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.

Background The Indian peafowl ( Pavo cristanus ) is native to South Asia and is the national bird of India. Here we present a draft genome sequence of the male blue peacock using Illumina and Oxford Nanopore technology (ONT). Results ONT sequencing gave ∼2.3-fold sequencing coverage, whereas Illumina generated 150–base pair paired-end sequence data at 284.6-fold coverage from 5 libraries. Subsequently, we generated a 0.915-gigabase pair de novo assembly of the peacock genome with a scaffold N50 of 0.23 megabase pairs (Mb). We predict that the peacock genome contains 23,153 protein-coding genes and 75.3 Mb (7.33%) of repetitive sequences. Conclusions We report a high-quality assembly of the peacock genome using a hybrid approach of sequences generated by both Illumina and ONT. The long-read chemistry generated by ONT was useful for addressing challenges related to de novo assembly, particularly at regions containing repetitive sequences spanning longer than the read length, and which could not be resolved with only short-read–based assembly. Contig assembly of Illumina short reads gave an N50 of 1,639 bases, whereas with ONT, the N50 increased by >9-fold to 14,749 bases. The initial contig assembly based on Illumina sequencing reads alone gave 685,241 contigs. Further scaffolding on assembled contigs using both Illumina and ONT sequencing reads resulted in a final assembly of 15,025 super-scaffolds, with an N50 of ∼0.23 Mb. Ninety-five percent of proteins predicted by homology matched with those in a public repository, verifying the completeness of our assembly. Like other phylogenetic studies of avian conserved genes, we found P. cristatus to be most closely related to Gallus gallus , followed by Meleagris gallopavo and Anas platyrhynchos . Compared with the recently published peacock genome assembly, the current, superior, hybrid assembly has greater sequencing depth, fewer non-ATGC sequences, and fewer scaffolds.

BackgroundThe knowledge of the extent and pattern of diversity in the crop species is a prerequisite for any crop improvement as it helps breeders in deciding suitable breeding strategies for their future improvement. Rice is the main staple crop in India with the large number of varieties released every year. Studies based on the small set of rice genotypes have reported a loss in genetic diversity especially after green revolution. However, a detailed study of the trend of diversity in Indian rice varieties is lacking. SSR markers have proven to be a marker of choice for studying the genetic diversity. Therefore, the present study was undertaken with the aim to characterize and assess trends of genetic diversity in a large set of Indian rice varieties (released between 1940–2013), conserved in the National Gene Bank of India using SSR markers.ResultA set of 729 Indian rice varieties were genotyped using 36 HvSSR markers to assess the genetic diversity and genetic relationship. A total of 112 alleles was amplified with an average of 3.11 alleles per locus with mean Polymorphic Information Content (PIC) value of 0.29. Cluster analysis grouped these varieties into two clusters whereas the model based population structure divided them into three populations. AMOVA study based on hierarchical cluster and model based approach showed 3 % and 11 % variation between the populations, respectively. Decadal analysis for gene diversity and PIC showed increasing trend from 1940 to 2005, thereafter values for both the parameters showed decreasing trend between years 2006-2013. In contrast to this, allele number demonstrated increasing trend in these varieties released and notified between1940 to 1985, it remained nearly constant during 1986 to 2005 and again showed an increasing trend.ConclusionOur results demonstrated that the Indian rice varieties harbors huge amount of genetic diversity. However, the trait based improvement program in the last decades forced breeders to rely on few parents, which resulted in loss of gene diversity during 2006 to 2013. The present study indicates the need for broadening the genetic base of Indian rice varieties through the use of diverse parents in the current breeding program.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0437-7) contains supplementary material, which is available to authorized users.

BackgroundSalinity severely limits wheat production in many parts of the world. Development of salt tolerant varieties represents the most practical option for enhancing wheat production from these areas. Application of marker assisted selection may assist in fast tracking development of salt tolerant wheat varieties. However, SSR markers available in the public domain are not specifically targeted to functional regions of wheat genome, therefore large numbers of these need to be analysed for identification of markers associated with traits of interest. With the availability of a fully annotated wheat genome assembly, it is possible to develop SSR markers specifically targeted to genic regions. We performed extensive analysis to identify candidate gene based SSRs and assessed their utility in characterizing molecular diversity in a panel of wheat genotypes.ResultsOur analysis revealed, 161 SSR motifs in 94 salt tolerance candidate genes of wheat. These SSR motifs were nearly equally distributed on the three wheat sub-genomes; 29.8% in A, 35.7% in B and 34.4% in D sub-genome. The maximum number of SSR motifs was present in exons (31.1%) followed by promoters (29.8%), 5’UTRs (21.1%), introns (14.3%) and 3’UTRs (3.7%). Out of the 65 candidate gene based SSR markers selected for validation, 30 were found polymorphic based on initial screening and employed for characterizing genetic diversity in a panel of wheat genotypes including salt tolerant and susceptible lines. These markers generated an average of 2.83 alleles/locus. Phylogenetic analysis revealed four clusters. Salt susceptible genotypes were mainly represented in clusters I and III, whereas high and moderate salt tolerant genotypes were distributed in the remaining two clusters. Population structure analysis revealed two sub-populations, sub-population 1 contained the majority of salt tolerant whereas sub-population 2 contained majority of susceptible genotypes. Moreover, we observed reasonably higher transferability of SSR markers to related wheat species.ConclusionWe have developed salt responsive gene based SSRs in wheat for the first time. These were highly useful in unravelling functional diversity among wheat genotypes with varying responses to salt stress. The identified gene based SSR markers will be valuable genomic resources for genetic/association mapping of salinity tolerance in wheat.Electronic supplementary materialThe online version of this article (10.1186/s12870-018-1476-1) contains supplementary material, which is available to authorized users.

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