Quantitative Trait Loci Frequencies Research Articles

The impact of QTL allele frequency distribution on the accuracy of genomic prediction

Abstract. The accuracy of genomic prediction of quantitative traits based on single nucleotide polymorphism (SNP) markers depends among other factors on the allele frequency distribution of quantitative trait loci (QTL). Therefore, the aim of this study was to investigate different QTL allele frequency distributions and their effect on the accuracy of genomic estimated breeding values (GEBVs) using best linear unbiased genomic prediction (GBLUP) in simulated data. A population of 1000 individuals composed of 500 males and 500 females as well as a genome of 1000 cM consisting of 10 chromosomes and with a mutation rate of 2.5 × 10−5 per locus was simulated. QTL frequencies were derived from five distributions of allele frequency including constant, uniform, U-shaped, L-shaped and minor allele frequency (MAF) less than 0.01 (lowMAF). QTL effects were generated from a standard normal distribution. The number of QTL was assumed to be 500, and the simulation was done in 10 replications. The genomic prediction accuracy in the first-validation generation in constant, and the uniform allele frequency distribution was 0.59 and 0.57, respectively. Results showed that the highest accuracy of GEBVs was obtained with constant and uniform distributions followed by L-shaped, U-shaped and lowMAF QTL allele frequency distribution. The regression of true breeding values on predicted breeding values in the first-validation generation was 0.94, 0.92, 0.88, 0.85 and 0.75 for constant, uniform, L-shaped, U-shaped and lowMAF distributions, respectively. Depite different values of regression coefficients, in all scenarios GEBVs are biased downward. Overall, results showed that when QTL had a lower MAF relative to SNP markers, a low linkage disequilibrium (LD) was observed, which had a negative effect on the accuracy of GEBVs. Hence, the effect of the QTL allele frequency distribution on prediction accuracy can be alleviated through using a genomic relationship weighted by MAF or an LD-adjusted relationship matrix.

Genetic Insight into Yield-Associated Traits of Wheat Grown in Multiple Rain-Fed Environments

BackgroundGrain yield is a key economic driver of successful wheat production. Due to its complex nature, little is known regarding its genetic control. The goal of this study was to identify important quantitative trait loci (QTL) directly and indirectly affecting grain yield using doubled haploid lines derived from a cross between Hanxuan 10 and Lumai 14.Methodology/Principal FindingsTen yield-associated traits, including yield per plant (YP), number of spikes per plant (NSP), number of grains per spike (NGS), one-thousand grain weight (TGW), total number of spikelets per spike (TNSS), number of sterile spikelets per spike (NSSS), proportion of fertile spikelets per spike (PFSS), spike length (SL), density of spikelets per spike (DSS) and plant height (PH), were assessed across 14 (for YP) to 23 (for TGW) year × location × water regime environments in China. Then, the genetic effects were partitioned into additive main effects (a), epistatic main effects (aa) and their environment interaction effects (ae and aae) by using composite interval mapping in a mixed linear model.Conclusions/SignificanceTwelve (YP) to 33 (PH) QTLs were identified on all 21 chromosomes except 6D. QTLs were more frequently observed on chromosomes 1B, 2B, 2D, 5A and 6B, and were concentrated in a few regions on individual chromosomes, exemplified by three striking yield-related QTL clusters on chromosomes 2B, 1B and 4B that explained the correlations between YP and other traits. The additive main-effect QTLs contributed more phenotypic variation than the epistasis and environmental interaction. Consistent with agronomic analyses, a group of progeny derived by selecting TGW and NGS, with higher grain yield, had an increased frequency of QTL for high YP, NGS, TGW, TNSS, PFSS, SL, PH and fewer NSSS, when compared to low yielding progeny. This indicated that it is feasible by marker-assisted selection to facilitate wheat production.

Genetic Analysis of Carbon Isotope Discrimination and its Relation to Yield in a Wheat Doubled Haploid Population

Carbon isotope discrimination (Δ(13)C) is considered a useful indicator for indirect selection of grain yield (GY) in cereals. Therefore, it is important to evaluate the genetic variation in Δ(13)C and its relationship with GY. A doubled haploid (DH) population derived from a cross of two common wheat varieties, Hanxuan 10 (H10) and Lumai 14 (L14), was phenotyped for Δ(13)C in the flag leaf, GY and yield associated traits in two trials contrasted by water availability, specifically, rain-fed and irrigated. Quantitative trait loci (QTLs) were identified by single locus and two locus QTL analyses. QTLs for Δ(13)C were located on chromosomes 1A, 2B, 3B, 5A, 7A and 7B, and QTLs for other traits on all chromosomes except 1A, 4D, 5A, 5B and 6D. The population selected for high Δ(13)C had an increased frequency of QTL for high Δ(13)C, GY and number of spikes per plant (NSP) when grown under rain-fed conditions and only for high Δ(13)C and NSP when grown under irrigated conditions, which was consistent with agronomic performance of the corresponding trait values in the high Δ(13)C progeny; that is, significantly greater than that in the low Δ(13)C. Therefore, selection for Δ(13)C was beneficial in increasing grain yield in rain-fed environments.

