Detection of QTLs for salt tolerance in Asian barley (Hordeum vulgare L.) by association analysis with SNP markers

Two hundred ninety-six Asian barley (Hordeum vulgare L.) accessions were assessed to detect QTLs underlying salt tolerance by association analysis using a 384 single nucleotide polymorphism (SNP) marker system. The experiment was laid out at the seedling stage in a hydroponic solution under control and 250 mM NaCl solution with three replications of four plants each. Salt tolerance was assessed by leaf injury score (LIS) and salt tolerance indices (STIs) of the number of leaves (NL), shoot length (SL), root length (RL), shoot dry weight (SDW) and root dry weight (RDW). LIS was scored from 1 to 5 according to the severity of necrosis and chlorosis observed on leaves. There was a wide variation in salt tolerance among Asian barley accessions. LIS and STI (SDW) were the most suitable traits for screening salt tolerance. Association was estimated between markers and traits to detect QTLs for LIS and STI (SDW). Seven significant QTLs were located on chromosomes 1H (2 QTLs), 2H (2 QTLs), 3H (1 QTL), 4H (1 QTL) and 5H (1 QTL). Five QTLs were associated with LIS and 2 QTLs with STI (SDW). Two QTLs associated with LIS were newly identified on chromosomes 3H and 4H.     

Mapping of QTLs associated with cadmium tolerance and accumulation during seedling stage in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Cadmium (Cd) is a non-essential element and toxic to plants. To investigate the genetics of Cd tolerance and accumulation in rice, quantitative trait loci (QTL) associated with Cd tolerance and accumulation at the seedling stage were mapped using a doubled haploid (DH) population derived from a cross between a japonica JX17 and an indica ZYQ8. A total of 22 QTLs were found to be associated with shoot height (SH), root length (RL), shoot dry weight (SDW), root dry weight (RDW), total dry weight (TDW) and chlorophyll content (CC), and 10 and 12 QTLs were identified under the control and Cd stress conditions, respectively. For Cd tolerant coefficient (CTC), 6 QTLs were detected on chromosomes 1, 3, 5, 8 and 10. Under Cd stress, 3 QTLs controlling root and shoot Cd concentrations were mapped on chromosome 6 and 7. One QTL for shoot/root rate of Cd concentration was identified on chromosome 3. The results indicated that Cd tolerance and accumulation were quantitatively inherited, and the detected QTLs may be useful for marker-assistant selection (MAS) and identification of the genes controlling Cd tolerance and accumulation in rice.     

利用重组自交群体检测水稻抗亚铁毒胁迫的QTLs

潜育性水稻田广泛分布于中国、斯里兰卡、印度、印度尼西亚、塞拉里昂、利比亚、尼日利亚、哥伦比亚和菲律宾等国，其中我国南方稻区就有670万公顷低产潜育性水稻田。该类水稻田还原性强，矿质营养失调，尤以Fe2+ 过量积累，对水稻生长发育产生不良的逆境胁迫作用。培育抗亚铁毒的水稻品种是简便、经济有效地提高稻谷产量的重     

QTL mapping for seedling traits under different nitrogen forms in wheat

The uptake and utilization of nitrogen (N) by plants are affected by the different forms of N in the soil. In this study, eight morphological traits at the seedling stage were investigated using a set of recombinant inbred lines (RILs). Three hydroponic culture experiments were conducted using three different NO₃ ^?/NH₄ ⁺ ratios (T1 at 50/50 %, T2 at 100/0 % and T3 at 0/100 %). The investigated traits in T2 and T1 were significantly higher than T3 in all three experiments, indicating that NO₃ ^? promoted or NH₄ ⁺ suppressed the production of biomass. Comparing T1 with T2, NO₃ ^? significantly increased the values of root fresh weight (RFW), total fresh weight (TFW) and root dry weight (RDW) and significantly decreased shoot dry weight (SDW). A total of 147 quantitative trait loci (QTLs) for the eight traits were detected on 18 chromosomes (except 2A, 3D and 4D). Among them, 16 QTLs (QRfw-1A, QRfw-1D, QSfw-1D, QSfw-2B.1, QTfw-1A, QTfw-1D, QRsfw-2B, QRsfw-3B.1, QRdw-1A.1, QRdw-1A.2, QSdw-6B.1, QSdw-7A.1, QTdw-1A.1, QRsdw-1A.1, QRsdw-5A.1 and QRsdw-7A.1) were detected in more than three of the nine treatment–experiments, and most of the 16 QTLs made large contributions of approximately 15 %. Surprisingly, QRsfw-4A.1 and QRsfw-4A.2 explained as much as 47.9 and 55.5 % of the phenotypic variation, respectively. Thirteen important QTL clusters (C1-C13) with more than four QTLs and involving 66 QTLs (44.9 %) were mapped on chromosomes 1A, 1D, 2B, 2D, 4A, 4B, 5B, 5D, 6B, 7A and 7B.     

