Automated discretization of 'transpiration restriction to increasing VPD' features from outdoors high-throughput phenotyping data.

BACKGROUND: Restricting transpiration under high vapor pressure deficit (VPD) is a promising water-saving trait for drought adaptation. However, it is often measured under controlled conditions and at very low throughput, unsuitable for breeding. A few high-throughput phenotyping (HTP) studies exist, and have considered only maximum transpiration rate in analyzing genotypic differences in this trait. Further, no study has precisely identified the VPD breakpoints where genotypes restrict transpiration under natural conditions. Therefore, outdoors HTP data (15 min frequency) of a chickpea population were used to automate the generation of smooth transpiration profiles, extract informative features of the transpiration response to VPD for optimal genotypic discretization, identify VPD breakpoints, and compare genotypes. RESULTS: Fifteen biologically relevant features were extracted from the transpiration rate profiles derived from load cells data. Genotypes were clustered (C1, C2, C3) and 6 most important features (with heritability > 0.5) were selected using unsupervised Random Forest. All the wild relatives were found in C1, while C2 and C3 mostly comprised high TE and low TE lines, respectively. Assessment of the distinct p-value groups within each selected feature revealed highest genotypic variation for the feature representing transpiration response to high VPD condition. Sensitivity analysis on a multi-output neural network model (with R of 0.931, 0.944, 0.953 for C1, C2, C3, respectively) found C1 with the highest water saving ability, that restricted transpiration at relatively low VPD levels, 56% (i.e. 3.52 kPa) or 62% (i.e. 3.90 kPa), depending whether the influence of other environmental variables was minimum or maximum. Also, VPD appeared to have the most striking influence on the transpiration response independently of other environment variable, whereas light, temperature, and relative humidity alone had little/no effect. CONCLUSION: Through this study, we present a novel approach to identifying genotypes with drought-tolerance potential, which overcomes the challenges in HTP of the water-saving trait. The six selected features served as proxy phenotypes for reliable genotypic discretization. The wild chickpeas were found to limit water-loss faster than the water-profligate cultivated ones. Such an analytic approach can be directly used for prescriptive breeding applications, applied to other traits, and help expedite maximized information extraction from HTP data.

Multi-trait analysis of domestication genes in Cicer arietinum - Cicer reticulatum hybrids with a multidimensional approach: Modeling wide crosses for crop improvement.

Domestication and subsequent breeding have eroded genetic diversity in the modern chickpea crop by ˜100-fold. Corresponding reductions to trait variation create the need, and an opportunity, to identify and harness the genetic capacity of wild species for crop improvement. Here we analyze trait segregation in a series of wild x cultivated hybrid populations to delineate the genetic underpinnings of domestication traits. Two species of wild chickpea, C. reticulatum and C. echinospermum, were crossed with the elite, early flowering C. arietinum cultivar ICCV96029. KASP genotyping of F2 parents with an FT-linked molecular marker enabled selection of 284 F3 families with reduced phenological variation: 255 F3 families of C. arietinum x reticulatum (AR) derived from 17 diverse wild parents and 29 F3 families of C. arietinum x echinospermum (AE) from 3 wild parents. The combined 284 lineages were genotyped using a genotyping-by-sequencing strategy and phenotyped for agronomic traits. 50 QTLs in 11 traits were detected from AR and 35 QTLs in 10 traits from the combined data. Using hierarchical clustering to assign traits to six correlated groups and mixed model based multi-trait mapping, four pleiotropic loci were identified. Bayesian analysis further identified four inter-trait relationships controlling the duration of vegetative growth and seed maturation, for which the underlying pleiotropic genes were mapped. A random forest approach was used to explore the most extreme trait differences between AR and AE progenies, identifying traits most characteristic of wild species origin. Knowledge of the genomic basis of traits that segregate in wild-cultivated hybrid populations will facilitate chickpea improvement by linking genetic and phenotypic variation in a quantitative genetic framework.

Ecology and genomics of an important crop wild relative as a prelude to agricultural innovation.

Domesticated species are impacted in unintended ways during domestication and breeding. Changes in the nature and intensity of selection impart genetic drift, reduce diversity, and increase the frequency of deleterious alleles. Such outcomes constrain our ability to expand the cultivation of crops into environments that differ from those under which domestication occurred. We address this need in chickpea, an important pulse legume, by harnessing the diversity of wild crop relatives. We document an extreme domestication-related genetic bottleneck and decipher the genetic history of wild populations. We provide evidence of ancestral adaptations for seed coat color crypsis, estimate the impact of environment on genetic structure and trait values, and demonstrate variation between wild and cultivated accessions for agronomic properties. A resource of genotyped, association mapping progeny functionally links the wild and cultivated gene pools and is an essential resource chickpea for improvement, while our methods inform collection of other wild crop progenitor species.