Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue

ABSTRACT: Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue

PROVIDER: PRJNA630463 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR11691900.fastq.gz	Fastqsanger.gz
	SRR11691901.fastq.gz	Fastqsanger.gz
	SRR11691902.fastq.gz	Fastqsanger.gz
	SRR11691903.fastq.gz	Fastqsanger.gz
	SRR11691904.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 73

Similar Datasets

Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue [plasmid]

Project description:Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue [plasmid]

| PRJNA630417 | ENA

Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue.

Project description:Understanding the contributions of transcription factor DNA binding sites to transcriptional enhancers is a significant challenge. We developed Quantitative enhancer-FACS-Seq for highly parallel quantification of enhancer activities from a genomically integrated reporter in Drosophila melanogaster embryos. We investigate the contributions of the DNA binding motifs of four poorly characterized TFs to the activities of twelve embryonic mesodermal enhancers. We measure quantitative changes in enhancer activity and discover a range of epistatic interactions among the motifs, both synergistic and alleviating. We find that understanding the regulatory consequences of TF binding motifs requires that they be investigated in combination across enhancer contexts.

| S-EPMC8686523 | biostudies-literature

Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue [Drosophila melanogaster]

Project description:Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue [Drosophila melanogaster]

| PRJNA630468 | ENA

Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue

Project description:This SuperSeries is composed of the SubSeries listed below.

2021-12-08 | GSE149908 | GEO

Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue [plasmid]

Project description:Activity of enhancers in Drosophila embryos was measured by highly parallel reporter assay. We examined the results of mutating binding sites for 4 poorly studied TFs individually or in combination, and characterized complex genetic interactions among the different classes of motif mutant.

2021-12-08 | GSE149875 | GEO

Quantitative-enhancer-FACS-seq (QeFS) reveals epistatic interactions among motifs within transcriptional enhancers in developing Drosophila tissue [Drosophila melanogaster]

2021-12-08 | GSE149906 | GEO

Network of epistatic interactions within a yeast snoRNA.

Project description:Epistatic interactions play a fundamental role in molecular evolution, but little is known about the spatial distribution of these interactions within genes. To systematically survey a model landscape of intragenic epistasis, we quantified the fitness of ~60,000 Saccharomyces cerevisiae strains expressing randomly mutated variants of the 333-nucleotide-long U3 small nucleolar RNA (snoRNA). The fitness effects of individual mutations were correlated with evolutionary conservation and structural stability. Many mutations had small individual effects but had large effects in the context of additional mutations, which indicated negative epistasis. Clusters of negative interactions were explained by local thermodynamic threshold effects, whereas positive interactions were enriched among large-effect sites and between base-paired nucleotides. We conclude that high-throughput mapping of intragenic epistasis can identify key structural and functional features of macromolecules.

| S-EPMC5137784 | biostudies-literature

A systematic approach to identify functional motifs within vertebrate developmental enhancers.

Project description:Uncovering the cis-regulatory logic of developmental enhancers is critical to understanding the role of non-coding DNA in development. However, it is cumbersome to identify functional motifs within enhancers, and thus few vertebrate enhancers have their core functional motifs revealed. Here we report a combined experimental and computational approach for discovering regulatory motifs in developmental enhancers. Making use of the zebrafish gene expression database, we computationally identified conserved non-coding elements (CNEs) likely to have a desired tissue-specificity based on the expression of nearby genes. Through a high throughput and robust enhancer assay, we tested the activity of approximately 100 such CNEs and efficiently uncovered developmental enhancers with desired spatial and temporal expression patterns in the zebrafish brain. Application of de novo motif prediction algorithms on a group of forebrain enhancers identified five top-ranked motifs, all of which were experimentally validated as critical for forebrain enhancer activity. These results demonstrate a systematic approach to discover important regulatory motifs in vertebrate developmental enhancers. Moreover, this dataset provides a useful resource for further dissection of vertebrate brain development and function.

| S-EPMC3330829 | biostudies-literature

Epistatic regulation of complex traits and gene expression in mice

Project description:The genetic contribution of additive versus non-additive (epistasis) effects in the regulation of hematologic and other complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, in part because of the lack of statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate and powerful model for detecting epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both additive and epistatic loci that regulate a range of hematologic- and metabolism-related traits, as well as hepatic gene expression. Quantitative trait loci (QTLs) were identified using a modified backcross strategy involving the segregation of variants on the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. By analyzing the transcriptomes of offspring from this cross, we identified and mapped additive QTLs regulating the expression of 768 genes, and epistatic QTLs for 519 genes. Similarly, we identified additive QTLs for fat pad weight, platelets, and percentage of granulocyte in the blood as well as epistatic QTLs controlling the percentage of lymphocytes in the blood and red cell distribution width. The variance attributed to the epistatic QTLs was approximately equal to that of the additive QTLs, demonstrating the importance of identifying genetic interactions to understand the genetic basis of complex traits. Of particular note, even the epistatic QTLs identified that accounted for the largest variances were undetected in our single loci GWAS-like association analyses, highlighting the need to account for epistasis in association studies.

2020-10-05 | GSE145607 | GEO

Epistatic transcriptional interations underlying oncogenic genetic interactions (GI) via combinatorial CROP-seq

Project description:Epistatic transcriptional interations underlying oncogenic genetic interactions (GI) via combinatorial CROP-seq

| PRJNA692740 | ENA