The Third International Genomic Medicine Conference (3rd IGMC) was organised by the Centre of Excellence in Genomic Medicine Research (CEGMR) at the King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia (KSA). This conference is a continuation of a series of meetings, which began with the first International Genomic Medicine Conference (1st IGMC, 2011) followed by the second International Genomic Medicine Conference (2nd IGMC, 2013). The 3rd IGMC meeting presented as a timely opportunity to bring scientists from across the world to gather, discuss, and exchange recent advances in the field of genomics and genetics in general as well as practical information on using these new technologies in different basic and clinical applications. The meeting undoubtedly inspired young male and female Saudi researchers, who attended the conference in large numbers, as evidenced by the oversubscribed oral and poster presentations. The conference also witnessed the launch of the first content for npj Genomic Medicine, a high quality new journal was established in partnership by CEGMR with Springer Nature and published as part of the Nature Partner Journal series. Here, we present a brief summary report of the 2-day meeting including highlights from the oral presentations, poster presentations, workshops, poster prize-winners and comments from the distinguished scientists.

BackgroundThe identification of charge clusters (runs of charged residues) in proteins and their mapping within the protein structure sequence is an important step toward a comprehensive analysis of how these particular motifs mediate, via electrostatic interactions, various molecular processes such as protein sorting, translocation, docking, orientation and binding to DNA and to other proteins. Few algorithms that specifically identify these charge clusters have been designed and described in the literature. In this study, 197 distinctive human viral proteomes were screened for the occurrence of charge clusters (CC) using a new computational approach.ResultsThree hundred and seventy three CC have been identified within the 2549 viral protein sequences screened. The number of protein sequences that are CC-free is 2176 (85.3 %) while 150 and 180 proteins contained positive charge (PCC) and negative charge clusters (NCC), respectively. The NCCs (211 detected) were more prevalent than PCC (162). PCC-containing proteins are significantly longer than those having NCCs (p = 2.10-16). The most prevalent virus families having PCC and NCC were Herpesviridae followed by Papillomaviridae. However, the single-strand RNA group has in average three times more NCC than PCC. According to the functional domain classification, a significant difference in distribution was observed between PCC and NCC (p = 2. 10−8) with the occurrence of NCCs being more frequent in C-terminal region while PCC more often fall within functional domains. Only 29 proteins sequences contained both NCC and PCC. Moreover, 101 NCC were conserved in 84 proteins while only 62 PCC were conserved in 60 protein sequences. To understand the mechanism by which the membrane translocation functionalities are embedded in viral proteins, we screened our PCC for sequences corresponding to cell-penetrating peptides (CPPs) using two online databases: CellPPd and CPPpred. We found that all our PCCs, having length varying from 7 to 30 amino-acids were predicted as CPPs. Experimental validation is required to improve our understanding of the role of these PCCs in viral infection process.ConclusionsScreening distinctive cluster charges in viral proteomes suggested a functional role of these protein regions and might provide potential clues to improve the current understanding of viral diseases in order to tailor better preventive and therapeutic approaches.

BackgroundPreterm birth (PTB), birth at <37 weeks of gestation, is a significant global public health problem. World-wide, about 15 million babies are born preterm each year resulting in more than a million deaths of children. Preterm neonates are more prone to problems and need intensive care hospitalization. Health issues may persist through early adulthood and even be carried on to the next generation. Majority (70 %) of PTBs are spontaneous with about a half without any apparent cause and the other half associated with a number of risk factors. Genetic factors are one of the significant risks for PTB. The focus of this review is on single nucleotide gene polymorphisms (SNPs) that are reported to be associated with PTB.ResultsA comprehensive evaluation of studies on SNPs known to confer potential risk of PTB was done by performing a targeted PubMed search for the years 2007–2015 and systematically reviewing all relevant studies. Evaluation of 92 studies identified 119 candidate genes with SNPs that had potential association with PTB. The genes were associated with functions of a wide spectrum of tissue and cell types such as endocrine, tissue remodeling, vascular, metabolic, and immune and inflammatory systems.ConclusionsA number of potential functional candidate gene variants have been reported that predispose women for PTB. Understanding the complex genomic landscape of PTB needs high-throughput genome sequencing methods such as whole-exome sequencing and whole-genome sequencing approaches that will significantly enhance the understanding of PTB. Identification of high risk women, avoidance of possible risk factors, and provision of personalized health care are important to manage PTB.