Advertisement

Theoretical and Applied Genetics

, Volume 130, Issue 2, pp 419–431 | Cite as

Genome-wide association mapping and agronomic impact of cowpea root architecture

  • James D. Burridge
  • Hannah M. Schneider
  • Bao-Lam Huynh
  • Philip A. Roberts
  • Alexander Bucksch
  • Jonathan P. Lynch
Original Article

Abstract

Key message

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.

Abstract

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.

Keywords

Quantitative Trait Locus Root Trait Root Architecture Phene Root Crown 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

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.

Supplementary material

122_2016_2823_MOESM1_ESM.docx (100 kb)
Supplementary material 1 (DOCX 100 kb)

References

  1. Agbicodo EM, Fatokun CA, Muranaka S, Visser RGF, Linden van der CG (2009) Breeding drought tolerant cowpea: constraints, accomplishments, and future prospects. Euphytica 167:353–370CrossRefGoogle Scholar
  2. Atokple IDK, Singh BB, Emechebe AM (1995) Genetics of resistance to Striga and Alectra in cowpea. J Hered 86:45–49Google Scholar
  3. Barber S (1995) Soil nutrient bioavailability: a mechanistic approach. Wiley, New YorkGoogle Scholar
  4. Bayuelo-Jiménez JS, Gallardo-Valdéz M, Pérez-Decelis VA, Magdaleno-Armas L, Ochoa I, Lynch JP (2011) Genotypic variation for root traits of maize (Zea mays L.) from the Purhepecha Plateau under contrasting phosphorus availability. Field Crops Res 121:350–362CrossRefGoogle Scholar
  5. Beebe SE (2012) Common bean breeding in the tropics. In: Janick J (ed) Plant breeding reviews, vol 36. Wiley, New York, pp 357–426CrossRefGoogle Scholar
  6. Beebe SE, Rojas-Pierce M, Yan X, Blair MW, Pedraza F, Muñoz F, Tohme J, Lynch JP (2006) Quantitative trait loci for root architecture traits correlated with phosphorus acquisition in common bean. Crop Sci 46:413–423CrossRefGoogle Scholar
  7. 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
  8. Belko N, Zaman-Allah M, Diop NN, Cisse N, Zombre G, Ehlers JD, Vadez V (2012b) Restriction of transpiration rate under high vapour pressure deficit and non-limiting water conditions is important for terminal drought tolerance in cowpea. Plant Biol 15:304–316CrossRefPubMedGoogle Scholar
  9. Belko N, Cisse N, Diop NN, Zombre G, Thiaw S, Muranaka S, Ehlers JD (2014) Selection for postflowering drought resistance in short- and medium- duration cowpeas using stress tolerance indices. Crop Sci 54:25–33CrossRefGoogle Scholar
  10. Bonser AM, Lynch JP, Snapp S (1996) Effect of phosphorus deficiency on growth angle of basal roots in Phaseolus vulgaris. New Phytol 132:281–288CrossRefPubMedGoogle Scholar
  11. Bucksch A, Burridge J, York LM, Das A, Nord E, Weitz JS, Lynch JP (2014) Image-based high-throughput field phenotyping of crop roots. Plant Physiol 166:470–486CrossRefPubMedPubMedCentralGoogle Scholar
  12. Burridge J, Jochua CN, Bucksch A, Lynch JP (2016) Legume shovelomics: high—throughput phenotyping of common bean (Phaseolus vulgaris L.) and cowpea (Vigna unguiculata subsp, unguiculata) root architecture in the field. Field Crops Res 192:21–32CrossRefGoogle Scholar
  13. Cattivelli L, Rizza F, Badeck FW, Mazzucotelli E, Mastrangelo AM, Francia E, Marè C, Tondelli A, Stanca AM (2008) Drought tolerance improvement in crop plants: an integrated view from breeding to genomics. Field Crops Res 105:1–14CrossRefGoogle Scholar
  14. Das A, Schneider H, Burridge J, Karine A, Ascanio M, Topp CN, Lynch JP, Weitz JS, Bucksch A (2015) Digital Imaging of Root Traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics. Plant Methods 11:1–12CrossRefGoogle Scholar
  15. de Barros I, Gaiser T, Lange F-M, Romheld V (2007) Mineral nutrition and water use patterns of a maize/cowpea intercrop on a highly acidic soil of the tropic semiarid. Field Crops Res 101:26–36CrossRefGoogle Scholar
  16. Ehlers JD, Hall AE (1997) Cowpea (Vigna unguiculata L. Walp). Field Crops Res 53:187–204CrossRefGoogle Scholar
  17. Fehr W (1993) Principles of cultivar development. Macmillan Publishing Company, New YorkGoogle Scholar
  18. Franke AC, Ellis-Jones J, Tarawali G, Schulz S, Hussaini MA, Kureh I, White R, Chikoye D, Douthwaite B, Oyewole BD, Olanrewaju AS (2006) Evaluating and scaling-up integrated Striga hermonthica control technologies among farmers in northern Nigeria. Crop Prot 25:868–878CrossRefGoogle Scholar
