Genome-wide association mapping and agronomic impact of cowpea root architecture
- 1k Downloads
Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance.
Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.
KeywordsQuantitative Trait Locus Root Trait Root Architecture Phene Root Crown
This work was supported by the Howard G. Buffet Foundation, the USAID Feed the Future Innovation Laboratory for Climate Resilient Beans, and the Feed the Future Innovation Lab for Collaborative Research on Grain Legumes. Genotyping was supported by the CGIAR Generation Challenge Program. This work was also supported by the USDA National Institute of Food and Agriculture, Hatch Project 4372, the NSF Plant Genome Research Program, NSF 0820624 and the Center for Data Analytics, Georgia, Institute of Technology, Spatial Networks in Biology: Organizing and Analyzing the Structure of Distributed Biological Systems. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the National Institute of Food and Agriculture (NIFA) or the United States Department of Agriculture (USDA).
Compliance with ethical standards
The authors declare that they have no conflict of interest.
- Atokple IDK, Singh BB, Emechebe AM (1995) Genetics of resistance to Striga and Alectra in cowpea. J Hered 86:45–49Google Scholar
- Barber S (1995) Soil nutrient bioavailability: a mechanistic approach. Wiley, New YorkGoogle Scholar
- Belko N, Zaman-allah M, Cisse N, Ndack Diop N, Zombre G, Ehlers JD, Vadez V (2012a) Lower soil moisture threshold for transpiration decline under water deficit correlates with lower canopy conductance and higher transpiration efficiency in drought-tolerant cowpea. Funct Plant Biol 39:306–322CrossRefGoogle Scholar
- Fehr W (1993) Principles of cultivar development. Macmillan Publishing Company, New YorkGoogle Scholar
- Huynh B-L, Matthews WC, Ehlers JD, Lucas MR, Santos JRP, Ndeve A, Close TJ, Roberts PA (2016) A major QTL corresponding to the Rk locus for resistance to root-knot nematodes in cowpea (Vigna unguiculata L. Walp.). Theor Appl Genet 129(1):87–95. doi: 10.1007/s00122-015-2611-0 CrossRefPubMedGoogle Scholar
- Kugblenu YO, Kumaga FK, Ofori K, Adu-Gyamfi JJ (2014) Evaluation of cowpea genotypes for phosphorus use efficiency. J Agric Crop Res 2:202–210Google Scholar
- Muchero W, Diop NN, Bhat PR, Fenton RD, Wanamaker S, Pottorft M, Hearne S, Cisse N, Fatokun C, Ehlers JD, Roberts PA, Close TJ (2009) A consensus genetic map of cowpea [Vigna unguiculata (L) Walp.] and synteny based on EST-derived SNPs. Proc Natl Acad Sci USA 106:18159–18164CrossRefPubMedPubMedCentralGoogle Scholar
- Muchero W, Ehlers JD, Close TJ, Roberts PA (2011) Genic SNP markers and legume synteny reveal candidate genes underlying QTL for Macrophomina phaseolina resistance and maturity in cowpea [Vigna unguiculata (L) Walp.]. BMC Genomics 12:8. doi: 10.1186/1471-2164-12-8 CrossRefPubMedPubMedCentralGoogle Scholar
- Muchero W, Roberts PA, Diop NN, Drabo I, Cisse N, Close TJ, Muranaka S, Boukar O, Ehlers JD (2013) Genetic architecture of delayed senescence, biomass, and grain yield under drought stress in cowpea. PLoS One 8:1–10Google Scholar
- Niklas KJ (1994) Plant allometry: the scaling of form and process. University of Chicago Press, ChicagoGoogle Scholar
- Noubissie Tchiagam JB, Bell JM, Guissai Birwe S, Gonne S, Youmbi E (2010) Varietal response of cowpea (Vigna unguiculata (L.) Walp.) to Striga gesnerioides (Willd.) vatke race SG5 infestation. Not Bot Hort Agrobot Cluj 38:33–41Google Scholar
- Omoigui LO, Ishiyaku MF, Ousmane B, Gowda BS, Timko MP (2011) Application of fast technology for analysis (FTA) for sampling and recovery of deoxyribonucleic acid (DNA) for molecular characterization of cowpea breeding lines for Striga resistance. Afr J Biotechnol 10:19681–19686Google Scholar
- Ouedraogo JT, Ouedraogo M, Gowda BS, Timko MP (2012) Development of sequence characterized amplified region (SCAR) markers linked to race-specific resistance to Striga gesnerioides in cowpea (Vigna unguiculata L.). Afr J Biotechnol 11:12555–12562Google Scholar
- Pottorff M, Wanamaker S, Ma YQ, Ehlers JD, Roberts PA, Close TJ (2012) Genetic and Physical Mapping of Candidate Genes for Resistance to Fusarium oxysporum f.sp. tracheiphilum Race 3 in Cowpea [Vigna unguiculata (L.) Walp]. PLoS One 7 (7):e41600. doi: 10.1371/journal.pone.0041600 CrossRefPubMedPubMedCentralGoogle Scholar
- Pottorff MO, Li G, Ehlers JD, Close TJ, Roberts PA (2014) Genetic mapping, synteny, and physical location of two loci for Fusarium oxysporum f. sp. tracheiphilum race 4 resistance in cowpea [Vigna unguiculata (L.) Walp]. Mol Breeding 33(4):779–791. doi: 10.1007/s11032-013-9991-0 CrossRefGoogle Scholar
- R Core Team (2014) R: a language and environment for statistical computingGoogle Scholar
- Rao IM, Beebe SE, Polania J, Grajales M, Cajiao C, Garcia R, Ricaurte J, Rivera M (2009) Physiological basis of improved drought resistance in common bean: the contribution of photosynthate mobilization to grain. Interdrought III: the 3rd international conference on integrated approaches to improve crop production under drought-prone environments, Shanghai, pp 11–16Google Scholar
- Rao I, Beebe S, Polania J, Ricaurte J, Cajiao C, Garcia R, Rivera M (2013) Can Tepary Bean be a model for improvement of drought resistance in Common Bean? Afr Crop Sci J 21:265–281Google Scholar
- Singh BB, Chambliss OL, Sharma B (1997) Recent advances in cowpea breeding. In: Singh BB, Mohan Raj DR, Dashiell KE (eds) Advances in cowpea research. Copublication of International Institute of Tropical Agriculture (IITA) and Japan International Research Center for Agricultural Sciences (JIRCAS). IITA, Ibadan, pp 30–49Google Scholar
- Yadav SS, Hunter D, Redden B, Nang M, Yadava DK, Habibi AB (2015) Impact of climate change on agriculture production, food, and nutritional security. Crop wild relatives and climate change, pp 1–23Google Scholar