text:
Is it the sphincter that flexes when a human pushes a bowel movement?
Of course the sphincter muscle is at the exit point. To use a toothpaste tube analogy, if I want to squeeze out some toothpaste, it does me little to no good to jostle the nozzle; I need to squeeze the tube (which is analogous to the colon) to get the paste (payload) to come out.
So when a human is sitting on the toilet squeezing, is that squeezing flexing of the sphincter, or squeezing muscles along the sides of the colon pushing on it as one's fingers push on the tube to get toothpaste to come out.
If it's the sphincter that's getting flexed, how is that helping get a big log out?

Excellent use of the medical terminology!

The pressure that you apply when you push during a bowel movement derives from an increase in the pressure of the abdomino-pelvic cavity.  You generate this pressure by closing the glottis (the opening to the lungs) and contracting the anteriolateral abdominal muscles (i.e., the external oblique, internal oblique, and transversus abdominus).  This reduces the volume of the (now sealed) abdominopelvic cavity and increases pressure helping to drive feces from the rectum.  This is mechanism is also used to expel urine and during childbirth.
If you do this with the glottis open, then you forcibly exhale because the increased pressure of the abdominopelvic cavity is transferred across the diaphragm and into the thoracic cavity compressing the lungs.


text:
How did viruses come to be?
My question is out of curiosity and got me thinking. How did viruses with the head, tail and tail fibres actually evolve? These viruses look more like machines than biological entities. Are there any theories to how these viruses evolved?

Does a biological entity not look like a machine? Look closer.

A bird looks like an aeroplane too...

If you look from another perspective machines resemble biological entities.

I found a book chapter for you here
Quick summary:
3 hypotheses to Origin of viruses

From pre-cellular world (virus first hypothesis)
From reductive evolution of parasites (reduction hypothesis)
From fragments of cellular genetic material (escape hypothesis)

Drawbacks:

virus require cells (to infect) so how can they come first
virus do not look like known reduced parasites from Bacteria/Eukarya/Archaea
unlikely that genetic fragments form complex viral structures for viral function

Because of these drawbacks, the problem of virus origin was for a
  long time considered untractable and not worth serious consideration

The rest of the chapter looks more in-depth into the 3 hypotheses

Could you summarise in your answer perhaps? It’s preferred here to preferred here to provide links for further information and references, not as the sole point of the answer.

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What determines when a virus becomes a "new strain"?
The reason we cannot find a cure for the common cold is because viruses mutate rapidly. Where do the mutations occur in the DNA/mRNA of viruses and does this have any effect on the protein level? what has to change for the virus to be considered a new strain?

I don't know if this is a comprehensive enough answer, but viruses are taxonomically broken down into order (-virales), family (-viridae), subfamily (-virinae), genus (-virus) and species. This system was developed by the ICTV and is concurrently used with the Baltimore System.
A lot of species contain variations called virus strains. There are two types, serotype and genotype.
In serotypes, the differences are detected by variation in antigens. Genotypes are detected by differences in genome sequence.(1).
The reason a vaccine is difficult to create for the common cold, or upper respiratory tract infections is not only because of the frequency of mutation but also due to the large number of serotypes present.(2),(3).

Virology: Principles and Applications - Carter.
Princuples and Practice of Infectious Diseases - Mendell, et al.
E.g. Olszewska, et al. Development of vaccines against common colds. Br Med Bull. 2002. 62(1):99-111.

It is comprehensive enough for me. You have summarised the points and provided references for further reading. Thanks!

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Foveal ganglion cell density (Tay-Sachs Disease)
I’m currently reading on Tay-Sachs disease and have stumbled upon something regarding the typical “cherry red” macula symptom.
On the one hand it is mentioned that the macula is almost devoid of ganglion cells (GCs) and this actually the reason for the high acuity in this region since there is not obstruction of light [Suvarna JC, Hajela SA. Cherry-red spot. J Postgrad Med 2008;54:54-7].
On the other hand google books gives me numerous textbooks that highlight the fovea as the location of highest GC density and conclude that this leads to the high acuity because a GC only receives information from one or two cone cells.
I guess both are correct but how does one fit the other? It seems contradictory to me.
To be precise some sources specifically mention the boundary regions of the central fovea to have the high GC density, this could leave the fovea devoid of them and therefore combine both facts, however if this is correct I still wonder:
1: Where are the GCs that the cones in the central fovea are connected to?
2: Why is the “cherry red” spot in the macula so large on all the pictures. If my explanation is correct only the tiny area of the central fovea should be red and the surroundings the complete opposite due to the high GC density, right?
I’d really appreciate if someone could shed some light into this.