Variation in heading date conceals quantitative trait loci for other traits of importance in breeding selection of rice

To identify quantitative trait loci (QTLs) associated with the primary target traits for selection in practical rice breeding programs, backcross inbred lines (BILs) derived from crosses between temperate japonica rice cultivars Nipponbare and Koshihikari were evaluated for 50 agronomic traits at six experimental fields located throughout Japan. Thirty-three of the 50 traits were significantly correlated with heading date. Using a linkage map including 647 single-nucleotide polymorphisms (SNPs), a total of 122 QTLs for 38 traits were mapped on all rice chromosomes except chromosomes 5 and 9. Fifty-eight of the 122 QTLs were detected near the heading date QTLs Hd16 and Hd17 and the remaining 64 QTLs were found in other chromosome regions. QTL analysis of 51 BILs having homozygous for the Koshihikari chromosome segments around Hd16 and Hd17 allowed us to detect 40 QTLs associated with 27 traits; 23 of these QTLs had not been detected in the original analysis. Among the 97 QTLs for the 30 traits measured in multiple environments, the genotype-by-environment interaction was significant for 44 QTLs and not significant for 53 QTLs. These results led us to propose a new selection strategy to improve agronomic performance in temperate japonica rice cultivars.     

Mapping QTLs for salt tolerance in an introgression line population between Japonica cultivars in rice

QTL analysis of physiological traits related to salt tolerance was carried out using 117 BC₃F₅ lines derived from a cross between “Ilpumbyeo” as a recurrent parent and “Moroberekan” as a donor parent. The 117 introgression lines with the parents were evaluated for five traits; dry weight, fresh weight, leaf area, seedling height, and survival rate under control and salinity conditions (55 mM) at the seedling stage. To identify QTLs related to salt tolerance, 125 SSR markers showing polymorphisms between the parents were genotyped for the 117 BC₃F₅ lines. A total of eight QTLs were detected on chromosomes 1, 6, and 7. These include two QTLs on chromosomes 6 and 7 for reduction rate of dry weight (R² = 10.2∼13.6%), three QTLs on chromosomes 1, 6, and 7 for reduction rate of fresh weight (R² = 10.9∼13.9 %), two QTLs on chromosomes 1 and 7 for reduction rate of leaf area (R² = 12.1%), and one QTL on chromosome 7 for reduction rate of seedling height (R² = 10.5%). The Moroberekan alleles contributed the positive effect at these eight QTL loci. Although the parents, Ilpumbyeo and Moroberekan, were not salt tolerant as the salt tolerant check variety, Pokkali, some lines displayed a similar level of tolerance as Pokkali. The effect of the QTL on chromosome 7 was further confirmed by evaluating four lines containing the target QTL for fresh and dry weight, turgid weight, and relative water content (RWC). Significant differences between each line and Ilpumbyeo were detected for dry and fresh weight, and RWC values, and these results seem to indicate the beneficial effect of the Moroberekam alleles for salt tolerance. A set of introgression lines are being developed containing only few chromosomal segments from Moroberekan in the Ilpumbyeo background. These would be useful in developing salt tolerant lines in the breeding program.     

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.     

Genetics and mapping of quantitative traits for nodule number, weight, and size in soybean (Glycine max L.[Merr.])

