Identification of new QTL for salt tolerance from rice variety Pokkali

Salt stress is an ever-present threat to rice production worldwide. Rice salinity tolerance is complex, both genetically and physiologically. The success and effectiveness in selecting salt-tolerant rice variety require the identification of QTL for the tolerance and closely linked molecular markers. In the present study, a RIL population consisting of 148 lines, derived from a cross between IR29 (salt-sensitive) and Pokkali (salt-tolerant), was used to identify new QTL for salt tolerance and investigate the relationships between salt stress caused injury and the changes in different physiological and morphological traits at the seedling stage. 14,470 high-quality SNP markers generated by the Rice 56K SNP array were converted to 1,467 bin markers for linkage mapping. A high-density genetic linkage map covering 1,680.9 cM was constructed, with the physical to genetic distance ratio being 222 Kb/cM. In total, 23 QTL for different salt tolerance indices were identified, including the previously reported Saltol which is currently used in breeding programmes. Three QTL for salt injury score (SIS) were located on chromosomes 1, 4 and 12, all being closely related to the long-distant Na⁺ transport from roots to shoots. These QTL showed additive effects, thus can be effectively used in breeding programme to pyramid various tolerance genes.     

QTL analysis for alkaline tolerance of rice and verification of a major QTL

Alkaline stress causes injuries to rice seedlings in many parts of the world and is therefore an important factor affecting rice production in such areas. In this study, we preliminarily located quantitative trait loci (QTLs) for survival days of seedlings (SDS) and the concentrations of Na⁺ and K⁺ in shoots (SNC and SKC) and roots (RNC and RKC) under alkaline stress using an F_2:3 population, which was derived from a cross between Caidao and WD20342 with 151 simple sequence repeat (SSR) markers. A total of seven QTLs were detected. Of these QTLs, qSNC3 had the largest effect, which explained 21.24% of the total phenotypic and is a major QTL. Next, a mapping population consisting of 190 BC₂F₂ plants was constructed using WD20342 as a donor parent to verify qSNC3. As a result, qSNC3 was delimited to an 81.7‐kb region between markers RM1221 and RM4404. In this region, LOC_Os03 g62500 and LOC_Os03 g62620 exhibited different expression between Caidao and WD20342 under alkaline stress. These results provide a basis for identifying genes related to alkaline tolerance in rice.     

Identification of novel QTL for leaf traits in soybean

Several leaf traits of soybean (Glycine max L. Merr.), including leaf area (LA), leaf shape (LS) and specific leaf weight (SLW) may be related to soybean yield. The objective of this study was to identify novel quantitative trait loci (QTL) for LA, LS and SLW in a recombinant inbred line (RIL) population. The phenotype data were collected in 2011 and 2012 for 93 F_7:10 RILs using a randomized complete block design with 2 replicates each year. Five hundred and sixteen single‐nucleotide polymorphism (SNP) markers and the phenotype data were used to detect QTL using single marker analysis (SMA) and composite interval mapping (CIM). Single markers analysis identified 26 QTL for the three traits, of which 17 were novel and the rests were previously reported QTL. Most of these QTL were also identified by CIM. Most QTL reported in this study were in close proximity (<1 cM) of one or more SNP markers. These publicly available SNP markers with close linkage to LA, LS and SLW should be useful for marker‐assisted breeding for these traits.     

Identification of QTL controlling post-flowering period in soybean

The length of the reproductive period affects the grain yield of soybean (Glycine max [L.] Merr), and genetic control of the period might contribute to yield improvement. To detect genetic factor(s) controlling the reproductive period, a population of recombinant inbred lines (RILs) was developed from a cross between Japanese landrace ‘Ippon-Sangoh’ and, Japanese cultivar ‘Fukuyutaka’ which differ in their duration from flowering to maturation (DFM) relative to the difference in the duration from sowing to flowering (DSF). In the RIL population, the DFM correlated poorly (r = −0.16 to 0.34) with the DSF in all field trials over 3 years. Two stable QTLs for the DFM on chromosomes (Chr-) 10 and 11 as well as two stable QTLs for the DSF on Chr-10 and -16 were identified. The QTL on Chr-11 for the reproductive period (designated as qDfm1; quantitative trait locus for duration from flowering to maturation 1) affected all three trials, and the difference in the DFM between the Fukuyutaka and Ippon-Sangoh was mainly accounted for qDfm1, in which the Fukuyutaka allele promoted a longer period. qDfm1 affected predominantly the reproductive period, and thus it might be possible to alter the period with little influence on the vegetative period.     

