70
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Genome Sequence of Leishmania (Leishmania) amazonensis: Functional Annotation and Extended Analysis of Gene Models

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We present the sequencing and annotation of the Leishmania (Leishmania) amazonensis genome, an etiological agent of human cutaneous leishmaniasis in the Amazon region of Brazil. L. (L.) amazonensis shares features with Leishmania (L.) mexicana but also exhibits unique characteristics regarding geographical distribution and clinical manifestations of cutaneous lesions (e.g. borderline disseminated cutaneous leishmaniasis). Predicted genes were scored for orthologous gene families and conserved domains in comparison with other human pathogenic Leishmania spp. Carboxypeptidase, aminotransferase, and 3′-nucleotidase genes and ATPase, thioredoxin, and chaperone-related domains were represented more abundantly in L. (L.) amazonensis and L. (L.) mexicana species. Phylogenetic analysis revealed that these two species share groups of amastin surface proteins unique to the genus that could be related to specific features of disease outcomes and host cell interactions. Additionally, we describe a hypothetical hybrid interactome of potentially secreted L. (L.) amazonensis proteins and host proteins under the assumption that parasite factors mimic their mammalian counterparts. The model predicts an interaction between an L. (L.) amazonensis heat-shock protein and mammalian Toll-like receptor 9, which is implicated in important immune responses such as cytokine and nitric oxide production. The analysis presented here represents valuable information for future studies of leishmaniasis pathogenicity and treatment.

          Related collections

          Most cited references65

          • Record: found
          • Abstract: found
          • Article: not found

          The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications.

          P. Sharp, W Li (1987)
          A simple, effective measure of synonymous codon usage bias, the Codon Adaptation Index, is detailed. The index uses a reference set of highly expressed genes from a species to assess the relative merits of each codon, and a score for a gene is calculated from the frequency of use of all codons in that gene. The index assesses the extent to which selection has been effective in moulding the pattern of codon usage. In that respect it is useful for predicting the level of expression of a gene, for assessing the adaptation of viral genes to their hosts, and for making comparisons of codon usage in different organisms. The index may also give an approximate indication of the likely success of heterologous gene expression.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            UniRef: comprehensive and non-redundant UniProt reference clusters.

            Redundant protein sequences in biological databases hinder sequence similarity searches and make interpretation of search results difficult. Clustering of protein sequence space based on sequence similarity helps organize all sequences into manageable datasets and reduces sampling bias and overrepresentation of sequences. The UniRef (UniProt Reference Clusters) provide clustered sets of sequences from the UniProt Knowledgebase (UniProtKB) and selected UniProt Archive records to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences. Currently covering >4 million source sequences, the UniRef100 database combines identical sequences and subfragments from any source organism into a single UniRef entry. UniRef90 and UniRef50 are built by clustering UniRef100 sequences at the 90 or 50% sequence identity levels. UniRef100, UniRef90 and UniRef50 yield a database size reduction of approximately 10, 40 and 70%, respectively, from the source sequence set. The reduced redundancy increases the speed of similarity searches and improves detection of distant relationships. UniRef entries contain summary cluster and membership information, including the sequence of a representative protein, member count and common taxonomy of the cluster, the accession numbers of all the merged entries and links to rich functional annotation in UniProtKB to facilitate biological discovery. UniRef has already been applied to broad research areas ranging from genome annotation to proteomics data analysis. UniRef is updated biweekly and is available for online search and retrieval at http://www.uniprot.org, as well as for download at ftp://ftp.uniprot.org/pub/databases/uniprot/uniref. Supplementary data are available at Bioinformatics online.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              SSAHA: a fast search method for large DNA databases.

              We describe an algorithm, SSAHA (Sequence Search and Alignment by Hashing Algorithm), for performing fast searches on databases containing multiple gigabases of DNA. Sequences in the database are preprocessed by breaking them into consecutive k-tuples of k contiguous bases and then using a hash table to store the position of each occurrence of each k-tuple. Searching for a query sequence in the database is done by obtaining from the hash table the "hits" for each k-tuple in the query sequence and then performing a sort on the results. We discuss the effect of the tuple length k on the search speed, memory usage, and sensitivity of the algorithm and present the results of computational experiments which show that SSAHA can be three to four orders of magnitude faster than BLAST or FASTA, while requiring less memory than suffix tree methods. The SSAHA algorithm is used for high-throughput single nucleotide polymorphism (SNP) detection and very large scale sequence assembly. Also, it provides Web-based sequence search facilities for Ensembl projects.
                Bookmark

                Author and article information

                Journal
                DNA Res
                DNA Res
                dnares
                dnares
                DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes
                Oxford University Press
                1340-2838
                1756-1663
                December 2013
                15 July 2013
                15 July 2013
                : 20
                : 6
                : 567-581
                Affiliations
                [1 ]Departamento de Microbiologia, Imunologia e Parasitologia, Escola Paulista de Medicina, Universidade Federal de São Paulo − EPM/UNIFESP , Rua Botucatu 862, 6 o andar, 04023-062 São Paulo, Brazil
                [2 ]Laboratório Nacional de Biociências, LNBio/CNPEM , Campinas, Brazil
                [3 ]Laboratório de Genômica e Expressão, LGE/UNICAMP , Campinas, Brazil
                [4 ]Centro de Pesquisa e Desenvolvimento de Recursos Genéticos Vegetais, Instituto Agronômico de Campinas – IAC , Campinas, Brazil
                [5 ]Department of Pediatrics, School of Medicine, University of California , San Diego, CA, USA
                [6 ]Departamento de Ciência e Tecnologia, Universidade Federal de São Paulo − UNIFESP , São José dos Campos, Brazil
                [7 ]Department of Genetics, School of Medicine, University of North Carolina , Chapel Hill, NC, USA
                [8 ]Departamento de Biologia Geral, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais-ICB/UFMG , Minas Gerais, Brazil
                Author notes
                [* ]To whom correspondence should be addressed: Tel. +55 11 5576-4532. Fax. +55 11 5571-1095. E-mail: dianabahia@ 123456hotmail.com
                [†]

                The authors agree that the first three authors should be regarded as joint first authors.

                Article
                dst031
                10.1093/dnares/dst031
                3859324
                23857904
                89f1166c-2b0f-4650-99f6-f3cc1725635f
                © The Author 2013. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.

                History
                : 24 January 2013
                : 17 June 2013
                Page count
                Pages: 16
                Categories
                Full Papers

                Genetics
                amastin,genome,leishmania amazonensis,interactome,heat-shock protein
                Genetics
                amastin, genome, leishmania amazonensis, interactome, heat-shock protein

                Comments

                Comment on this article