Victor McKusick and his short course.

The Short Course in Human and Mammalian Genetics and Genomics (aka the Short Course or the Bar Harbor course ) is one of Victor McKusick\u27s landmark contributions to medical genetics. Conceived in 1959 as a way to increase the contribution of genetic advances to medicine, it has directly affected more than 7000 students and 600 participating faculty from around the world. Now, more than 10 years after his death, it continues to be a vibrant disseminator of genetics, and genomics knowledge for medicine, a catalytic agent for ongoing research and a source of collegiality in our field. What an extraordinary gift

Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs

Background: MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Although such homogeneous networks can predict potential disease-associated miRNAs, they do not consider the roles of the target genes of the miRNAs. Here, we introduce a novel method based on a heterogeneous network that not only considers miRNAs but also the corresponding target genes in the network model. Results: Instead of constructing homogeneous miRNA networks, we built heterogeneous miRNA networks consisting of both miRNAs and their target genes, using databases of known miRNA-target gene interactions. In addition, as recent studies demonstrated reciprocal regulatory relations between miRNAs and their target genes, we considered these heterogeneous miRNA networks to be undirected, assuming mutual miRNA-target interactions. Next, we introduced a novel method (RWRMTN) operating on these mutual heterogeneous miRNA networks to rank candidate disease-related miRNAs using a random walk with restart (RWR) based algorithm. Using both known disease-associated miRNAs and their target genes as seed nodes, the method can identify additional miRNAs involved in the disease phenotype. Experiments indicated that RWRMTN outperformed two existing state-of-the-art methods: RWRMDA, a network-based method that also uses a RWR on homogeneous (rather than heterogeneous) miRNA networks, and RLSMDA, a machine learning-based method. Interestingly, we could relate this performance gain to the emergence of "disease modules" in the heterogeneous miRNA networks used as input for the algorithm. Moreover, we could demonstrate that RWRMTN is stable, performing well when using both experimentally validated and predicted miRNA-target gene interaction data for network construction. Finally, using RWRMTN, we identified 76 novel miRNAs associated with 23 disease phenotypes which were present in a recent database of known disease-miRNA associations. Conclusions: Summarizing, using random walks on mutual miRNA-target networks improves the prediction of novel disease-associated miRNAs because of the existence of "disease modules" in these networks

Étude des anomalies du développement humain# un modèle d’analyse phénotypique

Depuis le début des années 90, le projet génome humain a permis l’émergence de nombreuses techniques globalisantes porteuses du suffixe –omique : génomique, transcriptomique, protéomique, épigénomique, etc.… L’étude globale de l’ensemble des phénotypes humains (« phénome ») est à l’origine de nouvelles technologies constituant la « phénomique ». L’approche phénomique permet de déterminer des liens entre des combinaisons de traits phénomiques. Nous voulons appliquer cette approche à l’étude des malformations humaines en particulier leurs combinaisons, ne formant des syndromes, des associations ou des séquences bien caractérisés que dans un petit nombre de cas. Afin d’évaluer la faisabilité de cette approche, pour une étude pilote nous avons décidé d’établir une base de données pour la description phénotypique des anomalies foetales. Nous avons effectué ces étapes : o Réalisation d’une étude rétrospective d’une série d’autopsies de foetus au CHU Sainte- Justine (Montréal, QC, Canada) entre 2001-2006 o Élaboration de trois thésaurus et d’une ontologie des anomalies développementales humaines o Construction une base de données en langage MySQL Cette base de données multicentrique accessible sur (http://www.malformations.org), nous permet de rechercher très facilement les données phénotypiques des 543 cas observés porteurs d’une anomalie donnée, de leur donner une description statistique et de générer les différents types d’hypothèses. Elle nous a également permis de sélectionner 153 cas de foetus malformés qui font l’objet d’une étude de micropuce d’hybridation génomique comparative (aCGH) à la recherche d’une anomalie génomique.Since the early 90s, the Human Genome Project (HGP) has allowed the development of numerous worldwide techniques which carried the suffix “omic”: genomic, transcriptomic, proteomic, epigenomic, etc…. The global investigation of the sets of human phenotypes (phenome) is called phenomic. With phenomic studies we should be able to determine the links among similar phenotypic groups. We wish to apply this approach to human dysmorphology, particularly malformation combinations, which form characteristic malformation associations, malformation sequences, malformation syndromes or malformation disorders only in a minority of cases. As a graduate student research project, we decided to perform a retrospective study of the sets of pathology reports including 543 fetuses autopsied in the Department of Pathology of CHU Sainte-Justine (Montreal, QC, Canada) between 2001 and 2006. We have established an open Malformation Database (MDB) which can be accessed at http://www.malformations.org. To achieve this, we conducted the following steps: o Realization of a retrospective study of fetopathology reports for fetal malformations. o Development of an ontology along with three thesauruses of human developmental anomalies. o Implementation of these thesauruses and ontology in the MySQL system. This hypothesis-generating database allows us to easily retrieve the fetal cases (phenotypic data) with anomalies, calculate the frequencies of these anomalies, and evaluate the feasibility of the phenomic approach to human dysmorphogenesis. We were able as well to select 153 cases of malformed fetuses which will be the subject of aCGH array study for genomic research of human anomalies

