Effects of gene-by-environment interaction on the transcriptome of mice deficient for tryptophan hydroxylase 2 [RNA-seq]
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ABSTRACT:
PROVIDER: PRJNA433807 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6706350_1.fastq.gz | Fastqsanger.gz | |||
| SRR6706350_2.fastq.gz | Fastqsanger.gz | |||
| SRR6706360_1.fastq.gz | Fastqsanger.gz | |||
| SRR6706360_2.fastq.gz | Fastqsanger.gz | |||
| SRR6706370_1.fastq.gz | Fastqsanger.gz |
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Project description:Effects of gene-by-environment interaction on the transcriptome and methylome of mice deficient for tryptophan hydroxylase 2
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Project description:Effects of gene-by-environment interaction on the methylome of mice deficient for tryptophan hydroxylase 2 [MBD-seq]
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Project description:Purpose: Investigation of effects of early adversity in mice deficient for brain serotonin on the methylome Methods: Following materal separation in early childhood and behavioural screening in adulthood, 4 moth old males, either wildtype or carrying a hetero- or homozygous knockout of the thryptophan hyroxylase 2 gene, were sacrificed, brains extracted, the amygdalae of both hemispheres dissected, blended and separated in two protions. From one of these portions DNA was processed by an external company, i.e. Nxt-Dx (Ghent, Belgium). DNA was sheared by sonication, followed by methyl binding domain (MBD) based capture, leading to an enrichment of methylated fragments. Subsequently, library preparation was performed followed by multiplexed paired-end sequencing with a read-length of 50 bp and an approximate output of 20 million reads/sample on the Illumina HiSeq4000 platform. Reads were mapped to the Mus musculus GRCm38.p5 genome using Bowtie2 (v2.1.0) software in end-to-end & sensitive-mode. After mapping, coverage peaks were generated using MACS 14 peak caller (Zhang et al. 2008). Results: Either Tph2 genotype, early adversity as well as their interaction resulted in unique profiles of differentially enriched methylated peaks as well as expressed RNA. As expected, the effect sizes and significances were rather subtle and the overlap between top hits of methylome and transcriptome were marginal. Conclusion: Tph2, MS and their interaction induced changes in gene expression and DNA methylation, within a physiological range. The observed changes by MS seemed furthermore strongly influenced by the Tph2 genotype, ergo brain 5-HT availability.
2019-05-06 | GSE110329 | GEO
Project description:Purpose: Investigation of effects of early adversity in mice deficient for brain serotonin on the transcriptome Methods: Following materal separation in early childhood and behavioural screening in adulthood, 4 moth old males, either wildtype or carrying a hetero- or homozygous knockout of the thryptophan hyroxylase 2 gene, were sacrificed, brains extracted, the amygdalae of both hemispheres dissected, blended and separated in two protions. From one of these portions RNA was extracted. Extracted RNA was further processed by an external company, i.e. IGA Technologies (Udine, Italy). , library preparation was performed using TruSeq Stranded Total RNA Library Prep Kit (Illumina, San Diego, CA, US) that captures coding RNA and multiple forms of non-coding RNA, with a total input of 300 ng of RNA, as measured with Qubit 2.0 Fluorometer (Invitrogen, Carlsbad, CA) following manufacturer’s recommendations. The sequencing was performed using the Illumina HiSeq 2500 platform at a read-length of 125 bp with paired end reads yielding 60 million reads/sample. Reads were mapped to the Mus musculus GRCm38.p5 genome using STAR (Dobin et al. 2013). Following mapping, the reads per position were determined using HTSeq (Anders et al. 2015). Results: Either Tph2 genotype, early adversity as well as their interaction resulted in unique profiles of differentially expressed RNA. As expected, the effect sizes and significances were rather subtle. Conclusion: Tph2, MS and their interaction induced changes in gene expression and DNA methylation, within a physiological range. The observed changes by MS seemed furthermore strongly influenced by the Tph2 genotype, ergo brain 5-HT availability.
