AmiGO: online access to ontology and annotation data

Carbon, Seth; Ireland, Amelia; Mungall, Christopher J.; Shu, Shengqiang; Marshall, Brad; Lewis, Suzanna

doi:10.1093/bioinformatics/btn615

Cited by 1,726 publications

(1,522 citation statements)

References 4 publications

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“…The search was restricted to “Aves” and had an e‐value cutoff of 10 −10 . We also associated gene ontology (GO) annotation terms to all outlier SNPs using the Gene Ontology database (Carbon et al., 2009; Gene Ontology Consortium 2000). Enrichment analyses to compare representation of GO terms between all loci and only outliers were not performed due to the low number of outlier loci annotated using BLAST (see Results).…”

Section: Methodsmentioning

confidence: 99%

Outlier analyses to test for local adaptation to breeding grounds in a migratory arctic seabird

Tigano

Shultz

Edwards

et al. 2017

Ecology and Evolution

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Investigating the extent (or the existence) of local adaptation is crucial to understanding how populations adapt. When experiments or fitness measurements are difficult or impossible to perform in natural populations, genomic techniques allow us to investigate local adaptation through the comparison of allele frequencies and outlier loci along environmental clines. The thick‐billed murre (Uria lomvia) is a highly philopatric colonial arctic seabird that occupies a significant environmental gradient, shows marked phenotypic differences among colonies, and has large effective population sizes. To test whether thick‐billed murres from five colonies along the eastern Canadian Arctic coast show genomic signatures of local adaptation to their breeding grounds, we analyzed geographic variation in genome‐wide markers mapped to a newly assembled thick‐billed murre reference genome. We used outlier analyses to detect loci putatively under selection, and clustering analyses to investigate patterns of differentiation based on 2220 genomewide single nucleotide polymorphisms (SNPs) and 137 outlier SNPs. We found no evidence of population structure among colonies using all loci but found population structure based on outliers only, where birds from the two northernmost colonies (Minarets and Prince Leopold) grouped with birds from the southernmost colony (Gannet), and birds from Coats and Akpatok were distinct from all other colonies. Although results from our analyses did not support local adaptation along the latitudinal cline of breeding colonies, outlier loci grouped birds from different colonies according to their non‐breeding distributions, suggesting that outliers may be informative about adaptation and/or demographic connectivity associated with their migration patterns or nonbreeding grounds.

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Section: Methodsmentioning

confidence: 99%

Outlier analyses to test for local adaptation to breeding grounds in a migratory arctic seabird

Tigano

Shultz

Edwards

et al. 2017

Ecology and Evolution

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“…PANTHER was used to classify genes and proteins by biological processes [24]. Gene ontology (GO) enrichment analysis was performed by AmiGO [25] (full details of these analyses are described in ESM Methods). To identify altered pathways, genes/proteins that were differentially expressed or interacted in a network were loaded into the IPA software and database (Ingenuity Systems, www.…”

Section: Methodsmentioning

confidence: 99%

Early differences in islets from prediabetic NOD mice: combined microarray and proteomic analysis

et al. 2017

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Aims/hypothesis Type 1 diabetes is an endocrine disease where a long preclinical phase, characterised by immune cell infiltration in the islets of Langerhans, precedes elevated blood glucose levels and disease onset. Although several studies have investigated the role of the immune system in this process of insulitis, the importance of the beta cells themselves in the initiation of type 1 diabetes is less well understood. The aim of this study was to investigate intrinsic differences present in the islets from diabetes-prone NOD mice before the onset of insulitis. Methods The islet transcriptome and proteome of 2-3-week-old mice was investigated by microarray and 2-dimensional difference gel electrophoresis (2D-DIGE), respectively. Subsequent analyses using sophisticated pathway analysis and ranking of differentially expressed genes and proteins based on their relevance in type 1 diabetes were performed. Results In the preinsulitic period, alterations in general pathways related to metabolism and cell communication were already present. Additionally, our analyses pointed to an important role for post-translational modifications (PTMs), especially citrullination by PAD2 and protein misfolding due to low expression levels of protein disulphide isomerases (PDIA3, 4 and 6), as causative mechanisms that induce beta cell stress and potential auto-antigen generation. Conclusions/interpretation We conclude that the pancreatic islets, irrespective of immune differences, may contribute to the initiation of the autoimmune process. Data availability All microarray data are available in the ArrayExpress database (www.ebi.ac.uk/arrayexpress) under accession number E-MTAB-5264.

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“…Functional annotations were collected from (i) the ConsensusPath DB database (http://consensuspathdb.org; Kamburov et al , 2013), (ii) the Ami GO 2 Gene Ontology ( GO ) browser (http://amigo.geneontology.org/amigo; Carbon et al , 2009), as well from (iii) the biomedical literature. Known and predicted associations among the genes within each functional category/pathway were retrieved from the STRING database (http://string-db.org; Franceschini et al , 2013) using default parameters.…”

Section: Pathophysiological Insightsmentioning

confidence: 99%

The impact of genome‐wide association studies on the pathophysiology and therapy of cardiovascular disease

2016

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Cardiovascular diseases are leading causes for death worldwide. Genetic disposition jointly with traditional risk factors precipitates their manifestation. Whereas the implications of a positive family history for individual risk have been known for a long time, only in the past few years have genome‐wide association studies (GWAS) shed light on the underlying genetic variations. Here, we review these studies designed to increase our understanding of the pathophysiology of cardiovascular diseases, particularly coronary artery disease and myocardial infarction. We focus on the newly established pathways to exemplify the translation from the identification of risk‐related genetic variants to new preventive and therapeutic strategies for cardiovascular disease.

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AmiGO: online access to ontology and annotation data

Cited by 1,726 publications

References 4 publications

Outlier analyses to test for local adaptation to breeding grounds in a migratory arctic seabird

Outlier analyses to test for local adaptation to breeding grounds in a migratory arctic seabird

Early differences in islets from prediabetic NOD mice: combined microarray and proteomic analysis

The impact of genome‐wide association studies on the pathophysiology and therapy of cardiovascular disease

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