Improved alignment quality by combining evolutionary information, predicted secondary structure and self-organizing maps

Background  

Protein sequence alignment is one of the basic tools in bioinformatics. Correct alignments are required for a range of tasks including the derivation of phylogenetic trees and protein structure prediction. Numerous studies have shown that the incorporation of predicted secondary structure information into alignment algorithms improves their performance. Secondary structure predictors have to be trained on a set of somewhat arbitrarily defined states (e.g. helix, strand, coil), and it has been shown that the choice of these states has some effect on alignment quality. However, it is not unlikely that prediction of other structural features also could provide an improvement. In this study we use an unsupervised clustering method, the self-organizing map, to assign sequence profile windows to "structural states" and assess their use in sequence alignment.     

Biomarkers of neurodegenerative disorders： How good are they？

Biomarkers are very important indicators of normal and abnormal biological processes. Specific changes in pathologies,biochemistries and genetics can give us comprehensive information regarding the nature of any particular disease. A good biomarker should be precise and reliable, distinguishable between normal and interested disease, and differentiable between different diseases. It is believed that biomarkers have great potential in predicting chances for diseases, aiding in early diagnosis, and setting standards for the development of new remedies to treat diseases. New technologies have enabled scientists to identify biomarkers of several different neurodegenerative diseases. The followings, for instance,are only a few of the many new biomarkers that have been recently identified: the phosphorylated tau protein and aggregated β-amyloid peptide for Alzheimer‘s disease (AD), α-synuclein contained Lewy bodies and altered dopamine transporter (DAT) imaging for Parkinson‘s disease (PD), SOD mutations for familial amyotrophic lateral sclerosis (ALS), and CAG repeats resulted from Huntington‘s gene mutations in Huntington‘s disease (HD). This article will focus on the most-recent findings of biomarkers belonging to the four mentioned neurodegenerative diseases.     

AFLP-Based Genetic Diversity Assessment of Commercially Important Tea Germplasm in India

India has a large repository of important tea accessions and, therefore, plays a major role in improving production and quality of tea across the world. Using seven AFLP primer combinations, we analyzed 123 commercially important tea accessions representing major populations in India. The overall genetic similarity recorded was 51%. No significant differences were recorded in average genetic similarity among tea populations cultivated in various geographic regions (northwest 0.60, northeast and south both 0.59). UPGMA cluster analysis grouped the tea accessions according to geographic locations, with a bias toward China or Assam/Cambod types. Cluster analysis results were congruent with principal component analysis. Further, analysis of molecular variance detected a high level of genetic variation (85%) within and limited genetic variation (15%) among the populations, suggesting their origin from a similar genetic pool.     

Identification, characterization and utilization of unigene derived microsatellite markers in tea (Camellia sinensis L.)

Background

Despite great advances in genomic technology observed in several crop species, the availability of molecular tools such as microsatellite markers has been limited in tea (Camellia sinensis L.). The development of microsatellite markers will have a major impact on genetic analysis, gene mapping and marker assisted breeding. Unigene derived microsatellite (UGMS) markers identified from publicly available sequence database have the advantage of assaying variation in the expressed component of the genome with unique identity and position. Therefore, they can serve as efficient and cost effective alternative markers in such species.

Results

Considering the multiple advantages of UGMS markers, 1,223 unigenes were predicted from 2,181 expressed sequence tags (ESTs) of tea (Camellia sinensis L.). A total of 109 (8.9%) unigenes containing 120 SSRs were identified. SSR abundance was one in every 3.55 kb of EST sequences. The microsatellites mainly comprised of di (50.8%), tri (30.8%), tetra (6.6%), penta (7.5%) and few hexa (4.1%) nucleotide repeats. Among the dinucleotide repeats, (GA)n.(TC)n were most abundant (83.6%). Ninety six primer pairs could be designed form 83.5% of SSR containing unigenes. Of these, 61 (63.5%) primer pairs were experimentally validated and used to investigate the genetic diversity among the 34 accessions of different Camellia spp. Fifty one primer pairs (83.6%) were successfully cross transferred to the related species at various levels. Functional annotation of the unigenes containing SSRs was done through gene ontology (GO) characterization. Thirty six (60%) of them revealed significant sequence similarity with the known/putative proteins of Arabidopsis thaliana. Polymorphism information content (PIC) ranged from 0.018 to 0.972 with a mean value of 0.497. The average heterozygosity expected (H _E ) and observed (H _o ) obtained was 0.654 and 0.413 respectively, thereby suggesting highly heterogeneous nature of tea. Further, test for IAM and SMM models for the UGMS loci showed excess heterozygosity and did not show any bottleneck operating in the tea population.

