Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population

A recombinant inbred population developed from a cross between high-yielding lowland rice (Oryza sativa L.) subspecies indica cv. IR64 and upland tropical rice subspecies japonica cv. Cabacu was used to identify quantitative trait loci (QTLs) for grain yield (GY) and component traits under reproductive-stage drought stress. One hundred fifty-four lines were grown in field trials in Indonesia under aerobic conditions by giving surface irrigation to field capacity every 4 days. Water stress was imposed for a period of 15 days during pre-flowering by withholding irrigation at 65 days after seeding. Leaf rolling was scored at the end of the stress period and eight agronomic traits were evaluated after recovery. The population was also evaluated for root pulling force, and a total of 201 single nucleotide polymorphism markers were used to construct the molecular genetic linkage map and QTL mapping. A QTL for GY under drought stress was identified in a region close to the sd1 locus on chromosome 1. QTL meta-analysis across diverse populations showed that this QTL was conserved across genetic backgrounds and co-localized with QTLs for leaf rolling and osmotic adjustment (OA). A QTL for percent seed set and grains per panicle under drought stress was identified on chromosome 8 in the same region as a QTL for OA previously identified in three different populations.     

Fine mapping of grain length QTLs on chromosomes 1 and 7 in Basmati rice (Oryza sativa L.)

Grain dimensions (length, breadth and length/breadth ratio) are important quality attributes of Basmati rice for its high consumer acceptance. Earlier we identified two significant quantitative trait loci (QTL) intervals on chromosomes 1 and 7 for grain dimensions in Basmati rice using a population of recombinant inbred lines (RILs) from cross between Basmati variety Pusa 1121 and a short grain non-aromatic variety Pusa 1342. For fine mapping of these QTLs, 184 F₆ RILs were grown and phenotyped in the normal rice growing season at two different locations. Forty-nine new SSR markers targeting these QTL intervals were tested and nine were found polymorphic between the parents. Using revised genetic maps adding new markers, the grain length QTL qGRL1.1 on chromosome 1 was narrowed down to 108?kbp from the earlier reported 6,133?kbp. There were total 13 predicted gene models in this interval which includes the probable candidate gene for the exceptionally high grain length of Basmati variety Pusa 1121. Similarly, two tandem QTL intervals qGRL7.1 and qGRL7.2 on chromosome 7 were merged into a single one narrowed down to 2,390?kbp from the earlier reported length of 5,269?kbp. This region of chromosome 7 also has co-localized QTLs for grain breadth and length to breadth ratio. SSR markers tightly linked to the QTL at a map distance of ??0.2?cM were developed for the qGRL1.1 and qGRL7.1 loci that could be used for marker-assisted breeding. Validation of earlier published markers for the grain length gene GS3 on chromosome 3 showed no difference between Pusa 1121 and Pusa 1342, highlighting the significance of qGRL1.1 and qGRL7.1 for the extra grain length of Basmati variety Pusa 1121.     

Molecular dissection of QTL governing grain size traits employing association and linkage mapping in Basmati rice

Grain size is one of the key traits that determines the quality of Basmati rice from the consumers’ as well as the traders’ point of view. Though many genes governing grain size have been identified in indica and japonica, little work has been done in Basmati rice. The present study aims at dissection of a QTL region governing grain size traits in Basmati employing association and linkage mapping approaches. Association mapping revealed that three markers, i.e., RM 6024 (grain breadth), RM1237 and RM18582 (grain length-breadth ratio), which cover 889 kb in the targeted QTL region have been significantly associated with grain size traits. Using linkage mapping, the targeted QTL region has been further delimited to a physical distance of 268 kb that comprises 24 annotated genes. The gene expression analysis of parents, revealed 19 genes differentially expressing within the QTL. Of them, 15 genes showed high expression in Basmati370, while four were expressed in Jaya, and whereas five genes did not show any differential expression between parents. Among differentially expressed genes, a highly expressed gene in Basmati370, Os05g0374200 (Cytokinin dehydrogenase 1 precursor) seems to be involved in accumulation of cytokinins, thus affecting the grain size. Therefore, our findings demonstrated that by complimenting association and linkage mapping, it is likely to dissect a QTL governing grain size traits in Basmati rice and also the QTL could be a potential target for marker-assisted breeding and map-based cloning studies.     

