QTL mapping for downy mildew resistance in cucumber via bulked segregant analysis using next-generation sequencing and conventional methods

Key message

QTL mapping using NGS-assisted BSA was successfully applied to an F ₂ population for downy mildew resistance in cucumber. QTLs detected by NGS-assisted BSA were confirmed by conventional QTL analysis.

Abstract

Downy mildew (DM), caused by Pseudoperonospora cubensis, is one of the most destructive foliar diseases in cucumber. QTL mapping is a fundamental approach for understanding the genetic inheritance of DM resistance in cucumber. Recently, many studies have reported that a combination of bulked segregant analysis (BSA) and next-generation sequencing (NGS) can be a rapid and cost-effective way of mapping QTLs. In this study, we applied NGS-assisted BSA to QTL mapping of DM resistance in cucumber and confirmed the results by conventional QTL analysis. By sequencing two DNA pools each consisting of ten individuals showing high resistance and susceptibility to DM from a F₂ population, we identified single nucleotide polymorphisms (SNPs) between the two pools. We employed a statistical method for QTL mapping based on these SNPs. Five QTLs, dm2.2, dm4.1, dm5.1, dm5.2, and dm6.1, were detected and dm2.2 showed the largest effect on DM resistance. Conventional QTL analysis using the F₂ confirmed dm2.2 (R ² = 10.8–24 %) and dm5.2 (R ² = 14–27.2 %) as major QTLs and dm4.1 (R ² = 8 %) as two minor QTLs, but could not detect dm5.1 and dm6.1. A new QTL on chromosome 2, dm2.1 (R ² = 28.2 %) was detected by the conventional QTL method using an F₃ population. This study demonstrated the effectiveness of NGS-assisted BSA for mapping QTLs conferring DM resistance in cucumber and revealed the unique genetic inheritance of DM resistance in this population through two distinct major QTLs on chromosome 2 that mainly harbor DM resistance.

     

Genetic Analysis of Cold Tolerance at the Germination and Booting Stages in Rice by Association Mapping

Low temperature affects the rice plants at all stages of growth. It can cause severe seedling injury and male sterility resulting in severe yield losses. Using a mini core collection of 174 Chinese rice accessions and 273 SSR markers we investigated cold tolerance at the germination and booting stages, as well as the underlying genetic bases, by association mapping. Two distinct populations, corresponding to subspecies indica and japonica showed evident differences in cold tolerance and its genetic basis. Both subspecies were sensitive to cold stress at both growth stages. However, japonica was more tolerant than indica at all stages as measured by seedling survival and seed setting. There was a low correlation in cold tolerance between the germination and booting stages. Fifty one quantitative trait loci (QTLs) for cold tolerance were dispersed across all 12 chromosomes; 22 detected at the germination stage and 33 at the booting stage. Eight QTLs were identified by at least two of four measures. About 46% of the QTLs represented new loci. The only QTL shared between indica and japonica for the same measure was qLTSSvR6-2 for SSvR. This implied a complicated mechanism of old tolerance between the two subspecies. According to the relative genotypic effect (RGE) of each genotype for each QTL, we detected 18 positive genotypes and 21 negative genotypes in indica, and 19 positive genotypes and 24 negative genotypes in japonica. In general, the negative effects were much stronger than the positive effects in both subspecies. Markers for QTL with positive effects in one subspecies were shown to be effective for selection of cold tolerance in that subspecies, but not in the other subspecies. QTL with strong negative effects on cold tolerance should be avoided during MAS breeding so as to not cancel the effect of favorable QTL at other loci.     

A novel functional gene associated with cold tolerance at the seedling stage in rice

