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Zerlotini, A.

Publications and source records attributed to Zerlotini, A..

4 recordsLinked to original sources

Plant Co-expression Annotation Resource: a webserver for identifying targets for genetically modified crop breeding pipelines

BackgroundThe development of genetically modified crops (GM) includes the discovery of candidate genes through bioinformatics analysis using genomics data, gene expression, and others. Proteins of unknown function (PUFs) are interesting targets for GM crops breeding pipelines for the novelty associated to such targets and also to avoid copyright protections. One method of inferring the putative function of PUFs is by relating them to factors of interest such as abiotic stresses using orthology and co-expression networks, in a guilt-by-association manner. ResultsIn this regard, we have downloaded, analyzed, and processed genomics data of 53 angiosperms, totaling 1,862,010 genes and 2,332,974 RNA. Diamond and InterproScan were used to discover 72,266 PUFs for all organisms. RNA-seq datasets related to abiotic stresses were downloaded from NCBI/GEO. The RNA-seq data was used as input to the LSTrAP software to construct co-expression networks. LSTrAP also created clusters of transcripts with correlated expression, whose members are more probably related to the molecular mechanisms associated to abiotic stresses in the plants. Orthologous groups were created (OrhtoMCL) using all 2,332,974 proteins in order to associate PUFs to abiotic stress related clusters of co-expression and therefore infer their function in a guilt-by-association manner. ConclusionA freely available web resource named "Plant Co-expression Annotation Resource" (https://www.machado.cnptia.embrapa.br/plantannot), Plantannot, was created to provide indexed queries to search for PUF putatively associated to abiotic stresses. The web interface also allows browsing, querying and retrieving of public genomics data from 53 plants. We hope Plantannot to be useful for researchers trying to obtain novel GM crops resistant to climate change hazards.

bioinformatics↗

Machado: open source genomics data integration framework

BackgroundGenome projects and multiomics experiments generate huge volumes of data that must be stored, mined and transformed into useful knowledge. All this information is supposed to be accessible and, if possible, browsable afterwards. Computational biologists have been dealing with this scenario for over a decade and have been implementing software libraries, toolkits, platforms, and databases to succeed in this matter. The GMODs (Generic Model Organism Database project) biological relational database schema, known as Chado, is one of the few successful open source initiatives, it is widely adopted and many softwares are able to connect to it. ResultsWe have been developing an open source software named Machado (https://github.com/lmb-embrapa/machado), a genomics data integration framework implemented in Python, to enable research groups to both store and browse, query, and visualize genomics data. The framework relies on the Chado database schema and, therefore, should be very intuitive for current developers to adopt it or have it running on the top of already existing databases. It has several data loading tools for genomics and transcriptomics data and also for annotation results from tools such as BLAST, InterproScan, OrthoMCL and LSTrAP. There is an API to connect to JBrowse and a web browsing visualisation tool is implemented using Django Views and Templates. The Haystack library integrated with the ElasticSearch engine was used to implement a google-like search i.e. single auto-complete search box that provides fast results and incremental filters. ConclusionMachado aims to be a modern object-relational framework that uses the latests Python libraries to produce an effective open source resource for genomics research.

bioinformatics↗

Genetic regulators of mineral amount in Nelore cattle muscle predicted by a new co-expression and regulatory impact factor approach

Mineral amount in bovine muscle affect meat quality, growth, health and reproductive traits in beef cattle. To better understand the genetic basis of this phenotype, we implemented new applications of use for two complementary algorithms: the partial correlation and information theory (PCIT) and the regulatory impact factor (RIF), by including GEBVs as part of the input. We used PCIT to determine putative regulatory relationships based on significant associations between gene expression and mineral amount. Then, RIF was used to determine the regulatory impact of genes and miRNA expression over mineral amount. We also investigated over-represented pathways, as well as evidences from previous studies carried in the same population, to determine regulatory genes for mineral amount e.g. NOX1, whose expression was positively correlated to Zn and was described as regulated by this mineral in humans. With this methodology, we were able to identify genes, miRNAs and pathways not yet described as important for mineral amount. The results support the hypothesis that extracellular matrix interactions are the core regulator of mineral amount in muscle cells. Putative regulators described here add information to this hypothesis, expanding the molecular relationships between gene expression and minerals.

genomics↗

A comprehensive manually-curated Compendium of Bovine Transcription Factors

Transcription factors (TFs) are pivotal regulatory proteins that control gene expression in a context-dependent and tissue-specific manner. In contrast to human, where comprehensive curated TF collections exist, bovine TFs are only rudimentary recorded and characterized. In this article, we present a manually-curated compendium of 865 sequence-specific DNA-binding bovines TFs, which we analyzed for domain family distribution, evolutionary conservation, and tissue-specific expression. In addition, we provide a list of putative transcription cofactors derived from known interactions with the identified TFs. Since there is a general lack of knowledge concerning the regulation of gene expression in cattle, the curated list of TF should provide a basis for an improved comprehension of regulatory mechanisms that are specific to the species.

genomics↗