Bgee: Integrating and Comparing Heterogeneous Transcriptome Data Among Species

Bastian, Frederic; Parmentier, Gilles; Roux, Julien; Moretti, Sébastien; Laudet, Vincent; Robinson‐Rechavi, Marc

doi:10.1007/978-3-540-69828-9_12

Cited by 177 publications

(182 citation statements)

References 27 publications

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“…Gene expression values and calls were downloaded from the Bgee database 71 . For each gene, we computed the number of adult tissues for human or developmental stage for zebrafish in 380 which a gene is called as expressed.…”

Section: Gene Expression Datamentioning

confidence: 99%

Enhancer-gene maps in the human and zebrafish genomes using evolutionary linkage conservation

Clément

Torbey

Gilardi-Hebenstreit

et al. 2018

Preprint

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Gene regulation by enhancer sequences controls the spatiotemporal expression of target genes, often over long genomic distances. Current methods used to identify these interactions in the human genome require complex experimental setups and are restricted to specific cell types. Here we use PEGASUS, an approach that captures evolutionary signals 5 of synteny conservation to predict such interaction potentially in any biological context. We apply it to the human and zebrafish genomes and exploit the 1.3 million human and 55,000 zebrafish enhancers that we predicted to uncover fundamental principles of gene enhancer function in vertebrates. We show that the number of enhancers linked to a gene positively correlates with expression breadth in space and time and that the enhancer-target distance 10 is evolutionarily neutral. We uncover almost 2000 regulatory interactions ancestral to vertebrates, which are strongly enriched in core developmental processes. Using PEGASUS and its evolutionary view of enhancer-gene interactions, we provide a highly complementary resource to functional assays which uncovers key principles of enhancer biology.

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Section: Gene Expression Datamentioning

confidence: 99%

Enhancer-gene maps in the human and zebrafish genomes using evolutionary linkage conservation

Clément

Torbey

Gilardi-Hebenstreit

et al. 2018

Preprint

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“…EST data were retrieved from Bgee release 7 (dataBase for Gene Expression Evolution, http://bgee.unil.ch/), a database comparing transcriptome data between species (Bastian et al 2008), including EST libraries from UniGene (Pontius et al 2003). The mapping of UniGene clusters on Ensembl genes is taken from Ensembl 57 (Hubbard et al 2009), where a percentage of identity of 90% is set as the minimum threshold to link an Ensembl gene with a UniGene cluster.…”

Section: Est Countsmentioning

confidence: 99%

Age-dependent gain of alternative splice forms and biased duplication explain the relation between splicing and duplication

Roux

Robinson‐Rechavi

2010

Genome Res.

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We analyze here the relation between alternative splicing and gene duplication in light of recent genomic data, with a focus on the human genome. We show that the previously reported negative correlation between level of alternative splicing and family size no longer holds true. We clarify this pattern and show that it is sufficiently explained by two factors. First, genes progressively gain new splice variants with time. The gain is consistent with a selectively relaxed regime, until purifying selection slows it down as aging genes accumulate a large number of variants. Second, we show that duplication does not lead to a loss of splice forms, but rather that genes with low levels of alternative splicing tend to duplicate more frequently. This leads us to reconsider the role of alternative splicing in duplicate retention.

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“…The creation of public repositories will certainly help this endeavour (see resources in [98]), especially when created with an explicit evo-devo approach in mind [99]. Undoubtedly, though, this will present new challenges in terms of data analysis and integration.…”

Section: Homology Assessment: Gene Expression and Regulatory Strategiesmentioning

confidence: 99%

Deep homology in the age of next-generation sequencing

Tschopp

Tabin

2017

Phil. Trans. R. Soc. B

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One contribution of 17 to a theme issue 'Evodevo in the genomics era, and the origins of morphological diversity'. The principle of homology is central to conceptualizing the comparative aspects of morphological evolution. The distinctions between homologous or non-homologous structures have become blurred, however, as modern evolutionary developmental biology (evo-devo) has shown that novel features often result from modification of pre-existing developmental modules, rather than arising completely de novo. With this realization in mind, the term 'deep homology' was coined, in recognition of the remarkably conserved gene expression during the development of certain animal structures that would not be considered homologous by previous strict definitions. At its core, it can help to formulate an understanding of deeper layers of ontogenetic conservation for anatomical features that lack any clear phylogenetic continuity. Here, we review deep homology and related concepts in the context of a gene expression-based homology discussion. We then focus on how these conceptual frameworks have profited from the recent rise of high-throughput nextgeneration sequencing. These techniques have greatly expanded the range of organisms amenable to such studies. Moreover, they helped to elevate the traditional gene-by-gene comparison to a transcriptome-wide level. We will end with an outlook on the next challenges in the field and how technological advances might provide exciting new strategies to tackle these questions.This article is part of the themed issue 'Evo-devo in the genomics era, and the origins of morphological diversity'.

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Bgee: Integrating and Comparing Heterogeneous Transcriptome Data Among Species

Cited by 177 publications

References 27 publications

Enhancer-gene maps in the human and zebrafish genomes using evolutionary linkage conservation

Enhancer-gene maps in the human and zebrafish genomes using evolutionary linkage conservation

Age-dependent gain of alternative splice forms and biased duplication explain the relation between splicing and duplication

Deep homology in the age of next-generation sequencing

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