Phenotype/genotype associations for yield and salt tolerance in a barley mapping population segregating for two dwarfing genes

Barley traits related to salt tolerance are mapped in a population segregating for a dwarfing gene associated with salt tolerance. Twelve quantitative trait loci (QTLs) were detected for seven seedling traits in doubled haploids from the spring barley cross Derkado x B83-12/21/5 when given saline treatment in hydroponics. The location of QTLs for seedling growth stage (leaf appearance rate), stem weight prior to elongation, and tiller number are reported for the first time. In addition, four QTLs were found for the mature plant traits grain nitrogen and plot yield. In total, seven QTLs are co-located with the dwarfing genes sdw1, on chromosome 3H, and ari-e.GP, on chromosome 5H, including seedling leaf response (SGa) to gibberellic acid (GA(3)). QTLs controlling the growth of leaves (GS2) on chromosomes 2H and 3H and emergence of tillers (TN2) and grain yield were independent of the dwarfing genes. Field trials were grown in eastern Scotland and England to estimate yield and grain composition. A genetic map was used to compare the positions of QTLs for seedling traits with the location of QTLs for the mature plant traits. The results are discussed in relation to the study of barley physiology and the location of genes for dwarf habit and responses to GA.     

玉米叶夹角形成的遗传基础与分子机制解析*

玉米产量取决于植株捕获光能和固定CO₂合成有机化合物的效率。叶夹角是株型重要性状之一,较小叶夹角有利于提高玉米植株光合作用效率和种植密度,因而有利于提高玉米产量。研究表明玉米叶夹角为多基因控制的复杂数量性状,其遗传力较高,主要受基因的加性效应调控。目前,利用数量性状位点(quantitative trait loci, QTL)定位和全基因组关联分析(genome-wide association study, GWAS)等方法已鉴定数百个玉米叶夹角相关QTL;结合突变体分析等方法,已克隆数十个调控叶夹角关键基因,这为了解玉米叶夹角遗传机制提供了重要参考。由于前人研究所采用群体、分析方法及参考基因组版本不同,各研究之间所鉴定QTL差异较大,因此无法客观揭示叶夹角性状的遗传规律。为此,通过总结前人所定位叶夹角相关QTL和单核苷酸多态性(single nucleotide polymorphism,SNP)位点并构建一致性图谱,鉴定出叶夹角性状定位热点区间,并对调控叶夹角的已知基因进行功能分类。这不仅为了解玉米叶夹角的遗传结构、推动叶夹角相关重要基因克隆提供数据支撑,也对进一步开发叶夹角相关分子标记,指导玉米分子育种和提高玉米产量提供有益指导。     

Mapping of Defense Response Gene Homologs and Their Association with Resistance Loci in Maize

Defense response genes in higher plant species are involved in a variety of signal transduction pathways and biochemical reactions to counterattack invading pathogens. In this study, a total of 366 non-redundant defense response gene homologs （DRHs）, including 124 unigenes/expressed sequence tags, 226 tentative consensuses, and 16 DRH contigs have been identified by mining the Maize Genetics and Genomics and The Institute for Genomic Research maize databases using 35 essential defense response genes. Of 366 DRHs, 202 are mapped to 152 loci across ten maize chromosomes via both the genetic and in silico mapping approaches. The mapped DRHs seem to cluster together rather than be evenly distributed along the maize genome. Approximately half of these DHRs are located in regions harboring either major resistance genes or quantitative trait loci （QTL）. Therefore, this comprehensive DRH linkage map will provide reference sequences to identify either positional candidate genes for resistance genes and/or QTLs or to develop makers for fine-mapping and marker-assisted selection of resistance genes and/or QTLs.     

