QTL analysis for some quantitative traits in bread wheat

Quantitative trait loci (QTL) analysis was conducted in bread wheat for 14 important traits utilizing data from four different mapping populations involving different approaches of QTL analysis. Analysis for grain protein content (GPC) sug- gested that the major part of genetic variation for this trait is due to environmental interactions. In contrast, pre-harvest sprouting tolerance (PHST) was controlled mainly by main effect QTL (M-QTL) with very little genetic variation due to environmental interactions; a major QTL for PHST was detected on chromosome arm 3AL. For grain weight, one QTL each was detected on chromosome arms 1AS, 2BS and 7AS. QTL for 4 growth related traits taken together detected by different methods ranged from 37 to 40; nine QTL that were detected by single-locus as well as two-locus analyses were all M-QTL. Similarly, single-locus and two-locus QTL analyses for seven yield and yield contributing traits in two populations respectively allowed detection of 25 and 50 QTL by composite interval mapping (CIM), 16 and 25 QTL by multiple-trait composite interval mapping (MCIM) and 38 and 37 QTL by two-locus analyses. These studies should prove useful in QTL cloning and wheat improvement through marker aided selection.     

水稻千粒重QTL图谱整合研究

以粳稻品种日本晴的测序图谱Gramene Annotated Nipponbare Sequence 2006为基础,挑选较广泛应用于水稻QTL研究的标记绘制了公共图谱.并将国内外公开发表的251个水稻千粒重QTL整合到该图谱中.研究表明,目前定位的粒重QTL虽分散于各条染色体,但主要集中在1、3、5、6、10号染色体上并成簇状分布,其中6个区间可能存在主效QTL.     

Mixed linear model approaches for analyzing genetic models of complex quantitative traits

New approaches based on general mixed linear models were presented for analyzing complex quantitative traits in animal models, seed models and QTL (quantitative trait locus) mapping models. Variances and covariances can be appropriately estimated by MINQUE (minimum norm quadratic unbiased estimation) approaches. Random genetic effects can be predicted without bias by LUP (linear unbiased prediction) or AUP (adjusted unbiased prediction) methods. Mixed-model based composite interval mapping (MCIM) methods are suitable for efficiently searching QTLs along the whole genome. Bayesian methods and Markov Chain Monte Carlo (MCMC) methods can be applied in analyzing parameters of random effects as well as their variances. Projects supported by NSFC (39670390, 39893350) and the NIH Grant GM32518     

Fine mapping of multiple interacting quantitative trait loci using combined linkage disequilibrium and linkage information

Quantitative trait loci (QTL) and their additive, dominance and epistatic effects play a critical role in complex trait variation. It is often infeasible to detect multiple interacting QTL due to main effects often being confounded by interaction effects. Positioning interacting QTL within a small region is even more difficult. We present a variance component approach nested in an empirical Bayesian method, which simultaneously takes into account additive, dominance and epistatic effects due to multiple interacting QTL. The covariance structure used in the variance component approach is based on combined linkage disequilibrium and linkage (LDL) information. In a simulation study where there are complex epistatic interactions between QTL, it is possible to simultaneously fine map interacting QTL using the proposed approach. The present method combined with LDL information can efficiently detect QTL and their dominance and epistatic effects, making it possible to simultaneously fine map main and epistatic QTL.     

Rose without prickle: genomic insights linked to moisture adaptation

Prickles act against herbivores, pathogens or mechanical injury, while also preventing water loss. However, whether prickles have new function and the molecular genetics of prickle patterning remain poorly explored. Here, we generated a high-quality reference genome assembly for ‘Basye''s Thornless’ (BT), a prickle-free cultivar of Rosa wichuraiana, to identify genetic elements related to stem prickle development. The BT genome harbors a high level of sequence diversity in itself and with cultivar ‘Old Blush’ (R. chinensis), a founder genotype in rose domestication. Inheritance of stem prickle density was determined and two QTL were identified. Differentially expressed genes in QTL were involved in water-related functions, suggesting that prickle density may hitchhike with adaptations to moist environments. While the prickle-related gene-regulatory-network (GRN) was highly conserved, the expression variation of key candidate genes was associated with prickle density. Our study provides fundamental resources and insights for genome evolution in the Rosaceae. Ongoing efforts on identification of the molecular bases for key rose traits may lead to improvements for horticultural markets.     

