Tagging quantitative trait loci associated with grain yield and root morphological traits in rice (Oryza sativa L.) under contrasting moisture regimes

Plant breeding for drought-prone habitats envisages a favorable combination of grain yield and drought resistance. Though several components enhancing drought resistance have been identified in rice,their association with grain yield, under low-moisture stress, has been established in very few instances. We attempt to study the associations between rice grain yield and root system parameters both at phenotypic and genotypic levels. The doubled haploid population of IR64/Azucena was evaluated for root related traits at peak vegetative stage and grain yield related traits under both low-moisture stress and non stress conditions. ‘Mean environment’ was computed for yield related traits. Correlation and QTL mapping was attempted to find out the associations. The correlation between maximum root length and grain yield was positive under stress and negative in non stress. Genotypes with thicker and deeper roots, manifested higher biomass and grain yield under stress. Only one QTL found to increase days to flowering in non stress was also found to influence root volume and dry weight negatively under stress. The study suggests that loci enhancing grain yield and related traits were not pleiotropic with loci for desirable root morphological traits studied under low-moisture stress at vegetative stage, in the genetic material used in the study. It is thus possible to combine higher grain yield and desirable root morphological traits, favorably, to enhance productivity of rice under low-moisture stress. In rainfed ecologies, where deep roots contribute to enhanced drought resistance in rice, the results indicate the possibility of combining drought resistance with higher levels of grain yield. This revised version was published online in August 2006 with corrections to the Cover Date.     

Identification of quantitative trait loci underlying milling quality of rice (Oryza sativa) grains

Milling quality of rice grains is important to both producers and consumers. In this study, quantitative trait loci (QTLs) controlling brown rice rate (BR), milled rice recovery (MR) and head rice recovery (HR) were analysed by composite interval mapping over 2 years using 98 backcross inbred lines (BILs). A total of 12 QTLs for the three traits were detected, of which five were for BR, four for MR and three for HR. The proportion of phenotypic variation explained by individual QTLs ranged from 7.5 to 19.9%, and additive effects contributed by a single QTL accounted for 0.46 to 2.34% of the variation. QTL‐by‐environment interactions were observed by comparing QTL mapping of the same population grown in two consecutive years. Three of five QTLs for BR and two of four QTLs for MR were detected in 2 years, and all three QTLs for HR were detected in 1 year only. BR was significantly correlated with MR, and all four QTLs of MR were located in the same regions as those of BR. This indicated that QTLs for highly correlated traits could often be detected in the same interval.     

Quantitative trait loci for agronomic traits in soybean

There continues to be improvement in seed yields of soybean by conventional breeding, but molecular techniques may provide faster genetic gains. The objective of this study was to identify quantitative trait loci (QTL) associated with the agronomic traits seed yield, lodging, plant height, seed filling period and plant maturity in soybean. To achieve this objective, 101 F₆‐derived recombinant inbred lines (RIL) from a population developed from a cross of N87‐984‐16 × TN93‐99 were used. Experiments were conducted in six environments during 2002–2003. Heritability estimates on an entry mean basis from data combined across environments ranged from 0.12 to 0.65 for seed yield and seed filling period, respectively. Composite interval mapping detected one QTL for yield (near Satt076), two for lodging (near Satt225 and Satt593) and four for maturity (near Satt263, Satt292, Satt293 and Satt591) in this population. Additional environmentally sensitive QTL for these traits, and for seed filling period and plant height are also reported. The QTL associated with agronomic traits that we report and the recently released germplasm (PI 636460) from this population may be useful in soybean breeding programmes.     

Mapping of quantitative trait loci associated with rice black‐streaked dwarf virus disease and its insect vector in rice (Oryza sativa L.)