Validation of gene based marker-QTL association for grain dimension traits in rice

Validation of marker-QTL association for genes grain size 3 (GS3), grain weight 2 (GW2), seed width 5 (qSW5) and a QTL qgrl7.1 for grain length was undertaken in a set of 242 diverse rice germplasm. Further, the study was extended to an F₂ mapping population derived from cross of Sonasal, a short grain aromatic rice landrace with Pusa Basmati 1121, a variety with extra long slender grains. Seven gene specific markers, namely, SF28, SR17, RGS1and RGS2 based on GS3, W004 for GW2, MS40671 for qSW5 and RM505 for qgrl7.1, were used for validation. Single marker analysis revealed significant association of these markers to grain size and shape. The marker SF28 explained highest phenotypic variance (37 %) while the marker W004 explained lowest variance (2.6 %) for grain length in the germplasm set at the significance level P?<?0.05. Three markers namely, SF28, MS40671 and RM505 were polymorphic between the parents Sonasal and Pusa Basmati 1121. In the F₂ population, the marker SF28 linked to gene GS3 explained highest phenotypic variance (32.5 %), while RM505 linked to qgrl7.1 explained 5.4 % of phenotypic variance for grain length. The marker SF28 was found to be most robust in the validation studies both in germplasm and F₂ population. The validated gene specific markers can be utilised in marker assisted selection for improving grain size and shape as these traits have significant contribution towards grain quality and grain yield. This is the first study on validation of gene based markers for grain dimension traits in Indian rice germplasm.     

Fine mapping of qHd1, a minor heading date QTL with pleiotropism for yield traits in rice (Oryza sativa L.)

Key message

A minor QTL for heading date located on the long arm of rice chromosome 1 was delimitated to a 95.0-kb region using near isogenic lines with sequential segregating regions.

Abstract

Heading date and grain yield are two key factors determining the commercial potential of a rice variety. In this study, rice populations with sequential segregating regions were developed and used for mapping a minor QTL for heading date, qHd1. A total of 18 populations in six advanced generations through BC₂F₆ to BC₂F₁₁ were derived from a single BC₂F₃ plant of the indica rice cross Zhenshan 97 (ZS97)///ZS97//ZS97/Milyang 46. The QTL was delimitated to a 95.0-kb region flanked by RM12102 and RM12108 in the terminal region of the long arm of chromosome 1. Results also showed that qHd1 was not involved in the photoperiodic response, having an additive effect ranging from 2.4 d to 2.9 d observed in near isogenic lines grown in the paddy field and under the controlled conditions of either short day or long day. The QTL had pleiotropic effects on yield traits, with the ZS97 allele delaying heading and increasing the number of spikelets per panicle, the number of grains per panicle and grain yield per plant. The candidate region contains ten annotated genes including two genes with functional information related to the control of heading date. These results lay a foundation for the cloning of qHd1. In addition, this kind of minor QTLs could be of great significance in rice breeding for allowing minor adjustment of heading date and yield traits.     

Whole-Genome Quantitative Trait Locus Mapping Reveals Major Role of Epistasis on Yield of Rice

Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F₂ population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.     

Characterisation of a novel quantitative trait locus, <Emphasis Type="Italic">GN4</Emphasis>-<Emphasis Type="Italic">1</Emphasis>, for grain number and yield in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Key message

A novel QTL for grain number, GN4-1, was identified and fine-mapped to an ~ 190-kb region on the long arm of rice chromosome 4.

Abstract

Rice grain yield is primarily determined by three components: number of panicles per plant, grain number per panicle and grain weight. Among these traits, grain number per panicle is the major contributor to grain yield formation and is a crucial trait for yield improvement. In this study, we identified a major quantitative trait locus (QTL) responsible for rice grain number on chromosome 4, designated GN4-1 (a QTL for Grain Number on chromosome 4), using advanced segregating populations derived from the crosses between an elite indica cultivar ‘Zhonghui 8006’ (ZH8006) and a japonica rice ‘Wuyunjing 8’ (WYJ8). GN4-1 was delimited to an ~ 190-kb region on chromosome 4. The genetic effect of GN4-1 was estimated using a pair of near-isogenic lines. The GN4-1 gene from WYJ8 promoted accumulation of cytokinins in the inflorescence and increased grain number per panicle by ~ 17%. More importantly, introduction of the WYJ8 GN4-1 gene into ZH8006 increased grain yield by ~ 14.3 and ~ 11.5% in the experimental plots in 2014 and 2015, respectively. In addition, GN4-1 promoted thickening of the culm and may enhance resistance to lodging. These results demonstrate that GN4-1 is a potentially valuable gene for improvement of yield and lodging resistance in rice breeding.