Conclusion

UGMS markers identified and characterized in this study provided insight about the abundance and distribution of SSR in the expressed genome of C. sinensis. The identification and validation of 61 new UGMS markers will not only help in intra and inter specific genetic diversity assessment but also be enriching limited microsatellite markers resource in tea. Further, the use of these markers would reduce the cost and facilitate the gene mapping and marker-aided selection in tea. Since, 36 of these UGMS markers correspond to the Arabidopsis protein sequence data with known functions will offer the opportunity to investigate the consequences of SSR polymorphism on gene functions.     

Silicon and Nitric Oxide-Mediated Regulation of Growth Attributes,Metabolites and Antioxidant Defense System of Radish (<i>Raphanus sativus</i> L.) under Arsenic Stress

Arsenic (As) contaminated food chains have emerged as a serious public concern for humans and animals and are known to affect the cultivation of edible crops throughout the world. Therefore, the present study was designed to investigate the individual as well as the combined effects of exogenous silicon (Si) and sodium nitroprusside (SNP), a nitric oxide (NO) donor, on plant growth, metabolites, and antioxidant defense systems of radish (Raphanus sativus L.) plants under three different concentrations of As stress, i.e., 0.3, 0.5, and 0.7 mM in a pot experiment. The results showed that As stress reduced the growth parameters of radish plants by increasing the level of oxidative stress markers, i.e., malondialdehyde and hydrogen peroxide. However, foliar application of Si (2 mM) and pretreatment with SNP (100 µM) alone as well as in combination with Si improved the plant growth parameters, i.e., root length, fresh and dry weight of plants under As stress. Furthermore, As stress also reduced protein, and metabolites contents (flavonoids, phenolic and anthocyanin). Activities of antioxidative enzymes such as catalase (CAT), ascorbate peroxidase (APX), guaiacol peroxidase (POD), and polyphenol oxidase (PPO), as well as the content of non-enzymatic antioxidants (glutathione and ascorbic acid) decreased under As stress. In most of the parameters in radish, As III concentration showed maximum reduction, as compared to As I and II concentrations. However, the individual and combined application of Si and NO significantly alleviated the As-mediated oxidative stress in radish plants by increasing the protein, and metabolites content. Enhancement in the activities of CAT, APX, POD and PPO enzymes were recorded. Contents of glutathione and ascorbic acid were also enhanced in response to co-application of Si and NO under As stress. Results obtained were more pronounced when Si and NO were applied in combination under As stress, as compared to their individual application. In short, the current study highlights that Si and NO synergistically regulate plant growth through lowering the As-mediated oxidative stress by upregulating the metabolites content, activity of antioxidative enzymes and non-enzymatic antioxidants in radish plants.

     

MeTaDoR: a comprehensive resource for membrane targeting domains and their host proteins

MOTIVATION: Protein-lipid interactions play a central role in cellular signaling and membrane trafficking and at the core of these interactions are domains specialized in lipid binding and membrane targeting. Considering the importance of these domains, we have created MeTaDoR, a comprehensive resource dedicated to membrane targeting domains (MTDs). RESULT: MeTaDoR begins with a brief introduction about all the important MTDs including their subcellular localization and structural features. Sequences of all known MTDs are then provided in two formats: standard Prosite format and a parsed tab-delimited format that provides a manually curated classification into binding or non-binding. Structures of all MTDs and host proteins known so far are provided with links to PDB and Pfam databases. Membrane-binding orientation of these proteins, whether experimentally determined or proposed, is also provided with links to the appropriate literature. To facilitate molecular dynamics studies of these proteins, the force-field parameters for many non-standard lipids that commonly interact with these proteins are also provided. Finally, an online server for predicting membrane-binding proteins and a search function with various search fields are included. The resource is publicly available and will be updated on a regular basis.     

Biosynthesis and therapeutic implications of iridoid glycosides from <Emphasis Type="Italic">Picrorhiza</Emphasis> genus: the road ahead

Picrorhiza genus is emerging as an important paradigm for herbal drug formulations due to its versatile iridoid glycosides exhibition and robustness in the treatment of diverse infections including hepatic amoebiasis, cancer, malaria, ulcerative colitis and cerebral ischemia reperfusion injury. Owing to the superiority of these bioactivities, iridoid glycosides from Picrorhiza have become a hot research area over the years. A metabolic pathway for the formation of iridoid glycosides has been proposed. However, some enzymes and genes of this route are still unidentified and demand the enumeration of facilitating pathways contributing to the biosynthesis of iridoid glycosides. This review summarizes the current knowledge of all naturally occurring iridoid glycosides from Picrorhiza, their biosynthesis and pharmacological capabilities which could provide the insight into metabolic regulation and the basis for the development of new drugs.