Soybean research has found that nodule traits, especially nodule biomass, are associated with N₂ fixation ability. Two genotypes, differing in nodule number per plant and individual nodule weight, KS4895 and Jackson, were mated to create 17 F₃- and 80 F₅-derived RILs. The population was mapped with 664 informative markers with an average distance of less than 20 cM between adjacent markers. Nodule traits were evaluated in 3-year field trials. Broad-sense heritability for nodule number (no. plant^?1), individual nodule dry weight (mg nodule^?1), individual nodule size (mm nodule^?1), and total nodule dry weight (g plant^?1) was 0.41, 0.42, 0.45, and 0.27, respectively. Nodule number was negatively correlated with individual nodule weight and size. Nodule number, individual nodule weight, and size are major components which likely contributed to increased total nodule weight per plant. Composite interval mapping (CIM) identified eight QTLs for nodule number with R² values ranging from 0.14 to 0.20. Multiple interval mapping (MIM) identified two QTLs for nodule number, one of which was located close to the QTL identified with CIM. Six QTLs for individual nodule weight were detected with CIM, and one QTL was identified with MIM. For nodule size, CIM identified seven QTLs with R² values ranging from 0.14 to 0.27. Five QTLs for total nodule weight were detected with CIM, one of which was located close to a QTL identified with MIM. These results document the first QTL information on nodule traits in soybean from field experiments utilizing a dense, complete linkage map.     

Quantitative trait loci for adventitious and lateral roots in rice

The mass of a root is determined by two underlying morphogenetic factors: (1) the length of the main root axis (root axis length: RAL), and (2) the amount of lateral root development generated by a unit length of the axis (branching index: BI). The mass of a rice adventitious root was partitioned into these two factors at the quantitative trait locus (QTL) level, using ‘Akihikari’ (a lowland cultivar as a recurrent parent) × ‘IRAT 109’ (an upland cultivar) backcross inbred lines. Four QTLs were detected for the dry weight of individual adventitious roots (root dry weight: RDW), which were associated with a QTL for RAL (chromosomes 1 and 9) or a QTL for BI (chromosomes 6 and 11). For BI, an additional QTL was detected on chromosome 1. The absence of co‐located QTLs suggested that RAL and BI are under separate genetic control. Despite its small population size and few replications, this study suggests that the partitioning of root mass into these underlying components could be useful for understanding the complexity involved in the genetic control of root growth.     

Linkage map construction and QTL identification of P-deficiency tolerance in <Emphasis Type="Italic">Oryza rufipogon</Emphasis> Griff. at early seedling stage

Low phosphorus availability is a major factor limiting rice productivity. In this study, a population of backcross recombinant inbred lines (BILs) derived from an inter-specific cross (Oryza sativa L. × O. rufipogon Griff.) was used for genetic linkage map construction and quantitative trait locus (QTL) mapping. The results showed that a linkage map consisting of 153 markers was constructed. Twenty-one out of 231 BILs were tolerant of low-phosphorus according to the index to P-deficiency tolerance. Twenty-three QTLs on chromosomes 1, 2, 3, 7, 8, 9 and 11 were detected, of which eight QTLs showed high (22.93–37.32%) contribution to phenotypic variation. In addition, most of QTLs in this study (18 out of 23 QTLs) were located and overlapped on the chromosome 1, 3 and 11, which individually explained 6.07–34.70% phenotypic variation, indicating that there might be multiple main effect QTLs related to P-deficiency tolerance in O. rufipogon, and these QTLs might cluster in the same region. These results would provide helpful information for cloning and utilizing the P-deficiency tolerance-responsive genes from O. rufipogon.     

