B. P. Mallikarjuna Swamy

qDTY1.1 , a major QTL for rice grain yield under reproductive-stage drought stress with a consistent effect in multiple elite genetic backgrounds

BackgroundDrought is one of the most important abiotic stresses causing drastic reductions in yield in rainfed rice environments. The suitability of grain yield (GY) under drought as a selection criterion has been reported in the past few years. Most of the quantitative trait loci (QTLs) for GY under drought in rice reported so far has been in the background of low-yielding susceptible varieties. Such QTLs have not shown a similar effect in multiple high- yielding drought-susceptible varieties, thus limiting their use in marker-assisted selection. Genetic control of GY under reproductive-stage drought stress (RS) in elite genetic backgrounds was studied in three F3:4 mapping populations derived from crosses of N22, a drought-tolerant aus cultivar, with Swarna, IR64, and MTU1010, three high-yielding popular mega-varieties, with the aim to identify QTLs for GY under RS that show a consistent effect in multiple elite genetic backgrounds. Three populations were phenotyped under RS in the dry seasons (DS) of 2009 and 2010 at IRRI. For genotyping, whole-genome scans for N22/MTU1010 and bulked segregant analysis for N22/Swarna and N22/IR64 were employed using SSR markers.ResultsA major QTL for GY under RS, qDTY1.1 , was identified on rice chromosome 1 flanked by RM11943 and RM431 in all three populations. In combined analysis over two years, qDTY1.1showed an additive effect of 29.3%, 24.3%, and 16.1% of mean yield in N22/Swarna, N22/IR64, and N22/MTU1010, respectively, under RS. qDTY1.1also showed a positive effect on GY in non-stress (NS) situations in N22/Swarna, N22/IR64 over both years, and N22/MTU1010 in DS2009.ConclusionsThis is the first reported QTL in rice with a major and consistent effect in multiple elite genetic backgrounds under both RS and NS situations. Consistency of the QTL effect across different genetic backgrounds makes it a suitable candidate for use in marker-assisted breeding.

Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus.

BackgroundIn the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection. In this study, an attempt was made to locate consistent QTL regions associated with yield increase under drought by applying a genome-wide QTL meta-analysis approach.ResultsThe integration of 15 maps resulted in a consensus map with 531 markers and a total map length of 1821 cM. Fifty-three yield QTL reported in 15 studies were projected on a consensus map and meta-analysis was performed. Fourteen meta-QTL were obtained on seven chromosomes. MQTL1.2, MQTL1.3, MQTL1.4, and MQTL12.1 were around 700 kb and corresponded to a reasonably small genetic distance of 1.8 to 5 cM and they are suitable for use in marker-assisted selection (MAS). The meta-QTL for grain yield under drought coincided with at least one of the meta-QTL identified for root and leaf morphology traits under drought in earlier reports. Validation of major-effect QTL on a panel of random drought-tolerant lines revealed the presence of at least one major QTL in each line. DTY12.1was present in 85% of the lines, followed by DTY4.1in 79% and DTY1.1in 64% of the lines. Comparative genomics of meta-QTL with other cereals revealed that the homologous regions of MQTL1.4 and MQTL3.2 had QTL for grain yield under drought in maize, wheat, and barley respectively. The genes in the meta-QTL regions were analyzed by a comparative genomics approach and candidate genes were deduced for grain yield under drought. Three groups of genes such as stress-inducible genes, growth and development-related genes, and sugar transport-related genes were found in clusters in most of the meta-QTL.ConclusionsMeta-QTL with small genetic and physical intervals could be useful in Marker-assisted selection individually and in combinations. Validation and comparative genomics of the major-effect QTL confirmed their consistency within and across the species. The shortlisted candidate genes can be cloned to unravel the molecular mechanism regulating grain yield under drought.

Genetic, physiological, and gene expression analyses reveal that multiple QTL enhance yield of rice mega-variety IR64 under drought.

Background Rice (Oryza sativa L.) is a highly drought sensitive crop, and most semi dwarf rice varieties suffer severe yield losses from reproductive stage drought stress. The genetic complexity of drought tolerance has deterred the identification of agronomically relevant quantitative trait loci (QTL) that can be deployed to improve rice yield under drought in rice. Convergent evidence from physiological characterization, genetic mapping, and multi-location field evaluation was used to address this challenge. Methodology/Principal Findings Two pairs of backcross inbred lines (BILs) from a cross between drought-tolerant donor Aday Sel and high-yielding but drought-susceptible rice variety IR64 were produced. From six BC4F3 mapping populations produced by crossing the +QTL BILs with the −QTL BILs and IR64, four major-effect QTL - one each on chromosomes 2, 4, 9, and 10 - were identified. Meta-analysis of transcriptome data from the +QTL/−QTL BILs identified differentially expressed genes (DEGs) significantly associated with QTL on chromosomes 2, 4, 9, and 10. Physiological characterization of BILs showed increased water uptake ability under drought. The enrichment of DEGs associated with root traits points to differential regulation of root development and function as contributing to drought tolerance in these BILs. BC4F3-derived lines with the QTL conferred yield advantages of 528 to 1875 kg ha−1 over IR64 under reproductive-stage drought stress in the targeted ecosystems of South Asia. Conclusions/Significance Given the importance of rice in daily food consumption and the popularity of IR64, the BC4F3 lines with multiple QTL could provide higher livelihood security to farmers in drought-prone environments. Candidate genes were shortlisted for further characterization to confirm their role in drought tolerance. Differential yield advantages of different combinations of the four QTL reported here indicate that future research should include optimizing QTL combinations in different genetic backgrounds to maximize yield advantage under drought.

qDTY12.1: a locus with a consistent effect on grain yield under drought in rice.

