Efficiency of low heritability QTL mapping under high SNP density

Viana, José Marcelo Soriano; Silva, Fabyano Fonseca e; Mundim, Gabriel Borges; Azevedo, Camila Ferreira; Jan, Hikmat Ullah

doi:10.1007/s10681-016-1800-5

Cited by 26 publications

(29 citation statements)

References 42 publications

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“…This software uses the quantitative genetics theory that was described in the previous sections and in Viana (2004). REALbreeding has been used to provide simulated data in investigations in the areas of genomic selection (Viana et al 2019), GWAS (Pereira et al 2018), QTL mapping (Viana et al 2017b), linkage disequilibrium (Andrade et al 2019), population structure (Viana et al 2013), and heterotic grouping/genetic diversity (Viana et al 2020).…”

Section: Methodsmentioning

confidence: 99%

Significance of linkage disequilibrium and epistasis on the genetic variances and covariance between relatives in non-inbred and inbred populations

Viana

Garcia

2021

Preprint

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Because no feasible theoretical model can depict the complexity of phenotype development from a genotype, the joint significance of linkage disequilibrium (LD), epistasis, and inbreeding on the genetic variances remains unclear. The objective of this investigation was to assess the impact of LD and epistasis on the genetic variances and covariances between relatives in non-inbred and inbred populations using simulated data. We provided the theoretical background and simulated grain yield assuming 400 genes in 10 chromosomes of 200 and 50 cM. We generated five populations with low to high LD levels, assuming 10 generations of random cross and selfing. The analysis of the parametric LD in the populations shows that the LD level depends mainly on the gene density. The significance of the LD level is impressive on the magnitude of the genotypic and additive variances, which is the most important component of the genotypic variance, regardless of the LD level and the degree of inbreeding. Regardless of the type of epistasis, the ratio epistatic variance/genotypic variance is proportional to the percentage of the epistatic genes. For the epistatic variances, except for duplicate epistasis and dominant and recessive epistasis, with 100% of epistatic genes, their magnitudes are much lower than the magnitude of the additive variance. The additive x additive variance is the most important epistatic variance. Our results explain why LD for genes and relationship information are key factors affecting the genomic prediction accuracy of complex traits and the efficacy of association studies.

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Section: Methodsmentioning

confidence: 99%

Significance of linkage disequilibrium and epistasis on the genetic variances and covariance between relatives in non-inbred and inbred populations

Viana

Garcia

2021

Preprint

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“…To evaluate if the LD maps allow inference of the overall degree of LD by chromosome in the populations, we also processed a simulated data set, generated with REALbreeding software (available by request). This software has been recently used in studies on population structure [18], QTL mapping [19], genomic selection [20], and genome-wide association studies [21]. We simulated the genotyping of 200 individuals in a population (generation 0) and 200 individuals in the same population after 10 generations of random crossings (generation 10), for 287 SNPs spanning 298 cM (density of 1 cM) of a single chromosome.…”

