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.
BackgroundThe macaúba palm is a novel feedstock for oil production suitable for multiple uses, including as biodiesel and in the food and cosmetic industries. As an efficient alternative, the macaúba palm has limited genomic resources, particularly expressed sequence tag (EST) markers. We report a comprehensive set of validated EST-simple sequence repeat (SSR) markers by using transcriptome sequencing, its application in genetic diversity analysis and cross transferability in other palm trees with environmental and economic importance.ResultsIn this study, a total of 418 EST-SSRs were identified to be unique for one transcript and region; 232 EST-SSRs were selected, with trinucleotide repeats being the most frequent motif, representing 380 (90.9%), followed by composited (4.5%), di- (3.6%), and hexanucleotides (3.6%). A total of 145 EST-SSRs (62.5%) were validated for consistent amplification in seventeen macaúba palm samples, and 100 were determined to be polymorphic with PIC values ranging from 0.25 to 0.77. Genetic diversity analysis was performed with the 20 most informative EST-SSR markers showing a distinct separation of the different groups of macaúba palm. Additionally, these 145 markers were transferred in six other palm species resulting in transferability rates of 99% (144) in Acrocomia intumescens, 98% (143) in Acrocomia totai, 80.7% (117 EST-EST) in African oil palm (Elaeis guineensis) and peach palm (Bactris gasipaes) samples, 70% (102) in the juçara palm (Euterpe edulis) and 71.7% (104) in the hat palm (Sabal causiarum). Analysis of genetic distance showed a high separation in accordance with geographic location, establishing distinct groups by genera.ConclusionsThe EST markers identified in our study are a valuable resource and provide a genomic tool for genetic mapping and further genetic studies, as well as evaluation of co-location between QTLs and functionally associated markers.Electronic supplementary materialThe online version of this article (10.1186/s12870-018-1509-9) contains supplementary material, which is available to authorized users.
BackgroundHigh-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted.ResultsWe describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web.ConclusionsWe have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.