Maximum-likelihood models for mapping genetic markers showing segregation distortion. 2. F2 populations

In F₂ populations, gametic and zygotic selection may affect the analysis of linkage in different ways. Therefore, specific likelihood equations have to be developed for each case, including dominant and codominant markers. The asymptotic bias of the classical estimates are derived for each case, in order to compare them with the standard errors of the suggested estimates. We discuss the utility and the efficiency of a previous model developed for dominant markers. We show that dominant markers provide very poor information in the case of segregation distortion and, therefore, should be used with circumspection. On the other hand, the estimation of recombination fractions between codominant markers is less affected by selection than is that for dominant markers. We also discuss the analysis of linkage between dominant and codominant markers.     

Effects of genotyping errors,missing values and segregation distortion in molecular marker data on the construction of linkage maps

A simulation study was performed to investigate the effects of missing values, typing errors and distorted segregation ratios in molecular marker data on the construction of genetic linkage maps, and to compare the performance of three locus-ordering criteria (weighted least squares, maximum likelihood and minimum sum of adjacent recombination fractions criteria) in the presence of such effects. The study was based upon three linkage groups of 10 loci at 2, 6, and 10 cM spacings simulated from a doubled-haploid population of size 150. Criteria performance were assessed using the number of replicates with correctly estimated orders, the mean rank correlation between the estimated and the true order and the mean total map length. Bootstrap samples from replicates in the maximum likelihood analysis produced a measure of confidence in the estimated locus order. The effects of missing values and/or typing errors in the data are to reduce the proportion of correctly ordered maps, and this problem worsens as the distances between loci decreases. The maximum likelihood criterion is most successful at ordering loci correctly, but gives estimated map lengths, which are substantially inflated when typing errors are present. The presence of missing values in the data produces shorter map lengths for more widely spaced markers, especially under the weighted least-squares criterion. Overall, the presence of segregation distortion has little effect on this population.     

Methodologies for segregation analysis and QTL mapping in plants

Most characters of biological interest and economic importance are quantitative traits. To uncover the genetic architecture of quantitative traits, two approaches have become popular in China. One is the establishment of an analytical model for mixed major-gene plus polygenes inheritance and the other the discovery of quantitative trait locus (QTL). Here we review our progress employing these two approaches. First, we proposed joint segregation analysis of multiple generations for mixed major-gene plus polygenes inheritance. Second, we extended the multilocus method of Lander and Green (1987), Jiang and Zeng (1997) to a more generalized approach. Our methodology handles distorted, dominant and missing markers, including the effect of linked segregation distortion loci on the estimation of map distance. Finally, we developed several QTL mapping methods. In the Bayesian shrinkage estimation (BSE) method, we suggested a method to test the significance of QTL effects and studied the effect of the prior distribution of the variance of QTL effect on QTL mapping. To reduce running time, a penalized maximum likelihood method was adopted. To mine novel genes in crop inbred lines generated in the course of normal crop breeding work, three methods were introduced. If a well-documented genealogical history of the lines is available, two-stage variance component analysis and multi-QTL Haseman-Elston regression were suggested; if unavailable, multiple loci in silico mapping was proposed.     

Maximum-likelihood models for mapping genetic markers showing segregation distortion. 1. Backcross populations

A maximum-likelihood approach is used in order to estimate recombination fractions between markers showing segregation distortion in backcross populations. It is assumed that the distortions are induced by viability differences between gametes or zygotes due to one or more selected genes. We show that Bailey's (1949) estimate stays consistent and efficient under more general assumptions than those defined by its author. This estimate should therefore be used instead of the classical maximum-likelihood estimate. The question of detection of linkage is also discussed. We show that the order of markers on linkage groups may be affected by segregation distortion.     

Molecular mapping of segregation distortion loci in Aegilops tauschii.

