Biology subjects

Bartlett, A.

Publications and source records attributed to Bartlett, A..

39 records · Page 3Linked to original sources

bioRxiv2018

Single-cell multi-omic profiling of chromatin conformation and DNA methylome

Recent advances in the development of single cell epigenomic assays have facilitated the analysis of gene regulatory landscapes in complex biological systems. Methods for detection of single-cell epigenomic variation such as DNA methylation sequencing and ATAC-seq hold tremendous promise for delineating distinct cell types and identifying their critical cis-regulatory sequences. Emerging evidence has shown that in addition to cis-regulatory sequences, dynamic regulation of 3D chromatin conformation is a critical mechanism for the modulation of gene expression during development and disease. It remains unclear whether single-cell Chromatin Conformation Capture (3C) or Hi-C profiles are suitable for cell type identification and allow the reconstruction of cell-type specific chromatin conformation maps. To address these challenges, we have developed a multi-omic method single-nucleus methyl-3C sequencing (sn-m3C-seq) to profile chromatin conformation and DNA methylation from the same cell. We have shown that bulk m3C-seq and sn-m3C-seq accurately capture chromatin organization information and robustly separate mouse cell types. We have developed a fluorescent-activated nuclei sorting strategy based on DNA content that eliminates nuclei multiplets caused by crosslinking. The sn-m3C-seq method allows high-resolution cell-type classification using two orthogonal types of epigenomic information and the reconstruction of cell-type specific chromatin conformation maps.

genomics↗

bioRxiv2018

Multi-omic profiling of transcriptome and DNA methylome in single nuclei with molecular partitioning

Single-cell transcriptomic and epigenomic analyses provide powerful strategies for unbiased determination of cell types in mammalian tissues. Although previous studies have identified cell types using individual molecular signatures, the generation of consensus cell type classification requires the integration of multiple data types. Most existing single-cell techniques can only make one type of molecular measurement. Here we describe single-nucleus methylcytosine and transcriptome sequencing (snmCT-seq), a multi-omic method that requires no physical separation of DNA and RNA molecules. We demonstrated that snmCT-seq profiles generated from single cells or nuclei robustly distinguish human cell types and accurately measures cytosine DNA methylation and gene expression signatures of each cell type.

genomics↗

bioRxiv2017

Recurrent loss of heterozygosity correlates with clinical outcome in pancreatic neuroendocrine cancer

Pancreatic neuroendocrine tumors (pNETs) are uncommon cancers arising from pancreatic islet cells. Analysis of gene mutation, copy number and RNA expression of 57 sporadic pNETs showed that pNET genomes are dominated by aneuploidy. Remarkably, ~25% of pNETs had genomes characterized by recurrent loss of heterozygosity (LoH) of the same 10 chromosomes, accompanied by bi-allelic MEN1 inactivation, and these cases had generally poor clinical outcome. Another ~25% of all pNETs had chromosome 11 LoH and bi-allelic MEN1 inactivation, lacking the recurrent LoH pattern - these had universally good clinical outcome. Some level of aneuploidy was common, and overall ~80% of pNETs had LoH of [≥]1 chromosome. This aneuploidy led to changes in RNA expression at the level of whole chromosomes and allowed pathogenic germline variants (e.g. ATM) to be expressed unopposed, inactivating downstream tumor suppressor pathways. Some pNETs appear to utilize VHL gene methylation or mutation to activate pseudo-hypoxia. Contrary to expectation neither tumor morphology within well-differentiated pNETs nor single gene mutation had significant associations with clinical outcome, nor did expression of RNAs reflecting the activity of immune, differentiation, proliferative or tumor suppressor pathways. MEN1 was the only statistically significant recurrently mutated driver gene in pNETs. Only one pNET had clearly oncogenic and actionable SNVs (in PTEN and FLCN) confirmed by corroborating RNA expression changes. The two distinct patterns of aneuploidy described here, associated with markedly poor and good clinical outcome respectively, define a novel oncogenic mechanism and the first route to genomic precision oncology for this tumor type.

cancer biology↗