Experimental evaluation of several cycles of marker-assisted selection in maize

A program was initiated in 1994 to compare the efficiency of marker-assisted selection (MAS) and conventional phenotypic selection. A population of 300 F_3:4 families was generated from the cross between two maize inbred lines F2 and F252 and selected on an index combining grain yield and grain moisture at harvest. This population was characterised for 93 RFLP markers and evaluated as testcrosses in a large range of environments. Three methods of selection were applied (i) two cycles of conventional phenotypic selection; (ii) two cycles of MAS based on an index combining phenotypic values and QTL genetic values and (iii) one cycle of combined MAS followed by two cycles of selection based only on the QTL effects estimated in the first generation. The different populations were characterised for RFLP markers. The evolution of allele frequencies showed that selection on only-markers was very efficient for fixing QTL alleles found favourable in the initial population. This evolution was quite different from that observed for phenotypic selection or combined MAS. Genetic gain was evaluated and found significant for each method of selection. Nevertheless, the difference between phenotypic selection and combined MAS was not significant. The two additional cycles of MAS on only-markers did not improve significantly the genetic value of the population. Moreover, the genetic variance of this population remained high, despite most of the QTL initially detected were almost fixed. The results suggest that the QTL effects estimated in the initial population were not stable due to epistasis and/or QTL by environment interactions. This revised version was published online in July 2006 with corrections to the Cover Date.     

人工神经网络在作物基因组选择中的应用

目前, 基因组选择育种主要采用线性模型估计遗传育种值指导作物遗传育种的筛选过程, 但是生物体内的基因以及遗传位点的关系主要是复杂的非线性调控。本研究将人工神经网络技术应用到作物基因组选择育种中, 对现有的作物基因组选择育种模型进行优化, 建立了高效的作物基因组选择预测系统, 并与其他线性回归预测模型进行比较。通过分析小麦的育种数据发现, 基于人工神经网络的遗传育种估计效果优于其他线性回归预测模型, 预测育种值与实际育种值间的相关系数平均值达到0.6636, 相应的岭回归BLUP、贝叶斯线性回归模型和基于系谱信息的贝叶斯回归模型的预测能力分别为0.6422、0.6294和0.6573; 最优的预测效果达到0.8379, 远高于其他2种模型的最优结果。同时, 基于人工神经网络的基因组选择模型的预测效果稳定, 与传统的统计模型相近, 因此, 利用人工神经网络技术建立基因组选择是可行的。     

Validation of a major QTL for scab resistance with SSR markers and use of marker-assisted selection in wheat

The objectives of this study were to validate the major quantitative trait locus (QTL) for scab resistance on the short arm of chromosome 3B in bread wheat and to isolate near‐isogenic lines for this QTL using marker‐assisted selection (MAS). Two resistant by susceptible populations, both using ‘Ning7840’ as the source of resistance, were developed to examine the effect of the 3BS QTL in different genetic backgrounds. Data for scab resistance and simple sequence repeat (SSR) markers linked to the resistance QTL were analyzed in the F_2:3 lines of one population and in the F_3:4 lines of the other. Markers linked to the major QTL on chromosome 3BS in the original mapping population (‘Ning7840’/‘Clark’) were closely associated with scab resistance in both validation populations. Marker‐assisted selection for the QTL with the SSR markers combined with phenotypic selection was more effective than selection based solely on phenotypic evaluation in early generations. Marker‐assisted selection of the major QTL during the seedling stage plus phenotypic selection after flowering effectively identified scab resistant lines in this experiment. Near‐isogenic lines for this 3BS QTL were isolated from the F₆ generation of the cross ‘Ning7840’/‘IL89‐7978’ based on two flanking SSR markers, Xgwm389 and Xbarc147. Based on these results, MAS for the major scab resistance QTL can improve selection efficiency and may facilitate stacking of scab resistance genes from different sources.     

