Dataset Information

Proteome and genome integration analysis of obesity.

ABSTRACT:

Abstract

The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variant-obesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.

SUBMITTER: Zhao Q

PROVIDER: S-EPMC10278747 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Publications

Proteome and genome integration analysis of obesity.

Zhao Qigang Q Han Baixue B Xu Qian Q Wang Tao T Fang Chen C Li Rui R Zhang Lei L Pei Yufang Y

Chinese medical journal 20230331 8

<h4>Abstract</h4>The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challeng ...[more]

PMID: 37000968

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Project description:BackgroundIn Europe, Ixodes ricinus ticks are the most important vectors of diseases threatening humans, livestock, wildlife and companion animals. Nevertheless, genomic sequence information is missing and functional annotation of transcripts and proteins is limited. This lack of information is restricting studies of the vector and its interactions with pathogens and hosts. Here we present and integrate the first analysis of the I. ricinus genome with the transcriptome and proteome of the unfed I. ricinus midgut.MethodsWhole genome sequencing was performed on I. ricinus ticks and the sequences were de novo assembled. In parallel, I. ricinus ticks were dissected and the midgut transcriptome sequenced. Both datasets were integrated by transcript discovery analysis to identify putative genes and genome contigs were screened for homology. An alignment-based and a motif-search-based approach were combined for the annotation of the midgut transcriptome. Additionally, midgut proteins were identified and annotated by mass spectrometry with public databases and the in-house built transcriptome database as references and results were cross-validated.ResultsThe de novo assembly of 1 billion DNA sequences to a reference genome of 393 Mb length provides an unprecedented insight into the I. ricinus genome. A homology search revealed sequences in the assembled genome contigs homologous to 89% of the I. scapularis genome scaffolds indicating coverage of most genome regions. We identified moreover 6,415 putative genes. More than 10,000 transcripts from naïve midgut were annotated with respect of predicted function and/or cellular localization. By combining an alignment-based with a motif-search-based annotation approach, we doubled the number of annotations throughout all functional categories. In addition, 574 gel spots were significantly identified by mass spectrometry (p<0.05) and 285 distinct proteins expressed in the naïve midgut were annotated functionally and/or for cellular localization. Our systems approach reveals a midgut metabolism of the unfed tick that is prepared to sense and process an anticipated blood meal.ConclusionsThis multiple-omics study vastly extends the publicly available DNA and RNA databases for I. ricinus, paving the way for further in-depth analysis of the most important European disease vector and its interactions with pathogens and hosts.

Dataset Information

Proteome and genome integration analysis of obesity.

Abstract

Publications

Proteome and genome integration analysis of obesity.

Similar Datasets

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