BackgroundSelection for grain yield under drought is an efficient criterion for improving the drought tolerance of rice. Recently, some drought-tolerant rice varieties have been developed using this selection criterion and successfully released for cultivation in drought-prone target environments. The process can be made more efficient and rapid through marker-assisted breeding, a well-known fast-track approach in crop improvement. QTLs have been identified for grain yield under drought with large effects against drought-susceptible varieties. Most of the identified QTLs show large QTL × environment or QTL × genetic background interactions. The development of mapping populations in the background of popular high-yielding varieties, screening across environments, including the target environments, and the identification of QTLs with a consistent effect across environments can be a suitable alternative marker-assisted breeding strategy. An IR74371-46-1-1 × Sabitri backcross inbred line population was screened for reproductive-stage drought stress at the International Rice Research Institute, Philippines, and Regional Agricultural Research Station, Nepalgunj, Nepal, in the dry and wet seasons of 2011, respectively. A bulk segregant analysis approach was used to identify markers associated with high grain yield under drought.ResultsA QTL, qDTY12.1, significantly associated with grain yield under reproductive-stage drought stress was identified on chromosome 12 with a consistent effect in two environments: IRRI, Philippines, and RARS, Nepalgunj, Nepal. This QTL explained phenotypic variance of 23.8% and contributed an additive effect of 45.3% for grain yield under drought. The positive QTL allele for qDTY12.1 was contributed by tolerant parent IR74371-46-1-1.ConclusionsIn this study, qDTY12.1 showed a consistent effect across environments for high grain yield under lowland reproductive-stage drought stress in the background of popular high-yielding but drought-susceptible recipient variety Sabitri. qDTY12.1 was also reported previously [Crop Sci 47:507–516, 2007] to increase grain yield under upland reproductive-stage drought stress situations. qDTY12.1 is the only QTL reported so far in rice to have shown a large effect against multiple recipient genetic backgrounds as well as under highly diverse upland and lowland rice ecosystems. qDTY12.1 can be successfully introgressed to improve grain yield under drought of popular high-yielding but drought-susceptible lowland as well as upland adapted varieties following marker-assisted breeding.

Drought susceptibility of modern rice varieties: an effect of linkage of drought tolerance with undesirable traits.

Green Revolution (GR) rice varieties are high yielding but typically drought sensitive. This is partly due to the tight linkage between the loci governing plant height and drought tolerance. This linkage is illustrated here through characterization of qDTY1.1, a QTL for grain yield under drought that co-segregates with the GR gene sd1 for semi-dwarf plant height. We report that the loss of the qDTY1.1 allele during the GR was due to its tight linkage in repulsion with the sd1 allele. Other drought-yield QTLs (qDTY) also showed tight linkage with traits rejected in GR varieties. Genetic diversity analysis for 11 different qDTY regions grouped GR varieties separately from traditional drought-tolerant varieties, and showed lower frequency of drought tolerance alleles. The increased understanding and breaking of the linkage between drought tolerance and undesirable traits has led to the development of high-yielding drought-tolerant dwarf lines with positive qDTY alleles and provides new hope for extending the benefits of the GR to drought-prone rice-growing regions.

Increased drought tolerance and wider adaptability of qDTY 12.1 conferred by its interaction with qDTY 2.3 and qDTY 3.2

The genetic basis of high grain yield under reproductive-stage drought was studied using an F3-derived population generated from the cross of upland rice (Oryza sativa L.) cultivars Vandana and Way Rarem. Contributed by the susceptible parent Way Rarem, locus qDTY12.1 was hypothesized to have interaction with loci from the Vandana genome to enhance the grain yield of tolerant line Vandana under drought. A test of the digenic interaction of qDTY12.1 showed that two loci, qDTY2.3 on chromosome 2 and qDTY3.2 on chromosome 3, significantly increased the yield and harvest index of qDTY12.1-positive lines under severe upland and lowland drought conditions. qDTY2.3 and qDTY3.2, in interaction with qDTY12.1, reduced days to flowering and plant height of qDTY12.1-positive lines under stress and non-stress conditions in upland. BC2F3-derived backcross inbred lines (BILs) were used to validate these results and identify new quantitative trait loci. Lines with qDTY2.3 and qDTY12.1 showed increased yield over Way Rarem under severe and moderate stress conditions, in upland. IR84996-50-4-B-4, a selection from one of the BILs, yielded more than the popular drought-tolerant cultivars Apo, UPLRi7, and IR74371-54-1-1 under severe stress conditions. Introgressed segments from Vandana also improved yield under non-stress conditions. The results indicate that digenic interactions can explain the genetic control of complex quantitative traits such as grain yield under drought, and a few interacting loci with large effects on grain yield or yield-related traits may enhance drought response across a wide range of genetic backgrounds and environments when introgressed together.

