180 Integrating structural and systems biology: structure-based prediction of protein–protein interactions on a genome-wide scale

Selection by means of genetic markers is a promising approach to the eradication of infectious diseases in farm animals, especially in the absence of eﬀective methods of treatment and prevention. Bovine leukemia virus (BLV) is spread throughout the world and represents one of the biggest problems for the livestock production and food security in Russia. However, recent genome-wide association studies have shown that sensitivity/resistance to BLV is polygenic. The aim of this study was to create a catalog of cattle genes and genes of other mammalian species involved in the pathogenesis of BLV-induced infection and to perform gene prioritization using bioinformatics methods. Based on manually collected information from a range of open sources, a total of 446 genes were included in the catalog of cattle genes and genes of other mammals involved in the pathogenesis of BLV-induced infection. The following criteria were used to prioritize 446 genes from the catalog: (1) the gene is associated with leukemia according to a genome-wide association study; (2) the gene is associated with leukemia according to a case-control study; (3) the role of the gene in leukemia development has been studied using knockout mice; (4) protein-protein interactions exist between the gene-encoded protein and either viral particles or individual viral proteins; (5) the gene is annotated with Gene Ontology terms that are overrepresented for a given list of genes; (6) the gene participates in biological pathways from the KEGG or REACTOME databases, which are over-represented for a given list of genes; (7) the protein encoded by the gene has a high number of protein-protein interactions with proteins encoded by other genes from the catalog. Based on each criterion, a rank was assigned to each gene. Then the ranks were summarized and an overall rank was determined. Prioritization of 446 candidate genes allowed us to identify 5 genes of interest (TNF,LTB,BOLA-DQA1,BOLA-DRB3,ATF2), which can aﬀect the sensitivity/resistance of cattle to leukemia.

Download Full-text

A phylogenomic analysis of the role and timing of molecular adaptation in the aquatic transition of cetartiodactyl mammals

Royal Society Open Science ◽

10.1098/rsos.150156 ◽

2015 ◽

Vol 2 (9) ◽

pp. 150156 ◽

Cited By ~ 19

Author(s):

Georgia Tsagkogeorga ◽

Michael R. McGowen ◽

Kalina T. J. Davies ◽

Simon Jarman ◽

Andrea Polanowski ◽

...

Keyword(s):

Protein Interactions ◽

Dna Sequences ◽

Brain Function ◽

Molecular Adaptation ◽

Phylogenomic Analysis ◽

Protein Protein Interactions ◽

Orthologous Genes ◽

Genome Wide ◽

A Genome ◽

The Common

Recent studies have reported multiple cases of molecular adaptation in cetaceans related to their aquatic abilities. However, none of these has included the hippopotamus, precluding an understanding of whether molecular adaptations in cetaceans occurred before or after they split from their semi-aquatic sister taxa. Here, we obtained new transcriptomes from the hippopotamus and humpback whale, and analysed these together with available data from eight other cetaceans. We identified more than 11 000 orthologous genes and compiled a genome-wide dataset of 6845 coding DNA sequences among 23 mammals, to our knowledge the largest phylogenomic dataset to date for cetaceans. We found positive selection in nine genes on the branch leading to the common ancestor of hippopotamus and whales, and 461 genes in cetaceans compared to 64 in hippopotamus. Functional annotation revealed adaptations in diverse processes, including lipid metabolism, hypoxia, muscle and brain function. By combining these findings with data on protein–protein interactions, we found evidence suggesting clustering among gene products relating to nervous and muscular systems in cetaceans. We found little support for shared ancestral adaptations in the two taxa; most molecular adaptations in extant cetaceans occurred after their split with hippopotamids.

Download Full-text

Molecular interplay between organisms by phylogenetic profiling

10.7287/peerj.preprints.27373 ◽

2018 ◽

Author(s):

Gabriella Sferra ◽

Marta Ponzi ◽

Elisabetta Pizzi

Keyword(s):

Protein Interactions ◽

Malaria Parasite ◽

Protein Protein Interactions ◽

Human Malaria Parasite ◽

Distance Correlation ◽

Profile Similarity ◽

Genome Wide ◽

A Genome ◽

Phylogenetic Profiling ◽

Host Parasite

In recent years, several computational methods have been developed to predict protein-protein interactions (PPIs) at a genome-wide level. Between them phylogenetic profiling is routinely used to infer PPIs occurring within an organism. Recent improvements of the methods rely on the usage of large genomic datasets and on the distance correlation, a correlation-based measure, as novel measure of profile similarity. Here we adapted the robust improved phylogenetic profiling strategy to predict PPIs occurring between organisms. Specifically, we inferred PPIs occurring in the host-parasite system of Plasmodium falciparum, the deadliest human malaria parasite, and the human erythrocyte, in which the parasite performs an asexual reproduction and that is responsible of the greatest part of the parasitosis symptoms. By applying the method we could predict host-host, erythrocyte-erythrocyte and host-erythrocyte PPIs. As proof of principle, we demonstrated that the phylogenetic profiling can be extended to predict interactions that not necessarily are performed by proteins belonging to the same organism.

Download Full-text

Molecular interplay between organisms by phylogenetic profiling

10.7287/peerj.preprints.27373v1 ◽

2018 ◽

Author(s):

Gabriella Sferra ◽

Marta Ponzi ◽

Elisabetta Pizzi

Keyword(s):

Protein Interactions ◽

Malaria Parasite ◽

Protein Protein Interactions ◽

Human Malaria Parasite ◽

Distance Correlation ◽

Profile Similarity ◽

Genome Wide ◽

A Genome ◽

Phylogenetic Profiling ◽

Host Parasite

In recent years, several computational methods have been developed to predict protein-protein interactions (PPIs) at a genome-wide level. Between them phylogenetic profiling is routinely used to infer PPIs occurring within an organism. Recent improvements of the methods rely on the usage of large genomic datasets and on the distance correlation, a correlation-based measure, as novel measure of profile similarity. Here we adapted the robust improved phylogenetic profiling strategy to predict PPIs occurring between organisms. Specifically, we inferred PPIs occurring in the host-parasite system of Plasmodium falciparum, the deadliest human malaria parasite, and the human erythrocyte, in which the parasite performs an asexual reproduction and that is responsible of the greatest part of the parasitosis symptoms. By applying the method we could predict host-host, erythrocyte-erythrocyte and host-erythrocyte PPIs. As proof of principle, we demonstrated that the phylogenetic profiling can be extended to predict interactions that not necessarily are performed by proteins belonging to the same organism.

Download Full-text