Journal articles 2014
Documents
Two in one sweep: aluminum tolerance and grain yield in P-limited soils are associated to the same genomic region in West African Sorghum
Leiser WL, Rattunde HFW, Weltzien E, Cisse N, Abdou M, Diallo A, Tourè AO, Magalhaes JV and Haussmann BIG (2014). Two in one sweep: aluminum tolerance and grain yield in P-limited soils are associated to the same genomic region in West African Sorghum. BMC Plant Biology 14:206 (DOI:10.1186/s12870-014-0206-6). (G7010.03.03)
Abstract: Background Sorghum (Sorghum bicolor L. Moench) productivity is severely impeded by low phosphorus (P) and aluminum (Al) toxic soils in sub-Saharan Africa and especially West Africa (WA). Improving productivity of this staple crop under these harsh conditions is crucial to improve food security and farmer’s incomes in WA.
Results This is the first study to examine the genetics underlying sorghum adaptation to phosphorus limitation in a wide range of WA growing conditions. A set of 187 diverse sorghum genotypes were grown in 29 –P and + P field experiments from 2006-2012 in three WA countries. Sorghum grain yield performance under –P and + P conditions was highly correlated (r = 0.85***). Significant genotype-by-phosphorus interaction was detected but with small magnitude compared to the genotype variance component. We observed high genetic diversity within our panel, with rapid linkage disequilibrium decay, confirming recent sequence based studies in sorghum. Using genome wide association mapping based on 220 934 SNPs we identified one genomic region on chromosome 3 that was highly associated to grain yield production. A major Al-tolerance gene in sorghum, SbMATE, was collocated in this region and SbMATE specific SNPs showed very high associations to grain yield production, especially under –P conditions, explaining up to 16% of the genotypic variance.
Conclusion The results suggest that SbMATE has a possible pleiotropic role in providing tolerance to two of the most serious abiotic stresses for sorghum in WA, Al toxicity and P deficiency. The identified SNPs can help accelerate breeding for increased sorghum productivity under unfavorable soil conditions and contribute to assuring food security in WA.
Leiser WL, Rattunde HFW, Weltzien E, Cisse N, Abdou M, Diallo A, Tourè AO, Magalhaes JV and Haussmann BIG (2014). Two in one sweep: aluminum tolerance and grain yield in P-limited soils are associated to the same genomic region in West African Sorghum. BMC Plant Biology 14:206 (DOI:10.1186/s12870-014-0206-6). (G7010.03.03)
Abstract: Background Sorghum (Sorghum bicolor L. Moench) productivity is severely impeded by low phosphorus (P) and aluminum (Al) toxic soils in sub-Saharan Africa and especially West Africa (WA). Improving productivity of this staple crop under these harsh conditions is crucial to improve food security and farmer’s incomes in WA.
Results This is the first study to examine the genetics underlying sorghum adaptation to phosphorus limitation in a wide range of WA growing conditions. A set of 187 diverse sorghum genotypes were grown in 29 –P and + P field experiments from 2006-2012 in three WA countries. Sorghum grain yield performance under –P and + P conditions was highly correlated (r = 0.85***). Significant genotype-by-phosphorus interaction was detected but with small magnitude compared to the genotype variance component. We observed high genetic diversity within our panel, with rapid linkage disequilibrium decay, confirming recent sequence based studies in sorghum. Using genome wide association mapping based on 220 934 SNPs we identified one genomic region on chromosome 3 that was highly associated to grain yield production. A major Al-tolerance gene in sorghum, SbMATE, was collocated in this region and SbMATE specific SNPs showed very high associations to grain yield production, especially under –P conditions, explaining up to 16% of the genotypic variance.
Conclusion The results suggest that SbMATE has a possible pleiotropic role in providing tolerance to two of the most serious abiotic stresses for sorghum in WA, Al toxicity and P deficiency. The identified SNPs can help accelerate breeding for increased sorghum productivity under unfavorable soil conditions and contribute to assuring food security in WA.
