Co-location of seed oil content,seed hull content and seed coat color QTL in three different environments in <Emphasis Type="Italic">Brassica napus</Emphasis> L.

Increasing seed oil content is an important breeding goal for Brassica napus L. (B. napus). The identification of quantitative trait loci (QTL) for seed oil content and related traits is important for efficient selection of B. napus cultivars with high seed oil content. To get better knowledge on these traits, a molecular marker linkage map for B. napus was constructed with a recombinant inbred lines (RIL) population. The length of the map was 1,589 cM with 451 markers distributed over 25 linkage groups. QTL for seed oil content, seed hull content and seed coat color in three environments were detected by composite interval mapping (CIM) tests. Eleven QTL accounted for 5.19–13.57% of the variation for seed oil content. Twelve QTL associated with seed hull content were identified with contribution ranging from 5.80 to 22.71% and four QTL for seed coat color accounted for 5.23–15.99% of the variation. It is very interesting to found that co-localization between QTL for the three traits were found on N8. These results indicated the possibility to combine favorable alleles at different QTL to increase seed oil content, as well as to combine information about the relationship between seed oil content and other traits.     

栽培种花生荚果大小相关性状QTL定位

以远杂9102为母本,徐州68-4为父本杂交衍生的F5和F6共188个家系,构建了一张包含365个标记,总长度713.07 c M,标记间平均距离1.96 c M的栽培种花生遗传图谱。图谱包含22个连锁群,各连锁群平均长度12.37~81.39 c M,连锁群上标记数量3~46个。结合2013和2014年采集的荚果表型数据,采用Win QTLcart 2.5软件的复合区间作图法(composite interval mapping,CIM)进行QTL定位和效应估计。2个环境下共检测到41个QTL,其中与荚果长、宽、厚和百果重相关的QTL分别为13、7、13和8个,表型变异解释率为3.14%~18.27%。有6个QTL在2种环境下被重复检测到,其中百果重相关的2个(q HPWLG13.1、q HPWLG14.1),分布在LG13和LG14连锁群,遗传贡献率为6.95%~14.60%;与荚果长相关的3个(q LPLG2.2、q LPLG13.1、q LPLG14.1),分布在LG2、LG13和LG14连锁群,遗传贡献率为3.14%~18.27%;与荚果厚相关的1个(q TPLG3.4),分布在LG3连锁群,遗传贡献率为8.24%~9.24%。本研究涉及性状存在9个QTL热点区,每个热点区涉及2~3个性状,表型贡献率为3.57%~18.27%。     

甘蓝型油菜产量及相关性状的QTL分析

高产是甘蓝型油菜育种的重要目标之一，产量是多基因控制的数量性状。本文通过QTL作图分析了产量及其相关性状的数量性状位点，以甘蓝型油菜中油821和保604 F₁代小孢子培养获得的DH系为作图群体，构建了由20个连锁群组成的，包括251个分子标记( 2个RFLP标记，72个RAPD标记，91个SSR标记，86个SRAP标记)的遗传连锁图(10个标记没有分配到连锁群中)。图谱的平均图距为6.96 cM，共覆盖油菜基因组1 746.5 cM。在此图谱基础上采取复合区间作图法，检测到与油菜产量及其相关性状有关的QTL共17个。其中控制株高的3个分别位于第4、第9和第10连锁群上，对性状的解释率为9.42%～17.58%；与分枝部位有关的4个分别位于第4、第6和第7连锁群上，其中Bp1 和Bp2 均位于第4连锁群，对性状的解释率为8.13%～15.20%；与主花序有效长有关的3个分别位于第4、第10和第16连锁群上，对性状的解释率为7.49%～23.36%；与一次有效分枝有关的2个分别位于第1、第4连锁群上，对性状的解释率为15.29%～19.58%；与角果总数和千粒重有关的分别位于第4连锁群和第9连锁群上，贡献率分别为17.42%和7.64%；与单株产量有关的3个分别位于第3、第4和第15连锁群，共解释26.60%的表型变异。部分性状的QTL在连锁群上成簇分布,对性状贡献率很大，表现主效QTLs的特点，相应的性状之间也呈显著相关，这表明一因多效或者相关的QTLs之间紧密连锁是性状相关的遗传基础。本研究中与主效QTLs连锁的标记可用于油菜产量性状的分子标记辅助选择。     

