Comparative Aerial and Ground Based High Throughput Phenotyping for the Genetic Dissection of NDVI As a Proxy for Drought Adaptive Traits in Durum Wheat

Overview

Journal Front Plant Sci

Date 2018 Jul 13

PMID 29997645

Citations 54

Authors

Giuseppe E Condorelli

Marco Maccaferri

Maria Newcomb

Pedro Andrade-Sanchez

Jeffrey W White

Andrew N French

Giuseppe Sciara

Rick Ward

Roberto Tuberosa

Affiliations

Soon will be listed here.

Abstract

High-throughput phenotyping platforms (HTPPs) provide novel opportunities to more effectively dissect the genetic basis of drought-adaptive traits. This genome-wide association study (GWAS) compares the results obtained with two Unmanned Aerial Vehicles (UAVs) and a ground-based platform used to measure Normalized Difference Vegetation Index (NDVI) in a panel of 248 elite durum wheat ( L. ssp Desf.) accessions at different growth stages and water regimes. Our results suggest increased ability of aerial over ground-based platforms to detect quantitative trait loci (QTL) for NDVI, particularly under terminal drought stress, with 22 and 16 single QTLs detected, respectively, and accounting for 89.6 vs. 64.7% phenotypic variance based on multiple QTL models. Additionally, the durum panel was investigated for leaf chlorophyll content (SPAD), leaf rolling and dry biomass under terminal drought stress. In total, 46 significant QTLs affected NDVI across platforms, 22 of which showed concomitant effects on leaf greenness, 2 on leaf rolling and 10 on biomass. Among 9 QTL hotspots on chromosomes 1A, 1B, 2B, 4B, 5B, 6B, and 7B that influenced NDVI and other drought-adaptive traits, 8 showed effects unrelated to phenology.

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References

Peleg Z, Fahima T, Krugman T, Abbo S, Yakir D, Korol A . Genomic dissection of drought resistance in durum wheat x wild emmer wheat recombinant inbreed line population. Plant Cell Environ. 2009; 32(7):758-79. DOI: 10.1111/j.1365-3040.2009.01956.x. View

Maccaferri M, Sanguineti M, Demontis A, El-Ahmed A, Garcia del Moral L, Maalouf F . Association mapping in durum wheat grown across a broad range of water regimes. J Exp Bot. 2010; 62(2):409-38. DOI: 10.1093/jxb/erq287. View

Evanno G, Regnaut S, Goudet J . Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol. 2005; 14(8):2611-20. DOI: 10.1111/j.1365-294X.2005.02553.x. View

Pinto R, Reynolds M, Mathews K, McIntyre C, Olivares-Villegas J, Chapman S . Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects. Theor Appl Genet. 2010; 121(6):1001-21. PMC: 2938441. DOI: 10.1007/s00122-010-1351-4. View

Price A, Zaitlen N, Reich D, Patterson N . New approaches to population stratification in genome-wide association studies. Nat Rev Genet. 2010; 11(7):459-63. PMC: 2975875. DOI: 10.1038/nrg2813. View

Berger G, Liu S, Hall M, Brooks W, Chao S, Muehlbauer G . Marker-trait associations in Virginia Tech winter barley identified using genome-wide mapping. Theor Appl Genet. 2012; 126(3):693-710. DOI: 10.1007/s00122-012-2011-7. View

Liu W, Maccaferri M, Bulli P, Rynearson S, Tuberosa R, Chen X . Genome-wide association mapping for seedling and field resistance to Puccinia striiformis f. sp. tritici in elite durum wheat. Theor Appl Genet. 2017; 130(4):649-667. DOI: 10.1007/s00122-016-2841-9. View

Christopher J, Christopher M, Borrell A, Fletcher S, Chenu K . Stay-green traits to improve wheat adaptation in well-watered and water-limited environments. J Exp Bot. 2016; 67(17):5159-72. PMC: 5014159. DOI: 10.1093/jxb/erw276. View

Liu Z, Li C, Zhou P, Chen X . A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China. Sci Rep. 2016; 6:35105. PMC: 5054395. DOI: 10.1038/srep35105. View

10.

Rexroad 3rd C, Vallejo R . Estimates of linkage disequilibrium and effective population size in rainbow trout. BMC Genet. 2009; 10:83. PMC: 2800115. DOI: 10.1186/1471-2156-10-83. View

11.

Pinto R, Lopes M, Collins N, Reynolds M . Modelling and genetic dissection of staygreen under heat stress. Theor Appl Genet. 2016; 129(11):2055-2074. PMC: 5069319. DOI: 10.1007/s00122-016-2757-4. View

12.

Pritchard J, Stephens M, Donnelly P . Inference of population structure using multilocus genotype data. Genetics. 2000; 155(2):945-59. PMC: 1461096. DOI: 10.1093/genetics/155.2.945. View

13.

Zhang Z, Ersoz E, Lai C, Todhunter R, Tiwari H, Gore M . Mixed linear model approach adapted for genome-wide association studies. Nat Genet. 2010; 42(4):355-60. PMC: 2931336. DOI: 10.1038/ng.546. View

14.

Gao F, Wen W, Liu J, Rasheed A, Yin G, Xia X . Genome-Wide Linkage Mapping of QTL for Yield Components, Plant Height and Yield-Related Physiological Traits in the Chinese Wheat Cross Zhou 8425B/Chinese Spring. Front Plant Sci. 2016; 6:1099. PMC: 4683206. DOI: 10.3389/fpls.2015.01099. View

15.

Araus J, Cairns J . Field high-throughput phenotyping: the new crop breeding frontier. Trends Plant Sci. 2013; 19(1):52-61. DOI: 10.1016/j.tplants.2013.09.008. View

16.

Money D, Gardner K, Migicovsky Z, Schwaninger H, Zhong G, Myles S . LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms. G3 (Bethesda). 2015; 5(11):2383-90. PMC: 4632058. DOI: 10.1534/g3.115.021667. View

17.

Letta T, Maccaferri M, Badebo A, Ammar K, Ricci A, Crossa J . Searching for novel sources of field resistance to Ug99 and Ethiopian stem rust races in durum wheat via association mapping. Theor Appl Genet. 2013; 126(5):1237-56. DOI: 10.1007/s00122-013-2050-8. View

18.

Shakoor N, Lee S, Mockler T . High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field. Curr Opin Plant Biol. 2017; 38:184-192. DOI: 10.1016/j.pbi.2017.05.006. View

19.

Reynolds M, Tuberosa R . Translational research impacting on crop productivity in drought-prone environments. Curr Opin Plant Biol. 2008; 11(2):171-9. DOI: 10.1016/j.pbi.2008.02.005. View

20.

Yousfi S, Marquez A, Betti M, Araus J, Serret M . Gene expression and physiological responses to salinity and water stress of contrasting durum wheat genotypes. J Integr Plant Biol. 2015; 58(1):48-66. DOI: 10.1111/jipb.12359. View