RESEARCH OFFICER, Division of Human Genetics, Institute of Infectious Disease and
Molecular Medicine, University of Cape Town
(1 year contract possible renewal)
_____________________________________________________________________
A. THE CONTEXT
Our project will be the first to apply current genomic sequencing approaches to study
schizophrenia in a sub-Saharan population of African lineage. We have assembled a team
with the capacity and commitment to complete such a study in South Africa. Our team
comprises psychiatrists (Drs Susser, Stein, and McClellan) and geneticists (Drs King, Ramesar,
Walsh) who have worked together over decades, both within and across South Africa and
the United States.
Each site has defined roles critical to achieving the study aims. Columbia University (CU) will
serve as the coordinating center for the study, and will be the primary liaison with the
National Institutes of Mental Health (NIMH). The Columbia team will oversee the
coordination of subject recruitment, analysis of diagnostic and cognitive data, and
manuscript development. The University of Cape Town (UCT) will recruit, evaluate, and
sample African cases and controls. They will provide phenotypic information, participate in
the interpretation of genomic results, help prioritize candidate genes, and follow-up on
potential associations between the rare deleterious mutations and clinical subtypes within
their patients. Dr Ramesar’s laboratory at UCT will carry out CNV discovery and analyses, and
with the resources provided by this grant, develop the capacity to conduct exome and
genomic sequencing. The University of Washington (UW) will conduct exome and targeted
genomic sequencing, and with UCT, analyze genomic data. The Illumina-based HiSeq
platform used by the King laboratory at UW for exome, targeted genome, and whole
genome sequencing is now widely used, but has not previously been applied to a study of
complex disease in a sub-Saharan African population.
Each site will be a full partner in the research and participate in decisions affecting the
implementation of the study or interpretation of the data produced by the study. All
protocols will be monitored by institutional IRBs.
B. THE RESEARCH PROJECT
The goal of this project is to identify genes important for schizophrenia, based on genomic
analysis of the Xhosa population of South Africa. We propose to identify and characterize
rare mutations present in Xhosa with schizophrenia but not in age and gender–matched
Xhosa controls. Rare point mutations, small insertions and deletions (indels), and copy
number variants (CNVs) will be identified. Genomic approaches will include whole exome
sequencing, targeted genome sequencing, and CNV analysis. This project will be the first to
use current genomic approaches to study schizophrenia in an ancient African population.
The Xhosa are the largest population of the South African Eastern Cape region. Because the
number of alleles to be found in ancient African populations is far greater than in nonAfrican populations, genomic analysis of schizophrenia in the Xhosa offers the opportunity to
identify critical mutations for this illness not detectable elsewhere. Importantly, the genes
harbouring such mutations in the Xhosa are very likely to harbour other damaging mutations
in other populations worldwide.
1
We and others previously demonstrated that genomes of individuals with schizophrenia are
enriched for rare structural mutations, including those that are de novo or arose in recent
generations. Genes impacted by these rare CNVs in patients disproportionately contribute to
cellular signalling and neurodevelopmental processes, including neuregulin and glutamate
pathways1. Recurrent deletions or duplications at genomic hotspots, e.g., 1q21.1, 15q13.3,
and 22q11.2; are associated with substantial disease risk5, although none of these regions
explains more than ~1 % of the illness. Thus, schizophrenia is characterized by marked
genetic heterogeneity, to the remarkable extent that most patients may have a different
genetic cause5.
We hypothesize that a gene important to schizophrenia will harbour different diseasecausing mutations indifferent affected individuals. We will use a gene-based approach to
identify genes that harbour multiple rare orde novo deleterious mutations in cases but not in
controls. Given the genetic diversity of African populations, our project will potentially find
novel candidate genes for schizophrenia that have not yet emerged from studies of other
populations. This grant will also foster the development of gene discovery research for
neuropsychiatric disorders in Africa.
Aim 1: Identify candidate genes for schizophrenia in a discovery sample of 200 Xhosa
individuals with the illness compared to 200 age- and gender-matched Xhosa controls.
Aim 1A: Identify all rare point mutations and indels using exome sequencing (Illumina HiSeq
platform at UW).
Aim 1B: Identify all rare, gene-impacting copy number variants (CNVs) genome-wide using
the Affymetrix6.0platform (at UCT).
Aim 1C: Characterize the predicted impact of rare mutations identified in Aims 1A and 1B on
gene function.
Prioritize candidate genes for Aim 2 based on (i) genes harbouring de novo deleterious
mutations in cases but not controls; (ii) genes harbouring putatively deleterious events in
more than one case but not controls; (iii) genes with biological relevance for schizophrenia
that harbour putatively deleterious mutations in cases but not controls. Using these criteria,
we will identify approximately 250 candidate genes to use for gene discovery in Aim 2.
Aim 2: Characterize the mutational spectra of candidate genes prioritized in Aim 1 in a
validation sample of 900 Xhosa individuals with schizophrenia and 900 Xhosa controls.
Create a cRNA oligonucleotide solution capture pool to detect all exonic mutations in every
candidate gene identified in Aim 1 (~1.5 MB). Capture, barcode, and multiplex sequence
genomic DNA from 900 cases and900 controls. Identify all rare variants and characterize the
potential impact of each on protein functioning using bioinformatic tools.
Aim 3: Identify genes enriched for deleterious mutations in African individuals with
schizophrenia.
From the genomic analyses in Aim 2, identify the total burden of rare putatively deleterious
mutations in each candidate gene. Identify genes disproportionately disrupted in cases or in
controls. Compare the total number and ontogeny profiles of these outlier genes in cases
versus controls. In future projects, we will determine the biological impact of candidate
mutations on protein function and expression, and examine the mutational spectra of outlier
genes in other schizophrenia cohorts.
2
C. THE POST
This is a one year contract post located in the Division of Human Genetics, IIDMM, University
of Cape Town. This post could possibly be renewed.
D. ROLE OF THE INCUMBENT
The Research Officer will conduct and contribute to the research project with minimal
supervision. The candidate should develop research capacity regarding
bioinformatics/molecular genetics. S/he will oversee that all relevant information for
biological samples is collected, that biological materials are correctly received and
processed in the laboratory, and shipped where this is necessary. While having
oversight of these operational issues, this person will have extensive knowledge of
state-of-the-art molecular genetic technologies, and will have technical and
analytical expertise with high throughput technologies (e.g. microarray technology,
DNA sequencing) and data analysis. S/he will be responsible for all bioinformatic
processing required by the project and the division. S/he will be expected to train
other students in bioinformatics.
E. JOB DESCRIPTION
JOB TITLE:
Research Officer
AREA:
Human Genetics, IIDMM
REPORTS TO:
Prof Raj Ramesar, Head of Division
JOB PURPOSE:
To conduct and contribute to the research process with minimal supervision and to continue
to develop individual research capacity.
KEY PERFORMANCE AREAS:
i.







