Download Malaria and the human genome

STUDENT’S GUIDE
Case Study
Malaria and the
human genome
Steve Cross,
Bronwyn Terrill
and colleagues
Wellcome Trust Sanger Institute
Hinxton
Version 1.1
Case Stu
Case Stud
malaria and the human genome
Malaria and the
human genome
IMAGE FROM: Wellcome Images.
Each year, the malaria parasite Plasmodium falciparum kills over a
million African children and causes debilitating illness in over half
a billion people worldwide. Malaria is the strongest known selective
force in the recent history of the human genome. Many types of genetic
variation have evolved in humans due to selection by the malarial
parasite, causing variation in red blood cell regulation, structure and
antigen expression.
In this activity, you will investigate the origin and action of mutations
that are thought to have arisen in human populations in response to
selection pressure from malaria.
Activity overview
Malaria is a debilitating illness that affects more than 40% of the world’s
population caused by parasites of the genus Plasmodium. This disease is
thought to be the strongest selective force on our species’ in recent history.
Researchers believe that this is responsible for the diverse range of genetic
adaptations that protect against malaria in different populations’ genomes.
In this activity, you will use a common statistical test (chi-squared) to work
out whether a genetic mutation is associated with incidence of the disease,
or whether the two events are independent.
What is malaria?
Every year, malaria causes hundreds of millions of people to be ill and kills
between one and three million, most of them children in sub-Saharan
Africa. It is a disease caused by a protozoan parasite that is spread by
mosquitoes and which multiplies inside human blood cells. It causes fevers,
chills and shortness of breath (the symptoms are like severe flu) and, in
extreme cases, coma and death.
Malaria is a disease that is older than humans, and there are malarial
parasites that infect birds, lizards and primates other than humans. The
human form of malaria seems to have existed for at least 100,000 years,
although it probably only became such a vicious killer about 10,000 years
ago. Malaria is currently found in a band that extends across the tropics,
throughout Africa, southern Asia, Central America and the north of
South America. At one time, it also extended north into Europe and North
America.
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malaria and the human genome
Malaria can be treated with a wide variety of drugs, from the threehundred-year-old quinine to recently-developed treatments. The choice
of drug depends on the type of malaria infection and the development of
resistance to drugs by some strains in some areas. There is currently no
vaccine for malaria, but there is a huge international effort to develop one.
Malaria is the focus of a large amount of medical research, and the genome
of the most common forms of the disease was sequenced in 2002 by staff at
the Wellcome Trust Sanger Institute.
How malaria is caused
Malaria is caused by a group of protozoan parasites of the genus Plasmodium.
There are four types of Plasmodium. P. falciparum is the most common form
on the African continent and causes the most severe malaria of any type.
P. vivax is the form of the infection most often seen in Asia. The other two
species, P. ovale and P. malariae, are less common.
Malaria life cycle
The malaria parasites are spread
by female Anopheles mosquitoes,
being injected into the human
bloodstream when the mosquito
sucks blood (1).
Once in the blood vessels (2), the
parasites (known as sporozoites)
migrate to the liver (3), where they
can multiply, safe from attack by
the immune system.
The next stage in the parasite’s life
cycle is to invade red blood cells (4).
In the red blood cells, the malarial
parasites of this stage (merozoites)
can multiply to huge numbers before
bursting the cells and re-entering
the bloodstream (5a). Alternatively,
they can invade red blood cells
to turn into sex cells known as
gametocytes (5b). Gametocytes can
be taken up by mosquitoes through
the same biting process and blood
meal as before. In the mosquito’s
intestine, the sex cells mate; their
offspring can then migrate to the
mosquito salivary glands ready to
be passed into a new human host.
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malaria and the human genome
Malaria as a selective pressure on humans
Researchers believe that there is evidence in the human genome that
malaria has been the single greatest selective pressure on human beings
in recent genetic history. Because it is so widespread, and so deadly,
malaria has killed huge numbers of humans, and our genomes bear scars
of a long ‘arms race’ with this disease. There are numerous specific genetic
variations which are found most often in areas where malaria is common,
some of which have been shown to offer protection against infection.
One of these genetic variants might explain why P. vivax is so rare in Africa
compared to P. falciparum. In western and central Africa most people have
genetic variants that mean that they do not produce a specific protein,
called the Duffy protein, on the surface of their red blood cells. This protein
is used by P. vivax as a way to enter red blood cells, and thus these people are
immune to P. vivax. This suggests that there has been very high exposure
to P. vivax in these regions in the past few thousand years, but that human
DNA changes have meant that this particular parasite is much rarer now.
Sickle cell trait and sickle cell anaemia
Sickle cell anaemia is a genetic condition that is found mainly in areas
where malaria in endemic. The mutation that causes sickle cell anaemia
is commonly said to be recessive, in that only people with two copies of
the disorder form of the gene are affected by the full disease. In fact, even
carriers with one copy of the gene, who are said to have ‘sickle cell trait’,
will have a small percentage of sickled cells in their blood. At a molecular
level, they also have a significant change in half of their haemoglobin
molecules.
