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.     

Identification of QTLs associated with heat tolerance at the heading and flowering stage in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

The ongoing rise in temperatures caused by global climate change is a critical climatic risk factor for rice production, and enhancing rice heat tolerance is an area of particular research interest. A recombinant inbred line (RIL) mapping population was developed from heat sensitive, rice cultivar IAPAR-9 crossed with heat tolerant, Liaoyan241. RIL and parental lines were exposed to high temperature at the heating and flowering stage in experiments in 2014 and 2015. As indicators of heat tolerance, the seed setting rate under natural (NS) and heat stress (HTS) conditions were measured, and the reduction rate of seed set (RRS) was calculated. Quantitative trait loci (QTL) analysis revealed eleven heat tolerance QTLs located on chromosomes 1, 3, 4, 5, and 6. Single QTL contribution rates were 4.75–13.81% and effect values were ? 5.98 to 5.00. Four major QTLs (qNS1, qNS4, qNS6, and qRRS1) were stable detected in different environments in both years. Thirteen QTLs with epistatic interactions and nine QTLs with environmental interactions were also detected. Major QTLs were all involved in epistatic and environmental interactions. Three QTLs from the SSR marker interval RM471 to RM177 region of chromosome 4 (qNS4, qHTS4, and qRRS4) were all involved in epistatic and environmental interactions and contributed to phenotypic variation, indicating that this region constituted a major QTL hotspot. The major QTL for heat tolerance identified in this study will aid in breeding tolerant cultivars and facilitating investigation of the molecular underpinnings of heat tolerance in rice.     

Identification of QTLs for resistance to Fusarium wilt and Ascochyta blight in a recombinant inbred population of chickpea (<Emphasis Type="Italic">Cicer arietinum</Emphasis> L.)

Fusarium wilt (FW; caused by Fusarium oxysporum f. sp. ciceris) and Ascochyta blight (AB; caused by Ascochyta rabiei) are two major biotic stresses that cause significant yield losses in chickpea (Cicer arietinum L.). In order to identify the genomic regions responsible for resistance to FW and AB, 188 recombinant inbred lines derived from a cross JG 62 × ICCV 05530 were phenotyped for reaction to FW and AB under both controlled environment and field conditions. Significant variation in response to FW and AB was detected at all the locations. A genetic map comprising of 111 markers including 84 simple sequence repeats and 27 single nucleotide polymorphism (SNP) loci spanning 261.60 cM was constructed. Five quantitative trait loci (QTLs) were detected for resistance to FW with phenotypic variance explained from 6.63 to 31.55%. Of the five QTLs, three QTLs including a major QTL on CaLG02 and a minor QTL each on CaLG04 and CaLG06 were identified for resistance to race 1 of FW. For race 3, a major QTL each on CaLG02 and CaLG04 were identified. In the case of AB, one QTL for seedling resistance (SR) against ‘Hisar race’ and a minor QTL each for SR and adult plant resistance against isolate 8 of race 6 (3968) were identified. The QTLs and linked markers identified in this study can be utilized for enhancing the FW and AB resistance in elite cultivars using marker-assisted backcrossing.     

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.     

QTL mapping and identification of corresponding genomic regions for black pod disease resistance to three <Emphasis Type="Italic">Phytophthora</Emphasis> species in <Emphasis Type="Italic">Theobroma cacao</Emphasis> L.

The cacao tree (Theobroma cacao L.) is a species of great importance because cacao beans are the raw material used in the production of chocolate. However, the economic success of cacao is largely limited by important diseases such as black pod, which is responsible for losses of up to 30–40% of the global cacao harvest. The discovery of resistance genes could extensively reduce these losses. Therefore, the aims of this study were to construct an integrated multipoint genetic map, align polymorphisms against the available cacao genome, and identify quantitative trait loci (QTLs) associated with resistance to black pod disease in cacao. The genetic map had a total length of 956.41 cM and included 186 simple sequence repeat (SSR) markers distributed among 10 linkage groups. The physical “in silico” map covered more than 200 Mb of the cacao genome. Based on the mixed model predicted means of Phytophthora evaluation, a total of 6 QTLs were detected for Phytophthora palmivora (1 QTL), Phytophthora citrophthora (1 QTL), and Phytophthora capsici (4 QTLs). Approximately 1.77–3.29% of the phenotypic variation could be explained by the mapped QTLs. Several SSR marker-flanking regions containing mapped QTLs were located in proximity to disease regions. The greatest number of resistance genes was detected in linkage group 6, which provides strong evidence for a QTL. This joint analysis involving multipoint and mixed-model approaches may provide a potentially promising technique for detecting genes resistant to black pod and could be very useful for future studies in cacao breeding.     