Rice black‐streaked dwarf virus disease (RBSDVD), transmitted by small brown planthopper (SBPH, Laodelphax striatellus), causes serious loss in rice production. Breeding resistant cultivars are one of the most effective strategies to control the virus disease and its vector. By both natural inoculations in the field and modified seedling‐box screening test in the glasshouse, an indica variety WR24 showed high resistance to RBSDVD and SBPH. An F_2:3 population consisting of 153 lines derived from a cross between WR24 and a susceptible japonica variety Suyunuo was used for quantitative trait loci (QTL) analysis of RBSDVD and SBPH resistance. The linkage map consisting of 130 SSR markers was constructed with an average marker interval of 13.90 cM, spanning a total of 1890.9 cM. Totally, five QTLs for RBSDV resistance, viz. qRBSDV3^WR24, qRBSDV6^WR24, qRBSDV7^WR24, qRBSDV9^WR24 and qRBSDV11^WR24, were detected on chromosomes 3, 6, 7, 9 and 11, with LOD scores of 2.7, 3.08, 3.13, 5.28 and 3.7, respectively. Meanwhile, three QTLs for SBPH resistance, including qSBPH5^WR24, qSBPH7^WR24 and qSBPH10^WR24, were mapped on chromosomes 5, 7 and 10, with LOD scores of 2.18, 3.5 and 3.57, respectively. All resistant alleles were from WR24. Among these QTLs, qRBSDV7^WR24, qSBPH5^WR24 and qSBPH10^WR24 were newly reported, and qSBPH10^WR24 showed major effect that explained 17.9% of total phenotypic variance. The RBSDVD and SBPH resistance QTLs and the tightly linked DNA markers can be utilized in RBSDV and SBPH resistance breeding in rice.     

Mapping quantitative trait loci influencing panicle‐related traits from Chinese common wild rice (Oryza rufipogon) using introgression lines

Panicle‐related traits are important agronomic traits which directly associated with grain yield. In this study, we investigated quantitative trait loci (QTLs) associated with panicle‐related traits using a set of 265 introgression lines (ILs) of common wild rice (Oryza rufipogon Griff.) in the background of Indica high‐yielding cultivar Guichao 2 (O. sativa L.). A total of 39 QTLs associated with panicle‐related traits including panicle length (PL), primary branch number (PBN), secondary branch number (SBN), spikelet number per panicle (SPP) and spikelet density (SD), were detected in the ILs with single‐point analysis. The alleles of 20 QTLs derived from wild rice showed positive effects, and some QTLs, such as, QPl1b for PL, QPbn8 for PBN, QSd4 and QSd11b for SD and QSpp4 for SPP showed larger positive effects, providing good candidates and useful information for marker‐aided improvement of yield potential of rice. Most of the QTLs controlling SPP, SBN and SD were located in cluster or closely linked on chromosomes, and the directions of their additive effects were consistent, which explained the genetic basis of significant correlations between their phenotypic characters.     

Identification and verification of quantitative trait loci for eating and cooking quality of rice (Oryza sativa)

This study was conducted to identify new quantitative trait loci (QTLs) that have stable effects for eating and cooking quality (ECQ) of rice. Three recombinant inbred line populations of indica rice were each planted in two years. Three traits for ECQ, amylose content (AC), gel consistency (GC) and alkali spreading value (ASV), were measured for QTL analysis. A total of 13 QTLs were detected, including four for AC, six for ASV and three for GC. Two QTLs, qGC4 in the interval RM16252–RM335 on the short arm of chromosome 4 and qGC6.2 in the Alk region, were validated in a population derived from a residual heterozygote that was homozygous at the major locus Wx. In the absence of segregation at the Wx locus, qGC4 and qGC6.2 had additive effects of 2.46 and 8.18 mm, respectively, offering a potential for improving GC property of rice varieties. Comparison between qGC4 and previous results suggests that qGC4 is likely a new QTL for GC, providing a candidate for gene cloning and functional characterization.     

