Detection of quantitative trait loci (QTLs) for seedling traits and drought tolerance in wheat using three related recombinant inbred line (RIL) populations

In order to detect quantitative trait loci (QTLs) for drought tolerance in wheat during seed germination conditional and unconditional QTL analyses of eight seedling traits were conducted under two water regimes using three related F₉ recombinant inbred line populations with a common female parent. A total of 87 QTLs for the eight seedlings traits and 34 specific QTLs related to drought tolerance were detected. Seventy-one of these QTLs were major QTLs with contributions to phenotypic variance of >10 %. Of the 34 QTLs related to drought tolerance only eight were also detected by unconditional analysis of seedling traits under osmotic stress conditions indicating that most of the QTLs related to drought tolerance could not be detected by unconditional QTL analysis. Therefore, conditional QTL analysis of stress-tolerance traits such as drought tolerance was feasible and effective. Of 11 important QTL clusters located on chromosomes 1BL, 1D, 2A, 2B, 2D, 4A, 6B, and 7B, nine were detected in multiple populations and eight were detected by both unconditional and conditional analyses.     

Mapping QTLs in breeding for drought tolerance in maize (Zea mays L.)

Summary Grain yield in the maize (Zea mays L) plant is sensitive to drought in the period three weeks either side of flowering. Maize is well-adapted to the use of restriction fragment length polymorphisms (RFLPs) to identify a tight linkage between gene(s) controlling the quantitative trait and a molecular marker. We have determined the chromosomal locations of quantitative trait loci (QTLs) affecting grain yield under drought, anthesis-silking interval, and number of ears per plant. The F₃ families derived from the cross SD34(tolerant) × SD35 (intolerant) were evaluated for these traits in a two replicated experiment. RFLP analysis of the maize genome included non-radioactive DNA-DNA hybridization detection using chemiluminescence. To identify QTLs underlying tolerance to drought, the mean phenotypic performances of F₃ families were compared based on genotypic classification at each of 70 RFLP marker loci. The genetic linkage map assembled from these markers was in good agreement with previously published maps. The phenotypic correlations between yield and other traits were highly significant. In the combined analyses, genomic regions significantly affecting tolerance to drought were found on chromosomes 1,3,5,6, and 8. For yield, a total of 50% of the phenotypic variance could be explained by five putative QTLs. Different types of gene action were found for the putative QTLs for the three traits.     

Identification of quantitative trait loci associated with drought tolerance traits in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) under PEG and field drought stress

Two recombinant inbred line F₁₀ rice populations (IAPAR-9/Akihikari and IAPAR-9/Liaoyan241) were used to identify quantitative trait loci (QTLs) for ten drought tolerance traits at the budding and early seedling stage under polyethylene glycol-induced drought stress, and two traits of leaf rolling index (LRI) and leaf withering degree (LWD) under field drought stress. The results showed that the drought-tolerance capacity of IAPAR-9 was stronger than that of Akihikari and Liaoyan241. Thirty-four QTLs for 12 drought tolerance traits were detected, and among them, in the IAPAR-9/Akihikari population, qLRI9-1 and qLRI10-1 for LRI were repeatedly detected in RM3600-RM553 on chromosome 9 and in RM6100-RM3773 on chromosome 10, respectively, at two times points of July 31 and August 13 in 2014. The two QTLs are stable against the environmental impact, and qLRI9-1 and qLRI10-1 explained 6.77–13.66% and 5.01–8.32% of the phenotypic variance, respectively, at the two times points. qLWD9-2 for LWD in the IAPAR-9/Liaoyan241 population contributed 8.73% of variation was detected in the same marker interval with the qLRI9-1, and qLRI1-1 for LRI and qLWD1-1 for LWD were located in the same marker interval RM11054-RM5646 on chromosome 1, which contributed 18.82 and 5.78% of phenotype variation respectively. qGV3 for germination vigor and qRGV3 for relative germination vigor at the budding stage were detected in the same marker interval RM426-RM570 on chromosome 3, which explained 14.98 and 16.30% of the observed phenotypic variation respectively, representing major QTLs. The above-mentioned stable or major QTLs regions could be useful for molecular marker assisted selection breeding, fine mapping, and cloning.     

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 %).     