Identification of Genetic Factors Contributing to Heterosis in a Hybrid from Two Elite Maize Inbred Lines Using Molecular Markers

The use of molecular markers to identify quantitative trait loci (QTLs) affecting agriculturally important traits has become a key approach in plant genetics-both for understanding the genetic basis of these traits and to help design novel plant improvement programs. In the study reported here, we mapped QTLs (and evaluated their phenotypic effects) associated with seven major traits (including grain yield) in a cross between two widely used elite maize inbred lines, B73 and Mo17, in order to explore two important phenomena in maize genetics-heterosis (hybrid vigor) and genotype-by-environment (G x E) interaction. We also compared two analytical approaches for identifying QTLs, the traditional single-marker method and the more recently described interval-mapping method. Phenotypic evaluations were made on 3168 plots (nearly 100,000 plants) grown in three states. Using 76 markers that represented 90-95% of the maize genome, both analytical methods showed virtually the same results in detecting QTLs affecting grain yield throughout the genome, except on chromosome 6. Fewer QTLs were detected for other quantitative traits measured. Whenever a QTL for grain yield was detected, the heterozygote had a higher phenotype than the respective homozygote (with only one exception) suggesting not only overdominance (or pseudooverdominance) but also that these detected QTLs play a significant role in heterosis. This conclusion was reinforced by a high correlation between grain yield and proportion of heterozygous markers. Although plant materials were grown and measured in six diverse environments (North Carolina, Iowa and Illinois) there was little evidence for G x E interaction for most QTLs.     

Mining of Candidate Maize Genes for Nitrogen Use Efficiency by Integrating Gene Expression and QTL Data

Breeding maize varieties for high nitrogen (N) use efficiency (NUE) by marker-assisted selection using NUE quantitative trait locus (QTL) or by genetic transfer of NUE-associated genes is a viable approach for increasing grain yield in N-limited production areas. In this investigation, we evaluated a set of introgression line populations under N supply and N deficiency conditions. From 42 QTLs for grain yield and yield components, 23 were identified under N supply conditions and 33 from N limited conditions. Meta-analysis of published maize NUE QTLs revealed 37 “consensus” QTLs, of which, 18 was detected under low N conditions. In addition, 258 unique ESTs associated with low N stress response, N uptake, transport, and assimilation were aligned on the maize genome by in silico mapping. Integrating the EST map with the QTL map has resulted in the identification of candidate NUE-associated genes of the following functional categories: N uptake, transport, and assimilation; carbon (C) metabolism and assimilation; and cascades of stress response and signal transduction genes. Nine candidates that have been introgressed into Ye478 significantly altered grain yield/yield components. It is suggested that the dynamics of interactions between C and N metabolism are important for maize yield. A high NUE variety should have a highly efficient C assimilation per unit N and actively express CO₂ assimilation-related genes under N-limited conditions.     

Genetic dissection of starch paste viscosity characteristics in waxy maize revealed by high-density SNPs in a recombinant inbred line population

Starch paste viscosity properties are widely used as important indicators for quality estimation in waxy maize. To elucidate the genetic basis of paste viscosity characteristics of waxy maize, seven parameters from the rapid visco analyzer (RVA) profile were analyzed for quantitative trait loci (QTLs) in this study, using a recombinant inbred line population derived from a cross between the inbred lines Tongxi5 and Hengbai522. A high-density linkage map was constructed using 2703 bin markers, covering 1876.20 cM of the whole genome with an average genetic distance of 0.73 cM between adjacent bin markers. Seventy-two QTLs were detected for RVA parameters across 3 years, of which 17 could be identified in 2 years, and 6 identified in all 3 years. Eight QTL clusters were observed to be co-associated with two or more RVA parameters. Three major QTLs, qPV4-1, qTV4-1, and qFV5-2, which explained over 10% of the phenotypic variation, were stably mapped to the chromosomes 4 or 5 in all years. Based on functional annotations, two genes were considered as potential candidate genes for the identified major QTLs. The QTLs and candidate genes identified in this study will be useful for further understanding of the genetic architecture of starch paste viscosity characteristics in waxy maize, and may facilitate molecular breeding for grain quality improvement in breeding programs, and simultaneously provide a basis for cloning of the genes underlying these QTLs.     

