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. 2014 Jul 3;9(7):e101218.
doi: 10.1371/journal.pone.0101218. eCollection 2014.

Genetic control of water use efficiency and leaf carbon isotope discrimination in sunflower (Helianthus annuus L.) subjected to two drought scenarios

Affiliations

Genetic control of water use efficiency and leaf carbon isotope discrimination in sunflower (Helianthus annuus L.) subjected to two drought scenarios

Afifuddin Latif Adiredjo et al. PLoS One. .

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.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Principles of the water treatments used in this study.
(A) In experiment 2011, three replicates (each of 150 plants) were subjected to progressive water-stress by water withholding from 1 to 31 DAE. In this experiment a control replicate (150 plants) was watered to maintain non-stressful conditions (SWC = 30%). (B) In Experiment 2012, two replicates (each of 150 plants) were maintained at in stressful conditions SWC = 16% from 1 to 23 DAE whereas two other replicates (each of 150 plants) were irrigated to maintain non-stressful conditions (SWC = 30%). DAE: day after emergence.
Figure 2
Figure 2. Frequency distribution for water use efficiency (WUE) in Exp. 2011 and 2012 of 150 recombinant inbred lines (RILs).
WUET2011: total water use efficiency “total” in Exp. 2011; WUEE2011: water use efficiency “estimation” in Exp. 2011; WUET2012: water use efficiency “total” in Exp. 2012. WW: well-watered; WS: water-stressed. For WUET2011 and WUEE2011 at WW, data represent 150 RILs (n = 150); for WUET2011 and WUEE2011 at WS, data represent mean of three replicates of 150 RILs (n = 150); for WUET2012 at WW and WS, data represent mean of two replicates of 150 RILs (n = 150). SD: standard deviation.
Figure 3
Figure 3. Frequency distribution for carbon isotope discrimination (CID) in Exp. 2011 and 2012 of 150 recombinant inbred lines (RILs).
WW: well-watered; WS: water-stressed. For CID in Exp. 2011 at WW, data represent 150 RILs (n = 150); for CID in Exp. 2012 at WS, data represent mean of three replicates of 150 RILs (n = 150); for CID in 2012 at WW and WS, data represent mean of two replicates of 150 RILs (n = 150). SD: standard deviation.
Figure 4
Figure 4. Relationship between water use efficiency (WUE) and carbon isotope discrimination (CID) of 150 recombinant inbred lines (RILs) in Exp. 2011 and Exp. 2012.
Relationship between (A) WUET2011 and CID in Exp. 2011, (B) WUET2011 and CID at WW in Exp. 2011, (C) WUET2011 and CID at WS in Exp. 2011, (D) WUEE2011 and CID in Exp. 2011, (E) WUEE2011 and CID at WW in Exp. 2011, (F) WUEE2011 and CID at WS in Exp. 2011, (G) WUET2012 and CID in Exp. 2012, (H) WUET2012 and CID at WW in Exp. 2012; (I) WUET2012 and CID at WS in Exp. 2012. Phenotypic correlation (rp) value is provided in each graph.
Figure 5
Figure 5. Relationship between (A, B) WUE and (B) CID values for 150 recombinant inbred lines (RILs) determined in two separate experiments (Exp. 2011 and 2012).
For each trait and experiment, mean of well-watered (WW) and water-stressed (WS) plants were grouped together (n = 300). Phenotypic correlation (rp) value is provided in each graph.
Figure 6
Figure 6. Genetic locations of QTL for water use efficiency (WUE), carbon isotope discrimination (CID), biomass (BM) and cumulative water transpired (CWT) in the progressive stress experiment (2011) and the stable stress experiment (2012).
Numbers on the left of linkage groups (LG) indicate the cumulative distance in centimorgan (cM) to the first marker at the top LG. Marker names and QTL are specified to the right of LG. The same QTLs which are found in a LG are shown in bold. Not all these chromosomes contain the complete markers (each chromosome has only been provided by the markers at the top, middle and bottom of LG as well as the markers for identified QTLs). QTL confidence intervals were estimated using the two-LOD confidence region.

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