Section: Methodsmentioning

confidence: 99%

Linkage disequilibrium and haplotype block patterns in popcorn populations

et al. 2019

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Linkage disequilibrium (LD) analysis provides information on the evolutionary aspects of populations. Recently, haplotype blocks have been used to increase the power of quantitative trait loci detection in genome-wide association studies and the prediction accuracy of genomic selection. Our objectives were as follows: to compare the degree of LD, LD decay, and LD decay extent in popcorn populations; to characterize the number and length of haplotype blocks in the populations; and to determine whether maize chromosomes also have a pattern of interspaced regions of high and low rates of recombination. We used a biparental population, a synthetic, and a breeding population, genotyped for approximately 75,000 single nucleotide polymorphisms (SNPs). The sample size ranged from 190 to 192 plants. For the whole-genome LD and haplotype block analyses, we assumed a window of 500 kb. To characterize the block and step patterns of LD in the populations, we constructed LD maps by chromosome, defining a cold spot as a chromosome segment including SNPs with the same LDU position. The LD and haplotype block analyses were also performed at the intragenic level, selecting 12 genes related to zein, starch, cellulose, and fatty acid biosynthesis. The populations with the higher and lower frequencies of |D'| values greater than 0.75 were the biparental (65–74%) and the breeding population (26–58%), respectively. There were slight differences between the populations regarding the average distance for SNPs with |D'| values greater than 0.75 (in the range of approximately 207 to 229 kb). The level of LD expressed by the r2 values was low in the populations (0.02, 0.04, and 0.04, on average) but comparable to some non-isolated human populations. The frequency of r2 values greater than 0.75 was lower in the biparental population (0.2–0.5%) and higher in the other populations (0.2–1.6%). The average distance for SNPs with r2 values greater than 0.75 was much higher in the biparental population (approximately 80 to 126 kb). In the other populations, the ranges were approximately 6 to 19 and 6 to 35 kb. The heatmaps for the regions covered by the first 100 SNPs in each chromosome, in each population (1 to 3.3 Mb, approximately), provided evidence that the comparatively few high r2 values (close to 1.0) occurred only for SNPs in close proximity, especially in the synthetic and breeding populations. Due to the reduced number of SNPs in the haplotype blocks (2 to 3) in the populations, it is not expected advantage of a haplotype-based association study as well as genomic selection along generations. The results concerning LD decay (rapid decay after 5–10 kb) and LD decay extent (along up to 300 kb) are in the range observed with maize inbred line panels. The LD maps indicate that maize chromosomes had a pattern of regions of extensive LD interspaced with regions of low LD. However, our simulated LD map provides evidence that this pattern can reflect regions with differences in allele frequencies and LD levels (expressed by |D'|) and not regions...

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“…The datasets of DHs, testers, and testcrosses were simulated using the software REALbreeding (developed in Xojo, Version 2017 Release 3; available by request). This program has been used for studies on population structure (Viana et al, 2013), quantitative trait locus (QTL) mapping (Viana et al, 2017b), genomic selection (Viana et al, 2018), and genome‐wide association studies (Viana et al, 2017a). The genotyping and phenotyping processes begin with the positioning of molecular markers and QTLs and minor genes on up to 10 chromosomes of up to 300 cM in length.…”

Section: Methodsmentioning

confidence: 99%

Efficiency of Genomic Prediction of Nonassessed Testcrosses

et al. 2019

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In plant breeding, genomic selection has been mainly used to predict untested single crosses and testcrosses. The objectives of this study were to assess the efficiency of prediction of untested testcrosses and the significance of the factors affecting the prediction. We simulated 20,000 testcrosses from two groups of 5000 related doubled haploid lines (DHs) and two unrelated elite inbred lines. The DHs were genotyped for 20,000 single nucleotide polymorphisms (SNPs) and the testcrosses were phenotyped for grain yield. The average SNP density was 0.1 cM. We assumed genetic control by 400 quantitative trait loci (QTLs) and heritability of 25, 50, and 75% for the assessed testcrosses. The training set sizes were 10 and 30% of the available DHs. The process of random sampling of the field assessed and predicted testcrosses were replicated 50 times. We computed the prediction accuracy and the coincidence index, a measure of the selection efficacy of the nonassessed testcrosses. The results evidenced that genomic selection is an efficient process for selecting superior nonassessed testcrosses, if there is sufficient relatedness between the available DHs, linkage disequilibrium in the DHs and genotypic variance between testcrosses, a training set size of at least 10% of the available DHs, and a SNP density of at least 1 cM. The efficacy of selecting the superior nonassessed testcrosses ranged between 0.1 and 0.9, proportional to the heritability of the assessed testcrosses (0.25–1.00). It is important to highlight that the parametric coincidence ranged from 0.1 to 0.8. Furthermore, genomic prediction is much more efficient than pedigree‐based best linear unbiased prediction.

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Efficiency of low heritability QTL mapping under high SNP density

Cited by 26 publications

References 42 publications

Significance of linkage disequilibrium and epistasis on the genetic variances and covariance between relatives in non-inbred and inbred populations

Significance of linkage disequilibrium and epistasis on the genetic variances and covariance between relatives in non-inbred and inbred populations

Linkage disequilibrium and haplotype block patterns in popcorn populations

Efficiency of Genomic Prediction of Nonassessed Testcrosses

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