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.     

Genetic dissection of rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) tiller,plant height,and grain yield based on QTL mapping and metaanalysis

Tiller number per plant (TN) and plant height (PH) are important agronomic traits related to grain yield (GY) in rice (Oryza sativa L.). A total of 30 additive quantitative trait loci (A-QTL) and 9 significant additive × environment interaction QTLs (AE-QTL) were detected, while the phenotypic and QTL correlations confirmed the intrinsic relationship of the three traits. These QTLs were integrated with 986 QTLs from previous studies by metaanalysis. Consensus maps contained 7156 markers for a total map length of 1112.71 cM, onto which 863 QTLs were projected; 78 meta-QTLs (MQTLs) covering 11 of the 30 QTLs were detected from the cross between Dongnong422 and Kongyu131 in this study. A total of 705 predicted genes were distributed over the 21 MQTL intervals with physical length <0.3 Mb; 13 of the 21 MQTLs, and 34 candidate genes related to grain yield and plant development, were screened. Five major QTLs, viz. qGY6-2, qPH7-2, qPH6-3, qTN6-1, and qTN7-1, were not detected in the MQTL intervals and could be used as newly discovered QTLs. Candidate genes within these QTL intervals will play a meaningful role in molecular marker-assisted selection and map-based cloning of rice TN, PH, and GY.     

东乡野生稻抗褐飞虱QTL分析

野生稻是水稻抗褐飞虱基因的重要种质资源。应用东乡野生稻与栽培稻协青早B构建的2套材料,开展水稻抗褐飞虱基因鉴定研究。先以协青早B//协青早B/东乡野生稻BC₁F₅群体为材料,应用褐飞虱田间种群进行抗虫鉴定,检测到2个抗褐飞虱QTL,其中,qBph2位于水稻第2染色体RM29–RG157区间,东乡野生稻等位基因可降低死苗率22.2%;qBph7位于第7染色体RM11–RM234区间,东乡野生稻等位基因可降低死苗率43.7%。进一步以协青早B为轮回亲本,构建了BC₃F₃群体,应用褐飞虱生物型I、II和III进行抗虫鉴定,QTL分析表明qBph2抗褐飞虱生物型I和II,qBph7抗褐飞虱生物型I和III。这2个QTL对培育抗褐飞虱水稻品种具有重要应用价值。     

Dynamic QTL analysis and validation for plant height using maternal and paternal backcrossing populations in Upland cotton

Plant height determines plant biomass yield, harvest index and economic yield. We analyzed quantitative trait loci (QTL) and gene action controlling plant height. We generated the maternal and paternal testcrossing (TC/M and TC/P) populations based on a recombinant inbred line population. Data for plant height at t1, t2, t3, t4 or t5 stages were collected over 2 years from 3 TC/M field trials and 2 TC/P field trials. At single-locus level, 32 QTLs at five stages and 24 conditional QTLs at four intervals were detected, and 14 QTLs shared in different years or populations or stages. Plant height displayed dynamic characteristics through expression of QTLs. A total of 21 novel QTLs were detected and 11 QTLs validated the previous results. And 19 QTLs explained over 10% of phenotypic variation, such as qPH-Chr9-2, qPH-Chr19-4 and qPH-Chr22-4. The region of NAU5330-NAU1269 on chromosome 19 may be a desired target for genetic improvement of plant height in Upland cotton. In addition, five and eight heterotic loci were identified in TC/M and TC/P populations, respectively. Additive, partial dominance and overdominance effects were observed in both TC populations. We also identified 43 epistatic QTLs and QTLs by environment interactions by inclusive composite interval mapping method. Taken together, additive, partial dominance and overdominance effects together with epistasis explained the genetic basis of plant height in Upland cotton.     