  19. Gwathmey OC, Hall AE, Madore MA (1992) Adaptive attributes of cowpea genotypes with delayed monocarpic leaf senescence. Crop Sci 32:765–772CrossRefGoogle Scholar
  20. Hall AE (2012) Phenotyping cowpeas for adaptation to drought. Front Physiol 3:1–8CrossRefGoogle Scholar
  21. Ho MD, Rosas JC, Brown KM, Lynch JP (2005) Root architectural tradeoffs for water and phosphorus acquisition. Funct Plant Biol 32:737–748CrossRefGoogle Scholar
  22. Huynh B, Close TJ, Roberts PA, Hu Z, Wanamaker S, Lucas MR, Chiulele R, Cisse N, David A, Hearne S, Fatokun C, Diop NN, Ehlers JD (2013) Gene pools and the genetic architecture of domesticated cowpea. Plant Genome 6:1–8CrossRefGoogle Scholar
  23. Huynh B-L, Ehlers JD, Ndeve A, Wanamaker S, Lucas MR, Close TJ, Roberts PA (2015) Genetic mapping and legume synteny of aphid resistance in African cowpea (Vigna unguiculata L. Walp.) grown in California. Mol Breeding 35:36. doi: 10.1007/s11032-015-0254-0 CrossRefGoogle Scholar
  24. 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
  25. Kamara AY, Ekeleme F, Jibrin JM, Tarawali G, Tofa I (2014) Agriculture, Ecosystems and environment assessment of level, extent and factors influencing Striga infestation of cereals and cowpea in a Sudan savanna ecology of northern Nigeria. Agric Ecosyst Environ 188:111–121CrossRefGoogle Scholar
  26. Kirkegaard JA, Lilley JM, Howe GN, Graham JM (2007) Impact of subsoil water use on wheat yield. Aust J Agric Res 58:303–315CrossRefGoogle Scholar
  27. 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
  28. Li J, Lis KE, Timko MP (2009) Molecular genetics of race-specific resistance of cowpea to Striga gesnerioides (Willd.). Pest Manag Sci 65:520–527CrossRefPubMedGoogle Scholar
  29. Lipka AE, Tian F, Wang Q, Peiffer J, Li M, Bradbury PJ, Gore MA, Buckler ES, Zhang Z (2012) GAPIT: genome association and prediction integrated tool. Bioinformatics 28:2397–2399CrossRefPubMedGoogle Scholar
  30. Lucas MR, Diop N-N, Wanamaker S, Ehlers JD, Roberts PA, Close TJ (2011) Cowpea–soybean synteny clarified through an improved genetic map. Plant Genome 4:218–225CrossRefGoogle Scholar
  31. Lucas MR, Ehlers JD, Huynh B-L, Diop N-N, Roberts PA, Close TJ (2013a) Markers for breeding heat-tolerant cowpea. Molecular Breeding 31(3):529–536. doi: 10.1007/s11032-012-9810-z CrossRefGoogle Scholar
  32. Lucas MR, Huynh B, Vinholes S, Cisse N, Drabo I, Ehlers JD, Roberts PA, Close TJ (2013b) Association studies and legume synteny reveal haplotypes determining seed size in Vigna unguiculata. Front Plant Sci 4:95. doi: 10.3389/fpls.2013.00095 CrossRefPubMedPubMedCentralGoogle Scholar
  33. Lynch JP (2011) Root phenes for enhanced soil exploration and phosphorus acquisition: tools for future crops. Plant Physiol 156:1041–1049CrossRefPubMedPubMedCentralGoogle Scholar
  34. Lynch JP (2015) Root phenes that reduce the metabolic costs of soil exploration: opportunities for 21st century agriculture. Plant Cell Environ 38:1775–1784CrossRefPubMedGoogle Scholar
  35. Lynch JP, Brown KM (2001) Topsoil foraging—an architectural adaptation of plants to low phosphorus availability. Plant Soil 237:225–237CrossRefGoogle Scholar
  36. Lynch JP, Brown KM (2012) New roots for agriculture: exploiting the root phenome. Philos Trans R Soc Lond Ser B Biol Sci 367:1598–1604CrossRefGoogle Scholar
  37. Lynch JP, Wojciechowski T (2015) Opportunities and challenges in the subsoil: pathways to deeper rooted crops. J Exp Bot 66:2199–2210CrossRefPubMedPubMedCentralGoogle Scholar
  38. Matsui T, Singh BB (2003) Root characteristics in cowpea related to drought tolerance at the seedling stage. Exp Agric 39:29–38CrossRefGoogle Scholar
  39. Miguel MA, Postma JA, Lynch JP (2015) Phene synergism between root hair length and basal root growth angle for phosphorus acquisition. Plant Physiol 167:1430–1439CrossRefPubMedPubMedCentralGoogle Scholar
  40. Miller C, Ochoa I, Nielsen K, Beck D, Lynch JP (2003) Genetic variation for adventitious rooting in response to low phosphorus availability: potential utility for phosphorus acquisition from stratified soils. Funct Plant Biol 30:973–985CrossRefGoogle Scholar
  41. 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
  42. Muchero W, Ehlers JD, Roberts PA (2010) Restriction site polymorphism-based candidate gene mapping for seedling drought tolerance in cowpea [Vigna unguiculata (L.) Walp.]. Theor Appl Genet 120(3):509–518. doi: 10.1007/s00122-009-1171-6 CrossRefPubMedGoogle Scholar
