Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

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Integrative genomics viewer

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

An integrated encyclopedia of DNA elements in the human genome.

Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today’s sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license.

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Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration

Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease. Here we report a public database of common variation in the human genome: more than one million single nucleotide polymorphisms (SNPs) for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted. These data document the generality of recombination hotspots, a block-like structure of linkage disequilibrium and low haplotype diversity, leading to substantial correlations of SNPs with many of their neighbours. We show how the HapMap resource can guide the design and analysis of genetic association studies, shed light on structural variation and recombination, and identify loci that may have been subject to natural selection during human evolution.

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A haplotype map of the human genome

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

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Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

Chronic hepatitis C (CHC) affects 170 million people worldwide and is a risk factor for end-stage liver disease and hepatocellular carcinoma. The majority of patients with CHC are from Asian descent (94.6 million); however, CHC is an underappreciated disease in Asian patients. The goal of this study is to review the current literature on Asians with CHC. A PubMed search was used to review the pertinent literature for Asians with CHC. This research has revealed that Hepatitis C virus (HCV) positivity in Asians tends to mirror the prevalence found in the patient’s native country. Asian patients with CHC rarely present with well-known risk factors. The most common genotype in East Asia and South Asia is genotype 1b while genotype 6 is more commonly found in Southeast Asia. Asian patients have superior rates of sustained virologic response (SVR) rates than their non-Asian counterparts regardless of HCV genotype. As the conclusions of this research, we recommend screening for HCV in Asians if the prevalence of a patient’s native country is equal to or exceeds 2%. Additional studies are needed to explore the ethnic differences in patients with CHC.

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Management of Chronic Hepatitis C among Asian Americans

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Diversifying the biomedical workforce during the COVID-19 pandemic.

Rifaximin for the Prophylaxis of Spontaneous Bacterial Peritonitis: A Meta-Analysis

Gut microbial metabolism of 5-ASA diminishes its clinical efficacy in inflammatory bowel disease

Objective Poor metabolic health and certain lifestyle factors have been associated with risk and severity of coronavirus disease 2019 (COVID-19), but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its intersection with socioeconomic deprivation. Design We used data from 592,571 participants of the smartphone-based COVID Symptom Study. Diet quality was assessed using a healthful plant-based diet score, which emphasizes healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate hazard ratios (HR) and 95% confidence intervals (95% CI) for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalization with oxygen support, respectively. Results Over 3,886,274 person-months of follow-up, 31,815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR, 0.91; 95% CI, 0.88-0.94) and severe COVID-19 (HR, 0.59; 95% CI, 0.47-0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate for lowest vs highest quartile of diet score was 22.5 (95% CI, 18.8-26.3) and 40.8 (95% CI, 31.7-49.8; 10,000 person-months) among persons living in areas with low and high deprivation, respectively. Conclusions A dietary pattern characterized by healthy plant-based foods was associated with lower risk and severity of COVID-19. These association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.

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Long H. Nguyen

Papers

Management of Chronic Hepatitis C among Asian Americans

Diversifying the biomedical workforce during the COVID-19 pandemic.

Rifaximin for the Prophylaxis of Spontaneous Bacterial Peritonitis: A Meta-Analysis

Gut microbial metabolism of 5-ASA diminishes its clinical efficacy in inflammatory bowel disease

Diet quality and risk and severity of COVID-19: a prospective cohort study