Distorted segregation ratios of genetic markers are often observed in progeny of inter- and intraspecific hybrids and may result from competition among gametes or from abortion of the gamete or zygote. In this study, 194 markers mapped in an Aegilops tauschii F2 population were surveyed for distorted segregation ratios. Region(s) with skewed segregation ratios were detected on chromosomes 1D, 3D, 4D, and 7D. These distorter loci are designated as QSd.ksu-1D, QSd. ksu-3D, QSd.ksu-4D, and QSd.ksu-7D. Three regions of segregation distortion identified on chromosome 5D were analyzed in two sets of reciprocal backcross populations to analyze the effect of sex and cytoplasm on segregation distortion. Extreme distortion of marker segregation ratios was observed in populations in which the F1 was used as the male parent, and ratios were skewed in favor of TA1691 alleles. There was some evidence of differential transmission caused by nucleo-cytoplasmic interactions. Our results agree with other studies stating that loci affecting gametophyte competition in male gametes are located on 5DL. The distorter loci on 5DL are designated as QSd.ksu-5D.1, QSd.ksu-5D.2, and QSd.ksu-5D.3.     

Influence of epistatic segregation distortion loci on genetic marker linkages in Japanese flounder

For genetic linkage analysis of Japanese flounder, 160 doubled haploids (DH) were artificially produced using mitotic gynogenesis and were genotyped for 458 simple sequence repeat (SSR) markers, 101 of which show distortional segregation. The genetic linkage map was constructed by modifying recombination fractions between the distorted markers. Between the corrected and uncorrected genetic maps, there were considerable differences in genetic distance, but not in relative locations among markers. Using a liability model, a segregation distortion locus (SDL), with an additive genetic effect of 1.772, was mapped between markers BDHYP387 and Poli56TUF of chromosome 24 in the corrected genetic map. Additionally, six pairs of epistatic SDLs were identified on chromosomes 1, 5, 8, 9, 23, and 24. Changes in genetic distances between markers did not occur on chromosome regions with main effect SDLs. However, most chromosome regions where genetic distances changed covered the detected epistatic SDLs. This study concluded that epistatic SDLs decrease linkages between markers and lengthen genetic distances in Japanese flounder. This finding has been partially validated in other DH populations derived from three female Japanese flounders.     

A comparison of bivariate and univariate QTL mapping in livestock populations

This study presents a multivariate, variance component-based QTL mapping model implemented via restricted maximum likelihood (REML). The method was applied to investigate bivariate and univariate QTL mapping analyses, using simulated data. Specifically, we report results on the statistical power to detect a QTL and on the precision of parameter estimates using univariate and bivariate approaches. The model and methodology were also applied to study the effectiveness of partitioning the overall genetic correlation between two traits into a component due to many genes of small effect, and one due to the QTL. It is shown that when the QTL has a pleiotropic effect on two traits, a bivariate analysis leads to a higher statistical power of detecting the QTL and to a more precise estimate of the QTL''s map position, in particular in the case when the QTL has a small effect on the trait. The increase in power is most marked in cases where the contributions of the QTL and of the polygenic components to the genetic correlation have opposite signs. The bivariate REML analysis can successfully partition the two components contributing to the genetic correlation between traits.     

QTL mapping of stay-green in two sorghum recombinant inbred populations

The stay-green trait is a reported component of tolerance to terminal drought stress in sorghum. To map quantitative trait loci (QTLs) for stay-green, two sorghum recombinant inbred populations (RIPs) of 226 F(3:5) lines each were developed from crosses (1) IS9830 x E36-1 and (2) N13 x E36-1. The common parental line, E36-1 of Ethiopian origin, was the stay-green trait source. The genetic map of RIP 1 had a total length of 1,291 cM, with 128 markers (AFLPs, RFLPs, SSRs and RAPDs) distributed over ten linkage groups. The map of RIP 2 spanned 1,438 cM and contained 146 markers in 12 linkage groups. The two RIPs were evaluated during post-rainy seasons at Patancheru, India, in 1999/2000 (RIP 2) and 2000/2001 (RIP 1). The measures of stay-green mapped were the green leaf area percentages at 15, 30 and 45 days after flowering (% GL15, % GL30 and % GL45, respectively). Estimated repeatabilities for % GL15, % GL30 and % GL45 amounted to 0.89, 0.81 and 0.78 in RIP 1, and 0.91, 0.88 and 0.85 in RIP 2, respectively. The number of QTLs for the three traits detected by composite interval mapping ranged from 5 to 8, explaining 31% to 42% of the genetic variance. In both RIPs, both parent lines contributed stay-green alleles. Across the three measures of the stay-green trait, three QTLs on linkage groups A, E and G were common to both RIPs, with the stay-green alleles originating from E36-1. These QTLs were therefore consistent across the tested genetic backgrounds and years. After QTL validation across sites and verification of the general benefit of the stay-green trait for grain yield performance and stability in the target areas, the corresponding chromosomal regions could be candidates for marker-assisted transfer of stay-green into elite materials.     