Genome mapping and molecular markers identification for yield,yield component and fibre quality traits in tetraploid cotton

The identification of quantitative trait loci (QTL) across different environments is a prerequisite for marker‐assisted selection (MAS) in crop improvement programmes. CottonSNP63k Illumina infinium array was used for genotyping 178 inter‐specific recombinant inbred lines and the parents, and identified 1,667 homozygous polymorphic markers between the parents. Of these, 1,430 markers were used for the construction of linkage map after removing 237 redundant markers. The genetic map spans a total genetic length of 3,149.8 cM with an average marker interval size of 2.2 cM. The phenotypic data from five environments were analysed separately using inclusive composite interval mapping which identified a total of 56 QTL explaining phenotypic variances (PVE) in the range of 8.18%–28.91%. There were 11 and 24 major QTL found for fibre quality and yield components, respectively. A total of 64 QTL were identified through Multi‐Environment Trials analysis, of which 34 recorded QTL × Environment interactions.     

Quantitative trait loci mapping of freezing tolerance and photosynthetic acclimation to cold in winter two‐ and six‐rowed barley

Photoacclimation (PA) and freezing tolerance (FT) have been identified as closely related traits, due to common mechanisms of environmental control. In this study, diversity array technology (DArT) was used for identification of the quantitative trait loci (QTL) of FT and PA in winter barley. Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers were subsequently used to saturate QTL regions. Two F₂ mapping populations were created, for two‐rowed (P44) and six‐rowed barley (CaP). Different regions of the genome were responsible for differences in traits between parents in these two populations. Eleven QTLs were identified in the P44 population, including five typical for FT and PA, on chromosomes 2H, 3H and 7H. In the CaP population, only one QTL connected with PA and 10 connected with FT were found on all chromosomes except 2H. Our results demonstrate that different sets of markers should be applied in marker‐assisted selection for FT in two‐ and six‐rowed barley, as several loci determine FT at the level of biparental crosses.     

Quantitative trait loci of frost tolerance and physiologically related trait in faba bean (Vicia faba L.)

In faba bean, field based winter-hardiness is a complex trait that is significantly correlated to frost tolerance. Frost tolerance could be used to indirectly select for faba bean winter-hardiness. The aim of this study was to identify putative QTL associated with frost tolerance and auxiliary traits and to quantify the efficiency of marker assisted selection. Thus, 101 recombinant inbred lines derived from the cross between two frost tolerant lines were tested for their hardened and unhardened frost tolerance and for their leaf fatty acid content in both treatments. Significant differences among the RIL were observed for all studied traits. For frost tolerance, five putative QTL were detected; three for unhardened frost tolerance that explained 40.7% (8.6% after cross-validation, CV) of its genotypic variance and two for hardened frost tolerance that explained 21.8% (1.0% after CV). For fatty acid content, three QTL were detected for oleic acid content in unhardened leaves that explained 62.9% (40.6% after CV) of its genotypic variance. This fatty acid was significantly correlated with unhardened frost tolerance. The unbiased genotypic variance explained enabled to draw realistic prospects of MAS for frost tolerance. In this study, combined MAS was more efficient than classical phenotypic selection and was expected to be higher on larger populations at early generations. Moreover, favourable alleles inherited from the exotic line BPL 4628 could be introgressed to European winter-hardy beans for further improvement.     

QTL detection of seven spike-related traits and their genetic correlations in wheat using two related RIL populations

Spike-related traits contribute greatly to grain yield in wheat. To localize wheat chromosomes for factors affecting the seven spike-related traits??i.e., the spike length (SL), the basal sterile spikelet number (BSSN), the top sterile spikelet number (TSSN), the sterile spikelet number in total (SSN), the spikelet number per spike (SPN), the fertile spikelet number (FSN) and the spike density (SD)??two F_8:9 recombinant inbred line (RIL) populations were generated. They were derived from crosses between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY), comprising 485 and 229 lines, respectively. Combining the two new linkage maps and the phenotypic data collected from the four environments, we conducted quantitative trait locus (QTL) detection for the seven spike-related traits and evaluated their genetic correlations. Up to 190 putative additive QTL for the seven spike-related traits were detected in WJ and WY, distributing across all the 21 wheat chromosomes. Of these, at least nine pairwise QTL were common to the two populations. In addition, 38 QTL showed significance in at least two of the four different environments, and 18 of these were major stable QTL. Thus, they will be of great value for marker assisted selection (MAS) in breeding programs. Though co-located QTL were universal, every trait owned its unique QTL and even two closely related traits were not excluded. The two related populations with a large/moderate population size made the results authentic and accurate. This study will enhance the understanding of the genetic basis of spike-related traits.     