Relationships between water-use traits and photosynthesis in Brassica oleracea resolved by quantitative genetic analysis

The genetic control of water‐use and photosynthetic traits in Brassica oleracea is resolved by genetic analysis of quantitative trait loci (QTL). Variations in leaf conductance, photosynthetic assimilation rate, leaf thickness and leaf nitrogen content were assessed in a segregating population of F₁‐derived doubled haploid (DH) B. oleracea lines. In addition, stable carbon isotope ratios in leaf organic material were used as a surrogate measure of plant water‐use efficiency. Analysis of an existing linkage map for the population revealed significant QTL on seven linkage groups. Single significant QTL explained between 3.4% and 36.6% of the phenotypic variance in each of the traits measured. The locations of QTL for several traits were found to coincide in a physiologically meaningful way; stable carbon isotope discrimination had QTL co‐locating with leaf level water‐use efficiency, photosynthetic capacity with leaf thickness and nitrogen content and stomatal density with leaf thickness. Taken together, these results suggest that single genes or clusters of genes at these loci may have an influence on the expression of physiologically related traits controlling water‐use and photosynthesis.     

Mapping QTL for seed yield and canning quality following processing of black bean (<Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> L.)

Quantitative trait loci (QTL) analysis was conducted to identify QTL for seed yield and color retention following processing of a recombinant inbred line (RIL) black bean population. A population of 96 RILs were derived from the cross of black bean cultivars ‘Jaguar’ and 115M and evaluated in replicated trials at one location over 4 years (2004–2007) in Michigan. A 119-point genetic map constructed using simple sequence repeat (SSR), sequence related amplified polymorphism (SRAP), target region amplified polymorphism (TRAP) and phenotypic markers spanned fifteen linkage groups (LG) or 460 cM of the bean genome. Fourteen QTL for yield and color retention in four environments were identified by composite interval mapping on six linkage groups. A major QTL SY10.2^J115 for seed yield was identified on LG B10 with additional QTL on B3, B5, and B11. Color retention following processing was associated with loci on B1, B3, B5, B8, and B11. 115M possessed positive alleles for yield, but negative alleles for color retention. Some QTL for yield and color retention co-localized with regions identified in previous studies while others, particularly for color retention, were unique. Additional QTL for agronomic and canning quality traits were detected and individual contributions to future black bean breeding are discussed.     

Identification of coincident QTL for days to heading,spike length and spikelets per spike in <Emphasis Type="Italic">Lolium perenne</Emphasis> L.

Flowering time is a trait which has a major influence on the quality of forage. In addition, flowering and subsequent seed yields are important traits for seed production by grass breeders. In this study, we have identified quantitative trait loci (QTL) for flowering time and morphological traits of the flowering head in an F₁ mapping population in Lolium perenne L (perennial ryegrass), a number of which have not previously been identified in L. perenne mapping studies. QTL for days to heading (DTH) were mapped in both outdoor and glasshouse experiments, revealing three and five QTL for DTH which explained 53% and 42% of the total phenotypic variation observed, respectively. Two QTL for DTH were detected in both environments, although they had contrasting relative magnitudes in each environment. One QTL for spike length and three QTL for spikelets per spike were also identified explaining, a total of 32 and 33% of the phenotypic variance, respectively. Furthermore, the QTL for spike length and spikelets per spike generally coincided with QTL for days to heading, implying co-ordinate regulation by underlying genes. Of particular interest was a region harbouring overlapping QTL for days to heading, spike length and spikelets per spike on the top of linkage group 4, containing the major QTL for spike length identified in this population.     

Quantitative trait analysis of flowering time in spring rapeseed (B. napus L.)