Molecular mapping of quantitative trait loci for plant growth, yield and yield related traits across three diverse locations in a doubled haploid rice population

A doubled haploid (DH) population of 125lines derived from IR64 × Azucena, an indica – japonica cross were grown in three different locations in India during the wet season of 1995. The parents of mapping population had diverse phenotypic values for the eleven traits observed. The DH lines exhibited considerable amount of variation for all the traits. Transgressive segregants were observed. Interval analysis with threshold LOD > 3.00 detected a total of thirty four quantitative trait loci (QTL) for eleven traits across three locations. The maximum number of twenty QTL were detected at Punjab location of North India. A total of seven QTL were identified for panicle length followed by six QTL for plant height. Eight QTL were identified on three chromosomes which were common across locations. A maximum of seven QTL were identified for panicle length with the peak LOD score of 6.01 and variance of 26.80%. The major QTL for plant height was located on Chromosome 1 with peak LOD score of 16.06 flanked by RZ730-RZ801 markers. Plant height had the maximum number of common QTL across environment at the same marker interval. One QTL was identified for grain yield per plant and four QTL for thousand grain weight. Clustering of QTL for different traits at the same marker intervals was observed for plant height, panicle exsertion, panicle number, panicle length and biomass production. This suggests that pleiotropism and or tight linkage of different traits could be the plausible reason for the congruence of several QTL. Common QTL identified across locations and environment provide an excellent opportunity for selecting stable chromosomal regions contributing to yield and yield components to develop QTL introgressed lines that can be deployed in rice breeding program. This revised version was published online in July 2006 with corrections to the Cover Date.     

Mapping of quantitative trait loci controlling seed longevity of rice (Oryza sativa L.) after various periods of seed storage

Seed longevity varies considerably in cultivated rice (Oryza sativa L.), but the underlying genetic mechanism of longevity has not been well elucidated. Quantitative trait loci (QTL) that control seed longevity after various periods of seed storage were sought using recombinant inbred lines derived from a combination involving ‘Milyang23’(Indica‐type) and ‘Akihikari’ (Japonica‐type). In all, 12 QTLs for germination and normal seedling growth were detected as indices of seed longevity on chromosome 7 (one region) and chromosome 9 (two regions) in treated seeds that had been stored under laboratory conditions for 1, 2 or 3 years.‘Milyang23’ alleles of all QTLs promoted germination and normal seedling growth after all durations of storage. These QTL regions were detected repeatedly in more than one seed condition. Therefore, we infer that these regions control seed longevity.     

Identification of quantitative trait loci (QTLs) for the characters of vascular bundles in peduncle related to indica-japonica differentiation in rice (Oryza sativa L.)

The number of vascular bundles in peduncle and the ratio of vascular bundles to primary rachis branches (V/R ratio)distinguishable between indica andjaponica, are the traits associated with the processes of differentiation between indica and japonica inrice (Oryza sativa L.). In this paper a doubled-haploid population derived from the F₁ hybrid of a cross between anindica cultivar and a japonicacultivar was used to map quantitative trait loci(QTLs) controlling numbers of vascular bundles in peduncle, primary rachis branches and the V/R ratio. For vascular bundles, three QTLs were detected and they collectively explained 58.8% of the total variation. Among them, the QTLqVB-8 with the largest effect,located on chromosome 8, individually accounted for 31.1% of the total variation. Two QTLs controlling primary rachis branches, located on chromosome 8and 10 respectively, were identified and they individually explained 10.5% and18.0% of the total variation respectively. Three QTLs for the V/R ratio, mapped on chromosome 1, 2 and 8, respectively,jointly explained 61.3% of the total variation. Of the three QTLs, the QTL qV/R-1 with the largest additive effect,explained 25.3% of the total variation,was located on chromosome 1 and found to be closely linked to the gene sh-2, a major gene underlying grain-shattering ability. In addition, four and two pairs of significant epistatic QTLs were detected for vascular bundles and the V/R ratio,respectively, but none for rachis branches. Our results suggested that the numbers of vascular bundles and primary rachis branches were independently controlled by different polygenic systems, but the two polygenic systems shared a fraction of quantitative trait loci. The present study also demonstrated that the chromosome region carrying the QTL qV/R-1 for the V/R ratio and the gene sh-2 might play an important role in the processes ofindica-japonica differentiation in rice (Oryza sativa L.). This revised version was published online in August 2006 with corrections to the Cover Date.     

