Nav

Tuesday, July 2, 2013

No gene is an island

Many people, scientists and non-scientists
alike, object to what they perceive as genetic determinism. This is often a
reaction to geneticists apparently over-reaching and claiming that some trait
or condition is “caused by” a single gene. A common rejoinder is that any
biological process obviously involves many hundreds of gene products,
interacting with each other in complex ways and so it is nonsense to say that
the trait is determined by a single gene. That is absolutely true, if you are
using the word “gene” purely in the molecular biology sense – as a piece of DNA
that encodes a particular product (usually a protein). But geneticists also use
it in the original sense, as a unit of heredity – a genetic variant or mutation
that can be passed on across generations and that influences some phenotype.

Genetics is not about how a characteristic
arises, it is about how variation in
that characteristic arises. For example, when you are describing someone, you
might say: “She’s got blue eyes”, but you probably wouldn’t say: “She’s got two
eyes”. Both characteristics are determined by the genetic program, but only one
is affected by genetic variation. Eye colour is therefore a trait, because it
varies across the population and that variation is due to genetic differences.
Having blue eyes, insofar as it necessarily involves having eyes in the first
place, is obviously not caused by a single piece of DNA – it takes thousands of
gene products to build eyes, blue or otherwise. But having eyes that are blue, as opposed to brown, can be due to a
single genetic variation.

As it happens, though, eye colour is also a
good example of genetic interactions. Because, while it’s true that a single
mutation can explain the difference in eye colour between some people, it’s
also true that many people carry more than one such mutation in any of several
different genes. The ultimate colour that emerges is thus often determined by
interactions amongst multiple genetic variants.

This is even more true for traits like
height or IQ which differ in a quantitative way across the population. The
differences between any two individuals for traits like these are typically not
caused by a single genetic variant, but by many. When we talk of genetic
interactions, we are asking how the effects of such mutations combine. Do their
effects simply sum up or do they interact in a more complex way?

This is an important question because it
affects our ability to discover the contributing mutations in the first place
and, crucially, to predict any particular individual’s phenotype from their
genotype.

Height provides a good example. Genome-wide association studies with huge numbers of people (both subjects and authors)
have identified variable positions in the genome that show a statistical
association with height. While the sequence at most positions in the genome is
the same in most people in the world, around one in a thousand positions comes
in different flavours – at such positions, the DNA might be an “A” in some
people, but a “T” in others. By looking at millions of such sites, researchers
have found 180 where the average height of people with one version, say the “T”,
is very slightly greater than the average of those with the “A”.

For any individual, you can then count how
many “tall” variants they have across all these sites. If you plot the
distribution of this score across the population you can see how it correlates
with height. It turns out this relationship is remarkably linear. As you
increase the number of tall variants, the average height continues to increase
at the same rate – people don’t suddenly start to get much more tall with each
new variant and they also don’t reach a point where adding more tall variants
starts to have a smaller effect. The exact same linear relationship is seen for
genetic variants affecting body-mass index.

From Speliotes et al. (This graph is kind of misleading because
it makes the relationship look very predictive by plotting a single value for
mean height in each bin. For any particular number, there will still be a very
wide range of heights – the average is just slightly different. This is similar
to the effect of the Y chromosome – the average height of men is greater than
the average height of women but if all you know about someone is their sex you
have effectively no predictive power of their specific height).

To me, this is a genuinely surprising
result. It seems to go against expectations from experimental genetics, where
non-linear (or “epistatic”) interactions between mutations are the norm –
ubiquitous really. It is quite common, for example, for two mutations, in two
different genes, to have no effect singly but a drastic effect when combined. Or
for a mutation to have very different effects on different genetic backgrounds
(this is true for disease-causing mutations in humans as well as in animals).

By contrast, the results from genome-wide
association studies in humans seem to suggest that it is simply the number of
such variants that matters in any individual and that the precise combination
has little effect. Indeed, that is precisely how it has been interpreted by
people who suggest that the value of such a score could be used to predict an
individual’s phenotype.