A comparison of marker-assisted and phenotypic selection for high grain protein content in spring wheat

Wheat grain protein content (GPC) is a primary end-use quality determinant for hard spring wheat (Triticum aestivum L.), and marker-assisted selection (MAS) could help plant breeders to develop high GPC cultivars. Two experiments were conducted using two populations developed by crossing low GPC cultivars (Ember) and (McVey) with (Glupro), which contains a high GPC QTL from Triticum dicoccoides (DIC). In one experiment, MAS and phenotypic selection (PS) were employed to select high GPC genotypes, and the selected genotypes were grown in six North Dakota (ND), USA environments. In a second experiment, molecular markers were used to select BC₂F₂ plants from each marker class for the DIC allele from each population. These plants were twice self-pollinated to produce BC₂F₄ plants, which were grown in single ND and Minnesota (MN) environments. Mean GPC was highest among lines using PS at two environments and not significantly different between MAS and PS in the other four environments. Lines presumably homozygous for DIC alleles had significantly higher GPC than their respective low GPC parents. The phenotypic GPC variation explained by the markers (r ²) was 30% at the ND and 15% at the MN environment. The use of PS was as effective as MAS in selecting for high GPC genotypes and more effective in some environments. This likely can be attributed to PS enabling selection for both the major QTL and other genes contributing to GPC. The use of molecular markers might be more advantageous for transferring the high GPC DIC QTL in a backcrossing program during parent development.     

Mapping of quantitative trait loci conferring resistance to bacterial wilt in tobacco (Nicotiana tabacum L.)

Tobacco bacterial wilt (TBW) is one of the most serious tobacco diseases in the world. Studies have shown that tobacco resistance to TBW is quantitatively inherited. This study aimed to map quantitative trait loci (QTL) conferring TBW resistance. An F_2 : 3 population containing 237 lines was developed from a cross between two flue‐cured tobacco cultivars, ‘Yanyan 97’ (YY97; moderately resistant to TBW) and ‘Honghua Dajinyuan’ (HD; highly susceptible to TBW), and a linkage map consisting of 201 simple sequence repeats (SSR) markers and spanning a total length of 2326.7 cM was constructed based on the population. Field experiments were conducted 2011 and 2012, and disease symptoms were investigated three times in each year. The phenotypic data were analysed either separately or jointly for QTL mapping using the software QTLNetwork 2.1. Eight QTL with significant main effects were mapped on chromosomes 2, 6, 12, 17 and 24. A major QTL (qBWR17a) was detected on chromosome 17, which explained up to 30% of the phenotypic variation. The results can facilitate marker‐assisted selection (MAS) in TBW resistance breeding programme.     

Quantitative trait loci for early maturity and their potential in breeding for earliness in Brassica juncea

A doubled haploid population of Brassica juncea, developed from a cross between two parental lines differing for days to maturity, was used to study the efficiency of indirect selection for a primary trait through selection of secondary trait(s) over direct selection for the primary trait when quantitative trait loci information is available for both primary and secondary traits, and applied. Days to maturity was considered as primary trait, while days to first flowering, days to end of flowering, flowering period and plant height were considered as secondary traits. An RFLP linkage map was employed for QTL analysis of maturity and maturity-determinant traits, and a stable QTL B6 simultaneously affecting these two types of traits was identified. This linked QTL explained 11.7% phenotypic variation for days to maturity, 20.7% variation for days to first flowering, 24.3% variation for days to end of flowering and 14.4% variation for plant height. Phenotypic evaluation of maturity and/or maturity-determinant traits, viz. days to first flowering, days to end of flowering and plant height revealed that limited genetic advance for early maturity can be achieved through phenotypic selection of the primary and/or the secondary trait(s). However, the estimates of genetic advance for early maturity based on combined phenotypic evaluation and linked QTL data was found to be, at least, three times higher compared to genetic advance based on phenotypic evaluation only, demonstrating the potential of marker-assisted selection in breeding for early maturity in B. juncea.     