The inheritance of flowering time trait in spring-type rapeseed (Brassica napus L.) is poorly understood, and the investigations on mapping of quantitative trait loci (QTL) for the trait are only few. We identified QTL underlying variation for flowering time in a doubled haploid (DH) mapping population of nonvernalization-responsive canola (B. napus L.) cultivar 465 and line 86 containing introgressions from Houyou11, a Chinese early-flowering cultivar in Brassica rapa L. Significant genetic variation in flowering time and response to photoperiod were observed among the DH lines from 465/86. A molecular linkage map was generated comprising three types of markers loci. QTL analysis indicated that flowering time is a complex trait and is controlled by at least 4 major loci, localized on four different linkage groups A6, A7, C8 and C9. These loci each accounted for between 9.2 and 12.56 % of the total genotypic variation for first flowering. The published high-density maps for flowering time mapping used different marker systems, and the parents of our crosses have different genetic origins, with either spring-type B. napus or B. rapa. So we cannot determine whether the QTL on the same linkage groups were in the same region or not. There was evidence of additive × additive epistatic effects for flowering time in the DH population. Epistasis existed not only between main-effect QTLs, but also between QTLs with minor effects. Four pair of epistasis effects between minor QTLs explained about 20 % of the genetic variance observed in the DH population. The results indicated that minor QTLs for flowering time should not be ignored. Significant genotypes × environment interactions were also found for the quantitative traits, and with significant change in the ranking of the DH lines in different environments. The results implied that FQ3 was a non-environment-specific QTL and may control flowering time by autonomous pathway. FQ4 were winter-environment-specific QTL and may control flowering time by photoperiod-pathway. Identification of the chromosomal location and effect of the genes influencing flowering time may hasten the development of canola varieties having an optimal time for flowering in target environments such as for high altitude areas, via marker-assisted selection.     

Quantitative trait loci for grain yield and yield components in a cross between a six-rowed and a two-rowed barley

Summary The positions of quantitative trait loci (QTL) for yield and yield components were estimated using a 85-point linkage map and phenotype data from a F₁-derived doubled haploid (DH) population of barley. Yield and its components were recorded in two growing seasons. Highly significant QTL effects were found for all traits at several sites in the genome. A major portion of the QTL was found on chromosome 2. The effect of the alleles in locus v on thousand grain weight and kernels per ear explained 70–80% of the genetic variation in the traits. QTL × year interaction was found for grain yield. Several different QTL were found within the two-rowed DH lines compared to those found in the six-rowed DH lines. Epistasis between locus v and several loci for yield and yield components indicates that genes are expressed differently in the two ear types. This may explain the difficulties of selecting high yielding lines from crosses between two-rowed and six-rowed barley.Abbreviations DH doubled haploid - QTL quantitative trait locus/loci - RAPD random amplified polymorphic DNA - RFLP restriction fragment length polymorphism - T. Prentice Tystofte Prentice - V. Gold Vogelsanger Gold     

QTL identification for molecular breeding of fibre yield and fibre quality traits in jute

In jute (Corchorus olitorius), quantitative trait loci (QTL) analysis was conducted to study the genetics of eight fibre yield traits and two fibre quality traits. For this purpose, we used a mapping population consisting of 120 recombinant inbred lines (RILs) and also used a linkage map consisting of 36 SSR markers that was developed by us earlier (Das et al. 2011). The RIL population was derived from the cross JRO 524 (coarse fibre) × PPO4 (fine fibre) following single seed descent. Using single-locus analysis involving composite interval mapping, a total of 21 QTLs were identified for eight fibre yield traits whereas for fibre quality (fibre fineness), only one QTL was detected. The QTL for fibre fineness explained 8.31–10.56% of the phenotypic variation and was detected in two out of three environments. Using two-locus analysis involving QTLNetwork, as many as 11 M-QTLs were identified for seven fibre yield traits (excluding top diameter) and one M-QTL was identified for fibre fineness which accounted for 4.57% of the phenotypic variation. For six fibre yield traits, we detected 16 E-QTLs involved in nine QQ epistatic interactions. For fibre fineness, four E-QTLs involved in two QQ epistatic interactions and for fibre strength, six E-QTLs involved in three QQ epistatic interactions were identified. Eight out of the 11 M-QTLs observed for the fibre yield traits were also involved in QE interactions; for fibre fineness and fibre strength, no QE interactions were observed.     

