Identification, isolation and pyramiding of quantitative trait loci for rice breeding

Many agronomically important traits are governed by several genes known as quantitative trait loci (QTLs). The identification of important, QTL-controlled agricultural traits has been difficult because of their complex inheritance; however, completion of the rice genomic sequence has facilitated the cloning of QTLs and their pyramiding for breeding. Because QTLs are derived from natural variation, the use of a wider range of variations such as that found in wild species is important. In addition, Introgression Lines (ILs) developed from wild species in combination with Marker Assisted Selection should facilitate efficient gene identification. This review describes recent developments in rice QTL analysis including mapping, cloning and pyramiding QTLs.     

作物QTL定位常用作图群体

作物大多重要农艺性状是数量性状,受多基因控制,基因之间及基因与环境之间都会发生互作,这为研究带来了很大的不便。因此,好的QTL作图群体,是研究QTL间的互作、QTL与环境的互作、QTL定位以及基因克隆的最根本保障。随着分子标记技术的发展,QTL定位的作图群体也在不断的发展并逐渐满足研究者对于QTL的精细定位及基因克隆等研究的进一步要求。文章主要综述了作物QTL定位常用作图群体的构建及优缺点。     

作物数量性状基因研究进展

分子生物技术的发展对作物数量性状基因（QTL）研究提供了条件,不同的定位群体各有其特点,相继出现的QTL定位也逐步完善。大量的研究揭示了QTL的基本特征,剖析了重要农艺4性状的遗传基础,给作物遗传改良带来了新的策略,不断深入的研究已经完成了特定的QTL的精细定位和克隆。本从QTL的定位群体,定位方法,研究现状,精细定位与克隆,以及QTL利用等方面对作物数量性状基因的研究进行了综述。     

Natural variation for carbohydrate content in Arabidopsis. Interaction with complex traits dissected by quantitative genetics

Besides being a metabolic fuel, carbohydrates play important roles in plant growth and development, in stress responses, and as signal molecules. We exploited natural variation in Arabidopsis (Arabidopsis thaliana) to decipher the genetic architecture determining carbohydrate content. A quantitative trait locus (QTL) approach in the Bay-0 x Shahdara progeny grown in two contrasting nitrogen environments led to the identification of 39 QTLs for starch, glucose, fructose, and sucrose contents representing at least 14 distinct polymorphic loci. A major QTL for fructose content (FR3.4) and a QTL for starch content (ST3.4) were confirmed in heterogeneous inbred families. Several genes associated with carbon (C) metabolism colocalize with the identified QTL. QTLs for senescence-related traits, and for flowering time, water status, and nitrogen-related traits, previously detected with the same genetic material, colocalize with C-related QTLs. These colocalizations reflect the complex interactions of C metabolism with other physiological processes. QTL fine-mapping and cloning could thus lead soon to the identification of genes potentially involved in the control of different connected physiological processes.     

植物数量性状基因的定位与克隆

作物的许多重要农艺性状属于数量性状, 鉴定和发掘控制数量性状的基因及其优异的等位变异, 并使之快速应用于育种实践是新时期作物科学家和育种学家所面临的重大课题。本文从QTL作图、QTL的精细定位与图位克隆、QTL近等基因系和染色体片断代换系的建立以及基于LD的关联分析等方面对植物数量性状的研究进展进行了讨论, 提出了以植物基因组学技术为平台, 将QTL作图与关联分析方法相结合, 是进行数量性状遗传机理研究同时服务于作物育种实践的有效途径。     

Advances in cereal genomics and applications in crop breeding

Recent advances in cereal genomics have made it possible to analyse the architecture of cereal genomes and their expressed components, leading to an increase in our knowledge of the genes that are linked to key agronomically important traits. These studies have used molecular genetic mapping of quantitative trait loci (QTL) of several complex traits that are important in breeding. The identification and molecular cloning of genes underlying QTLs offers the possibility to examine the naturally occurring allelic variation for respective complex traits. Novel alleles, identified by functional genomics or haplotype analysis, can enrich the genetic basis of cultivated crops to improve productivity. Advances made in cereal genomics research in recent years thus offer the opportunities to enhance the prediction of phenotypes from genotypes for cereal breeding.     

植物数量性状基因的定位与克隆

作物的许多重要农艺性状属于数量性状,鉴定和发掘控制数量性状的基因及其优异的等位变异,并使之快速应用于育种实践是新时期作物科学家和育种学家所面临的重大课题。本文从QTL作图、QTL的精细定位与图位克隆、QTL近等基因系和染色体片断代换系的建立以及基于LD的关联分析等方面对植物数量性状的研究进展进行了讨论,提出了以植物基因组学技术为平台,将QTL作图与关联分析方法相结合,是进行数量性状遗传机理研究同时服务于作物育种实践的有效途径。     

