Dataset Information

Identifying Improved Sites for Heterologous Gene Integration Using ATAC-seq.

ABSTRACT: Constructing efficient cellular factories often requires integration of heterologous pathways for synthesis of novel compounds and improved cellular productivity. Few genomic sites are routinely used, however, for efficient integration and expression of heterologous genes, especially in nonmodel hosts. Here, a data-guided framework for informing suitable integration sites for heterologous genes based on ATAC-seq was developed in the nonmodel yeast Komagataella phaffii. Single-copy GFP constructs were integrated using CRISPR/Cas9 into 38 intergenic regions (IGRs) to evaluate the effects of IGR size, intensity of ATAC-seq peaks, and orientation and expression of adjacent genes. Only the intensity of accessibility peaks was observed to have a significant effect, with higher expression observed from IGRs with low- to moderate-intensity peaks than from high-intensity peaks. This effect diminished for tandem, multicopy integrations, suggesting that the additional copies of exogenous sequence buffered the transcriptional unit of the transgene against effects from endogenous sequence context. The approach developed from these results should provide a basis for nominating suitable IGRs in other eukaryotic hosts from an annotated genome and ATAC-seq data.

SUBMITTER: Brady JR

PROVIDER: S-EPMC7506950 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Identifying Improved Sites for Heterologous Gene Integration Using ATAC-seq.

Brady Joseph R JR Tan Melody C MC Whittaker Charles A CA Colant Noelle A NA Dalvie Neil C NC Love Kerry Routenberg KR Love J Christopher JC

ACS synthetic biology 20200824 9

Constructing efficient cellular factories often requires integration of heterologous pathways for synthesis of novel compounds and improved cellular productivity. Few genomic sites are routinely used, however, for efficient integration and expression of heterologous genes, especially in nonmodel hosts. Here, a data-guided framework for informing suitable integration sites for heterologous genes based on ATAC-seq was developed in the nonmodel yeast <i>Komagataella phaffii</i>. Single-copy GFP con ...[more]

PMID: 32786350

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Project description:ObjectiveAlthough glucagon-secreting α-cells and insulin-secreting β-cells have opposing functions in regulating plasma glucose levels, the two cell types share a common developmental origin and exhibit overlapping transcriptomes and epigenomes. Notably, destruction of β-cells can stimulate repopulation via transdifferentiation of α-cells, at least in mice, suggesting plasticity between these cell fates. Furthermore, dysfunction of both α- and β-cells contributes to the pathophysiology of type 1 and type 2 diabetes, and β-cell de-differentiation has been proposed to contribute to type 2 diabetes. Our objective was to delineate the molecular properties that maintain islet cell type specification yet allow for cellular plasticity. We hypothesized that correlating cell type-specific transcriptomes with an atlas of open chromatin will identify novel genes and transcriptional regulatory elements such as enhancers involved in α- and β-cell specification and plasticity.MethodsWe sorted human α- and β-cells and performed the "Assay for Transposase-Accessible Chromatin with high throughput sequencing" (ATAC-seq) and mRNA-seq, followed by integrative analysis to identify cell type-selective gene regulatory regions.ResultsWe identified numerous transcripts with either α-cell- or β-cell-selective expression and discovered the cell type-selective open chromatin regions that correlate with these gene activation patterns. We confirmed cell type-selective expression on the protein level for two of the top hits from our screen. The "group specific protein" (GC; or vitamin D binding protein) was restricted to α-cells, while CHODL (chondrolectin) immunoreactivity was only present in β-cells. Furthermore, α-cell- and β-cell-selective ATAC-seq peaks were identified to overlap with known binding sites for islet transcription factors, as well as with single nucleotide polymorphisms (SNPs) previously identified as risk loci for type 2 diabetes.ConclusionsWe have determined the genetic landscape of human α- and β-cells based on chromatin accessibility and transcript levels, which allowed for detection of novel α- and β-cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.

Dataset Information

Identifying Improved Sites for Heterologous Gene Integration Using ATAC-seq.

Publications

Identifying Improved Sites for Heterologous Gene Integration Using ATAC-seq.

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