Significance: Rhodnius prolixus is a major vector of Chagas disease, an illness caused by Trypanosoma cruzi which affects approximately 7 million people worldwide. This report describes the first genome sequence of a nondipteran insect vector of an important human parasitic disease. This insect has a gene repertoire substantially distinct from dipteran disease vectors, including immune signaling pathways that display major departures from the canonical network. Large gene expansions related to chemoreception, feeding, and digestion have facilitated triatomine adaptation to a blood-feeding lifestyle. This study provides information about the physiology and evolution of an important disease vector that will boost understanding of transmission of a life-threatening parasite and may lead to the development of innovative control methods.

SNPs (Single Nucleotide Polymorphisms) are genetic markers whose precise identification is a prerequisite for association studies. Methods to identify them are currently well developed for model species, but rely on the availability of a (good) reference genome, and therefore cannot be applied to non-model species. They are also mostly tailored for whole genome (re-)sequencing experiments, whereas in many cases, transcriptome sequencing can be used as a cheaper alternative which already enables to identify SNPs located in transcribed regions. In this paper, we propose a method that identifies, quantifies and annotates SNPs without any reference genome, using RNA-seq data only. Individuals can be pooled prior to sequencing, if not enough material is available from one individual. Using pooled human RNA-seq data, we clarify the precision and recall of our method and discuss them with respect to other methods which use a reference genome or an assembled transcriptome. We then validate experimentally the predictions of our method using RNA-seq data from two non-model species. The method can be used for any species to annotate SNPs and predict their impact on the protein sequence. We further enable to test for the association of the identified SNPs with a phenotype of interest.

Crosses between close species can lead to genomic disorders, often considered to be the cause of hybrid incompatibility, one of the initial steps in the speciation process. How these incompatibilities are established and what are their causes remain unclear. To understand the initiation of hybrid incompatibility, we performed reciprocal crosses between two species of Drosophila (D. mojavensisandD. arizonae) that diverged less than 1 Mya. We performed a genome-wide transcriptomic analysis on ovaries from parental lines and on hybrids from reciprocal crosses. Using an innovative procedure of co-assembling transcriptomes, we show that parental lines differ in the expression of their genes and transposable elements. Reciprocal hybrids presented specific gene categories and few transposable element families misexpressed relative to the parental lines. Because TEs are mainly silenced by piwi-interacting RNAs (piRNAs), we hypothesize that in hybrids the deregulation of specific TE families is due to the absence of such small RNAs. Small RNA sequencing confirmed our hypothesis and we therefore propose that TEs can indeed be major players of genome differentiation and be implicated in the first steps of genomic incompatibilities through small RNA regulation.

Transposable elements (TEs) are repetitive nucleotide sequences that make up a large portion of eukaryotic genomes. They can move and duplicate within a genome, increasing genome size and contributing to genetic diversity within and across species. Accurate identification and classification of TEs present in a genome is an important step towards understanding their effects on genes and their role in genome evolution. We introduce TE-Learner, a framework based on machine learning that automatically identifies TEs in a given genome and assigns a classification to them. We present an implementation of our framework towards LTR retrotransposons, a particular type of TEs characterized by having long terminal repeats (LTRs) at their boundaries. We evaluate the predictive performance of our framework on the well-annotated genomes of Drosophila melanogaster and Arabidopsis thaliana and we compare our results for three LTR retrotransposon superfamilies with the results of three widely used methods for TE identification or classification: RepeatMasker, Censor and LtrDigest. In contrast to these methods, TE-Learner is the first to incorporate machine learning techniques, outperforming these methods in terms of predictive performance, while able to learn models and make predictions efficiently. Moreover, we show that our method was able to identify TEs that none of the above method could find, and we investigated TE-Learner’s predictions which did not correspond to an official annotation. It turns out that many of these predictions are in fact strongly homologous to a known TE. Over the years, with the increase of the acquisition of biological data, the extraction of knowledge from this data is getting more important. To understand how biology works is very important to increase the quality of the products and services which use biological data. This directly influences companies and governments, which need to remain in the knowledge frontier of an increasing competitive economy. Transposable Elements (TEs) are an example of very important biological data, and to understand their role in the genomes of organisms is very important for the development of products based on biological data. As an example, we can cite the production biofuels such as the sugar-cane-based ones. Many studies have revealed the presence of active TEs in this plant, which has gained economic importance in many countries. To understand how TEs influence the plant should help researchers to develop more resistant varieties of sugar-cane, increasing the production. Thus, the development of computational methods able to help biologists in the correct identification and classification of TEs is very important from both theoretical and practical perspectives.

Zaprionus indianus is a dipteran (Drosophilidae) with a wide distribution throughout the tropics and temperate Palearctic and Nearctic regions. There have been proposals to reclassify the genus Zaprionus as a subgenus or group of the genus Drosophila because various molecular markers have indicated a close relationship between Zaprionus species and the immigrans-Hirtodrosophila radiation within Drosophila. These markers, together with alloenzymes and quantitative traits, have been used to describe the probable scenario for the expansion of Zaprionus indianus from its center of dispersal (Africa) to regions of Asia (ancient dispersal) and the Americas (recent dispersal). The introduction of Z. indianus into Brazil was first reported in 1999 and the current consensus is that the introduced flies came from high-latitude African populations through the importation of fruit. Once in Brazil, Z. indianus spread rapidly throughout the Southeast and then to the rest of the country, in association with highway-based fruit commerce. These and other aspects of the evolutionary biology of Z. indianus are addressed in this review, including a description of a probable route for this species' dispersal during its recent expansion.