Multi-environment mapping and meta-analysis of 100-seed weight in soybean

100-Seed weight (100-SW) of soybean is an important but complicated quantitative trait to yield. This study was focus on the quantitative trait loci (QTLs) of soybean 100-SW from 2006 to 2010, using recombination inbred lines population that was derived from a cross between Charleston and Dongnong 594. A total of 23 QTLs for 100-SW were detected in the linkage group C2, D1a, F, G and O. Nine QTLs were identified by composite interval mapping including one QTL with the minimum confidence interval (CI) of 1.3?cM, while 14 QTLs by multiple interval mapping. Furthermore, 94 reported QTLs of 100-SW were integrated with our QTL mapping results using BioMercator. As a result, 15 consensus QTLs and their corresponding markers were identified. The minimum CI was reduced to 1.52?cM by the combination of meta-analysis. These findings may merit fine-mapping of these QTL in soybean.     

High-resolution quantitative trait locus mapping for body weight in mice by recombinant progeny testing

A major obstacle to the positional cloning of quantitative trait loci (QTLs) lies in resolving genetic factors whose allelic effects are blurred by environmental and background genetic variation. We investigate a fine-mapping approach that combines the use of an interval-specific congenic strain with progeny testing of recombinants for markers flanking a QTL. We apply the approach to map a murine QTL with an approximately 20% effect on growth rate by progeny testing 39 recombinants in a 12 cM region of the X chromosome. We use a likelihood analysis in an attempt to maximize the information on QTL map location and effect. The major X-linked effect is mapped to an approximately 2 cM region flanked by markers about 5 cM apart, outside which LOD support for the QTL drops extremely steeply by about 80. Nearly unambiguous assignment of the QTL genotypic state is obtained for each recombinant. The resolution of individual recombinants in the region is therefore sufficiently high to facilitate the positional cloning of the locus, although progress has been hampered because the genomic region containing the QTL shows an exceptionally low level of polymorphism in comparison with recent studies.     

QTL‐seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations

The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker‐assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time‐consuming and labor‐intensive. Here we report the rapid identification of plant QTLs by whole‐genome resequencing of DNAs from two populations each composed of 20–50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL‐seq as applied to plant species. We applied QTL‐seq to rice recombinant inbred lines and F₂ populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL‐seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps.     

水稻QTL分析的研究进展

水稻许多重要的性状是由多基因控制的数量性状,经典的数量遗传学只能把数量性状作为一个整体进行研究。近年来．高密度分子标记连锁图的构建和有效的生物统计学方法的发展使人们对数量性状遗传基础的研究出现了革命性的变化。通过对不同群体内的个体或品系的分子标记基因型和表型数据的共分离分析,能对QTL进行检测和定位。本文对QTL定位的原理和方法进行了介绍,从QTL的数目和效应、上位性效应、QTL基因型与环境的互作、相关性状的QTL以及个体发育不同阶段的QTL等方面对水稻QTL分析的研究进展进行了综述。水稻基因组测序计划已经完成,本文还对基因组时代水稻QTL精细定位和克隆的方法进行了探讨,对QTL分析在水稻育种中的应用前景进行了展望。     

Use of randomization testing to detect multiple epistatic QTLs

Here, we describe a randomization testing strategy for mapping interacting quantitative trait loci (QTLs). In a forward selection strategy, non-interacting QTLs and simultaneously mapped interacting QTL pairs are added to a total genetic model. Simultaneous mapping of epistatic QTLs increases the power of the mapping strategy by allowing detection of interacting QTL pairs where none of the QTL can be detected by their marginal additive and dominance effects. Randomization testing is used to derive empirical significance thresholds for every model selection step in the procedure. A simulation study was used to evaluate the statistical properties of the proposed randomization tests and for which types of epistasis simultaneous mapping of epistatic QTLs adds power. Least squares regression was used for QTL parameter estimation but any other QTL mapping method can be used. A genetic algorithm was used to search for interacting QTL pairs, which makes the proposed strategy feasible for single processor computers. We believe that this method will facilitate the evaluation of the importance at epistatic interaction among QTLs controlling multifactorial traits and disorders.     

Identification of QTLs for eight agronomically important traits using an ultra-high-density map based on SNPs generated from high-throughput sequencing in sorghum under contrasting photoperiods

The productivity of sorghum is mainly determined by agronomically important traits. The genetic bases of these traits have historically been dissected and analysed through quantitative trait locus (QTL) mapping based on linkage maps with low-throughput molecular markers, which is one of the factors that hinder precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, an ultra-high-density linkage map based on high-quality single nucleotide polymorphisms (SNPs) generated from low-coverage sequences (~0.07 genome sequence) in a sorghum recombinant inbred line (RIL) population was constructed through new sequencing technology. This map consisted of 3418 bin markers and spanned 1591.4 cM of genome size with an average distance of 0.5 cM between adjacent bins. QTL analysis was performed and a total of 57 major QTLs were detected for eight agronomically important traits under two contrasting photoperiods. The phenotypic variation explained by individual QTLs varied from 3.40% to 33.82%. The high accuracy and quality of this map was evidenced by the finding that genes underlying two cloned QTLs, Dw3 for plant height (chromosome 7) and Ma1 for flowering time (chromosome 6), were localized to the correct genomic regions. The close associations between two genomic regions on chromosomes 6 and 7 with multiple traits suggested the existence of pleiotropy or tight linkage. Several major QTLs for heading date, plant height, numbers of nodes, stem diameter, panicle neck length, and flag leaf width were detected consistently under both photoperiods, providing useful information for understanding the genetic mechanisms of the agronomically important traits responsible for the change of photoperiod.     

