Genome-Wide Association Study (GWAS) Analysis of Camelina Seedling Germination under Salt Stress Condition

Abstract

Camelina sativa is an important renewable oilseed crop for biofuel and feedstock that can relieve the reliance on petroleum-derived oils and reduce greenhouse gases and waste solids resulting from petroleum-derived oils consumption. C. sativa has recently seen revived attention due to its high oil content, high omega-3 unsaturated fatty acids, short life cycle, broader regional adaptation, and low-input agronomic requirements. However, abiotic stress such as salinity stress has imposed threatens on plant photosynthesis and growth by reducing water availability or osmotic stress, ion (Na+ and Cl−) toxicity, nutritional disorders and oxidative stress yield. There still remains much to know for the molecular mechanisms underlying these effects. In this study, a preliminary study applying 10 C. sativa cultivars to be treated under a gradient NaCl concentrations ranging from 0–250 mM and found that 100 mM was the optimal NaCl concentration to effectively differentiate phenotypic performance among different genotypes. Then, a spring panel consisting of 211 C. sativa accessions were germinated under 100 mM NaCl concentration. Six seedling germination traits, including germination rate at two stages (5-day and 9-day seedling stages), germination index, dry and fresh weight, and dry/fresh ratio, were measured. Significant correlations were found between the germination rate at two stages as well as plant biomass traits. Combining the phenotypic data and previously obtained genotypic data, a total of 17 significant trait-associated single nucleotide polymorphisms (SNPs) for the germination rate at the two stages and dry weight were identified from genome-wide association analysis (GWAS). These SNPs are located on putative candidate genes controlling plant root development by synergistically mediating phosphate metabolism, signal transduction and cell membrane activities. These identified SNPs could provide a foundation for future molecular breeding efforts aimed at improved salt tolerance in C. sativa.

Genome-wide association study (GWAS) of seed germination-related traits in rice and identification of candidate genes

“…Auxin is positively related to the germination process (Hussain et al 2020). This QTL is similar to S1_1910174 QTL for SDW under salinity condition reported by Luo et al (2020). Other candidate gene was calmodulin-related calcium sensor protein.…”

Realizing the Potential of Camelina sativa as a Bioenergy Crop for a Changing Global Climate

“…Using 189 lines from this population, a genetic map was created containing 2376 single nucleotide polymorphisms (SNPs) to identify quantitative trait loci (QTLs) associated with oil content, seed size, pod size, and seed number per pod as a first step towards isolating genes that control for seed development and oil accumulation [ 301 ]. In another example, a total of 213 spring C. sativa accessions were collected and genotyped to assess the genetic diversity available for future breeding efforts [ 302 ]. A total of 6192 SNPs were identified using genotyping-by-sequencing technology and used to reveal two distinct populations of C. sativa arising from Germany and eastern Europe [ 302 ].…”

“…In another example, a total of 213 spring C. sativa accessions were collected and genotyped to assess the genetic diversity available for future breeding efforts [ 302 ]. A total of 6192 SNPs were identified using genotyping-by-sequencing technology and used to reveal two distinct populations of C. sativa arising from Germany and eastern Europe [ 302 ].…”

A review of biotechnological approaches towards crop improvement in African yam bean (Sphenostylis stenocarpa Hochst. Ex A. Rich.)

“…Genome-wide association studies (GWAS) is a tool used to assess the relationship between single-nucleotide polymorphisms (SNP) and variation in a particular phenotypic trait. This technique overcomes some limitations associated with conventional breeding ( Luo et al., 2020 ) and has been applied in several crops to identify genes controlling specific characteristics ( Table 5 ). In using GWAS, consideration is given to the magnitude of linkage disequilibrium (degree of non-random association of alleles at different loci); and likely spurious association derived from the population structure and genetic relatedness ( Zeng et al., 2017 ).…”