Identification and cloning of cold‐tolerant genes that can stably express under different cold environments are crucial for molecular rice breeding for cold tolerance. In the previous study, we identified a cold‐tolerant QTL at the seedling stage, qCTS‐9 which could be detected under different cold environments using a recombinant inbred line (RIL) population derived from a cold‐tolerant variety Lijiangxintuanheigu (LTH) and a cold‐sensitive variety Shanhuangzhan 2 (SHZ‐2). In this study, eight candidate genes within the qCTS‐9 interval were identified through integrated analysis of QTL mapping with genomewide differential expression profiling of LTH. The qRT‐PCR assay showed that only Os09g0410300 exhibited different expression patterns between LTH and SHZ‐2 during cold stress, and significantly positive correlation was found between cold induction of Os09g0410300 and seedling cold tolerance in the RI lines. Five SNPs and one InDel in the promoters of Os09g0410300 were detected between LTH and SHZ‐2, and the InDel marker ID410300 designed based on the insertion–deletion polymorphism in the promoter was significantly associated with seedling cold tolerance in RIL population. Further, Os09g0410300 over‐expression plants exhibited enhanced cold tolerance at the seedling stage compared with the wild‐type plants. Thus, our results suggest that Os09g0410300 is the functional gene underlying qCTS‐9. To our knowledge, it is a novel gene contributed to enhance cold tolerance at the seedling stage in rice. Identification of the functional gene underlying qCTS‐9 and development of the gene‐specific marker will facilitate molecular breeding for cold tolerance at the seedling stage in rice through transgenic approach and marker‐assisted selection (MAS).     

QTL sequencing strategy to map genomic regions associated with resistance to ascochyta blight in chickpea

Whole‐genome sequencing‐based bulked segregant analysis (BSA) for mapping quantitative trait loci (QTL) provides an efficient alternative approach to conventional QTL analysis as it significantly reduces the scale and cost of analysis with comparable power to QTL detection using full mapping population. We tested the application of next‐generation sequencing (NGS)‐based BSA approach for mapping QTLs for ascochyta blight resistance in chickpea using two recombinant inbred line populations CPR‐01 and CPR‐02. Eleven QTLs in CPR‐01 and six QTLs in CPR‐02 populations were mapped on chromosomes Ca1, Ca2, Ca4, Ca6 and Ca7. The QTLs identified in CPR‐01 using conventional biparental mapping approach were used to compare the efficiency of NGS‐based BSA in detecting QTLs for ascochyta blight resistance. The QTLs on chromosomes Ca1, Ca4, Ca6 and Ca7 overlapped with the QTLs previously detected in CPR‐01 using conventional QTL mapping method. The QTLs on chromosome Ca4 were detected in both populations and overlapped with the previously reported QTLs indicating conserved region for ascochyta blight resistance across different chickpea genotypes. Six candidate genes in the QTL regions identified using NGS‐based BSA on chromosomes Ca2 and Ca4 were validated for their association with ascochyta blight resistance in the CPR‐02 population. This study demonstrated the efficiency of NGS‐based BSA as a rapid and cost‐effective method to identify QTLs associated with ascochyta blight in chickpea.     

Identification and pyramiding of QTLs for cold tolerance at the bud bursting and the seedling stages by use of single segment substitution lines in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Cold stress is one of the main constraints in rice production, and damage from cold can occur at different developmental stages in rice. Understanding the genetic basis of cold tolerance is the key for breeding cold-tolerant variety. In this study, we used single segment substitution lines (SSSLs) derived from a cross between cold-tolerant japonica variety “Nan-yang-zhan” and a popular indica variety “Hua-jing-xian 74” to detect and pyramid QTLs for cold tolerance at the bud bursting and the seedling stages. Evaluation of cold tolerance of these SSSLs and their recurrent parent helped identify two cold-tolerant QTLs (qCTBB-5 and qCTBB-6) at the bud bursting stage and two cold-tolerant QTLs (qCTS-6 and qCTS-12) at the seedling stage. The SSSLs carrying these QTLs showed stronger cold tolerance than their recurrent parent HJX74 did in three independent experiments. The qCTBB-6 and qCTS-6 were mapped to the same chromosomal region. QTL pyramiding was performed by intercrossing of SSSLs carrying the respective QTLs for cold tolerance at the bud bursting stage and the seedling stage and marker-assisted selection (MAS). The selected pyramiding line SC1-1 with different cold-tolerant QTLs showed cumulative effects on cold tolerance. Our results suggest that different genes (QTLs) control cold tolerance at bud bursting and seedling stages, and pyramiding of stable expression QTLs for cold tolerance at different developmental stages through MAS is a good strategy to prevent cold damage in rice.     

