Dataset Information

Non-coding RNA gene families in the genomes of anopheline mosquitoes.

ABSTRACT: Only a small fraction of the mosquito species of the genus Anopheles are able to transmit malaria, one of the biggest killer diseases of poverty, which is mostly prevalent in the tropics. This diversity has genetic, yet unknown, causes. In a further attempt to contribute to the elucidation of these variances, the international "Anopheles Genomes Cluster Consortium" project (a.k.a. "16 Anopheles genomes project") was established, aiming at a comprehensive genomic analysis of several anopheline species, most of which are malaria vectors. In the frame of the international consortium carrying out this project our team studied the genes encoding families of non-coding RNAs (ncRNAs), concentrating on four classes: microRNA (miRNA), ribosomal RNA (rRNA), small nuclear RNA (snRNA), and in particular small nucleolar RNA (snoRNA) and, finally, transfer RNA (tRNA).Our analysis was carried out using, exclusively, computational approaches, and evaluating both the primary NGS reads as well as the respective genome assemblies produced by the consortium and stored in VectorBase; moreover, the results of RNAseq surveys in cases in which these were available and meaningful were also accessed in order to obtain supplementary data, as were "pre-genomic era" sequence data stored in nucleic acid databases. The investigation included the identification and analysis, in most species studied, of ncRNA genes belonging to several families, as well as the analysis of the evolutionary relations of some of those genes in cross-comparisons to other members of the genus Anopheles.Our study led to the identification of members of these gene families in the majority of twenty different anopheline taxa. A set of tools for the study of the evolution and molecular biology of important disease vectors has, thus, been obtained.

SUBMITTER: Dritsou V

PROVIDER: S-EPMC4300560 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Non-coding RNA gene families in the genomes of anopheline mosquitoes.

Dritsou Vicky V Deligianni Elena E Dialynas Emmanuel E Allen James J Poulakakis Nikos N Louis Christos C Lawson Dan D Topalis Pantelis P

BMC genomics 20141128

<h4>Background</h4>Only a small fraction of the mosquito species of the genus Anopheles are able to transmit malaria, one of the biggest killer diseases of poverty, which is mostly prevalent in the tropics. This diversity has genetic, yet unknown, causes. In a further attempt to contribute to the elucidation of these variances, the international "Anopheles Genomes Cluster Consortium" project (a.k.a. "16 Anopheles genomes project") was established, aiming at a comprehensive genomic analysis of se ...[more]

PMID: 25432596

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Project description:MotivationSearching genomes for non-coding RNAs (ncRNAs) by their secondary structure has become an important goal for bioinformatics. For pseudoknot-free structures, ncRNA search can be effective based on the covariance model and CYK-type dynamic programming. However, the computational difficulty in aligning an RNA sequence to a pseudoknot has prohibited fast and accurate search of arbitrary RNA structures. Our previous work introduced a graph model for RNA pseudoknots and proposed to solve the structure-sequence alignment by graph optimization. Given k candidate regions in the target sequence for each of the n stems in the structure, we could compute a best alignment in time O(k(t)n) based upon a tree width t decomposition of the structure graph. However, to implement this method to programs that can routinely perform fast yet accurate RNA pseudoknot searches, we need novel heuristics to ensure that, without degrading the accuracy, only a small number of stem candidates need to be examined and a tree decomposition of a small tree width can always be found for the structure graph.ResultsThe current work builds on the previous one with newly developed preprocessing algorithms to reduce the values for parameters k and t and to implement the search method into a practical program, called RNATOPS, for RNA pseudoknot search. In particular, we introduce techniques, based on probabilistic profiling and distance penalty functions, which can identify for every stem just a small number k (e.g. k <or= 10) of plausible regions in the target sequence to which the stem needs to align. We also devised a specialized tree decomposition algorithm that can yield tree decomposition of small tree width t (e.g. t <or= 4) for almost all RNA structure graphs. Our experiments show that with RNATOPS it is possible to routinely search prokaryotic and eukaryotic genomes for specific RNA structures of medium to large sizes, including pseudoknots, with high sensitivity and high specificity, and in a reasonable amount of time.

Project description:Residual vector populations that do not come in contact with the most frequently utilized indoor-directed interventions present major challenges to global malaria eradication. Many of these residual populations are mosquito species about which little is known. As part of a study to assess the threat of outdoor exposure to malaria mosquitoes within the Southern and Central Africa International Centers of Excellence for Malaria Research, foraging female anophelines were collected outside households in Nchelenge District, northern Zambia. These anophelines proved to be more diverse than had previously been reported in the area. In order to further characterize the anopheline species, sequencing and phylogenetic approaches were utilized. Anopheline mosquitoes were collected from outdoor light traps, morphologically identified, and sent to Johns Hopkins Bloomberg School of Public Health for sequencing. Sanger sequencing from 115 field-derived samples yielded mitochondrial COI sequences, which were aligned with a homologous 488 bp gene segment from known anophelines (n = 140) retrieved from NCBI. Nuclear ITS2 sequences (n = 57) for at least one individual from each unique COI clade were generated and compared against NCBI's nucleotide BLAST database to provide additional evidence for taxonomical identity and structure. Molecular and morphological data were combined for assignment of species or higher taxonomy. Twelve phylogenetic groups were characterized from the COI and ITS2 sequence data, including the primary vector species Anopheles funestus s.s. and An. gambiae s.s. An unexpectedly large proportion of the field collections were identified as An. coustani and An. sp. 6. Six phylogenetic groups remain unidentified to species-level. Outdoor collections of anopheline mosquitoes in areas frequented by people in Nchelenge, northern Zambia, proved to be extremely diverse. Morphological misidentification and underrepresentation of some anopheline species in sequence databases confound efforts to confirm identity of potential malaria vector species. The large number of unidentified anophelines could compromise the malaria vector surveillance and malaria control efforts not only in northern Zambia but other places where surveillance and control are focused on indoor-foraging and resting anophelines. Therefore, it is critical to continue development of methodologies that allow better identification of these populations and revisiting and cleaning current genomic databases.

Dataset Information

Non-coding RNA gene families in the genomes of anopheline mosquitoes.

Publications

Non-coding RNA gene families in the genomes of anopheline mosquitoes.

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