Mapping and validation of PCR-based markers associated with a major QTL for seed dormancy in wheat

Seed dormancy is one of the important factors controlling pre-harvest sprouting (PHS) resistance in wheat. We identified a major quantitative trait locus (QTL) for seed dormancy on the long arm of wheat chromosome 4A (4AL) via simple sequence repeat (SSR)-based genetic mapping using doubled haploid lines from a cross between Japanese PHS resistant variety ‘Kitamoe’ and the Alpine non-resistant variety “Münstertaler” (K/M). The QTL explained 43.3% of total phenotypic variation for seed dormancy under greenhouse conditions. SSR markers flanking the QTL were assigned to the chromosome long arm fraction length 0.59–0.66 on the basis of chromosome deletion analysis, suggesting that the gene(s) controlling seed dormancy are probably located within this region. Under greenhouse conditions, the QTL explained 28.5 and 39.0% of total phenotypic variation for seed dormancy in Haruyutaka/Leader (HT/L) and OS21-5/Haruyokoi (O/HK) populations, respectively. However, in field conditions, the effect was relatively low or not significant in both the K/M and HT/L populations. These markers were considered to be widely useful in common with various genetic backgrounds for improvement of seed dormancy through the use of marker-assisted selection. Further detailed research using near isogenic lines will be needed to define how this major QTL interacts with environmental conditions in our area.     

Simple sequence repeat markers linked to a major QTL controlling pod shattering in soybean

Shattering of soybean pods prior to harvest leads to a reduction in yield. In order to identify simple sequence repeat (SSR) markers linked to quantitative trait loci (QTLs) conditioning pod shattering, QTL analysis was conducted using an recombinant inbred line (RIL) population segregating for this trait. The degrees of pod‐shattering resistance were evaluated by heat treatment applied to pods harvested from plants in the field and in a growth chamber. Composite interval mapping identified one major QTL between SSR markers Sat_093 and Sat_366 on linkage group J for both environments. The position and the effect of this QTL were confirmed in an F₂ population derived from a cross between the pod shattering‐susceptible parental cultivar and a pod shattering‐resistant RIL. The SSR markers linked to the major QTL will be useful for marker‐assisted selection in soybean‐breeding programmes.     

QTL analysis of salt tolerance in Sorghum bicolor during whole-plant growth stages

To study the salt tolerance genetics of sorghum, 181 recombinant inbred lines (RILs) were used to locate quantitative trait loci (QTLs) underlying salt stress adaptability. Six traits, namely, plant height (PH), stem diameter (SD), total biomass (TB), stem fresh weight (SFW), juice weight (JW) and Brix, were investigated under normal and salt stress conditions in two years. A total of 53 QTLs for the six traits under both conditions and their corresponding salt tolerance index (STI) were detected and phenotypic variation explained (PVE) ranged from 4.16% to 20.42%. Six of the QTLs, qTB6, qSFW9, qJW9, qBrix2, qBrix10 and qSTI-Brix9, were the main effect QTLs controlling salt tolerance and had a PVE more than 10%. qSFW9 and qJW9 colocalized in the same marker interval as SB5069-UGSM18 and had PVEs of 17.70% and 14.20%, respectively, with positive effects from L-Tian. QTL clusters controlling PH, TB, STI-TB, SFW and JW were consistently mapped in the marker interval of Xcup19-SB4177 on chromosome 7. These locations might serve as target sites for marker-assisted selection (MAS) in improving salt tolerance of sorghum.     

花生资源耐盐性的鉴定与评价

为筛选耐盐花生种质并为花生遗传基础研究提供材料,本研究选用相对发芽势、相对发芽率、相对发芽指数和盐害率为指标,以0.5%的NaCl为胁迫浓度,对128份花生种质进行芽期耐盐性鉴定。结果表明,盐胁迫对花生种子萌发有显著的抑制作用,但盐胁迫的抑制效应因种质不同而存在明显差异;128份种质中,高耐盐种质仅占5%左右。在耐盐评价指标方面,除盐害率或相对发芽率以外,相对发芽指数可以作为评价指标之一。此外,盐胁迫条件下,地方品种的发芽速度高于育成品种。本研究筛选出JS011、JS024、JS125、JS491、JS523、JS524、JS525等7份高度耐盐种质可用于花生耐盐性基础研究的材料。     

Identification and validation of a yield-enhancing QTL cluster in rice (Oryza sativa L.)