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。     

作物数量性状基因图位克隆研究进展

对数量性状基因(QTL)的鉴定和克隆不仅有利于从分子水平上阐明作物重要农艺性状的形成机理,而且对于有效开展这些性状的分子育种,进一步提高作物增产潜力具有重要意义.近年来作物QTL图位克隆取得了重要突破,一批QTL被成功克隆,而模式植物基因组研究的快速发展则为作物QTL图位克隆技术带来了新的策略和方法.本文就相关研究的主要进展和发展趋势进行了综述.     

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.     

Molecular mapping of QTLs for resistance to the greenbug <Emphasis Type="Italic">Schizaphis graminum</Emphasis> (Rondani) in <Emphasis Type="Italic">Sorghum bicolor</Emphasis> (Moench)

Sorghum is a worldwide important cereal crop and widely cultivated for grain and forage production. Greenbug, Schizaphis graminum (Rondani) is one of the major insect pests of sorghum and can cause serious damage to sorghum plants, particularly in the US Great Plains. Identification of chromosomal regions responsible for greenbug resistance will facilitate both map-based cloning and marker-assisted breeding. Thus, a mapping experiment was conducted to dissect sorghum genetic resistance to greenbug biotype I into genomic regions. Two hundred and seventy-seven (277) F(2) progeny and their F(2:3) families from a cross between Westland A line (susceptible parent) and PI550610 (resistant parent) combined with 118 polymorphic simple sequence repeat (SSR) markers were used to map the greenbug resistance QTLs. Composite interval mapping (CIM) and multiple interval mapping (MIM) revealed two QTLs on sorghum chromosome nine (SBI-09) consistently conditioned the resistance of host plant to the greenbug. The two QTLs were designated as QSsgr-09-01 (major QTL) and QSsgr-09-02 (minor QTL), accounting for approximately 55-80%, and 1-6% of the phenotypic variation for the resistance to greenbug feeding, respectively. These resistance QTLs appeared to have additive and partially dominant effects. The markers Xtxp358, Xtxp289, Xtxp67 and Xtxp230 closely flanked the respective QTLs, and can be used in high-throughput marker-assisted selections (MAS) for breeding new resistant parents and producing commercial hybrids.     

Mapping of quantitative trait loci (QTLs) for oil yield using SSRs and gene-based markers in African oil palm (<Emphasis Type="Italic">Elaeis guineensis</Emphasis> Jacq.)

The identification of quantitative trait loci (QTLs) based on anchor markers, especially candidate genes that control a trait of interest, has been noted to increase the power of QTL detection. Since these markers can be scored as co-dominant data, they are also valuable for comparing and integrating the QTL linkage maps from diverse mapping populations. To estimate the position and effects of QTLs linked to oil yield traits in African oil palm, co-dominant microsatellites (SSR) and candidate gene-based sequence polymorphisms were applied to construct a linkage map for a progeny showing large differences in oil yield components. The progeny was genotyped for 97 SSR markers, 93 gene-linked markers, and 12 non-gene-linked SNP markers. From these, 190 segregating loci could be arranged into 31 linkage groups while 12 markers remained unmapped. Using the single marker linkage, interval mapping and multiple QTL methods, 16 putative QTLs on seven linkage groups affecting important oil yield related traits such as fresh fruit bunch yield (FFB), ratio of oil per fruit (OF), oil per bunch (OB), fruit per bunch (FB) and wet mesocarp per fruit (WMF) could be identified in the segregating population with estimated values for explained variance ranging from 12.4 % to 54.5 %. Markers designed from some candidate genes involved in lipid biosynthesis were found to be mapped near significant QTLs for various economic yield traits. Associations between QTLs and potential candidate genes are discussed.     

Genetic and molecular dissection of quantitative traits in rice

Recent progress in the generation of a molecular genetic map and markers for rice has made possible a new phase of mapping individual genes associated with complex traits. This type of analysis is often referred to as quantitative trait locus (QTL) analysis. Increasing numbers of QTL analyses are providing enormous amounts of information about QTLs, such as the numbers of loci involved, their chromosomal locations and gene effects. Clarification of genetic bases of complex traits has a big impact not only on fundamental research on rice plant development, but it also has practical benefits for rice breeding. In this review, we summarize recent progress of QTL analysis of several complex traits in rice. A strategy for positional cloning of genes at QTLs is also discussed.     

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.