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

Shin, Min-Gyoung; Bulyntsev, S. V.; Chang, Peter L.; Korbu, Lijalem; Carrasquila-Garcia, Noelia; Vishnyakova, M. A.; Samsonova, Maria; Cook, Douglas R.; Nuzhdin, Sergey V.

doi:10.1016/j.plantsci.2019.04.018

Cited by 16 publications

(17 citation statements)

References 31 publications

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“…A recent international collaboration has built a large introgression resource from the newly expanded collection of wild diversity (von Wettberg et al, 2018). Advanced introgression lines, currently in F 4 to F 6 stages, have been developed, using 20 C. reticulatum and six C. echinospermum parents into five different cultivated accessions (Shin et al, 2019; von Wettberg et al, 2018).…”

Section: How To Effectively Use the Diversity Of Cwrs?mentioning

confidence: 99%

Potential and limits of exploitation of crop wild relatives for pea, lentil, and chickpea improvement

Coyne¹,

Kumar²,

Wettberg

et al. 2020

Legume Science

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Legumes represent the second most important family of crop plants after grasses, accounting for approximately 27% of the world's crop production. Past domestication processes resulted in a high degree of relatedness between modern varieties of crops, leading to a narrower genetic base of cultivated germplasm prone to pests and diseases. Crop wild relatives (CWRs) harbor genetic diversity tested by natural selection in a range of environments. To fully understand and exploit local adaptation in CWR, studies in geographical centers of origin combining ecology, physiology, and genetics are needed. With the advent of modern genomics and computation, combined with systematic phenotyping, it is feasible to revisit wild accessions and landraces and prioritize their use for breeding, providing sources of disease resistances; tolerances of drought, heat, frost, and salinity abiotic stresses; nutrient densities across major and minor elements; and food quality traits. Establishment of hybrid populations with CWRs gives breeders a considerable benefit of a prebreeding tool for identifying and harnessing wild alleles and provides extremely valuable long-term resources. There is a need of further collecting and both ex situ and in situ conservation of CWR diversity of these taxa in the face of habitat loss and degradation and climate change. In this review, we focus on three legume crops domesticated in the Fertile Crescent, pea, chickpea, and lentil, and summarize the current state and potential of their respective CWR taxa for crop improvement.

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Section: How To Effectively Use the Diversity Of Cwrs?mentioning

confidence: 99%

Potential and limits of exploitation of crop wild relatives for pea, lentil, and chickpea improvement

Coyne¹,

Kumar²,

Wettberg

et al. 2020

Legume Science

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show abstract

“…Random forest and gradient boosting methods are widely applied powerful machine learning methods ( Lubke et al, 2013 ; Mittrapiyanuruk and Charoen-Ung, 2018 ; Shin et al, 2019 ). Although both approaches adapt a tree-based model scheme, their internal logic is different, and the investigation of their performance difference according to different types of data sets can provide valuable information.…”

Section: Discussionmentioning

confidence: 99%

“…The Bari and Egil data used in this study are subsets of the 2,521 F2 hybrid chickpea materials crossed between 20 wild-type parent lines and the early flowering parent ICCV96029. After further filtering based on FT locus to prevent the confounding effect of segregating phenology linked to that locus, 284 F2 lines were selected ( Shin et al, 2019 ). To perform GBS sequencing, restriction enzymes Hin dIII and Nla III were used, and Illumina HiSeq 4000 was used to generate sequence data.…”

Section: Methodsmentioning

confidence: 99%

“…Using interspecific hybrid, we can investigate wild genetic variations that are associated with important traits and locate causal QTLs by performing association analysis, an application that has been used in staple crop studies. For example, in a 2019 chickpea study, QTLs associated with chickpea germination, flowering duration, and bean characteristics were found using NAM materials developed by crossing cultivar chickpeas and wild chickpea plants collected from Turkey ( Warburton et al, 2017 ; Osorio-Guarín et al, 2019 ; Shin et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“…These methods build multiple small predictive decision trees to make the final prediction, making them more powerful than prediction methods that use only a single model. Another advantage of these methods is that they can rank markers based on marker contribution to trait prediction ( Genuer et al, 2010 ; Mittrapiyanuruk and Charoen-Ung, 2018 ; Shah et al, 2019 ; Shin et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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Interspecific Sample Prioritization Can Improve QTL Detection With Tree-Based Predictive Models

Shin

Nuzhdin

2021

Front. Genet.

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Due to increasing demand for new advanced crops, considerable efforts have been made to explore the improvement of stress and disease resistance cultivar traits through the study of wild crops. When both wild and interspecific hybrid materials are available, a common approach has been to study two types of materials separately and simply compare the quantitative trait locus (QTL) regions. However, combining the two types of materials can potentially create a more efficient method of finding predictive QTLs. In this simulation study, we focused on scenarios involving causal marker expression suppressed by trans-regulatory mechanisms, where the otherwise easily lost associated signals benefit the most from combining the two types of data. A probabilistic sampling approach was used to prioritize consistent genotypic phenotypic patterns across both types of data sets. We chose random forest and gradient boosting to apply the prioritization scheme and found that both facilitated the investigation of predictive causal markers in most of the biological scenarios simulated.

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Towards the Development, Maintenance and Standardized Phenotypic Characterization of Single‐Seed‐Descent Genetic Resources for Chickpea

et al. 2022

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Here we present the approach used to develop the INCREASE "Intelligent Chickpea" Collections, from analysis of the information on the life history and population structure of chickpea germplasm, the availability of genomic and genetic resources, the identification of key phenotypic traits and methodologies to characterize chickpea. We present two phenotypic protocols within H2O20 Project INCREASE to characterize, develop, and maintain chickpea single-seed-descent (SSD) line collections. Such protocols and related genetic resource data from the project will be available for the legume community to apply the standardized approaches to develop Chickpea Intelligent Collections further or for multiplication/seed-increase purposes.

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

Cited by 16 publications

References 31 publications

Potential and limits of exploitation of crop wild relatives for pea, lentil, and chickpea improvement

Potential and limits of exploitation of crop wild relatives for pea, lentil, and chickpea improvement

Interspecific Sample Prioritization Can Improve QTL Detection With Tree-Based Predictive Models

Towards the Development, Maintenance and Standardized Phenotypic Characterization of Single‐Seed‐Descent Genetic Resources for Chickpea

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