Genome-wide SNP identification and characterization in two soybean cultivars with contrasting Mungbean Yellow Mosaic India Virus disease resistance traits

Abstract

Mungbean yellow mosaic India virus (MYMIV) is a bipartite Geminivirus, which causes severe yield loss in soybean (Glycine max). Considering this, the present study was conducted to develop large-scale genome-wide single nucleotide polymorphism (SNP) markers and identify potential markers linked with known disease resistance loci for their effective use in genomics-assisted breeding to impart durable MYMIV tolerance. The whole-genome re-sequencing of MYMIV resistant cultivar 'UPSM-534' and susceptible Indian cultivar 'JS-335' was performed to identify high-quality SNPs and InDels (insertion and deletions). Approximately 234 and 255 million of 100-bp paired-end reads were generated from UPSM-534 and JS-335, respectively, which provided ~98% coverage of reference soybean genome. A total of 3083987 SNPs (1559556 in UPSM-534 and 1524431 in JS-335) and 562858 InDels (281958 in UPSM-534 and 280900 in JS-335) were identified. Of these, 1514 SNPs were found to be present in 564 candidate disease resistance genes. Among these, 829 non-synonymous and 671 synonymous SNPs were detected in 266 and 286 defence-related genes, respectively. Noteworthy, a non-synonymous SNP (in chromosome 18, named 18-1861613) at the 149th base-pair of LEUCINE-RICH REPEAT RECEPTOR-LIKE PROTEIN KINASE gene responsible for a G/C transversion [proline (CCC) to alanine(GCC)] was identified and validated in a set of 12 soybean cultivars. Taken together, the present study generated a large-scale genomic resource such as, SNPs and InDels at a genome-wide scale that will facilitate the dissection of various complex traits through construction of high-density linkage maps and fine mapping. In the present scenario, these markers can be effectively used to design high-density SNP arrays for their large-scale validation and high-throughput genotyping in diverse natural and mapping populations, which could accelerate genomics-assisted MYMIV disease resistance breeding in soybean.

Fig 1. Phenotypic expression of soybean cultivars (a) UPSM-534 [MYMIV tolerant] and (b) JS-335 [MYMIV susceptible] in field conditions.

Fig 2. Comparison of (a) SNP and (b) InDel distributions between both the cultivars (JS-335 and UPSM-534).

Fig 3. Frequency of different nucleotides substitution types in the identified SNPs from JS-335 and UPSM-534.

Fig 4. Frequency of length distribution of InDels JS-335 and UPSM-534.

Fig 5. Number and distribution of (a) SNPs and (b) InDels detected on the soybean chromosomes in both the cultivars (JS-335 and UPSM-534).

Fig 6. Density distribution of (a) SNP and (b) InDel in all the 20 chromosomes of soybean.

JS-335 (outer circle) and UPSM-534 (inner circle).

Fig 7. Annotation of single-nucleotide polymorphisms (SNPs) and InDels.

(a) Distribution of SNPs and Indels in intergenic, upstream and downstream region. (b, c) Distribution of SNPs in different genic regions for JS-335 and UPSM-534. (d, e) Distribution of InDels in genic regions for JS-335 and UPSM-534. The number of synonymous and non-synonymous SNPs detected within the CDS region has also been shown.

Fig 8. PCR amplification of 12 genomic DNA samples using 18–1861613 primer.

M, Marker; JS-335 (susceptible); UPSM-534 (resistant); 1S - 5S, susceptible cultivars; 6R - 10R; resistant cultivars.

Fig 9. Multiple alignment of sequences obtained from 18–1861613 primer in 12 soybean cultivars using Glycine max var.

‘Williams 82’ genome as reference. SNP position is indicated with blue down arrow.

Fig 10. Physical map showing representative SNPs and the LRR-RP linked SNP 18–1861613 highlighted in a box.

The numbers at the left indicate the physical position of respective SNPs in megabase and the SNP IDs are shown in the right. The complete physical map of 1514 SNPs detected in 564 defence response-related genes is shown in S3 Fig.