Selection of Contrasting Parents for Drought Tolerance in Sunower (Helianthus Annuus L.)

The aim of this research was select the best combination of contrasting parents to develop a mapping 10 population for drought tolerance, based on phenotypic and genotypic data. Phenotyping was conducted in a greenhouse 11 during 16 days at vegetative stage under well-watered (WW) and water-deficit (WD) conditions. Traits evaluated 12 were: gain of leaf area (GLA), total water use (TWU), net assimilation rate (NAR), water use efficiency (WUE) and 13 transpiration rate (TR) response to vapor pressure deficit (VPD) (slope and breakpoint). Genotyping was performed 14 with 127 SSR markers and a cluster analyses was conducted. An important interaction was observed for NAR, WUE 15 and breakpoint in the VPD response. Under WD conditions, all genotypes showed lower GLA and TWU, whereas 16 NAR and WUE increased its values. All genotypes showed reduction of the slope and breakpoint in high VPD 17 response on WD. PCA analysis explains the 80% of the total variability. PC1 discriminated HA89 and R419 due to a 18 lower slope and higher breakpoint, while PC2 separated by water treatment based on the WUE and TWU values. 19 Nighty nine SSR marker were amplified detecting 262 alleles. Cluster analyzes showed two main groups, one 20 including HAR4 and B59 and the other one including five remaining genotypes. According to these results, only 21 R419xHA64 and HA89xHAR4 had a greater genetic distance (1.08), besides a high polymorphism level between ILs 22 (about 60%). Therefore, we conclude that these would be the best combination of contrasting parents to develop 23 mapping populations for drought tolerance in sunflower.


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In the '90s, the sunflower crop was displaced towards areas with lower quality and agroecological aptitude. This 71 caused that the yields have not experienced significant increases in the last five years, despite the technological 72 changes incorporated (FAS USDA 2021). These marginal areas are characterized by a marked water deficit, due to 73 the reduction in the frequency of annual rainfall. These changes in the seasonal distribution cause a discrepancy 74 between crop cycles and water availability in the soil. Consequently, the water stress produced during this period 75 causes significant yield losses, also affecting the content and chemical quality of the oil in the seed (D. Álvarez 76 personal communication). Therefore, the increase in the drought tolerance in sunflower hybrids is our goal and for 77 this, it is interesting to explore the genetic resources in order to identify genomic regions associated with this trait. In   Table   86 1), were included in this study for drought tolerance phenotyping and molecular assay. Six of them were previously 87 evaluated for drought tolerance in the field, under well-watered (WW) and water-deficit (WD) conditions during 2003-

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Based on these water constants the target weight was determined for each water condition, which were maintained 100 with the irrigation applied daily. Seedlings were thinned to one plant per pot and were grown without water limitations 101 until eight-leaf stage initiation in each IL. At this moment, soil water content was gradually decreased using the method     oven-dried at 105 °C for 24 h, to determine total DW. Water transpired (WT) per plant was estimated every day from NAR = (W 2 − W 1 ) (log e L 2 − log e L 2 ) (L 2 − L 1 )(t 2 − t 1 )

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where W1 and W2 are total dry weight and L1 and L2 total leaf area at times t1 and t2, respectively.

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Water use efficiency (WUE) (on a whole plant basis) was determined at the end of the experiments as the ratio of 133 dry weight gain (DWG= W2 -W1) to TWU during the effective water stress period. For daily transpiration rate (TR) 134 response to vapor pressure deficit (VPD), slope and breakpoint were estimated from non-linear regression. The TR 135 daily was calculated as the ratio of WT to LA per plant and VPD was estimated as detailed above.

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The genomic DNA from each IL was isolated from 10 mg of lyophilized material according to a modified CTAB

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Significant differences were observed between genotypes and water treatments for all traits. While the interaction 157 was also significant for NAR (p=0.0022), WUE (p=0.0264) and the breakpoint to the VPD response (p=0.0021).

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WD treatments with respect to WW condition was observed, thus decreasing the TRlim reached by each genotypes 195 ( Figure 4B).

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The correlation between traits was analyzed by Pearson correlation coefficients (

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Whereas, a higher significant negative correlation was found between slope and breakpoint in the VPD response (r= 213 -0.73, p<0.0001).

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These seven ILs were genotyped with 127 SSR markers of which amplified 91 loci that allowed identifying 262 222 alleles, as well as a high level of polymorphism between the possible combinations of contrasting parents (Table 3).