Bayesian mapping of QTL in outbred F2 families allowing inference about whether F0 grandparents are homozygous or heterozygous at QTL

In this paper, we propose a new Bayesian method for QTL analysis in outbred F2 families based on Markov chain Monte Carlo (MCMC) estimation allowing inference about whether each of F0 founders (grandparents) is homozygous or heterozygous at QTL. This, in turn, allows us to select a model accurately explaining observations of phenotypes for F2 individuals. The proposed method performs the fitting a statistical model of the two possible QTL states in each F0 grandparent, that is, homozygous and heterozygous at QTL, and gives a posterior distribution for the QTL states in each F0 grandparent. We confine ourselves to the discrimination of two QTL states, homozygous or heterozygous, for each of the F0 grandparents without taking into consideration whether common alleles are shared by F0 grandparents. The statistical model includes allelic effects and dominance effects for each QTL. The number of parameters representing allelic effects and dominance effects is therefore changed depending on the QTL states. A Reversible Jump MCMC technique is used for transition between the models of different dimensions. The effectiveness of the proposed method was investigated using simulation experiments. It was practicable to estimate the QTL states of F0 grandparents as well as the number, the locations and the effects of QTL segregating in an outbred F2 family.     

QTL mapping for haploid male fertility by a segregation distortion method and fine mapping of a key QTL <Emphasis Type="Italic">qhmf4</Emphasis> in maize

Key message

Four QTL related to haploid male fertility were detected by a segregation distortion method and the key QTL qhmf4 was fine mapped to an interval of ~800 kb.

Abstract

Doubled haploid (DH) technology enables rapid development of homozygous lines in maize breeding programs. However, haploid genome doubling is a bottleneck for the commercialization of DH technology and is limited by haploid male fertility (HMF). This is the first study reporting the quantitative trait locus (QTL) analysis of HMF in maize. Four QTL, qhmf1, qhmf2, qhmf3, and qhmf4, controlling HMF have been identified by segregation distortion (SD) loci detection in the selected haploid population derived from ‘Yu87-1/Zheng58’. Three loci, qhmf1, qhmf2, and qhmf4, were also detected in the selected haploid population derived from ‘4F1/Zheng58’. The QTL qhmf4 showed the strongest SD in both haploid populations. Based on the sequence information of ‘Yu87-1’ and ‘Zheng58’, thirteen markers being polymorphic between the two lines were developed to saturate the qhmf4 region. A total of 8168 H₁BC₂ (haploid backcross generation) plants produced from ‘Yu87-1’ and ‘Zheng58’ were screened for recombinants. All the 48 recombinants were backcrossed to ‘Zheng58’ to develop H₁BC₃ progeny. The heterozygous H₁BC₃ individuals were crossed with CAU5 to induce haploids. In each H₁BC₃ progeny, haploids were genotyped and evaluated for anther emergence score (AES). Significant (or no significant) difference (P?<?0.05) between haploids with or without ‘Yu87-1’ donor segment indicated presence or absence of qhmf4 in the donor segment. The analysis of the 48 recombinants narrowed the qhmf4 locus down to an ~800 kb interval flanked by markers IND166 and IND1668.

     

Joint mapping of quantitative trait loci using F2 populations

In this paper, the theory of joint mapping of quantitative trait loci is extended to F₂ populations. Two independent regression equations, related to the additive and dominance effects respectively, are derived. Therefore, there are three alternative strategies for mapping QTLs, called additive-based mapping (ABM), dominance-based mapping (DBM) and additive-dominance-based mapping (ADBM). Simulation results have shown that ADBM is the most appropriate in most situations.     

QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat

In bread wheat, single-locus and two-locus QTL analyses were conducted for seven yield and yield contributing traits using two different mapping populations (P I and P II). Single-locus QTL analyses involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated yield traits to detect the pleiotropic QTLs. Two-locus analyses were conducted to detect main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions (QE and QQE). Only a solitary QTL for spikelets per spike was common between the above two populations. HomoeoQTLs were also detected, suggesting the presence of triplicate QTLs in bread wheat. Relatively fewer QTLs were detected in P I than in P II. This may be partly due to low density of marker loci on P I framework map (173) than in P II (521) and partly due to more divergent parents used for developing P II. Six QTLs were important which were pleiotropic/coincident involving more than one trait and were also consistent over environments. These QTLs could be utilized efficiently for marker assisted selection (MAS).     

QTL mapping in outbred tetraploid (and diploid) diallel populations

Over the last decade, multiparental populations have become a mainstay of genetics research in diploid species. Our goal was to extend this paradigm to autotetraploids by developing software for quantitative trait locus (QTL) mapping in connected F1 populations derived from a set of shared parents. For QTL discovery, phenotypes are regressed on the dosage of parental haplotypes to estimate additive effects. Statistical properties of the model were explored by simulating half-diallel diploid and tetraploid populations with different population sizes and numbers of parents. Across scenarios, the number of progeny per parental haplotype (pph) largely determined the statistical power for QTL detection and accuracy of the estimated haplotype effects. Multiallelic QTL with heritability 0.2 were detected with 90% probability at 25 pph and genome-wide significance level 0.05, and the additive haplotype effects were estimated with over 90% accuracy. Following QTL discovery, the software enables a comparison of models with multiple QTL and nonadditive effects. To illustrate, we analyzed potato tuber shape in a half-diallel population with three tetraploid parents. A well-known QTL on chromosome 10 was detected, for which the inclusion of digenic dominance lowered the Deviance Information Criterion (DIC) by 17 points compared to the additive model. The final model also contained a minor QTL on chromosome 1, but higher-order dominance and epistatic effects were excluded based on the DIC. In terms of practical impacts, the software is already being used to select offspring based on the effect and dosage of particular haplotypes in breeding programs.     

Multiple QTL mapping in related plant populations via a pedigree-analysis approach

QTL mapping experiments in plant breeding may involve multiple populations or pedigrees that are related through their ancestors. These known relationships have often been ignored for the sake of statistical analysis, despite their potential increase in power of mapping. We describe here a Bayesian method for QTL mapping in complex plant populations and reported the results from its application to a (previously analysed) potato data set. This Bayesian method was originally developed for human genetics data, and we have proved that it is useful for complex plant populations as well, based on a sensitivity analysis that was performed here. The method accommodates robustness to complex structures in pedigree data, full flexibility in the estimation of the number of QTL across multiple chromosomes, thereby accounting for uncertainties in the transmission of QTL and marker alleles due to incomplete marker information, and the simultaneous inclusion of non-genetic factors affecting the quantitative trait.     

Construction of a high-density composite map and comparative mapping of segregation distortion regions in barley

Segregation distortion can negatively impact on gains expected using selection. In order to increase our understanding of genetic factors that may influence the extent and direction of segregation distortion, segregation distortion analyses were conducted in four different doubled haploid (DH) populations. A high-density composite map of barley was then constructed by integrating information from the four populations. The composite map contained 2,111 unique loci, comprising RFLP, SSR and DArT markers and spanned 1,136 cM. In the four populations investigated, the proportion of markers with segregation distortion ranged from 15 to 38%, depending on the population. The highest distortion was observed in populations derived by the microspore culture technique. Distorted loci tended to be clustered, which allowed definition of segregation distortion regions (SDRs). A total of 14 SDRs were identified in the 4 populations. Using the high-density composite map, several SDRs were shown to have consistent map locations in two or more populations; one SDR on chromosome 1H was present in all four populations. The analysis of haplotypes underlying seven SDRs indicated that in three cases the under-represented haplotypes were common across populations, but for four SDRs the under-represented haplotypes varied across populations. Six of the seven centromeric regions harboured SDRs suggesting that genetic processes related to position near a centromere caused the segregation distortion in these SDRs. Other SDRs were most likely due to the methods used to produce the DH populations. The association of the SDRs identified in this study and some of the genes involved in the process of haploid production described in other studies were compared. The composite map constructed in this study provides an additional resource for the barley community via increased genome coverage and the provision of additional marker options. It has also enabled further insights into mechanisms that underpin segregation distortion.     