Use of stochastic simulations to investigate the power and design of a whole genome association study using single nucleotide

This paper presents a quick, easy to implement and versatile way of using stochastic simulations to investigate the power and design of using single nucleotide polymorphism (SNP) arrays for genome-wide association studies in farm animals. It illustrates the methodology by discussing a small example where 6 experimental designs are considered to analyse the same resource consisting of 6006 animals with pedigree and phenotypic records: (1) genotyping the 30 most widely used sires in the population and all of their progeny (515 animals in total), (2) genotyping the 100 most widely used sires in the population and all of their progeny (1 102 animals in total), genotyping respectively (3) 515 and (4) 1 102 animals selected randomly or genotyping respectively (5) 515 and (6) 1 102 animals from the tails of the phenotypic distribution. Given the resource at hand, designs where the extreme animals are genotyped perform the best, followed by designs selecting animals at random. Designs where sires and their progeny are genotyped perform the worst, as even genotyping the 100 most widely used sires and their progeny is not as powerful of genotyping 515 extreme animals.     

Influence of outliers on QTL mapping for complex traits

A method was proposed for the detection of outliers and influential observations in the framework of a mixed linear model, prior to the quantitative trait locus (QTL) mapping analysis. We investigated the impact of outliers on QTL mapping for complex traits in a mouse BXD population, and observed that the dropping of outliers could provide the evidence of additional QTL and epistatic loci affecting the 1 stBrain-OB and the 2ndBrain-OB in a cross of the abovementioned population. The results could also reveal a remarkable increase in estimating heritabilities of QTL in the absence of outliers. In addition, simulations were conducted to investigate the detection powers and false discovery rates (FDRs) of QTLs in the presence and absence of outliers. The results suggested that the presence of a small proportion of outliers could increase the FDR and hence decrease the detection power of QTLs. A drastic increase could be obtained in the estimates of standard errors for position, additive and additivex environment interaction effects of QTLs in the presence of outliers.     

Comparative mapping of QTLs for Al tolerance in rice and identification of positional Al-induced genes

Aluminum (Al) toxicity is the major factor limiting crop productivity in acid soils. In this study, a recombinant inbreed line (RIL) population derived from a cross between an A1 sensitive lowland indica rice variety IR1552 and an Al tolerant upland japonica rice variety Azucena, was used for mapping quantitative trait loci (QTLs) for A1 tolerance. Three QTLs for relative root length (RRL) were detected on chromosome 1, 9, 12, respectively, and I QTL for root length under Al stress is identical on chromosome I after one week and two weeks stress. Comparison of QTLs on chromosome 1 from different studies indicated an identical interval between C86 and RZ801 with gene(s) for Al tolerance. This interval provides an important start point for isolating genes responsible for A1 tolerance and understanding the genetic nature of Al tolerance in rice. Four Al induced ESTs located in this interval were screened by reverse Northern analysis and confirmed by Northern analysis. They would be candidate genes for the QTL.     

3D graphical visualization of the genetic architectures underlying complex traits in multiple environments

An approach for generating interactive 3D graphical visualization of the genetic architectures of complex traits in multiple environments is described. 3D graphical visualization is utilized for making improvements on traditional plots in quan- titative trait locus (QTL) mapping analysis. Interactive 3D graphical visualization for abstract expression of QTL, epistasis and their environmental interactions for experimental populations was developed in framework of user-friendly software QTLNetwork (http://ibi.zju.edu.cn/software/qtlnetwork). Novel definition of graphical meta system and computation of virtual coordinates are used to achieve explicit but meaningful visualization. Interactive 3D graphical visualization for QTL analysis provides geneticists and breeders a powerful and easy-to-use tool to analyze and publish their research results.     

QTL analysis of flag leaf in barley (Hordeum vulgare L.) for morphological traits and chlorophyll content

To understand genetic patterns of the morphological and physiological traits in flag leaf of barley, a double haploid (DH) population derived from the parents Yerong and Franklin was used to determine quantitative trait loci (QTL) controlling length, width, length/width, and chlorophyll content of flag leaves. A total of 9 QTLs showing significantly additive effect were detected in 8 intervals on 5 chromosomes. The variation of individual QTL ranged from 1.9% to 20.2%. For chlorophyll content expressed as SPAD value, 4 QTLs were identified on chromosomes 2H, 3H and 6H; for leaf length and width, 2 QTLs located on chromosomes 5H and 7H, and 2 QTLs located on chromosome 5H were detected; and for length/width, 1 QTL was detected on chromosome 7H. The identification of these QTLs associated with the properties of flag leaf is useful for barley improvement in breeding programs. Project supported by the National Natural Science Foundation of China (No. 30630047) and the Project on Absorption of Intellects by Institutions of Higher Education for Academic Disciplinary Innovations (the 111 Project) (No. B06014), China