     

A cluster of Ankyrin and Ankyrin-TPR repeat genes is associated with panicle branching diversity in rice

The number of grains per panicle is an important yield-related trait in cereals which depends in part on panicle branching complexity. One component of this complexity is the number of secondary branches per panicle. Previously, a GWAS site associated with secondary branch and spikelet numbers per panicle in rice was identified. Here we combined gene capture, bi-parental genetic population analysis, expression profiling and transgenic approaches in order to investigate the functional significance of a cluster of 6 ANK and ANK-TPR genes within the QTL. Four of the ANK and ANK-TPR genes present a differential expression associated with panicle secondary branch number in contrasted accessions. These differential expression patterns correlate in the different alleles of these genes with specific deletions of potential cis-regulatory sequences in their promoters. Two of these genes were confirmed through functional analysis as playing a role in the control of panicle architecture. Our findings indicate that secondary branching diversity in the rice panicle is governed in part by differentially expressed genes within this cluster encoding ANK and ANK-TPR domain proteins that may act as positive or negative regulators of panicle meristem’s identity transition from indeterminate to determinate state.     

A novel QTL <Emphasis Type="Italic">qSPP2.2</Emphasis> controlling spikelet per panicle identified from <Emphasis Type="Italic">Oryza longistaminata</Emphasis> (A. Chev. et Roehr.), mapped and transferred to <Emphasis Type="Italic">Oryza sativa</Emphasis> (L.)

Increasing the rice productivity from the current 10 to 12 tons/ha to meet the demand of estimated 8.8 billion people in 2035 is posing a major challenge. Wild relatives of rice contain some novel genes which can help in improving rice yield. Spikelet per panicle (SPP) is a valuable trait for determining yield potential in rice. In this study, a major QTL for increasing SPP has been identified, mapped, and transferred from African wild rice O. longistaminata to O. sativa (L.). The QTL was mapped on the long arm of chromosome 2 in a 167.1 kb region flanked by SSR markers RM13743 and RM13750, which are 1.0 cM apart, and is designated as qSPP2.2. The QTL explained up to 30% of phenotypic variance in different generations/seasons and showed positive additive effect of allele contributed by O. longistaminata. In addition, O. longistaminata allele in qSPP2.2 contributed to increase in grains per panicle, but decrease in the tillers per plant. The 167.1 kb region contains 23 predicted genes. Based on the functional annotation, three genes, LOC_Os02g44860, LOC_Os02g44990, and LOC_Os02g45010, were selected as putative candidates for characterization. Sequence analysis of the three genes revealed functional variations between the parental lines for LOC_Os02g44990 and a variation in 5′UTR for LOC_Os02g45010 which will help further to identify putative candidate gene(s). This is the first yield component QTL to be identified, mapped, and transferred from O. longistaminata.     

Fine mapping of a quantitative trait locus for grain number per panicle from wild rice (Oryza rufipogon Griff.)

SIL040, an introgression line (IL) developed by introgressing chromosomal segments from an accession of Oryza rufipogon into an indica cultivar Guichao 2, showed significantly less grains per panicle than the recurrent parent Guichao 2. Quantitative trait locus (QTL) analysis in F₂ and F₃ generations derived from the cross between SIL040 and Guichao 2 revealed that gpa7, a QTL located on the short arm of chromosome 7, was responsible of this variation. Alleles from O. rufipogon decreased grains per panicle. To fine mapping of gpa7, a high-resolution map with 1,966 F₂ plants derived from the cross between SIL040 and Guichao 2 using markers flanking gpa7 was constructed, and detailed quantitative evaluation of the structure of main panicle of each of F₃ families derived from recombinants screened was performed. By two-step substitution mapping, gpa7 was finally narrowed down to a 35-kb region that contains five predicted genes in cultivated rice. The fact that QTLs for five panicle traits (length of panicle, primary branches per panicle, secondary branches per panicle, grains on primary branches and grains on secondary branches) were all mapped in the same interval as that for gpa7 suggested that this locus was associated with panicle structure, showing pleiotropic effects. The characterizing of panicle structure of IL SIL040 further revealed that, during the domestication from common wild allele to cultivated rice one at gpa7, not only the number of branches and grains per panicle increased significantly, more importantly, but also the ratio of secondary branches per panicle to total branches per panicle and the ratio of grains on secondary branches per panicle to total grains per panicle increased significantly. All these results reinforced the idea that gpa7 might play an important role in the regulation of grain number per panicle and the ratio of secondary branches per panicle during the domestication of rice panicle.Feng Tian and Zuo Feng Zhu contributed equally to this work.     

