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.

Lentil (Lens culinaris Medik.) germplasm with sufficient winter hardiness to survive most winters in cold northern areas is available. However, the use of that germplasm in breeding programs is hampered by variable winter conditions that make field evaluations needed for effective breeding and selection difficult. Our objectives were to gain additional information on the genetics of winter hardiness in lentil by QTL analysis and to identify markers for use in marker‐assisted selection. A total of 106 F6 derived recombinant inbred lines (RILs) from the cross WA8649090/Precoz were evaluated for winter survival in the field at Pullman, WA, USA, Haymana, Turkey, and Sivas, Turkey, in a randomized complete block design with three replications over 3 yr. Winter survival was based on plant stand counts before and after winter. In addition, winter injury was monitored at Pullman during the 1998‐1999 winter season. Mean survival of the RILs was 49.7, 5.3, and 89.5% at Haymana in 1997‐1998, at Pullman in 1998‐1999, and at Haymana in 1999‐2000, respectively. For QTL analysis of winter survival, three QTL were detected at Haymana in 1997‐1998, one QTL was detected at Pullman in 1998‐1999, and three QTL were identified at Haymana in 1999‐2000. Only one of the QTL was common to all environments. For winter injury scores at Pullman in 1999, four QTL were identified that influenced winter survival. Overall results indicated that winter hardiness is influenced by several genes and the cumulative effects of winter stress.

Lentil (Lens culinaris Medik.) germplasm with sufficient winter hardiness to survive most winters in cold northern areas is available. However, the use of that germplasm in breeding programs is hampered by variable winter conditions that make field evaluations needed for effective breeding and selection difficult. Our objectives were to gain additional information on the genetics of winter hardiness in lentil by QTL analysis and to identify markers for use in marker‐assisted selection. A total of 106 F6 derived recombinant inbred lines (RILs) from the cross WA8649090/Precoz were evaluated for winter survival in the field at Pullman, WA, USA, Haymana, Turkey, and Sivas, Turkey, in a randomized complete block design with three replications over 3 yr. Winter survival was based on plant stand counts before and after winter. In addition, winter injury was monitored at Pullman during the 1998‐1999 winter season. Mean survival of the RILs was 49.7, 5.3, and 89.5% at Haymana in 1997‐1998, at Pullman in 1998‐1999, and at Haymana in 1999‐2000, respectively. For QTL analysis of winter survival, three QTL were detected at Haymana in 1997‐1998, one QTL was detected at Pullman in 1998‐1999, and three QTL were identified at Haymana in 1999‐2000. Only one of the QTL was common to all environments. For winter injury scores at Pullman in 1999, four QTL were identified that influenced winter survival. Overall results indicated that winter hardiness is influenced by several genes and the cumulative effects of winter stress.

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BackgroundAccurate prediction of crop flowering time is required for reaching maximal farm efficiency. Several models developed to accomplish this goal are based on deep knowledge of plant phenology, requiring large investment for every individual crop or new variety. Mathematical modeling can be used to make better use of more shallow data and to extract information from it with higher efficiency. Cultivars of chickpea, Cicer arietanum, are currently being improved by introgressing wild C. reticulatum biodiversity with very different flowering time requirements. More understanding is required for how flowering time will depend on environmental conditions in these cultivars developed by introgression of wild alleles.ResultsWe built a novel model for flowering time of wild chickpeas collected at 21 different sites in Turkey and grown in 4 distinct environmental conditions over several different years and seasons. We propose a general approach, in which the analytic forms of dependence of flowering time on climatic parameters, their regression coefficients, and a set of predictors are inferred automatically by stochastic minimization of the deviation of the model output from data. By using a combination of Grammatical Evolution and Differential Evolution Entirely Parallel method, we have identified a model that reflects the influence of effects of day length, temperature, humidity and precipitation and has a coefficient of determination of R2=0.97.ConclusionsWe used our model to test two important hypotheses. We propose that chickpea phenology may be strongly predicted by accession geographic origin, as well as local environmental conditions at the site of growth. Indeed, the site of origin-by-growth environment interaction accounts for about 14.7% of variation in time period from sowing to flowering. Secondly, as the adaptation to specific environments is blueprinted in genomes, the effects of genes on flowering time may be conditioned on environmental factors. Genotype-by-environment interaction accounts for about 17.2% of overall variation in flowering time. We also identified several genomic markers associated with different reactions to climatic factor changes. Our methodology is general and can be further applied to extend existing crop models, especially when phenological information is limited.Electronic supplementary materialThe online version of this article (10.1186/s12870-019-1685-2) contains supplementary material, which is available to authorized users.