Genetics and molecular mapping for salinity stress tolerance at seedling stage in lentil (<i>Lens culinaris</i>Medik)

Singh, Dharmendra; Singh, Chandan Kumar; Tomar, R. S.; Sharma, S.R.; Karwa, Sourabh; Pal, Madan; Singh, V. P.; Sanwal, Satish Kumar; Sharma, P. C.

doi:10.1002/csc2.20030

Cited by 17 publications

(6 citation statements)

References 46 publications

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“…In this direction, drought stress-associated QTL analysis was conducted in a RIL population (ILL6002 × ILL5888) which revealed 18 QTLs associated with 14 root and shoot traits such as dry root biomass, lateral root number, specific root length, root-shoot ratio, and chlorophyll content ( Idrissi et al, 2016 ). Similarly, a QTL associated with seedling survival under salinity stress was identified in a population developed by crossing salt-tolerant (PDL-1 and PSL-9) and salt-sensitive (L-4147 and L-4076) genotypes ( Singh et al, 2020 ). Lentils, based on their geographic location, and being a temperate legume are often exposed to very low-temperature conditions, and hence, it is imperative to look for QTL associated with winter hardiness.…”

Section: Genomic Innovations Reveal a New Genetic Landscape For Lenti...mentioning

confidence: 99%

Omics Path to Increasing Productivity in Less-Studied Crops Under Changing Climate—Lentil a Case Study

et al. 2022

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Conventional breeding techniques for crop improvement have reached their full potential, and hence, alternative routes are required to ensure a sustained genetic gain in lentils. Although high-throughput omics technologies have been effectively employed in major crops, less-studied crops such as lentils have primarily relied on conventional breeding. Application of genomics and transcriptomics in lentils has resulted in linkage maps and identification of QTLs and candidate genes related to agronomically relevant traits and biotic and abiotic stress tolerance. Next-generation sequencing (NGS) complemented with high-throughput phenotyping (HTP) technologies is shown to provide new opportunities to identify genomic regions and marker-trait associations to increase lentil breeding efficiency. Recent introduction of image-based phenotyping has facilitated to discern lentil responses undergoing biotic and abiotic stresses. In lentil, proteomics has been performed using conventional methods such as 2-D gel electrophoresis, leading to the identification of seed-specific proteome. Metabolomic studies have led to identifying key metabolites that help differentiate genotypic responses to drought and salinity stresses. Independent analysis of differentially expressed genes from publicly available transcriptomic studies in lentils identified 329 common transcripts between heat and biotic stresses. Similarly, 19 metabolites were common across legumes, while 31 were common in genotypes exposed to drought and salinity stress. These common but differentially expressed genes/proteins/metabolites provide the starting point for developing high-yielding multi-stress-tolerant lentils. Finally, the review summarizes the current findings from omic studies in lentils and provides directions for integrating these findings into a systems approach to increase lentil productivity and enhance resilience to biotic and abiotic stresses under changing climate.

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Section: Genomic Innovations Reveal a New Genetic Landscape For Lenti...mentioning

confidence: 99%

Omics Path to Increasing Productivity in Less-Studied Crops Under Changing Climate—Lentil a Case Study

et al. 2022

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“…To improve lentil productivity, the most direct approach is to identify and increase the presence of novel genes and alleles associated with salt tolerance in commercially relevant lentil germplasm. Although, there have been several studies undertaken in lentil describing salt tolerance genetics [18,64], a comprehensive analysis based on diverse germplasm and genome-wide set of SNP markers is limited. As such, the present study was conducted for a better understanding of the salt tolerance in lentil using both advanced genomics and phenomics approaches.…”

