QTL mapping of flag leaf-related traits in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Key message

QTL controlling flag leaf length, flag leaf width, flag leaf area and flag leaf angle were mapped in wheat.

Abstract

This study aimed to advance our understanding of the genetic mechanisms underlying morphological traits of the flag leaves of wheat (Triticum aestivum L.). A recombinant inbred line (RIL) population derived from ND3331 and the Tibetan semi-wild wheat Zang1817 was used to identify quantitative trait loci (QTLs) controlling flag leaf length (FLL), flag leaf width (FLW), flag leaf area (FLA), and flag leaf angle (FLANG). Using an available simple sequence repeat genetic linkage map, 23 putative QTLs for FLL, FLW, FLA, and FLANG were detected on chromosomes 1B, 2B, 3A, 3D, 4B, 5A, 6B, 7B, and 7D. Individual QTL explained 4.3–68.52% of the phenotypic variance in different environments. Four QTLs for FLL, two for FLW, four for FLA, and five for FLANG were detected in at least two environments. Positive alleles of 17 QTLs for flag leaf-related traits originated from ND3331 and 6 originated from Zang1817. QTLs with pleiotropic effects or multiple linked QTL were also identified on chromosomes 1B, 4B, and 5A; these are potential target regions for fine-mapping and marker-assisted selection in wheat breeding programs.

     

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers

Key message

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay.

Abstract

Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai?×?Shi 4185 (D?×?S), Gaocheng 8901?×?Zhoumai 16 (G?×?Z) and Linmai 2?×?Zhong 892 (L?×?Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5–32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

     

An intervarietal genetic linkage map of Indian bread wheat (Triticum aestivum L.) and QTL maps for some metric traits

Bread wheat (Triticum aestivum L.) exhibits very narrow genetic diversity and hence there is high relatedness among cultivated varieties. However, a population generated from an intervarietal cross, with the parents differing in a large number of traits, could lead to the generation of QTL maps which will be useful in practice. In this report a genetic linkage map of wheat is constructed using a cross between two Indian bread wheat varieties: Sonalika and Kalyansona. The linkage map consisted of 236 markers and spanned a distance of 3639 cM, with 1211.2 cM for the A genome, 1669.2 cM for the B genome, 192.4 cM for the D genome and 566.2 cM for unassigned groups. Linkage analysis defined 37 linkage groups of which 24 were assigned to 17 chromosomes. The genetic map was used to identify QTLs by composite internal mapping (CIM) for three metric traits, viz. culm length (CL), flag leaf length (FLL) and flag leaf breadth (FLB). Of 25 QTLs identified in this study, 15 have not been reported previously. Multitrait CIM (MCIM) analysis was carried out for traits that were significantly correlated such as FLB-FLL and CL-FLB-FLL. Detection of a large number of QTLs for the three traits analysed suggests that in parent cultivars that are not too diverse, the differences at genetic level detected as polymorphisms may be mostly associated with QTLs for the observed differences.     

QTLs for cell membrane stability and flag leaf area under drought stress in a wheat RIL population

A population of 206 recombinant inbred lines (RILs F₉–F₁₀) derived from wheat cross WL711/C306 was phenotyped for morpho-physiological traits such as flag leaf area (FLA), flag leaf length (FLL), flag leaf width (FLW), and cell membrane stability (CMS) under water deficit stress (WDS) environment. High yielding cultivar, WL711 had higher FLA than the medium yielding cultivar C306 across trials under both environments. Parent cultivar C306 maintained membrane integrity while WL711 showed higher membrane damage under WDS. The RIL population showed considerable variation, normal distribution and transgressive segregation for FLA, FLL, FLW and CMS under WDS. The genetic linkage map of WL711/C306 RIL population was constructed comprising of 346 markers. The total map distance was 4526.8 cM with an averaged interval of 12.9 cM between adjacent markers. Major consistent QTL for FLA, FLL, FLW, and CMS were identified on chromosomes 2DS and 3BS respectively in the WL711/C306 RIL population under WDS. The major QTL for FLA, qFLAWD.2D.1 which expressed in multiple environments and for CMS, qCMSWD.3B.3 and qCMSWD.3B.4, accounted for a large proportion of phenotypic variance (PV) with positive allele being contributed by C306, a drought resistant (DR) parent. QTL qFLAWD.2D.1 for FLA co-located with QTL for grain number (GN) and days to flowering (DTF) while QTL qCMSWD.3B.3 and qCMS.3B.4 co-located with QTL for grain yield and its components, days to flowering, canopy temperature and coleoptiles length as reported in our previous publications on the WL711/C306 population (Shukla et al. in Euphytica 203:449–467, 2015; Singh et al. in J Plant Biochem Biotechnol 24:324–330, 2015). Two candidate genes Ghd7 for grain yield and heading date and OsCDK4 for calcium dependent protein kinases were identified in the 2DS and 3BS QTL regions respectively on comparison with gene content of rice chromosomes 7 and 1 respectively. Hence, QTLs qFLAWD.2D.1 and qCMSWD.3B.3 are potential target regions for fine mapping and marker assisted selection for FLA and CMS respectively in wheat under water deficit environments.