Full article
A chromosomal genomics approach to assess and validate the desi and kabuli draft chickpea genome assemblies
Ruperao P, Chan CKK, Azam S, Karafiátová M, Hayashi S, Čížková J, Saxena RK, Šimková H, Song C, Vrána J, Chitikineni A, Visendi P, Gaur PM, Millán T, Singh KB, Taran B, Wang J, Batley J, Doležel J, Varshney RK and Edwards D (2014). A chromosomal genomics approach to assess and validate the desi and kabuli draft chickpea genome assemblies. Plant Biotechnology Journal 12:778–786 (DOI: 10.1111/pbi.12182). Not open access; view abstract.
Ruperao P, Chan CKK, Azam S, Karafiátová M, Hayashi S, Čížková J, Saxena RK, Šimková H, Song C, Vrána J, Chitikineni A, Visendi P, Gaur PM, Millán T, Singh KB, Taran B, Wang J, Batley J, Doležel J, Varshney RK and Edwards D (2014). A chromosomal genomics approach to assess and validate the desi and kabuli draft chickpea genome assemblies. Plant Biotechnology Journal 12:778–786 (DOI: 10.1111/pbi.12182). Not open access; view abstract.
Structural variations in plant genomes
Saxena RK, Edwards D and Varshney RK (2014). Structural variations in plant genomes. Briefings in Functional Genomics 13(4):296-307 (DOI: 10.1093/bfgp/elu016).
Abstract: Differences between plant genomes range from single nucleotide polymorphisms to large-scale duplications, deletions and rearrangements. The large polymorphisms are termed structural variants (SVs). SVs have received significant attention in human genetics and were found to be responsible for various chronic diseases. However, little effort has been directed towards understanding the role of SVs in plants. Many recent advances in plant genetics have resulted from improvements in high-resolution technologies for measuring SVs, including microarray-based techniques, and more recently, high-throughput DNA sequencing. In this review we describe recent reports of SV in plants and describe the genomic technologies currently used to measure these SVs.
Saxena RK, Edwards D and Varshney RK (2014). Structural variations in plant genomes. Briefings in Functional Genomics 13(4):296-307 (DOI: 10.1093/bfgp/elu016).
Abstract: Differences between plant genomes range from single nucleotide polymorphisms to large-scale duplications, deletions and rearrangements. The large polymorphisms are termed structural variants (SVs). SVs have received significant attention in human genetics and were found to be responsible for various chronic diseases. However, little effort has been directed towards understanding the role of SVs in plants. Many recent advances in plant genetics have resulted from improvements in high-resolution technologies for measuring SVs, including microarray-based techniques, and more recently, high-throughput DNA sequencing. In this review we describe recent reports of SV in plants and describe the genomic technologies currently used to measure these SVs.
Selection of sorghum hybrids grown under aluminum saturation
Menezes CB, Carvalho Junior GA, Silva LA, Bernardino KC, Magalhães JV, Guimarães CT, Guimarães LJM and Schaffert RE (2014). Selection of sorghum hybrids grown under aluminum saturation. Genetics and Molecular Research 13(3):5964–5973 (DOI: 10.4238/2014.August.7.12).
Abstract: The purpose of this study was to evaluate 165 hybrids derived from lines previously selected for aluminum (Al) tolerance. Nine check cultivars were used, eight commercial hybrids and one experimental hybrid. Hybrids were evaluated at three levels of Al saturation (0, 20 and 40% on average). The differences between the environments were significant. Environment with 0% Al saturation yielded 29.5% more than that with 40% Al saturation, showing the importance of genotype selection for acid soils. The best check cultivar was the hybrid DKB550. The hybrids AG1020 and AG1040 also performed well, where the latter was more tolerant but the former more responsive to environment improvement. The hybrid BRS304 was susceptible to high levels of Al saturation. The three commercial BRS hybrids (BRS310, BRS330 and BRS332) performed better than BRS304 at high Al saturation. The hybrid BRS330 was the best BRS hybrid to grow on a field with high Al saturation. The hybrid DKB559 performed well at high Al saturation but did not respond to environment improvement. The hybrids 727029, 727039, 729041, 729095, 729109, AG1040, and DKB550 were tolerant to higher levels of Al saturation and responsive to environment improvement, and showed good stability and adaptability at both low and high Al saturation.
