Genome-wide association studies reveal novel loci controlling tuber flesh color and oxidative browning inDioscorea alata

Abstract

Background Consumers preferences for food crops are guided by quality attributes. This study aimed at deciphering the genetic basis of quality traits, especially tuber flesh color (FC) and oxidative browning (OB) in Dioscorea alata, based on the genome-wide association studies (GWAS) approach. The D. alata panel was planted at two locations in Guadeloupe. At harvest, the FC was scored visually as white, cream, or purple on longitudinally sliced mature tubers. The OB was scored visually as the presence or absence of browning after 15 minutes of exposure of the sliced samples to ambient air. Results Phenotypic characterization for FC and OB of a diverse panel of D. alata genotypes highlighted significant variation within the panel and across two locations. The genotypes within the panel displayed a weak structure and could be classified into 3 subpopulations. GWAS identified 14 and 4 significant associations for tuber FC and OB, respectively, with phenotypic variance, explained values ranging from 7.18 to 18.04%. Allele segregation analysis at the significantly associated loci highlighted the favorable alleles for the desired traits, i.e., white FC and no OB. A total of 24 putative candidate genes were identified around the significant signals. A comparative analysis with previously reported quantitative trait loci indicated that numerous genomic regions control these traits in D. alata. Conclusion Our study provides important insights into the genetic control of tuber FC and OB in D. alata. The major and stable loci can be further utilized to improve selection in breeding programs for developing new cultivars with enhanced tuber quality.

Detecting the genetic variants associated with key culinary traits inDioscorea alata

“…In our previous study, we performed a comprehensive genetic analysis on our diversity panel consisting of multiple genotypes and showed a low structure and its suitability for GWAS [36]. In order to determine how statistical models and SNP density affect GWAS, we selected two traits, cooking time and DM, and performed GWAS with two SNP densities: low density with 45,000 SNPs (Figure 3A, 0.09 SNPs/kb) and high density with 1.9M SNPs (3.9 SNPs/kb)) as well as two statistical models (FarmCPU and MLM).…”

“… A) subplot A displays the SNP density at a lower level, with 45,000 SNPs. The plot with 1.9 M SNPs was presented by Dossa et al [36]. This plot illustrates the distribution and density of SNPs across the genome, indicating the coverage and resolution of the genotyping data used in the GWAS analysis B) The Manhattan plot in subplot B represents the GWAS associations obtained using the lower SNP density.…”

“…GWAS was performed using two statistical models: Fixed and random model circulating probability unification (FarmCPU) and mix linear model. The FarmCPU algorithm has enhanced statistical power and computational efficiency and can mitigate false associations in GWAS [36]. To identify SNPs significantly associated with traits in each environment, the adjusted p-value was utilized.…”

Genomic insights into greater yam tuber quality traits

“…The UDP-glucosyltransferase was found associated with purple colour confirming its role in colour formation in yam tuber. None of these genes were found by Wu et al (2015) through transcriptome analysis of two contrasting D. alata genotypes for tuber purple colour, or by a genome-wide association analysis (Dossa et al, 2023). These results indicate that more genes could be involved in this trait.…”

“…was extracted from leaves according to a protocol using mixed alkyl trimethylammonium bromide (MATAB) buffer and NucleoMag Plant Kit (Macherey-Nagel, Germany) already described by (Cormier et al, 2019). Sequencing libraries were prepared as described in Dossa et al (2023). Paired-end high throughput sequencing (2 × 150 bp) was performed on an Illumina NovaSeq 6000 instrument on GeT-PlaGe platform, (Toulouse, France) and Genewiz company (Leipzig, Germany).…”