向日葵高密度遗传连锁图谱构建及两种水分条件下芽期性状的QTL分析

干旱胁迫对向日葵发芽出苗有重要影响。以K55×K58组合衍生的187个F6重组自交系为材料,利用SSR、SRAP、AFLP标记构建向日葵高密度遗传连锁图谱,设置正常水分(CK)和模拟干旱(18%聚乙二醇PEG-6000)两种水分条件,调查9个芽期数量性状,PCR扩增株系,构建一张包含17个连锁群、1105个标记(368个SSR、368个SRAP和369个AFLP)的高密度遗传连锁图谱。该图谱覆盖基因组长度3846.0 c M,平均图距3.48 c M,连锁群长度147.6~295.5 c M,每个连锁群标记数10~165个。两种条件下检测到33个QTL,其中干旱条件下检测到发芽指数、发芽率、胚芽长、胚根长、胚芽鲜重和胚根鲜重6个性状的14个QTL,可解释6.1%~14.0%的表型变异;正常水分(CK)条件下检测到发芽势、胚根长、胚芽鲜重、胚根鲜重、胚根干重和胚芽干重6个性状的19个QTL,可解释6.1%~25.8%的表型变异。两种水分条件下检测到Qefw5-1、Qefw5-2、Qefw5-4、Qrfw5、Qrfw10和Qrl9共6个QTL的遗传贡献率超过10%,此外,还检测到9个影响干旱胁迫与正常水分条件下性状差值的QTL,可能对抗旱性有直接贡献。这些QTL可为向日葵芽期抗旱分子设计育种研究提供重要参考。     

Identification of Quantitative Trait Loci Associated with Aluminum Tolerance in Rice (Oryza Sativa L.)

Summary Quantitative trait loci (QTL) analysis for Al tolerance was performed in rice using a mapping population of 98 BC₁F₁₀ lines (backcross inbred lines: BILs), derived from a cross of Al-tolerant cultivar of rice (Oryza sativa L. cv. Nipponbare) and Al-sensitive cultivar (cv. Kasalath). Three characters related to Al tolerance, including root elongation under non-stress conditions (CRE), root elongation under Al stress (SRE) and the relative root elongation (RRE) under Al stress versus non-stress conditions, were evaluated for the BILs and the parents at seedling stage. A total of seven QTLs for the three traits were identified. Among them, three putative QTLs for CRE (qCRE-6, qCRE-8 and qCRE-9) were mapped on chromosomes 6, 8 and 9, respectively. One QTL for SRE (qSRE-4) was identified on chromosome 4. Three QTLs (qRRE-5, qRRE-9 and qRRE-10) for RRE were detected on chromosomes 5, 9, 10 and accounted for 9.7–11.8% of total phenotypic variation. Interestingly, the QTL qRRE-5 appears to be syntenic with the genomic region carrying a major Al tolerance gene on chromosome 6 of maize. Another QTL, qRRE-9, appears to be similar among different rice populations, while qRRE-10 is unique in the BIL population. The common QTLs for CRE and RRE indicate that candidate genes conferring Al tolerance in the rice chromosome 9 may be associated with root growth rates. The existence of QTLs for Al tolerance was confirmed in substitution lines for corresponding chromosomal segments. These results also provide the possibilities of enhancing Al tolerance in rice through using marker-assisted selection (MAS) and pyramiding QTLs.     

Mapping QTLs for seedling root traits in a doubled haploid wheat population under different water regimes

A deep and thick root system has a positive effect on wheat yield, particularly in drought environments. A doubled haploid (DH) population of 150 lines derived from the cross Hanxuan 10?×?Lumai 14 was used to map QTLs for seedling root characteristics. The DH lines were cultivated in an agarose gel-chamber under well-watered (WW) and water-stressed (WS) regimes. Water stress was simulated by adding mannitol to the agarose gel. The seminal root traits, including maximum root length (MRL), seminal root number, total root length, project root area, root surface area, and seminal root angle were measured after 6?days of seedling development. Grain yields (GY) were measured in a field experiment. A total of 29 QTLs were identified for seedlings cultured under WW regimes, and 23 QTLs under WS regimes. Individual QTL accounted for phenotypic variations ranging from 4.98 to 24.31?%. The QTLs were distributed on 17 chromosomes, except 1D, 4D, 6B and 6D. Seven consistently expressed QTLs were detected for all the traits tested except MRL under both water regimes. The QTLs for root traits were unevenly distributed among chromosomes, and clustered in eight loci on seven chromosomes, showing pleiotropic effects on target traits. One region in the interval Xgwm644.2?CP6901.2 on chromosome 3B contained 9 QTLs affecting most root traits. The present data provide an insight into the genetic basis of seedling root development under different water regimes and may benefit breeding programs using marker-assisted selection (MAS) for root traits.     