Identification of QTLs controlling quantitative characters in rice using RFLP markers

Summary Segregation of plant height (PH), tiller number (TN), panicle number (PN), average panicle length per plant (PL), average primary branch number per panicle per plant (PBN) and 1000 grain weight (1000G) were specific in an F₂ population derived from a cross of Palawan, a tall Javanica variety, and IR42, an Indica semidwarf variety. One hundred and four informative RFLP markers covering all 12 chromosomes were used for detecting putative QTLs controlling the traits. Orthogonal contrasts and interval mapping analysis were used for the analysis. QTL detected for PH on the region of chromosome 1, where semidwarfing gene sd-1 locus is located, seems to be a multiple allelic locus. An additional QTL for PH was identified on chromosome 2. Two QTLs for TN were detected on chromosomes 4 and 12. The QTL on chromosome 4 seemed also to govern the variation in PN. Four QTLs were found for the other traits, two of them for PL were located on chromosomes 6 and 2, one for PBN on chromosome 6 and the other for 1000G on chromosome 1. Additive gene actions were found to be predominant, except one QTL for PH and one QTL for PL, but partial or incomplete dominance also existed for the QTLs detected.     

QTL analysis for brown spot resistance in American rice cultivar ‘Dawn’

Rice brown spot (BS), caused by Bipolaris oryzae, causes yield loss and deterioration of grain quality. Using single-nucleotide polymorphism (SNP) markers, we conducted quantitative trait locus (QTL) analysis of BS resistance in backcross inbred lines (BILs) from a cross between an American rice cultivar, ‘Dawn’ (resistant), and ‘Koshihikari’ (susceptible). Four QTLs for BS resistance were detected in a three-year field evaluation, and ‘Dawn’ contributed the resistance alleles at all QTLs. The QTL with the greatest effect, qBSR6-kd, explained 15.1% to 20.3% of the total phenotypic variation. Although disease score and days to heading (DTH) were negatively correlated in all three years, qBSR6-kd was located near a QTL for DTH at which the ‘Dawn’ allele promoted heading. Another BS resistance QTL (qBSR3.1-kd) was unlinked to the QTLs for DTH. Therefore, these two QTLs are likely to be useful for breeding BS-resistant varieties without delaying heading. The other two BS resistance QTLs (qBSR3.2-kd and qBSR7-kd) were located near DTH QTLs at which the ‘Dawn’ alleles delayed heading. The QTLs reported here will be good candidates for developing BS-resistant cultivars.     

水稻第1染色体长臂上微效千粒重QTL qTGW1.2的验证与分解

本文报道了水稻第1染色体长臂上微效千粒重QTL qTGW1.2的验证和分解。针对前期qTGW1.2定位结果, 应用SSR标记检测, 从籼籼交组合珍汕97³/密阳46衍生的1个BC₂F_{7分离群体中, 筛选到杂合区间分别为RM11621-RM297和RM212-RM265的2个单株, 构建了两套BC2F8:9近等基因系, 将qTGW1.2进一步界定在RM212-RM265及其两侧交换区间的区域内。}在此基础上, 筛选出5个在目标区间内分离片段缩小且呈阶梯状排列的单株, 衍生了5套BC₂F₁₀分离群体, 应用Windows QTL Cartographer 2.5进行QTL分析。结果表明, 每套群体均检测到千粒重QTL, 加性效应为0.13~0.38 g, 来自密阳46的等位基因提高千粒重; 经比较各个群体的分离区间, 将qTGW1.2分解为互引连锁的2个QTL, 其中, qTGW1.2a位于RM11730和RM11762之间934 kb的区域内, 呈加性作用, qTGW1.2b位于RM11800和RM11885之间2.1 Mb的区域内, 呈正向超显性。     

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.     

利用双向回交导入系定位水稻苗期耐亚铁毒和锌毒的QTL

铁和锌是水稻生长必需的微量元素,也是重金属污染元素。在低洼或酸性土壤中,水稻容易遭受亚铁和锌毒害,抑制水稻生长,造成生物量和产量下降。为探讨水稻苗期耐亚铁毒、锌毒的遗传机制,利用优质粳稻品种Lemont和高产籼稻品种特青为亲本构建的高代双向回交导入系和308个在染色体上均匀分布的SNP标记剖析耐亚铁毒、锌毒相关的QTL。从双向导入系共检测到42个影响耐亚铁毒、锌毒相关性状如苗高、苗干重、根干重以及胁迫与对照相对值的QTL,多数位点增强亚铁毒、锌毒抗性的有利等位基因来自Lemont。其中同时在2个背景下表达的QTL有4个,占定位QTL总数的9.52%,说明大多数QTL的表达具有明显的遗传背景效应。同一遗传背景下同时影响耐亚铁毒和锌毒的QTL有9个,其中QSdw5在2个背景中均被检测到,其效应大小和方向一致,说明水稻苗期耐亚铁毒、锌毒之间存在遗传重叠位点。因此,通过分子标记辅助选择从Lemont中导入或聚合有利的遗传重叠区域,可以提高特青对亚铁毒、锌毒的抗性水平。     