Quantitative trait loci analysis of economically important traits inSorghum bicolor×S. sudanensehybrid

Lu, X-p., Yun, J-f., Gao, C-p. and Acharya, S. 2011. Quantitative trait loci analysis of economically important traits in Sorghum bicolor×S. sudanense hybrid. Can. J. Plant Sci. 91: 81–90. Many agronomic traits of Sorghum bicolor×S. sudanense hybrid are quantitatively inherited, and the gene mapping of these traits has important research and practical consequences. In this study, genetic mapping and quantitative trait loci (QTL) analyses were conducted using 248 F2:3plants of a cross between sorghum 314A (female parent) and Sudan grass 2002GZ-1 (male parent). A total of 178 markers (170 amplified fragment length polymorphism and 8 random amplified polymorphic DNA) were employed to construct a linkage map with 10 linkage groups covering 836 cM of the genome. The two parents expressed polymorphism for 10 agronomic characters (plant height, stem diameter, leaf number, leaf length, leaf width, spike length, tiller number, ratio of stem and leaf weight, fresh plant weight and dry plant weight). When analyzed for possible QTLs a total of 98 QTLs were identified in two test sites, out of which 26 QTLs overlapped in both sites. The average number of QTLs per character was found to be 2.6 and the distributions of these QTLs were found to be uneven across linkage groups. This, and the fact that molecular marker densities were not proportional with QTL frequencies, indicates that the detectable QTLs correlated with the agronomic traits and the genetic map can be useful for improvement in relevant characters in Sorghum bicolor×S. sudanense hybrids.

Molecular detection of genomic regions associated with grain yield and yield-related components in an elite bread wheat cross evaluated under irrigated and rainfed conditions

Grain yield and grain weight of wheat are often decreased by water-limitation in the north-eastern cropping belt of Australia. Based on knowledge that CIMMYT lines are well-adapted in this region, a recombinant inbred line (RIL) population between two elite CIMMYT bread wheats (Seri M82 and Babax) was evaluated under water-limited environments. Fourteen productivity traits were evaluated in 192 progeny in up to eight trials. For three aggregations of the environments (all, high yield or low yield), multiple quantitative trait loci (QTL) were detected, each explaining <15% of variation. Co-location of multiple trait QTL was greatest on linkage groups 1B-a, 1D-b, 4A-a, 4D-a, 6A-a, 6B-a, 7A-a and an unassigned linkage group. Two putative QTL (LOD > 3) from Seri (6D-b and UA-d) increased grain yield and co-located with a suggestive (2 < LOD < 3) and a putative QTL for increased stem carbohydrate content (WSC), respectively; the latter QTL also co-located with a putative anthesis QTL for earlier flowering. Both QTL were detected only in high yield (>4t ha(-1)) environments. A third increased grain yield QTL (7A-a) from Babax co-located with QTL for increased grain number. Six putative QTL increased grain weight and co-located with QTL for harvest index, grains per spike and spike number. Three putative QTL for increased grains per spike co-located with strong QTL for earlier flowering, increased grain weight and fewer spikes. A group of progeny that exceeded the mean grain yield and grain weight of commercial checks had an increased frequency of QTL for high WSC, large grain size, increased harvest index and greater height, but fewer stems, when compared to low yielding (20% less), low grain weight progeny. These findings were consistent with agronomic analyses of the germplasm and demonstrate that there should be opportunities to independently manipulate grain number and grain size which is typically difficult due to strong negative correlations.

Introgressing multiple QTL in breeding programmes of limited size

The ability to enrich a breed with favourable alleles from multiple unlinked quantitative trait loci (QTL) of a donor breed through marker-assisted introgression (MAI) in a population of limited size was evaluated by considering the effects of the proportion selected, the size of the marker intervals, the number of introgressed QTL and the uncertainty of QTL position. Informative flanking markers were used to select progeny with the largest expected number of donor QTL alleles over five generations of backcrossing and five generations of intercrossing. In the backcrossing phase, with 5% selected and 20 cM marker intervals for three QTL, there were sufficient backcross progeny that were heterozygous for all markers, and QTL frequencies dropped below 0.5 only because of double recombinants. For higher fractions selected, longer marker intervals, and more QTL, frequency reductions from 0.5 were greater and increased with additional generations of backcrossing. However, even with 20% selected, three QTL, and marker intervals of 5 or 20 cM, mean QTL frequencies in generation 5 were 0.35 and 0.30, sufficient to allow subsequent selection of QTL in the intercrossing phase. After five generations of intercrossing, over 90% of individuals were homozygous for all QTL, and 85% when five QTL were introgressed. The higher the proportions selected, the longer the marker intervals, and larger numbers of introgressed QTL increased the number of intercrossing generations required to achieve fixation of QTL. Location of the QTL in the marked intervals did not affect QTL frequencies or the proportion of QTL lost at the end of the introgression programme. In conclusion, introgressing multiple QTL can be accomplished in a MAI programme of limited size without requiring that all individuals selected during the backcrossing phase to be carriers of favourable alleles at all QTL.

