Visual Analysis Tool in Comparative Genomics

Detecting regions with mutations associated with different pathologies is an important step in selecting relevant genes, proteins or diseases. The corresponding information of the mutations and genes is distributed in different public sources and databases, so it is necessary to use systems that can contrast different sources and select conspicuous information. This work presents a visual analysis tool that automatically selects relevant segments and the associated genes or proteins that could determine different pathologies

Sex-biased mouse liver lincRNAs: validation and impact of mouse knockout models that perturb hepatic growth signaling

Sexual dimorphism has a broad impact on human health and disease, including autoimmune diseases, cardiovascular diseases, and liver diseases, specifically hepatocellular carcinoma. Pituitary growth hormone (GH) secretion has a major impact on sex differences in the liver. Previous studies show that signal transducer and activator transcription factor 5b (STAT5b) impacts male-biased gene expression. Somatostatin (SST) inhibits the release of GH, and this in turn impacts STAT5b activity and GH regulation feedback. Long intergenic noncoding RNAs (lincRNAs), which do not encode proteins, have various roles in diverse biological processes including cell differentiation, chromatin remodeling, and gene regulation. In the present study, we discovered lincRNAs in mouse liver using RNA-seq datasets, and identified male and female-biased lincRNAs. Moreover, we validated the sex-specificity of lincRNAs by performing real time PCR (qPCR) and analyzing UCSC genome browser screen shots by comparing male and female expression patterns. We validated the sex-specificities of 22 lincRNAs. Moreover, we investigated whether pituitary GH secretion impacts the regulation of these sex-biased lincRNAs in the same manner as seen in sex-biased protein coding RefSeq genes. qPCR experiments investigated the impact of GH secretion by using SST and STAT5b knockout mouse models, and hypophysectomized, and intermittent (pulsatile) GH-treated mice. Our results show that pituitary GH secretion impacts the regulation of sex-biased lincRNAs. The last part of this thesis investigates the molecular and functional role of sexbiased lincRNAs by using The Database for Annotation, Visualization, and Integrated Discovery (DAVID)

PLAZA 4.0 : an integrative resource for functional, evolutionary and comparative plant genomics

PLAZA (https://bioinformatics.psb.ugent.be/plaza) is a plant-oriented online resource for comparative, evolutionary and functional genomics. The PLAZA platform consists of multiple independent instances focusing on different plant clades, while also providing access to a consistent set of reference species. Each PLAZA instance contains structural and functional gene annotations, gene family data and phylogenetic trees and detailed gene colinearity information. A user-friendly web interface makes the necessary tools and visualizations accessible, specific for each data type. Here we present PLAZA 4.0, the latest iteration of the PLAZA framework. This version consists of two new instances (Dicots 4.0 and Monocots 4.0) providing a large increase in newly available species, and offers access to updated and newly implemented tools and visualizations, helping users with the ever-increasing demands for complex and in-depth analyzes. The total number of species across both instances nearly doubles from 37 species in PLAZA 3.0 to 71 species in PLAZA 4.0, with a much broader coverage of crop species (e.g. wheat, palm oil) and species of evolutionary interest (e.g. spruce, Marchantia). The new PLAZA instances can also be accessed by a programming interface through a RESTful web service, thus allowing bioinformaticians to optimally leverage the power of the PLAZA platform

VisGenome: visualization of single and comparative genome representations

VisGenome visualizes single and comparative representations for the rat, the mouse and the human chromosomes at different levels of detail. The tool offers smooth zooming and panning which is more flexible than seen in other browsers. It presents information available in Ensembl for single chromosomes, as well as homologies (orthologue predictions including ortholog one2one, apparent ortholog one2one, ortholog many2many) for any two chromosomes from different species. The application can query supporting data from Ensembl by invoking a link in a browser

The Chlamydomonas genome project: A decade on

The green alga Chlamydomonas reinhardtii is a popular unicellular organism for studying photosynthesis, cilia biogenesis, and micronutrient homeostasis. Ten years since its genome project was initiated an iterative process of improvements to the genome and gene predictions has propelled this organism to the forefront of the omics era. Housed at Phytozome, the plant genomics portal of the Joint Genome Institute (JGI), the most up-to-date genomic data include a genome arranged on chromosomes and high-quality gene models with alternative splice forms supported by an abundance of whole transcriptome sequencing (RNA-Seq) data. We present here the past, present, and future of Chlamydomonas genomics. Specifically, we detail progress on genome assembly and gene model refinement, discuss resources for gene annotations, functional predictions, and locus ID mapping between versions and, importantly, outline a standardized framework for naming genes

Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

The organization and mining of malaria genomic and post-genomic data is highly motivated by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum, but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should therefore be as reliable and versatile as possible. In this context, we examined five aspects of the organization and mining of malaria genomic and post-genomic data: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Progresses toward a grid-enabled chemogenomic knowledge space are discussed.Comment: 43 pages, 4 figures, to appear in Malaria Journa

MorphDB : prioritizing genes for specialized metabolism pathways and gene ontology categories in plants

Recent times have seen an enormous growth of "omics" data, of which high-throughput gene expression data are arguably the most important from a functional perspective. Despite huge improvements in computational techniques for the functional classification of gene sequences, common similarity-based methods often fall short of providing full and reliable functional information. Recently, the combination of comparative genomics with approaches in functional genomics has received considerable interest for gene function analysis, leveraging both gene expression based guilt-by-association methods and annotation efforts in closely related model organisms. Besides the identification of missing genes in pathways, these methods also typically enable the discovery of biological regulators (i.e., transcription factors or signaling genes). A previously built guilt-by-association method is MORPH, which was proven to be an efficient algorithm that performs particularly well in identifying and prioritizing missing genes in plant metabolic pathways. Here, we present MorphDB, a resource where MORPH-based candidate genes for large-scale functional annotations (Gene Ontology, MapMan bins) are integrated across multiple plant species. Besides a gene centric query utility, we present a comparative network approach that enables researchers to efficiently browse MORPH predictions across functional gene sets and species, facilitating efficient gene discovery and candidate gene prioritization. MorphDB is available at http://bioinformatics.psb.ugent.be/webtools/morphdb/morphDB/index/. We also provide a toolkit, named "MORPH bulk" (https://github.com/arzwa/morph-bulk), for running MORPH in bulk mode on novel data sets, enabling researchers to apply MORPH to their own species of interest