The molecular structure of
haemoglobin. The two beta
subunits are in blue.
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malaria and the human genome
A change of a single nucleotide in the HBB gene, β-globin (on chromosome
11), causes sickle cell trait, and having this change on both copies of
chromosome 11 causes sickle cell anaemia. β-globin is one of the proteins
that makes up haemoglobin — a complex found in red blood cells that binds
oxygen for transport around the body. The allele with this change is often
called Hbs for short, with the non-sickle cell version being known as Hba.
The unaffected genotype is therefore written Hba Hba , the sickle cell trait
genotype is Hba Hbs and the sickle cell anaemia genotype is Hbs Hbs .
PHOTO BY: E.M. Unit, Royal Free Hospital
School of Medicine/Wellcome Images.
The symptoms of the disorder are visible at a microscopic level. The red
blood cells of a homozygote for the sickle cell allele tend to adopt a rigid
sickle shape. This means that they cannot move as freely through small
blood vessels, and therefore cannot transfer oxygen as effectively to some
organs. Symptoms include organ pain and fever, and often occur in bouts
rather than being continuous. People with sickle cell anaemia usually have
a shortened life span.
Sickle and normal red blood cells.
People with one copy of the sickle cell allele and one standard allele only
tend to feel sickle cell symptoms under extreme conditions of oxygen
deprivation, such as climbing a mountain, or if seriously dehydrated.
Because the sickle-cell mutation only alters a single base in the DNA
sequence, it is known as a single-nucleotide polymorphism, or SNP
(pronounced ‘snip’). Internationally, researchers focus on the role that SNPs
play in human disease. SNPs have been found that offer some protection
against obesity, heart disease and diabetes. In malarial regions of Africa,
about 1 in 10 people carries at least one sickle cell allele.
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malaria and the human genome
Is sickle cell trait or anaemia associated
with malaria?
Sickle cell anaemia is, at first glance, a paradox. If possessing two copies of
an allele causes such serious disorder, and historically would have caused
death before reproductive age, how can that allele be so common? A clue
to the reasons can be found by looking at the distribution of the sickle cell
allele on a world map, and comparing it to the distribution of P. falciparum;
Both are found in the same regions. This would suggest that maybe the
sickle cell allele is protecting some people against malaria, even as it has
adverse effects on others.
Number of cases of malaria
1 million or more
1 million — 500, 000
500, 000 — 100, 000
100, 000 — 10, 000
10, 000 — 1, 000
Fewer than 1, 000
A map of the distribution of
malaria in populations of Africa
and South Asia. The darker the
green, the greater the incidence
of the disease. Data source: World
Health Organisation.
% of population with Hbs
14 +
12 — 14
10 — 12
8 — 10
6—8
4—6
A map of the distribution of the
sickle cell allele in populations of
Africa and South Asia.
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malaria and the human genome
The key to this protection is that carriers of only one copy of the sickle cell
allele, who also have one healthy allele, do not suffer from the anaemia, but
are protected against malaria by their sickle cell trait. This is often quoted
as an example of a phenomenon known as heterozygote advantage. In this
instance, because the heterozygote is fitter (in an evolutionary sense) than
either of the homozygotes in a specific set of circumstances, there will
always be a balance of genes in the population, rather than one form being
fixed by selective pressure. Where there is little malaria, the superior
fitness of the non-sickle form drives this variant to fixation.
Exercise 1
Exploring the effects of sickled cells
To understand the effect of the SNP that causes sickle cell trait and sickle
cell anaemia, you will first need to characterise it. You will be using
JavaScript DNA Translator 1.1, a simple tool for analysing DNA sequences.
The first 60 nucleotides of the normal form of the gene look like this:
ATG GTG CAT CTG ACT CCT GAG GAG AAG TCT GCC GTT
ACT GCC CTG TGG GGC AAG GTG AAC
The mutated (sickle cell) form looks like this:
ATG GTG CAT CTG ACT CCT GTG GAG AAG TCT GCC GTT
ACT GCC CTG TGG GGC AAG GTG AAC
Open the file JVTtranslator.shtml with a web browser (it looks best in Mozilla
Firefox). You will be presented with this screen:
Give your sequence a name here.
Paste the DNA sequence here.
Ensure that the 'Reading frame' is
set to '1' so that the software starts
at the beginning of the sequence.
Click 'Translate'.
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malaria and the human genome
Type a name for your sequence into the top box (‘standard’ or ‘sickle’ for
example). Cut and paste one of the DNA sequences from the text file called
DNA_sequences.txt into the second box. You’ll need to tell the software
that you’re only interested in one protein sequence from this DNA, by
changing Reading Frame to 1. Now click the Translate button.
The screen that is generated will give you your results. The easiest version
of the protein sequence to read is in the yellow box. Here is a list of what
the letter codes in the yellow box represent in terms of the amino acids in
the predicted protein.
