Genetic Dissection and Identification of Candidate Genes for Salinity Tolerance Using Axiom®CicerSNP Array in Chickpea.
Khela Ram SorenPraveen MadugulaNeeraj KumarRutwik BarmukhMeenu Singh SengarChellapilla BharadwajParbodh Chander SharmaSarvjeet SinghAditi BhandariJogendra SinghSatish Kumar SanwalMadan PalSneha Priya P RAnita MannSomeswar Rao SagurthiPichandampalayam Subramaniam ShanmugavadivelKadambot H M SiddiqueNarendra Pratap SinghManish RoorkiwalRajeev Kumar VarshneyPublished in: International journal of molecular sciences (2020)
Globally, chickpea production is severely affected by salinity stress. Understanding the genetic basis for salinity tolerance is important to develop salinity tolerant chickpeas. A recombinant inbred line (RIL) population developed using parental lines ICCV 10 (salt-tolerant) and DCP 92-3 (salt-sensitive) was screened under field conditions to collect information on agronomy, yield components, and stress tolerance indices. Genotyping data generated using Axiom®CicerSNP array was used to construct a linkage map comprising 1856 SNP markers spanning a distance of 1106.3 cM across eight chickpea chromosomes. Extensive analysis of the phenotyping and genotyping data identified 28 quantitative trait loci (QTLs) explaining up to 28.40% of the phenotypic variance in the population. We identified QTL clusters on CaLG03 and CaLG06, each harboring major QTLs for yield and yield component traits under salinity stress. The main-effect QTLs identified in these two clusters were associated with key genes such as calcium-dependent protein kinases, histidine kinases, cation proton antiporter, and WRKY and MYB transcription factors, which are known to impart salinity stress tolerance in crop plants. Molecular markers/genes associated with these major QTLs, after validation, will be useful to undertake marker-assisted breeding for developing better varieties with salinity tolerance.
Keyphrases
- genome wide
- microbial community
- dna methylation
- transcription factor
- high throughput
- copy number
- high density
- high resolution
- big data
- stress induced
- climate change
- electronic health record
- ionic liquid
- machine learning
- genome wide identification
- small molecule
- social media
- dna binding
- human immunodeficiency virus
- single cell
- amino acid
- men who have sex with men
- hiv infected