Marker-assisted improvement of bacterial blight resistance in parental lines of Pusa RH10, a superfine grain aromatic rice hybrid

Pusa RH10, the widely cultivated superfine grain aromatic rice hybrid, and its parental lines Pusa6B and PRR78 are susceptible to bacterial blight (BB) disease caused by Xanthomonas oryzae pv. oryzae. Pusa1460, a Basmati rice variety, was utilized as the donor for introgressing BB resistance genes xa13 and Xa21 into Pusa6B and PRR78 using a marker-assisted backcross breeding program. The markers RG136 and pTA248 linked to BB resistance genes xa13 and Xa21, respectively, were used for foreground selection. Seventy-four STMS markers polymorphic between Pusa6B and Pusa1460, and 54 STMS markers polymorphic between PRR78 and Pusa1460, were utilized for background selection to recover the recurrent parent genome ranging from 85.14 to 97.30% and 87.04 to 92.81% in the 10 best BC₂F₅ families of Pusa6B and PRR78, respectively. RM6100, an STMS marker linked to fertility restorer gene (Rf), was used for marker-assisted selection of Rf gene in an improved version of PRR78. The extent of donor segments in the improved version of Pusa6B was estimated to be <0.97 and <2.15 Mb in the genomic regions flanking xa13 and Xa21, respectively, whereas in improved PRR78, it was estimated to be <2.07 and <3.45 Mb in the corresponding genomic regions. Improved lines of Pusa6B and PRR78 showed yield advantages of up to 8.24 and 5.23%, respectively. The performance of the BB-resistant version of Pusa RH10 produced by intercrossing the improved parental lines was on a par with or superior to the original Pusa RH10.     

Epistasis for Three Grain Yield Components in Rice (Oryza Sativa L.)

The genetic basis for three grain yield components of rice, 1000 kernel weight (KW), grain number per panicle (GN), and grain weight per panicle (GWP), was investigated using restriction fragment length polymorphism markers and F(4) progeny testing from a cross between rice subspecies japonica (cultivar Lemont from USA) and indica (cv. Tequing from China). Following identification of 19 QTL affecting these traits, we investigated the role of epistasis in genetic control of these phenotypes. Among 63 markers distributed throughout the genome that appeared to be involved in 79 highly significant (P < 0.001) interactions, most (46 or 73%) did not appear to have ``main'''' effects on the relevant traits, but influenced the trait(s) predominantly through interactions. These results indicate that epistasis is an important genetic basis for complex traits such as yield components, especially traits of low heritability such as GN and GWP. The identification of epistatic loci is an important step toward resolution of discrepancies between quantitative trait loci mapping and classical genetic dogma, contributes to better understanding of the persistence of quantitative genetic variation in populations, and impels reconsideration of optimal mapping methodology and marker-assisted breeding strategies for improvement of complex traits.     