Asp
Glu
Arg
Lys
His
Asn
Gln
Ser
Thr
Tyr
D
Aspartic acid
E
Glutamic acid
RArginine
KLysine
HHistidine
NAsparagine
QGlutamine
SSerine
TThreonine
YTyrosine
Ala AAlanine
Gly GGlycine
Val
VValine
Leu
LLeucine
IleIIsoleucine
Pro
PProline
Phe
FPhenylalanine
Met
MMethionine
Trp
WTryptophan
Cys
CCysteine
Amino acid codes
The three-letter and single letter codes
for the 20 amino acids that are found
in proteins. Most computer software
uses the single-letter codes to show the
different amino acids.
An example of output from the
JaveScript Translator. The amino
acid sequence is in the yellow box.
Questions
a. What has changed in the sickle cell gene?
b. What has changed in the sickle cell protein?
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malaria and the human genome
Exercise 2
Does sickle cell protect against malaria?
In this exercise you will test the hypothesis that the sickle cell allele
is associated with protection against malaria. Rather than look at the
geographical distribution of the parasite and the gene, you will be looking
directly at the life histories of people with and without the sickle cell SNP,
and comparing their chances of infection.
When trying to demonstrate a relationship or association between a genetic
change and a disease, it is important to gather data in different ways and
from different sources, to prevent yourself from coming to inaccurate
conclusions about a gene’s importance. There are many studies that claim
to have found a correlation between a specific genetic change and a disease
or susceptibility, without any idea of how this might happen. Only by
repeating studies and looking for mechanisms by which the disease is
caused can scientists be sure that associations are real rather than just
statistical anomalies.
The data
You are going to analyse real data from a 2008 study to evaluate the
evidence that the sickle cell allele is associated with malarial incidence.
The hypothesis is that people with sickle cell trait will be less likely to
become hospitalised with malaria.
Every year millions of children worldwide are hospitalised with severe
malaria. For this study, DNA was taken from 500 children attending a
single hospital. The DNA was examined, and the sickle cell SNP status was
determined for each child.
As the control sample, DNA was also taken from 500 people in the
population near the hospital. These were people who had not been admitted
to hospital with severe malaria as children. The sickle cell SNP status was
also determined for each person in this population.
You will need to perform a statistical test to find out whether the prevalence
of the sickle cell allele is significantly greater in the general population
than in children being admitted to hospital with severe malaria. This test
evaluates whether the variation in numbers is a result of chance or a real
effect. You will be looking at individual chromosomes rather than people.
This is because the paired chromosomes of humans would make the test
much more complicated than it would be if you were to use individual
chromosomes.
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malaria and the human genome
The Chi-Squared test
The Chi-Squared test can be used here to test the following null hypothesis.
Null hypothesis: There is no difference in the prevalence of the sickle cell allele
in the chromosomes of people with and without malaria.
Alternative hypothesis: There is a significant difference in the prevalence of
the sickle cell allele in these populations.
Open the Excel spreadsheet called malaria_data_student. There are two
worksheets: Cases and Controls. (Your teacher may also give you another
worksheet called Student Table to use.)
On the Cases and Controls worksheets, there are 500 people’s genotypes at
specific locations in the genome. Remember the Cases were from people in
hospital with malaria; Controls were from people in the community. The
column you’re interested in is Column E: HbS. Sort the data and count the
rows to work out how many As and Ts have been observed in the different
populations.
Fill in the table below using the chromosome data you have been given:
Category
Observed (O)
Expected* (E)
(see below)
O–E
(O–E)2
(O–E)2
E
Has malaria
Has Hbs (T)
Has malaria
No Hbs (A)
No malaria
Has Hbs (T)
No malaria
No Hbs (A)
TOTALS
* To calculate the Expected values, you will need to count the number of
Hbs alleles found across the entire population under test (1,000 people
and therefore 2,000 chromosomes). This figure, divided by the total
chromosome population size (2,000) will give you the prevalence of the
Hbs allele. Multiplying the prevalence of each form of the allele by the
number of people’s chromosomes in each test group, will give you the
Expected values.
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malaria and the human genome
Size of population
(ignoring alleles)
Category
Prevalence of allele
Expected
Has Hbs
No Hbs
(O–E)2
The total of E across all four groups is the chi-squared value ( χ 2). There
is only one degree of freedom in this experiment. Using this information,
calculate the probability of the null hypothesis being true using this lookup
table, where p is the probability.
p
0.25
0.2
0.15
0.1
0.05
0.025
0.01
0.005
0.001
0.0005
χ 2
1.32
1.64
2.07
2.71
3.84
5.02
6.63
7.88
10.83
12.12
Questions
c. What is the probability that the null hypothesis is true?
d. Does this mean that the result is statistically significant?
e. Does this information reinforce or contradict the data based on
mapping the prevalence of malaria and the sickle cell allele published
above?
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