Dataset Information

High-Throughput Single-Cell Sequencing with Linear Amplification.

ABSTRACT: Conventional methods for single-cell genome sequencing are limited with respect to uniformity and throughput. Here, we describe sci-L3, a single-cell sequencing method that combines combinatorial indexing (sci-) and linear (L) amplification. The sci-L3 method adopts a 3-level (3) indexing scheme that minimizes amplification biases while enabling exponential gains in throughput. We demonstrate the generalizability of sci-L3 with proof-of-concept demonstrations of single-cell whole-genome sequencing (sci-L3-WGS), targeted sequencing (sci-L3-target-seq), and a co-assay of the genome and transcriptome (sci-L3-RNA/DNA). We apply sci-L3-WGS to profile the genomes of >10,000 sperm and sperm precursors from F1 hybrid mice, mapping 86,786 crossovers and characterizing rare chromosome mis-segregation events in meiosis, including instances of whole-genome equational chromosome segregation. We anticipate that sci-L3 assays can be applied to fully characterize recombination landscapes, to couple CRISPR perturbations and measurements of genome stability, and to other goals requiring high-throughput, high-coverage single-cell sequencing.

SUBMITTER: Yin Y

PROVIDER: S-EPMC6874760 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Publications

High-Throughput Single-Cell Sequencing with Linear Amplification.

Yin Yi Y Jiang Yue Y Lam Kwan-Wood Gabriel KG Berletch Joel B JB Disteche Christine M CM Noble William S WS Steemers Frank J FJ Camerini-Otero R Daniel RD Adey Andrew C AC Shendure Jay J

Molecular cell 20190905 4

Conventional methods for single-cell genome sequencing are limited with respect to uniformity and throughput. Here, we describe sci-L3, a single-cell sequencing method that combines combinatorial indexing (sci-) and linear (L) amplification. The sci-L3 method adopts a 3-level (3) indexing scheme that minimizes amplification biases while enabling exponential gains in throughput. We demonstrate the generalizability of sci-L3 with proof-of-concept demonstrations of single-cell whole-genome sequenci ...[more]

PMID: 31495564

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Project description:Recent discoveries suggest that photoheterotrophs (rhodopsin-containing bacteria (RBs) and aerobic anoxygenic phototrophs (AAPs)) and chemoautotrophs may be significant for marine and freshwater ecosystem productivity. However, their abundance and taxonomic identities remain largely unknown. We used a combination of single-cell and metagenomic DNA sequencing to study the predominant photoheterotrophs and chemoautotrophs inhabiting the euphotic zone of temperate, physicochemically diverse freshwater lakes. Multi-locus sequencing of 712 single amplified genomes, generated by fluorescence-activated cell sorting and whole genome multiple displacement amplification, showed that most of the cosmopolitan freshwater clusters contain photoheterotrophs. These comprised at least 10-23% of bacterioplankton, and RBs were the dominant fraction. Our data demonstrate that Actinobacteria, including clusters acI, Luna and acSTL, are the predominant freshwater RBs. We significantly broaden the known taxonomic range of freshwater RBs, to include Alpha-, Beta-, Gamma- and Deltaproteobacteria, Verrucomicrobia and Sphingobacteria. By sequencing single cells, we found evidence for inter-phyla horizontal gene transfer and recombination of rhodopsin genes and identified specific taxonomic groups involved in these evolutionary processes. Our data suggest that members of the ubiquitous betaproteobacteria Polynucleobacter spp. are the dominant AAPs in temperate freshwater lakes. Furthermore, the RuBisCO (ribulose 1,5-bisphosphate carboxylase/oxygenase) gene was found in several single cells of Betaproteobacteria, Bacteroidetes and Gammaproteobacteria, suggesting that chemoautotrophs may be more prevalent among aerobic bacterioplankton than previously thought. This study demonstrates the power of single-cell DNA sequencing addressing previously unresolved questions about the metabolic potential and evolutionary histories of uncultured microorganisms, which dominate most natural environments.

Dataset Information

High-Throughput Single-Cell Sequencing with Linear Amplification.

Publications

High-Throughput Single-Cell Sequencing with Linear Amplification.

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