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Solving genetic diseases is hard.
Like, there are a ton of genes and gene variants,
and picking through them all one by one
to find out
which ones are troublemakers
is like looking for a needle
in a haystack.
It’s such a problem that geneticists
have been kind of stuck for awhile -
after the completion of
the Human Genome Project,
there’s only been so much progress made
with the data available.
Researchers figured
they may be able to pick through
that hay a lot faster
if they widen the search net a little.
So some geneticists interested
in curing human diseases
have been exploring the DNA not of humans,
but of a huge group of animals.
Specifically, our fellow primates.
[intro song]
This project has been called
the Primate Genome Project,
for obvious reasons.
It involved more than 100 researchers
based in countries all over the world.
One of the groups involved
in all this cataloged DNA samples
from more than 200 kinds of primates,
representing around
half of the primate species out there.
Some blood or skin samples
came from animals in captivity,
while others were taken
from animals living au naturel,
in the wild.
And some of the DNA
came from dead specimens
from zoos and other institutions
that were collected as far back
as the 1960s.
Getting ahold of tissues
from all of these species
was a huge undertaking,
largely supported by Illumina,
a DNA-sequencing company
that usually deals with genetic material
of the human variety.
The story goes
that they initially proposed the project
with the idea that the company
would cover the sequencing in return
for the hard-won samples,
and the resulting data
would be shared all around.
But this wasn’t just fueled
by a passion for primate genetics research.
See, despite the revolution
in DNA sequencing technology,
the field of human genetics research
has been an uphill battle for quite a while.
So scientists decided to cast a bigger net to capture genome data
from nearly half of all primate species
with the hopes of gaining
new insights into age-old problems.
The Human Genome Project,
which began in 1990
and led to the publication
of the first nearly-complete
human genome sequence in 2003,
came with, like, some high hopes.
Researchers had dreams of deciphering
the entire make-up of our genetic code
and finding lots of new approaches
to predict, prevent, and treat disease
without harmful side effects.
But even though
we know that genetic mutations cause diseases,
actually finding the specific genetic mutations
to blame has been challenging.
Because our genomes
are so immensely long and complicated,
it’s pretty much inevitable
that a few errors get made
every time the DNA is replicated.
Which adds up when you consider
that a human’s genome
is about three billion characters long.
.
Part of what makes
any individual human unique
is these differences
, what we know as mutations, or variants.
Most genes instruct our cells
to build molecules called proteins
that do all kinds of things in our bodies,
like helping us digest food
and creating pigment in our skin or hair…
That’s just to name just a couple of things.
.
But sometimes
when genetic mutations mess up the code,
a really important protein with a crucial function
might get built incorrectly,
or might not get built at all.
When these mutations occur
in the cells that become sperm and egg,
they’re heritable,
meaning they can be passed to the next generation.
Which is how we end up
with genetic diseases like,
say, Huntington’s Disease.
Huntington’s is actually
a really simplified example,
since it’s controlled
by mutations in just one gene.
Most human diseases
are complex and stem from mutations
in lots of genes,
plus how those genes are expressed,
and environmental factors, too.
Which is why finding out which mutations
are contributing or not contributing
to disease has not been easy.
There are over 70 million
predicted possible protein-altering variants
in the human genome.
But so far,
only about 0.1% of those variants
have known links to diseases.
The rest are considered variants
of “uncertain clinical significance” -
meaning, we’ve got no idea
if they’re harmful or not.
And This new idea
was to get rid of a little of that uncertainty
by comparing these mutations
to a much larger dataset.
So, now that we have all these primate genomes
, what are we gonna do with them?
Essentially, we need to play a massive game of
“spot the difference.”
The researchers
needed to identify genes that are stable,
or almost never vary across all of these species.
The idea is that
if a gene almost never varies,
that means mutations in it
would be like, really bad.
And the opposite is also true:
If a specific mutation shows up
in lots of other species,
you can infer that mutation probably doesn’t mess
with any important functions
even if it tweaks a protein.
Basically, not that bad.
So when they play "spot the difference"
and find a gene variant in multiple species,
that gene gets crossed off the list
of suspects for being harmful.
Using this model,
they flagged over 4 million variants
that seemed likely to be benign
because they showed up
in lots of other primates, too.
But there’s still a lot left to do.
Like we said,
there are more than 70 million variants
to pick through.
And this is where AI comes in.
The team used the primate variants
to train a neural network
that they named PrimateAI-3D.
It analyzes the structure of proteins
to figure out whether mutations
in the code mess it up enough to cause problems.
These researchers used scores from PrimateAI-3D
to identify genes that had a higher association
with disease when compared
to gene variant data
of more than 450,000 humans.
And the specific messed-up genes
that the program identified allowed researchers
to hone in on potential causes
of complex health issues..
One example is high cholesterol.
The team identified
certain rare variants in two genes,
LDLR and PCSK9,
that probably affect your odds
of developing high cholesterol
and heart disease.
Previous work had identified PCSK9
as a gene of interest,
but hadn’t figured out if this specific variant
was a major player or not.
So having this evidence
gives researchers more ammo
to investigate both genes’ roles in heart disease.
They believe it could even be used
to make targeted therapies for people
with the mutations.
And even though the main goal
of the Primate Genome Project
was to help solve human diseases,
the unprecedented breadth of data gathered
by both this team and others,
has led to far-reaching insights
about other primates, too.
The newly revealed genomic relationships
between these hundreds of species tell stories of
primate migration and adaptations.
Scientists are hopeful
that it can be used
in conservation efforts, too.
For instance,
analyzing these primate genomes
has contributed to the body of science
that challenges
the somewhat dated idea of immutable species.
When we think about a species,
the most simplified definition
is that two animals are in the same species
if they can reproduce
and make fertile offspring
with each other.
The classic example
is that even though a horse and a donkey
can breed to make a mule,
they’re not the same species
because the mule is almost always sterile.
Research has increasingly shown
that the whole idea of a species
doesn’t always work that way.
Hybrids, as in the offspring
of two individuals
that are in totally different species,
can occasionally be fertile.
And this new genome data
revealed that primates can
and often do have fertile hybrids, too
- enough to see the evidence of them
in their genomes.
That tells us a ton
about what these little guys get up to in the wild,
where their territories overlap, and also…
like, how they see their like,
species cousins, so to speak.
The research is also revealing details
about the effects of varied habitats
on genomic change in species.
This knowledge could help
with conservation efforts of threatened primates.
We’re continuing to learn about ourselves
by investigating other primates
with these new approaches,
uncovering more than we knew before.
There is still a lot more to learn
from these primate genomes,
both about us and about them.
But thanks to our evolutionary cousins,
we’re picking through that haystack
faster than before!
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