Molecular Phylogenetic Analysis of the AIG Family in Vertebrates

Genome of tropical bed bug Cimex hemipterus (Cimicidae, Hemiptera) reveals tetraspanin expanded in bed bug ancestor

Cimex species are ectoparasites that exclusively feed on warm-blooded animals such as birds and mammals. Three cimicid species are known to be persistent pests for humans, including the tropical bed bug Cimex hemipterus, common bed bug Cimex lectularius, and Eastern bat bug Leptocimex boueti. To date, genomic information is restricted to the common bed bug C. lectularius, which limits understanding their biology and to provide controls of bed bug infestations. Here, a chromosomal-level genome assembly of C. hemipterus (495 Mb [megabase pairs]) contained on 16 pseudochromosomes (scaffold N50 = 34 Mb), together with 9 messenger RNA and small RNA transcriptomes were obtained. In comparison between hemipteran genomes, we found that the tetraspanin superfamily was expanded in the Cimex ancestor. This study provides the first genome assembly for the tropical bed bug C. hemipterus, and offers an unprecedented opportunity to address questions relating to bed bug infestations, as well as genomic evolution to hemipterans more widely.

Developing a bioinformatics pipeline for comparative protein classification analysis

BACKGROUND

Protein classification is a task of paramount importance in various fields of biology. Despite the great momentum of modern implementation of protein classification, machine learning techniques such as Random Forest and Neural Network could not always be used for several reasons: data collection, unbalanced classification or labelling of the data.As an alternative, I propose the use of a bioinformatics pipeline to search for and classify information from protein databases. Hence, to evaluate the efficiency and accuracy of the pipeline, I focused on the carotenoid biosynthetic genes and developed a filtering approach to retrieve orthologs clusters in two well-studied plants that belong to the Brassicaceae family: Arabidopsis thaliana and Brassica rapa Pekinensis group. The result obtained has been compared with previous studies on carotenoid biosynthetic genes in B. rapa where phylogenetic analysis was conducted.

RESULTS

The developed bioinformatics pipeline relies on commercial software and multiple databeses including the use of phylogeny, Gene Ontology terms (GOs) and Protein Families (Pfams) at a protein level. Furthermore, the phylogeny is coupled with "population analysis" to evaluate the potential orthologs. All the steps taken together give a final table of potential orthologs. The phylogenetic tree gives a result of 43 putative orthologs conserved in B. rapa Pekinensis group. Different A. thaliana proteins have more than one syntenic ortholog as also shown in a previous finding (Li et al., BMC Genomics 16(1):1-11, 2015).

CONCLUSIONS

This study demonstrates that, when the biological features of proteins of interest are not specific, I can rely on a computational approach in filtering steps for classification purposes. The comparison of the results obtained here for the carotenoid biosynthetic genes with previous research confirmed the accuracy of the developed pipeline which can therefore be applied for filtering different types of datasets.