大白菜种皮颜色基因的QTL定位与分析

利用已构建的包括457个标记位点的大白菜分子遗传图谱,采用多QTL复合作图方法(MQM),通过目测和利用色差计测量两种方法对种皮颜色性状进行了QTL定位和分析。结果表明,共得到种皮颜色的QTLs 9个,其中最重要的QTLs位于A6上,命名为Sc-1,与利用色差计测量法检测到的控制种皮颜色性状L值QTL(ScL-2)和b值(Scb-2)位置完全相同,解释80.4%～100%的表型变异。     

Quantitative trait loci mapping of seed colour,hairy leaf,seedling anthocyanin,leaf chlorosis and days to flowering in F2 population of Brassica rapa L.

A diversity arrays technology (DArT) map was constructed to identify quantitative trait loci (QTL) affecting seed colour, hairy leaf, seedling anthocyanin, leaf chlorosis and days to flowering in Brassica rapa using a F₂ population from a cross between two parents with contrasting traits. Two genes with dominant epistatic interaction were responsible for seed colour. One major dominant gene controls the hairy leaf trait. Seedling anthocyanin was controlled by a major single dominant gene. The parents did not exhibit leaf chlorosis; however, 32% F₂ plants showed leaf chlorosis in the population. A distorted segregation was observed for days to flowering in the F₂ population. A linkage map was constructed with 376 DArT markers distributed over 12 linkage groups covering 579.7 cM. The DArT markers were assigned on different chromosomes of B. rapa using B. rapa genome sequences and DArT consensus map of B. napus. Two QTL (RSC1‐2 and RSC12‐56) located on chromosome A8 and chromosome A9 were identified for seed colour, which explained 19.4% and 18.2% of the phenotypic variation, respectively. The seed colour marker located in the ortholog to Arabidopsis thaliana Transparent Testa2 (AtTT2). Two QTL RLH6‐0 and RLH9‐16 were identified for hairy leaf, which explained 31.6% and 20.7% phenotypic variation, respectively. A single QTL (RSAn‐12‐157) on chromosome A7, which explained 12.8% of phenotypic variation was detected for seedling anthocyanin. The seedling anthocyanin marker is found within the A. thaliana Transparent Testa12 (AtTT12) ortholog. A QTL (RLC6‐04) for leaf chlorosis was identified, which explained 55.3% of phenotypic variation. QTL for hairy leaf and leaf chlorosis were located 0–4 cM apart on the same chromosome A1. A single QTL (RDF‐10‐0) for days to flowering was identified, which explained 21.4% phenotypic variation.     

Genetic mapping of QTLs for horticulture traits in a F2-3 population of bitter gourd (Momordica charantia L.)

An extensive genetic linkage map was constructed for bitter gourd (Momordica charantia L.) via the study of F₂ progenies derived from two cultivated inbred lines (gynoecia Z-1-4 and 189-4-1). The map included 194 loci on 11 chromosomes consisting of 26 EST-SSR loci, 28 SSR loci, 124 AFLP loci, and 16 SRAP loci. This map covered 1005.9 cM with 12 linkage groups. A total of 43 quantitative trait loci (QTLs), with a single QTL associated with 5.1–33.1 % phenotypic variance, were identified on nine chromosomes for 13 horticulture traits by analyzing the F_2-3 families and the genetic linkage map. The 13 horticulture traits which were investigated in three environments included female flower ratios (FFR), first female flower node (FFFN), fruit length, fruit diameter, flesh thickness, fruit shape, fruit pedicel length, fruit length pedicel ratios, fruit weight (FW), fruit numbers per plant (FPP), yield per plant (YPP), stem diameter (SD), and internodes length (IL). One QTL cluster region was detected on Lg-5 which contained the most important QTLs for YPP, FPP, FFFN, FFR, and FW with high contributions to phenotypic variance (5.8–25.4 %).     