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Project description:Genotype Environment interaction in Salmon
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2019-05-06 | GSE110330 | GEO
Project description:Genotype Environment interaction in shell breakage
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Project description:Serotonin in the mammary gland is known to regulate processes such as calcium homeostasis, tight junction permeability, and milk protein gene expression. The objective of this study was to discover novel genes, pathways and functions which serotonin modulates during lactation. The rate-limiting enzyme in the synthesis of non-neuronal serotonin is tryptophan-hydroxylase (TPH1). Therefore, we used TPH1 knock-out mice dams (serotonin deficient) and compared them to wild-type dams and also Tph1 deficient dams injected daily with 5-HTP. Mammary gland tissues were collected on day 10 of lactation and then analyzed by RNA sequencing. Genome-wide gene expression profiles of 12 mouse mammary gland samples were evaluated using RNA sequencing; these 12 samples belong to wild-type dams (WT; n = 4), Tryptophan hydroxylase (Tph1) knock-out dams (KO; Tph1 deficient; n = 4), and Tph1 deficient dams injected daily with 5-HTP (RC; n = 4). Mammary tissues were collected on day 10 of lactation and then underwent RNA extraction, library generation, and subsequent sequencing.
2015-04-28 | E-GEOD-68315 | biostudies-arrayexpress
Project description:This study is a quantitative trait linkage mapping study targeted at gene-environment interaction. A family of yeast derived from BY4716 and RM11-1a was grown in two carbon sources (glucose and ethanol) and expression profiled. The analysis revealed how the influence of genetic factors changes in different conditions. Abstract: The effects of genetic variants on phenotypic traits often depend on environmental and physiological conditions, but such gene–environment interactions are poorly understood. Recently developed approaches that treat transcript abundances of thousands of genes as quantitative traits offer the opportunity to broadly characterize the architecture of gene–environment interactions. We examined the genetic and molecular basis of variation in gene expression between two yeast strains (BY and RM) grown in two different conditions (glucose and ethanol carbon sources). We observed that most transcripts vary by strain and condition, with 2,996, 3,448, and 2,037 transcripts showing significant strain, condition, and strain–condition interaction effects, respectively. We expression profiled over 100 segregants derived from a cross between RM and BY in both growth conditions, and identified 1,555 linkages for 1,382 transcripts that show significant gene–environment interaction. At the locus level, local linkages, which usually correspond to polymorphisms in cis-regulatory elements, tend to be more stable across conditions, such that they are more likely to show the same effect or the same direction of effect across conditions. Distant linkages, which usually correspond to polymorphisms influencing trans-acting factors, are more condition-dependent, and often show effects in different directions in the two conditions. We characterized a locus that influences expression of many growth- related transcripts, and showed that the majority of the variation is explained by polymorphism in the gene IRA2. The RM allele of IRA2 appears to inhibit Ras/PKA signaling more strongly than the BY allele, and has undergone a change in selective pressure. Our results provide a broad overview of the genetic architecture of gene–environment interactions, as well as a detailed molecular example, and lead to key insights into how the effects of different classes of regulatory variants are modulated by the environment. These observations will guide the design of studies aimed at understanding the genetic basis of complex traits. Keywords: QTL This data set includes 24 parental arrays (6 of each parent in each condition, 218 segregant arrays (109 in both conditions), and 4 allele replacement arrays (IRA2 replacements in both backgrounds in both conditions). All arrays are from an unique biological sample, and many are randomized for dye (no dye-swaps on the same RNA sample). For the 24 parental arrays, there are three of each strain*condition*dye combination. The segregant arrays were randomized for dye. The replacement arrays are all of the Cy5 = experimental, Cy3 = reference type. All arrays are hybridized to a common reference consisting of an equal portions of RNA samples. from BY and RM grown in glucose and ethanol. Analysis was performed using default settings in Agilent Feature Extractor software versions 8.0-9.5. Spots were excluded if their intensity was below 350 or if they were flagged as non-uniformity outliers. Transcripts were considered good if they were present in all parental arrays (for the parental analysis) or 80% of all arrays in each condition for the segregant analysis.
2008-04-15 | E-GEOD-9376 | biostudies-arrayexpress