A whole genome analyses of genetic variants in two Kelantan Malay individuals

The sequencing of two members of the Royal Kelantan Malay family genomes will provide insights on the Kelantan Malay whole genome sequences. The two Kelantan Malay genomes were analyzed for the SNP markers associated with thalassemia and Helicobacter pylori infection. Helicobacter pylori infection was reported to be low prevalence in the north-east as compared to the west coast of the Peninsular Malaysia and beta-thalassemia was known to be one of the most common inherited and genetic disorder in Malaysia.By combining SNP information from literatures, GWAS study and NCBI ClinVar, 18 unique SNPs were selected for further analysis. From these 18 SNPs, 10 SNPs came from previous study of Helicobacter pylori infection among Malay patients, 6 SNPs were from NCBI ClinVar and 2 SNPs from GWAS studies. The analysis reveals that both Royal Kelantan Malay genomes shared all the 10 SNPs identified by Maran (Single Nucleotide Polymorphims (SNPs) genotypic profiling of Malay patients with and without Helicobacter pylori infection in Kelantan, 2011) and one SNP from GWAS study. In addition, the analysis also reveals that both Royal Kelantan Malay genomes shared 3 SNP markers; HBG1 (rs1061234), HBB (rs1609812) and BCL11A (rs766432) where all three markers were associated with beta-thalassemia.Our findings suggest that the Royal Kelantan Malays carry the SNPs which are associated with protection to Helicobacter pylori infection. In addition they also carry SNPs which are associated with beta-thalassemia. These findings are in line with the findings by other researchers who conducted studies on thalassemia and Helicobacter pylori infection in the non-royal Malay population.Wan Khairunnisa Wan Juhari, Nur Aida Md Tamrin, Mohd Hanif Ridzuan Mat Daud, Hatin Wan Isa, Nurfazreen Mohd Nasir, Sathiya Maran, Nur Shafawati Abdul Rajab, Khairul Bariah Ahmad Amin Noordin, Nik Norliza Nik Hassan, Rick Tearle, Rozaimi Razali, Amir Feisal Merican and Bin Alwi Zilfali

Κλινικές δοκιμές γενετικών θεραπειών με αντιπληροφοριακό RNA και φορείς DNA

Οι γενετικές ασθένειες απειλούν την ανθρώπινη υγεία και έχουν παρουσιάσει αυξημένη συχνότητα στον γενικό πληθυσμό τα τελευταία χρόνια. Σήμερα, γονιδιακές θεραπείες όπως είναι τα siRNA, shRNA, ολιγονουκλεοτίδια αντιπληροφοριακού RNA, αλλά και φορείς γενετικού υλικού, έχουν δείξει καλές προοπτικές στην εφαρμογή τους στην κλινική πρακτική. Οι τελευταίες εξελίξεις που αφορούν τις χημικές μετατροπές των αντι-πληροφοριακών νουκλεοτιδίων, καθώς και η ανάπτυξη συστημάτων μεταφοράς DNA (φορέων) προκειμένου να αποφευχθεί η διάσπαση των φαρμάκων γονιδιακής θεραπείας στον οργανισμό, είναι ιδιαίτερης σημασίας στην εξέλιξη των γονιδιακών θεραπειών και την εφαρμογή τους με μεγαλύτερη συχνότητα στην κλινική πρακτική. Στην παρούσα μελέτη, γίνεται μια συστηματική ανασκόπηση της βιβλιογραφίας με σκοπό την παρουσίαση των πιο πρόσφατων εξελίξεων σε σχέση με τις κλινικές δοκιμές γενετικών θεραπειών με αντιπληροφοριακό RNA και με φορείς DNA.Genetic diseases threaten human health and have become increasingly common in the general population in recent years. Today, gene therapies such as siRNA, shRNA, antisense RNA oligonucleotides, but also genetic carriers, have shown good prospects for their application in clinical practice.Recent developments regarding the chemical transformations of anti-information nucleotides, as well as the development of DNA transport systems (vectors) in order to prevent the breakdown of gene therapy drugs in the body, are of particular importance in the development of gene therapies and their application with greater frequency in clinical practice.In the present study, a systematic review of the literature is performed in order to present the latest developments in relation to clinical trials of genetic therapies with antisense RNA and DNA vectors

