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tl;dr: new competition in genome sequencing hardware will drive expanded use cases for sequencing analytics across industries

In Nature’s Metropolis, the brilliant economic history of Chicago, William Cronon describes the shifts in power between agricultural producers and different industrial groups as technologies like the grain elevator upended traditional market relationships.

In this telling, a set of small steps gradually severed the connection between the buyer of a grain like corn and its original source — while in 1850 someone might buy a bag of corn from an individual producer and know that each individual kernel came from a specific plot of land, by 1880 that same buyer would likely be buying a quantity of "Number 2", pooled from corn produced in any number of anonymous locations.

The 1000 Genomes Project was completed in 2015 and culminated in its "phase 3 release" of phased genotypes from 2504 individuals at over 80 million variants, and remains the largest fully open-sourced genomic dataset [0]. The final variant callset was based on a combination low-coverage whole-genome sequencing (at an average of around 7x) along with whole exome sequencing and results from genotyping array assays of these individuals.

Along with Warren Snelling and other colleagues at the USDA MARC (Meat Animal Research Center), we recently performed a study investigating the utility of imputation from low pass sequencing data in cattle in the context of genomic prediction for beef steers. This study is now published in MDPI Genes and can be accessed at the following link [0]. In this blog post, we briefly review the motivations behind this study and outline the main results.

At Gencove, we’re continuously expanding the selection of species which can be used with imputation pipelines based off of low-pass sequencing. Unlike, for instance, cattle in the form of the 1000 Bull Genomes Project [1], there does not currently exist a large-scale public resequencing effort to characterize the genetic diversity of extant breeds used for agricultural purposes, and the existing literature on the performance on genotype imputation in pigs is primarily limited to genotyping array imputation [2,3,4].

To address this current shortcoming, we have recently developed and released a pipeline for low-pass sequencing in pigs on the latest reference genome (Sscrofa11.1/susScr11) and a diverse haplotype reference panel encompassing the range of genetic diversity in the most common breeds found in the swine industry.

The new product supports more breeds and returns higher accuracy through an updated reference panel. We have also made it easier to use for industrial scale applications.

We are excited to announce an update to our cattle imputation reference panel, which now includes over 50 breeds and 1800 animals. This better supports the demand we’ve had for all the most important breeds being utilized by the cattle industry today. Since launching our original panel, we’ve been busy optimizing our pipeline and adding new features to make low-pass sequencing more powerful and easier to use. We believe this platform is now the best high-throughput solution for building genomic breeding programs.

At Gencove, our mission is to make genome sequencing accessible and interpretable. Over the past several weeks, it has become clear that a key missing piece of the response to the coronavirus crisis in the United States involves sequencing to monitor virus strains as they arise and spread. This was driven home by the identification of an apparently more contagious virus lineage in the UK and a potentially similar report from South Africa.

It seems certain that virus lineages with worrying properties (e.g. increased transmission or vaccine escape) are arising elsewhere in the world; these variants were only identified in the countries in question because they have systems for systematic viral surveillance by genome sequencing.

Users can now assign arbitrary JSON-formatted metadata to Gencove samples for downstream use.

We’ve been receiving consistent feedback from users saying they would like to store additional non-genomic data together with genomic data for their Gencove samples. These requests can be grouped into two broad clusters according to the nature of the data being stored:

• Phenotypic data about the individual represented by the sample
• Technical processing data
  • Batch information
  • Alternative or auxiliary identifiers

NEW YORK, March 13, 2019 /PRNewswire/ -- Gencove, the leading low-pass genome sequencing platform, announced today a $3 million investment led by Spero Ventures. Alexandria Venture Investments and Burst Capital participated in the round, along with existing investors Third Kind Venture Capital and Version One Ventures. The funding will be used to develop new applications for agricultural markets as well as expand Gencove's commercial operations in human genetics. Shripriya Mahesh, partner at Spero, will join Gencove's board of directors.