Development of high-density interspecific genetic maps for the identification of QTLs conferring resistance to <Emphasis Type="Italic">Valsa ceratosperma</Emphasis> in apple

Valsa canker (Valsa ceratosperma (Tode ex Fr.) Maire) is one of the most destructive fungal diseases of apple, especially in Eastern Asia. In this study, the first high density genetic linkage map of Malus asiatica × Malus domestica was constructed by 640 simple sequence repeats (SSRs) and 490 single nucleotide polymorphisms (SNPs), which spanned 1497.5 cM with an average marker interval of 1.33 cM per marker. Quantitative trait loci (QTLs) for apple’s resistance to V. ceratosperma isolates 03-8 and xc56 were identified using the linkage map. Lesion lengths were used as the phenotypic data for the QTL analysis, which were measured on 1-year-old shoots inoculated with conidia of the two isolates. One QTL for resistance to isolate 03-8 was mapped on LG 16, and one QTL for resistance to isolate xc56 was detected on LG 9. Our research not only promoted the further understanding of the genetic basis of apple’s resistance to Valsa canker but also provided two molecular markers that might be used in future marker-assisted selection for resistance in apple breeding programs.     

Identification of QTLs controlling low-temperature germinability and cold tolerance at the seedling stage in rice (<Emphasis Type="Italic">Oryza Sativa</Emphasis> L.)

Both low-temperature germinability (LTG) and cold tolerance at the seedling stage (CTS) are important traits for rice. In this study, a rice population of recombinant inbred lines (RILs), derived from the backcross population of a cross between Dongnong422 and Kongyu131, was developed to detect quantitative trait loci (QTL) affecting LTG and CTS by using seed of different storage times. Correlation analysis indicated that there was no significant relationship between LTG and CTS, suggesting that cold tolerance might be genetic differences for LTG and CTS. In total, Twelve and twenty-three major QTLs were detected for LTG and CTS, respectively, which could explain greater than 10% of the phenotypical variation. Eight (qCG12-1, qGI12-1, qGV9-1, qMLIT12-1, qPV6-1, qMDG12-1, qLDWcold10-1, qLFWcold10-1) significant QTLs were mapped for different storage time, it concluded that such QTLs were not affected by environment (storage time) and were closely related QTLs to cold tolerance. One or more QTLs were identified for each trait with some of these QTLs co-locating, qMLIT7-1, qCG7-1, and qGI7-1 for LTG, qLFWcold10-1, and qLDWcold10-1 for CTS with contributions over 15% were mapped common marker interval, respectively, co-location of QTLs for different traits can be an indication that a locus has pleiotropic effects on multiple traits due to a common mechanistic basis. Two lines, RIL128 and RIL73, might be valuable to improve the LTG and CTS through a combination of crosses. The identified QTLs might be applicable to improve the rice cold tolerance by the marker-assisted selection approach.     

A new gene <Emphasis Type="Italic">Bph33</Emphasis>(<Emphasis Type="Italic">t</Emphasis>) conferring resistance to brown planthopper (BPH), <Emphasis Type="Italic">Nilaparvata lugens</Emphasis> (Stål) in rice line RP2068-18-3-5

The rice brown planthopper (BPH) Nilaparvata lugens (Stål) is one of the major pests of rice across Asia. Host-plant resistance is the most ecologically acceptable means to manage this pest. A rice breeding line RP2068-18-3-5 (RP2068) derived from the land race Velluthacheera is reported to be resistant to BPH populations across India. We identified a new R gene [Bph33(t)] in this line using advanced generation RILs derived from TN1 × RP2068 cross through phenotyping at two locations and linkage analysis with 99 polymorphic SSR markers. QTL analysis through IciMapping identified at least two major QTL on chromosome 1 influencing seedling damage score in seed box screening, honey dew excretion by adults and nymphal survival. Since no BPH R gene has been reported on chromosome 1, we designate this locus as a new gene Bph33(t) which accounted for over 20% of phenotypic variance. Scanning the region for candidate gene suggested two likely candidates a leucine rich repeat (LRR) gene and a heat shock protein (HSP) coding gene. Expression profiling of the two genes in the two contrasting parents and RILs showed induction of the HSP gene (LOC_Os01g42190.1) at 6 h after infestation while LRR gene did not show such induction. It is likely that the HSP represented Bph33(t).     

