ArticleBMC genomics2007
Cross-species analysis of gene expression in non-model mammals: reproducibility of hybridization on high density oligonucleotide microarrays.
Article in BMC genomics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 25 citations in OpenAlex.
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- Transcript profiling of common bean (Phaseolus vulgaris L.) using the GeneChip Soybean Genome Array: optimizing analysis by masking biased probes.BMC plant biology · 2010Article
- General and species-specific transcriptional responses to downy mildew infection in a susceptible (Vitis vinifera) and a resistant (V. riparia) grapevine species.BMC genomics · 2010Article
- A Method to Detect Differential Gene expression in Cross-Species Hybridization Experiments at Gene and Probe Level.Biomedical informatics insights · 2010Article
- Identification of genes related to the development of bamboo rhizome bud.Journal of experimental botany · 2010Article
- Genome-wide screen for temperature-regulated genes of the obligate intracellular bacterium, Rickettsia typhi.BMC microbiology · 2008Article
- The Songbird Neurogenomics (SoNG) Initiative: community-based tools and strategies for study of brain gene function and evolution.BMC genomics · 2008Article
- Detection and validation of single feature polymorphisms in cowpea (Vigna unguiculata L. Walp) using a soybean genome array.BMC genomics · 2008Article
- Preferential gene expression in the limbus of the vervet monkey.Molecular vision · 2008Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene expression profiles of non-model mammals may provide valuable data for biomedical and evolutionary studies. However, due to lack of sequence information of other species, DNA microarrays are currently restricted to humans and a few model species. This limitation may be overcome by using arrays developed for a given species to analyse gene expression in a related one, an approach known as "cross-species analysis". In spite of its potential usefulness, the accuracy and reproducibility of the gene expression measures obtained in this way are still open to doubt. The present study examines whether or not hybridization values from cross-species analyses are as reproducible as those from same-species analyses when using Affymetrix oligonucleotide microarrays.
resultsThe reproducibility of the probe data obtained hybridizing deer, Old-World primates, and human RNA samples to Affymetrix human GeneChip U133 Plus 2.0 was compared. The results show that cross-species hybridization affected neither the distribution of the hybridization reproducibility among different categories, nor the reproducibility values of the individual probes. Our analyses also show that a 0.5% of the probes analysed in the U133 plus 2.0 GeneChip are significantly associated to un-reproducible hybridizations. Such probes-called in the text un-reproducible probe sequences- do not increase in number in cross-species analyses.
conclusionOur study demonstrates that cross-species analyses do not significantly affect hybridization reproducibility of GeneChips, at least within the range of the mammal species analysed here. The differences in reproducibility between same-species and cross-species analyses observed in previous studies were probably caused by the analytical methods used to calculate the gene expression measures. Together with previous observations on the accuracy of GeneChips for cross-species analysis, our analyses demonstrate that cross-species hybridizations may provide useful gene expression data. However, the reproducibility and accuracy of these measures largely depends on the use of appropriated algorithms to derive the gene expression data from the probe data. Also, the identification of probes associated to un-reproducible hybridizations-useless for gene expression analyses- in the studied GeneChip, stress the need of a re-evaluation of the probes' performance.
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