IBD-based QTL detection in inbred pedigrees: A case study of cereal breeding programs

Mapping quantitative trait loci in plants is usually conducted using a population derived from a cross between two lines. The power of such QTL detection and mapping strategies and the estimation of the effects highly depend on the choice of the two parental lines. Thus, the QTL detected in such populations only represent a small part of the genetic architecture of the trait. Besides, the effects of only two alleles are characterized, which is of limited interest to the breeder. On the other hand, common pedigree breeding material remains unexploited for QTL mapping. From a pre-breeding perspective, the utilization of the good quality phenotypic data generated by breeders can be improved through the search and manipulation of QTL. The development of statistical techniques suitable for QTL mapping in general conventional breeding populations is thus challenging. In this study, we extend QTL mapping methodology to a generalized framework, based on a two-step IBD variance component approach, applicable to any type of breeding population coming from inbred parents. The proposed developments attempt to make full use of any inferable relatedness information between the parents. The power and accuracy of this method were assessed on simulated data mimicking conventional breeding programs in cereals, in an effort to reproduce actual conditions of marker and gene allelic frequencies across the parental lines. A wide range of breeding scenarios and of genetic architectures was explored. We demonstrated that taking into account the estimable relatedness between the parents significantly improved the power and accuracy of the QTL parameter estimations. This revised version was published online in July 2006 with corrections to the Cover Date.     

Marker-assisted selection for complex trait in common bean (Phaseolus vulgaris L.) using QTL-based index

A procedure was developed for marker-assisted selection of complex traits for common bean (Phaseolus vulgarisL.) using an index based on QTL-linked markers and ultrametric genetic distances between lines and a target parent. A comparison of the mean seed yields of the top five lines selected by different schemes demonstrated that the highest yielding group was selected on the basis of a combination of phenotypic performance and a high QTL-based index,followed by groups identified by a high QTL-based-index, conventional selection,and a low QTL-based-index. This study demonstrated a simple way to use information obtained from QTL studies to make selection decisions. The study also showed that the use of the QTL-based-index in conjunction with the ultrametric genetic distance to the target parent would enablea plant breeder to select lines that retain important QTL in a desirable genetic background. Therefore, this type of MAS would be expected to be superior to the phenotypic selection. This revised version was published online in August 2006 with corrections to the Cover Date.     

Identifying quantitative trait loci for the general combining ability of yield-relevant traits in maize

Maize is the most important staple crop worldwide. Many of its agronomic traits present with a high level of heterosis. Combining ability was proposed to exploit the rule of heterosis, and general combining ability (GCA) is a crucial measure of parental performance. In this study, a recombinant inbred line population was used to construct testcross populations by crossing with four testers based on North Carolina design II. Six yield-relevant traits were investigated as phenotypic data. GCA effects were estimated for three scenarios based on the heterotic group and the number of tester lines. These estimates were then used to identify quantitative trait loci (QTL) and dissect genetic basis of GCA. A higher heritability of GCA was obtained for each trait. Thus, testing in early generation of breeding may effectively select candidate lines with relatively superior GCA performance. The GCA QTL detected in each scenario was slightly different according to the linkage mapping. Most of the GCA-relevant loci were simultaneously detected in all three datasets. Therefore, the genetic basis of GCA was nearly constant although discrepant inbred lines were appointed as testers. In addition, favorable alleles corresponding to GCA could be pyramided via marker-assisted selection and made available for maize hybrid breeding.     

QTL analysis for early-maturing traits in cotton using two upland cotton (Gossypium hirsutum L.) crosses

Making use of the markers linked closely to QTL for early-maturing traits for MAS (Marker-assisted selection) is an effective method for the simultaneous improvement of early maturity and other properties in cotton. In this study, two F₂ populations and their F_2:3 families were generated from the two upland cotton (Gossypium hirsutum L.) crosses, Baimian2 × TM-1 and Baimian2 × CIR12. QTL for early-maturing traits were analyzed using F_2:3 families. A total of 54 QTL (31 suggestive and 23 significant) were detected. Fourteen significant QTL had the LOD scores not only > 3 but also exceeding permutation threshold. At least four common QTL, qBP-17 for bud period (BP), qGP-17a/qGP-17b (qGP-17) for growth period (GP), qYPBF-17a/qYPBF-17b (qYPBF-17) for yield percentage before frost (YPBF) and qHFFBN-17 for height of first fruiting branch node (HFFBN), were found in both populations. These common QTL should be reliable and could be used for MAS to facilitate early maturity. The common QTL, qBP-17, had a LOD score not only > 3 but also exceeding permutation threshold, explaining 12.6% of the phenotypic variation. This QTL should be considered preferentially in MAS. Early-maturing traits of cotton are primarily controlled by dominant and over-dominant effects.     

