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What's hindering progress in biological research?


zensunni

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This question is in no way rhetorical or implying that things should be going faster. I'm simply curious what barriers in biology that people have yet to overcome in order to understand biology.

 

Of course, it's a vague question, so I'll elaborate.

 

The latest I've seen in genetic research was epigenetics or gene expression. So, why does it take so long to map epigenetic outcomes? If we know how elements and molecules react from chemistry, can't we just link an epegenetic expression to it's outcome?

 

That is all I can think of that is not related to genetics or epigenetics. Here's a list of all the genetic/epigenetic related things (or at least, I think they are related):

-Allergies

-Diabetes

-Immunities and germ resistances

 

So, basically, I just want to know where the "frontline" is for biological research. Thanks for any information.

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In all fairness there have been some very important advances in recent years in genetics, mostly through the development of genome-wide SNP chips that allow genotyping at 500,000 SNP's across the whole genome. From there genome-wide association studies have been carried out to start probing common alleles in case-control studies. Using this GWAS approach there have been numerous risk association alleles attributed to a number of diseases, including autoimmune diseases. The barrier with this approach is the need for very high statistical power to detect the small effects that these risk alleles confer.

 

The next step after determining the association is the functional study approach, which is underway on many of these susceptibility loci.

 

Additionally you have the spectrum of variation across the genome that is being elucidated. The impact of copy number variation on the outcome and susceptibility to certain diseases is being investigated.

 

A lot of this work isn't reaching the publics ears, its all rather complex, but I'm still a little surprised that even educated laymen haven't encountered this.

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Well, I do not think that there is anything hindering progress except the complexity of the system itself. However, funds are limited. In many cases the functions can only be studied in detailed in animal models, with all its ethical and financial implications, for instance. Knowing that an area is active/silenced for instance tells you nil about the function of it.

Just to make my point clear, the genome of E. coli has been sequenced years ago, every single (non-essential) gene has been knocked out in a mutant library or another. It is arguably the most genetically accessible organism we have. Yet roughly 25% of its genome has an unknown function. The reason is essentially very simple. To date the way to infer function is to knock the gene out see phenotype changes and ideally also associate it with activity changes. So you knock out a gene, the strain becomes heat sensitive and in other experiments you see that the gene gets induced under heat stress. Ergo: the gene is involved in heat stress response.

However, as you can easily imagine there are virtually unlimited stimuli around that you could test. Worse even cells have the habit to compensate for mutations that you introduce so that most experiments are not clear-cut that way.

Cells have to respond to any number of internal, as well as external changes. The big hope of the postgenome era was that highthroughput data would eventually give a complete view of what is happening in a cell. To date it isn't. You can see what is happening (within the technical restrictions) but the story they tell is sometimes almost as complex as the cell itself.

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One limit is on computing power to model the effects of proteins. We can easily find the sequence of amino acids on a protein, but finding out its shape and function can be extremely time-consuming. As CharonY mentioned, the easy way to infer its function is to eliminate it and watch the effects, but that of course is rather crude and not always reliable. Finding the shape used to involve x-ray crystallography, but it is very hard and unnatural to put proteins into a crystalline form. I've heard of an easier way involving very short x-ray flashes to eliminate the need for forming crystals, but don't know if anything will come of it.

 

I think we can model the shape of a protein from its sequence, but that takes a long time due to the amount of computing power required. Also, other things can affect proteins than just their sequence, which makes the modeling unreliable.

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This bottom up approach is being used in a limited manner (partially due to above mentioned computational limitations), however, even if it wasn't the knowing the structure does not necessarily confer sufficient information about function. It will obviously only work with structures of already known functions.

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There are basically 2 things hindering research and finding in the field of biology.

the first is the absolute scope of identifying literally billions upon billions of genes coupled with their functions.

 

The second thing is the hindrances from ethics, government, and religious groups put upon research in these fields. for example if you want to research something on an animal you must do it humanely, something on humans and it must be ethical.

If we did not have the boundaries of stem cell research we could potentially research a whole new field with millions of possible advances and outcomes, but religion gets in the way.

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the first is the absolute scope of identifying literally billions upon billions of genes

 

Actually we are not even close to a billion genes. Moreover, to date there are only few examples where ethics really inhibit science. Actually, the only one I could think of is the stem cell research controversy. Doing animal experiments as humanely as possible may prolong the protocols a little bit (paperwork beforehand tends to be worse), yet I consider that a fairly small price.

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