The HUGO Journal

Multiple lines of evidence suggest regulatory variation to play an important role in phenotypic evolution and disease development, but few regulatory polymorphisms have been characterized genetically and molecularly. Recent technological advances have made it possible to identify bona fide regulatory sequences experimentally on a genome-wide scale and opened the window for the biological interrogation of germ-line polymorphisms within these sequences. In this study, through a forward genetic analysis of bona fide p53 binding sites identified by a genome-wide chromatin immunoprecipitation and sequence analysis, we discovered a SNP (rs1860746) within the motif sequence of a p53 binding site where p53 can function as a regulator of transcription. We found that the minor allele (T) binds p53 poorly and has low transcriptional regulation activity as compared to the major allele (G). Significantly, the homozygosity of the minor allele was found to be associated with an increased risk of ER negative breast cancer (OR = 1.47, P = 0.038) from the analysis of five independent breast cancer samples of European origin consisting of 6,127 breast cancer patients and 5,197 controls. rs1860746 resides in the third intron of the PRKAG2 gene that encodes the γ subunit of the AMPK protein, a major sensor of metabolic stress and a modulator of p53 action. However, this gene does not appear to be regulated by p53 in lymphoblastoid cell lines nor in a cancer cell line. These results suggest that either the rs1860746 locus regulates another gene through distant interactions, or that this locus is in linkage disequilibrium with a second causal mutation. This study shows the feasibility of using genomic scale molecular data to uncover disease associated SNPs, but underscores the complexity of determining the function of regulatory variants in human populations.

Recently articles have been published disputing the main finding of the ENCODE project that the majority of the human genome exhibits biochemical indices of function, based primarily on low sequence conservation and the existence of larger genomes in some ostensibly simpler organisms (the C-value enigma), indicating the likely presence of significant amounts of junk. Here we challenge these arguments, showing that conservation is a relative measure based on circular assumptions of the non-functionality of transposon-derived sequences and uncertain comparison sets, and that regulatory sequence evolution is subject to different and much more plastic structure-function constraints than protein-coding sequences, as well as positive selection for adaptive radiation. We also show that polyploidy accounts for the higher than expected genome sizes in some eukaryotes, compounded by variable levels of repetitive sequences of unknown significance. We argue that the extent of precise dynamic and differential cell- and tissue-specific transcription and splicing observed from the majority of the human genome is a more reliable indicator of genetic function than conservation, although the unexpectedly large amount of regulatory RNA presents a conceptual challenge to the traditional protein-centric view of human genetic programming. Finally, we suggest that resistance to these findings is further motivated in some quarters by the use of the dubious concept of junk DNA as evidence against intelligent design.

Growing investments in health research by governments and charitable organizations have fueled an increase in collaborative research projects between investigators from affluent and developing countries. Current international guidelines are silent on common intra-consortium data-sharing issues that arise in the context of such collaborations. A lack of guidance on intra-consortium data sharing threatens to undermine the success of crucial research ventures. In this work we outline some of the practical problems commonly faced by investigators working in multi-institutional, international genomic collaborations and offer recommendations on these issues. A data sharing policy should be prospectively negotiated and concluded between collaborators as early as possible. Sponsors of research, including those from developing countries, should issue detailed guidance on the above and related issues as doing so will facilitate research and catalyze scientific progress.

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.

We identified 531 and 616 putative HIF-1α target sites by ChIP-Seq in the cancerous cell line DLD-1 and the non-cancerous cell line TIG-3, respectively. We also examined the positions and expression levels of transcriptional start sites (TSSs) in these cell lines using our TSS-Seq method. We observed that 121 and 48 genes in DLD-1 and TIG-3 cells, respectively, had HIF-1α binding sites in proximal regions of the previously reported TSSs that were up-regulated at the transcriptional level. In addition, 193 and 123 of the HIF-1α target sites, respectively, were located in proximal regions of previously uncharacterized TSSs, namely, TSSs of putative alternative promoters of protein-coding genes or promoters of putative non-protein-coding transcripts. The hypoxic response of DLD-1 cells was more significant than that of TIG-3 cells with respect to both the number of target sites and the degree of induced changes in transcript expression. The Nucleosome-Seq and ChIP-Seq analyses of histone modifications revealed that the chromatin formed an open structure in regions surrounding the HIF-1α binding sites, but this event occurred prior to the actual binding of HIF-1α. Different cellular histories may be encoded by chromatin structures and determine the activation of specific genes in response to hypoxic shock.

Fanconi Anemia (FA) is a rare disorder with incidence of 1in 350,000 births. It is characterized by progressive bone marrow failure leading to death of many patients in their childhood while development of cancer at later stages of life in some. The treatment of FA is still a medical challenge. Current treatments of FA include androgen administration, hematopoietic growth factors administration and hematopoietic stem cell transplantation (HSCT). Clinical gene therapy trials are still ongoing. The partial success of current therapies has renewed interest in the search for new treatments. Generation of patient-specific induced pluripotent stem (iPS) has shown promising results for cell and gene based therapy. Small molecule interventions have been observed to delay tumor onset in FA. Tumors deficient in FA pathway can be treated by profiling of DNA repair pathway through synthetic lethality mechanism. Targeting toll-like receptor 8 (TLR8) dependent TNFα overexpression is yet another upcoming therapeutic approach to treat FA patients. In conclusion, in the present scenario of treatments available for FA, a proper algorithm of treatment decisions must be followed for better management of FA patients and to ensure their increased survival. Innovative therapeutic approaches that can prevent both anemia and cancer should be developed for more effective treatment of FA.