QTL analysis for thousand-grain weight under terminal drought stress in bread wheat (<Emphasis Type="Italic">Triticum</Emphasis><Emphasis Type="Italic">aestivum</Emphasis> L.)

Grain yield under post-anthesis drought stress is one of the most complex traits, which is inherited quantitatively. The present study was conducted to identify genes determining post-anthesis drought stress tolerance in bread wheat through Quantitative Trait Loci (QTLs) analysis. Two cultivated bread wheat accessions were selected as parental lines. Population phenotyping was carried out on 133 F_2:3 families. Two field experiments and two experiments in the greenhouse were conducted at IPK-Gatersleben, Germany with control and post-anthesis stress conditions in each experiment. Thousand-grain weight was recorded as the main wheat yield component, which is reduced by post-anthesis drought stress. Chemical desiccation was applied in three experiments as simulator of post-anthesis drought stress whereas water stress was applied in one greenhouse experiment. Analysis of variance showed significant differences among the F_2:3 families. The molecular genetic linkage map including 293 marker loci associated to 19 wheat chromosomes was applied for QTL analysis. The present study revealed four and six QTLs for thousand-grain weight under control and stress conditions, respectively. Only one QTL on chromosome 4BL was common for both conditions. Five QTLs on chromosomes 1AL, 4AL, 7AS, and 7DS were found to be specific to the stress condition. Both parents contributed alleles for drought tolerance. Taking the known reciprocal translocation of chromosomes 4AL/7BS into account, the importance of the short arms of homoeologous group 7 is confirmed for drought stress.     

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.     

Further QTL mapping for yield component traits using introgression lines in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) under drought field environments

To better understand the underlying mechanisms of agronomic traits related to drought resistance and discover candidate genes or chromosome segments for drought-tolerant rice breeding, a fundamental introgression population, BC₃, derived from the backcross of local upland rice cv. Haogelao (donor parent) and super yield lowland rice cv. Shennong265 (recurrent parent) had been constructed before 2006. Previous quantitative trait locus (QTL) mapping results using 180 and 94 BC₃F_6,7 rice introgression lines (ILs) with 187 and 130 simple sequence repeat (SSR) markers for agronomy and physiology traits under drought in the field have been reported in 2009 and 2012, respectively. In this report, we conducted further QTL mapping for grain yield component traits under water-stressed (WS) and well-watered (WW) field conditions during 3 years (2012, 2013 and 2014). We used 62 SSR markers, 41 of which were newly screened, and 492 BC₄F_2,4 core lines derived from the fourth backcross between D123, an elite drought-tolerant IL (BC₃F₇), and Shennong265. Under WS conditions, a total of 19 QTLs were detected, all of which were associated with the new SSRs. Each QTL was only identified in 1 year and one site except for qPL-12-1 and qPL-5, which additively increased panicle length under drought stress. qPL-12-1 was detected in 2013 between new marker RM1337 and old marker RM3455 (34.39 cM) and was a major QTL with high reliability and 15.36% phenotypic variance. qPL-5 was a minor QTL detected in 2013 and 2014 between new marker RM5693 and old marker RM3476. Two QTLs for plant height (qPHL-3-1 and qPHP-12) were detected under both WS and WW conditions in 1 year and one site. qPHL-3-1, a major QTL from Shennong265 for decreasing plant height of leaf located on chromosome 3 between two new markers, explained 22.57% of phenotypic variation with high reliability under WS conditions. On the contrary, qPHP-12 was a minor QTL for increasing plant height of panicle from Haogelao on chromosome 12. Except for these two QTLs, all other 17 QTLs mapped under WS conditions were not mapped under WW conditions; thus, they were all related to drought tolerance. Thirteen QTLs mapped from Haogelao under WS conditions showed improved drought tolerance. However, a major QTL for delayed heading date from Shennong265, qDHD-12, enhanced drought tolerance, was located on chromosome 12 between new marker RM1337 and old marker RM3455 (11.11 cM), explained 21.84% of phenotypic variance and showed a negative additive effect (shortening delay days under WS compared with WW). Importantly, chromosome 12 was enriched with seven QTLs, five of which, including major qDHD-12, congregated near new marker RM1337. In addition, four of the seven QTLs improved drought resistance and were located between RM1337 and RM3455, including three minor QTLs from Haogelao for thousand kernel weight, tiller number and panicle length, respectively, and the major QTL qDHD-12 from Shennong265. These results strongly suggested that the newly screened RM1337 marker may be used for marker-assisted selection (MAS) in drought-tolerant rice breeding and that there is a pleiotropic gene or cluster of genes linked to drought tolerance. Another major QTL (qTKW-1-2) for increasing thousand kernel weight from Haogelao was also identified under WW conditions. These results are helpful for MAS in rice breeding and drought-resistant gene cloning.     