Menezes CB, Carvalho Junior GA, Silva LA, Bernardino KC, Magalhães JV, Guimarães CT, Guimarães LJM and Schaffert RE (2014). Selection of sorghum hybrids grown under aluminum saturation. Genetics and Molecular Research 13(3):5964–5973 (DOI: 10.4238/2014.August.7.12).
Abstract: The purpose of this study was to evaluate 165 hybrids derived from lines previously selected for aluminum (Al) tolerance. Nine check cultivars were used, eight commercial hybrids and one experimental hybrid. Hybrids were evaluated at three levels of Al saturation (0, 20 and 40% on average). The differences between the environments were significant. Environment with 0% Al saturation yielded 29.5% more than that with 40% Al saturation, showing the importance of genotype selection for acid soils. The best check cultivar was the hybrid DKB550. The hybrids AG1020 and AG1040 also performed well, where the latter was more tolerant but the former more responsive to environment improvement. The hybrid BRS304 was susceptible to high levels of Al saturation. The three commercial BRS hybrids (BRS310, BRS330 and BRS332) performed better than BRS304 at high Al saturation. The hybrid BRS330 was the best BRS hybrid to grow on a field with high Al saturation. The hybrid DKB559 performed well at high Al saturation but did not respond to environment improvement. The hybrids 727029, 727039, 729041, 729095, 729109, AG1040, and DKB550 were tolerant to higher levels of Al saturation and responsive to environment improvement, and showed good stability and adaptability at both low and high Al saturation.
Genomics-assisted breeding for drought tolerance in chickpea
Thudi M, Gaur PM, Krishnamurthy L, Mir RR, Kudapa H, Fikre A, Kimurto P, Tripathi S, Soren KR, Mulwa R, Bharadwaj C, Datta S, Chaturvedi SK and Varshney RK (2014). Genomics-assisted breeding for drought tolerance in chickpea. Functional Plant Biology 41(11):1178–1190 (DOI: 10.1071/FP13318).
Abstract: Terminal drought is one of the major constraints in chickpea (Cicer arietinum L.), causing more than 50% production losses. With the objective of accelerating genetic understanding and crop improvement through genomics-assisted breeding, a draft genome sequence has been assembled for the CDC Frontier variety. In this context, 544.73 Mb of sequence data were assembled, capturing of 73.8% of the genome in scaffolds. In addition, large-scale genomic resources including several thousand simple sequence repeats and several million single nucleotide polymorphisms, high-density diversity array technology (15 360 clones) and Illumina GoldenGate assay genotyping platforms, high-density genetic maps and transcriptome assemblies have been developed. In parallel, by using linkage mapping approach, one genomic region harbouring quantitative trait loci for several drought tolerance traits has been identified and successfully introgressed in three leading chickpea varieties (e.g. JG 11, Chefe, KAK 2) by using a marker-assisted backcrossing approach. A multilocation evaluation of these marker-assisted backcrossing lines provided several lines with 10–24% higher yield than the respective recurrent parents.Modern breeding approaches like marker-assisted recurrent selection and genomic selection are being deployed for enhancing drought tolerance in chickpea. Some novel mapping populations such as multiparent advanced generation intercross and nested association mapping populations are also being developed for trait mapping at higher resolution, as well as for enhancing the genetic base of chickpea. Such advances in genomics and genomics-assisted breeding will accelerate precision and efficiency in breeding for stress tolerance in chickpea.
