Section 4 Week 3: Genomics and human health
Note that in the 2020/21 academic year, students were not asked to do these exercises during Week 3.
However, you might find them useful for revision purposes.
Here, we will take a look at several web-based resources to support what we have learned in lectures and outside reading about applying genomics to human health. We will try solve some of the web-based problems (Weblems) posed by the author of our primary course textbook; see: https://global.oup.com/uk/orc/biosciences/evolution/leskgenomics3e/student/weblems/.
4.1 Browsing the human genome
In previous practicals, you have downloaded small microbial genomes onto your local computer and browsed them using the IGV software. We can, in principal, do the same thing with the human genome. However, it is usually more convenient to use one of the freely available web-based human genome browsers. The most popular human genome browswers on the web include:
Both of these browsers are rich with large amounts of data overlaid onto a human reference genome sequence. Let’s use these to try to solve Weblem 9.1 from Lesk’s Introduction to Genomics.
4.1.1 What gene appears between the genes for C4A and C4B in the human genome?
Both of these browsers are rich with large amounts of data overlaid onto a human reference genome sequence.
Let’s use these to try to solve Weblem 8.1 from Lesk’s Introduction to Genomics.
In Ensembl (https://www.ensembl.org/Homo_sapiens/Info/Index), let’s try searching for ‘C4A’:
This should lead you to an entry for the human C4A gene:
And this will include a link to the relevant location in the browser. Although there is a lot (too much?) of information on the browser, navigation should be fairly self-explanatory. By zooming into the appropriate region and configuring the tracks, you should be able to view the genomic region between genes C4A and C4B:
You might also wish to try the same task using the UCSC browser instead of Ensembl …
Let’s use these to try to solve Weblem 8.4 from Lesk’s Introduction to Genomics.
4.1.2 Find three examples of mutations in the CFTR gene (associated with cystic fibrosis) that produce reduced but not entirely absent chloride channel function. What are the clinical symptoms of these mutations?
We can see the sites of phenotype-associated short variants in the Ensembl browser here:
Notice that you can click on any of these variants and it will take you to the database entry for that variant, including some information about the phenotype(s) associated with that variant.
What you are looking at above is still within the Ensembl database. However, (most of) these variants are drawn from a database called SNPdb and we can follow the link to take us directly to that SNP in SNPdb:
From the SNPdb web page, we can follow a link to (yet another database) ClinVar, which will tell us what is known about the clinical significance of this particular variant. However, the degree of detail recorded in this database does not distinguish between reduced function versus completely absent function. I presume that what Lesk is getting at here is that some mutations are nonsense mutations leading to premature stop codons whilst others are missense mutations leading to a slightly altered amin-acid sequence but not complete loss of function.
4.2 Online Mendelian Inheritance in Man
Recall that during the lectures, we very briefly discussed the OMIM (Online Mendelian Inheritance in Man) database. OMIM is a comprehensive, authoritative compendium of human genes and genetic phenotypes that is freely available and updated daily. The full-text, referenced overviews in OMIM contain information on all known mendelian disorders and over 15,000 genes. OMIM focuses on the relationship between phenotype and genotype. It is updated daily, and the entries contain copious links to other genetics resources (https://www.omim.org/about).
Let’s use OMIM to try to solve Weblem 8.5 from Lesk’s Introduction to Genomics.
Weblem 8.5 asks us to find examles of diseases that are (a) autosomal dominant (b) autosomal recessive (other than cystic fibrosis) (c) X-linked dominant (d) X-linked recessive (e) Y-linked (f) resulting from abnormal mitochondrial DNA (g) resulting from abnormal copy-number expansion and (h) the result of a deletion of a region longer than 1 kb.
|Disease characteristics||Example of disease with these characteristics|
|Autosomal recessive (other than cystic fibrosis)|
|The result of abnormal mitochondrial DNA|
|The result of abnormal copy-number expansion|
|The result of a deletion of a region longer than 1kb|
Hint: the summary table at https://www.omim.org/statistics/entry is helpful for the first six categories. The final two are going to require broader web searching.
4.3 Genome-wide association studies (GWAS)
We are going to tackle Weblem 8.8 from Lesk’s Introduction to Genomics.
Find SNPs that are associated with foetal haemoglobin measurement. Which SNP has the smallest p-value? In what chromosome band does it appear?
To solve this, first navigate to the EBI-NHGRI GWAS catalogue (https://www.ebi.ac.uk/gwas/). You have seen this previously in a lecture. Select Haematological measurement:
4.4 Cancer genomics
During the lectures, we learn that a large number of cancer genomes have been sequenced and compared against matched healthy genomes from the same patients. This produces catalogues of genes implicated in cancer and catalogues of driver mutations. Let’s explore some freely available web-based databases that curate these data. The go-to web portal is: https://cancer.sanger.ac.uk/cosmic.
Let’s investigate a specific cancer-associated gene, IDH1. In which types of cancer (which tissues) is its mutation most prevalent? See: https://cancer.sanger.ac.uk/cosmic/gene/analysis?ln=IDH1#tissue
Using the census of cancer genes at https://cancer.sanger.ac.uk/census, which of the hallmarks of cancer are promoted by mutations in the genes VHL, PIK3CA, IDH1, RB1? How many genes are known to be implicated in cancer?
You should be able to find a summary for each gene that looks something like this:
Take a look at the VHL gene in the Cosmic3D viewer (https://cancer.sanger.ac.uk/cosmic3d/protein/VHL?pdb=6BVB). Look at the profile of cancer-associated somatic mutations found in this gene. Based on this profile, do you think it is a tumour-suppressor? Or an oncogene?
And how about gene PIK3CA? Oncogene or tumour-suppressor gene?
How about genes IDH1 and RB1?
If you want to learn more about the Cosmic database, see: https://cancer.sanger.ac.uk/cosmic/help/tutorials
Well done! You reached the end! If you still have time left, you may wish to attempt any of the other Weblems(https://global.oup.com/uk/orc/biosciences/evolution/leskgenomics3e/student/weblems/) that pique your interest.