QTL linkage analysis of connected populations using ancestral marker and pedigree information

The common assumption in quantitative trait locus (QTL) linkage mapping studies that parents of multiple connected populations are unrelated is unrealistic for many plant breeding programs. We remove this assumption and propose a Bayesian approach that clusters the alleles of the parents of the current mapping populations from locus-specific identity by descent (IBD) matrices that capture ancestral marker and pedigree information. Moreover, we demonstrate how the parental IBD data can be incorporated into a QTL linkage analysis framework by using two approaches: a Threshold IBD model (TIBD) and a Latent Ancestral Allele Model (LAAM). The TIBD and LAAM models are empirically tested via numerical simulation based on the structure of a commercial maize breeding program. The simulations included a pilot dataset with closely linked QTL on a single linkage group and 100 replicated datasets with five linkage groups harboring four unlinked QTL. The simulation results show that including parental IBD data (similarly for TIBD and LAAM) significantly improves the power and particularly accuracy of QTL mapping, e.g., position, effect size and individuals’ genotype probability without significantly increasing computational demand.     

Mapping quantitative trait loci in selected breeding populations: A segregation distortion approach

Quantitative trait locus (QTL) mapping is often conducted in line-crossing experiments where a sample of individuals is randomly selected from a pool of all potential progeny. QTLs detected from such an experiment are important for us to understand the genetic mechanisms governing a complex trait, but may not be directly relevant to plant breeding if they are not detected from the breeding population where selection is targeting for. QTLs segregating in one population may not necessarily segregate in another population. To facilitate marker-assisted selection, QTLs must be detected from the very population which the selection is targeting. However, selected breeding populations often have depleted genetic variation with small population sizes, resulting in low power in detecting useful QTLs. On the other hand, if selection is effective, loci controlling the selected trait will deviate from the expected Mendelian segregation ratio. In this study, we proposed to detect QTLs in selected breeding populations via the detection of marker segregation distortion in either a single population or multiple populations using the same selection scheme. Simulation studies showed that QTL can be detected in strong selected populations with selected population sizes as small as 25 plants. We applied the new method to detect QTLs in two breeding populations of rice selected for high grain yield. Seven QTLs were identified, four of which have been validated in advanced generations in a follow-up study. Cloned genes in the vicinity of the four QTLs were also reported in the literatures. This mapping-by-selection approach provides a new avenue for breeders to improve breeding progress. The new method can be applied to breeding programs not only in rice but also in other agricultural species including crops, trees and animals.     

Mutation variability and marker trait inheritance in hybrid-mutant populations F2M2 of winter wheat

Influence of hybrid seed treatment with mutagenes on genetic variability in hybrid populations of the second generation of winter wheat has been investigated. Treatment with mutagenes in moderate doses results in deviation of segregation of marker traits as compared to control towards either increase or decrease of the ratio of recessive allels. It was shown that in crossing combinations with red-ear form as one of the parental components, treatment with gamma rays at the dose of 100 Gy leads to significantly larger deviations of disintegration comparing to control.     

QTL mapping and molecular marker analysis for the resistance of rice to ozone

The resistance of rice to ozone (O3) is a quantitative trait controlled by nuclear genes. The identification of quantitative trait loci (QTL) and analysis of molecular markers of O3 resistance is important for increasing the resistance of rice to O3 stress. QTL associated with the O3 resistance of rice were mapped on chromosomes 1, 7 and 11 using 164 recombinant inbred (RI) lines from a cross between 'Milyang 23' and 'Gihobyeo'. The quantitative trait loci were tightly linked to the markers RG109, C507 and RG1094 and were detected in each of three replications. The association between these markers and O3 resistance in 26 rice cultivars and doubled haploid (DH) populations was analysed. The markers permit the screening of rice germplasm for O3 resistance and the introduction of resistance into elite lines in breeding programs.