Genetic regulation of growth and nutrient content under phosphorus deficiency in the wild barley introgression library S42IL

Phosphorus (P) is an important macronutrient required for plant growth and yield formation. Since decades, breeders aim to optimize P efficiency in crops. We studied a set of 47 wild barley (Hordeum vulgare ssp. spontaneum, Hsp) introgression lines (ILs) in hydroponic culture to identify quantitative trait loci (QTLs) improving growth and nutrient content under P deficiency. Applying a mixed model analysis, a total of 91 independent QTLs were located among 39 ILs, of which 64 QTLs displayed trait‐improving Hsp effects. For example, an unknown Hsp allele on barley chromosome 4H increased shoot dry weight under P deficiency in three overlapping ILs by 25.9%. Likewise, an Hsp allele on barley chromosome 6H increased root dry weight under P deficiency in two overlapping ILs by 27.6%. In total, 31 QTLs confirmed Hsp effects already identified in previous field and glasshouse experiments with the same ILs. We conclude that wild barley contains numerous trait‐improving QTL alleles, which are active under P deficiency. In future, the underlying genes can be subjected to cloning and, simultaneously, used in elite barley breeding.     

Identification of drought responsive QTLs during vegetative growth stage of rice using a saturated GBS-based SNP linkage map

Drought is a major abiotic constraint for rice production worldwide. The quantitative trait loci (QTLs) for drought tolerance traits identified in earlier studies have large confidence intervals due to low density linkage maps. Further, these studies largely focused on the above ground traits. Therefore, this study aims to identify QTLs for root and shoot traits at the vegetative growth stage using a genotyping by sequencing (GBS) based saturated SNP linkage map. A recombinant inbred line (RIL) population from a cross between Cocodrie and N-22 was evaluated for eight morphological traits under drought stress. Drought was imposed to plants grown in 75 cm long plastic pots at the vegetative growth stage. Using a saturated SNP linkage map, 14 additive QTLs were identified for root length, shoot length, fresh root mass, fresh shoot mass, number of tillers, dry root mass, dry shoot mass, and root-shoot ratio. Majority of the drought responsive QTLs were located on chromosome 1. The expression of QTLs varied under stress and irrigated condition. Shoot length QTLs qSL1.38 and qSL1.11 were congruent to dry shoot mass QTL qDSM1.38 and dry root mass QTL qDRM1.11, respectively. Analysis of genes present within QTL confidence intervals revealed many potential candidate genes such as laccase, Calvin cycle protein, serine threonine protein kinase, heat shock protein, and WRKY protein. Another important gene, Brevis radix, present in the root length QTL region, was known to modulate root growth through cell proliferation and elongation. The candidate genes and the QTL information will be helpful for marker-assisted pyramiding to improve drought tolerance in rice.     

Genotyping by sequencing of rice interspecific backcross inbred lines identifies QTLs for grain weight and grain length