Mapping quantitative trait loci for yield-related traits in Chinese cabbage (Brassica rapa L. ssp. pekinensis)

Chinese cabbage (Brassica rapa L. ssp. pekinensis) is one of the most important vegetables in China. However, the inheritance of yield-related traits in Chinese cabbage is poorly understood to date. To map quantitative trait loci (QTL) for yield-related traits in Chinese cabbage, a genetic linkage map was constructed with 192 doubled haploid (DH) lines. The genetic map was constructed based on 190 sequence-related amplified polymorphisms and 43 simple sequence repeats. QTL mapping was conducted for 11 yield-related traits in 170 DH lines derived from a cross between two diverse Chinese cabbage lines, ‘WZ’ and ‘FT’, under different environmental conditions. A total of 46 main QTL (M-QTL) and 7 epistatic QTL (E-QTL) were identified. The phenotypic variation explained by each M-QTL and E-QTL ranged from 4.85 to 25.06 % and 1.85 to 13.29 %, respectively. The QTL-by-environment interactions were detected using the QTLNetwork 2.0 program in joint analyses of multi-environment phenotypic values. The phenotypic variation explained by each QTL and by QTL × environment interaction was 1.14–4.24 % and 0.00–1.26 %, respectively. Our results provide a better understanding of the genetic factors controlling leaf and head-related traits in Chinese cabbage.     

Molecular mapping of quantitative trait loci for plant growth, yield and yield related traits across three diverse locations in a doubled haploid rice population

A doubled haploid (DH) population of 125lines derived from IR64 × Azucena, an indica – japonica cross were grown in three different locations in India during the wet season of 1995. The parents of mapping population had diverse phenotypic values for the eleven traits observed. The DH lines exhibited considerable amount of variation for all the traits. Transgressive segregants were observed. Interval analysis with threshold LOD > 3.00 detected a total of thirty four quantitative trait loci (QTL) for eleven traits across three locations. The maximum number of twenty QTL were detected at Punjab location of North India. A total of seven QTL were identified for panicle length followed by six QTL for plant height. Eight QTL were identified on three chromosomes which were common across locations. A maximum of seven QTL were identified for panicle length with the peak LOD score of 6.01 and variance of 26.80%. The major QTL for plant height was located on Chromosome 1 with peak LOD score of 16.06 flanked by RZ730-RZ801 markers. Plant height had the maximum number of common QTL across environment at the same marker interval. One QTL was identified for grain yield per plant and four QTL for thousand grain weight. Clustering of QTL for different traits at the same marker intervals was observed for plant height, panicle exsertion, panicle number, panicle length and biomass production. This suggests that pleiotropism and or tight linkage of different traits could be the plausible reason for the congruence of several QTL. Common QTL identified across locations and environment provide an excellent opportunity for selecting stable chromosomal regions contributing to yield and yield components to develop QTL introgressed lines that can be deployed in rice breeding program. This revised version was published online in July 2006 with corrections to the Cover Date.     

甘蓝型油菜产量及其构成因素的QTL定位与分析

产量性状是复杂的数量性状, 对种子的单株产量及其构成因素(全株总有效角果数、每角粒数、千粒重)进行QTL定位和上位性分析,确定其在染色体上的位置及其遗传效应,可以探讨油菜杂种优势产生原因,提高育种中对产量性状优良基因型选择的效率,达到提高油菜产量的目的。在双低油菜细胞质雄性不育保持系1141B和双高恢复系垦C₁构建的F₂作图群体中,运用SRAP、AFLP和SSR三种标记技术构建了一个甘蓝型油菜(Brassica napus L.)的分子标记遗传连锁图谱。共包含244个标记,分布于20个主要连锁群、1个三联体上,图谱总长度为2 769.5 cM。采用Windows QTL Cartographer Version 2.0统计软件及复合区间作图法,对油菜单株产量及其3大构成因素进行QTL定位,共检测到QTLs 16个分布在9个连锁群上,其中第6和13连锁群最多,均有3个。单个QTL解释性状表型变异的0.38%～73.34%。对于同一性状,等位基因的增效作用既来自母本,亦源自父本;采用双向方差分析法对位点间互作及其上位性进行分析,检测到26对影响产量构成性状的上位性互作效应QTL,说明油菜基因组中存在大量控制产量的互作位点,油菜产量性状的上位性存在着多效性,上位性互作包括QTL与非QTL位点,其中以非QTL位点较多。一般互作位点的独立效应值较小,而互作的效应值显著增大,且一般超过两位点独立效应值之和。反映了控制产量性状基因的复杂性。上位性是甘蓝型油菜产量性状杂种优势的重要遗传基础。     

Quantitative trait loci (QTL) mapping of silique length and petal colour in Brassica rapa