Mapping quantitative trait loci associated with starch paste viscosity in rice (Oryza sativa L.) under different environmental conditions

A recombinant inbred line (RIL) population consisting of 153 lines derived from a cross between indica ‘Zhongyouzao8’ and japonica ‘Toyonishiki’ rice was used to detect stable quantitative trait loci (QTL) for rapid visco analyser (RVA) characteristics under four environmental conditions. We identified 93 QTL for RVA profiles, and four pleiotropic regions harbouring stably expressed QTL were detected on chromosomes 2, 6, 7 and 11. These newly identified and stable QTL will facilitate further research into the genetic mechanism regulating RVA profiles. Amylose content (AC) was correlated with RVA traits. AC and RVA traits were unaffected by indica–japonica subspecies differentiation, suggesting that RVA profiles were mainly influenced by the Wx gene. The RIL population was divided into two subpopulations according to Wx genotypes. A total of 106 QTL associated with RVA profiles were detected in the subpopulations. These QTL differed from those detected in the whole population in terms of their genomic location, number, logarithm of odds values and amount of phenotypic variance explained. Using this strategy, we detected QTL with minor effects and eliminated false due to the Wx gene.     

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.     

Co-localization of quantitative trait loci for foliar disease resistance in sorghum

Quantitative trait loci (QTL) analysis of resistance to three foliar diseases, viz. target leaf spot, zonate leaf spot and drechstera leaf blight was undertaken in sorghum using 168 F₇ recombinant inbred lines derived from a cross between '296B' (resistant) and 'IS18551' (susceptible) parents. The genomic region flanked by plant colour locus ( Plcor ) and simple sequence repeat marker Xtxp95 on chromosome SBI-06 harboured disease-response QTL for all the three diseases caused by different fungal pathogens. It is hypothesized that this region on sorghum chromosome SBI-06 could harbour a cluster of disease-response loci to different pathogens as observed in the syntenic regions on rice chromosome 4 and maize chromosome 2. The information gained in this study can be used in deploying marker-assisted selection for foliar resistance and map-based isolation of important disease resistance genes in sorghum.     

Identification of quantitative trait loci for grain yield, seed protein concentration and maturity in field pea (Pisum sativum L.)

Breeding efforts to improve grain yield, seed protein concentration and early maturity in pea (Pisum sativum L.) have proven to be difficult. The use of molecular markers will improve our understanding of the genetic factors conditioning these traits and is expected to assist in selection of superior genotypes. This study was conducted to identify genetic loci associated with grain yield, seed protein concentration and early maturity in pea. A population of 88 recombinant inbred lines (RILs) that was developed from a cross between 'Carneval' and 'MP1401' was evaluated at 13 environments across the provinces of Alberta, Manitoba and Saskatchewan, Canada in 1998, 1999 and 2000. A linkage map consisting of 193 AFLPs (amplified fragment length polymorphism), 13 RAPDs (random amplified polymorphic DNA) and one STS (sequence tagged site) marker was used to identify putative quantitative trait loci (QTL) for grain yield, seed protein concentration and early maturity. Four QTL were identified each for grain yield and days to maturity, and three QTL were identified for seed protein concentration. A multiple QTL model for each trait showed that these genomic regions accounted for 39%, 45% and 35% of the total phenotypic variation for grain yield, seed protein concentration and days to maturity, respectively. The consistency of these QTL across environments and their potential for marker-assisted selection are discussed in this report.     

Detection of quantitative trait loci (QTL) associated with resistance to whitebacked planthopper (Sogatella furcifera) in rice (Oryza sativa)

