Project description:204 placentas from three cohorts were processed for DNAme arrays in Vancouver, Canada. The three cohorts consisted of: (i) V-NORM, a normative population of term pregnancies recruited at BC Women’s Hospital (BCWH) in Vancouver, Canada (n=35), as part of a study on Epigenetics in Pregnancy Complications (EPIC); ii) V-SSRI, a population of pregnant individuals recruited in Vancouver, Canada in the 20th week of gestation (n=64), with/without clinical depression, and with/without the use of selective serotonin reuptake inhibitors (SSRIs); and (iii) QF-2011, a population of term pregnancies that were exposed to sudden-onset stress during gestation due to catastrophic flooding in the Australian state of Queensland in early January 2011 (n=105). DNA samples from all three cohorts were run on Illumina Infinium MethylationEPIC arrays in Vancouver, BC, Canada. Processing included DNA purification after extraction using the DNeasy Blood & Tissue Kit (Qiagen, Valencia, CA, USA), bisulfite conversion using the EZ DNAme Kit (Zymo Research, Orange, CA, USA), and hybridization to and processing of the Illumina Infinium MethylationEPIC BeadChip arrays according to the manufacturer’s protocol (Illumina, San Diego, CA, USA). Samples from the three cohorts were randomized and run in 3 array batches across 44 eight-sample chips as illustrated in Supp Figure 5. In the case of the V-SSRI and QF-2011 cohorts, sample exposure groups (SSRI exposed/non-exposed and objective flood stress high/low) and infant sex were carefully distributed across array chips (1-44) and rows (1-8) to minimize potential batch effects. DNAme data from raw IDAT files were read into R v4.2.2(54) and annotated with the Illumina Infinium MethylationEPIC v1.0 B4 Manifest. Several data quality control checks were undertaken using the R packages minfi(55,56), wateRmelon(57,58), and ewastools(59). First, each sample was assessed at 17 Illumina control probes to evaluate bisulfite conversion efficiency and array run quality; all samples passed the manufacturer-recommended thresholds at the control probes. Next, average total (methylated + unmethylated) fluorescence intensity was assessed between samples, and between array batches. All samples had similar total fluorescence, though samples run on the EPIC array in Batch 3 had slightly higher average intensities than those in Batch 1 and 2. Sample sex was assessed with the ewastools package(59), using the mean total fluorescence intensity (methylated + unmethylated) of the X and Y chromosome probes, normalized to the per-sample mean autosomal total fluorescence intensity, and was confirmed to match the clinically-reported sex of the infant in all cases. Sample genetic identity was assessed using the 59 SNP (‘rs’) probes on the EPIC array with the call_genotypes() and enumerate_sample_donors() functions (ewastools)(59). Finally, DNAme beta value density plots of all samples were visually assessed to determine overall similarity of the beta value distributions between samples, with no outliers identified.

Project description:2 normal lung parenchyma SAGE libraries, generated from 2 pools of 4 individuals each Discussed in the study: IDENTIFICATION OF NOVEL LUNG GENES IN BRONCHIAL EPITHELIUM BY SERIAL ANALYSIS OF GENE EXPRESSION Kim M. Lonergan1, Raj Chari1, Ronald J. deLeeuw1, Ashleen Shadeo1, Bryan Chi1, Ming-Sound Tsao2, Steven Jones3, Marco Marra3, Victor Ling1, Raymond Ng1,4, Calum MacAulay5, Stephen Lam5 and Wan L. Lam1 From the 1Department of Cancer Genetics & Developmental Biology, 5Department of Cancer Imaging, 3Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC, Canada, 2Ontario Cancer Institute / Princess Margaret Hospital, Toronto, ON, Canada, 4the Department of Computer Science, University of British Columbia, Vancouver, BC, Canada A description of the transcriptome of human bronchial epithelium should provide a basis for studying lung diseases including cancer. We demonstrate here that minute epithelial specimens obtained by bronchial brushings afford reliable profiling by serial analysis of gene expression (SAGE) leading to lung gene discovery. We have deduced global gene expression profiles of bronchial epithelium and lung parenchyma, based upon a vast data set of nearly two million sequence tags from 21 SAGE libraries generated from individuals with a history of smoking. Cluster and linear regression analysis demonstrate the repeatability and reproducibility of bronchial SAGE libraries, and suggest that the transcriptome of the bronchial epithelium is distinct from that of lung parenchyma and other tissue types. This distinction is highlighted by the abundant expression of signature genes that reflect tissue-specific and region-specific functions. Through our analysis we have identified novel bronchial-enriched genes and a novel transcript variant for surfactant, pulmonary-associated protein B in lung parenchyma. Conspicuously, gene expression associated with ciliogenesis is evident in bronchial epithelium. Additionally, it is noted that a large number of unmapped tags awaits further investigation. This study represents a comprehensive delineation of the bronchial and parenchyma transcriptomes, identifying more than 20,000 known and hypothetical genes expressed in the human lung, constituting one of the largest human SAGE studies reported to date. Keywords: lung parenchyma