Recombinant inbred lines (RILs) derived from a cross between Brassica rapa L. cv. ‘Sampad’, and an inbred line 3‐0026.027 was used to map the loci controlling silique length and petal colour. The RILs were evaluated under four environments. Variation for silique length in the RILs ranged from normal, such as ‘Sampad’, to short silique, such as 3‐0026.027. Three QTL, SLA3, SLA5 and SLA7, were detected on the linkage groups A3, A5 and A7, respectively. These QTL explained 36.0 to 42.3% total phenotypic variance in the individual environments and collectively 32.5% phenotypic variance. No additive × additive epistatic interaction was detected between the three QTL. Moreover, no QTL × environment interaction was detected in any of the four environments. The number of loci for silique length detected based on QTL mapping agrees well with the results from segregation analysis of the RILs. In case of petal colour, a single locus governing this trait was detected on the linkage group A2.     

大豆油分含量相关的QTL间的上位效应和QE互作效应

利用Charleston × 东农594重组自交系构建的SSR遗传图谱, 及混合线性模型方法对2002年到2006年连续5年的大豆油分含量进行QTL定位, 并作加性效应, 加性×加性上位互作效应及环境互作效应分析。共检测到11个控制油分含量的QTL, 分别位于第A1、A2、B1、C2、D1a、D1b、F、H和O连锁群上, 其中2个表现为遗传正效应, 9个表现为遗传负效应, 另检测到15对影响油分含量的加性×加性上位互作效应的QTL, 解释该性状总变异的17.84%。发现9个QTL与环境存在互作, 贡献率达到5.76%。     

Identification of quantitative trait loci for grain yield, seed protein concentration and maturity in field pea (Pisum sativum L.)

Breeding efforts to improve grain yield, seed protein concentration and early maturity in pea (Pisum sativum L.) have proven to be difficult. The use of molecular markers will improve our understanding of the genetic factors conditioning these traits and is expected to assist in selection of superior genotypes. This study was conducted to identify genetic loci associated with grain yield, seed protein concentration and early maturity in pea. A population of 88 recombinant inbred lines (RILs) that was developed from a cross between 'Carneval' and 'MP1401' was evaluated at 13 environments across the provinces of Alberta, Manitoba and Saskatchewan, Canada in 1998, 1999 and 2000. A linkage map consisting of 193 AFLPs (amplified fragment length polymorphism), 13 RAPDs (random amplified polymorphic DNA) and one STS (sequence tagged site) marker was used to identify putative quantitative trait loci (QTL) for grain yield, seed protein concentration and early maturity. Four QTL were identified each for grain yield and days to maturity, and three QTL were identified for seed protein concentration. A multiple QTL model for each trait showed that these genomic regions accounted for 39%, 45% and 35% of the total phenotypic variation for grain yield, seed protein concentration and days to maturity, respectively. The consistency of these QTL across environments and their potential for marker-assisted selection are discussed in this report.     

花生籽仁大小相关性状QTL定位

花生籽仁大小相关性状是决定花生产量的直接因素。为发掘与花生籽仁大小相关的QTL,本研究以中花16×J11构建的RIL群体为材料,得到了一张包含289个SSR标记、21个连锁群、覆盖长度为947.3cM的遗传连锁图谱。连续2年对籽仁大小相关性状鉴定表明,各性状在群体中变异广泛,呈典型正态分布,且大部分性状间显著相关。结合本研究构建的遗传图谱,利用WinCart2.5进行QTL定位分析,2年共检测到66个QTL,贡献率为3.23%~33.01%。与籽仁长(SL)、籽仁宽(SW)、籽仁长宽比(LWR)和百仁重(HSW)相关的QTL分别有18、16、18和14个。在这些QTL中,A05染色体上的区间A05A1500?A05A1530同时存在控制籽仁长(qSLA05.1和qSLA05.2)和百仁重的相关的QTL(qHSWA05.1);B06染色体上的区间A06B135?A06B113同时存在控制籽仁宽(qSWB06.2和qSWB06.4)和百仁重相关的QTL(qHSWB06.4),这些稳定存在的主效QTL将为花生产量相关性状的精细定位和分子育种奠定基础。