QTL mapping for fiber yield-related traits by constructing the first genetic linkage map in ramie (Boehmeria nivea L. Gaud)

Ramie fiber extracted from stem bast is one of the most important natural fibers. The fiber yield of ramie is a valuable trait and is decided by several components, including stem number per plant (SN), the fiber yield per stem (FYPS), stem length (SL), stem diameter (SD), and bark thickness (BT). All of these fiber yield-related traits are inherited in a quantitative manner. The genetic basis for these traits is still uncharacterized, which has hindered the improvement of yield traits through selective ramie breeding. In this study, an F₂ population derived from two ramie varieties, Zhongzhu 1 and Qingyezhuma, with striking differences in fiber yield-related traits, was used for cutting propagation and to develop an F₂ agamous line (FAL) population. A genetic linkage map with 132 DNA loci spanning 2,265.1 cM was first constructed. The analysis of quantitative trait locus (QTL) for fiber yield-related traits was performed in ramie for the first time. Finally, a total of 6, 9, 5, 7, and 6 QTLs for FYPS, SL, SN, SD, and BT, respectively, were identified in the FAL population in two environments. Among these 33 QTLs, 9 QTLs were detected in both environments and 24 QTLs exhibited overdominance. The overdominance of these QTLs possibly contributed to the heterosis of these yield-related traits in ramie. Moreover, there were 7 QTL clusters identified. The identification of the QTLs for fiber yield-related traits will be helpful for improving the fiber yield in ramie breeding programs.     

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.     

绿豆5个产量相关性状的QTL分析

利用绿豆(Vigna radiata)品种苏绿16-10和潍绿11杂交构建的F2和F3群体发掘调控绿豆产量相关性状的遗传位点。同时对绿豆产量相关性状进行表型鉴定和相关性分析,并利用构建的遗传连锁图谱进行QTL定位。结果表明,单株产量与单株荚数、单荚粒数、百粒重和分枝数均呈正相关。单株产量与单株荚数的相关性最高,这2个性状在F2和F3群体中的相关系数分别为0.950和0.914。在F2群体中,共检测到8个与产量性状相关的QTL位点,其中与单株荚数、单荚粒数和单株产量相关的QTL位点各1个,分别解释11.09%(qNPP3)、17.93%(qNSP3)和14.18%(qYP3)的表型变异;2个与分枝数相关的QTL位点qBMS3和qBMS11,分别解释18.51%和7.06%的表型变异;3个与百粒重相关的QTL位点qHSW3、qHSW7和qHSW10,分别解释5.33%、46.07%和4.24%的表型变异。在F3群体中,qNSP3和qHSW7再次被检测到,表明这2个QTLs有较好的遗传稳定性。同时,开发了1个与百粒重主效QTLqHSW7紧密连锁的InDel标记R7-13.4,并利用自然群体对...     

Quantitative trait loci for rice yield-related traits using recombinant inbred lines derived from two diverse cultivars

The thousand-grain weight and spikelets per panicle directly contribute to rice yield. Heading date and plant height also greatly influence the yield. Dissection of genetic bases of yield-related traits would provide tools for yield improvement. In this study, quantitative trait loci (QTL) mapping for spikelets per panicle, thousand-grain weight, heading date and plant height was performed using recombinant inbred lines derived from a cross between two diverse cultivars, Nanyangzhan and Chuan7. In total, 20 QTLs were identified for four traits. They were located to 11 chromosomes except on chromosome 4. Seven and five QTLs were detected for thousand-grain weight and spikelets per panicle, respectively. Four QTLs were identified for both heading date and plant height. About half the QTLs were commonly detected in both years, 2006 and 2007. Six QTLs are being reported for the first time. Two QTL clusters were identified in regions flanked by RM22065 and RM5720 on chromosome 7 and by RM502 and RM264 on chromosome 8, respectively. The parent, Nanyangzhan with heavy thousand-grain weight, carried alleles with increased effects on all seven thousand-grain weight QTL, which explained why there was no transgressive segregation for thousand-grain weight in the population. In contrast, Chuan7 with more spikelets per panicle carried positive alleles at all five spikelets per panicle QTL except qspp5. Further work on distinction between pleiotropic QTL and linked QTL is needed in two yield-related QTL clusters.     

