Genetic Control of Water Use Efficiency and Leaf Carbon Isotope Discrimination in Sunflower (Helianthus Annuus L.) Subjected to Two Drought Scenarios

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2014 Jul 4

PMID 24992022

Citations 17

Authors

Afifuddin Latif Adiredjo

Olivier Navaud

Stephane Munos

Nicolas B Langlade

Thierry Lamaze

Philippe Grieu

Affiliations

Soon will be listed here.

Abstract

High water use efficiency (WUE) can be achieved by coordination of biomass accumulation and water consumption. WUE is physiologically and genetically linked to carbon isotope discrimination (CID) in leaves of plants. A population of 148 recombinant inbred lines (RILs) of sunflower derived from a cross between XRQ and PSC8 lines was studied to identify quantitative trait loci (QTL) controlling WUE and CID, and to compare QTL associated with these traits in different drought scenarios. We conducted greenhouse experiments in 2011 and 2012 by using 100 balances which provided a daily measurement of water transpired, and we determined WUE, CID, biomass and cumulative water transpired by plants. Wide phenotypic variability, significant genotypic effects, and significant negative correlations between WUE and CID were observed in both experiments. A total of nine QTL controlling WUE and eight controlling CID were identified across the two experiments. A QTL for phenotypic response controlling WUE and CID was also significantly identified. The QTL for WUE were specific to the drought scenarios, whereas the QTL for CID were independent of the drought scenarios and could be found in all the experiments. Our results showed that the stable genomic regions controlling CID were located on the linkage groups 06 and 13 (LG06 and LG13). Three QTL for CID were co-localized with the QTL for WUE, biomass and cumulative water transpired. We found that CID and WUE are highly correlated and have common genetic control. Interestingly, the genetic control of these traits showed an interaction with the environment (between the two drought scenarios and control conditions). Our results open a way for breeding higher WUE by using CID and marker-assisted approaches and therefore help to maintain the stability of sunflower crop production.

Citing Articles

Genome-wide identification and characterization of protein phosphatase 2C (PP2C) gene family in sunflower (Helianthus annuus L.) and their expression profiles in response to multiple abiotic stresses.

Akter N, Islam M, Rahman M, Zohra F, Rahman S, Manirujjaman M PLoS One. 2024; 19(3):e0298543.

PMID: 38507444 PMC: 10954154. DOI: 10.1371/journal.pone.0298543.

Identification of loci associated with water use efficiency and symbiotic nitrogen fixation in soybean.

Arifuzzaman M, Mamidi S, Sanz-Saez A, Zakeri H, Scaboo A, Fritschi F Front Plant Sci. 2023; 14:1271849.

PMID: 38034552 PMC: 10687445. DOI: 10.3389/fpls.2023.1271849.

Agricultural Parameters and Essential Oil Content Composition Prediction of Aniseed, Based on Growing Year, Locality and Fertilization Type-An Artificial Neural Network Approach.

Pezo L, Loncar B, Sovljanski O, Tomic A, Travicic V, Pezo M Life (Basel). 2022; 12(11).

PMID: 36362877 PMC: 9694612. DOI: 10.3390/life12111722.

Variations in Plant Water Use Efficiency Response to Manipulated Precipitation in a Temperate Grassland.

Hai X, Li J, Li J, Liu Y, Dong L, Wang X Front Plant Sci. 2022; 13:881282.

PMID: 35665164 PMC: 9162798. DOI: 10.3389/fpls.2022.881282.

The genetic basis of water-use efficiency and yield in lettuce.

Damerum A, Smith H, Clarkson G, Truco M, Michelmore R, Taylor G BMC Plant Biol. 2021; 21(1):237.

PMID: 34044761 PMC: 8157645. DOI: 10.1186/s12870-021-02987-7.

References

Al-Chaarani G, Gentzbittel L, Huang X, Sarrafi A . Genotypic variation and identification of QTLs for agronomic traits, using AFLP and SSR markers in RILs of sunflower (Helianthus annuus L.). Theor Appl Genet. 2004; 109(7):1353-60. DOI: 10.1007/s00122-004-1770-1. View

Martin B, Thorstenson Y . Stable Carbon Isotope Composition (deltaC), Water Use Efficiency, and Biomass Productivity of Lycopersicon esculentum, Lycopersicon pennellii, and the F(1) Hybrid. Plant Physiol. 1988; 88(1):213-7. PMC: 1055551. DOI: 10.1104/pp.88.1.213. View

Jourjon M, Jasson S, Marcel J, Ngom B, Mangin B . MCQTL: multi-allelic QTL mapping in multi-cross design. Bioinformatics. 2004; 21(1):128-30. DOI: 10.1093/bioinformatics/bth481. View

