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Identifying reference genes with stable expression from high throughput sequence data.

ABSTRACT: Genes that are constitutively expressed across multiple environmental stimuli are crucial to quantifying differentially expressed genes, particularly when employing quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) assays. However, the identification of these potential reference genes in non-model organisms is challenging and is often guided by expression patterns in distantly related organisms. Here, transcriptome datasets from the diatom Thalassiosira pseudonana grown under replete, phosphorus-limited, iron-limited, and phosphorus and iron co-limited nutrient regimes were analyzed through literature-based searches for homologous reference genes, k-means clustering, and analysis of sequence counts (ASC) to identify putative reference genes. A total of 9759 genes were identified and screened for stable expression. Literature-based searches surveyed 18 generally accepted reference genes, revealing 101 homologs in T. pseudonana with variable expression and a wide range of mean tags per million. k-means analysis parsed the whole transcriptome into 15 clusters. The two most stable clusters contained 709 genes, but still had distinct patterns in expression. ASC analyses identified 179 genes that were stably expressed (posterior probability < 0.1 for 1.25 fold change). Genes known to have a stable expression pattern across the test treatments, like actin, were identified in this pool of 179 candidate genes. ASC can be employed on data without biological replicates and was more robust than the k-means approach in isolating genes with stable expression. The intersection of the genes identified through ASC with commonly used reference genes from the literature suggests that actin and ubiquitin ligase may be useful reference genes for T. pseudonana and potentially other diatoms. With the wealth of transcriptome sequence data becoming available, ASC can be easily applied to transcriptome datasets from other phytoplankton to identify reference genes.

SUBMITTER: Alexander H

PROVIDER: S-EPMC3494082 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Identifying reference genes with stable expression from high throughput sequence data.

Alexander Harriet H Jenkins Bethany D BD Rynearson Tatiana A TA Saito Mak A MA Mercier Melissa L ML Dyhrman Sonya T ST

Frontiers in microbiology 20121109

Genes that are constitutively expressed across multiple environmental stimuli are crucial to quantifying differentially expressed genes, particularly when employing quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) assays. However, the identification of these potential reference genes in non-model organisms is challenging and is often guided by expression patterns in distantly related organisms. Here, transcriptome datasets from the diatom Thalassiosira pseudonana grown unde ...[more]

PMID: 23162540

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Project description:Genes that are constitutively expressed across multiple environmental stimuli are crucial to quantifying differentially expressed genes, particularly when employing quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) assays. However, the identification of these potential reference genes in non-model organisms is challenging and is often guided by expression patterns in distantly related organisms. Here, transcriptome datasets from the diatom Thalassiosira pseudonana grown under replete, phosphorus-limited, iron-limited, and phosphorus and iron co-limited nutrient regimes were analyzed through literature-based searches for homologous reference genes, k-means clustering, and Analysis of Sequence Counts (ASC) to identify putative reference genes. A total of 9759 genes were identified and screened for stable expression. Literature-based searches surveyed 18 generally accepted reference genes, revealing 101 homologs in T. pseudonana with variable expression and a wide range of mean tags per million. K-means analysis parsed the whole transcriptome into 15 clusters. The two most stable clusters contained 709 genes but still had distinct patterns in expression. ASC analyses identified 179 genes that were stably expressed (posterior probability < 0.1 for 1.25 fold change). Genes known to have a stable expression pattern across the test treatments, like actin, were identified in this pool of 179 candidate genes. ASC can be employed on data without biological replicates and was more robust than the k-means approach in isolating genes with stable expression. The intersection of the genes identified through ASC with commonly used reference genes from the literature suggests that actin and ubiquitin ligase may be useful reference genes for T. pseudonana and potentially other diatoms. With the wealth of transcriptome sequence data becoming available, ASC can be easily applied to transcriptome datasets from other phytoplankton to identify reference genes. Axenic T. pseudonana CCMP 1335 was grown at 14Â°C under 24 hour light (120 Âµmol photons m-2 s-1) after Dyhrman et al. (2012) in f/2 plus silica chelated media made from surface Sargasso Sea water. Nitrate, silica, vitamins, and trace metals were at f/2 concentrations (Guillard and Ryther 1962), while iron and phosphate were modified across treatments. In brief, triplicate cultures of replete (36 ÂµM PO4, 400 nM Fe), P-limited (0.4 ÂµM PO4, 400 nM Fe), Fe-limited (36 ÂµM PO4, 40 nM Fe), and Co-limited (0.4 ÂµM PO4, 40 nM Fe) treatments were harvested when growth deviated from the replete control. Growth was monitored by cell counts. Biomass was harvested onto 0.2 Âµm filters and flash frozen in liquid nitrogen and total RNA was extracted as described in Dyhrman et al. (2012). Tag-seq sequencing of the transcriptome was performed by Illumina with a polyA selection and NlaIII digestion, resulting in 21 bp sequence reads or tags (Dyhrman et al., 2012). Libraries were of varied sizes as follows: replete (~12 million), P-limited (~13 million), Fe-limited (~23 million), and Co-limited (~26 million). Tags were mapped to gene models (predicted protein coding regions) with a pipeline designed by Genesifter Inc., requiring 100% identity and covering 9759 genes. Tag counts within a gene were pooled and normalized to the size of the library, with resulting data expressed in tags per million (tpm). Genes with normalized tag counts less than 2.5 tpm for each of the four treatments were excluded (Figure S1) , leaving 7380 genes in the analysis.

Project description:Quantitative Reverse Transcription PCR (qRT-PCR) is currently one of the most popular, high-throughput and sensitive technologies available for quantifying gene expression. Its accurate application depends heavily upon normalisation of gene-of-interest data with reference genes that are uniformly expressed under experimental conditions. The aim of this study was to provide the first validation of reference genes for Lupinus angustifolius (narrow-leafed lupin, a significant grain legume crop) using a selection of seven genes previously trialed as reference genes for the model legume, Medicago truncatula. In a preliminary evaluation, the seven candidate reference genes were assessed on the basis of primer specificity for their respective targeted region, PCR amplification efficiency, and ability to discriminate between cDNA and gDNA. Following this assessment, expression of the three most promising candidates [Ubiquitin C (UBC), Helicase (HEL), and Polypyrimidine tract-binding protein (PTB)] was evaluated using the NormFinder and RefFinder statistical algorithms in two narrow-leafed lupin lines, both with and without vernalisation treatment, and across seven organ types (cotyledons, stem, leaves, shoot apical meristem, flowers, pods and roots) encompassing three developmental stages. UBC was consistently identified as the most stable candidate and has sufficiently uniform expression that it may be used as a sole reference gene under the experimental conditions tested here. However, as organ type and developmental stage were associated with greater variability in relative expression, it is recommended using UBC and HEL as a pair to achieve optimal normalisation. These results highlight the importance of rigorously assessing candidate reference genes for each species across a diverse range of organs and developmental stages. With emerging technologies, such as RNAseq, and the completion of valuable transcriptome data sets, it is possible that other potentially more suitable reference genes will be identified for this species in future.

Dataset Information

Identifying reference genes with stable expression from high throughput sequence data.

Publications

Identifying reference genes with stable expression from high throughput sequence data.

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