Research
Collect and manage project data
Perform wet lab-based molecular genetics and dry-lab based bioinformatic analyses
Conduct research projects related to the project
Manage research projects with regard to effective project planning, implementation, coordination and data management
Process and analyse results from high-throughput DNA analysis
Present research findings
Co-author peer reviewed publications
3
ii.




Teaching & Learning
Undergraduate co-supervision
Co-facilitate bioinformatics workshops
Support training and development activities
Development bioinformatic research capabilities within our own division
iii.
Social responsiveness
Engage with relevant public entities and stakeholders
Translate probable research findings into practice for public benefit under the
appropriate supervision


iv.






Leadership, Management and Administration
Attend and participate in project Management Meetings,
Provide and present updated relevant information at meetings
Contribute to strategic planning goal setting
Communication and liaison between collaborators
Support the project director
Coordinates the arrival of biological samples containing all the necessary information
and ensuring that those samples are shipped to Collaborators in the correct format
within the appropriate time frame and according to their specificities
Characteristics of the incumbent
Desirable personal attributes and competencies:
 The ability to work in a team, foster co-operation between team members, build team
spirit, and manage people and co-ordinate their involvement in projects
 The ability to be innovative, to look for creative solutions to difficult problems, to seek
and propose new opportunities and to enhance effectiveness
 The ability to effect appropriate leadership in the attainment of goals and objectives,
express opinions in a constructive and assertive way, sharing information and
encouraging feedback
 The ability to think analytically and independently and aggressively tackle new challenges,
breaking down complex tasks into manageable parts in a systematic way
Qualification
MSc degree, preferably PhD degree, in Human Molecular Genetics (or a relevant course
pertinent to population and statistical genetics). Bioinformatics knowledge and exposure is
an inherent requirement.
Skills and Abilities
 Bioinformatic analysis (programming would be an advantage)
 Skills and experience in molecular genetic techniques and technologies
 Skills and experience in teaching
 Experience in group facilitation
 Skills and experience in research methods
 Excellent communication and writing skills
 Sound administration skills
 Computer Literacy and basic data management skills
 Basic biostatistics knowledge and skills
 Leadership skills
4



Good interpersonal skills
Management skills
Sound presentation skills
Experience
 At least two to three years relevant research experience (this could be concurrent to
doing a higher degree)
 Experience regarding high throughput technologies and data analysis
 Bioinformatics analysis (programming would be advantageous)
Publications
 Evidence of contribution to research publications
5