Proposal: Number

PPM1-1122-150008

Program Cycle

: 

PPM 01

Submitting Institution Name

: 

Sidra Medicine

Project Status

: 

Award Tech. Completed

Start Date

: 

3/1/2017

Lead Investigator

: 

Dr. Younes Mokrab

Project Duration

: 

2 Year(s)

End Date

: 

19/02/2020

Submission Type

: 

New

Proposal Title

: 

Mapping the population transcriptome for the Pilot phase of the Qatar Genome Project: Towards elucidating the causal functional consequences of Qatari genetic variation

Proposal Description:

MOTIVATION : A major goal of human population genetics studies is to unveil polymorphisms in the human genome and understand how genotype influences phenotype in health and disease. Large-scale sequencing initiatives such as the HapMap, 1000 Genomes and lately national consortia have documented extensive genetic variation and linkage disequilibrium in various populations. However, our understanding of the origins, global distribution, and functional consequences of this variation is far from complete. So far, regulatory variation influencing gene expression has mostly been studied in small population sizes. In addition, the breadth of transcriptome is yet to be revealed on large scales mirroring the sequencing efforts. Furthermore, population-wide studies performed to date are limited in scope, with regions of Middle East and North Africa (MENA) region and Qatar remaining largely underexplored. OBJECTIVES : The Qatar Genome Project (QGP) has been launched recently with the aim of obtaining unprecedented population view of genetic variation in Qatar and the wider Arabian Peninsula. With this in hand, the next great challenge is to functionally characterize this vast landscape of polymorphism and understand its interplay with the molecular and clinical phenotypes at the population scale. Here, we propose to (a) Sequence the transcriptomes (messenger RNA and small RNA) from a primary human tissue (whole blood) for 2,000 individuals whose genomes are being elucidated, (b) Preform a systematic analysis to integrate the genotype and expression data and (c) Build the Integrated Qatar Genome Encyclopedia for Expression and Associated Variation Effects (iQGEN) web portal as a national resource for Qatar. This effort will add an important layer of knowledge to the QGP, creating the largest dataset and integrative analysis of transcriptomics for a single human population to date. Furthermore, it will be of unique value given that it will be uniformly generated and processed. This will be performed as multidisciplinary collaboration involving experienced teams from the divisions of Biomedical Informatics and Translational Medicine at Sidra Medical Research Center (SMRC). Notably, this will involve established researchers including Dr Ena Wang and Prof Xavier Estivill who has had a key role at the GEUVADIS Consortium (www.geuvadis.org), which systematically analyzed the genotypes and RNA profiles for individuals form the 1000 Genome Project. Our main objectives are: (1) Generate the RNA sequencing profiles from whole blood for 2,000 individuals from the QGP pilot phase cohort. This would provide a detailed reference map of the transcribed elements of the Qatar genome, (2) Analyze transcriptome variation amongst the Qatari population, the various genetically-distinct subpopulations identifiable in the cohort, as well as phenotype-based groups. This will identify sources of variations that can be attributed to genetic and environmental factors as well as outlier samples that need to be treated carefully in subsequent analyses. We will also use systems biology and machine learning approaches to build a network view of the collective Qatari genome with the goal of identifying signature pathways and genetic modules that are likely to be implicated in disease, (3) Perform a Quantitative Trait Loci (QTL) analysis on the transcriptome for appropriate samples to understand the transcriptional consequences of the different types of genetic variations (SNVs, Indels and CNVs) on various expression traits including gene expression (eQTL), alternative splicing (sQTL) and allelic expression (aseQTL). This will be the first QTL study to date to rely entirely on sequenced genotypes at full genome resolution, without using imputation. We will further replicate and validate the results to build a comprehensive repertoire of robust QTLs including those likely to represent causal effects. Phenotypic data on the subjects from QBB will be used to define appropriate normal/disease subcohorts for this objective, (4) Construct a web portal for the Integrated Qatar Genome Encyclopedia for Expression and Associated Variation Effects (iQGEN) that will give the research community interactive access to the transcriptomic data and QTLs produced in this study. This will be a national infrastructure based in SMRC providing high-throughput functional annotation of the Qatari genome as part of a Qatar Genome Browser and will serve as a reference set for further studies and building testable hypotheses about molecular phenotype, aetiology and biomarker discovery. SIGNIFICANCE : By generating extensive transcriptomics data and analyses, our project would help gain a more complete understanding of the landscape of human regulatory variation than previously possible. This will improve our interpretation of the genetics of gene expression and potential mechanisms of effect on higher-level traits. This project will have tangible and wide-reaching effects on human health in Qatar and worldwide by forming a substantial national resource expanding knowledge around the genotypic data from QGP pilot phase and greatly accelerating the process of identifying causal polymorphisms underlying diverse human traits and diseases. Therefore, the output from this work will be essential to the next phase of QGP – Functional genomics. It will benefit both basic and clinical researchers and will lay the foundation for further studies on populations in Qatar and MENA. In addition, in line with the PPM objectives, we will provide a training and development opportunity as part of this PPM project consisitng of applied internship in bioinformatics research, training in genomic data analysis and writing and communication skills for young scientists. This will target exceptional national undergraduate and graduate students from local biomedical/bioinformatics academic programs in Qatar.

Research Area Keywords:

Transcriptomics; whole genome sequencing; eQTLs; Qatar Genome Project; Genetic variation

Research Type

Basic Research