Localization of QTL for basal root thickness in <Emphasis Type="Italic">japonica</Emphasis> rice and effect of marker-assisted selection for a major QTL

Root traits are key components of plant adaptation to drought environment. By using a 120 recombined inbred lines (RILs) rice population derived from a cross between IRAT109, a japonica upland rice cultivar and Yuefu, a japonica lowland rice cultivar, a complete genetic linkage map with 201 molecular markers covering 1,833.8 cM was constructed and quantitative trait loci (QTLs) associated with basal root thickness (BRT) were identified. A major QTL, conferring thicker BRT, located on chromosome 4, designated brt4, explained phenotypic variance of 20.6%, was selected as target QTL to study the effects of marker-assisted selection (MAS) using two early segregating populations derived from crosses between IRAT109 and two lowland rice cultivars. The results showed that the flanking markers of brt4 were genetically stable in populations with different genetic backgrounds. In the two populations under upland conditions, the difference between the means of BRT of plants carrying positive and negative favorable alleles at brt4 flanking markers loci was significant. Phenotypic effects of BRT QTL brt4 were 5.05–8.16%. When selected plants for two generations were planted at Beijing and Hainan locations under upland conditions, MAS effects for BRT QTL brt4 were 4.56–18.56% and 15.46–26.52% respectively. The means of BRT for the homozygous plants were greater than that of heterozygous plants. This major QTL might be useful for rice drought tolerance breeding. L. Liu and P. Mu are contributed equally to this work.     

Dissection of genetic architecture for oil content in soybean seed using two backcross populations

Soybean seed oil was valued in foods, animal feed and some industrial applications. Molecular marker‐assisted selection (MAS) for high‐oil‐content cultivars was an important method for soybean breeders. The objective of this study was to identify quantitative trait loci (QTL) and epistatic QTL underlying the seed oil content of soybeans across two backcross (BC) populations (with one common male parent ‘Dongnong47’) and two different environments. Two molecular genetic maps were constructed. They encompassed 1046.8 cM [with an average distance of 6.75 cM in the ‘Dongnong47’  ×  ‘Jiyu89’ (DJ) population] and 846.10 cM [with an average distance of 5.76 cM in the ‘Dongnong47’  ×  ‘Zaoshu18’ (DZ) population]. Nine and seven QTL were identified to be associated with oil content in the DJ and DZ populations, respectively. The phenotypic variation explained by most of the QTL was usually less than 10%. Among the identified QTL, those stable ones across multiple environments and populations often had stronger additive effects. In addition, three stable QTL in the DZ populations were identified in the similar genomic region of the three QTL in the DJ population [qDJE and qDZE‐1 were located near Satt151 of Chromosome 15 (Chr15), qDJA1 and qDZA1 were located near Satt200 of Chr15 (LG A1), and qDJD2‐1 and qDZD2‐1 were located near Sat365 of Chr17]. In conclusion, MAS will be able more effectively to combine beneficial alleles of the different donors to design new genotypes with higher soybean seed oil content using the BC populations.     

数量性状基因的完备区间作图方法

结合分子标记和表型数据的QTL作图已成为数量性状遗传分析的常规方法。复合区间作图是近10多年来广泛应用的一种QTL定位方法,但它在算法上有一些缺陷,致使QTL效应可能会被侧连标记区间之外的标记变量吸收,同时不同的背景标记选择方法对作图结果的影响较大,并且难以推广到上位型互作QTL的定位。针对这些问题,笔者提出完备区间作图方法。本文介绍了该方法的遗传和统计原理,并通过一个大麦加倍单倍体群体说明其在定位加性QTL和加性×加性互作QTL中的应用。完备区间作图包含两个步骤：首先利用所有标记的信息,通过逐步回归选择重要的标记变量并估计其效应;然后利用逐步回归得到的线性模型校正表型数据,通过一维扫描定位加(显)性效应QTL,通过二维扫描定位上位型互作QTL。这种作图策略简化了复合区间作图中控制背景遗传变异的过程,提高了对QTL的检测功效。     