Protein interactions across and between eukaryotic kingdoms: networks, inference strategies, integration of functional data and evolutionary dynamics

Thesis (Ph.D.)--Boston UniversityHow cellular elements coordinate their function is a fundamental question in biology. A crucial step towards understanding cellular systems is the mapping of physical interactions between protein, DNA, RNA and other macromolecules or metabolites. Genome-scale technologies have yielded protein-protein interaction networks for several eukaryotic species and have provided insight into biological processes and evolution, but many of the currently available networks are biased. Towards a true human protein-protein interaction network, we examined literature-based aggregations of lowthroughput experiments, high-throughput experimental networks validated using different strategies, and predicted interaction networks to infer how the underlying interactome may differ from current maps. Using systematically mapped interactome networks, which appear to be the least biased, we explored the functional organization of Arabidopsis thaliana and characterize the asymmetric divergence of duplicated paralogous proteins through their interaction profiles. To further dissect the relationship between interactions and function enforced by evolution, we investigated a first-of-its-kind systematic crossspecies human-yeast hybrid interactome network. Although the cross-species network is topologically similar to conventional intra-species networks, we found signatures of dynamic changes in interaction propensities due to countervailing evolutionary forces. Collectively, these analyses of human, plant and yeast interactome networks bridge separate experiments to characterize bias, function and evolution across eukaryotic kingdoms

Mechanisms of defective insulin secretion in type 2 diabetes

Defective insulin secretion from the pancreatic B-cells is a central feature in type 2 diabetes (T2D). There is a strong hereditary component in type T2D, but the underlying pathophysiology remains largely unknown. This thesis uses a combination of gene network analysis and cell-physiological techniques to explore the genetic and cellular basis for impaired insulin secretion in T2D. We found that genetic variants for type 2 diabetes near TCF7L2 and ADRA2A were associated with reduced glucose-induced insulin secretion. Moreover, susceptibility variants near ADRA2A, KCNJ11, KCNQ1, and TCF7L2 were associated with reduced depolarization-evoked insulin exocytosis. We combined our results to create a novel genetic risk score for B-cell dysfunction that includes aberrant granule docking, decreased Ca2+ sensitivity of exocytosis, and reduced insulin release. Individuals with a high risk score displayed an impaired response to intravenous glucose and deteriorating insulin secretion over time. To obtain a more global view of the pathophysiology of T2D we next analyzed gene expression from microarray data of human pancreatic islets. A group of coexpressed genes (module), enriched for interleukin-1-related genes, was associated with T2D and reduced insulin secretion. One of the module genes that was highly overexpressed in islets from T2D patients is SFRP4, which encodes secreted frizzled-related protein 4. SFRP4 expression correlated with inflammatory markers, and its release from islets was stimulated by interleukin-1B. Elevated systemic SFRP4 caused reduced glucose tolerance through decreased islet expression of Ca2+ channels and suppressed insulin exocytosis. SFRP4 thus provides the first molecular link between islet inflammation and impaired insulin secretion. Moreover, the protein was increased in serum from diabetic patients several years before the diagnosis, suggesting that SFRP4 could be a potential biomarker for islet dysfunction in T2D. We have also identified a gene co-expression module in human pancreatic islets that is enriched for genes with islet-specific open chromatin. In individuals with T2D this module displays an expression pattern that is reminiscent of a B-cell dedifferentiation profile. We have studied key transcription factors that may regulate this module. Taken together, the findings shed new light on the pathophysiology of T2D and show the potential of combining genetics, bioinformatics and cell-physiology to better understand complex polygenic diseases