MSc Genomic Medicine
Introduc0on to Human Gene0cs and Genomics Module –
Assignment
The assignment for this module will be an essay (part A) on the topic
shown below and a prac:cal (part B) outlined further below.
Please return as single word document
Part A
To which extent are non-protein coding regions of the genome
implicated in human gene0c disease – contrast Mendelian versus
common complex diseases
Assay not to exceed 1500 words (excluding Tables and references)
PART B – Prac0cal
Introduc0on
In the prac:cal you will be given two lists, one comprising 23 gene
names and the other 21 DNA sequence variants (see table at the end
of the document) – the selected genes are part of a study.
Repor0ng
Please prepare your report as a word document not exceeding 2000
words excluding Tables and references. Use a 12 font and double
spacing throughout the document and list URLs as references. You
will find more detailed guidelines on how to prepare reports on
QMplus. Provide a (very) brief Introduc:on outlining the objec:ves
of this prac:cal followed by answers to each Task in the order
provided, and finally a brief ‘Conclusions and Discussion’ sec:on
Tasks
1. Establish the correct gene(s) – variant pairs using a genome
browser; variants may also be located outside a gene; typically,
the nearest gene(s) to this variant will be included in the list.
Obtain a reference sequence (rs) id for all variants.
2. Use database resources to explore what is known about the
func:on of each gene and the protein it encodes (i.e. a few
sentences summarising what the gene does) as well as its :ssue
expression profile. Prepare a table with each gene’s poten:al
implica:on to disease.
3. Establish the func:onal impact of each sequence variant; for
example, is a variant located in a coding region of the genome
and if yes, does it alter an amino acid? or is it overlapping a
regulatory element? Report this element e.g. promoter
4. Are there any good proxy SNPs (r2 ≥ 0.8) for the variants rs7636
and rs13107325?
5. Report, where possible, the minor allele frequency of each
variant in the popula:on – reference the data source you used
(e.g. URL of data base or repository). Use a database to report
MAF in different popula:on groups i.e. HapMap /
1000Genomes panels. Discuss if you observe any frequency
differences between popula:ons.
6. Inves:gate using both variant iden:fier and the gene name
whether there is a known associa:on to one or more human
traits (e.g. blood pressure) including disease.
7. For those genes you have established an associa:on to a
human trait(s) report the number of known rare variants and
how many of these rare variants are Loss of Func:on.
8. Does rs13107325 have any unusual features in terms of its LD
rela:onship to other nearby common variants in Europeandescent popula:ons? In which common diseases this variant
may play a role?
9. Based on all the informa:on assembled, assess whether the
genes found in ques:on 1 could be divided in to subgroups
underlying a specific trait or combina:on of traits.
10.Are there any epigene:c effects known to be associated with
the trait(s) of the subgroup(s) you defined (i.e. ques:on 9)
gene name
DNA Sequence
variant
ACHE rs2145270
ALDOA rs6235
ANAPC4 rs10146997
BCL7A rs1064395
BMP2 rs10838738
BPTF rs11546878
C6orf106 rs11835818
CASC20 rs12602912
CYB5B rs13107325
DNAJC27 rs141845046
ECE2 3:185529080
GIPC2 1:78623626
IGF2BP2 rs17782313
LOXL4 rs1983864
MC4R rs2814993
MIR1538 rs34811474
MTCH2 rs4665736
NCAN rs4783718
NRXN3 rs7636
PCCB rs9844666
PCSK1 rs9928448
SLC39A8
ZBTB7B