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In addition, a neighbor-joining tree ( Figure 6) was constructed based on the Nei Standard genetic distances (Nei 1972) 224 calculated between pairs of ILs. At a distance of 1.05, two groups can be identified; one (group 1) composed of   HA89xHAR4 showed the highest phenotypic contrast. Besides, a greater genetic distance (1.08) and a high 239 polymorphism level between them (about 60%) (Table 3). That is why these are the most suitable combinations of 240 contrasting parents to develop mapping populations for drought tolerance in sunflower.

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Phenotyping assay allow finding a differential response to water stress, among those contrasting genotypes 242 potential to be used as parents to build segregating mapping populations. Thus, the selection of highly contrasting 243 genotypes increase the probability of finding genomic regions or allelic variants associated with the trait.

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Consequently, the phenotyping must be accurate and show an experimental design that allows finding significant 245 differences between parental evaluated. In addition, a greater genetic distance and a high level of marker 246 polymorphism between genotypes also increase the probability of finding QTLs associated with the trait. In this study, 247 phenotyping for drought tolerance was made in a greenhouse during vegetative stage for 16 days. Based on these 248 results, a wide genotypic variation of response was observed for traits and water stress level evaluated in seven inbred

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Although leaf expansion is the first morpho-physiological process affected by water-deficit due to the reduction in closure. This mechanism is one of the main causes of reduction of transpiration rate under water-deficit; because of a stress increased from moderate to severe, respectively. Therefore, in our experiments all genotypes showed lower HA64 genotype was the unique IL, which showed significant differences between both water conditions (a decrease 260 of 27%) and consequently, a reduction of 18% of TWU. Moreover, HAR4, B59 and R419 also showed significant 261 differences (p<0,05) between WW and WD conditions for the last because of the lower GLA. In this sense, the 262 reduction on transpiration rate under water-stress is a consequence of the reduction of GLA and the decline of stomatal expansion. Thus, they conclude that there is a negative association between these traits, probably because of reduction 267 in leaf expansion is the most important mechanisms to avoid water loss.

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The net assimilation rate (NAR) is an index that measures the photosynthetic efficiency and the net gain of

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The transpiration rate (TR) is defined as the water transpired per unit leaf area per unit of time and depends on the 289 concentration gradient of water vapor (estimated from the Vapor Pressure Deficit or VPD) between the subestomatic 290 cavity and the air surrounding the leaf. As the VPD increases, the TR also increases; however, this increase is not 291 unlimited since the TR reaches a limit (TRlim) above a threshold value of VPD or breakpoint (Turner et al. 1984). For 292 establish the relationship between daily TR and VPD response under two water conditions, the slope and the 293 breakpoint were determined. The evidence is that under WD there was a decrease in the slope and breakpoint (6% and 294 5%, respectively), decreasing the TRlim reached by each line. Thus, ILs with higher slope showed lower breakpoint 295 (HA64 and R432) and those with lower slope showed a higher breakpoint (R419 and HA89) (Figure 3). Therefore,

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HA64 and R432 reached the TRlim at a lower VPD, reduced the stomatal conductance and consequently the water loss.

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Instead, R419 and HA89 reached the TRlim at a higher VPD, probably due to a lower stomatal sensitivity to water

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Concerning PCA analysis, PC1 discriminated HA89 and R419 from the other ILs due to a lower slope and higher 314 breakpoint for both treatments; whereas PC2 separated all genotypes by treatment based on WUE and TWU values.

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In this regard, plants under WD condition showed lower water consumption and were more conservative with the 316 water in the tissues. Thus, HA89 and R419 that showed lower WUE and NAR may be classified as low photosynthetic

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In order to establish the genetic relationship between ILs evaluated, a cluster analysis was performed. Thus, a 328 neighbor-joining tree was constructed ( Figure 6) and at a distance of 1.05, two well-defined groups can be identified.

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One of them (group 1) was composed of maintainer lines of Argentinian origin (HAR4 and B59) and the other (group 330 2) was dominated by the presence of restorer lines and separated into two subgroups at a distance of 0.95. One of these 331 contains R423, HA89 and R419 (subgroup 1) which is expected since R419 derives from HA89. While grouping with 332 R423 was probably due to is a restorer line of Argentinian origin, just like R419. The second subgroup was conformed 333 by R432 and HA64 because of they share 45% of similarity among the SSR markers analyzed. Although in the records 334 HA64 is from USA and R432 is from Argentinian germplasm, these could have some common origin, which would 335 cause them to be located together in the neighbor-joining tree. These groups are coincident with that found by Filippi

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Based on phenotyping results, four possible combinations between contrasting parents were achieved (Table 3).

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However, only two (R419xHA64 and HA89xHAR4) showed a greater genetic distance (1.08) and a high level of 339 polymorphic markers between them (about 60%). In conclusion, these would be the best combinations to develop

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The datasets generated during and/or analysed during the current study are available from the corresponding author 494 on reasonable request.