Quantitative trait loci for agronomic traits in an elite barley population for Mediterranean conditions

Advances in plant breeding through marker-assisted selection (MAS) are only possible when genes or quantitative trait loci (QTLs) can contribute to the improvement of elite germplasm. A population of recombinant inbred lines (RILs) was developed for one of the best crosses of the Spanish National Barley Breeding Program, between two six-row winter barley cultivars Orria and Plaisant. The objective of this study was to identify favourable QTLs for agronomic traits in this population, which may help to optimise breeding strategies for these and other elite materials for the Mediterranean region. A genetic linkage map was developed for 217 RILs, using 382 single nucleotide polymorphism markers, selected from the barley oligonucleotide pool assay BOPA1 and two genes. A subset of 112 RILs was evaluated for several agronomic traits over a period of 2 years at three locations, Lleida and Zaragoza (Spain) and Fiorenzuola d’Arda (Italy), for a total of five field trials. An important segregation distortion occurred during population development in the region surrounding the VrnH1 locus. A QTL for grain yield and length of growth cycle was also found at this locus, apparently linked to a differential response of the VrnH1 alleles to temperature. A total of 33 QTLs was detected, most of them for important breeding targets such as plant height and thousand-grain weight. QTL × environment interactions were prevalent for most of the QTLs detected, although most interactions were of a quantitative nature. Therefore, QTLs suitable for MAS for most traits were identified.     

Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.)

Development of high-yielding wheat varieties with good end-use quality has always been a major concern for wheat breeders. To genetically dissect quantitative trait loci (QTLs) for yield-related traits such as grain yield, plant height, maturity, lodging, test weight and thousand-grain weight, and for quality traits such as grain and flour protein content, gluten strength as evaluated by mixograph and SDS sedimentation volume, an F₁-derived doubled haploid (DH) population of 185 individuals was developed from a cross between a Canadian wheat variety “AC Karma” and a breeding line 87E03-S2B1. A genetic map was constructed based on 167 marker loci, consisting of 160 microsatellite loci, three HMW glutenin subunit loci: Glu-A1, Glu-B1 and Glu-D1, and four STS-PCR markers. Data for investigated traits were collected from three to four environments in Manitoba, Canada. QTL analyses were performed using composite interval mapping. A total of 50 QTLs were detected, 24 for agronomic traits and 26 for quality-related traits. Many QTLs for correlated traits were mapped in the same genomic regions forming QTL clusters. The largest QTL clusters, consisting of up to nine QTLs, were found on chromosomes 1D and 4D. HMW glutenin subunits at Glu-1 loci had the largest effect on breadmaking quality; however, other genomic regions also contributed genetically to breadmaking quality. QTLs detected in the present study are compared with other QTL analyses in wheat.     

Genetic dissection of the relationship between carbon metabolism and early growth in maize,with emphasis on key-enzyme loci

The determinism of carbon metabolism traits during early growth in maize has been investigated using a marker-based quantitative genetics approach. In addition to growth traits, concentration of carbohydrates and activity of four key enzymes of their metabolism (sucrose phosphate synthase, ADP-glucose pyrophosphorylase, invertases and sucrose synthase) have been measured in leaves of individuals of a recombinant inbred line population. Using more than 100 RFLP markers, quantitative trait loci (QTLs) were mapped for each biochemical and developmental trait. Causal relationships, suggested by previous physiological studies, were reinforced by common locations of QTLs for different traits. Thus, the strong correlation between growth rate and invertase activity, which may reflect sink organ strength, could be explained to a large extent by a single region of chromosome 8. Moreover, some of the structural genes of the enzymes mapped to regions with QTLs affecting the activity of the encoded enzyme and/or concentration of its product, and sometimes growth traits. These results emphasize the possible role of the polymorphism of key-enzyme genes in physiological processes, and hence in maize growth.     

Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat

Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.     

玉米株高和穗位高的遗传基础与分子机制*

株高和穗位高是玉米重要育种性状,直接影响植株的养分利用效率及抗倒伏性,进而影响玉米产量。玉米株高和穗位高属于典型数量性状,目前通过数量性状位点(quantitative trait loci mapping,QTL)定位和全基因组关联分析(genome-wide association study, GWAS)等方法已挖掘到较多相关遗传位点,通过QTL精细定位及利用突变体克隆了一些调控株高和穗位高关键基因。但是由于各研究组所利用的群体类型和大小、标记类型和密度以及统计方法不同,所鉴定QTL差异较大,单个研究难以揭示玉米株高和穗位高遗传结构。早期QTL定位的结果多以遗传距离来展示,不同时期GWAS研究所使用参考基因组版本不同,这进一步增加了借鉴和利用前人研究结果的难度。首次将目前已鉴定株高和穗位高遗传定位信息统一锚定至玉米自交系B73参考基因组V4版本,构建了株高和穗位高性状定位的一致性图谱,并鉴定出可被多个独立研究定位的热点区间。进一步对已克隆玉米株高和穗位高调控基因进行总结与分类,揭示株高和穗位高性状调控机制,对深度解析株高和穗位高遗传结构、指导基因克隆和利用分子标记辅助选择优化玉米株高和穗位高性状均具有重要意义。     

