RESULTS: A first set of sORFs was identified from existing annotations that fitted the maximum of 80 residues criterion. A second set was predicted using parameters that specifically searched for ORF candidates of 80 codons or less in the exonic, intronic and intergenic sequences of the subject genomes. A total of 1986 conserved sORFs were predicted and characterized.
CONCLUSIONS: It is evident that numerous open reading frames that could potentially encode for polypeptides consisting of 80 amino acid residues or less are overlooked during standard gene prediction and annotation. From our results, additional targeted reannotation of genomes is clearly able to complement standard genome annotation to identify sORFs. Due to the lack of, and limitations with experimental validation, we propose that a simple conservation analysis can provide an acceptable means of ensuring that the predicted sORFs are sufficiently clear of gene prediction artefacts.
RESULTS: In general, the genetic diversity decreased from Costa Rica towards the north (Honduras) and south-east (Colombia). Principle coordinate analysis (PCoA) showed a single cluster indicating low divergence among palms. The phylogenetic tree and STRUCTURE analysis revealed clusters based on country of origin, indicating considerable gene flow among populations within countries. Based on the values of the genetic diversity parameters, some genetically diverse populations could be identified. Further, a total of 34 individual palms that collectively captured maximum allelic diversity with reduced redundancy were also identified. High pairwise genetic differentiation (Fst > 0.250) among populations was evident, particularly between the Colombian populations and those from Honduras, Panama and Costa Rica. Crossing selected palms from highly differentiated populations could generate off-springs that retain more genetic diversity.
CONCLUSION: The results attained are useful for selecting palms and populations for core collection. The selected materials can also be included into crossing scheme to generate offsprings that capture greater genetic diversity for selection gain in the future.
METHODS: All reported DENV protein sequence data for each serotype was retrieved from the NCBI Entrez Protein (nr) Database (txid: 12637). The downloaded sequences were then separated according to the individual serotype proteins by use of BLASTp search, and subsequently removed for duplicates and co-aligned across the serotypes. Shannon's entropy and mutual information (MI) analyses, by use of AVANA, were performed to measure the diversity within and between the serotype proteins to identify HCSS nonamers. The sequences were evaluated for the presence of promiscuous T-cell epitopes by use of NetCTLpan 1.1 and NetMHCIIpan 3.2 server for human leukocyte antigen (HLA) class I and class II supertypes, respectively. The predicted epitopes were matched to reported epitopes in the Immune Epitope Database.
RESULTS: A total of 2321 nonamers met the HCSS selection criteria of entropy 0.8. Concatenating these resulted in a total of 337 HCSS sequences. DENV4 had the most number of HCSS nonamers; NS5, NS3 and E proteins had among the highest, with none in the C and only one in prM. The HCSS sequences were immune-relevant; 87 HCSS sequences were both reported T-cell epitopes/ligands in human and predicted epitopes, supporting the accuracy of the predictions. A number of the HCSS clustered as immunological hotspots and exhibited putative promiscuity beyond a single HLA supertype. The HCSS sequences represented, on average, ~ 40% of the proteome length for each serotype; more than double of pan-DENV sequences (conserved across the four serotypes), and thus offer a larger choice of sequences for vaccine target selection. HCSS sequences of a given serotype showed significant amino acid difference to all the variants of the other serotypes, supporting the notion of serotype-specificity.
CONCLUSION: This work provides a catalogue of HCSS sequences in the DENV proteome, as candidates for vaccine target selection. The methodology described herein provides a framework for similar application to other pathogens.
RESULTS: This work describes a computational methodology to achieve this analysis, with data of dengue, West Nile, hepatitis A, HIV-1, and influenza A viruses as examples. Our methodology has been implemented as an analytical pipeline that brings significant advancement to the field of reverse vaccinology, enabling systematic screening of known sequence data in nature for identification of vaccine targets. This includes key steps (i) comprehensive and extensive collection of sequence data of viral proteomes (the virome), (ii) data cleaning, (iii) large-scale sequence alignments, (iv) peptide entropy analysis, (v) intra- and inter-species variation analysis of conserved sequences, including human homology analysis, and (vi) functional and immunological relevance analysis.
CONCLUSION: These steps are combined into the pipeline ensuring that a more refined process, as compared to a simple evolutionary conservation analysis, will facilitate a better selection of vaccine targets and their prioritization for subsequent experimental validation.
Materials and Methods: Genomic DNA was extracted from 21 fresh-frozen tumor tissues and blood samples of the same meningioma patients. The entire mtDNA D-loop region (positions 16024-576) was polymerase chain reaction amplified using designed primers, and then amplification products were purified before the direct DNA sequencing proceeds.
Results: Overall, 10 (47.6%) patients were detected to harbor a total of 27 somatic mtDNA D-loop mutations. Most of these mtDNA mutations were identified in the hypervariable segment II (40.7%), with 33.3% being located mainly in the conserved sequence block II of the D310 sequence. Furthermore, 58 different germline variations were observed at 21 nucleotide positions.
Conclusion: Our results suggest that mtDNA alterations in the D-loop region may be an important and early event in developing meningioma. Further studies are needed, including validation in a larger patient cohort, to verify the clinicopathological outcomes of mtDNA mutation biomarkers in meningiomas.