     

Genetic architecture of quantitative trait loci associated with morphological and agronomic trait differences in a wild by cultivated barley cross.

Hordeum vulgare subsp. spontaneum is the progenitor of cultivated barley (Hordeum vulgare L.). Domestication combined with plant breeding has led to the morphological and agronomic characteristics of modern barley cultivars. The objective of this study was to map the genetic factors that morphologically and agronomically differentiate wild barley from modern barley cultivars. To address this objective, we identified quantitative trait loci (QTLs) associated with plant height, flag leaf width, spike length, spike width, glume length in relation to seed length, awn length, fragility of ear rachis, endosperm width and groove depth, heading date, flag leaf length, number of tillers per plant, and kernel color in a Harrington/OUH602 advanced backcross (BC2F8) population. This population was genotyped with 113 simple sequence repeat markers. Thirty QTLs were identified, of which 16 were newly identified in this study. One to 4 QTLs were identified for each of the traits except glume length, for which no QTL was detected. The portion of phenotypic variation accounted for by individual QTLs ranged from about 9% to 54%. For traits with more than one QTL, the phenotypic variation explained ranged from 25% to 71%. Taken together, our results reveal the genetic architecture of morphological and agronomic traits that differentiate wild from cultivated barley.     

Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two testcross populations

To understand the types of gene action controlling seven quantitative traits in rice, QTL mapping was performed to dissect the main effect (M-QTLs) and digenic epistatic (E-QTLs) QTLs responsible for the trait performance of 254 recombinant inbred lines (RILs) of "Lemont/Teqing", and two testcross (TC) F(1) populations derived from these RILs. The correlation analyses reveal a general pattern, i.e. trait heritability in the RILs was negatively correlated to trait heterosis in the TC hybrids. A large number of M-QTLs and E-QTLs affecting seven traits, including heading date (HD), plant height (PH), flag leaf length (FLL), flag leaf width (FLW), panicle length (PL), spikelet number per panicle (SN) and spikelet fertility (SF), were identified and could be classified into two predominant groups, additive QTLs detected primarily in the RILs, and overdominant QTLs identified exclusively in the TC populations. There is little overlap between QTLs identified in the RILs and in the TC populations. This result implied that additive gene action is largely independent from non-additive gene action in the genetic control of quantitative traits of rice. The detected E-QTLs collectively explained a much greater portion of the total phenotypic variation than the M-QTLs, supporting prior findings that epistasis has played an important role in the genetic control of quantitative traits in rice. The implications of these results to the development of inbred and hybrid cultivars were discussed.     

The application of high-density genetic maps of rye for the detection of QTLs controlling morphological traits

The development of genetic maps is, nowadays, one of the most intensive research activities of plant geneticists. One of the major goals of genome mapping is the localisation of quantitative trait loci (QTLs). This study was aimed at the identification of QTLs controlling morphological traits of rye and comparison of their localisation on genetic maps constructed with the use of genetically different germplasms. For QTL analyses, two high-density consensus maps of two populations (RIL-S and RIL-M) of recombinant inbred lines (RIL) were applied. Plant height (Ph), length of spikes (Sl) and the number of spikelets per spike (Sps) were studied in both populations. Additionally, the number of kernels per spike under isolation (Kps), the weight of kernels per spike (Kw) and thousand kernel weight (Tkw) were assessed in the RIL-M population. Except for Tkw, the majority of the traits were correlated to each other. The non-parametric Kruskal–Wallis (K-W) test and composite interval mapping (CIM) revealed 18/48 and 24/18 regions of rye chromosomes engaged in the determination of Ph, Sl and Sps in the RIL-S and RIL-M populations, respectively. An additional 18/15 QTLs controlling Kps, Kw and Tkw were detected on a map of the RIL-M population. A numerous group of QTLs detected via CIM remained in agreement with the genomic regions found when the K-W test was applied. Frequently, the intervals indicated by CIM were narrower.     