Project description:19 bronchial epithelial SAGE libraries were constructed and analyzed in this study. Discussed in the study: IDENTIFICATION OF NOVEL LUNG GENES IN BRONCHIAL EPITHELIUM BY SERIAL ANALYSIS OF GENE EXPRESSION Kim M. Lonergan1, Raj Chari1, Ronald J. deLeeuw1, Ashleen Shadeo1, Bryan Chi1, Ming-Sound Tsao2, Steven Jones3, Marco Marra3, Victor Ling1, Raymond Ng1,4, Calum MacAulay5, Stephen Lam5 and Wan L. Lam1 From the 1Department of Cancer Genetics & Developmental Biology, 5Department of Cancer Imaging, 3Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC, Canada, 2Ontario Cancer Institute / Princess Margaret Hospital, Toronto, ON, Canada, 4the Department of Computer Science, University of British Columbia, Vancouver, BC, Canada A description of the transcriptome of human bronchial epithelium should provide a basis for studying lung diseases including cancer. We demonstrate here that minute epithelial specimens obtained by bronchial brushings afford reliable profiling by serial analysis of gene expression (SAGE) leading to lung gene discovery. We have deduced global gene expression profiles of bronchial epithelium and lung parenchyma, based upon a vast data set of nearly two million sequence tags from 21 SAGE libraries generated from individuals with a history of smoking. Cluster and linear regression analysis demonstrate the repeatability and reproducibility of bronchial SAGE libraries, and suggest that the transcriptome of the bronchial epithelium is distinct from that of lung parenchyma and other tissue types. This distinction is highlighted by the abundant expression of signature genes that reflect tissue-specific and region-specific functions. Through our analysis we have identified novel bronchial-enriched genes and a novel transcript variant for surfactant, pulmonary-associated protein B in lung parenchyma. Conspicuously, gene expression associated with ciliogenesis is evident in bronchial epithelium. Additionally, it is noted that a large number of unmapped tags awaits further investigation. This study represents a comprehensive delineation of the bronchial and parenchyma transcriptomes, identifying more than 20,000 known and hypothetical genes expressed in the human lung, constituting one of the largest human SAGE studies reported to date. Keywords: bronchial epithelium

Project description:19 bronchial epithelial SAGE libraries were constructed and analyzed in this study. Discussed in the study: IDENTIFICATION OF NOVEL LUNG GENES IN BRONCHIAL EPITHELIUM BY SERIAL ANALYSIS OF GENE EXPRESSION Kim M. Lonergan1, Raj Chari1, Ronald J. deLeeuw1, Ashleen Shadeo1, Bryan Chi1, Ming-Sound Tsao2, Steven Jones3, Marco Marra3, Victor Ling1, Raymond Ng1,4, Calum MacAulay5, Stephen Lam5 and Wan L. Lam1 From the 1Department of Cancer Genetics & Developmental Biology, 5Department of Cancer Imaging, 3Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC, Canada, 2Ontario Cancer Institute / Princess Margaret Hospital, Toronto, ON, Canada, 4the Department of Computer Science, University of British Columbia, Vancouver, BC, Canada A description of the transcriptome of human bronchial epithelium should provide a basis for studying lung diseases including cancer. We demonstrate here that minute epithelial specimens obtained by bronchial brushings afford reliable profiling by serial analysis of gene expression (SAGE) leading to lung gene discovery. We have deduced global gene expression profiles of bronchial epithelium and lung parenchyma, based upon a vast data set of nearly two million sequence tags from 21 SAGE libraries generated from individuals with a history of smoking. Cluster and linear regression analysis demonstrate the repeatability and reproducibility of bronchial SAGE libraries, and suggest that the transcriptome of the bronchial epithelium is distinct from that of lung parenchyma and other tissue types. This distinction is highlighted by the abundant expression of signature genes that reflect tissue-specific and region-specific functions. Through our analysis we have identified novel bronchial-enriched genes and a novel transcript variant for surfactant, pulmonary-associated protein B in lung parenchyma. Conspicuously, gene expression associated with ciliogenesis is evident in bronchial epithelium. Additionally, it is noted that a large number of unmapped tags awaits further investigation. This study represents a comprehensive delineation of the bronchial and parenchyma transcriptomes, identifying more than 20,000 known and hypothetical genes expressed in the human lung, constituting one of the largest human SAGE studies reported to date. Keywords: bronchial epithelium 19 bronchial epithelial SAGE libraries were constructed and analyzed in this study.

			Action	DRS
	ERR380526_1.fastq.gz	Fastqsanger.gz
	ERR380526_2.fastq.gz	Fastqsanger.gz
	ERR380527_1.fastq.gz	Fastqsanger.gz
	ERR380527_2.fastq.gz	Fastqsanger.gz
	ERR380528_1.fastq.gz	Fastqsanger.gz

Dataset Information

MRSA from rats and humans from Vancouver, BC, Canada

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets