Prashant Vikram
International Rice Research Institute
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Featured researches published by Prashant Vikram.
BMC Genetics | 2011
Prashant Vikram; B. P. Mallikarjuna Swamy; Shalabh Dixit; Helal Uddin Ahmed; Ma Teresa Sta Cruz; Alok Kumar Singh; Arvind Kumar
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.
BMC Genomics | 2011
B. P. Mallikarjuna Swamy; Prashant Vikram; Shalabh Dixit; Helaluddin Ahmed; Arvind Kumar
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.
PLOS ONE | 2013
B. P. Mallikarjuna Swamy; Helal Uddin Ahmed; Amelia Henry; Ramil Mauleon; Shalabh Dixit; Prashant Vikram; Ram Tilatto; Satish Verulkar; Puvvada Perraju; Nimai Prasad Mandal; Mukund Variar; S. Robin; Ranganath Chandrababu; Onkar Singh; J.L. Dwivedi; Sankar Prasad Das; Krishna K. Mishra; Ram Baran Yadaw; Tamal Lata Aditya; Biswajit Karmakar; Kouji Satoh; Ali Moumeni; Shoshi Kikuchi; Hei Leung; Arvind Kumar
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.
BMC Genetics | 2013
Krishna Kumar Mishra; Prashant Vikram; Ram Baran Yadaw; B. P. Mallikarjuna Swamy; Shalabh Dixit; Ma Teresa Sta Cruz; Paul T. Maturan; Shailesh Marker; Arvind Kumar
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.
Molecular Breeding | 2012
Shalabh Dixit; B. P. Mallikarjuna Swamy; Prashant Vikram; Jerome Bernier; M. T. Sta Cruz; Modesto Amante; Dinesh Atri; Arvind Kumar
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.
Scientific Reports | 2016
C. Saint Pierre; Juan Burgueño; José Crossa; G. Fuentes Dávila; P. Figueroa López; E. Solís Moya; J. Ireta Moreno; V. M. Hernández Muela; V. M. Zamora Villa; Prashant Vikram; Ky L. Mathews; Carolina Paola Sansaloni; Deepmala Sehgal; Diego Jarquin; Peter Wenzl; Sukhwinder Singh
Genomic and pedigree predictions for grain yield and agronomic traits were carried out using high density molecular data on a set of 803 spring wheat lines that were evaluated in 5 sites characterized by several environmental co-variables. Seven statistical models were tested using two random cross-validations schemes. Two other prediction problems were studied, namely predicting the lines’ performance at one site with another (pairwise-site) and at untested sites (leave-one-site-out). Grain yield ranged from 3.7 to 9.0 t ha−1 across sites. The best predictability was observed when genotypic and pedigree data were included in the models and their interaction with sites and the environmental co-variables. The leave-one-site-out increased average prediction accuracy over pairwise-site for all the traits, specifically from 0.27 to 0.36 for grain yield. Days to anthesis, maturity, and plant height predictions had high heritability and gave the highest accuracy for prediction models. Genomic and pedigree models coupled with environmental co-variables gave high prediction accuracy due to high genetic correlation between sites. This study provides an example of model prediction considering climate data along-with genomic and pedigree information. Such comprehensive models can be used to achieve rapid enhancement of wheat yield enhancement in current and future climate change scenario.
Agricultural research | 2016
Prashant Vikram; Suhas Kadam; Bikram Pratap Singh; You Jin lee; Jitendra Kumar Pal; Sanjay Singh; O. N. Singh; B. P. Mallikarjuna Swamy; Karthikeyan Thiyagarajan; Sukhwinder Singh; Nagendra K. Singh
Genetic diversity analysis based on genome-wide single-nucleotide polymorphism (SNP) assay of a set of Indian rice cultivars including modern high-yielding varieties and landraces revealed two broad groups, one with “Aus” and the other with “Indica” cultivars. Marker analysis of these genotypes was carried out for three major drought tolerance QTLs as well as green revolution gene, sd1. This gene collocates with a drought QTL, qDTY1.1. The well-known drought-tolerant landraces or traditional varieties had the “tall” allele of the sd1 gene, indicating the possibility of close linkage, pleiotropy or both associated with this gene. Profiling of rice genotypes investigated in the present study with drought QTL markers, genome-wide SNPs, and sd1 gene reveals the importance of using multiple genes rather focusing on any single major QTL/gene for drought tolerance. Our results suggested that rice genetic improvement for rain-fed areas require enhanced use of pre-green revolution varieties.
Molecular Breeding | 2017
Shalabh Dixit; Anshuman Singh; Nitika Sandhu; Aditi Bhandari; Prashant Vikram; Arvind Kumar
TDK1 is a popular rice variety from the Lao PDR. Originally developed for irrigated conditions, this variety suffers a high decline in yield under drought conditions. Studies have identified three quantitative trait loci (QTLs) for grain yield under drought conditions, qDTY3.1, qDTY6.1, and qDTY6.2, that show a high effect in the background of this variety. We report here the pyramiding of these three QTLs with SUB1 that provides 2–3 weeks of tolerance to complete submergence, with the aim to develop drought- and submergence-tolerant near-isogenic lines (NILs) of TDK1. We used a tandem approach that combined marker-assisted backcross breeding with phenotypic selection to develop NILs with high yield under drought stress and non-stress conditions and preferred grain quality. The effect of different QTL combinations on yield and yield-related traits under drought stress and non-stress conditions is also reported. Our results show qDTY3.1 to be the largest and most consistent QTL affecting yield under drought conditions, followed by qDTY6.1 and qDTY6.2, respectively. QTL class analysis also showed that lines with a combination of qDTY3.1 and qDTY6.1 consistently showed a higher tolerance to drought than those in which one of these QTLs was missing. In countries such as Lao PDR, where large areas under rice cultivation suffer vegetative-stage submergence and reproductive-stage drought, these lines could ensure yield stability. These lines can also serve as valuable genetic material to be used for further breeding of high-yielding, drought- and submergence-tolerant varieties in local breeding programs.
Theoretical and Applied Genetics | 2012
Shalabh Dixit; B. P. Mallikarjuna Swamy; Prashant Vikram; Helaluddin Ahmed; M. T. Sta Cruz; Modesto Amante; Dinesh Atri; Hei Leung; Arvind Kumar
Field Crops Research | 2012
Krishna Hari Ghimire; Lenie A. Quiatchon; Prashant Vikram; B. P. Mallikarjuna Swamy; Shalabh Dixit; Helaluddin Ahmed; Jose E. Hernandez; Teresita H. Borromeo; Arvind Kumar