Effects of introgressions from <Emphasis Type="Italic">Festuca pratensis</Emphasis> on winter hardiness of <Emphasis Type="Italic">Lolium perenne</Emphasis>

Previous studies reported that some genotypes with introgressed Festuca chromosome segment(s) in Lolium genome showed enhanced winter hardiness compared to Lolium. The aim of this study was to search comprehensively for the Festuca pratensis chromosome regions affecting winter hardiness-related traits when introgressed into the Lolium perenne genome. Association between F. pratensis introgression and winter hardiness-related traits (fall and winter hardiness indexes, early-spring dry matter yield, and freezing tolerance) were screened in the diploid introgression populations (n = 203) that had some F. pratensis chromosome segments introgressed. Eighty-four intron markers corresponding to unique rice genes randomly distributed across the genome were used for genotyping. Winter hardiness of almost all plants in the introgression populations was lower than that of the F. pratensis and triploid hybrid parents, but the average was higher than that of L. perenne. A significant positive effect of F. pratensis introgression on early-spring dry matter yield was detected on chromosome 7. This quantitative trait locus (QTL) was confirmed by linkage analysis using a backcross population with F. pratensis introgression in the target region of chromosome 7. However, the contribution of the newly identified QTL was rather small (6.7–9.6%), suggesting that superior winter hardiness of F. pratensis compared to L. perenne is conferred by multiple small-effect QTLs. We also detected a previously unreported negative effect of Festuca introgression on winter hardiness. Newly obtained QTL information in this study would contribute to the design of Festuca/Lolium hybrid breeding.     

Identifying QTL–allele system of seed protein content in Chinese soybean landraces for population differentiation studies and optimal cross predictions

Soybean originated in ancient China has been quickly extended globally as a major protein and oil crop. The QTL–allele constitution of seed protein content (SPC) in the Chinese soybean landrace population (CSLRP) was studied using a representative sample composed of 365 accessions tested under multiple environments and analysed under the novel restricted two-stage multi-locus genome-wide association study (RTM-GWAS) procedure based on 29,121 SNPLDB (single nucleotide polymorphism linkage disequilibrium blocks) markers. The SPC varied from 37.51 to 50.46% among accessions, for which 89 QTLs, each with 2–9 alleles in a total of 255 alleles were identified, accounting for 83.16% of the phenotypic variation covering most of the genetic variation (h²?=?84.31%). The QTL–alleles of the 365 landraces were organized into a 255?×?365 QTL–allele matrix as the compact form of SPC genetic constitution in CSLRP. Of the 89 QTLs, 53 showed significantly differentiated allele frequency distribution patterns among geographic eco-regions (sub-populations). There were 32.09% alleles not common among sub-populations but found only in some sub-populations; new allele(s) emerged on some loci in some respective sub-populations, with Eco-region III showing less but Eco-region VI more emergence. The QTL–allele matrix was also used for prediction of optimal crosses for breeding purpose to reach a 99th percentile potential of up to 54.81%, more than the highest accession (50.46%). From the 89 QTLs, 59 SPC candidate genes involving biological processes, cellular components and molecular functions were annotated. Among them, Glyma18g13574 and Glyma20g21370 were inferred as two of the major SPC genes in the whole genome.     

Mapping association of molecular markers and sheath blight (<Emphasis Type="Italic">Rhizoctonia solani</Emphasis>) disease resistance and identification of novel resistance sources and loci in rice

Sheath blight (ShB) disease caused by Rhizoctonia solani is one of the major threats to rice crop world-wide. Progress in breeding for resistant rice varieties is limited due to lack of highly resistant germplasm against sheath blight. In present study, diverse rice landrace were phenotyped against R. solani and resistant and moderately resistant sources were identified from the panel of 134 germplasm pool. Landrace Nizam shait showed resistance, where as Bidar local-2, Jigguvaratiga, NavaliSali, Jaddu and Tetep exhibited moderate resistance. Population structure was analysed by genotyping the accessions using 63 genome wide Rice Microsatellite markers which divided the mapping panel into two groups. Association mapping using GLM?+?Q model of TASSEL indicated significant association between twenty-one marker loci on nine chromosomes with ShB resistance with phenotypic variation (R²) ranging 3.02–22.71 per cent. We identified 13 new markers to be associated with ShB resistance. The present work validates previously identified eight markers flanking different shB QTLs. None of the allele from the tested markers was unique and common among resistant and moderately resistant landraces identified in this work except allele 420 bp of RM337 and allele 310 bp of RM5556 noticed only in Tetep. Our findings predict the possible presence of unreported QTL region in marker interval of RM337 and RM5556 on chromosome 8 for ShB resistance in Tetep which invites further investigation.     