Kernel weight per spike: what contributes to it at the individual QTL level?

Spike length (SL), spikelet number (SPN) per spike, kernel number per spike (KNPS), and thousand-kernel weight (TKW) have strong genetic associations with kernel weight per spike (KWPS) in wheat. To investigate their genetic relationships at the individual quantitative trait locus (QTL) level, both unconditional and conditional QTL mapping for KWPS with respect to SL, SPN, KNPS, and TKW were conducted. Two related F_8:9 recombinant inbred line populations, comprising 485 and 229 lines, respectively, were used. The trait phenotypic performances of each population were evaluated in four different environments. Unconditional QTL mapping analysis identified 22 putative additive QTL for KWPS, five of which were stable QTL, and only QKwps-WJ-1B.2 showed significant additive-by-environment interaction effects. In comparison with unconditional QTL mapping analysis, conditional QTL mapping analysis indicated that, at the QTL level, KNPS and TKW contributed more to KWPS than did SL and SPN. Any unconditional QTL for KWPS detected in this study was associated with at least one of its four related traits. The present study will provide assistance in the understanding of the genetic relationships between KWPS and its related traits.     

Premature progression of anther early developmental programs accompanied by comprehensive alterations in transcription during high-temperature injury in barley plants

Kernel number per spike is one of the most important yield components of wheat. To map QTLs related to kernel number including spike length (SPL), spikelet number per spike (SPN), fertile spikelet number (FSPN), sterile spikelet number (SSPN) and compactness, and to characterize the inheritance modes of the QTLs and two-locus interactions, 136 recombinant inbred lines (RILs) derived from ‘Nanda2419’ x ‘Wangshuibai’ and an immortalized F₂ population (IF₂) generated by randomly permutated intermating of these RILs were investigated. QTL mapping made use of the previously constructed over 3300 cM linkage map of the RIL population. Three, five, two, two and six chromosome regions were identified, respectively, for their association with SPL, SPN, FSPN, SSPN, and compactness in at least two of the three environments examined. All compactness QTLs but one shared the respective intervals of QSpn.nau-5A and the SPL QTLs. Xcfd46–Xwmc702 interval on chromosome 7D was related to all traits but SSPN and had consistently the largest effects. The fact that not all the compactness QTL intervals were related to both SPL and SPN indicates that compactness is regulated by different mechanisms. Interval coincidence between QTLs of SPL and SPN and between QTLs of FSPN and SSPN was minimal. For all the traits, favorable alleles exist in both parents. Inheritance modes from additiveness to overdominance of the QTLs were revealed and two-locus interactions were detected, implying that the traits studied are under complex genetic control. The results could contribute to wheat yield improvement and better use of Wangshuibai and Nanda2419 the two special germplasms in wheat breeding program.     

Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?

Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F(8:9) recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.     

Genetic dissection of yield-related traits in a recombinant inbred line population created using a key breeding parent in China’s wheat breeding

Understanding the genetics underlying yield formation of wheat is important for increasing wheat yield potential in breeding programs. Nanda2419 was a widely used cultivar for wheat production and breeding in China. In this study, we evaluated yield components and a few yield-related traits of a recombinant inbred line (RIL) population created by crossing Nanda2419 with the indigenous cultivar Wangshuibai in three to four trials at different geographical locations. Negative and positive correlations were found among some of these evaluated traits. Five traits had over 50 % trial-wide broad sense heritability. Using a framework marker map of the genome constructed with this population, quantitative trait loci (QTL) were identified for all traits, and epistatic loci were identified for seven of them. Our results confirmed some of the previously reported QTLs in wheat and identified several new ones, including QSn.nau-6D for effective tillers, QGn.nau-4B.2 for kernel number, QGw.nau-4D for kernel weight, QPh.nau-4B.2 and QPh.nau-4A for plant height, and QFlw.nau-5A.1 for flag leaf width. In the investigated population, Nanda2419 contributed all QTLs associated with higher kernel weight, higher leaf chlorophyll content, and a major QTL associated with wider flag leaf. Seven chromosome regions were related to more than one trait. Four QTL clusters contributed positively to breeding goal-based trait improvement through the Nanda2419 alleles and were detected in trials set in different ecological regions. The findings of this study are relevant to the molecular improvement of wheat yield and to the goal of screening cultivars for better breeding parents.     

