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Front Plant Sci ; 10: 345, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31105714


Based on evolutionary, phylogenomic, and synteny analyses of genome sequences for more than a dozen diverse legume species as well as analysis of chromosome counts across the legume family, we conclude that the genus Cercis provides a plausible model for an early evolutionary form of the legume genome. The small Cercis genus is in the earliest-diverging clade in the earliest-diverging legume subfamily (Cercidoideae). The Cercis genome is physically small, and has accumulated mutations at an unusually slow rate compared to other legumes. Chromosome counts across 477 legume genera, combined with phylogenetic reconstructions and histories of whole-genome duplications, suggest that the legume progenitor had 7 chromosomes - as does Cercis. We propose a model in which a legume progenitor, with 7 chromosomes, diversified into species that would become the Cercidoideae and the remaining legume subfamilies; then speciation in the Cercidoideae gave rise to the progenitor of the Cercis genus. There is evidence for a genome duplication in the remaining Cercidoideae, which is likely due to allotetraploidy involving hybridization between a Cercis progenitor and a second diploid species that existed at the time of the polyploidy event. Outside the Cercidoideae, a set of probably independent whole-genome duplications gave rise to the five other legume subfamilies, at least four of which have predominant counts of 12-14 chromosomes among their early-diverging taxa. An earlier study concluded that independent duplications occurred in the Caesalpinioideae, Detarioideae, and Papilionoideae. We conclude that Cercis may be unique among legumes in lacking evidence of polyploidy, a process that has shaped the genomes of all other legumes thus far investigated.

Educ Health (Abingdon) ; 31(3): 163-167, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-31134947


Background: Although alcohol and tobacco are leading causes of mortality and morbidity, their use continues to be common. We hypothesized that awareness about this issue can be spread in a time-efficient way if health talks are conducted within hospital premises itself. Furthermore, this could potentially provide good experiential learning to medical students. Methods: In this longitudinal study, we implemented such an awareness activity and evaluated the outcome. Students who showed interest to volunteer were helped to develop an in-depth understanding of the issue, through detailed presentation and discussions. They conducted health talks near the wards, with patients and their relatives, after routine college hours. An iterative process was used to improve the health talk, based on self-reflection and formative feedback. A pre- and post-self-assessment of students regarding their knowledge and skills on this issue was obtained. A structured, anonymous questionnaire was administered to the audience before and after three of the educational talks. Results: In 29 days, our team of 24 students gave 21 health talks reaching out to 1090 rural people. Pre-post analysis of audience showed improvement in their awareness level and many developed the motivation to quit their addictions. Self-rating of students across all knowledge domains increased by at least 2 points (scale of 1-7) and across all skill domains, it increased by 3 points (P < 0.0001). Conclusion: This model of conducting health talks in hospital premises can enable us to spread health awareness effectively, in a time-efficient and cost-effective way. Furthermore, this model can prove to be a novel and effective academic tool for grooming medical students.

Conhecimentos, Atitudes e Prática em Saúde , Promoção da Saúde/métodos , Educação de Pacientes como Assunto/métodos , Estudantes de Medicina , Alcoolismo , Família , Feminino , Hospitais , Humanos , Índia , Masculino , Inquéritos e Questionários , Tabagismo
PLoS One ; 8(4): e60204, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-23593174


Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6-40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.

Bases de Dados de Ácidos Nucleicos , Genoma/genética , Análise de Sequência de DNA/métodos , Animais , Caenorhabditis elegans/genética , Escherichia coli/genética , Saccharomyces/genética
Bioinformation ; 8(19): 953-6, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-23144557


The function of the protein is primarily dictated by its structure. Therefore it is far more logical to find the functional clues of the protein in its overall 3-dimensional fold or its global structure. In this paper, we have developed a novel Support Vector Machines (SVM) based prediction model for functional classification and prediction of proteins using features extracted from its global structure based on fragment libraries. Fragment libraries have been previously used for abintio modelling of proteins and protein structure comparisons. The query protein structure is broken down into a collection of short contiguous backbone fragments and this collection is discretized using a library of fragments. The input feature vector is frequency vector that counts the number of each library fragment in the collection of fragments by all-to-all fragment comparisons. SVM models were trained and optimised for obtaining the best 10-fold Cross validation accuracy for classification. As an example, this method was applied for prediction and classification of Cell Adhesion molecules (CAMs). Thirty-four different fragment libraries with sizes ranging from 4 to 400 and fragment lengths ranging from 4 to 12 were used for obtaining the best prediction model. The best 10-fold CV accuracy of 95.25% was obtained for library of 400 fragments of length 10. An accuracy of 87.5% was obtained on an unseen test dataset consisting of 20 CAMs and 20 NonCAMs. This shows that protein structure can be accurately and uniquely described using 400 representative fragments of length 10.