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 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.     

Identification and validation of root length QTLs for water stress resistance in hexaploid wheat (<Emphasis Type="Italic">Titicum aestivum</Emphasis> L.)

Thorough understanding of the genetic mechanisms governing drought adaptive traits can facilitate drought resistance improvement. This study was conducted to identify chromosome regions harbouring QTLs contributing for water stress resistance in wheat. A RIL mapping population derived from a cross between W7984 (Synthetic) and Opata 85 was phenotyped for root length and root dry weight under water stress and non-stress growing conditions. ANOVA showed highly significant (p ≤ 0.01) variation among the RILs for both traits. Root length and root dry weight showed positive and significant (p ≤ 0.01) phenotypic correlation. Broad sense heritability was 86% for root length under stress and 65% for root dry weight under non-stress conditions. A total of eight root length and five root dry weight QTLs were identified under both water conditions. Root length QTLs Qrln.uwa.1BL, Qrln.uwa.2DS, Qrln.uwa.5AL and Qrln.uwa.6AL combined explained 43% of phenotypic variation under non-stress condition. Opata was the source of favourable alleles for root length QTLs under non-stress condition except for Qrln.uwa.6AL. Four stress specific root length QTLs, Qrls.uwa.1AS, Qrls.uwa.3AL, Qrls.uwa.7BL.1 and Qrls.uwa.7BL.2 jointly explained 47% of phenotypic variation. Synthetic wheat contributed favourable alleles for Qrls.uwa.1AS and Qrls.uwa.3AL. Two stable root dry weight QTLs on chromosomes 4AL and 5AL were consistently found in both water conditions. Three validation populations were developed by crossing cultivars Lang, Yitpi, and Chara with Synthetic W7984 to transfer two of the QTLs identified under stress condition. The F_2.3 and F_3.4 validation lines were phenotyped under the same level of water stress as RILs to examine the effect of these QTLs. There were 13.5 and 14.5% increases in average root length due to the inheritance of Qrls.uwa.1AS and Qrls.uwa.3AL, respectively. The result indicated that closely linked SSR markers Xbarc148 (Qrls.uwa.1AS) and Xgwm391 (Qrls.uwa.3AL) can be incorporated into MAS for water stress improvement in wheat.     

Conferring resistance to pre-harvest sprouting in durum wheat by a QTL identified in <Emphasis Type="Italic">Triticum spelta</Emphasis>

Pre-harvest sprouting (PHS) causes significant yield loss and degrade the end-use quality of wheat, especially in regions with prolonged wet weather during the harvesting season. Unfortunately, the gene pool of Triticum durum (tetraploid durum wheat) has narrow genetic base for PHS resistance. Therefore, finding out new genetic resources from other wheat species to develop PHS resistance in durum wheat is of importance. A major PHS resistance QTL, Qphs.sicau-3B.1, was mapped on chromosome 3BL in a recombinant inbred line population derived from ‘CSCR6’ (Triticum spelta), a PHS resistant hexaploid wheat and ‘Lang’, a PHS susceptible Australian hexaploid wheat cultivar. This QTL, Qphs.sicau-3B.1, is positioned between DArT marker wPt-3107 and wPt-6785. Two SCAR markers (Ph3B.1 and Ph3B.2) were developed to track this major QTL and were used to assay a BC₂F₈ tetraploid population derived from a cross between the durum wheat ‘Bellaroi’ (PHS susceptible) and ‘CSCR6’ (PHS resistant). Phenotypic assay and marker-assisted selection revealed five stable tetraploid lines were highly PHS resistant. This study has successfully established that PHS-resistance QTL from hexaploid wheat could be efficiently introgressed into tetraploid durum wheat. This tetraploid wheat germplasm could be useful in developing PHS resistant durum cultivars with higher yield and good end-use quality.