多效性基因Ghd7调控水稻剑叶面积

光合作用是植物的唯一能量来源,剑叶是水稻开花后进行光合作用的主要部位。Ghd7是一个多效性产量基因,能显著提高水稻产量。为了研究Ghd7对水稻剑叶形态的遗传效应,文章利用一个包含190个家系的BC2F2群体对水稻剑叶长度(FLL)、剑叶宽(FLW)和剑叶面积(FLA)进行QTL定位分析。在BC2F2群体,FLL、FLW和FLA性状表型值均显示为双峰分布,符合孟德尔单基因分离比,并均与每穗实粒数呈现显著正相关。在第7染色体上RM3859和C39分子标记间定位到FLL、FLW和FLA的QTL,分别解释变异的73.3%、62.3%和71.8%,均与Ghd7共分离。以珍汕97为轮回亲本,特青和明恢63分别为供体亲本,获得两个Ghd7近等基因系NIL(MH63)和NIL(TQ),FLL、FLW和FLA表型值均比珍汕97显著提高。另外,超表达Ghd7的合江19转基因植株的FLL、FLW和FLA表型值分别比合江19增加了8.9 cm、0.5 cm和17.8 cm2。这些结果表明Ghd7对调控剑叶面积起重要作用。     

Comparative analysis of genetic architectures for nine developmental traits of rye

Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1–3 RILs population of rye using the genes interaction assorting by divergent selection (GIABDS) method. Complex sets of QTL for particular traits contained 1–5 loci of the epistatic D class and 10–28 loci of the hypostatic, mostly R and E classes controlling traits variation through D–E or D–R types of two-loci interactions. QTL were distributed on each of the seven rye chromosomes in unique positions or as a coinciding loci for 2–8 traits. Detection of considerable numbers of the reversed (D′, E′ and R′) classes of QTL might be attributed to the transgression effects observed for most of the studied traits. First examples of E* and F QTL classes, defined in the model, are reported for awn length, leaf area, thousand-kernel weight and kernel length. The results of this study extend experimental data to 11 quantitative traits (together with pre-harvest sprouting and alpha-amylase activity) for which genetic architectures fit the model of mechanism underlying alleles distribution within tails of bi-parental populations. They are also a valuable starting point for map-based search of genes underlying detected QTL and for planning advanced marker-assisted multi-trait breeding strategies.     

Chromosomal Localization of Genes Conferring Desirable Agronomic Traits from Wheat-Agropyron cristatum Disomic Addition Line 5113

Creation of wheat-alien disomic addition lines and localization of desirable genes on alien chromosomes are important for utilization of these genes in genetic improvement of common wheat. In this study, wheat-Agropyron cristatum derivative line 5113 was characterized by genomic in situ hybridization (GISH) and specific-locus amplified fragment sequencing (SLAF-seq), and was demonstrated to be a novel wheat-A. cristatum disomic 6P addition line. Compared with its parent Fukuhokomugi (Fukuho), 5113 displayed multiple elite agronomic traits, including higher uppermost internode/plant height ratio, larger flag leaf, longer spike length, elevated grain number per spike and spikelet number per spike, more kernel number in the middle spikelet, more fertile tiller number per plant, and enhanced resistance to powdery mildew and leaf rust. Genes conferring these elite traits were localized on the A. cristatum 6P chromosome by using SLAF-seq markers and biparental populations (F₁, BC₁F₁ and BC₁F₂ populations) produced from the crosses between Fukuho and 5113. Taken together, chromosomal localization of these desirable genes will facilitate transferring of high-yield and high-resistance genes from A. cristatum into common wheat, and serve as the foundation for the utilization of 5113 in wheat breeding.     