  43. 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
  44. 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
  45. Niklas KJ (1994) Plant allometry: the scaling of form and process. University of Chicago Press, ChicagoGoogle Scholar
  46. Nord EA, Shea K, Lynch JP (2011) Optimizing reproductive phenology in a two-resource world: a dynamic allocation model of plant growth predicts later reproduction in phosphorus-limited plants. Ann Bot 108:391–404. doi: 10.1093/aob/mcr143 CrossRefPubMedPubMedCentralGoogle Scholar
  47. 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
  48. 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
  49. Ouedraogo J, Maheshwari V, Berner D, St Pierre C-A, Belzile F, Timko M (2001) Identification of AFLP markers linked to resistance of cowpea (Vigna unguiculata L.) to parasitism by Striga gesnerioides. Theor Appl Genet 102:1029–1036CrossRefGoogle Scholar
  50. 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
  51. Ouédraogo JT, Tignedre J-B, Timko MP, Belzile FJ (2002) AFLP markers linked to resistance against Striga gesnerioides race 1 in cowpea (Vigna unguiculata). Genome 45(5):787–793. doi: 10.1139/G02-043 CrossRefPubMedGoogle Scholar
  52. Parniske M (2008) Arbuscular mycorrhiza: the mother of plant root endosymbioses. Nat Rev Microbiol 6:763–775CrossRefPubMedGoogle Scholar
  53. 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
  54. 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
  55. R Core Team (2014) R: a language and environment for statistical computingGoogle Scholar
  56. 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
  57. 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
  58. Rubiales D, Fernández-Aparicio M (2012) Innovations in parasitic weeds management in legume crops. A review. Agron Sustain Dev 32:433–449CrossRefGoogle Scholar
  59. Serebrovsky AS (1925) ‘Somatic segreation’ in domestic fowl. J Genet 16:33–42CrossRefGoogle Scholar
  60. 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
  61. Singh BB, Ajeigbe HA, Tarawali SA, Fernandez-Rivera S, Abubakar M (2003) Improving the production and utilization of cowpea as food and fodder. Field Crops Res 84:169–177CrossRefGoogle Scholar
  62. Vadez V, Soltani A, Sinclair TR (2012) Modelling possible benefits of root related traits to enhance terminal drought adaptation of chickpea. Field Crops Res 137:108–115CrossRefGoogle Scholar
  63. Vadez V, Kholová J, Yadav RS, Hash CT (2013) Small temporal differences in water uptake among varieties of pearl millet (Pennisetum glaucum (L.) R. Br.) are critical for grain yield under terminal drought. Plant Soil 371:447–462CrossRefGoogle Scholar
  64. Van Delft GJ, Graves JD, Fitter AH, Van Ast A (2000) Striga seed avoidance by deep planting and no-tillage in sorghum and maize. Int J Pest Manag 46:251–256CrossRefGoogle Scholar
  65. Varshney RK, Terauchi R, McCouch SR (2014) Harvesting the promising fruits of genomics: applying genome sequencing technologies to crop breeding. PLoS Biol 12(6):e1001883CrossRefPubMedPubMedCentralGoogle Scholar
  66. White JW, Singh SP (1991) Sources and inheritance of earliness in tropically adapted indeterminate common bean. Euphytica 55:15–19CrossRefGoogle Scholar
  67. 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
  68. York LM, Nord EA, Lynch JP (2013) Integration of root phenes for soil resource acquisition. Front Plant Sci 4:1–15CrossRefGoogle Scholar
  69. Zhang Z, Ersoz E, Lai C-Q, Todhunter RJ, Tiwari HK, Gore MA, Bradbury PJ, Yu J, Arnett DK, Ordovas JM, Buckler ES (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42:355–360CrossRefPubMedPubMedCentralGoogle Scholar
  70. Zhu J, Brown KM, Lynch JP (2010) Root cortical aerenchyma improves the drought tolerance of maize (Zea mays L.). Plant Cell Environ 33:740–749PubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • James D. Burridge
    • 1
  • Hannah M. Schneider
    • 1
  • Bao-Lam Huynh
    • 2
  • Philip A. Roberts
    • 2
  • Alexander Bucksch
    • 3
  • Jonathan P. Lynch
    • 1
  1. 1.Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkUSA
  2. 2.Department of NematologyUniversity of CaliforniaRiversideUSA
  3. 3.Schools of Biology and Interactive ComputingGeorge Institute of TechnologyAtlantaUSA

Personalised recommendations