Zhou Lab
of
Population Genomics and Multi-Omics

Genetically supported multi-omics biomarkers for drug discovery

• We will identify causal circulating proteins and metabolites for diseases, using genetic epidemiological methods including Mendelian randomization (MR), statistical colocalization and PRS.


• We will explore and develop novel statistical methods for MR and colocalization that incorporates the evidence of pQTL/sQTL/eQTL and mQTL/sQTL/eQTL.

Ancestry specific proteogenomic signatures of complex diseases and traits

• We will perform multi-ancestry proteomics GWAS, identify ancestry specific pQTLs, generate protein polygenic risk scores (PRS) and assess the role of rare coding variants for protein quantity
• We will develop frameworks combining population genetics and post-GWAS methods mapping evolutionary important regions → population specific variants → gene → protein → pathways → disease

Neurological manifestations of post-acute sequelae SARS-CoV-2 infection (PASC)

• A high percentage of people with COVID-19 reported PASC, among PASC symptoms, long term neurological manifestations are the most impactful, with the most severe effects in cognition, memory problems and Alzheimer’s disease.
• Supported by large genomics and multi-omics datasets from BQC19 (Banque québécoise de la COVID-19), CLSA (Canadian Longitudinal Study on Aging), UK Biobank, and collaborating with international COVID-19 cohorts, we will study the genetic determinants of neurological manifestations of PASC.
• Our recent COVID-19 publication in Nature Medicine.

Genomic architecture of Arctic indigenous populations

• To increase the diversity of genomic research in underrepresented populations, we will generate whole genome sequencing data of an Arctic indigenous populations (Nunavik Inuit), following our previous publication.

• We aim to characterize founder, admixture, introgression and natural selection events of Nunavik Inuit, some of which may contribute to certain disease risks, the findings will advance our knowledge of the population and better serve the community.

1. PhD or MSc in Human Genetics or PhD in Quantitative Life Science

2. Postdoctoral fellow

We are looking for a motivated researcher with strong background in quantitative analysis/computational biology/biostatistics/bioinformatics.
• PhD in Human Genetics, Genetic Epidemiology, Population Genetics, Statistical Genetics or related field.
• Experience in bioinformatics and programming skills is required.
• Familiar with Linux environment, shell scripting and command-line software.
• Demonstrated proficiency in R is required.
• Demonstrated proficiency in Python is an asset.
• Familiar with cloud computing is an asset.
• Experience working with large scale human genomic and multi-omics dataset is an asset.
• Experience in population and evolutionary genetics is an asset.