Physiological traits contributed to the recent increase in yield potential of winter wheat from Henan Province,China

This experiment aims to test the traits responsible for the increase in yield potential of winter wheat released in Henan Province, China. Seven established cultivars released in the last 20 years and three advanced lines were assayed. The results showed that grain yield was positively correlated with harvest index（HI）, kernel number per square meter, and aboveground biomass. In addition, the HI and aboveground biomass showed an increasing trend with the year of release.Therefore, we can conclude that bread wheat breeding advances during recent decades in Henan Province, China,have been achieved through an increase in HI, kernel number per square meter, and aboveground biomass. A higher d13C seems also to be involved in these advances, which suggests a progressive improvement in constitutive water use efficiency not associated with a trend towards lower stomatal conductance in the most recent genotypes. However, genetic advance Researchdoes not appear related to changes in photosynthesis rates on area basis when measured in the flag leaf or the spike,but only to a higher, whole‐spike photosynthesis. Results also indirectly support the concept that under potential yield conditions, the spike contributed more than the flag leaf to kernel formation.     

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.     

A intervarietal genetic map and QTL analysis for yield traits in wheat

A new genetic linkage map was constructed based on recombinant inbred lines (RILs) derived from the cross between the Chinese winter wheat (Triticum aestivum L.) varieties, Chuang 35050 and Shannong 483 (ChSh). The map included 381 loci on all the wheat chromosomes, which were composed of 167 SSR, 94 EST-SSR, 76 ISSR, 26 SRAP, 15 TRAP, and 3 Glu loci. This map covered 3636.7 cM with 1327.7 cM (36.5%), 1485.5 cM (40.9%), and 823.5 cM (22.6%) for A, B, and D genome, respectively, and contained 13 linkage gaps. Using the RILs and the map, we detected 46 putative QTLs on 12 chromosomes for grain yield (GY) per m², thousand-kernel weight (TKW), spike number (SN) per m², kernel number per spike (KNS), sterile spikelet number per spike (SSS), fertile spikelet number per spike (FSS), and total spikelet number per spike (TSS) in four environments. Each QTL explained 4.42–70.25% phenotypic variation. Four QTL cluster regions were detected on chromosomes 1D, 2A, 6B, and 7D. The most important QTL cluster was located on chromosome 7D near the markers of Xwmc31, Xgdm67, and Xgwm428, in which 8 QTLs for TKW, SN, SSS and FSS were observed with very high contributions (27.53–67.63%).     

冀中北小麦品种抗旱性筛选研究

干旱是华北地区小麦生产的重要限制因素,从推广小麦品种中鉴定和筛选抗旱品种,对稳定小麦产量、降低区域水分消耗具有重要意义.本研究以近年来在河北省中北部审定、推广的13个小麦品种为材料,设置冬后浇2水(D2处理)、浇1水(D1处理)和不浇水(D0处理)3种处理方式,进行了大田条件下的抗旱品种筛选试验.结果表明,在D0处理时...     

QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat

In bread wheat, single-locus and two-locus QTL analyses were conducted for seven yield and yield contributing traits using two different mapping populations (P I and P II). Single-locus QTL analyses involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated yield traits to detect the pleiotropic QTLs. Two-locus analyses were conducted to detect main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions (QE and QQE). Only a solitary QTL for spikelets per spike was common between the above two populations. HomoeoQTLs were also detected, suggesting the presence of triplicate QTLs in bread wheat. Relatively fewer QTLs were detected in P I than in P II. This may be partly due to low density of marker loci on P I framework map (173) than in P II (521) and partly due to more divergent parents used for developing P II. Six QTLs were important which were pleiotropic/coincident involving more than one trait and were also consistent over environments. These QTLs could be utilized efficiently for marker assisted selection (MAS).     

大白菜部分形态性状的QTL定位与分析

应用352个标记位点的大白菜AFLP和RAPD图谱和一套栽培品种间杂交获得的重组自交系群体,采用复合区间作图的方法对大白菜9个形态性状进行QTL定位及遗传效应研究。在14个连锁群上检测到50个QTL:其中控制株型的QTL有5个;控制株高的QTL有6个;控制开展度的QTL有5个;控制最大叶长的QTL有7个;控制最大叶宽的QTL有4个;控制叶形指数的QTL有6个;控制中肋长的QTL有7个;控制中肋宽的QTL有4个;控制抽苔的QTL有6个。另外,估算了单个QTL的遗传贡献率和加性效应。这将为大白菜品种改良中形态性状的分子标记辅助选择提供理论依据。