Genome-wide association study (GWAS) of salt tolerance in worldwide soybean germplasm lines

Salt is a severe abiotic stress causing soybean yield loss in saline soils and irrigated fields. Marker-assisted selection (MAS) is a powerful genomic tool for improving the efficiency of breeding salt-tolerant soybean varieties. The objectives of this study were to uncover novel single-nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs) associated with salt tolerance and to confirm the previously identified genomic regions and SNPs for salt tolerance. A total of 283 diverse soybean plant introductions (PIs) were screened for salt tolerance in the greenhouse based on leaf chloride concentrations and leaf chlorophyll concentrations after 12–18 days of 120-mM NaCl treatment. A total of 33,009 SNPs across 283 genotypes from the Illumina Infinium SoySNP50K BeadChip database were employed in the association analysis with leaf chloride concentrations and leaf chlorophyll concentrations. Genome-wide association mapping showed that 45 SNPs representing nine genomic regions on chromosomes (Chr.) 2, 3, 7, 8, 10, 13, 14, 16, and 20 were significantly associated with both leaf chloride concentrations and leaf chlorophyll concentrations in 2014, 2015, and combined years. A total of 31 SNPs on Chr. 3 were mapped at or near the previously reported major salt tolerance QTL. The significant SNP on Chr. 2 was also in proximity to the previously reported SNP for salt tolerance. The other significant SNPs represent seven putative novel QTLs for salt tolerance. The significant SNP markers on Chr. 2, 3, 14, 16, and 20, which were identified in both general linear model and mixed linear model, were highly recommended for MAS in breeding salt-tolerant soybean varieties.     

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.     

小麦幼苗耐热性的QTL定位分析

以小麦DH群体(‘旱选10号’ב鲁麦14’)为材料,在高温(热胁迫)及常温(对照)两种条件下考察小麦幼苗的根干重、苗干重、幼苗生物量、叶片叶绿素含量、叶绿素荧光参数及其耐热指数,并应用基于混合线性模型的复合区间作图法分析幼苗性状及其耐热指数QTL的数量、染色体分布及表达情况,以及QTL与环境的互作效应。结果显示:(1)亲本‘旱选10号’的耐热性明显优于‘鲁麦14’,且杂交后代的耐热性出现超亲分离。(2)控制幼苗耐热相关性状的QTL位点在染色体2D、6B、3A、4A、5A和7A上分布较多,而控制幼苗性状耐热指数的QTL在染色体6A、6B、3A、2D、5A和7A上分布较多,QTL位点在染色体上的分布有区域化的趋势。(3)控制幼苗性状的单个加性QTL和上位性QTL解释的表型变异分别平均为2.48%和2.65%;而控制耐热指数的单个加性QTL和上位性QTL解释的表型变异分别平均为8.84%和1.98%。(4)在热胁迫和对照条件下共检测到与幼苗性状及其耐热指数有关的加性效应QTL 13个和上位性效应QTL 28对,分布在除4D和6D以外的19条染色体上。研究表明,控制幼苗性状的QTL以上位性效应为主,而其耐热指数的QTL以加性效应为主。     

Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations

Genotyping by sequencing (GBS) is the latest application of next-generation sequencing protocols for the purposes of discovering and genotyping SNPs in a variety of crop species and populations. Unlike other high-density genotyping technologies which have mainly been applied to general interest “reference” genomes, the low cost of GBS makes it an attractive means of saturating mapping and breeding populations with a high density of SNP markers. One barrier to the widespread use of GBS has been the difficulty of the bioinformatics analysis as the approach is accompanied by a high number of erroneous SNP calls which are not easily diagnosed or corrected. In this study, we use a 384-plex GBS protocol to add 30,984 markers to an indica (IR64) × japonica (Azucena) mapping population consisting of 176 recombinant inbred lines of rice (Oryza sativa) and we release our imputation and error correction pipeline to address initial GBS data sparsity and error, and streamline the process of adding SNPs to RIL populations. Using the final imputed and corrected dataset of 30,984 markers, we were able to map recombination hot and cold spots and regions of segregation distortion across the genome with a high degree of accuracy, thus identifying regions of the genome containing putative sterility loci. We mapped QTL for leaf width and aluminum tolerance, and were able to identify additional QTL for both phenotypes when using the full set of 30,984 SNPs that were not identified using a subset of only 1,464 SNPs, including a previously unreported QTL for aluminum tolerance located directly within a recombination hotspot on chromosome 1. These results suggest that adding a high density of SNP markers to a mapping or breeding population through GBS has a great value for numerous applications in rice breeding and genetics research.     