大豆耐旱选择群体QTL定位

以红丰11为轮回亲本、Clark为供体亲本构建回交群体进行耐旱性鉴定,对获得选择群体进行全基因组SSR标记扫描,计算供体基因型导入频率,利用卡方测验检测偏分离SSR位点,并结合GGT软件对各连锁群分析, 对5个耐旱相关性状进行QTL定位。以卡方测验检测到23个SSR偏分离位点(超导入),分布于10条连锁群。方差分析表明,8个叶片持水能力QTL分布于A₁、B₁、C₂、E、L和N连锁群;9个根长QTL分布于C₂、F、G和I连锁群;11个根干重QTL分布于A₂、B₁、B₂、E、F、K、L、M和O连锁群;12个产量QTL分布于B₁、D₁a、E、F、G、I、L、M和O连锁群;7个生物量QTL分布于E、F、G、K、L和N连锁群。在E连锁群的Sat_136位点,对于叶片持水能力、根干重、产量和生物量具有一致性;在F连锁群的GMRUBP位点,对于根干重和生物量具有一致性,Satt586位点,对于根长、根干重和产量具有一致性;在K连锁群的Satt167位点,对于根干重和生物量具有一致性,SOYPRP1位点,对于根长和生物量具有一致性;在L连锁群的Satt398位点,对于根长和产量具有一致性,Satt694位点对于叶片持水能力和生物量具有一致性;在M连锁群的GMSL514位点,对于根干重和产量具有一致性;以上位点均与卡方测验检测到的“超导入”位点具有一致性。经过供体等位基因卡方测验和耐旱QTL定位,共检测到33个QTL,其中有17个同时被检测到。这些位点可能是控制大豆耐旱性的重要位点。     

碱胁迫下粳稻幼苗前期耐碱性的数量性状基因座检测

以粳粳交“高产106/长白9号”F_2:3代200个家系为作图群体, 在0.15% Na₂CO₃溶液的碱性胁迫下, 进行了水稻耐碱性鉴定, 并以SSR标记构建的分子连锁图谱为基础, 对水稻幼苗前期的根数、根长和苗高及其相对碱害率进行了数量性状基因座(QTLs)的检测。结果表明, 上述性状在F₃家系群中均表现为具有1~2个峰的连续分布, 认为由主效基因和微效基因共同控制的数量性状。共检测到与碱胁迫下幼苗前期根数、根长和苗高及其相对碱害率相关的QTL 26个, 分布于第1、5、6、7、8、9和11染色体上。其中, 碱胁迫下与根数相关的QTL 4个, qRN6-1和qRN11对表型变异的解释率较大, 分别为29.91%和13.42%;与根数相对碱害率相关的QTL 5个, qRRN11-2对表型变异的解释率较大, 为23.86%;与根长相关的QTL 6个, qRRL11-2对表型变异的解释率较大, 为21.06%;与根长相对碱害率相关的QTL 2个, 但对表型变异的解释率均较低;与苗高相关的QTL 5个, qSH1和qSH11-2对表型变异的解释率较大, 分别为15.81%和16.53%;与苗高相对碱害率相关的QTL 4个, qRSH5和qRSH6-2对表型变异的解释率分别为29.89%和34.63%。而这些解释率较大的QTL所处的标记区间距离, 除qRN6-1相对较小(19.0 cM)外, 其余QTL的标记区间距离均大于26.3 cM, 需作进一步的精细定位。在所检测到的QTL中, 13个QTL的增效等位基因均来自耐碱亲本长白9号, 而其余QTL的增效等位基因来自敏碱亲本高产106;基因的主要作用方式为超显性或部分显性。     

Fine mapping of major QTLs for alkaline tolerance at the seedling stage in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.) through genetic linkage analysis combined with high-throughput DNA sequencing