The problem with such an interpretation is
that genome-wide association studies give us only an average effect of each
variant across the population – i.e., they measure the statistical effect of
having one version of a particular variant versus another, averaging all other
genetic variation out. Each such number is computed independently. If there are
many variants involved and some of them show non-additive interactions, we
would never see that because the number of individuals sharing both those
particular variants is such a small percentage of our sample and the background
of additional variants will be so diverse that any non-additive interactions
will tend to average out. Indeed, it has been shown that you can mathematically
treat the interactions as additive across the population, whether they are or
not in individuals – at least for the purposes of identifying variants
affecting a trait.

But that doesn’t mean they actually are
additive and this remains a crucial question for our ability to extrapolate
population averages to make predictions about individuals. The importance and
ubiquity of such non-additive interactions is revealed by a powerful approach
that is possible in animals.

If we have two individual organisms that
differ in some trait, presumably due to the effects of multiple genetic
differences, then we can imagine a thought experiment: what would happen if we
could decompose these mutations – if we could look at their effects one-by-one,
to see how much each one contributes to the difference and to compare this with
their combined effects?

Obviously, that experiment is not possible
with two individual organisms. But it is possible if we have clones of those individuals. Exactly
that situation exists for lines of inbred mice.

Many different lines (or strains) of lab
mice exist, most of which are completely inbred. That is, they have been
backcrossed for so many generations that no genetic variation exists within the
strain. Each animal within the strain is genetically identical – even the two
copies that each animal possesses of each chromosome are genetically identical.

When each such line was generated, some
arbitrary spectrum of genetic variants was effectively frozen in place – while
there is no genetic variation left in any particular line, there is lots of
genetic variation between lines.

This causes many phenotypic differences
between them. These are most obvious in things like coat colour, but extend to
all kinds of traits, including behavioural ones. Mice from some lines may be
more active, more anxious, more sociable, more aggressive, more clever (in
mouse terms, that is – the inbred ones are not the brightest at the best of
times), or differ in many other behavioural tendencies.

Now, if you’re a scientist interested in
the genetics of behaviour, these lines are a gold mine. If you can figure out
which of the genetic differences between two lines account for some behavioural
difference, you would have an entry point into the biological processes
controlling that behaviour (whether it’s aggression, anxiety or mouse-smarts).
Trouble is, these differences are rarely simple. In fact, they can be
complicated in very unexpected ways.

First, differences in quantitative traits
like behavioural tendencies rarely come down to a single genetic difference
between strains. Crossing strains together (say a highly active and a less
active strain) typically generates F1 hybrid offspring with a value for the
trait that is somewhere between the two parental lines. By backcrossing these
hybrids to either of the parental lines and correlating chromosome inheritance
with the value of the trait, it is possible to map out regions of the genome
influencing the trait (known as quantitative trait loci). A typical finding is
that there may be anywhere from 5 to 10 mappable loci contributing to the
differences in the trait between the two lines.

Now comes the unexpected part. Say you have
mapped 10 loci that all seem to contribute to the difference between a high and
a low activity strain. You might expect that each of these 10 different regions
would contribute a small percentage to the phenotypic difference and that their
effects would simply add up, quantitatively speaking. That is, if you had one
locus that caused 10% of the increase in activity, and another that caused 15%
of it, that if you combined both of them, you would see 25% of the increase.

How could we test these expectations? What
you would like to be able to do is examine the effects of each of these loci by
themselves, rather than comparing the two strains with all 10 of those
differences. Exactly that kind of experiment is made possible by the generation
of chromosome substitution strains. These are lines that have been generated by
crossing together two strains (let’s call them A and B) and then backcrossing
the hybrids to the A strain, while molecularly tracking inheritance of just one
of the chromosomes from the B strain (and vice versa). Over time, this can
generate a series of lines (one for each chromosome) that have the full genetic
background of the A strain, with the exception of a single B-type chromosome.

Now you can ask exactly the question we
wanted to ask – what is the effect on the trait of each of the individual loci
in isolation? If we start with the background of the low activity A strain, and
look at lines that each have one B chromosome containing a “high activity”
allele, where will their phenotypes lie on the line between the parental
strains?

Well, here’s the surprise. In many cases (like here and here),
the phenotypic effects of these single loci are much bigger than you would
expect – often explaining 50% or more of the difference between the two
strains. This means that if you simply added up their effects you would get
much more than the 100% of the difference you started with. In fact, the range
for behavioural traits averages at ~800%, if you simply add up the effects of the
decomposed individual loci. Even more remarkably, some of the individual
chromosome substitution strains show a phenotypic level that is outside the
range of either of the initial parents, sometimes even moving the trait
distribution in the opposite direction to the “donor” parent strain.