标记辅助选择育种中QTL基因型的多点联合推断

传统的育种方法对数量性状的选择存在很大难度,现代分子标记技术为实现控制数量性状基因的准确选择提供了有效的技术手段。目前分子标记辅助选择实践仅是对标记基因型的选择,而非直接对QTL基因型进行选择。尽管标记基因型容易获得,但标记基因型通常并非QTL基因型,除非有关的QTL恰巧在标记座位。因此,如何鉴别QTL的基因型成为分子标记辅助选择的关键。QTL基因型通常需要通过分子标记基因型进行推断,由于标记信息的不完全或缺失,使得对个体QTL基因型的鉴别会发生困难。本文在四向杂交设计的基础上,结合贝叶斯理论和马尔可夫链原理,提出一种通用的QTL基因型多点联合推断方法,该方法能够很方便地处理显性标记和缺失标记,同时结合标记信息和表型数据联合推断QTL基因型的条件概率。模拟研究发现,表型数据选择的效果较差,其选择的个体QTL基因型基本上都是错误的,而应用本文所论述的方法,将表型数据与标记数据相结合选择,对QTL基因型的判断正确,且推断的把握性很高。     

Optimizing phenotypic and genotypic selection for Fusarium head blight resistance in wheat

Fusarium head blight (FHB), or head scab, is an economically important disease of wheat (Triticum aestivum L.). In developing FHB-resistant soft winter wheat cultivars, breeders have relied on phenotypic selection, marker assisted selection (MAS), or a combination of the two. The objectives of this study were to estimate heritability of resistance in a resistant × susceptible cross and to simulate selection in order to determine the optimal combination of phenotypic and genotypic selection. F₂ derived lines from the cross of KY93C-1238-17-2 (high yielding, susceptible) × VA01W-476 (resistant line with two exotic quantitative trait loci (QTL) and additional resistance) were grown under artificial inoculation in scab nurseries at Lexington (2007 and 2008) and Princeton (2008), KY. Visual symptoms were estimated on a 1–3 scale; percentage Fusarium damaged kernels (FDK), and deoxynivalenol (DON) concentration were measured. VA01W-476 contributed resistance alleles at two major QTL: Fhb1 and a QTL on chromosome 2DL, QFhs.nau-2DL. In this genetic background, the effect of QFhs.nau-2DL was more pronounced than that of Fhb1: 55 vs. 25% DON reduction and 40 vs. 32% FDK reduction. Genotypic selection based on both QTL was equivalent to phenotypic selection of the most resistant 28% of the population for DON and the most resistant 24% of the population for FDK. We propose that an initial round of phenotypic selection at moderate selection intensity will enrich the population with major QTL resistance alleles while maintaining variation at minor scab resistance loci and for other traits in general. Genotyping can then be used to extract lines whose phenotypic worth has been demonstrated and which are homozygous for resistance alleles at the major QTL.     

Validation of two major quantitative trait loci for fusarium head blight resistance in Chinese wheat line W14

Identity of quantitative trait loci (QTL) governing resistance to fusarium head blight (FHB) initial infection (type I), spread (type II), kernel infection, and deoxynivalenol (DON) accumulation was characterized in Chinese wheat line W14. Ninety‐six double‐haploid lines derived from a cross of W14 × ’Pion2684’ were evaluated for FHB resistance in two greenhouse and one field experiment. Two known major QTL were validated on chromosomes 3BS and 5AS in W14 using the composite interval mapping method. The 3BS QTL had a larger effect on resistance than the 5AS QTL in the greenhouse experiments, whereas, the 5AS QTL had a larger effect in the field experiment. These two QTL together explained 33%, 35%, and 31% of the total phenotypic variation for disease spread, kernel infection, and DON concentration in the greenhouse experiments, respectively. In the field experiment, the two QTL explained 34% and 26% of the total phenotypic variation for FHB incidence and severity, respectively. W14 has both QTL, which confer reduced initial infection, disease spread, kernel infection, and DON accumulation. Therefore, marker‐assisted selection (MAS) for both QTL should be implemented in incorporating W14 resistance into adapted backgrounds. Flanking markers Xbarc133 and Xgwm493 on 3BS and Xbarc117 and Xbarc56 on 5AS are suggested for MAS.