Variation in key leaf photosynthetic traits across wheat wild relatives is accession dependent not species dependent

Abstract

The wild relatives of modern wheat represent an underutilized source of genetic and phenotypic diversity and are of interest in breeding owing to their wide adaptation to diverse environments. Leaf photosynthetic traits underpin the rate of production of biomass and yield and have not been systematically explored in the wheat relatives. This paper identifies and quantifies the phenotypic variation in photosynthetic, stomatal, and morphological traits in up to 88 wheat wild relative accessions across five genera. Both steady-state measurements and dynamic responses to step changes in light intensity are assessed. A 2.3-fold variation for flag leaf light and CO 2-saturated rates of photosynthesis A max was observed. Many accessions showing higher and more variable A max , maximum rates of carboxylation, electron transport, and Rubisco activity when compared with modern genotypes. Variation in dynamic traits was also significant; with distinct genus-specific trends in rates of induction of nonphotochemical quenching and rate of stomatal opening. We conclude that utilization of wild relatives for improvement of photosynthesis is supported by the existence of a high degree of natural variation in key traits and should consider not only genus-level properties but variation between individual accessions.

Dynamics of photosynthetic induction and relaxation within the canopy of rice and two wild relatives

“…rufipogon or O . nivara accessions (Figure 9 ), which resulted in higher iWUE and greater water conservation when the plant re‐entered low‐light conditions (Figure 4 )—similar to what has been shown previously in wheat (McAusland et al, 2020 ). Accessions with a slower stomatal closure response saw tradeoffs with intrinsic water‐use efficiency (Figure 4 ), which can result in lower drought resistance (Qu et al, 2016 ; McAusland et al, 2020 ).…”

“…The coordination between A and g s can decrease in response to changes in light intensity, resulting in greater water loss through transpiration (McAusland et al, 2016 ; Qu et al, 2016 ; McAusland et al, 2020 ). In rice, A and g s are strongly coupled during induction (McAusland et al, 2016 ; Zhang et al, 2019 ), but can become less coordinated during the transition from high‐to‐low light (McAusland et al, 2016 ).…”

“…Yet, steady‐state lighting is seldom achieved in leaves within a field crop canopy. Additionally, previous models that utilize steady‐state data potentially overestimate CO 2 assimilation and do not account for the loss of productivity due to the lags in efficiency during induction and relaxation (Pearcy, 1990 ; Taylor & Long, 2017 ; Wang, Burgess, et al, 2020 ) and will underestimate water loss (McAusland et al, 2016 ; Qu et al, 2016 ; McAusland et al, 2020 ). However, increased focus has recently been dedicated to characterizing, understanding, and modeling photosynthesis in non‐steady‐state conditions, to more accurately reflect conditions in the field (Kaiser et al, 2015 ; Kaiser et al, 2017 ; McAusland et al, 2016 ; Qu et al, 2016 ; Soleh et al, 2016 , 2017 ; Kaiser et al, 2018 ; Deans et al, 2019 ; Deans et al, 2019 ; De Souza et al, 2020 ; Wang, Burgess, et al, 2020 ; Acevedo‐Siaca, Coe, Quick, et al, 2020 ; Acevedo‐Siaca, Coe, Wang, et al, 2020 ; McAusland et al, 2020 ).…”

“…Additionally, previous models that utilize steady‐state data potentially overestimate CO 2 assimilation and do not account for the loss of productivity due to the lags in efficiency during induction and relaxation (Pearcy, 1990 ; Taylor & Long, 2017 ; Wang, Burgess, et al, 2020 ) and will underestimate water loss (McAusland et al, 2016 ; Qu et al, 2016 ; McAusland et al, 2020 ). However, increased focus has recently been dedicated to characterizing, understanding, and modeling photosynthesis in non‐steady‐state conditions, to more accurately reflect conditions in the field (Kaiser et al, 2015 ; Kaiser et al, 2017 ; McAusland et al, 2016 ; Qu et al, 2016 ; Soleh et al, 2016 , 2017 ; Kaiser et al, 2018 ; Deans et al, 2019 ; Deans et al, 2019 ; De Souza et al, 2020 ; Wang, Burgess, et al, 2020 ; Acevedo‐Siaca, Coe, Quick, et al, 2020 ; Acevedo‐Siaca, Coe, Wang, et al, 2020 ; McAusland et al, 2020 ). As a result, new targets for improving photosynthetic efficiency have been identified that could improve performance in non‐steady‐state conditions, such as increasing the speed of induction, reducing forgone assimilation during induction, reducing water loss, improving stomatal kinetics, or relaxing NPQ more quickly (Woodrow & Mott, 1989 ; Lawson & Blatt, 2014 ; McAusland et al, 2016 ; Kromdijk et al, 2016 ; Glowacka et al, 2018 ; Qu et al, 2016 ; De Souza et al, 2020 ; Acevedo‐Siaca, Coe, Quick, et al, 2020 ; Acevedo‐Siaca, Coe, Wang, et al, 2020 ; McAusland et al, 2020 ; Qu et al, 2020 ).…”

Diverse Physiological and Physical Responses among Wild, Landrace and Elite Barley Varieties Point to Novel Breeding Opportunities

“…McAusland et al [69] report significant differences in photosynthetic rates and potential in wild relatives of modern wheat and suggested that this represents an underutilized source of genetic and phenotypic diversity, while the same is also true for landraces and older elite varieties [38,67] that have yet to be evaluated. The greater QE observed in Dea and Hatif (Figure 5) suggests a greater efficiency in use of absorbed light in CO 2 fixation, as well as enhanced carboxylation capacity of Rubisco.…”