Improvement of rice grain yield (YD) is an important goal in rice breeding. YD is determined by its related traits such as spikelet fertility (SF), 1,000-grain weight (TGW), and the number of spikelets per panicle (SPP). We previously mapped quantitative trait loci (QTLs) for SPP and TGW using the recombinant inbred lines (RILs) derived from the crosses between Minghui 63 and Teqing. In this study, four QTLs for SF and four QTLs for YD were detected in the RILs. Comparison of the locations of QTLs for these three yield-related traits identified one QTL cluster in the interval between RM3400 and RM3646 on chromosome 3. The QTL cluster contained three QTLs, SPP3a, SF3 and TGW3a, but no YD QTL was located there. To validate the QTL cluster, a BC₄F₂ population was obtained, in which SPP3a, SF3 and TGW3a were simultaneously mapped to the same region. SPP3a, SF3 and TGW3a explained 36.3, 29.5 and 59.0 % of phenotype variance with additive effect of 16.4 spikelets, 6 % SF and 1.8 g grain weight, respectively. In the BC₄F₂ population, though the region has opposite effects on TGW and SPP/SF, a YD QTL YD3 identified in this cluster region can increase 4.6 g grains per plant, which suggests this QTL cluster is a yield-enhancing QTL cluster and can be targeted to improve rice yield by marker aided selection.     

甘蓝型油菜耐盐和耐旱相关性状的QTL分析

盐胁迫和干旱胁迫是非生物胁迫中影响作物产量的重要因素,检测与耐盐和耐旱相关的QTL,可为抗逆油菜品种的选育提供理论依据。本研究利用德国冬性甘蓝型油菜Express和中国半冬性甘蓝型油菜SWU07为亲本构建的包含261个株系的双单倍体(doubled haploid, DH)群体,分别以1.2%NaCl溶液和20%PEG-6000溶液作为培养液模拟盐胁迫和干旱胁迫,去离子水为对照,对2个亲本和DH群体进行发芽试验。播种后7 d测定幼苗根长、鲜重及发芽率,计算各性状在盐胁迫和干旱胁迫下的相对值,并作为评价耐盐和耐旱的指标。根据已构建的遗传连锁图谱进行QTL定位。盐胁迫下,在3次重复中共检测到与盐胁迫相关的QTL12个,分布在A02、A03、A05、A09、C01和C09染色体上,单个QTL可解释的表型变异为3.61%～10.59%,其中5个QTL在不同的重复中被检测到。干旱胁迫下,共检测到与干旱胁迫相关的QTL 9个,分布在A01、A02、A03、A05、A09、A10和C03染色体上,单个QTL可解释的表型变异为3.94%～12.90%,其中2个QTL在不同的重复中被检测到。此外,在A0...     

QTL analysis of flooding tolerance in soybean at an early vegetative growth stage

Soybean cultivars are sensitive to flooding stress and their seed yields are substantially reduced in response to the stress. This study was conducted to investigate the genetic basis of flooding tolerance at an early vegetative growth stage. Sixty recombinant inbred lines derived from a cross between a relatively tolerant cv. ‘Misuzudaizu’ and a sensitive cv. ‘Moshidou Gong 503’ were grown in pots in a vinyl plastic greenhouse in 2002 and 2003. At the two‐leaf stage, half of the pots were waterlogged by water placed in plastic containers and adjusted to 5 cm above the soil surface. After 3 weeks of treatment, the pots were returned to the greenhouse and grown until maturity. Flooding tolerance was evaluated by dividing the seed weight of the treated plants by that of the control plants. Quantitative trait loci (QTL) analysis using 360 genetic markers revealed three QTLs for flooding tolerance, ft1 to ft3 in 2002. The ft1 (molecular linkage group C2) was reproducible and an additional four QTLs, ft4 to ft7, were found in 2003. The ft1 had a high LOD score in both years (15.41 and 7.57) and accounted for 49.2% and 30.5% of the total variance, respectively. A large QTL for days to flowering was consistently observed across treatments and years at a similar position to ft1. Comparing the relative location with markers, the maturity gene probably corresponds to E1. Late maturity may have conferred a longer growth period for recovery from flooding stress.     