In silico integration of quantitative trait loci for seed yield and yield-related traits in Brassica napus

Mapping quantitative trait loci (QTLs) is a foundation for molecular marker-assisted selection and map-based gene cloning. During the past decade, numerous QTLs for seed yield (SY) and yield-related traits in Brassica napus L. have been identified. However, integration of these results in order to compare QTLs from different mapping populations has not been undertaken, due to the lack of common molecular markers between studies. Using previously reported Brassica rapa and Brassica oleracea genome sequences, we carried out in silico integration of 1,960 QTLs associated with 13 SY and yield-related traits from 15 B. napus mapping experiments over the last decade. A total of 736 SY and yield-related QTLs were mapped onto 283 loci in the A and C genomes of B. napus. These QTLs were unevenly distributed across the 19 B. napus chromosomes, with the most on chromosome A3 and the least on chromosome C6. Our integrated QTL map identified 142 loci where the conserved QTLs were detected and 25 multifunctional loci, mostly for the traits of flowering time (FT), plant height, 1,000-seed weight, maturity time and SY. These conserved QTLs and multifunctional loci may result from pleiotropism or clustered genes. At the same time, a total of 146 genes underlying the QTLs for FT and other yield-related traits were identified by comparative mapping with the Arabidopsis genome. These results facilitate the retrieval of B. napus SY and yield-related QTLs for research communities, increase the density of targeted QTL-linked markers, validate the existence of QTLs across different populations, and advance the fine mapping of genes.     

Conditional QTL mapping of protein content in wheat with respect to grain yield and its components

Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.     

QTL mapping for yield and photosynthetic related traits under different water regimes in wheat

The improvement for drought tolerance requires understanding of the genetic control of wheat (Triticum aestivum L.) reaction to drought. In this study, a set of 131 recombinant inbred lines of wheat were investigated under well-watered (WW) and drought stress (DS) environments across 2 years to map quantitative trait loci (QTLs) for yield and physiological traits. A total of 225 QTLs were detected, including 32 non-environment-specific loci that were significant in both DS and WW, one drought-specific locus and two watering-specific loci. Three consistently-expressed QTLs (QTkw-3A.2, QTss-1A, and QScn-7A.1) were identified in at least three environments and the QTkw-1D.1 was significant in DS across the 2 years. By unconditional and conditional QTL analysis, spike number per plant and kernel number per spike were more important than thousand-kernel weight for grain yield (GY) at the given genetic background. Meta-analysis identified 67 meta-QTLs that contained QTLs for at least two traits. High frequency co-location of QTLs was found among either the spike-related traits or the six physiological traits. Four photosynthesis traits (CHL, LWUE, P _N, and C _i) were co-located with GY and/or yield components on various MQTLs. The results provided QTLs that warrant further study for drought tolerance breeding and are helpful for understanding the genetic basis of drought tolerance and the genetic contribution of yield components to GY at individual QTL level in wheat.     

A complete genetic linkage map and QTL analyses for bast fibre quality traits, yield and yield components in jute (Corchorus olitorius L.)

We report the first complete microsatellite genetic map of jute (Corchorus olitorius L.; 2n = 2 × = 14) using an F₆ recombinant inbred population. Of the 403 microsatellite markers screened, 82 were mapped on the seven linkage groups (LGs) that covered a total genetic distance of 799.9 cM, with an average marker interval of 10.7 cM. LG5 had the longest and LG7 the shortest genetic lengths, whereas LG1 had the maximum and LG7 the minimum number of markers. Segregation distortion of microsatellite loci was high (61%), with the majority of them (76%) skewed towards the female parent. Genomewide non-parametric single-marker analysis in combination with multiple quantitative trait loci (QTL)-models (MQM) mapping detected 26 definitive QTLs for bast fibre quality, yield and yield-related traits. These were unevenly distributed on six LGs, as co-localized clusters, at genomic sectors marked by 15 microsatellite loci. LG1 was the QTL-richest map sector, with the densest co-localized clusters of QTLs governing fibre yield, yield-related traits and tensile strength. Expectedly, favorable QTLs were derived from the desirable parents, except for nearly all of those for fibre fineness, which might be due to the creation of new gene combinations. Our results will be a good starting point for further genome analyses in jute.     

Genetic analysis of wheat domestication and evolution under domestication

Wheat is undoubtedly one of the world's major food sources since the dawn of Near Eastern agriculture and up to the present day. Morphological, physiological, and genetic modifications involved in domestication and subsequent evolution under domestication were investigated in a tetraploid recombinant inbred line population, derived from a cross between durum wheat and its immediate progenitor wild emmer wheat. Experimental data were used to test previous assumptions regarding a protracted domestication process. The brittle rachis (Br) spike, thought to be a primary characteristic of domestication, was mapped to chromosome 2A as a single gene, suggesting, in light of previously reported Br loci (homoeologous group 3), a complex genetic model involved in spike brittleness. Twenty-seven quantitative trait loci (QTLs) conferring threshability and yield components (kernel size and number of kernels per spike) were mapped. The large number of QTLs detected in this and other studies suggests that following domestication, wheat evolutionary processes involved many genomic changes. The Br gene did not show either genetic (co-localization with QTLs) or phenotypic association with threshability or yield components, suggesting independence of the respective loci. It is argued here that changes in spike threshability and agronomic traits (e.g. yield and its components) are the outcome of plant evolution under domestication, rather than the result of a protracted domestication process. Revealing the genomic basis of wheat domestication and evolution under domestication, and clarifying their inter-relationships, will improve our understanding of wheat biology and contribute to further crop improvement.     