Toward understanding genetic mechanisms of complex traits in rice

Rice is the primary carbohydrate staple cereal feeding the world population. Many genes, known as quantitative trait loci (QTLs), con-trol most of the agronomically important traits in rice. The identification of QTLs controlling agricultural traits is vital to increase yield and meet the needs of the increasing human population, but the progress met with challenges due to complex QTL inheritance. To date,many QTLs have been detected in rice, including those responsible for yield and grain quality; salt, drought and submergence tolerance;disease and insect resistance; and nutrient utilization efficiency. Map-based cloning techniques have enabled scientists to successfully fine map and clone approximately seventeen QTLs for several traits. Additional in-depth functional analyses and characterizations of these genes will provide valuable assistance in rice molecular breeding.     

Mapping quantitative trait loci for yield,yield components and morphological traits in an advanced backcross population between <Emphasis Type="Italic">Oryza rufipogon</Emphasis> and the <Emphasis Type="Italic">Oryza sativa</Emphasis> cultivar Jefferson

An advanced backcross population between an accession of Oryza rufipogon (IRGC 105491) and the U.S. cultivar Jefferson (Oryza sativa ssp. japonica) was developed to identify quantitative trait loci (QTLs) for yield, yield components and morphological traits. The genetic linkage map generated for this population consisted of 153 SSR and RFLP markers with an average interval size of 10.3 cM. Thirteen traits were examined, nine of which were measured in multiple environments. Seventy-six QTLs above an experiment-wise significance threshold of P<0.01 (corresponding to an interval mapping LOD>3.6 or a composite interval mapping LOD>3.9) were identified. For the traits measured in multiple environments, 47% of the QTLs were detected in at least two environments. The O. rufipogon allele was favorable for 53% of the yield and yield component QTLs, including loci for yield, grains per panicle, panicle length, and grain weight. Morphological traits related to the domestication process and/or weedy characteristics, including plant height, shattering, tiller type and awns, were found clustered on chromosomes 1 and 4. Comparisons to previous studies involving wild x cultivated crosses revealed O. rufipogon alleles with stable effects in multiple genetic backgrounds and environments, several of which have not been detected in studies between Oryza sativa cultivars, indicating potentially novel alleles from O. rufipogon. Some O. rufipogon-derived QTLs, however, were in similar regions as previously reported QTLs from Oryza sativa cultivars, providing evidence for conservation of these QTLs across the Oryza genus. In addition, several QTLs for grain weight, plant height, and flowering time were localized to putative homeologous regions in maize where QTLs for these traits have been previously reported, supporting the hypothesis of functional conservation of QTLs across the grasses.     

Molecular-marker-facilitated studies of morphological traits in maize. II: Determination of QTLs for grain yield and yield components

Genetic factors controlling quantitative inheritance of grain yield and its components have not previously been investigated by using replicated lines of an elite maize (Zea mays L.) population. The present study was conducted to identify quantitative trait loci (QTLs) associated with grain yield and grain-yield components by using restriction fragment length polymorphism (RFLP) markers. A population of 150 random F₂₃ lines was derived from the single cross of inbreds Mo17 and H99, which are considered to belong to the Lancaster heterotic group. Trait values were measured in a replicated trial near Ames, Iowa, in 1989. QTLs were located on a linkage map constructed with one morphological and 103 RFLP loci. QTLs were found for grain yield and all yield components. Partial dominance to overdominance was the primary mode of gene action. Only one QTL, accounting for 35% of the phenotypic variation, was identified for grain yield. Two to six QTLs were identified for the other traits. Several regions with pleiotropic or linked effects on several of the yield components were detected.     

