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Quantifying expression divergence of duplicated genes with microarrays

Koen Van den Berge (UGent) , Riet De Smet (UGent) , Yves Van de Peer (UGent) and Lieven Clement (UGent)
(2015) Belgian Statistical Society, 23rd Annual meeting, Abstracts.
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Abstract
Whole genome duplication (WGD) events are widespread among flowering plants. They result in two redundant genomes within the individual. Most duplicated genes derived from a WGD event (i.e. homeologous genes) will get lost during evolution. Nonetheless, they provide raw material for the evolution of genes with novel functions. Expression divergence is often used to assess the contribution of WGD in this respect. Microarray technology can be used for this purpose. With microarrays, the expression of a gene is measured by multiple 'probes', i.e. a probeset. Quantifying expression divergence involves differential expression analysis between two distinct genes, which is challenging as it involves different probesets, each having different characteristics. We show that standard analysis methods adopted in the evolutionary genomics literature typically lead to an excess of false positives, explaining the high number of reported significantly diverged genes. We propose a novel data analysis strategy to account for these probe effects. An empirical null distribution is established by adopting a test statistic on probes within a probeset. This null distribution can be incorporated in a local fdr estimate for every gene pair, which rigorously defines significant expression divergence. We illustrate our method in a case study on Arabidopsis thaliana.

Citation

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MLA
Van den Berge, Koen, et al. “Quantifying Expression Divergence of Duplicated Genes with Microarrays.” Belgian Statistical Society, 23rd Annual Meeting, Abstracts, 2015.
APA
Van den Berge, K., De Smet, R., Van de Peer, Y., & Clement, L. (2015). Quantifying expression divergence of duplicated genes with microarrays. Belgian Statistical Society, 23rd Annual Meeting, Abstracts. Presented at the 23rd Annual meeting of the Belgian Statistical Society, Antwerp, Belgium.
Chicago author-date
Van den Berge, Koen, Riet De Smet, Yves Van de Peer, and Lieven Clement. 2015. “Quantifying Expression Divergence of Duplicated Genes with Microarrays.” In Belgian Statistical Society, 23rd Annual Meeting, Abstracts.
Chicago author-date (all authors)
Van den Berge, Koen, Riet De Smet, Yves Van de Peer, and Lieven Clement. 2015. “Quantifying Expression Divergence of Duplicated Genes with Microarrays.” In Belgian Statistical Society, 23rd Annual Meeting, Abstracts.
Vancouver
1.
Van den Berge K, De Smet R, Van de Peer Y, Clement L. Quantifying expression divergence of duplicated genes with microarrays. In: Belgian Statistical Society, 23rd Annual meeting, Abstracts. 2015.
IEEE
[1]
K. Van den Berge, R. De Smet, Y. Van de Peer, and L. Clement, “Quantifying expression divergence of duplicated genes with microarrays,” in Belgian Statistical Society, 23rd Annual meeting, Abstracts, Antwerp, Belgium, 2015.
@inproceedings{6963697,
  abstract     = {{Whole genome duplication (WGD) events are widespread among flowering plants. They result in two redundant genomes within the individual. Most duplicated genes derived from a WGD event (i.e. homeologous genes) will get lost during evolution. Nonetheless, they provide raw material for the evolution of genes with novel functions. Expression divergence is often used to assess the contribution of WGD in this respect.
Microarray technology can be used for this purpose. With microarrays, the expression of a gene is measured by multiple 'probes', i.e. a probeset. Quantifying expression divergence involves differential expression analysis between two distinct genes,  which is challenging as it involves different probesets, each having different characteristics. We show that standard analysis methods adopted in the evolutionary genomics literature typically lead to an excess of false positives, explaining the high number of reported significantly diverged genes.
We propose a novel data analysis strategy to account for these probe effects. An empirical null distribution is established by adopting a test statistic on probes within a probeset. This null distribution can be incorporated in a local fdr estimate for every gene pair, which rigorously defines significant expression divergence. We illustrate our method in a case study on Arabidopsis thaliana.}},
  author       = {{Van den Berge, Koen and De Smet, Riet and Van de Peer, Yves and Clement, Lieven}},
  booktitle    = {{Belgian Statistical Society, 23rd Annual meeting, Abstracts}},
  language     = {{eng}},
  location     = {{Antwerp, Belgium}},
  title        = {{Quantifying expression divergence of duplicated genes with microarrays}},
  year         = {{2015}},
}