Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

A novel aCGH method for non-model organisms for assessing genomes and de-novo transcriptome sequencing reads (Danio rerio)

ABSTRACT: Genomes and transcriptomes of non-model organisms can be analyzed using next-generation sequencing technologies, but de-novo sequencing and annotating a full eukaryotic genome is still challenging. So, -omics experimentation with non-model organisms requires a suite of technologies to obtain reliable results in a cost-effective manner. Here, a novel method for microarray-based genome analysis is presented which is especially suitable for non-model organisms. We show that it is useful for complementing regular aCGH analyses and for evaluating transcriptome next-generation sequencing reads. The principle of the method is straightforward: feature intensities obtained after hybridizing the test genome are compared with the feature intensities of a control hybridization. The control hybridization is performed with negative control probes (no targets in the control sample), and with positive control probes (with targets in the control sample). The method has in principle a resolution of a single probe and it does not depend on the structural information of a reference genome: the genomic ordering of probe targets is irrelevant. In a test, analyzing the genome content of a sequenced bacterial strain: Staphylococcus aureus MRSA252, this approach proved to be successful demonstrated by receiver operating characteristic area under the curve values larger than 0.9995. DNA from twelve Danio rerio individuals was extracted, fragmented, and hybridized onto the D. rerio microarray. DNA from the pool was used as common reference, but this channel was omitted in further analyses.

ORGANISM(S): Danio rerio

SUBMITTER: Paul Wackers

PROVIDER: E-GEOD-52121 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Absence/presence calling in microarray-based CGH experiments with non-model organisms.

Jonker Martijs J MJ de Leeuw Wim C WC Marinković Marino M Wittink Floyd R A FR Rauwerda Han H Bruning Oskar O Ensink Wim A WA Fluit Ad C AC Boel C H CH Jong Mark de Md Breit Timo M TM

Nucleic acids research 20140425 11

Structural variations in genomes are commonly studied by (micro)array-based comparative genomic hybridization. The data analysis methods to infer copy number variation in model organisms (human, mouse) are established. In principle, the procedures are based on signal ratios between test and reference samples and the order of the probe targets in the genome. These procedures are less applicable to experiments with non-model organisms, which frequently comprise non-sequenced genomes with an unknow ...[more]

PMID: 24771343

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Project description:Cellular stress responses are frequently presumed to be more sensitive than traditional ecotoxicological life cycle endpoints such as survival and growth. Yet, the focus to reduce test duration and to generate more sensitive endpoints has caused transcriptomics studies to be performed at low doses during short exposures, separately and independently from traditional ecotoxicity tests, making comparisons with life cycle endpoints indirect. Therefore we aimed to directly compare the effects on growth, survival and gene expression of the non-biting midge Chironomus riparius. To this purpose, we analyzed simultaneously life cycle and transcriptomics responses of chironomid larvae exposed to four model toxicants. We observed that already at the lowest test concentrations many transcripts were significantly differentially expressed, while the life cycle endpoints of C. riparius were hardly affected. Analysis of the differentially expressed transcripts showed that at the lowest test concentrations substantial and biologically relevant cellular stress was induced and that many transcripts responded already maximally at these lowest test concentrations. The direct comparison between molecular en life cycle responses after fourteen days of exposure revealed that gene expression is more sensitive to toxicant exposure than life cycle endpoints, underlining the potential of transcriptomics for ecotoxicity testing and environmental risk assessment. Cellular stress responses are frequently presumed to be more sensitive than traditional ecotoxicological life cycle endpoints such as survival and growth. Yet, the focus to reduce test duration and to generate more sensitive endpoints has caused transcriptomics studies to be performed at low doses during short exposures, separately and independently from traditional ecotoxicity tests, making comparisons with life cycle endpoints indirect. Therefore we aimed to directly compare the effects on growth, survival and gene expression of the non-biting midge Chironomus riparius. To this purpose, we analyzed simultaneously life cycle and transcriptomics responses of chironomid larvae exposed to four model toxicants. We observed that already at the lowest test concentrations many transcripts were significantly differentially expressed, while the life cycle endpoints of C. riparius were hardly affected. Analysis of the differentially expressed transcripts showed that at the lowest test concentrations substantial and biologically relevant cellular stress was induced and that many transcripts responded already maximally at these lowest test concentrations. The direct comparison between molecular en life cycle responses after fourteen days of exposure revealed that gene expression is more sensitive to toxicant exposure than life cycle endpoints, underlining the potential of transcriptomics for ecotoxicity testing and environmental risk assessment. Four 14-day Chironomus riparius sediment toxicity tests were conducted, one with each toxicant. The surviving larvae were individually flash frozen in liquid nitrogen. For each toxicant we analyzed the gene expression of larvae exposed to low, intermediate and high concentrations. We also included a control and a solvent control. For each treatment we analyzed 10 replicates (individual larvae).

Dataset Information

A novel aCGH method for non-model organisms for assessing genomes and de-novo transcriptome sequencing reads (Danio rerio)

Publications

Absence/presence calling in microarray-based CGH experiments with non-model organisms.

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