Current Genomics - Volume 20, Issue 2, 2019

Adaptive convergent evolution, which refers to the same or similar phenotypes produced by species from independent lineages under similar selective pressures, has been widely examined for a long time. Accumulating studies on the adaptive convergent evolution have been reported from many different perspectives (cellular, anatomical, morphological, physiological, biochemical, and behavioral). Recent advances in the genomic technologies have demonstrated that adaptive convergence can arise from specific genetic mechanisms in different hierarchies, ranging from the same nucleotide or amino acid substitutions to the biological functions or pathways. Among these genetic mechanisms, the same amino acid changes in protein-coding genes play an important role in adaptive phenotypic convergence. Methods for detecting adaptive convergence at the protein sequence level have been constantly debated and developed. Here, we review recent progress on using genomic approaches to evaluate the genetic mechanisms of adaptive convergent evolution, summarize the research methods for identifying adaptive amino acid convergence, and discuss the future perspectives for researching adaptive convergent evolution.

After human genome sequencing and rapid changes in genome sequencing methods, we have entered into the era of rapidly accumulating genome-sequencing data. This has derived the development of several types of methods for representing results of genome sequencing data. Circular genome visualization tools are also critical in this area as they provide rapid interpretation and simple visualization of overall data. In the last 15 years, we have seen rapid changes in circular visualization tools after the development of the circos tool with 1-2 tools published per year. Herein we have summarized and revisited all these tools until the third quarter of 2018.

Background: MicroRNAs participate in many molecular mechanisms and signaling transduction pathways that are associated with plant stress tolerance by repressing expression of their target genes. However, how microRNAs enhance tolerance to low temperature stress in plant cells remains elusive. Objective: In this investigation, we demonstrated that overexpression of the rice microRNA528 (OsmiR528) increases cell viability, growth rate, antioxidants content, ascorbate peroxidase (APOX) activity, and superoxide dismutase (SOD) activity and decreases ion leakage rate and thiobarbituric acid reactive substances (TBARS) under low temperature stress in Arabidopsis (Arabidopsis thaliana), pine (Pinus elliottii), and rice (Oryza sativa). Methods: To investigate the potential mechanism of OsmiR528 in increasing cold stress tolerance, we examined expression of stress-associated MYB transcription factors OsGAMYB-like1, OsMYBS3, OsMYB4, OsMYB3R-2, OsMYB5, OsMYB59, OsMYB30, OsMYB1R, and OsMYB20 in rice cells by qRT-PCR. Results: Our experiments demonstrated that OsmiR528 decreases expression of transcription factor OsMYB30 by targeting a F-box domain containing protein gene (Os06g06050), which is a positive regulator of OsMYB30. In OsmiR528 transgenic rice, reduced OsMYB30 expression results in increased expression of BMY genes OsBMY2, OsBMY6, and OsBMY10. The transcript levels of the OsBMY2, OsBMY6, and OsBMY10 were elevated by OsMYB30 knockdown, but decreased by Os- MYB30 overexpression in OsmiR528 transgenic cell lines, suggesting that OsmiR528 increases low temperature tolerance by modulating expression of stress response-related transcription factor. Conclusion: Our experiments provide novel information in increasing our understanding in molecular mechanisms of microRNAs-associated low temperature tolerance and are valuable in plant molecular breeding from monocotyledonous, dicotyledonous, and gymnosperm plants.

Background: Proteins may have none, single, double, or multiple domains, while a single domain may appear in multiple proteins. Their distribution patterns may have impacts on bacterial physiology and lifestyle. Objective: This study aims to understand how domains are distributed and duplicated in bacterial proteomes, in order to better understand bacterial physiology and lifestyles. Methods: In this study, we used 16712 Hidden Markov Models to screen 944 bacterial reference proteomes versus a threshold E-value<0.001. The number of non-redundant domains and duplication rates of redundant domains for each species were calculated. The unique domains, if any, were also identified for each species. In addition, the properties of no-domain proteins were investigated in terms of physicochemical properties. Results: The increasing number of non-redundant domains for a bacterial proteome follows the trend of an asymptotic function. The domain duplication rate is positively correlated with proteome size and increases more rapidly. The high percentage of single-domain proteins is more associated with small proteome size. For each proteome, unique domains were also obtained. Moreover, no-domain proteins show differences with the other three groups for several physicochemical properties analysed in this study. Conclusion: The study confirmed that a low domain duplication rate and a high percentage of singledomain proteins are more likely to be associated with bacterial host-dependent or restricted nicheadapted lifestyle. In addition, the unique lifestyle and physiology were revealed based on the analysis of species-specific domains and core domain interactions or co-occurrences.

Background: In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacterized protein sequence requires extensive, time-consuming and expensive tests. Methods: With the torrential slide of protein sequences produced in the post-genomic age, certain remarkable computational strategies are desired to overwhelm the issue. Keeping in view the composition and sequence order effect within polypeptide chains, an innovative in-silico predictor via a mathematical model is proposed. Results: Later, it was stringently verified using self-consistency, cross-validation and jackknife tests on benchmark datasets. It was established after a rigorous jackknife test that the new predictor values are superior to the values predicted by previous methodologies. Conclusion: This new mathematical technique is the most appropriate and encouraging as compared with the existing models.

Background: Micro RNAs act as a regulatory layer for pharmacogenomics-related gene expression. It could play a role in the efficacy and toxicity of the drug. The SNPs in miRNA genes are linked with different functional consequences. Methods: Hence, we examined the miR (146a G/C, 149C/T, and 196aC/T) polymorphisms in 34 patients with hepatotoxicity, 123 patients without hepatotoxicity, and 155 healthy controls using a PCRRFLP method. Results: In patients with hepatotoxicity, miR196aCT genotype and combined genotype GCT showed a risk for hepatotoxicity severity with borderline significance (OR=2.08, P=0.07; OR=2.88, P=0.06). While comparing between patients with hepatotoxicity and healthy controls, the combined genotypes CCC and GCT have shown a susceptibility to hepatotoxicity severity (OR=2.89, P=0.05; OR=2.60, P=0.09). The miR196TT genotype was associated with the individuals of advanced HIV disease stage (OR=3.68, P=0.04). In HIV patients who consumed alcohol and did not have hepatotoxicity, the miR 196aCT genotype showed susceptibility to acquisition of hepatotoxicity with borderline significance (OR=2.36, P=0.06). Discussion: The miR149TT and 196aTT genotypes showed a risk of acquisition of hepatotoxicity to nevirapine usage among HIV patients without hepatotoxicity (OR=4.19, P=0.07; OR=1.97, P=0.84). In HIV patients with and without hepatotoxicity, the miR 196aCT genotype showed a risk of acquisition of hepatotoxicity and its severity to the combined use of alcohol and nevirapine, respectively (OR=14.18, P=0.08; OR=2.29, P=0.08). In multivariate logistic regression, taking nevirapine, 196aCT genotype had an independent risk factor for hepatotoxicity severity (OR=5.98, P=0.005; OR=2.38, P=0.05). Conclusion: In conclusion, miR196aC/T polymorphism and combined genotypes GCT and CCC may facilitate the risk for acquisition of hepatotoxicity and its severity.