大豆根部水压胁迫耐逆指数遗传体系解析

大豆是重要的植物蛋白质和植物油脂来源,干旱是影响大豆产量的重要环境因子之一。为解析大豆耐旱性的遗传基础,本研究在PEG水压胁迫条件下,对由409个家系组成的巢式关联作图群体(具有1个共同亲本的2个重组自交系群体组成)进行叶片脯氨酸含量测定,通过限制性二阶段多位点全基因组关联分析(restrictivetwo-stagemultilocus genome-wide association study,RTM-GWAS),解析了大豆根部水压胁迫耐逆指数(root hydraulic stress tolerance index,RHSTI)的遗传体系。结果表明,在春季和夏季环境下,3个亲本蒙8260(共同亲本)、通山薄皮黄豆甲和正阳白毛平顶在RHSTI上均存在显著差异,其衍生群体RHSTI表型变异丰富,变幅分别为0.11~2.94和0.03~1.93,遗传力分别为97.7%和97.9%;2个环境联合分析发现,家系遗传力和家系与环境互作遗传力分别为37.9%和60.1%,说明群体RHSTI的变异受遗传和环境共同控制。通过RTM-GWAS方法,共检测到45个与RHSTI相关的QTL,分布在大豆18条染色体上,可以解释37.58%的表型变异,其中7个QTL的表型贡献率超过1%,为大贡献位点;这些QTL中,有34个位点与环境存在显著互作,可以解释12.50%的表型变异。结合PEG胁迫下大豆转录组数据,在定位区间500kb范围内共筛选到38个差异表达基因,可归为ABA响应因子、逆境响应因子、转录因子、发育因子、蛋白代谢因子、未知功能和其他等7类,其中逆境响应因子、转录因子和发育因子是最大的3类;其中位于主效位点的6个基因,与ABA响应因子、逆境响应因子、转录因子相关,应为主要候选基因。上述结果表明,大豆耐旱性是一个由多位点、多基因控制的复杂数量性状,且与环境存在互作,遗传基础复杂。研究结果为大豆耐旱性分子育种提供了依据。     

Fine mapping of a major flowering time QTL on soybean chromosome 6 combining linkage and association analysis

Flowering time is a key trait in the plant life cycle and an important selection criterion for soybean. Here, we combine the advantages of genome-wide association and linkage mapping to identify and fine map quantitative trait loci (QTLs) associated with flowering time. Linkage mapping was performed using 152 recombinant inbred lines and a major QTL, qFT6, affecting flowering time was found on chromosome 6. To refine the qFT6, the 192 natural accessions were genotyped using eight new simple sequence repeats and 10 single nucleotide polymorphisms markers covering the qFT6 region Haplotype analysis showed that the haplotype between markers BARC-014947-01929 and Satt365 could explain more phenotypic variation (26.5 %) than any other combination of markers. These results suggested that the target flowering time gene was located in ~300 kb between BARC-014947-01929 and Satt365, including three predicted genes. High-resolution map in qFT6 region will be useful not only for marker-assisted selection of flowering time but also for further positional cloning of the target gene. These results indicate that combining association and linkage mapping provides an efficient approach for fine mapping of soybean genes.     

Identification and verification of pleiotropic QTL controlling multiple amino acid contents in soybean seed

Soybean is important throughout the world due to its high seed protein and oil, while the quality and quantity of seed amino acids need to be improved. To improve the multiple amino acid concentrations in soybean simultaneously, detecting and utilizing the pleiotropic quantitative trait loci (QTL) and related genes become increasingly important. In view of this, a F_6:7 recombinant inbred line population was genotyped using 1739 polymorphic SNP and 127 SSR markers in the present study and was phenotyped for seventeen types of amino acids simultaneously. In total, twelve co-located or overlapped pleiotropic additive QTL clusters, which explained 2.38–16.79% of the amino acid variation, were identified. Of them, one novel pleiotropic QTL cluster with a phenotypic variation explained ranging from 8.84 to 16.79% for ten kinds of amino acid contents (glycine, alanine, isoleucine, leucine, valine, methionine, aspartic acid, glutamic acid, lysine and phenylalanine), was located at the same position on linkage group D2, and the confidence interval was only 0.8 cM. Moreover, the individuals in this family-based population (345 lines) and another cultivar-based population (254 varieties) with different genotypes at the common flanking markers for this QTL cluster showed significantly different amino acid contents, which further validated the QTL mapping results. Additionally, some candidate genes that might participate in the amino acid biosynthesis process were found in these pleiotropic QTL regions. Thus, novel pleiotropic QTL clusters could be applied in marker-assisted selection breeding or map-based candidate gene cloning in soybean for multiple amino acid genetic improvements in seed in the future.     

QTL mapping of phosphorus deficiency tolerance in soybean (Glycine max L. Merr.)