Molecular mapping of quantitative trait loci for three kernel-related traits in maize using a double haploid population

Kernel size and kernel weight are important factors possibly involved in the determination of grain yield in maize, so identifying the genetic basis of kernel-related traits provides insights into the breeding of high-yield maize varieties. Kernel length (KL), kernel width (KW) and hundred kernel weight (HKW) were evaluated in three various planting conditions for the 240 field-grown double haploid (DH) lines derived from the single-cross hybrid Xianyu335. Variations in KL, KW and HKW were observed among DH lines, and all three traits showed a broad sense heritability of 76%. A total of 964 single nucleotide polymorphisms (SNPs) from the MaizeSNP3072 chip was utilised to create a high-density genetic map of 1546.4 cM and to identify quantitative trait loci (QTLs). Using composite interval mapping, a total of five, seven and five QTLs have been mapped for KL, KW and HKW, respectively. qkl1-2 and qkl4-1 explained 17.8% and 14.2% of the phenotypic variation in KL, respectively, and the other three QTLs contributed 3.2–4.0%. The phenotypic variation explained (PVE) of seven QTLs responsible for KW ranged from 3.3 to 9.5%. Three QTLs for HKW, qhkw1, qhkw5 and qhkw10 each explained more than 10% of the phenotypic variation, and qhkw4 and qhkw9 accounted for 3.0% and 6.0%, respectively. Due to their detection in multiple planting environments, the loci mapped here appear to be potential targets for the improvement of maize grain yield.     

水稻籼粳交DH群体收获指数及源库性状的QTL分析

以 1个水稻籼粳交 (圭 6 30 0 2 4 2 8)来源的DH群体为材料 ,利用 1张含有 2 32个标记的RFLP连锁图谱和基于混合线性模型的定位软件QTLMapper1 0对水稻收获指数及生物量、籽粒产量、库容量和株高 5个性状进行QTL分析 ,共检测到 2 1个主效应QTLs和 9对上位性互作位点。其中 ,控制籽粒产量的 3个QTLs合计贡献率为 4 2 % ,LOD值为 7 10 ;这 3个QTLs或者与收获指数的QTL同位 ,或者与生物量的QTL同位 ,且加性效应的方向一致 ,从而揭示了“籽粒产量 =生物量×收获指数”的遗传基础所在。控制收获指数的 4个QTLs合计贡献率为 4 6 % ,LOD值为 10 3;控制生物量的 4个QTLs合计贡献率为 6 4 % ,LOD值为 14 0 9;收获指数的 4个QTLs与生物量的 4个QTLs均不同位。因此 ,通过基因重组 ,可能实现控制收获指数和生物量的增效基因的聚合 ,由此获得收获指数和生物量“双高”的基因型。检测到 5个株高QTLs,其合计贡献率为 6 4 % ,LOD值为 11 6 2 ;其中 ,有 3个效应较小的QTLs与生物量、库容量和 或籽粒产量QTLs同位 ,且同位QTLs的加性效应方向一致 ;未发现株高QTLs与收获指数QTLs的同位性。由此表明 ,株高与“源 流 库”概念中的“源”和“库”在遗传上有一定程度的关联 ,而与“流”无关联。此外还发现 ,在上述同位性QTL     

Can genetic variability for nitrogen metabolism in the developing ear of maize be exploited to improve yield?

Quantitative trait loci (QTLs) for the main steps of nitrogen (N) metabolism in the developing ear of maize (Zea mays L.) and their co-localization with QTLs for kernel yield and putative candidate genes were searched in order to identify chromosomal regions putatively involved in the determination of yield. During the grain-filling period, the changes in physiological traits were monitored in the cob and in the developing kernels, representative of carbon and N metabolism in the developing ear. The correlations between these physiological traits and traits related to yield were examined and localized with the corresponding QTLs on a genetic map. Glycine and serine metabolism in developing kernels and the cognate genes appeared to be of major importance for kernel production. The importance of kernel glutamine synthesis in the determination of yield was also confirmed. The genetic and physiological bases of N metabolism in the developing ear can be studied in an integrated manner by means of a quantitative genetic approach using molecular markers and genomics, and combining agronomic, physiological and correlation studies. Such an approach leads to the identification of possible new regulatory metabolic and developmental networks specific to the ear that may be of major importance for maize productivity.