Functional annotation of mulberry (Morus spp.) transcriptome, differential expression of genes related to growth and identification of putative genic SSRs, SNPs and InDels.

Abstract

Growth is a complex trait associated with mulberry leaf yield and controlled by several genes. In this study, we have explored the molecular basis underlying growth using Transcriptome profiling of contrasting genotypes. A total of 66.6 Mbp of primary transcriptomes from high growth (HGG)-Jalalgarah-3 and M. laevigata (H) and, low growth genotypes (LGG)-Harmutty and Vadagaraparai-2; resulting in 24210, 27998, 28085 and 28764 final transcripts respectively. Out of the 34096 pooled transcripts, 20249 transcripts matched with at least one sequence of the non-redundant database. Functional annotation resulted in the categorization of 18970 transcripts into 3 gene ontology (GO) terms and 7440 were assigned to 23 Kyoto encyclopaedia of genes and genomes (KEGG) pathway. Based on the differentially expressed genes and gene enrichment analysis, over expression of photosynthetic related transcripts in HGG and defence related transcripts in LGG were noted. Simple sequence repeats were mined from unique transcripts and the most abundant motifs were tri- (1883) followed by di- (1710), tetra- (192), penta- (68) and hexa- (40) repeats. Further, a total of 390897 high quality SNPs and 8081 InDels were identified by mapping onto Morus notabilis reference genome. The study provides an insight into the expression of genes involved in growth and further research on utilization in gentic improvement of the crop.