Human genomics articles

Whole exome sequencing (WES) is a popular and cost-effective method for capturing high quality genotype calls at the protein coding portion of the genome, and has been key in facilitating the discovery of functionally relevant variants across a range of research and clinical settings. Despite this, WES is designed to only capture exonic regions, meaning that the yield of on-target calls obtained through this technology is typically restricted to only around 1% of the genome in total. This has the potential to hamper discovery efforts that solely rely on WES, as it means that the intronic and intergenic fraction of the genome, which comprise the majority, remain un-assayed. Notably, over 90% of signals discovered through Genome Wide Association Studies (GWAS) fall within non-coding regions of the genome, and many analytical methods in the field of genomics rely on dense sampling of genotypes across samples genome-wide for statistical inference. Consequently, researchers who choose to employ WES for large-scale discovery efforts often have to supplement exome sequencing with array-based genotyping technologies in order to capture a more complete picture of their study population. 

RNA-sequencing has revolutionized human genomics by offering insights into gene expression and the broader transcriptomic landscape. This powerful technology is particularly impactful in fields such as oncology, drug development, and personalized medicine, where it allows researchers to identify biomarkers and develop targeted therapies by measuring gene expression levels and detecting RNA transcript mutations. 

The tools available to scientists and clinicians in the field of genetics are evolving rapidly. While genotyping microarrays once dominated the field, next-generation sequencing (NGS) technologies are becoming increasingly popular. This is particularly true among researchers studying pharmacogenomics (PGx). In recent years, the number of variants linked to an altered drug response has grown rapidly and consequently put a spotlight on the critical failings of microarrays.

The recent release of Whole Genome Sequencing (WGS) data for 490,640 participants in the UK Biobank (UKBB) has presented researchers with opportunities for comprehensive assessment of genomic risk factors underlying disease at an unprecedented resolution and scale. With the release of this data, we wanted to explore two traits of interest, Body Mass Index (BMI) and Type II Diabetes (T2D), to understand how increased resolution on genome-wide associations for these traits.

Investigating the genetic basis of complex human traits is a pivotal endeavor in modern biomedical research. In a recent study, researchers at the Weizmann Institute of Science delved into a deep repository of clinical and genetic data to unravel the genetic associations across a range of disease phenotypes.

In this blog post, we describe some imputation performance benchmarks for a recently released haplotype reference panel from the Martin Lab comprising haplotypes from high-depth sequence data from the 1000 Genomes project and the Human Genome Diversity Project and compare them against corresponding benchmarks for the New York Genome Center's resequencing effort of the 1000 Genomes project.

Pharmaceutical companies use Whole Exome Sequencing (WES) in their drug discovery and development process. However, R&D teams still need a comprehensive view of genomic variation outside the exome. Historically, the only way to augment WES was with arrays, but now pharma companies have an alternative - low-pass whole genome sequencing.