Thudi M, Gaur PM, Krishnamurthy L, Mir RR, Kudapa H, Fikre A, Kimurto P, Tripathi S, Soren KR, Mulwa R, Bharadwaj C, Datta S, Chaturvedi SK and Varshney RK (2014). Genomics-assisted breeding for drought tolerance in chickpea. Functional Plant Biology 41(11):1178–1190 (DOI: 10.1071/FP13318).
Abstract: Terminal drought is one of the major constraints in chickpea (Cicer arietinum L.), causing more than 50% production losses. With the objective of accelerating genetic understanding and crop improvement through genomics-assisted breeding, a draft genome sequence has been assembled for the CDC Frontier variety. In this context, 544.73 Mb of sequence data were assembled, capturing of 73.8% of the genome in scaffolds. In addition, large-scale genomic resources including several thousand simple sequence repeats and several million single nucleotide polymorphisms, high-density diversity array technology (15 360 clones) and Illumina GoldenGate assay genotyping platforms, high-density genetic maps and transcriptome assemblies have been developed. In parallel, by using linkage mapping approach, one genomic region harbouring quantitative trait loci for several drought tolerance traits has been identified and successfully introgressed in three leading chickpea varieties (e.g. JG 11, Chefe, KAK 2) by using a marker-assisted backcrossing approach. A multilocation evaluation of these marker-assisted backcrossing lines provided several lines with 10–24% higher yield than the respective recurrent parents.Modern breeding approaches like marker-assisted recurrent selection and genomic selection are being deployed for enhancing drought tolerance in chickpea. Some novel mapping populations such as multiparent advanced generation intercross and nested association mapping populations are also being developed for trait mapping at higher resolution, as well as for enhancing the genetic base of chickpea. Such advances in genomics and genomics-assisted breeding will accelerate precision and efficiency in breeding for stress tolerance in chickpea.
A SSR kit to study genetic diversity in chickpea (Cicer arietinum L.)
Varshney RK, Thudi M, Upadhyaya H, Dwivedi S, Udupa S, Furman B, Baum M and Hoisington D (2014). A SSR kit to study genetic diversity in chickpea (Cicer arietinum L.). Plant Genetic Resources 12(S):S118–S120 (DOI: 10.1017/S1479262114000392). Not open access; view abstract.
Varshney RK, Thudi M, Upadhyaya H, Dwivedi S, Udupa S, Furman B, Baum M and Hoisington D (2014). A SSR kit to study genetic diversity in chickpea (Cicer arietinum L.). Plant Genetic Resources 12(S):S118–S120 (DOI: 10.1017/S1479262114000392). Not open access; view abstract.
Identification of QTLs for seedling vigor in winter wheat
Li X-M, Chen X-M, Xiao Y-G, Xia X-C, Wang D-S, He Z-H and Wang H-J (2014). Identification of QTLs for seedling vigor in winter wheat. Euphytica 198(2):199–209 (DOI: 10.1007/s10681-014-1092-6). Not open access; view abstract. (G7010.02.01)
Li X-M, Chen X-M, Xiao Y-G, Xia X-C, Wang D-S, He Z-H and Wang H-J (2014). Identification of QTLs for seedling vigor in winter wheat. Euphytica 198(2):199–209 (DOI: 10.1007/s10681-014-1092-6). Not open access; view abstract. (G7010.02.01)
High throughput screening of rooting depth in rice using buried herbicide
Al-Shugeairy Z, Islam MS, Shrestha R, Al-Ogaidi F, Norton GJ and Price AH (2014). High throughput screening of rooting depth in rice using buried herbicide. Annals of Applied Biology 165(1):96–107 (DOI: 10.1111/aab.12118). Not open access; view abstract. (G3008.06)
Al-Shugeairy Z, Islam MS, Shrestha R, Al-Ogaidi F, Norton GJ and Price AH (2014). High throughput screening of rooting depth in rice using buried herbicide. Annals of Applied Biology 165(1):96–107 (DOI: 10.1111/aab.12118). Not open access; view abstract. (G3008.06)
Exploring germplasm diversity to understand the domestication process in Cicer spp. using SNP and DArT markers
Roorkiwal M, von Wettberg EJ, Upadhyaya HD, Warschefsky E, Rathore A and Varshney RK (2014). Exploring germplasm diversity to understand the domestication process in Cicer spp. using SNP and DArT markers. PLoS ONE 9(7):e102016 (DOI: 10.1371/journal.pone.0102016).
