Comparison of SSR and SNP Markers in Estimation of Genetic Diversity and Population Structure of Indian Rice Varieties

<div><p>Simple sequence repeat (SSR) and Single Nucleotide Polymorphic (SNP), the two most robust markers for identifying rice varieties were compared for assessment of genetic diversity and population structure. Total 375 varieties of rice from various regions of India archived at the Indian National GeneBank, NBPGR, New Delhi, were analyzed using thirty six genetic markers, each of hypervariable SSR (HvSSR) and SNP which were distributed across 12 rice chromosomes. A total of 80 alleles were amplified with the SSR markers with an average of 2.22 alleles per locus whereas, 72 alleles were amplified with SNP markers. Polymorphic information content (PIC) values for HvSSR ranged from 0.04 to 0.5 with an average of 0.25. In the case of SNP markers, PIC values ranged from 0.03 to 0.37 with an average of 0.23. Genetic relatedness among the varieties was studied; utilizing an unrooted tree all the genotypes were grouped into three major clusters with both SSR and SNP markers. Analysis of molecular variance (AMOVA) indicated that maximum diversity was partitioned between and within individual level but not between populations. Principal coordinate analysis (PCoA) with SSR markers showed that genotypes were uniformly distributed across the two axes with 13.33% of cumulative variation whereas, in case of SNP markers varieties were grouped into three broad groups across two axes with 45.20% of cumulative variation. Population structure were tested using K values from 1 to 20, but there was no clear population structure, therefore Ln(PD) derived Δk was plotted against the K to determine the number of populations. In case of SSR maximum Δk was at K=5 whereas, in case of SNP maximum Δk was found at K=15, suggesting that resolution of population was higher with SNP markers, but SSR were more efficient for diversity analysis. </p> </div

Model based clustering of (a) SSR (K=5) and (b) SNP (K=15) of Indica rice cultivars, (boxes indicates distribution of Autumn rice, also known as 'Aus' in West Bengal, 'Ahu' in Assam, 'Beali' in Orissa, 'Bhadai' in Bihar, 'Virippu' in Kerala and 'Kuruvai/kar/ Sornavari' in Tamil Nadu).

<p>Model based clustering of (a) SSR (K=5) and (b) SNP (K=15) of Indica rice cultivars, (boxes indicates distribution of Autumn rice, also known as 'Aus' in West Bengal, 'Ahu' in Assam, 'Beali' in Orissa, 'Bhadai' in Bihar, 'Virippu' in Kerala and 'Kuruvai/kar/ Sornavari' in Tamil Nadu).</p

Major allele frequency spectrum for (a) 36 SSR and (b) 36 SNPs in 375 rice varieties.

<p>Major allele frequency spectrum for (a) 36 SSR and (b) 36 SNPs in 375 rice varieties.</p

Principal Coordinate Analysis (PCoA) of 375 rice varieties based on (a) SSR data and (b) SNP data.

<p>Principal Coordinate Analysis (PCoA) of 375 rice varieties based on (a) SSR data and (b) SNP data.</p

Estimation of population using LnP(D) derived Δk for k from 1 to20, (a) SSRs and (b) SNPs.

<p>Estimation of population using LnP(D) derived Δk for k from 1 to20, (a) SSRs and (b) SNPs.</p

NJ tree constructed for (a) SSR and (b) SNP data based on regions south (red), north-east (sky blue), east (blue), north (green), west (pink) and CVR (orange).

<p>NJ tree constructed for (a) SSR and (b) SNP data based on regions south (red), north-east (sky blue), east (blue), north (green), west (pink) and CVR (orange).</p

Analysis of Molecular variance (AMOVA) of 375 rice varieties based on (a) SSR data and (b) SNP data.

<p>Analysis of Molecular variance (AMOVA) of 375 rice varieties based on (a) SSR data and (b) SNP data.</p

Analysis of Genetic Diversity and Population Structure of Rice Germplasm from North-Eastern Region of India and Development of a Core Germplasm Set

<div><p>The North-Eastern region (NER) of India, comprising of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland and Tripura, is a hot spot for genetic diversity and the most probable origin of rice. North-east rice collections are known to possess various agronomically important traits like biotic and abiotic stress tolerance, unique grain and cooking quality. The genetic diversity and associated population structure of 6,984 rice accessions, originating from NER, were assessed using 36 genome wide unlinked single nucleotide polymorphism (SNP) markers distributed across the 12 rice chromosomes. All of the 36 SNP loci were polymorphic and bi-allelic, contained five types of base substitutions and together produced nine types of alleles. The polymorphic information content (PIC) ranged from 0.004 for Tripura to 0.375 for Manipur and major allele frequency ranged from 0.50 for Assam to 0.99 for Tripura. Heterozygosity ranged from 0.002 in Nagaland to 0.42 in Mizoram and gene diversity ranged from 0.006 in Arunachal Pradesh to 0.50 in Manipur. The genetic relatedness among the rice accessions was evaluated using an unrooted phylogenetic tree analysis, which grouped all accessions into three major clusters. For determining population structure, populations K = 1 to K = 20 were tested and population K = 3 was present in all the states, with the exception of Meghalaya and Manipur where, K = 5 and K = 4 populations were present, respectively. Principal Coordinate Analysis (PCoA) showed that accessions were distributed according to their population structure. AMOVA analysis showed that, maximum diversity was partitioned at the individual accession level (73% for Nagaland, 58% for Arunachal Pradesh and 57% for Tripura). Using POWERCORE software, a core set of 701 accessions was obtained, which accounted for approximately 10% of the total NE India collections, representing 99.9% of the allelic diversity. The rice core set developed will be a valuable resource for future genomic studies and crop improvement strategies.</p></div

Additional file 1: Table S1. of Genetic diversity trend in Indian rice varieties: an analysis using SSR markers

List of rice varieties characterized using HvSSR markers along with their pedigree, IC number, year of release and traits. (XLSX 79 kb

Additional file 3: Figure S1. of Genetic diversity trend in Indian rice varieties: an analysis using SSR markers

Detailed population structure of 729 rice varieties based on SSR data. (PDF 459 kb