RESUMO
Tsetse flies use antennal expressed genes to navigate their environment. While most canonical genes associated with chemoreception are annotated, potential gaps with important antennal genes are uncharacterized in Glossina morsitans morsitans. We generated antennae-specific transcriptomes from adult male G. m. morsitans flies fed/unfed on bloodmeal and/or exposed to an attractant (ε-nonalactone), a repellant (δ-nonalactone) or paraffin diluent. Using bioinformatics approach, we mapped raw reads onto G. m. morsitans gene-set from VectorBase and collected un-mapped reads (constituting the gaps in annotation). We de novo assembled these reads (un-mapped) into transcript and identified corresponding genes of the transcripts in G. m. morsitans gene-set and protein homologs in UniProt protein database to further annotate the gaps. We predicted potential protein-coding gene regions associated with these transcripts in G. m. morsitans genome, annotated/curated these genes and identified their putative annotated orthologs/homologs in Drosophila melanogaster, Musca domestica or Anopheles gambiae genomes. We finally evaluated differential expression of the novel genes in relation to odor exposures relative to no-odor control (unfed flies). About 45.21% of the sequenced reads had no corresponding transcripts within G. m. morsitans gene-set, corresponding to the gap in existing annotation of the tsetse fly genome. The total reads assembled into 72,428 unique transcripts, most (74.43%) of which had no corresponding genes in the UniProt database. We annotated/curated 592 genes from these transcripts, among which 202 were novel while 390 were improvements of existing genes in the G. m. morsitans genome. Among the novel genes, 94 had orthologs in D. melanogaster, M. domestica or An. gambiae while 88 had homologs in UniProt. These orthologs were putatively associated with oxidative regulation, protein synthesis, transcriptional and/or translational regulation, detoxification and metal ion binding, thus providing insight into their specific roles in antennal physiological processes in male G. m. morsitans. A novel gene (GMOY014237.R1396) was differentially expressed in response to the attractant. We thus established significant gaps in G. m. morsitans genome annotation and identified novel male antennae-expressed genes in the genome, among which > 53% (108) are potentially G. m. morsitans specific.
Assuntos
Moscas Tsé-Tsé , Animais , Sequência de Bases , Biologia Computacional , Drosophila melanogaster/genética , Masculino , Transcriptoma , Moscas Tsé-Tsé/fisiologiaRESUMO
BACKGROUND: High-throughput sequencing generates large volumes of biological data that must be interpreted to make meaningful inference on the biological function. Problems arise due to the large number of characteristics p (dimensions) that describe each record [n] in the database. Feature selection using a subset of variables extracted from the large datasets is one of the approaches towards solving this problem. METHODOLOGY: In this study we analyzed the transcriptome of Glossina morsitans morsitans (Tsetsefly) antennae after exposure to either a repellant (δ-nonalactone) or an attractant (ε-nonalactone). We identified 308 genes that were upregulated or downregulated due to exposure to a repellant (δ-nonalactone) or an attractant (ε-nonalactone) respectively. Weighted gene coexpression network analysis was used to cluster the genes into 12 modules and filter unconnected genes. Discretized and association rule mining was used to find association between genes thereby predicting the putative function of unannotated genes. RESULTS AND DISCUSSION: Among the significantly expressed chemosensory genes (FDR < 0.05) in response to Æ-nonalactone were gustatory receptors (GrIA and Gr28b), ionotrophic receptors (Ir41a and Ir75a), odorant binding proteins (Obp99b, Obp99d, Obp59a and Obp28a) and the odorant receptor (Or67d). Several non-chemosensory genes with no assigned function in the NCBI database were co-expressed with the chemosensory genes. Exposure to a repellent (δ-nonalactone) did not show any significant change between the treatment and control samples. We generated a coexpression network with 276 edges and 130 nodes. Genes CAH3, Ahcy, Ir64a, Or67c, Ir8a and Or67a had node degree values above 11 and therefore could be regarded as the top hub genes in the network. Association rule mining showed a relation between various genes based on their appearance in the same itemsets as consequent and antecedent.