QTL Analysis for Grain Quality Traits in 2 BC2F2 Populations Derived from Crosses between Oryza sativa cv Swarna and 2 Accessions of O. nivara

The appearance and cooking quality of rice determine its acceptability and price to a large extent. Quantitative trait loci (QTLs) for 12 grain quality traits were mapped in 2 mapping populations derived from Oryza sativa cv Swarna × O. nivara. The BC(2)F(2) population of the cross Swarna × O. nivara IRGC81848 (population 1) was evaluated during 2005 and that from Swarna × O. nivara IRGC81832 (population 2) was evaluated during 2006. Linkage maps were constructed using 100 simple sequence repeat (SSR) markers in population 1 and 75 SSR markers in population 2. In all, 21 QTLs were identified in population 1 (43% from O. nivara) and 37 in population 2 (38% QTLs from O. nivara). The location of O. nivara-derived QTLs mp1.2 for milling percent, kw6.1 for kernel width, and klac12.1 for kernel length after cooking coincided in the 2 populations and appear to be useful for Marker Assisted Selection (MAS). Four QTLs for milling percent, 1 QTL each for amylose content, water uptake, elongation ratio, 2 QTLs for kernel width, and 3 QTLs for gel consistency, each explained more than 20% phenotypic variance. Three QTL clusters for grain quality traits were close to the genes/QTLs for shattering and seed dormancy. QTLs for 4 quality traits were associated with 5 of the 7 major yield QTLs reported in the same 2 mapping populations. Useful introgression lines have been developed for several agronomic traits. It emerges that 40% O. nivara alleles were trait enhancing in both populations, and QTLs for grain quality overlapped with yield meta-QTLs and QTLs for dormancy and seed shattering.

Mapping and introgression of QTL for yield and related traits in two backcross populations derived from Oryza sativa cv. Swarna and two accessions of O. nivara

Advanced backcross QTL (AB-QTL) analysis was carried out in two Oryza nivara-derived BC2F2 populations. For nine traits, we identified 28 QTL in population 1, and 26 QTL in population 2. The two most significant yield-enhancing QTL, yldp9.1 and yldp2.1, showed an additive effect of 16 and 7 g per plant in population 1, while yld2.1 and yld11.1 showed an additive effect of 11 and 10 g per plant in population 2. At least one O. nivara-derived QTL with a phenotypic variance of more than 15% was detected for seven traits in population 1 and three traits in population 2. The O. nivara-derived QTL ph1.1, nt12.1, nsp1.1, nfg1.1, bm11.1,yld2.1, and yld11.1 were conserved at the same chromosomal locations in both populations. Two major QTL clusters were detected at the marker intervals RM488–RM431 and RM6–RM535 on chromosomes 1 and 2, respectively. The co-location of O. nivara-derived yield QTL with yield meta-QTL on chromosomes 1, 2, and 9 indicates their accuracy and consistency. The major-effect QTL reported in this study are useful for marker-assisted breeding and are also suitable for further fine mapping and candidate gene identification.

Molecular Mapping of QTLs for Yield and Yield-Related Traits in Oryza sativa cv Swarna × O. nivara (IRGC81848) Backcross Population

Advanced backcross QTL analysis was used to identify QTLs for seven yield and yield-related traits in a BC2F2 population from the cross between a popular Oryza sativa cv Swarna and O. nivara IRGC81848. Transgressive segregants with more than 15% increased effect over Swarna were observed for all the traits except days to heading and days to 50% flowering. Thirty QTLs were detected for seven yield and yield-related traits using interval and composite interval mapping. Enhancing alleles at 13 (45%) of these QTLs were derived from O. nivara, and enhancing alleles at all the QTLs for stem diameter and rachis diameter were derived from O. nivara. Three stem diameter QTLs, two rachis diameter QTLs and one number of secondary branches QTL identified by both Interval and composite interval mapping contributed more than 15% of the total phenotypic variance. The QTL epistasis was significant for stem diameter and plot yield. The most significant QTLs qSD7.2, qSD8.1 and qSD9.1 for stem diameter, qRD9.1 for rachis diameter and qNSB1.1 for number of secondary branches are good targets to evaluate their use in marker-assisted selection. O. nivara is a good source of novel alleles for yield related traits and reveals major effect QTLs suitable for marker-assisted selection.

Physiological mechanisms contributing to the QTL-combination effects on improved performance of IR64 rice NILs under drought

Highlight Drought-yield QTLs qDTY 2.2 and qDTY 4.1 improved rice variety IR64 complementarily through peak QTL effects at distinct stress levels, and by increasing root hydraulic conductance and root growth at depth.