12 research outputs found

    Comparative transcriptome analysis reveals molecular regulation of salt tolerance in two contrasting chickpea genotypes

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    Salinity is a major abiotic stress that causes substantial agricultural losses worldwide. Chickpea (Cicer arietinum L.) is an important legume crop but is salt-sensitive. Previous physiological and genetic studies revealed the contrasting response of two desi chickpea varieties, salt-sensitive Rupali and salt-tolerant Genesis836, to salt stress. To understand the complex molecular regulation of salt tolerance mechanisms in these two chickpea genotypes, we examined the leaf transcriptome repertoire of Rupali and Genesis836 in control and salt-stressed conditions. Using linear models, we identified categories of differentially expressed genes (DEGs) describing the genotypic differences: salt-responsive DEGs in Rupali (1,604) and Genesis836 (1,751) with 907 and 1,054 DEGs unique to Rupali and Genesis836, respectively, salt responsive DEGs (3,376), genotype-dependent DEGs (4,170), and genotype-dependent salt-responsive DEGs (122). Functional DEG annotation revealed that the salt treatment affected genes involved in ion transport, osmotic adjustment, photosynthesis, energy generation, stress and hormone signalling, and regulatory pathways. Our results showed that while Genesis836 and Rupali have similar primary salt response mechanisms (common salt-responsive DEGs), their contrasting salt response is attributed to the differential expression of genes primarily involved in ion transport and photosynthesis. Interestingly, variant calling between the two genotypes identified SNPs/InDels in 768 Genesis836 and 701 Rupali salt-responsive DEGs with 1,741 variants identified in Genesis836 and 1,449 variants identified in Rupali. In addition, the presence of premature stop codons was detected in 35 genes in Rupali. This study provides valuable insights into the molecular regulation underpinning the physiological basis of salt tolerance in two chickpea genotypes and offers potential candidate genes for the improvement of salt tolerance in chickpeas