Fine Mapping of Aroma QTLs in Basmati Rice (Oryza sativa L) on Chromosomes 3, 4 and 8

Aroma is one of the most important quality traits of basmati rice (Oryza sativa L) that leads to high consumer acceptance. Earlier three significant QTLs for aroma, namely aro3-1, aro4-1 and aro8-1, have been mapped on rice chromosomes 3, 4 and 8, respectively, using a population of recombinant inbred lines (RILs) derived from a cross between Pusa 1121 (a basmati quality variety) and Pusa 1342 (a non-aromatic variety). For fine mapping of these QTLs, 184 F₆ RILs were grown in the Kharif season of 2005 at New Delhi and Karnal, India. A total of 115 new SSR markers covering the three QTL intervals were designed and screened for parental polymorphism. Of these, 26 markers were polymorphic between parents, eight for the interval aro3-1, eight for the interval aro4-1 and ten for the interval aro8-1, thus enriching the density of SSR markers in these QTL intervals. Revised genetic maps were constructed by adding 23 of these new markers to the earlier map, by giving physical order of the markers in the pseudomolecules a preference. In the revised maps, the interval for QTL aro4-1 could not be improved further but QTL aro3-1 was narrowed down to an interval of 390 kbp from the earlier reported interval of 8.6 Mbp and similarly the QTL aro8-1 was narrowed down to a physical interval of 430 kbp. The numbers of candidate genes in the aro3-1 and aro8-1 intervals have now been reduced to 51 and 66, respectively. The badh2 gene on chromosome 8 was not associated with the aroma QTL on this chromosome.     

Genome‐wide expression quantitative trait locus studies facilitate isolation of causal genes controlling panicle structure

The morphology of rice (Oryza sativa L.) panicles is an important determinant of grain yield, and elucidation of the genetic control of panicle structure is very important for fulfilling the demand for high yield in breeding programs. In a quantitative trait locus (QTL) study using 82 backcross inbred lines (BILs) derived from Koshihikari and Habataki, 68 QTLs for 25 panicle morphological traits were identified. Gene expression profiling from inflorescence meristems of BILs was obtained. A combination of phenotypic QTL (pQTL) and expression QTL (eQTL) analysis revealed co‐localization between pQTLs and eQTLs, consistent with significant correlations between phenotypic traits and gene expression levels. By combining pQTL and eQTL data, two genes were identified as controlling panicle structure: OsMADS18 modulates the average length of the primary rachis and OsFTL1 has pleiotropic effects on the total number of secondary rachides, number of grains per panicle, plant height and the length of flag leaves. Phenotypes were confirmed in RNA interference knocked‐down plants and overexpressor lines. The combination of pQTL and eQTL analysis could facilitate identification of genes involved in rice panicle formation.     

Simultaneous improvement and genetic dissection of grain yield and its related traits in a backbone parent of hybrid rice (Oryza sativa L.) using selective introgression

Three populations with a total of 125 BC2F3:4 introgression lines (ILs) selected for high yields from three BC2F2 populations were used for genetic dissection of rice yield and its related traits. The progeny testing in replicated phenotyping across two environments and genotyping with 140 polymorphic simple sequence repeat markers allowed the identification of 21 promising ILs that had significantly higher yields than the recurrent parent Shuhui527 (SH527). A total of 94 quantitative trait loci (QTL) were identified using the selective introgression method based on Chi-squared (χ ²) and multi-locus probability tests and the RSTEP-LRT method based on stepwise regression. These QTL were mostly mapped to 12 clusters on seven rice chromosomes. Several important properties of the QTL affecting grain yield (GY) and its related traits were revealed. The first one was the presence of strong and frequent non-random associations between or among QTL that affect low-heritability traits (GY and spikelet number per panicle, SN) in the ILs with high trait values. Second, beneficial alleles at 88.9 % GY and 75 % SN QTL for increased productivity were from the donors, suggesting that direct phenotypic selection for high yield in our introgression breeding program was a powerful way to transfer beneficial alleles at many loci from the donors into SH527. Third, most QTL were in clusters with large effects on multiple traits, which should be the focal points in further investigations and marker-assisted selection in rice. The majority of the QTL identified were expressed only in one of the environments, suggesting that differential expression of QTL in different environments is the primary genetic basis of genotype × environment interaction. Finally, a large variation in both the direction and magnitude of QTL effects was detected for different donor alleles at seven QTL in the same genetic background and environments. This finding suggests the possible presence of functional diversity among the donor alleles at these loci. The promising ILs and QTL identified provide valuable materials and genetic information for further improving the yield potential of SH527, which is a backbone restorer of hybrid rice in China.     

Fine mapping and candidate gene analysis of spd6, responsible for small panicle and dwarfness in wild rice (Oryza rufipogon Griff.)