Phosphorus (P) deficiency is a major abiotic stress that limits plant growth and crop productivity throughout the world. In the present study, 184 recombinant inbred line (RIL) families developed from soybean varieties Kefeng No. 1 and Nanong 1138-2 were used to identify quantitative trait loci (QTL) associated with P deficiency tolerance. Seven traits of plant height (HT), weight of fresh shoot (FSW), weight of fresh root (FRW), weight of dry root (DRW), length of main root (RL), phosphorus content in leaf (LP), phosphorus content in root (RP), were used as parameters to assess the phosphorus deficiency tolerance. The QTL mapping for the seven traits was performed using the program WinQTLCart. Seven QTLs were detected and mapped on two linkage groups for three traits of weight of fresh shoot, phosphorus contents in leaf and in root. The QTLs that had LOD scores more than three were detected for all of the three traits above. Most of the QTLs explained more than 10% of the total variation. The two QTLs for phosphorus content in leaf explained more than 20% of the total variation, respectively. Five QTLs were mapped on linkage group F2, and two on linkage F1. It was suggested that the genes related to phosphorus deficiency tolerance located on linkage group F in soybean.Contributed equally to this work.     

Identification of the QTL underlying the vitamin E content of soybean seeds

Vitamin E (VE) is an important antioxidant supplement for human health. Soybean seed extracts are the main source of VE supplements. Therefore, increasing the VE content of soybean seeds is important issue in breeding programmes. To detect quantitative trait loci (QTL) associated with VE in soybean seeds, 238 F_6:7 recombinant inbred lines (RILs) were created by crossing a high VE cultivar, ‘Beifeng 9’, with a low VE cultivar, ‘Freeborn’. A genetic map was constructed using 218 polymorphic simple sequence repeat (SSR) markers. Composite interval mapping analysis detected 66 QTLs for contents of individual and total VE, 21 for α‐tocopherol, seventeen for γ‐tocopherol, thirteen for δ‐tocopherol and fifteen for total VE. The QTLs were located on chromosomes 9, 10, 15, 18 and 19. Phenotypic variance underlain by each QTL ranged from 2.4% to 32.6%. Two major QTLs (BARCSOYSSR_10_1140–BARCSOYSSR_10_1188 and BARCSOYSSR_15_0855 to BARCSOYSSR_15_0887) associated with α‐Toc, γ‐Toc, δ‐Toc and total VE contents were mapped on chromosomes 10 and 15. They explained 12.0% and 32.6% of phenotypic variance for α‐Toc; 5.5% and 13.0% for γ‐Toc; 6.6% and 23.6% for δ‐Toc; and 19.6% and 21.8% for total VE. QTL intervals BARCSOYSSR_15_0790–BARCSOYSSR_15_0855 (Qα15_1, Qγ15_1), BARCSOYSSR_15_1113–BARCSOYSSR_15_1159 (Qα15_3, Qδ15_2, QTVE15_4) and BARCSOYSSR_15_1159–BARCSOYSSR_15_1190 (Qα15_4, Qγ15_5, QTVE15_5) were associated with α‐Toc and explained 22.2%, 23.8% and 24.4% of the phenotypic variation in multiple environments. BARCSOYSSR_09_1098–BARCSOYSSR_09_1128 (QTVE9_1) and BARCSOYSSR_15_0887–BARCSOYSSR_15_0935 (QTVE15_2, Qγ15_3) associated with total VE content explained 21.8% and 16.4% of the phenotypic variation in two environments. These QTLs allow for marker‐assisted selection for cultivars with high VE contents.     

Identification and validation of quantitative trait loci associated with seed yield in soybean

In soybean [Glycine max (L.) Merrill], the genetic analysis of seed yield is important to aid in the breeding of high-yielding cultivars. Seed yield is a complex trait, and the number of quantitative trait loci (QTL) involved in seed yield is high. The aims of this study were to identify QTL associated with seed yield and validate their effects on seed yield using near-isogenic lines. The QTL analysis was conducted using a recombinant inbred line population derived from a cross between Japanese cultivars ‘Toyoharuka’ and ‘Toyomusume’, and eight seed yield-associated QTL were identified. There were significant positive correlations between seed yield and the number of favorable alleles at QTL associated with seed yield in the recombinant inbred lines for three years. The effects of qSY8-1, a QTL promoting greater seed yield, was validated in the Toyoharuka background. In a two-year yield trial, the 100-seed weight and seed yield of Toyoharuka-NIL, the near-isogenic line having the Toyomusume allele at qSY8-1, were significantly greater than those of Toyoharuka (106% and 107%, respectively) without any change for days to flowering and maturity. Our results suggest that qSY8-1 was not associated with maturity genes, and contributed to the 100-seed weight.