Optimal selection on two quantitative trait loci with linkage

A mathematical approach to optimize selection on multiple quantitative trait loci (QTL) and an estimate of residual polygenic effects was applied to selection on two linked or unlinked additive QTL. Strategies to maximize total or cumulative discounted response over ten generations were compared to standard QTL selection on the sum of breeding values for the QTL and an estimated breeding value for polygenes, and to phenotypic selection. Optimal selection resulted in greater response to selection than standard QTL or phenotypic selection. Tight linkage between the QTL (recombination rate 0.05) resulted in a slightly lower response for standard QTL and phenotypic selection but in a greater response for optimal selection. Optimal selection capitalized on linkage by emphasizing selection on favorable haplotypes. When the objective was to maximize total response after ten generations and QTL were unlinked, optimal selection increased QTL frequencies to fixation in a near linear manner. When starting frequencies were equal for the two QTL, equal emphasis was given to each QTL, regardless of the difference in effects of the QTL and regardless of the linkage, but the emphasis given to each of the two QTL was not additive. These results demonstrate the ability of optimal selection to capitalize on information on the complex genetic basis of quantitative traits that is forthcoming.

Optimal selection on two quantitative trait loci with linkage.

A mathematical approach to optimize selection on multiple quantitative trait loci (QTL) and an estimate of residual polygenic effects was applied to selection on two linked or unlinked additive QTL. Strategies to maximize total or cumulative discounted response over ten generations were compared to standard QTL selection on the sum of breeding values for the QTL and an estimated breeding value for polygenes, and to phenotypic selection. Optimal selection resulted in greater response to selection than standard QTL or phenotypic selection. Tight linkage between the QTL (recombination rate 0.05) resulted in a slightly lower response for standard QTL and phenotypic selection but in a greater response for optimal selection. Optimal selection capitalized on linkage by emphasizing selection on favorable haplotypes. When the objective was to maximize total response after ten generations and QTL were unlinked, optimal selection increased QTL frequencies to fixation in a near linear manner. When starting frequencies were equal for the two QTL, equal emphasis was given to each QTL, regardless of the difference in effects of the QTL and regardless of the linkage, but the emphasis given to each of the two QTL was not additive. These results demonstrate the ability of optimal selection to capitalize on information on the complex genetic basis of quantitative traits that is forthcoming.

Quantitative trait locus mapping based on selective DNA pooling

Concepts of a simple method to map quantitative trait loci (QTL) based on selective DNA pooling in half-sib family, backcross, and F2 designs were developed. It is shown that the position of a QTL can be estimated from differences in allele frequencies for two flanking markers between individuals with high and low phenotypes and does not depend on the phenotypic means of the selected groups. An estimate of the QTL effect was obtained by relating group differences in phenotypic means to differences in QTL frequencies, which can be estimated from the QTL position and marker allele frequencies. Simulation of a half-sib family and a F2 family of 2000 individuals showed that the method gives close to unbiased results when power is high. Biases increased when measurement errors on marker allele frequencies increased and when the effect of the QTL was small. Similarities of QTL mapping based on selective DNA pooling data and on individual genotyping data are discussed, as are opportunities to extend the selective DNA pooling method to the use of multiple markers and multiple half-sib family designs. This study shows that the use of selective DNA pooling can be extended from the detection of marker associations to the mapping of QTL. Selective DNA pooling can greatly reduce the number of genotypings required.

Linkage disequilibrium in two‐stage marker‐assisted selection

Linkage disequilibrium in two‐stage marker‐assisted selection

Utilisation of marker assisted selection in a commercial dairy cow population

Abstract Genetic and economic benefits of marker assisted selection (MAS) to a commercial dairy cow population were evaluated by calculating selection advance resulting from four pathways of selection. In addition to background polygenic effects, a single additive quantitative trait loci (QTL) was segregating. Three sizes of QTL were assessed; 0.5, 1.0 and 2.0 genetic standard deviations ( σ G ) (difference between homozygotes), at each of four starting QTL frequencies; 0.01, 0.10, 0.35 and 0.75 over a thirty year time horizon. No recombination existed between QTL and a marker. Two MAS strategies were evaluated by comparison to a breeding scheme that had no genotypic knowledge of the QTL, over a thirty year time horizon. Economic benefits were calculated from the returns of extra milk produced (accounting for increased feed costs) less identification costs of the QTL and subsequent genotyping costs. In both strategies increase in QTL frequency was not immediate and thus returns were received in the later years of the analysis. The MAS strategy that utilised knowledge of QTL genotype for bull dams and bull sires had superior genetic gain at all QTL sizes and frequencies. However, it was only profitable for a 1.0 σ G QTL at 0.1 and 0.35 frequencies, and a 2.0 σ G QTL at all except the highest frequency (0.75). Long-term genetic loss was observed. The second MAS strategy of progeny testing only homozygous and heterozygous QTL bulls required a QTL of size 1.0 σ G at frequencies of 0.1 or 0.35 or a 2.0 σ G QTL at frequencies of 0.01, 0.1 and 0.35 to be more profitable than the current breeding scheme. The choice of MAS strategy should depend on QTL size and frequency.