Identification of genes in rice that affect production and quality is necessary for improving the critical global food source. CSSL58, a chromosome segment substitution line (CSSL) containing a chromosome segment of Oryza rufipogon in the genetic background of the indica cultivar Teqing showed significantly smaller panicles, fewer grains per panicle, smaller grains and dwarfness compared with the recurrent parent Teqing. Genetic analysis of the BC₄F₁ and BC₄F₂ generations, derived from a cross between CSSL58 and Teqing, showed that these traits are controlled by the recessive gene spd6, which mapped to the short arm of chromosome 6. Fine mapping and high-resolution linkage analysis using 24,120 BC₄F₃ plants and markers flanking spd6 were carried out, and the gene was localized to a 22.4 kb region that contains four annotated genes according to the genome sequence of japonica Nipponbare. Phenotypic evaluation of the nearly isogenic line NIL(spd6) revealed that spd6 from wild rice has pleiotropic effects on panicle number per plant, grain size, grain weight, grain number per panicle and plant height, suggesting that this gene might play an important role in the domestication of rice. The discovery of spd6 may ultimately be useful for the design and breeding of crops with high grain yield and quality.     

Genomewide markers as cofactors for precision mapping of quantitative trait loci

In composite interval mapping of quantitative trait loci (QTL), subsets of background markers are used to account for the effects of QTL outside the marker interval being tested. Here, I propose a QTL mapping approach (called G model) that utilizes genomewide markers as cofactors. The G model involves backward elimination on a given chromosome after correcting for genomewide marker effects, calculated under a random effects model, at all the other chromosomes. I simulated a trait controlled by 15 or 30 QTL, mapping populations of N = 96, 192, and 384 recombinant inbreds, and N _M = 192 and 384 evenly spaced markers. In the C model, which utilized subsets of background markers, the number of QTL detected and the number of false positives depended on the number of cofactors used, with five cofactors being too few with N = 384 and 20–40 cofactors being too many with N = 96. A window size of 0 cM for excluding cofactors maintained the number of true QTL detected while decreasing the number of false positives. The number of true QTL detected was generally higher with the G model than with the C model, and the G model led to good control of the type I error rate in simulations where the null hypothesis of no marker–QTL linkage was true. Overall, the results indicated that the G model is useful in QTL mapping because it is less subjective and has equal, if not better, performance when compared with the traditional approach of using subsets of markers to account for background QTL.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

A haplotype inference algorithm for trios based on deterministic sampling

Background

The three-dimensional shape of grain, measured as grain length, width, and thickness (GL, GW, and GT), is one of the most important components of grain appearance in rice. Determining the genetic basis of variations in grain shape could facilitate efficient improvements in grain appearance. In this study, an F_7:8 recombinant inbred line population (RIL) derived from a cross between indica and japonica cultivars (Nanyangzhan and Chuan7) contrasting in grain size was used for quantitative trait locus (QTL) mapping. A genetic linkage map was constructed with 164 simple sequence repeat (SSR) markers. The major aim of this study was to detect a QTL for grain shape and to fine map a minor QTL, qGL7.

Results

Four QTLs for GL were detected on chromosomes 3 and 7, and 10 QTLs for GW and 9 QTLs for GT were identified on chromosomes 2, 3, 5, 7, 9 and 10, respectively. A total of 28 QTLs were identified, of which several are reported for the first time; four major QTLs and six minor QTLs for grain shape were also commonly detected in both years. The minor QTL, qGL7, exhibited pleiotropic effects on GL, GW, GT, 1000-grain weight (TGW), and spikelets per panicle (SPP) and was further validated in a near isogenic F₂ population (NIL-F₂). Finally, qGL7 was narrowed down to an interval between InDel marker RID711 and SSR marker RM6389, covering a 258-kb region in the Nipponbare genome, and cosegregated with InDel markers RID710 and RID76.

Conclusion

Materials with very different phenotypes were used to develop mapping populations to detect QTLs because of their complex genetic background. Progeny tests proved that the minor QTL, qGL7, could display a single mendelian characteristic. Therefore, we suggested that minor QTLs for traits with high heritability could be isolated using a map-based cloning strategy in a large NIL-F₂ population. In addition, combinations of different QTLs produced diverse grain shapes, which provide the ability to breed more varieties of rice to satisfy consumer preferences.