Quantitative trait loci mapping of resistance to Laodelphax striatellus (Homoptera: Delphacidae) in rice using recombinant inbred lines

Laodelphax striatellus Fallén (Homoptera: Delphacidae), is a serious pest in rice, Oryza sativa L., production. A mapping population consisting of 81 recombinant inbred lines (RILs), derived from a cross between japonica' Kinmaze' and indica' DV85' rice, was used to detect quantitative trait loci (QTLs) for the resistance to L. striatellus. Seedbox screening test (SST), antixenosis test, and antibiosis test were used to evaluate the resistance response of the two parents and 81 RILs to L. striatellus at the seedling stage, and composite interval mapping was used for QTL analysis. When the resistance was measured by SST method, two QTLs conferring resistance to L. striatellus were mapped on chromosome 11, namely, Qsbph11a and Qsbph11b, with log of odds scores 2.51 and 4.38, respectively. The two QTLs explained 16.62 and 27.78% of the phenotypic variance in this population, respectively. In total, three QTLs controlling antixenosis against L. striatellus were detected on chromosomes 3, 4, and 11, respectively, accounting for 37.5% of the total phenotypic variance. Two QTLs expressing antibiosis to L. striatellus were mapped on chromosomes 3 and 11, respectively, explaining 25.9% of the total phenotypic variance. The identified QTL located between markers XNpb202 and C1172 on chromosome 11 was detected repeatedly by three different screening methods; therefore, it may be important to confer the resistance to L. striatellus. Once confirmed in other mapping populations, these QTLs should be useful in breeding for resistance to L. striatellus by marker-assisted selection of different resistance genes in rice varieties.     

Genome-wide association mapping of salinity tolerance in rice (Oryza sativa)

Salinity tolerance in rice is highly desirable to sustain production in areas rendered saline due to various reasons. It is a complex quantitative trait having different components, which can be dissected effectively by genome-wide association study (GWAS). Here, we implemented GWAS to identify loci controlling salinity tolerance in rice. A custom-designed array based on 6,000 single nucleotide polymorphisms (SNPs) in as many stress-responsive genes, distributed at an average physical interval of <100 kb on 12 rice chromosomes, was used to genotype 220 rice accessions using Infinium high-throughput assay. Genetic association was analysed with 12 different traits recorded on these accessions under field conditions at reproductive stage. We identified 20 SNPs (loci) significantly associated with Na⁺/K⁺ ratio, and 44 SNPs with other traits observed under stress condition. The loci identified for various salinity indices through GWAS explained 5–18% of the phenotypic variance. The region harbouring Saltol, a major quantitative trait loci (QTLs) on chromosome 1 in rice, which is known to control salinity tolerance at seedling stage, was detected as a major association with Na⁺/K⁺ ratio measured at reproductive stage in our study. In addition to Saltol, we also found GWAS peaks representing new QTLs on chromosomes 4, 6 and 7. The current association mapping panel contained mostly indica accessions that can serve as source of novel salt tolerance genes and alleles. The gene-based SNP array used in this study was found cost-effective and efficient in unveiling genomic regions/candidate genes regulating salinity stress tolerance in rice.     

水稻萌发耐淹性的遗传分析

水稻(Oryza sativa)萌发耐淹性受到复杂的网络调控, 其分子机制不同于苗期耐淹性的相关机制, 萌发耐淹性的强弱影响着直播稻的成苗率。通过对256份水稻核心种质的萌发耐淹性评估, 发现粳稻和籼稻之间的萌发耐淹性差异并不显著, 都存在广泛的遗传变异。利用以粳稻R0380为供体亲本, 籼稻RP2334为轮回亲本的170个高代回交自交系构建含146个分子标记的连锁图谱, 以低氧胚芽鞘长度为性状指标, 通过复合区间作图法检测到影响萌发耐淹性的4个QTLs(quantitative trait loci), 分别定位于第2(2个)、3(1个)和8号(1个)染色体。贡献率最大的QTL为qGS2.2, 其值为17.34%, 增效等位基因来自轮回亲本籼稻RP2334; 其余3个QTLs的增效等位基因均来自供体亲本粳稻R0380, 贡献率分别为12.86%、9.37%和14.60%。     

