Difference between revisions of "Identification of obesity and BMI associated intergenic long noncoding RNAs"

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'''Tools:''' To identify BMI/obesity associated lincRNAs, we will take advantage of publicly available RNA sequencing (RNAseq) data of lymphoblastoid cell lines (LCLs) from 373 individuals of European descent (Lappalainen et al. 2013). We will test the correlations between BMI/obesity associated variants and the expression levels of lincRNAs in their genomic vicinity. This project will involve RNA sequencing processing and genotype data manipulation and it will cover correlation and multiple testing correction calculations.
 
'''Tools:''' To identify BMI/obesity associated lincRNAs, we will take advantage of publicly available RNA sequencing (RNAseq) data of lymphoblastoid cell lines (LCLs) from 373 individuals of European descent (Lappalainen et al. 2013). We will test the correlations between BMI/obesity associated variants and the expression levels of lincRNAs in their genomic vicinity. This project will involve RNA sequencing processing and genotype data manipulation and it will cover correlation and multiple testing correction calculations.
  
'''Supervisors:''' [[User: Jennifer|Jennifer Tan]] and [[User: Ana|Ana Claudia Machado Rebelo Marques]]
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'''Supervisors:''' [[User: JenniferTan|Jennifer Tan]] and [[User: AnaMarques|Ana Claudia Machado Rebelo Marques]]

Revision as of 10:31, 18 February 2015

Background The number of long (>200 nucleotides) intergenic transcripts lacking protein coding potential, termed lincRNAs, identified in the human genome is at least 3 times higher than the number of protein-coding genes. To date, less than 0.5% of lincRNAs in the human genome have an established biological function. The experimental characterization of this handful of lincRNAs revealed they contribute at all levels of gene expression regulation, modulating transcriptionally or post-transcriptionally the levels of genomically adjacent or distally located gene products (reviewed in Kung et al., 2013). However, with the functional roles of the vast majority of lincRNAs being largely unknown, approaches allowing the prioritization of interesting candidates for experimental validation are needed if we are to understand the biological relevance of the extensive lincRNA transcription in eukaryote genomes.

Goal: The aim of this project is to identify lincRNAs whose expression is correlated with genetic variants recently linked to obesity and BMI through genome-wide association studies (Manolio, 2010). Such lincRNAs would be excellent candidates for future validation and functional characterization studies.

Tools: To identify BMI/obesity associated lincRNAs, we will take advantage of publicly available RNA sequencing (RNAseq) data of lymphoblastoid cell lines (LCLs) from 373 individuals of European descent (Lappalainen et al. 2013). We will test the correlations between BMI/obesity associated variants and the expression levels of lincRNAs in their genomic vicinity. This project will involve RNA sequencing processing and genotype data manipulation and it will cover correlation and multiple testing correction calculations.

Supervisors: Jennifer Tan and Ana Claudia Machado Rebelo Marques