METHOD: In this study, Rad50 mutations were retrieved from SNPeffect 4.0 database and literature. Each of the mutations was analyzed using various bioinformatic analyses such as PredictSNP, MutPred, SNPeffect 4.0, I-Mutant and MuPro to identify its impact on molecular mechanism, biological function and protein stability, respectively.
RESULTS: We identified 103 mostly occurred mutations in the Rad50 protein domains and motifs, which only 42 mutations were classified as most deleterious. These mutations are mainly situated at the specific motifs such as Walker A, Q-loop, Walker B, D-loop and signature motif of the Rad50 protein. Some of these mutations were predicted to negatively affect several important functional sites that play important roles in DNA repair mechanism and cell cycle signaling pathway, highlighting Rad50 crucial role in this process. Interestingly, mutations located at non-conserved regions were predicted to have neutral/non-damaging effects, in contrast with previous experimental studies that showed deleterious effects. This suggests that software used in this study may have limitations in predicting mutations in non-conserved regions, implying further improvement in their algorithm is needed. In conclusion, this study reveals the priority of acid substitution associated with the genetic disorders. This finding highlights the vital roles of certain residues such as K42E, C681A/S, CC684R/S, S1202R, E1232Q and D1238N/A located in Rad50 conserved regions, which can be considered for a more targeted future studies.
METHODS: In this study, we performed a hybrid assembly of 454 and Illumina sequencing reads from Polygonum minus root and leaf tissues, respectively, to generate a combined transcriptome library as a reference.
RESULTS: A total of 34.37 million filtered and normalized reads were assembled into 188,735 transcripts with a total length of 136.67 Mbp. We performed a similarity search against all the publicly available genome sequences and found similarity matches for 163,200 (86.5%) of Polygonum minus transcripts, largely from Arabidopsis thaliana (58.9%). Transcript abundance in the leaf and root tissues were estimated and validated through RT-qPCR of seven selected transcripts involved in the biosynthesis of phenylpropanoids and flavonoids. All the transcripts were annotated against KEGG pathways to profile transcripts related to the biosynthesis of secondary metabolites.
DISCUSSION: This comprehensive transcriptome profile will serve as a useful sequence resource for molecular genetics and evolutionary research on secondary metabolite biosynthesis in Polygonaceae family. Transcriptome assembly of Polygonum minus can be accessed at http://prims.researchfrontier.org/index.php/dataset/transcriptome.