Exploiting genes and quantitative trait loci (QTLs) related to maize (Zea mays L.) alkaline tolerance is helpful for improving alkaline resistance. To explore the inheritance of maize alkaline tolerance at the seedling stage, a mapping population comprising 151 F_2:3 lines derived from the maize cross between Zheng58, tolerant to alkaline, and Chang7-2, sensitive to alkaline, was used to establish a genetic linkage map with 200 SSR loci across the 10 maize linkage groups, with an average interval of 6.5 cM between adjacent markers. QTLs for alkaline resistant traits of alkaline tolerance rating (ATR), germination rate (GR), relative conductivity (RC), weight per plant (WPP) and proline content (PC) were detected. The obtained results were as follows: Five QTLs on chromosomes 2, 5 and 6 (GR and WPP: chr. 2; PC and ATR: chr. 5; and RC: chr. 6) were mapped. For precise mapping of the QTLs related to alkaline resistance, two bulked deoxyribonucleic acid (DNA) pools were constructed using individual DNAs from the most tolerant 30 F₂ individuals and the most sensitive 30 F₂ individuals according to the ATR and used to establish a high density map of SLAF markers strongly associated with the ATR by specific locus amplified fragment sequencing (SLAF-Seq) combined with super bulked segregant analysis (superBSA). One marker-intensive region involved three SLAFs at 296,000–6,203,000 bp on chromosome 5 that were closely related to the ATR. Combined with preliminary QTL mapping with superBSA, two major QTLs on chromosome 5 associated with alkaline tolerance at the maize seedling stage were mapped to marker intervals of dCap-SLAF31521 and dCap-SLAF31535 and phi024 and dCap-SLAF31521, respectively. These QTL regions involved 9 and 75 annotated genes, respectively. These results will be helpful for improving maize alkaline tolerance at the seedling stage by marker-assisted selection programs and will be useful for fine mapping QTLs for maize breeding.     

Quantitative trait locus mapping of drought and salt tolerance in an introgressed recombinant inbred line population of Upland cotton under the greenhouse and field conditions

Drought and salt tolerances are complex traits and controlled by multiple genes, environmental factors and their interactions. Drought and salt stresses can result in more than 50% yield loss in Upland cotton (Gossypium hirsutum L.). G. barbadense L. (the source of Pima cotton) carries desirable traits such as tolerance to abiotic and biotic stress along with high fiber quality. However, few studies have been reported on mapping quantitative trait loci (QTL) for abiotic stress tolerance using a permanent bi-parental population in multiple tests. The transfer of drought and salt tolerance from Pima to Upland cotton has been a challenge due to interspecific hybrid breakdown. This issue may be overcome by using introgression lines with genes transferred from Pima to Upland cotton. In this study, four replicated tests were conducted in the greenhouse each for drought and salt tolerance along with another test conducted in a field for drought tolerance using an Upland recombinant inbred line population of TM-1/NM24016 that has a stable introgression from Pima cotton. The objectives of the study were to investigate the genetic basis of drought and salt tolerance and to identify genetic markers associated with the abiotic stress tolerance. A total of 1004 polymorphic DNA marker loci including RGA-AFLP, SSR and GBS-SNP markers were used to construct a genetic map spanning 2221.28 cM. This population together with its two parents was evaluated for morphological, physiological, yield and fiber quality traits. The results showed that drought under greenhouse and field conditions and salt stress in the greenhouse reduced cotton plant growth at the seedling stage, and decreased lint yield and fiber quality traits in the field. A total of 165 QTL for salt and drought tolerance were detected on most of the cotton chromosomes, each explaining 5.98–21.43% of the phenotypic variation. Among these, common QTL for salt and drought tolerance were detected under both the greenhouse and field conditions. This study represents the first study to report consistent abiotic stress tolerance QTL from multiple tests in the greenhouse and the field that will be useful to understand the genetic basis of drought and salt tolerance and to breeding for abiotic stress tolerance using molecular marker-assisted selection in cotton.     