水稻耐亚铁毒QTLs的定位

亚铁毒是潜育性水稻土中限制水稻产量的主要因子。利用龙杂8503／IR64的F2和等价的F3群体,在营养液中培养来定位耐亚铁毒的QTLs。通过构建101SSR标记的遗传连锁图谱来确定耐亚铁毒QTLs的位置和特性。借助叶片棕色斑点指数、株高和最大根长3个性状,利用营养液在水稻苗期来评价F2单株、F3群体和亲本龙杂8503、IR64,共检测到叶片棕色斑点指数、株高和最大根长的QTLs20个,分布在水稻的10条染色体上,表明这些性状受多基因控制。控制叶片棕色斑点指数的QTLs分别定位在第1染色体的RM315-RM212、第2染色体的RM6-RM240和第4染色体的RM252-RM451之间。与前人的研究结果比较发现：1）位于第4染色体RM252-RM451之间的控制叶片棕色斑点指数的QTL与水稻功能图谱上控制叶绿素含量减少的QTL的位置一致。另一个位于第1染色体的RM315-RM212之间的控制叶片棕色斑点指数的QTL与水稻功能图谱上位于C178-R2635之间控制叶绿素含量的QTL连锁。2）位于第2染色体RM6-RM240之间的第3个控制叶片棕色斑点指数的QTL与位于RZ58-CD0686的控制钾吸收的QTL连锁。     

基于染色体置换系的普通野生稻耐盐性QTL定位

本研究分别利用SSR标记、InDel标记以及简化基因组测序技术对一套以普通野生稻为供体亲本,9311为受体亲本的染色体置换系进行基因型鉴定,并通过对其不同生育期的耐盐性鉴定,共发掘2个与发芽期耐盐相关的QTL,13个与苗期耐盐性相关的QTL。其中与苗期存活率相关的QTL qSSR5.1、苗期耐盐等级相关的QTL qSSG5.1均被定位于同一位点,该位点对苗期存活率、苗期耐盐等级均具有增效作用,贡献率分别为6.36%、8.13%。在此QTL内包含与非生物胁迫相关基因OsDi19-1。经序列比对发现,OsDi19-1启动子区域在两亲本间存在较大差异,且受到盐胁迫时该基因表达量上升。同时,鉴定出水稻芽期耐盐的优异种质资源CSSL72、苗期耐盐的优异种质资源CSSL23、CSSL153,为水稻育种中耐盐性的改良提供了新的种质资源。     

Mapping of QTLs associated with cold tolerance during the vegetative stage in rice

Low-temperature stress is an important factor affecting the growth and development of rice (Oryza sativa L.) in temperate and high-elevation areas. Cold stress may cause various seedling injuries, delayed heading and yield reduction due to spikelet sterility. In this study, 181 microsatellite marker loci were used to identify quantitative trait loci (QTLs) associated with cold tolerance at the vegetative stage in 191 recombinant inbred lines (RILs) derived from a cross of a cold-tolerant temperate japonica cultivar (M-202) with a cold-sensitive indica cultivar (IR50). Different temperature regimes were applied in growth chambers on 191 RILs. The temperature regimes imposed in the growth chamber simulated cold-stress injuries at the seedling and late vegetative stages. In this study a major QTL was identified on chromosome 12, designated as qCTS12a, that was closely associated with cold-induced necrosis and wilting tolerance, and accounted for 41% of the phenotypic variation. A number of QTLs with smaller effects were also detected on eight rice chromosomes.     

Mapping of quantitative trait loci for salt tolerance at the seedling stage in rice

Salt tolerance was evaluated at the young seedling stage of rice (Oryza sativa L.) using recombinant inbred lines (MG RILs) from a cross between Milyang 23 (japonica/indica) and Gihobyeo (japonica). 22 of 164 MG RILs were classified as tolerant with visual scores of 3.5-5.0 in 0.7% NaCl. Interval mapping of QTLs related to salt tolerance was conducted on the basis of the visual scores at the young seedling stage. Two QTLs, qST1 and qST3, conferring salt tolerance, were detected on chromosome 1 and 3, respectively, and the total phenotypic variance explained by the two QTLs was 36.9% in the MG RIL population. qST1 was the major QTL explaining 27.8% of the total phenotypic variation. qST1 was flanked by Est12-RZ569A, and qST3 was flanked by RG179-RZ596. The detection of new QTLs associated with salt tolerance will provide important information for the functional analysis of rice salt tolerance.     

