers were in the panel, the 4 models had accuracies of 63.9%. In panels that included causal variants, fitting µg in the model improved accuracy, but had little impact when the panel contained only markers.

scholarly journals Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology Abnormalities

Animals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 710 ◽  
Author(s):  
Yunxiang Zhao ◽  
Ning Gao ◽  
Jian Cheng ◽  
Saeed El-Ashram ◽  
Lin Zhu ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Genetic Parameters ◽  
Sperm Morphology ◽  
Genetic Parameter ◽  
Predictive Ability ◽  
Single Step ◽  
Swine Production ◽  
Forward Prediction ◽  
Best Linear Unbiased ◽  
First Time

Artificial insemination (AI) has been used globally as a routine technology in the swine production industry. However, genetic parameters and genomic prediction accuracy of semen traits have seldom been reported. In this study, we estimated genetic parameters and conducted genomic prediction for five types of sperm morphology abnormalities in a large Duroc boar population. The estimated heritability of the studied traits ranged from 0.029 to 0.295. In the random cross-validation scenario, the predictive ability ranged from 0.212 to 0.417 for genomic best linear unbiased prediction (GBLUP) and from 0.249 to 0.565 for single-step GBLUP (ssGBLUP). In the forward prediction scenario, the predictive ability ranged from 0.069 to 0.389 for GBLUP and from 0.085 to 0.483 for ssGBLUP. In conclusion, the studied sperm morphology abnormalities showed moderate to low heritability. Both GBLUP and ssGBLUP showed comparative predictive abilities of breeding values, and ssGBLUP outperformed GBLUP under many circumstances in respect to predictive ability. To our knowledge, this is the first time that the genetic parameters and genomic predictive ability of these traits were reported in such a large Duroc boar population.

scholarly journals Correction: Multi-trait single-step genomic prediction accounting for heterogeneous (co)variances over the genome

Heredity ◽  
2020 ◽  
Vol 124 (4) ◽  
pp. 618-618
Author(s):  
Emre Karaman ◽  
Mogens S. Lund ◽  
Guosheng Su
Keyword(s):  
Genomic Prediction ◽  
Single Step

Inbreeding and Population Structure

2020 ◽  
pp. 47-74
Author(s):  
Daniel L. Hartl
Keyword(s):  
Population Structure ◽  
Recombinant Inbred ◽  
Recombinant Inbred Lines ◽  
Inbred Lines ◽  
Inbreeding Coefficient ◽  
Main Subject ◽  
Identity By Descent ◽  
Intimate Connection ◽  
Genotype Frequencies ◽  
Identity By State

Inbreeding and its consequences are the main subject of Chapter 3, beginning with the concepts of identity by descent versus identity by state, the inbreeding coefficient F, genotype frequencies with inbreeding, and calculation of the inbreeding coefficient from pedigrees. Inbreeding and heterosis are discussed along with the effects of inbreeding in humans and other organisms, regular systems of mating (selfing and partial selfing, sib mating), and the utility of recombinant inbred lines. The chapter emphasizes the intimate connection between inbreeding and hierarchical population structure as measured by the F-statistics.

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