Zhang Q . Strategies for developing Green Super Rice. Proc Natl Acad Sci U S A. 2007; 104(42):16402-9. PMC: 2034246. DOI: 10.1073/pnas.0708013104. View

Condon A, Richards R, Rebetzke G, Farquhar G . Breeding for high water-use efficiency. J Exp Bot. 2004; 55(407):2447-60. DOI: 10.1093/jxb/erh277. View

Rebetzke G, Condon A, Farquhar G, Appels R, Richards R . Quantitative trait loci for carbon isotope discrimination are repeatable across environments and wheat mapping populations. Theor Appl Genet. 2008; 118(1):123-37. DOI: 10.1007/s00122-008-0882-4. View

de Givry S, Bouchez M, Chabrier P, Milan D, Schiex T . CARHTA GENE: multipopulation integrated genetic and radiation hybrid mapping. Bioinformatics. 2004; 21(8):1703-4. DOI: 10.1093/bioinformatics/bti222. View

Collins N, Tardieu F, Tuberosa R . Quantitative trait loci and crop performance under abiotic stress: where do we stand?. Plant Physiol. 2008; 147(2):469-86. PMC: 2409033. DOI: 10.1104/pp.108.118117. View

Via S, Gomulkiewicz R, de Jong G, Scheiner S, Schlichting C, van Tienderen P . Adaptive phenotypic plasticity: consensus and controversy. Trends Ecol Evol. 2011; 10(5):212-7. DOI: 10.1016/s0169-5347(00)89061-8. View

10.

Rengel D, Arribat S, Maury P, Martin-Magniette M, Hourlier T, Laporte M . A gene-phenotype network based on genetic variability for drought responses reveals key physiological processes in controlled and natural environments. PLoS One. 2012; 7(10):e45249. PMC: 3466295. DOI: 10.1371/journal.pone.0045249. View

11.

Condon A, Richards R, Rebetzke G, Farquhar G . Improving Intrinsic Water-Use Efficiency and Crop Yield. Crop Sci. 2002; 42(1):122-131. DOI: 10.2135/cropsci2002.1220. View

12.

Richards R, Rebetzke G, Condon A, van Herwaarden A . Breeding Opportunities for Increasing the Efficiency of Water Use and Crop Yield in Temperate Cereals. Crop Sci. 2002; 42(1):111-121. DOI: 10.2135/cropsci2002.1110. View

13.

Vincourt P, As-Sadi F, Bordat A, Langlade N, Gouzy J, Pouilly N . Consensus mapping of major resistance genes and independent QTL for quantitative resistance to sunflower downy mildew. Theor Appl Genet. 2012; 125(5):909-20. DOI: 10.1007/s00122-012-1882-y. View

14.

Scheidegger Y, Saurer M, Bahn M, Siegwolf R . Linking stable oxygen and carbon isotopes with stomatal conductance and photosynthetic capacity: a conceptual model. Oecologia. 2017; 125(3):350-357. DOI: 10.1007/s004420000466. View

15.

Hausmann N, Juenger T, Sen S, Stowe K, Dawson T, Simms E . Quantitative trait loci affecting delta13C and response to differential water availibility in Arabidopsis thaliana. Evolution. 2005; 59(1):81-96. View

16.

Ceccarelli M, Sarri V, Natali L, Giordani T, Cavallini A, Zuccolo A . Characterization of the chromosome complement of Helianthus annuus by in situ hybridization of a tandemly repeated DNA sequence. Genome. 2007; 50(5):429-34. DOI: 10.1139/g07-019. View

17.

Diab A, Teulat-Merah B, This D, Ozturk N, Benscher D, Sorrells M . Identification of drought-inducible genes and differentially expressed sequence tags in barley. Theor Appl Genet. 2004; 109(7):1417-25. DOI: 10.1007/s00122-004-1755-0. View

18.

Chen J, Chang S, Anyia A . Gene discovery in cereals through quantitative trait loci and expression analysis in water-use efficiency measured by carbon isotope discrimination. Plant Cell Environ. 2011; 34(12):2009-23. DOI: 10.1111/j.1365-3040.2011.02397.x. View

19.

Kliebenstein D, Figuth A, Mitchell-Olds T . Genetic architecture of plastic methyl jasmonate responses in Arabidopsis thaliana. Genetics. 2002; 161(4):1685-96. PMC: 1462221. DOI: 10.1093/genetics/161.4.1685. View

20.

Saranga Y, Menz M, Jiang C, Wright R, Yakir D, Paterson A . Genomic dissection of genotype x environment interactions conferring adaptation of cotton to arid conditions. Genome Res. 2001; 11(12):1988-95. DOI: 10.1101/gr.157201. View