Mapping QTLs of yield-related traits using RIL population derived from common wheat and Tibetan semi-wild wheat

Key message

QTLs controlling yield-related traits were mapped using a population derived from common wheat and Tibetan semi-wild wheat and they provided valuable information for using Tibetan semi-wild wheat in future wheat molecular breeding.

Abstract

Tibetan semi-wild wheat (Triticum aestivum ssp tibetanum Shao) is a kind of primitive hexaploid wheat and harbors several beneficial traits, such as tolerance to biotic and abiotic stresses. And as a wild relative of common wheat, heterosis of yield of the progeny between them was significant. This study focused on mapping QTLs controlling yield-related traits using a recombined inbred lines (RILs) population derived from a hybrid between a common wheat line NongDa3331 (ND3331) and the Tibetan semi-wild wheat accession Zang 1817. In nine location–year environments, a total of 148 putative QTLs controlling nine traits were detected, distributed on 19 chromosomes except for 1A and 2D. Single QTL explained the phenotypic variation ranging from 3.12 to 49.95 %. Of these QTLs, 56 were contributed by Zang 1817. Some stable QTLs contributed by Zang 1817 were also detected in more than four environments, such as QPh-3A1, QPh-4B1 and QPh-4D for plant height, QSl-7A1 for spike length, QEp-4B2 for ears per plant, QGws-4D for grain weight per spike, and QTgw-4D for thousand grain weight. Several QTL-rich Regions were also identified, especially on the homoeologous group 4. The TaANT gene involved in floral organ development was mapped on chromosome 4A between Xksm71 and Xcfd6 with 0.8 cM interval, and co-segregated with the QTLs controlling floret number per spikelet, explaining 4.96–11.84 % of the phenotypic variation. The current study broadens our understanding of the genetic characterization of Tibetan semi-wild wheat, which will enlarge the genetic diversity of yield-related traits in modern wheat breeding program.     

Quantitative trait loci underlying domestication- and yield-related traits in an Oryza sativa x Oryza rufipogon advanced backcross population

To understand the genetic characteristics of the traits related to differentiation between cultivated rice and its wild progenitor, genetic factors controlling domestication- and yield-related traits were identified using a BC3F2 population derived from an accession of common wild rice (donor, Oryza rufipogon Griff.) collected from Yuanjiang, Yunnan province, China, and an indica cultivar, Teqing (recipient, Oryza sativa L.). A genetic linkage map consisting of 125 simple sequence repeat (SSR) markers was constructed. Based on the phenotypes of the 383 BC3F2 families evaluated in two environments, two domestication-related morphological traits, panicle shape and growth habit, were found to be controlled by single Mendelian factors. This implies that the recessive mutations of single genes controlling some morphological traits could have been easily selected during early domestication. By single-point analysis and interval mapping, 59 putative quantitative trait loci (QTLs) that influence 11 quantitative traits were detected at two sites, and 37.5% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield-related traits in the Teqing background. Regions with significant QTLs for domestication- and yield-related traits were detected on chromosomes 1, 4, 5, 7, 8, and 12. Fine mapping and cloning of these domestication-related genes and QTLs will be useful in elucidating the origin and differentiation of Asian cultivated rice in the future.     

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F₇ RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

The genetics of nitrogen use in hexaploid wheat: N utilisation, development and yield

A genetic study is presented for traits relating to nitrogen use in wheat. Quantitative trait loci (QTLs) were established for 21 traits relating to growth, yield and leaf nitrogen (N) assimilation during grain fill in hexaploid wheat (Triticum aestivum L.) using a mapping population from the cross Chinese Spring × SQ1. Glutamine synthetase (GS) isozymes and estimated locations of 126 genes were placed on the genetic map. QTLs for flag leaf GS activity, soluble protein, extract colour and fresh weight were found in similar regions implying shared control of leaf metabolism and leaf size. Flag leaf traits were negatively associated with days to anthesis both phenotypically and genetically, demonstrating the complex interactions of metabolism with development. One QTL cluster for GS activity co-localised with a GS2 gene mapped on chromosome 2A, and another with the mapped GSr gene on 4A. QTLs for GS activity were invariably co-localised with those for grain N, with increased activity associated with higher grain N, but with no or negative correlations with grain yield components. Peduncle N was positively correlated, and QTLs co-localised, with grain N and flag leaf N assimilatory traits, suggesting that stem N can be indicative of grain N status in wheat. A major QTL for ear number per plant was identified on chromosome 6B which was negatively co-localised with leaf fresh weight, peduncle N, grain N and grain yield. This locus is involved in processes defining the control of tiller number and consequently assimilate partitioning and deserves further examination. Electronic Supplementary Material The online version of this article () contains supplementary material, which is available to authorized users.     

Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452x'AC Domain'.

Relatively little is known about the genetic control of agronomic traits in common wheat (Triticum aestivum L.) compared with traits that follow Mendelian segregation patterns. A doubled-haploid population was generated from the cross RL4452x'AC Domain' to study the inheritance of the agronomic traits: plant height, time to maturity, lodging, grain yield, test weight, and 1000-grain weight. This cross includes the genetics of 2 western Canadian wheat marketing classes. Composite interval mapping was conducted with a microsatellite linkage map, incorporating 369 loci, and phenotypic data from multiple Manitoba environments. The plant height quantitative trait loci (QTLs), QHt.crc-4B and QHt.crc-4D, mapped to the expected locations of Rht-B1 and Rht-D1. These QTLs were responsible for most of the variation in plant height and were associated with other agronomic traits. An additional 25 agronomic QTLs were detected in the RL4452x'AC Domain' population beyond those associated with QHt.crc-4B and QHt.crc-4D. 'AC Domain' contributed 4 alleles for early maturity, including a major time to maturity QTL on 7D. RL4452 contributed 2 major alleles for increased grain yield at QYld.crc-2B and QYld.crc-4A, which are potential targets for marker-assisted selection. A key test weight QTL was detected on 3B and prominent 1000-grain weight QTLs were identified on 3D and 4A.     

Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17-20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800-1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.     

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     

General combining ability of most yield-related traits had a genetic basis different from their corresponding traits per se in a set of maize introgression lines

Evaluation of combining ability is a crucial process in hybrid breeding, and dissection of the genetic basis of combining ability will facilitate hybrid breeding. In this study, molecular markers significantly associated with general combining ability (GCA) of seven yield-related traits and the traits per se were detected in a set of maize introgression lines (ILs) under three environments. Totally 25 and 31 significant loci for GCA and the traits per se were commonly detected under multiple environments, respectively. Correlation analysis and comparison among these significant loci revealed that the genetic basis of GCA of these yield-related traits was generally different from that of the traits per se except for the trait of ear row number. In addition, GCA of the ILs was positively and significantly correlated to the total relative effects of significant GCA loci in the ILs in general, implying that the GCA loci identified in this study would be useful in molecular breeding. Correlation analysis also showed that the GCA of yield per plant was strongly correlated to the GCA of kernel number per row, ear length and 100-kernel-weight, thus these traits were more important in genetic improvement for GCA. Results in this study would provide useful information for hybrid breeding in maize.     

银川番茄斑萎病毒的分子鉴定

为明确银川番茄(Lycopersicon esculentum)是否遭受了番茄斑萎病毒(TSWV)的危害, 采用国家标准TSWV RT- PCR检测技术对银川番茄上采集的14份疑似感染TSWV病叶样本进行分子鉴定, 对克隆得到的核衣壳蛋白基因N (Nucleocapsid)序列进行多序列比对和系统进化树分析, 随后对PCR阳性样本进行蛋白检测。结果表明, 14份病叶样本中有8份扩增出长度为394 bp的TSWV N基因序列, 且8条序列完全一致; 获得的银川番茄TSWV分离物与云南番茄、中国莴苣(Lactuca sativa)、中国鸢尾(Iris tectorum)和重庆辣椒(Capsicum annuum) TSWV分离物相对近缘, 与山东、黑龙江和北京等地及国外TSWV分离物相对远缘; 利用TSWV的抗体通过Western blot对8个PCR阳性样本进一步检测, 结果也证实8个阳性样本中存在TSWV感染。该研究首次通过分子鉴定及蛋白检测证明银川番茄上存在TSWV感染, 需要加快抗TSWV番茄品种的选育工作。     

生物信息学分析方法I: 全基因组关联分析概述

全基因组关联分析(GWAS)是动植物复杂性状相关基因定位的常用手段。高通量基因分型技术的应用极大地推动了GWAS的发展。在植物中, 利用GWAS不仅能够以较高的分辨率在全基因组水平鉴定出各种自然群体特定性状相关的基因或区间, 而且可揭示表型变异的遗传架构全景图。目前, 人们利用GWAS分析方法已在拟南芥(Arabidopsis thaliana)、水稻(Oryza sativa)、小麦(Triticum aestivum)、玉米(Zea mays)和大豆(Glycine max)等模式植物和重要农作物品系中发掘出与各种性状显著相关的数量性状座位(QTL)及其候选基因位点, 阐明了这些性状的遗传基础, 并为揭示这些性状背后的分子机理提供候选基因, 也为作物高产优质品种的选育提供了理论依据。该文对GWAS的方法、影响因素及数据分析流程进行了详细描述, 以期为相关研究提供参考。