Gene sequence signatures revealed by mining the UniGene affiliation network

Zhang, Jiexin; Zhang, Li; Coombes, Kevin R.

doi:10.1093/bioinformatics/bti796

Cited by 6 publications

(5 citation statements)

References 29 publications

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“…Given that 10 to 20% of EST sequences in UniGene were annotated in the wrong direction [46], reliable in silico screenings must be based on stringent parameters which could underestimate or exclude some genuine antisense transcripts. Nevertheless, we proceeded to experimentally validate our bioinformatics results by performing 5′ RACE experiments on total RNA isolated from the MA-10 Leydig tumor cell line.…”

Section: Resultsmentioning

confidence: 99%

Hormone-Dependent Expression of a Steroidogenic Acute Regulatory Protein Natural Antisense Transcript in MA-10 Mouse Tumor Leydig Cells

et al. 2011

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Cholesterol transport is essential for many physiological processes, including steroidogenesis. In steroidogenic cells hormone-induced cholesterol transport is controlled by a protein complex that includes steroidogenic acute regulatory protein (StAR). Star is expressed as 3.5-, 2.8-, and 1.6-kb transcripts that differ only in their 3′-untranslated regions. Because these transcripts share the same promoter, mRNA stability may be involved in their differential regulation and expression. Recently, the identification of natural antisense transcripts (NATs) has added another level of regulation to eukaryotic gene expression. Here we identified a new NAT that is complementary to the spliced Star mRNA sequence. Using 5′ and 3′ RACE, strand-specific RT-PCR, and ribonuclease protection assays, we demonstrated that Star NAT is expressed in MA-10 Leydig cells and steroidogenic murine tissues. Furthermore, we established that human chorionic gonadotropin stimulates Star NAT expression via cAMP. Our results show that sense-antisense Star RNAs may be coordinately regulated since they are co-expressed in MA-10 cells. Overexpression of Star NAT had a differential effect on the expression of the different Star sense transcripts following cAMP stimulation. Meanwhile, the levels of StAR protein and progesterone production were downregulated in the presence of Star NAT. Our data identify antisense transcription as an additional mechanism involved in the regulation of steroid biosynthesis.

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Section: Resultsmentioning

confidence: 99%

Hormone-Dependent Expression of a Steroidogenic Acute Regulatory Protein Natural Antisense Transcript in MA-10 Mouse Tumor Leydig Cells

et al. 2011

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“…The ontology term enrichment problem is not restricted to differential gene expression analysis or to microarray derived data. The current models, including the one implemented in BayGO, are capable of analysing the enrichment relative to other dichotomous properties such as "belonging to a particular gene cluster" vs. "not belonging", in clustering analysis [ 24 ]; "it is expressed (ON)" vs. "it is not expressed (OFF)", in gene transcription analysis; "narrowly expressed transcripts" vs. "prevalently expressed transcripts" [ 36 ]; and so on.…”

Section: Resultsmentioning

confidence: 99%

BayGO: Bayesian analysis of ontology term enrichment in microarray data

et al. 2006

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Background: The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a systemlevel analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem.

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“…In summary, while many recent scans of positive selection have resulted in extensive lists of candidate regions (Kelley et al, 2006; Voight et al, 2006; Wang et al, 2006; Zhang et al, 2006; Kimura et al, 2007; Sabeti et al, 2007; Tang et al, 2007), very little follow-up analysis has been reported. Here, we have focused on a region of chromosome 2p13 that contains three independent substrates of recent positive selection, and we have shown that additional clusters of independent selective events likely exist in the human genome.…”

Section: Discussionmentioning

confidence: 99%

Clusters of adaptive evolution in the human genome

et al. 2011

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Considerable work has been devoted to identifying regions of the human genome that have been subjected to recent positive selection. Although detailed follow-up studies of putatively selected regions are critical for a deeper understanding of human evolutionary history, such studies have received comparably less attention. Recently, we have shown that ALMS1 has been the target of recent positive selection acting on standing variation in Eurasian populations. Here, we describe a careful follow-up analysis of genetic variation across the ALMS1 region, which unexpectedly revealed a cluster of substrates of positive selection. Specifically, through the analysis of SNP data from the HapMap and Human Genome Diversity Project–Centre d’Etude du Polymorphisme Humain samples as well sequence data from the region, we find compelling evidence for three independent and distinct signals of recent positive selection across this 3 Mb region surrounding ALMS1. Moreover, we analyzed the HapMap data to identify other putative clusters of independent selective events and conservatively discovered 19 additional clusters of adaptive evolution. This work has important implications for the interpretation of genome-scans for positive selection in humans and more broadly contributes to a better understanding of how recent positive selection has shaped genetic variation across the human genome.

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Gene sequence signatures revealed by mining the UniGene affiliation network

Cited by 6 publications

References 29 publications

Hormone-Dependent Expression of a Steroidogenic Acute Regulatory Protein Natural Antisense Transcript in MA-10 Mouse Tumor Leydig Cells

Hormone-Dependent Expression of a Steroidogenic Acute Regulatory Protein Natural Antisense Transcript in MA-10 Mouse Tumor Leydig Cells

BayGO: Bayesian analysis of ontology term enrichment in microarray data

Clusters of adaptive evolution in the human genome

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