QTLs for chlorophyll and chlorophyll fluorescence parameters in barley under post-flowering drought

Drought is one of the major factors limiting barley yields in many developing countries worldwide. The identification of molecular markers linked to genes controlling drought tolerance in barley is one way to improve breeding efficiency. In this study, we analyzed the quantitative trait loci (QTL) controlling chlorophyll content and chlorophyll fluorescence in 194 recombinant inbred lines (RILs) developed from the cross between the cultivar ‘Arta’ and Hordeum spontaneum 41-1. Five traits, chlorophyll content, and four chlorophyll fluorescence parameters, namely initial fluorescence (F_o), maximum fluorescence (F_m), variable fluorescence (F_v), and maximum quantum efficiency of PSII (F_v/F_m) which are related to the activity of the photosynthetic apparatus, were measured under well-watered and drought stress conditions at post-flowering stage. QTL analysis identified a total of nine and five genomic regions, under well-watered and drought stress conditions, respectively, that were significantly associated with the expression of the five target traits at post-flowering stage. No common QTL was detected except one for chlorophyll content, which was identified in both growth conditions, demonstrating that the genetic control of the expression of the traits related to photosynthesis differed under different water conditions. A QTL for F_v/F_m, which is related to the drought tolerance of photosynthesis was identified on chromosome 2H at 116 cM in the linkage map under drought stress. This QTL alone explained more than 15% of phenotypic variance of maximum quantum yield of PSII, and was also associated with the expression of four other traits. In addition, another QTL for F_v/F_m was also located on the same chromosome (2H) but at 135.7 cM explaining around 9% of the phenotypic variance under drought conditions. The result presented here suggest that two major loci, located on chromosome 2H, are involved in the development of functional chloroplast at post-flowering stage for drought tolerance of photosynthesis in barley under drought stress. If validated in other populations, chlorophyll fluorescence parameters could be used as selection criteria for drought tolerance.     

小麦燕大1817×北农6号重组自交系群体在正常和盐胁迫水培条件下苗期性状的QTL定位

小麦苗期性状能够指示品种的耐盐性。本研究以小麦骨干亲本燕大1817与品系北农6号衍生的230个重组自交系为材料,利用2013年3个不同时间的水培试验数据和已经构建的SSR和SNP高密度遗传连锁图谱分别对正常和盐胁迫条件下根数和最长根长等7个苗期性状进行QTL定位。利用完备复合区间作图法(ICIM)共检测到69个加性效应QTL(LOD≥2.5),分布于除1A染色体外的所有20条染色体上,单个QTL解释的表型变异率为2.70%~19.00%。有46个QTL的增效效应来自于燕大1817,有23个QTL的增效效应来自于北农6号。有12个QTL能够在3个或3个以上的环境中被检测到,在燕大1817中定位到稳定的多分蘖主效QTL QTn.cau-7BS.1和盐胁迫条件下特异表达的根数QTL QRn.cau-2A,解析了小麦骨干亲本燕大1817的繁茂性和抗逆性遗传基础,为解析小麦品种耐盐遗传机制和耐盐性的分子标记辅助选择提供了重要信息。     

Quantitative analysis and QTL mapping for agronomic and fiber traits in an RI population of upland cotton

Genetic mapping is an essential tool for cotton (Gossypium hirsutum L.) molecular breeding and application of DNA markers for cotton improvement. In this present study, we evaluated an RI population including 188 RI lines developed from 94 F₂-derived families and their two parental lines, ‘HS 46’ and ‘MARCABUCAG8US-1-88’, at Mississippi State, MS, for two years. Fourteen agronomic and fiber traits were measured. One hundred forty one (141) polymorphic SSR markers were screened for this population and 125 markers were used to construct a linkage map. Twenty six linkage groups were constructed, covering 125 SSR loci and 965 cM of overall map distance. Twenty four linkage groups (115 SSR loci) were assigned to specific chromosomes. Quantitative genetic analysis showed that the genotypic effects accounted for more than 20% of the phenotypic variation for all traits except fiber perimeter (18%). Fifty six QTLs (LOD > 3.0) associated with 14 agronomic and fiber traits were located on 17 chromosomes. One QTL associated with fiber elongation was located on linkage group LGU01. Nine chromosomes in sub-A genome harbored 27 QTLs with 10 associated with agronomic traits and 17 with fiber traits. Eight chromosomes in D sub-genome harbored 29 QTLs with 13 associated with agronomic traits and 16 with fiber traits. Chromosomes 3, 5, 12, 13, 14, 16, 20, and 26 harbor important QTLs for both yield and fiber quality compared to other chromosomes. Since this RI population was developed from an intraspecific cross within upland cotton, these QTLs should be useful for marker assisted selection for improving breeding efficiency in cotton line development. Paper number J1116 of the Mississippi Agricultural and Forestry Experiment Station, Mississippi State University, Mississippi State, MS 39762. Mention of trademark, proprietary product, or vendor does not constitute a guarantee or warranty of the product by USDA, ARS and does not imply its approval to the exclusion of other products or vendors that may also be suitable.     