Whitebacked planthopper (WBPH) is an important insect pest of rice. In this study, we report quantitative trait loci (QTL) associated with resistance to WBPH using a doubled‐haploid (DH) mapping population derived from the cross IR64/Azucena. We evaluated a set of 91 DH lines using various screening tests which measure seedling resistance, antibiosis and tolerance to WBPH. QTL analysis involving a RFLP map of 175 markers detected a significant QTL on chromosome 7 (RG511‐RG477) associated with seedling resistance to WBPH. In addition, QTL analysis involving available defence related candidate genes as markers on a sub set of 60 DH lines showed significant association of genomic regions on chromosome 1 (W1‐pMRF1), 2 (XLRfrI7‐RG157) and 7 (RG711‐CDO418) with resistance to WBPH. Several suggestive QTL were detected on chromosomes 2, 3, 6, 7, 8 and 11 showing the possibility of their association with resistance to WBPH. The phenotypic contribution of the QTL ranged from 8.4% to 32.1%. Some of the WBPH resistance QTL detected in this study showed similar map positions with the QTL reported for resistance to brown planthopper (BPH) in the same mapping population. These results would be useful for attempts to trace the genes associated with resistance to planthoppers in rice.     

Fine mapping of qSS‐9, a major and stable quantitative trait locus,for seed storability in rice (Oryza sativa L.)

Seed storability in rice (Oryza sativa L.) is an important agronomic trait. We previously showed a quantitative trait locus of seed storability, qSS‐9, on chromosome 9 in a backcross population of ‘Koshihikari’ (japonica) / ‘Kasalath’ (indica) // ‘Koshihikari’. In this study, fine mapping of the chromosomal location of qSS‐9 was performed. Effect of ‘Kasalath’ allele of qSS‐9 was validated using a chromosome segment substitution line, SL36, which harboured the target quantitative trait loci (QTL) from ‘Kasalath’ in the genetic background of ‘Nipponbare’ under different ageing treatments in different environments. Subsequently, an F₂ population from a cross between ‘Nipponbare’ and SL36 was used for fine mapping of qSS‐9. Simultaneously, four subnear isogenic lines (sub‐NILs) that represented different recombination breakpoints across the qSS‐9 region were developed from F₃ progeny. Finally, the qSS‐9 locus was located between the Indel markers Y10 and Y13, which delimit a region of 147 kb in the ‘Nipponbare’ genome. These results provide a springboard for map‐based cloning of qSS‐9 and possibilities for breeding rice varieties with strong seed storability.     

Mapping and validation of the quantitative trait loci for leaf stay‐green‐associated parameters in maize

Functional stay‐green is generally regarded as a desirable trait of varieties in major crops including maize. In this study, we used an F_3:4 recombinant inbred line population with 165 lines from a cross between a stay‐green inbred line (Zheng58) and a model inbred line (B73) using 211 polymorphic simple sequence repeat markers to map quantitative trait loci for three stay‐green‐associated parameters, chlorophyll content, photosystem II photochemical efficiency and stay‐green area, at maturity stage, detected a total of 23 quantitative trait loci (QTL) on nine chromosomes. Single QTL explained 3.7–13.5% of the phenotypic variance. Additionally, we validated some important stay‐green QTL using a heterogeneous inbred family approach and found that the stay‐green‐associated parameters were significantly correlated with the plant yield. This study may contribute to a better insight into the regulatory mechanism behind leaf stay‐green in maize and a novel development of elite maize varieties with delayed leaf senescence through molecular marker‐assisted selection.     

Analysis of contributors to grain yield in wheat at the individual quantitative trait locus level

In wheat, strong genetic correlations have been found between grain yield (GY) and tiller number per plant (TN), fertile spikelet number per spike (FSN), kernel number per spike (KN) and thousand‐kernel weight (TKW). To investigate their genetic relationships at the individual quantitative trait locus (QTL) level, we performed both normal and multivariate conditional QTL analysis based on two recombinant inbred lines (RILs) populations. A total of 79 and 48 normal QTLs were identified in the International Triticeae Mapping Initiative (ITMI)/SHW‐L1 × Chuanmai 32 (SC) populations, respectively, as well as 55 and 35 conditional QTLs. Thirty‐two QTL clusters in the ITMI population and 18 QTL clusters in the SC population explained 0.9%–46.2% of phenotypic variance for two to eight traits. A comparison between the normal and conditional QTL mapping analyses indicated that FSN made the smallest contribution to GY among the four GY components that were considered at the QTL level. The effects of TN, KN and TKW on GY were stronger at the QTL level.