Blog

Sequencing projects come in many different forms. At Gencove, we’ve seen and supported a broad range of species and sample types. Occasionally, we receive projects that our partner service labs can't support using standard procedures, necessitating bespoke and innovative solutions.

Detecting structural variants in the human genome remains a substantial challenge for most sequencing projects. Most DNA sequencing projects use short-read NGS platforms, making it challenging to accurately resolve long, complex structural mutations. While long-read sequencing platforms are both available and well-suited for structural variant detection, the significant cost of using these platforms has prevented their widespread use.

Effectively we are rapidly approaching a world where sequencing costs per se are irrelevant to companies looking to implement genetic testing at massive scale. The scientific implications of this are fun to consider, but it’s also worth thinking about the overall business implications.

As sequencing costs continue to drop, the upstream (library preparation) and downstream (data analysis & management) pieces of next-generation sequencing are becoming more important. The costs associated with library preparation have remained constant, so finding cost-saving modifications to this step has become increasingly important, especially at Gencove in our mission towards ubiquitous sequencing.

At Gencove, we’ve long talked about Moo-res law, the trend of increasing genotype adoption in the cattle breeding world, with global genotyping in the cattle industry likely to hit 5 million samples annually by mid-decade. The successes of genomic selection are well known, led by the US dairy evaluation’s pioneering efforts over 15 years ago, with adoption following in many cattle breeding programs globally.

As we close the book on 2023, the Gencove team was busier than ever in the pursuit our mission: a healthier and more sustainable civilization through the application of ubiquitous sequencing. Our work with our partners spanned species and populations, today we look back on a few key highlights.

A recent study from the Gencove and Element Biosciences teams has demonstrated the efficacy of low-pass sequencing plus imputation using avidity sequencing compared to sequencing by synthesis.

We recently reported on the release of the novel gnomAD_v3.1.2 HGDP1KG human reference panel for build GRCh38. This new panel consists of a total of 4091 individuals, and we have previously discussed its considerable gains in imputation power when compared to other publicly available human reference panels. We have now made the HGDP1KG panel available for build GRCh37.

The human leukocyte antigen (HLA) locus is a cluster of genes on chromosome 6 of the human genome that play a crucial role in self/non-self recognition in the immune system. Understanding genetic variation at the HLA locus is essential in human genetics; however, accurately genotyping the HLA locus has proven challenging because it is complex and highly polymorphic. Here, we compare these two HLA imputation approaches to learn which path leads to greater accuracy.

At Gencove, we have repeatedly seen the complexity and insufficiency of existing tools limit research teams from fully unlocking the value of their genetic data. Gencove Explorer analysis cloud represents a full-stack solution that addresses the challenges that exist with currently data solutions, in a single integrated platform and with a minimal learning curve. In doing so, Explorer accelerates the rate at which scientists can answer critical biological questions, and furthers our goal of delivering insights that advance global health and sustainability.

The Broad recently released an update to the HGDP1KG panel as part of the gnomAD_v3.1.2 release that included several tweaks and changes meant to increase the accuracy of the combined panel. In this blog post we once compare imputation performance of this updated panel to the NYGC1KG panel.

The new "sample manifests" feature ensures accurate sample identification and reduces errors, streamlining the process from sample collection to solutions delivered by the platform.