Grain weight and grain length are the most stable components of rice yield and important indicators of consumer preference. Considering the potentials of wild rice and to enhance the rice yields to meet the increasing demands, 185 Backcross Inbred Lines (BILs) in the background of O. sativa ssp. indica cv. PR114, including 63 rufi-BILs derived from O. rufipogon IRGC104433 and 122 glumae-BILs from O. glumaepatula IRGC104387 were evaluated for mapping QTLs for yield and yield component traits using Genotyping by Sequencing (GBS). Phenotypic evaluation of BILs in three seasons spanning two locations revealed significant differences compared with recurrent parent. BILs which did not show significant differences for any trait under investigation, or similar based on pedigree, were excluded from GBS. Some glumae-BILs had to be excluded from mapping QTLs due to less sequence information. A custom designed approach for GBS data analysis identified 3322 informative SNPs in 55 rufi-BILs and 3437 informative SNPs in 79 glumae-BILs. QTL mapping identified one QTL for thousand grain weight (qtgw5.1), two for grain width (qgw5.1, qgw5.2) and one for grain length (qgl7.1) in rufi-BILs. In the glumae-BILs, three QTL for thousand grain weight (qtgw2.1, qtgw3.1, qtgw6.1) and two for grain length (qgl3.1, qgl7.1) were identified. Most of the grain weight and width QTL showed positive additive effect contributed by wild species allele, whereas the grain length QTL showed positive additive effect contributed by recurrent parent allele. Based on their physical position, none of the QTLs were found similar to previously cloned QTLs. QTLs for grain traits identified from low yielding wild relatives of rice reveals their significance in improving further the rice yields and widen the genetic base of cultivated rice.     

Quantitative trait loci for grain-quality traits across a rice F2 population and backcross inbred lines

Improving grain-quality is an important goal in rice breeding programs. One vital step is to find major quantitative trait loci (QTLs) for quality related traits and then investigate the relationships among them. We crossed ‘N22’, an indica variety with good appearance but low grain weight, to a japonica variety, ‘Nanjing35’, with superior grain yield but poor appearance. This enabled us to construct an F₂ population and a set of backcross inbred lines (BILs) for QTL-mapping for the traits related grain appearance. In all, 37 QTLs were identified for grain length (GL), grain width (GW), grain thickness (GT), thousand-grain weight (TGW), and the percentage of grains with chalkiness (PGWC). Of these, 17 QTLs detected from 184 plants in the F₂ population explained 4.97–27.26 % of the phenotypic variance, another 20 QTLs were identified using BILs from 2009 to 2010. Quantitative trait loci for major effects were detected in different populations and across years. A new QTL hot spot (marker interval RM504–RM520) was found on Chromosome 3, which harbored QTLs for GL, GW, GT, and TGW. Among our five examined traits, grain shape was significantly correlated with TGW and PGWC. The PGWC values of two heavier grains BILs, L93, and L145 are much lower than Nanjiing35, the analysis of genotype showed that this greater weight may due to the locus for GL occurring within RM504–RM520 on Chromosome 3. Therefore, those two lines will allow us to develop a long-grain high-yield rice variety with less chalkiness.     

Mapping and candidate gene identification of loci induced by phytohormones in barley (Hordeum vulgare L.)

Phytohormones, a group of structurally unrelated small molecules are plant-signalling compounds that trigger induced resistance against certain pathogens and herbivores. The hormones jasmonic acid (JA), ABA, salicilic acid (SA) and ethylene (ET) are known to play major roles in regulating plant defence responses. In order to determine the changes in growth and in the chlorophyll content induced by the exogenous application of these elicitors, a set of DH lines of the Oregon-Wolfe Barley mapping population, previously screened to locate aphid resistant genes, was investigated. The aim of the current research was to map the induced defence genes and to reveal the relationship with aphid resistance. There were highly significant differences between controls and hormone treated plants in the aerial fresh and dry weights (AFW, ADW), the foliar area (FA) and the root dry weight (RDW). More than 15 JA and ET-induced lines exceeded the chlorophyll (Ch) values of their controls. Most of the plant traits were associated with the same genetic windows on chromosomes 3H, 5H and 7H in the controls and hormone treated plants. QTL(s) identified on chromosome 3H and 5H explained most of the variation of AFW, ADW, FA and RDW of controls and treated plants. QTL(s) located on chromosome 5H were associated with the variation of chlorophyll contents on JA-treated plants. The Ch in ET and ABA-treated plants was associated with two different regions on chromosome 7H. One of the latter genetic windows also explained the variation of RDW of ET- and ABA-treated plants. A sequence homology search was performed to derive the putative function of the genes linked to the QTLs. Several QTLs were identified located close to aphid resistance genes previously mapped. This is the first report of genes associated with hormone response in barley that could be involved with insect resistance. Those recombinant lines carrying the appropriate alleles could be useful for breeding barley to enlarge the genetic base of defence against stress.