Section: Identification Of Genomic Regions Conferring Salt Tolerance mentioning

confidence: 99%

Application of Genomics to Understand Salt Tolerance in Lentil

Dissanayake

Cogan

Smith

et al. 2021

Genes

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Soil salinity is a major abiotic stress, limiting lentil productivity worldwide. Understanding the genetic basis of salt tolerance is vital to develop tolerant varieties. A diversity panel consisting of 276 lentil accessions was screened in a previous study through traditional and image-based approaches to quantify growth under salt stress. Genotyping was performed using two contrasting methods, targeted (tGBS) and transcriptome (GBS-t) genotyping-by-sequencing, to evaluate the most appropriate methodology. tGBS revealed the highest number of single-base variants (SNPs) (c. 56,349), and markers were more evenly distributed across the genome compared to GBS-t. A genome-wide association study (GWAS) was conducted using a mixed linear model. Significant marker-trait associations were observed on Chromosome 2 as well as Chromosome 4, and a range of candidate genes was identified from the reference genome, the most plausible being potassium transporters, which are known to be involved in salt tolerance in related species. Detailed mineral composition performed on salt-treated and control plant tissues revealed the salt tolerance mechanism in lentil, in which tolerant accessions do not transport Na+ ions around the plant instead localize within the root tissues. The pedigree analysis identified two parental accessions that could have been the key sources of tolerance in this dataset.

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“…The advent of DNA markers opened new opportunities in plant breeding that have enabled breeders to make more informed and accurate selections through marker-assisted selection (MAS) ( Kaur et al., 2014 ; Jain et al., 2017 ). In lentils, quantitative trait loci have been identified for ascochyta blight resistance, boron and salinity toxicity tolerance, yield, winter hardiness, seed weight, seed size and milling quality ( Taylor et al., 2006 ; Barrios et al., 2007 ; Kaur et al., 2014 ; Verma et al., 2015 ; Sudheesh et al., 2016 ; Singh et al., 2017 ; Subedi et al., 2018 ; Singh et al., 2020 ). While some success has been achieved in the use of MAS to accelerate genetic gain in breeding programs, it is neither effective nor practical for quantitative traits, which are controlled by multiple genes with minor effects ( Galli et al., 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Genomic selection for target traits in the Australian lentil breeding program

Gebremedhin,

Li,

Shunmugam

et al. 2024

Front. Plant Sci.

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Genomic selection (GS) uses associations between markers and phenotypes to predict the breeding values of individuals. It can be applied early in the breeding cycle to reduce the cross-to-cross generation interval and thereby increase genetic gain per unit of time. The development of cost-effective, high-throughput genotyping platforms has revolutionized plant breeding programs by enabling the implementation of GS at the scale required to achieve impact. As a result, GS is becoming routine in plant breeding, even in minor crops such as pulses. Here we examined 2,081 breeding lines from Agriculture Victoria’s national lentil breeding program for a range of target traits including grain yield, ascochyta blight resistance, botrytis grey mould resistance, salinity and boron stress tolerance, 100-grain weight, seed size index and protein content. A broad range of narrow-sense heritabilities was observed across these traits (0.24-0.66). Genomic prediction models were developed based on 64,781 genome-wide SNPs using Bayesian methodology and genomic estimated breeding values (GEBVs) were calculated. Forward cross-validation was applied to examine the prediction accuracy of GS for these targeted traits. The accuracy of GEBVs was consistently higher (0.34-0.83) than BLUP estimated breeding values (EBVs) (0.22-0.54), indicating a higher expected rate of genetic gain with GS. GS-led parental selection using early generation breeding materials also resulted in higher genetic gain compared to BLUP-based selection performed using later generation breeding lines. Our results show that implementing GS in lentil breeding will fast track the development of high-yielding cultivars with increased resistance to biotic and abiotic stresses, as well as improved seed quality traits.

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Genetics and molecular mapping for salinity stress tolerance at seedling stage in lentil (Lens culinarisMedik)

Cited by 17 publications

References 46 publications

Omics Path to Increasing Productivity in Less-Studied Crops Under Changing Climate—Lentil a Case Study

Omics Path to Increasing Productivity in Less-Studied Crops Under Changing Climate—Lentil a Case Study

Application of Genomics to Understand Salt Tolerance in Lentil

Genomic selection for target traits in the Australian lentil breeding program

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