Abstract: To estimate genetic diversity within and between 10 interfertile Cicer species (94 genotypes) from the primary, secondary and tertiary gene pool, we analysed 5,257 DArT markers and 651 KASPar SNP markers. Based on successful allele calling in the tertiary gene pool, 2,763 DArT and 624 SNP markers that are polymorphic between genotypes from the gene pools were analyzed further. STRUCTURE analyses were consistent with 3 cultivated populations, representing kabuli, desi and pea-shaped seed types, with substantial admixture among these groups, while two wild populations were observed using DArT markers. AMOVA was used to partition variance among hierarchical sets of landraces and wild species at both the geographical and species level, with 61% of the variation found between species, and 39% within species. Molecular variance among the wild species was high (39%) compared to the variation present in cultivated material (10%). Observed heterozygosity was higher in wild species than the cultivated species for each linkage group. Our results support the Fertile Crescent both as the center of domestication and diversification of chickpea. The collection used in the present study covers all the three regions of historical chickpea cultivation, with the highest diversity in the Fertile Crescent region. Shared alleles between different gene pools suggest the possibility of gene flow among these species or incomplete lineage sorting and could indicate complicated patterns of divergence and fusion of wild chickpea taxa in the past.
Roorkiwal M, von Wettberg EJ, Upadhyaya HD, Warschefsky E, Rathore A and Varshney RK (2014). Exploring germplasm diversity to understand the domestication process in Cicer spp. using SNP and DArT markers. PLoS ONE 9(7):e102016 (DOI: 10.1371/journal.pone.0102016).
Abstract: To estimate genetic diversity within and between 10 interfertile Cicer species (94 genotypes) from the primary, secondary and tertiary gene pool, we analysed 5,257 DArT markers and 651 KASPar SNP markers. Based on successful allele calling in the tertiary gene pool, 2,763 DArT and 624 SNP markers that are polymorphic between genotypes from the gene pools were analyzed further. STRUCTURE analyses were consistent with 3 cultivated populations, representing kabuli, desi and pea-shaped seed types, with substantial admixture among these groups, while two wild populations were observed using DArT markers. AMOVA was used to partition variance among hierarchical sets of landraces and wild species at both the geographical and species level, with 61% of the variation found between species, and 39% within species. Molecular variance among the wild species was high (39%) compared to the variation present in cultivated material (10%). Observed heterozygosity was higher in wild species than the cultivated species for each linkage group. Our results support the Fertile Crescent both as the center of domestication and diversification of chickpea. The collection used in the present study covers all the three regions of historical chickpea cultivation, with the highest diversity in the Fertile Crescent region. Shared alleles between different gene pools suggest the possibility of gene flow among these species or incomplete lineage sorting and could indicate complicated patterns of divergence and fusion of wild chickpea taxa in the past.
An Integrated SNP Mining and Utilization (ISMU) pipeline for next generation sequencing data
Azam S, Rathore A, Shah TM, Telluri M, Amindala B, Ruperao P, Katta MAVS and Varshney RK (2014). An Integrated SNP Mining and Utilization (ISMU) pipeline for next generation sequencing data. PLoS ONE 9(7):e101754 (DOI:10.1371/journal.pone.0101754).
Abstract: Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.
Azam S, Rathore A, Shah TM, Telluri M, Amindala B, Ruperao P, Katta MAVS and Varshney RK (2014). An Integrated SNP Mining and Utilization (ISMU) pipeline for next generation sequencing data. PLoS ONE 9(7):e101754 (DOI:10.1371/journal.pone.0101754).
Abstract: Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.