Identification of QTLs for rice grain size and shape of Iranian cultivars using SSR markers

Grain size is a main component of rice appearance quality. In this study, we performed the SSR mapping of quantitative trait loci (QTLs) controlling grain size (grain length and breadth) and shape (length/breadth ratio) using an F₂ population of a cross between two Iranian cultivars, Domsephid and Gerdeh, comprising of 192 individuals. A linkage map with 88 markers was constructed, which covered 1367.9 cM of the rice genome with an average distance of 18 cM between markers. Interval mapping procedure was used to identify the QTLs controlling three grain traits, and QTLs detected were further confirmed using composite interval mapping. A total of 11 intervals carrying 18 QTLs for three traits were identifed, that included five QTLs for grain length, seven QTLs for grain breadth, and six QTLs for grain shape. A major QTL for grain length was detected on chromosome 3, that explained 19.3% of the phenotypic variation. Two major QTLs for grain breadth were mapped on chromosomes 3 and 8, which explained 34.1% and 20% of the phenotypic variation, respectively. Another two major QTLs were identified for grain shape on chromosomes 3 and 8, which accounted for 27.1% and 20.5% of the phenotypic variance, respectively. The two QTLs that were mapped for grain shape coincided with the major QTLs detected for grain length and grain breadth. Intrestingly, gs2 QTL specific to grain shape was detected on chromosome 2 that explained 15% of the phenotypic variation.     

利用抗旱选择导入系定位向日葵产量性状QTL

干旱是造成向日葵减产的最主要因素之一。利用综合性状优良的自交系K55作为轮回亲本与抗旱自交系K58杂交构建回交导入系, 在干旱条件下进行单株产量筛选, 得到45个BC₃F₂抗旱定向选择导入系。通过全基因组SSR及SNP标记扫描, 以方差分析和基于遗传搭车原理的卡方检验对呼和浩特市及武川县两点、两种水分条件下的5个产量性状进行QTL检测。方差分析检测到的QTL根据不同环境下的表达情况分为三类, 第一类在两种水分条件下稳定表达, 包括武川的4个百粒重QTL及呼和浩特的2个单株产量QTL、3个单株实粒数QTL, 这些QTL可能对向日葵抗旱性有直接贡献; 第二类受干旱胁迫表达, 包括呼和浩特的30个和武川的27个; 第三类仅在正常供水条件下被检测到, 包括呼和浩特的38个和武川的64个。卡方检验检测到极显著位点274个。用两种方法共检测到一致性位点14个, 可能是与向日葵抗旱性相关的关键位点。本研究结果可为向日葵高效抗旱分子育种奠定基础并提供相关材料。     

Mapping quantitative trait loci for yield-related traits in soybean (Glycine max L.)

Development of soybean cultivars with high seed yield is a major focus in soybean breeding programs. This study was conducted to identify genetic loci associated with seed yield-related traits in soybean and also to clarify consistency of the detected QTLs with QTLs found by previous researchers. A population of 135 F_2:3 lines was developed from a cross between a vegetable soybean line (MJ0004-6) and a landrace cultivar from Myanmar ({"type":"entrez-nucleotide","attrs":{"text":"R18500","term_id":"772110","term_text":"R18500"}}R18500). They were evaluated in the experimental field of Kasetsart University, Kamphaeng Saen, Nakhon Pathom, Thailand in a randomized complete block design with two replications each in 2011 and 2012 growing seasons. The two parents exhibited contrasting characteristics for most of the traits that were mapped. Analysis of variance showed that the main effects of genotype and environment (year) were significant for all studied traits. Genotype by environment interaction was also highly significant for all the traits. The population was genotyped by 149 polymorphic SSR markers and the genetic map consisted of 129 SSR loci which converged into 38 linkage groups covering 1156 cM of soybean genome. There were 10 QTLs significantly associated with seed yield-related traits across two seasons with single QTLs explaining between 5.0% to 21.9% of the phenotypic variation. Three of these QTLs were detected in both years for days to flowering, days to maturity and 100 seed weight. Most of the detected QTLs in our research were consistent with earlier QTLs reported by previous researchers. However, four novel QTLs including SF1, SF2 and SF3 on linkage groups L and N for seed filling period and PN1 on linkage group D1b for pod number were identified in the present study.