These results clearly show that
non-additive interactions for variants affecting quantitative traits are
common, large and unpredictable. They are a ubiquitous feature of the genetic
architecture of quantitative traits, whether morphological, physiological or
behavioural and are seen across many different species, including worms, flies,
chickens, yeast. Even if such interactions average out across all the
combinations encountered in the population, so that they appear additive,
statistically, this biological reality places a severe limit on our ability to
predict any individual’s phenotype based purely on additive calculations.

In fact, even if we can begin to define
some non-additive interactions by studying the phenotypic effects of various
pairwise combinations across many people, it will still be very difficult to
predict any new individual’s phenotype because, just like each of the distinct
chromosome substitution strains in mice, their precise combination of all
variants will never have been seen before. In a strange way, I find that
comforting – we are each much more unique than a purely statistical overview
would suggest.

This paper is a perfect example of the failure of behavioral genetics and genetic determinism. I agree with Sir MIchael Rutter who a few years ago stated that the behavioral geneticists are on their way to extinction because (a) they consider the environment to be an irritant to be ignored and (b) they have to argue that human beings are the only organism in nature that is exempt from environmental influences.

You can review two articles published in a new journal OA-Autism that I was invited by the editor-in-chief to submit, This on-line journal is in response to Molecular Autism and the print autism journals that are dominated by the behavioral geneticists and molecular geneticists. The mission statement of this new journal is to encourage a healthy debate and argument and challenge the dogma of entrenched psychiatry that has dominated the field of autism research for sixty decades.

I don't think this article agrees with that thesis at all. Just because the genetics is complicated, does not mean disorders like autism or schizophrenia are any less genetic. Clearly, environment plays a role and gene-environment interactions are likely to be as complex and individual as gene-gene interactions. On the other hand, twin studies provide some limits on how important environmental variance across current populations is to variance in risk for the disorder (making a minor contribution).

Throughout the modern world the particular industry involving college essay writers creating will be modifying everyday along with the requirements involving creating are usually modifying very abruptly. Nonetheless, the most popular trend will be almost all of the pupils will still be unacquainted with that exciting actuality.

We all will certainly hand-select the latest continue design and style which will perform greatest on your knowledge degree along with market. The new design and style normally takes your guesswork outside of format along with enables you to simply place the correct content inside the suitable sites.review resume writing services

I'm not asking any of you to make drastic changes to every single one of your recipes or to totally change the way you do business. But what I am asking is that you consider reformulating your menu in pragmatic and incremental ways to create healthier versions of the foods that we all love.easy recipes

I admire the admired facts and abstracts you action in your pieces. I will bookmark your blog and acquire my adolescent kids ascertain up actuality often. I am rather assertive they will ascertain abounding of new actuality actuality than any actuality additional! Phoenix Electriican

The best part of playing an online casino game is the ability of players to move from one casino to another, if there were times when the going gets tough. In addition, any player also has the leeway to choose casinos casino room that provide the best offers, better winnings, appropriate set of rules and most importantly the best gaming experience.

Your psychological function is often a precise miraculous about human growth. Our own capacity to retrain our brain will likely be constantly gracing this pages with the health journals and also nerve whitepapers. Societal nervousness Glendale Blinds in several varieties can occur to be a 'memorized' response to what as their pharmicudical counterpart remembers just as one not comfortable circumstance.

Payouts – Payouts are what you would be interested in at the end of the day. An online casino guide will give you an in depth analysis of the payout structure and how it is made. Since, the payout for online casinos casinos online brasileiros is different from land based casinos, you would do well to know the structure beforehand.

Although casino slots are games of chance, there are certain elements of the game that is important for the player to bear in mind, while aiming to hit the big jackpot. Firstly, it is klikk her widely recommended to limit one's slots bankroll prior to playing.

Excellent blog and informative article. Children encounters the actual forms this also grows the Goblue card actual can forces. It is a method of "seeing" while using the fingers. Rudolf Steiner said "the collection is the subject matter instead of an image of a thing inside the outer world"