Mapping of genes controlling aluminum tolerance in rice: comparison of different genetic backgrounds

Aluminum toxicity is the main factor limiting the productivity of crop plants in acid soils, particularly in the tropics and subtropics. In this study, a doubled-haploid population derived from the rice ( Oryza sativa L.) breeding lines CT9993 and IR62266 was used to map genes controlling Al tolerance. A genetic linkage map consisting of 280 DNA markers (RFLP, AFLP and SSR) was constructed to determine the position and nature of quantitative trait loci (QTLs) affecting Al tolerance. Three characters - control root length (CRL), Al-stressed root length (SRL) and root length ratio (RR) - were evaluated for the DH lines and the parents at the seedling stage in nutrient solution. A total of 20 QTLs controlling root growth under Al stress and control conditions were detected and distributed over 10 of the 12 rice chromosomes, reflecting multigenic control of these traits. The two QTLs of largest effect, qALRR-1-1 and qALRR-8 for root length ratio (a measurement of Al tolerance) were localized on chromosomes 1 and 8, respectively. Three other QTLs in addition to qALRR-8 were apparently unique in the CT9993 x IR62266 mapping population, which may explain the high level of Al tolerance in CT9993. Comparative mapping identified a conserved genomic region on chromosome 1 associated with Al tolerance across three rice genetic backgrounds. This region provides an important starting point for isolating genes responsible for different mechanisms of aluminum tolerance and understanding the genetic nature of this trait in rice and other cereals.     

Identification of quantitative trait loci associated with salt tolerance at seedling stage from Oryza rufipogon

Soil salinity is one of the major abiotic stresses affecting plant growth and crop production.In the present study,salt tolerance at rice seedling stage was evaluated using 87 introgression lines (ILs),which were derived from a cross between an elite indica cultivar Teqing and an accession of common wild rice (Oryza rufipogon Griff.).Substantial variation was observed for four traits including salt tolerance score (STS),relative root dry weight (RRW),relative shoot dry weight (RSW) and relative total dry weight (RTW).STS was significantly positively correlated with all other three traits.A total of 15 putative quantitative trait loci (QTLs) associated with these four traits were detected using single-point analysis,which were located on chromosomes 1,2,3,6,7,9 and 10 with 8％-26％ explaining the phenotypic variance.The O.rufipogon-derived alleles at 13 QTLs (86.7％) could improve the salt tolerance in the Teqing background.Four QTL clusters affecting RRW,RSW and RTW were found on chromosomes 6,7,9 and 10,respectively.Among these four QTL clusters,a major cluster including three QTLs (qRRW10,qRSW10 and qRTW10) was found near the maker RM271 on the long arm of chromosome 10,and the O.rufipogon-derived alleles at these three loci increased RRW,RSW and RTW with additive effects of 22.7％,17.3％ and 18.5％,respectively,while the phenotypic variance explained by these three individual QTLs for the three traits varied from 19％ to 26％.In addition,several salt tolerant ILs were selected and could be used for identifying and utilizing favorable salt tolerant genes from common wild rice and used in the salt tolerant rice breeding program.     

QTL studies reveal little relevance of chilling-related seedling traits for yield in maize

Prolonged low temperature phases and short-term cold spells often occur in spring during the crucial stages of early maize (Zea mays L.) development. The effect of low temperature-induced growth retardation at the seedling stage on final yield is poorly studied. Therefore, the aim was to identify genomic regions associated with morpho-physiological traits at flowering and harvest stage and their relationship to previously identified quantitative trait loci (QTLs) for photosynthesis and morpho-physiological traits from the same plants at seedling stage. Flowering time, plant height and shoot biomass components at harvest were measured in a dent mapping population for cold tolerance studies, which was sown in the Swiss Midlands in early and late spring in two consecutive years. Early-sown plants exhibited chilling stress during seedling stage, whereas late-sown plants grew under favorable conditions. Significant QTLs, which were stable across environments, were found for plant height and for the time of flowering. The QTLs for flowering were frequently co-localized with QTLs for plant height or ear dry weight. The comparison with QTLs detected at seedling stage revealed only few common QTLs. A pleiotropic effect was found on chromosome 3 which revealed that a good photosynthetic performance of the seedling under warm conditions had a beneficial effect on plant height and partially on biomass at harvest. However, a high chilling tolerance of the seedling seemingly had an insignificant or small negative effect on the yield.