Develop accurate high-coverage and high-throughput single-cell Duplex-seq chemistry and multi-omics platforms for simultaneous profiling of somatic mutation and the transcriptome in single human cells
Project Number1UG3NS132132-01
Contact PI/Project LeaderZONG, CHENGHANG
Awardee OrganizationBAYLOR COLLEGE OF MEDICINE
Description
Abstract Text
SUMMARY
Here in this UG3/UH3 proposal, we aim to develop a new single-cell whole-genome amplification
chemistry that allows high-accuracy and high-coverage detection of somatic mutations in single
cells and the dual-omics assay that combines the high-accuracy and high-coverage genome
profiling assay with the single-cell transcriptome assay (UG3). And in the UH3, we aim to scale
up the throughput of the scDuplex-seq assay and the related dual-omics assay on the
picoinjection-based droplet platform and validate this platform for different tissue types that are
going to be profiled for somatic mosaicism by SMaTH program at the large scale. Understanding
the heterogeneity of the blueprint of life at single-cell resolution is critical for our understanding of
many fundamental biological processes such as aging and human diseases such as cancer and
neurodegeneration. Hence, the successful development of the proposed single-cell method is
important for reaching the goals of profiling somatic mosaicism set by the SMaHT program
considering that somatic mutations, to our knowledge, are the most frequently occurred type of
somatic variants. With the successful method development, we can determine the overall somatic
mutation burdens in single cells and the variations among them. Going beyond characterizing the
levels of somatic mutations, we can also effectively construct a lineage tree for all the sequenced
single cells. And we expect that there will be phenotypic differences between different branches
of the lineage tree, which correspond to different clones in our body, as recently observed in the
regional dissection-based studies. Upon identifying the different branches/clones, we can
characterize those phenotypic differences between them. The proposed dual-omics assay will
provide the exact tool for this characterization. In terms of our major strategy in developing an
accurate high-coverage genome profiling method, we will apply specialized transposition
chemistry to genomic DNA, which results in duplex-DNA with very uniform fragment size,
maximizing the recovery of these fragments in the downstream chemistry. Our major technical
specialty in scaling up the throughput is the picoinjection droplet system that essentially allows
the implementation of complicated chemistry onto the droplet system. The collaborative
experience between Zong lab and Weitz lab has also been proven to be productive in the
development of the droplet scTotalRNA-seq. Our ultimate goal of this proposal is to produce a
lineage tree with a large number of cells (³1000) with both accurate characterizations of somatic
mutations and the transcriptome in single cells, hence providing the proof of concept picture for
future large-scale profiling by Genome Characterization Centers of the SMaHT program.
Public Health Relevance Statement
NARRATIVE
In this application, we propose a critical development of a duplex-seq-based single-cell whole-
genome sequencing method that will achieve high accuracy and high coverage in detecting
somatic mutations in single cells and the corresponding dual-omics chemistry that allows
simultaneous transcriptome profiling and accurate detection of somatic mutations of single cells.
To meet the goal of large-scale profiling of somatic mosaicism set by the SMaHT program, we
will also develop a high-throughput platform for this chemistry with the innovative picoinjection
system. The large-scale single-cell dual omics profiling of both genome and transcriptome will
allow us to effectively construct the lineage tree of single cells, leading to the large-scale
characterization of different branches/clones in normal tissues and the phenotypical difference
between the different branches/clones, and the associated somatic mutations that drive these
differences.
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