    Crop Updates 2008 - Farming Systems

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    This session covers thirty nine papers from different authors: PLENARY 1. Developments in grain end use, Dr John de Majnik, New Grain Products, GRDC, Mr Paul Meibusch, New Farm Products and Services, GRDC, Mr Vince Logan, New Products Executive Manager, GRDC PRESENTATIONS 2. Global warming potential of wheat production in Western Australia: A life cycle assessment, Louise Barton1, Wahid Biswas2 and Daniel Carter3, 1School of Earth & Geographical Sciences, The University of Western Australia, 2Centre of Excellence in Cleaner Production, Division of Science and Engineering, Curtin University of Technology, 3Department of Agriculture and Food 3. How much fuel does your farm use for different farm operations? Nicolyn Short1, Jodie Bowling1, Glen Riethmuller1, James Fisher2 and Moin Salam1, 1Department of Agriculture and Food, 2Muresk Institute, Curtin University of Technology 4. Poor soil water storage and soil constraints are common in WA cropping soils, Stephen Davies, Jim Dixon, Dennis Van Gool and Alison Slade, Department of Agriculture and Food, Bob Gilkes, School of Earth and Geographical Sciences, University of Western Australia 5. Developing potential adaptations to climate change for low rainfall farming system using economic analysis tool. STEP, Megan Abrahams, Caroline Peek, Dennis Van Gool, Daniel Gardiner and Kari-Lee Falconer, Department of Agriculture and Food 6. What soil limitations affect the profitability of claying on non-wetting sandplain soils? David Hall1, Jeremy Lemon1, Harvey Jones1, Yvette Oliver2 and Tania Butler1, 1Department of Agriculture and Food, 2CSIRO Div Sustainable Ecology, Perth 7. Farming systems adapting to a variable climate; Two case studies, Kari-Lee Falconer, Department of Agriculture and Food 8. Importance of accounting for variation in crop yield potential when making fertiliser decisions, Michael Robertson and Yvette Oliver, CSIRO Sustainable Ecosystems, Floreat 9. Soil acidity is a widespread problem across the Avon River Basin, Stephen Carr1, Chris Gazey2, David York1 and Joel Andrew1, 1Precision SoilTech, 2Department of Agriculture and Food 10. The use of soil testing kits and ion-selective electrodes for the analysis of plant available nutrients in Western Australian soils, Michael Simeoni and Bob Gilkes School of Earth and Geographical Sciences, University of Western Australia 11. Redlegged earth mite resistance and integrated strategies for their control in Western Australia, Mangano G. Peter and Micic Svetlana, Department of Agriculture and Food 12. The economics of treating soil pH (liming), Chris Gazey, Steve Davies, Dave Gartner and Adam Clune, Department of Agriculture and Food, 13. Health benefits – A future differentiator for high value grains, Matthew Morell, Theme Leader, CSIRO Food Futures Flagship 14. Carbon in Sustralian cropping soils – We need to be realistic, Alan Umbers (M Rur Sc), GRDC/DAFF Sustainable Industries Initiative Project 15. AGWEST® Bartolo bladder clover (Trifolium spumosum) − a low cost annual pasture legume for the wheat/sheep zone, Angelo Loi, Brad Nutt and Clinton Revell, Department of Agriculture and Food 16. Maximising the value of point based soil sampling: Monitering trends in soil pH through time, Joel Andrew1, David York1, Stephen Carr1 and Chris Gazey2, 1Precision SoilTech, 2Department of Agriculture and Food 17. Improved crop root growth and productivity with deep ripping and deep placed lime, Stephen Davies1, Geoff Kew2*, Chris Gazey1, David Gartner1 and Adam Clune1, 1Department of Agriculture and Food, 2School of Earth and Geographical Sciences University of Western Australia, *Presenting author 18. The role of pastures in hosting Root Lesion Nematode (RLN, Pratylenchus neglectus), Vivien Vanstone, Ali Bhatti and Ming Pei You, Department of Agriculture and Food 19. To rip or not to rip. When does it pay? Imma Farre, Bill Bowden and Stephen Davies, Department of Agriculture and Food 20. Can yield be predicted from remotely sensed data, Henry Smolinski, Jane Speijers and John Bruce, Department of Agriculture and Food 21. Rotations for profit, David McCarthy and Gary Lang, Facey Group, Wickepin, WA 22. Rewriting rules for the new cropping economics, David Rees, Consultant, Albany 23. Reducing business risk in Binnu! – A case study, Rob Grima, Department of Agriculture and Food 24. Does improved ewe management offer grain farmers much extra profit? John Young, Farming Systems Analysis Service, Ross Kingwell, Department of Agriculture and Food, and UWA, Chris Oldham, Department of Agriculture and Food RESEARCH HIGHLIGHTS 25. Crop establishment and productivity with improved root zone drainage, Dr Derk Bakker, Research Officer, Department of Agriculture and Food 26. Will wheat production in Western Australia be more risky in the future? Imma Farre and Ian Foster, Department of Agriculture and Food PAPERS 27. Building farmers’ adaptive capacity to manage seasonal variability and climate change, David Beard, Department of Agriculture and Food 28. Precision placement increases crop phosphorus uptake under variable rainfall: Simulation studies, Wen Chen1 2, Richard Bell1, Bill Bowden2, Ross Brennan2, Art Diggle2 and Reg Lunt2, 1School of Environmental Science, Murdoch University, 2Department of Agriculture and Food 29. What is the role of grain legumes on red soil farms? Rob Grima, Department of Agriculture and Food 30. Fertiliser placement influences plant growth and seed yield of grain crops at different locations of WA, Qifu Ma1, Zed Rengel1, Bill Bowden2, Ross Brennan2, Reg Lunt2 and Tim Hilder2, 1Soil Science & Plant Nutrition, University of Western Australia, 2Department of Agriculture and Food 31. A review of pest and disease occurrences for 2007, Peter Mangano and Dusty Severtson, Department of Agriculture and Food 32. Effect of stocking rates on grain yield and quality of wheat in Western Australia in 2007, Shahajahan Miyan, Sam Clune, Barb Sage and Tenielle Martin, Department of Agriculture and Food 33. Storing grain is not ‘set and forget’ management, Chris Newman, Department of Agriculture and Food 34. Improving understanding of soil plant available water capacity (PAWC): The WA soil water database (APSoil), Yvette Oliver, Neal Dalgliesh and Michael Robertson, CSIRO Sustainable Ecosystems 35. The impact of management decisions in drought on a low rainfall northern wheatbelt farm, Caroline Peek and Andrew Blake, Department of Agriculture and Food 37. Cullen – A native pasture legume shows promise for the low-medium rainfall cropping zone, Megan Ryan, Richard Bennett, Tim Colmer, Daniel Real, Jiayin Pang, Lori Kroiss, Dion Nicol and Tammy Edmonds-Tibbett, School of Plant Biology, The University of Western Australia and Future Farm Industries CRC 38. Climate risk management tools – useful, or just another gadget? Lisa Sherriff, Kari-Lee Falconer, Daniel Gardiner and Ron McTaggart Department of Agriculture and Food 39. Benefits of crop rotation for management of Root Lesion Nematode (RLN, Pratylenchus neglectus), Vivien Vanstone, Sean Kelly and Helen Hunter, Department of Agriculture and Foo

    Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data

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    Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs

    Investigating drought tolerance in chickpea using genome-wide association mapping and genomic selection based on whole-genome resequencing data

    No full text
    Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs

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    <p>Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.</p
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