Differences in immunological response among vaccine recipients are determined both by their genetic differences and environmental factors. Knowledge of genetic determinants of immunological response to a vaccine can be used to design a vaccine that circumvents immunogenetic restrictions. The currently available vaccine for typhoid is a pure polysaccharide vaccine, immune response to which is T-cell independent. Little is known about whether genetic variation among vaccinees associates with variation in their antibody response to a polysaccharide vaccine. We conducted a study on 1,000 individuals resident in an area at high-risk for typhoid; vaccinated them with the typhoid vaccine, measured their antibody response to the vaccine, assayed >2,000 curated SNPs chosen from 283 genes that are known to participate in immune-response; and analyzed these data using a strategy to (a) minimize the statistical problems associated with testing of multiple hypotheses, and (b) internally cross-validate inferences, using a half-sample design, with little loss of statistical power. The first stage analysis, using the first half-sample, identified 54 SNPs in 43 genes to be significantly associated with immune response. In the second-stage, these inferences were cross-validated using the second half-sample. First-stage results of only 8 SNPs (out of 54) in 7 genes (out of 43) were cross-validated. We tested additional SNPs in these 7 genes, and found 8 more SNPs to be significantly associated. Haplotypes constructed with these SNPs in these 7 genes also showed significant association. These 7 genes are DEFB1, TLR1, IL1RL1, CTLA4, MAPK8, CD86 and IL17D. The overall picture that has emerged from this study is that (a) immune response to polysaccharide antigens is qualitatively different from that to protein antigens, and (b) polymorphisms in genes involved in polysaccharide recognition, signal transduction, inhibition of T-cell proliferation, pro-inflammatory signaling and eventual production of antimicrobial peptides are associated with antibody response to the polysaccharide vaccine for typhoid.

In the area of omics and translational bio(medical)sciences, there is an increasing need to integrate, normalize, analyze, store and protect genomics data. Large datasets and scientific knowledge are rationally combined into valuable clinical information that ultimately will benefit human healthcare and are en route to clinical practice. Data from biomarker discovery and Next Generation Sequencing (NGS) are very valuable and will combine in comprehensive analyses to stratify medicine and guide therapy planning and ultimately benefit patients. However, the combination into useful and applicable information and knowledge is not trivial. Personalized medicine generally promises to result in both higher quality in treatment for individual patients and in lower costs in health care since patients will be offered only such therapies that are more effective for them and treatments that will not be safe or effective will be avoided. Recent advancements in biomedical and genomic sciences have paved the way to translate such research into clinical practice and health policies. However, the move towards greater personalization of medicine also comes along with challenges in the development of novel diagnostic and therapeutic tools in a complex framework that assumes that the use of genomic information is part of a translational continuum, which spans from basic to clinical research, preclinical and clinical trials, to policy research and the analysis of health and economic outcomes. The use of next-generation genomic technologies to improve the quality of life and efficiency of healthcare delivered to patients has become a mainstay theme in the field as benefits derived from such approaches include reducing a patient’s need to go through ineffective therapies, lowering side- and off-target effects of drugs, prescribing prophylactic therapies before acute exacerbations, and reducing expenditures. As such, personalized medicine promises to increase the quality of clinical care and, in some cases, to decrease health care costs. Besides the scientific challenges, there are several economic hurdles. For instance, healthcare providers need to know, whether the approach of personalized healthcare is affordable and worth the expenses. In addition, the economic rationale of personalized healthcare includes not only the reduction of the high expense of hospitalizations, the predictive diagnostics that will help to reduce cost through prevention or the increased efficacy of personalized therapies needs to offset prices of drugs. There are also several factors that influence payer adoption, coverage and reimbursement; the strength of evidence drives payers‘ decisions about coverage and reimbursement, varies widely depending on the personalized healthcare technology applied and regulation and cost-effectiveness seem to be increasingly associated with reimbursement, which is strongly influenced by professional society guidelines. In general, we see the following main obstacles to the advancement of personalized medicine: (i) the scientific challenges (a poor understanding of molecular mechanisms or a lack of molecular markers associated with some diseases, for example), (ii) the economic challenges (poorly aligned incentives), and (iii) operational issues in public healthcare systems. The operational issues can often be largely resolved within a particular stakeholder group, but correcting the incentive structure and modifying the relationships between stakeholders is more complex. This article focuses on the scientific difficulties that remain to translate genomics technologies into clinical practice and reviews recent technological advances in genomics and the challenges and potential benefits of translating this knowledge into clinical practice, with a particular focus on their applications in oncology.