Haplotype resolution at the single-cell level
Year: 2017
Type: article
Abstract: One of the most rapidly advancing areas in genomics in recent years has been the explosion of platforms to assess properties at the single-cell level. The driving force behind these advancements has been a renaissance of sorts in how we think about the architecture and heterogeneity present in a population of cells (1, 2). While these concepts are not new, the advancement of technologies to assess latent cell heterogeneity has enabled this new era. One of the earliest iterations of single-cell “omics” was the sequencing of the genome itself, which has seen a rapid proliferation of technological advancements (3), including a novel platform by Chu et al. (4) presented in PNAS. Over the years, a number of studies have utilized single-cell genome sequencing to reveal novel insights into a wide range of biological systems from somatic mutation profiling, both in (5) and out (6) of the cancer context, to the determination of meiotic recombination rates (7).
To date, multiple platforms have been developed to sequence the genome of individual cells, each aimed at addressing specific types of variation. High-cell-count, low-depth strategies are tailored to assess copy number alterations: gains or losses of stretches of DNA up to entire chromosomes (8). However, these methods fail to capture point variation, single-nucleotide variants or very short insertions or deletions (indels), that may play a critical role in tumor clonal progression, or somatic variation in other contexts (9, 10). Strategies to ascertain point variation in single cells, which will be focused on in this commentary, involve the amplification of DNA and then sequencing to a high depth of coverage for each cell, resulting in higher costs and, typically, reduced cell numbers (3).
One of the primary challenges faced by these higher coverage methods is that they rely on even amplification …
[↵][1]1Email: adey{at}ohsu.edu.
[1]: #xref-corresp-1-1
Author: Andrew C. Adey
Institution: Oregon Health & Science University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2767723427