As you've already mentioned, cells near the primate macula tend to make one to one connections.  Due to this lack of convergence they can be somewhat smaller than normal cells (particularly in the size of their dendritic arbors) earning them the moniker "midget" ganglion and bipolar cells (also P cells).  By reducing the magnitude of photoreceptor convergence onto ganglion cells, the retina sacrifices luminal sensitivity for spatial acuity.  Or put another way, a downstream neuron in the LGN/V1 can be more "certain" about which photoreceptor is sending information when light is bright, but less certain that any information is being sent when light is dim.
The other side of the question you bring up is how the retinal ganglion cells themselves alter the image formed onto the photoreceptor layer.  For those that don't already know, photoreceptors are located at the very back of the retina.  Since they're the major light sensitive part of the retina, that means light has to go through the ganglion cells, bipolar cells, amacrine cells, and all of their associated processes before reaching the actual photosensitive part of the eye.  So, why not put photoreceptors at the front of the eye?  One major reason is metabolic, photoreceptors are tightly coupled with the retinal pigment epithelium which helps to re-process used photopigment as part of the retina's vitamin A cycle.
How can those two factors, a one to one correspondence and a decrease in thickness be present at the same time?  For reference, let's locate a cross section of a primate macula

Dark areas are cell nuclei.  The innermost layer of cells (bottom of the image) are ganglion cells, the next layer of cells up is bipolar cells (the inner nuclear layer) and the next layer up is photoreceptor cell bodies.  you can make out the cilial stalks of the photoreceptors pointing upwards toward the RPE.
From this image we can see a few transformations happening in the macula:

The photoreceptor layer is thicker, up to 7 or 8 cell bodies deep.  This means higher photoreceptor density.
The outer plexiform layer (photoreceptors to bipolar cell connections) is considerably thicker.  A single cone should connect to fewer bipolar cells in the retina, so how does this make sense?  We'll find the answer in #3.
The outer nuclear layer is only one cell thick.  This is the first layer that is actually thinner in the foveal region.  The cell bodies for photoreceptors from tis region have been displaced laterally, and the outer plexiform layer from #2 had to be larger to accommodate this lateral shift
The inner plexiform layer, connections between bipolar cells and ganglion cells, is nonexistent.  Also absent is the ganglion cell layer itself.

So how do these observations resolve your question?  Quite simply, the lateral movement of information from the foveal/macular photoreceptors happens predominantly in the outer plexiform layer.  That buys the inner plexiform layer considerably more space to further spread those signals laterally to ganglion cells, and avoids the problematic situation you suggested of having an extra-thick ring of ganglion cells immediately around the fovea.  The end result is that ganglion cells that respond to photoreceptors in the foveal region of space are even further out from the retina than the bipolar cells they connect to, which are themselves displaced.
As far as why a cherry red spot looks so large, that honestly depends on two factors: the disease or disorder in question and the zoom used.  Bear in mind that the red color comes from, as far as I know, the blood vessels in the choroid itself.  It would therefore not necessarily correspond exactly to the size of the macula, but instead to any area which is thinned in that vicinity.  I think you'll become more comfortable with that idea if you look back at the thickness of the total retina in the above figure and notice that even outside of the foveal region it is still growing thicker.
I think your question shows good instincts, because I believe that if the eye evolved to have a larger "true" fovea then you would get exactly what you describe: a large area of super high density vision surrounded by a region with non-linearly worse vision designed to support the central region.  Instead it appears that the primate macula is just large enough that we have a moderate sized central acute region and a (relatively) linear drop in spatial acuity moving out from it.

+1 This appears to be an excellent and thorough answer, although it is a lot of material to post without citing any primary literature.


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Measuring reverse transcriptase activity in E. coli
Goal: To quantify the HIV-1 reverse transcriptase (RT) activity for a number of mutated RTs.
Idea:

Put RT into a vector in E.coli.
Deliver GFP mRNA to E.coli.
RT will process the mRNA.
The resulting DNA will be integrated into E. coli.
RT activity correlates with the GFP we observe.

First question: Does this logic make sense?
Second question: An alternative procedure?

Wouldn't it be far, far easier to do the whole experiment in vitro instead of inside E. coli? You're introducing a whole lot of problems in your plan, and I'm having a had time understanding how you would get a quantitative result from it. You might want to add more detail about your specific goal.

the devil is in the details here - the logic is okay, but there is no experiment here. Too many unanswered questions.
Are you doing anything specific to see optimize RT activity?
How are you preventing your GFP mRNA from being turned into protein, producing much larger signal than you will ever see from RT activity?
Once its integrated into the chromosome, how will this gene be expressed when it has been suppressed in all these other stages?
How do you know that the plasmid isn't just being incorporated into the chromosome by some other means?
Where is the RT coming from ?  E coli doesn't have the gene. this experiment is very likely to give no results.
When/how does this RT work?  If its some sort of phage RT ( i don't know if there are such things) any sort of viral RT will probably kill the cell the way normally it would.
so many questions before this could work - need to do some homework here.

Thanks for the reply. (1) I should have mentioned that it is RT from HIV-1. (2) I would like to quantify the RT activity in a number of conformations of RT (mutant RTs).(3) I did not quite get why it may not be expressed after the integration? (4) I do not have any idea how frequent the incorporation into the plasmid by other means occurs - any estimate? (5) E.coli uptake of the RT is indeed an issue - but I suppose E.coli can handle the viral RT?

just because the GFP gene sequence is in the chromosome, does not mean it will be copied into mRNA.  You need to have a RNA polymerase binding site nearby upstream of the gene and an intact shine delgarno sequence 8 bp up from a start codon.  how will you get the HIV RT into the e coli?  expressed from a plasmid?  HIV cannot infect e coli - they will just sit in solution until the coli eats it, which probably wont do for your experiment.  Even if it did get inside the e coli, I doubt it would be active in a bacteria at all.... lots of little details to add to your question - feel free to edit.

I'm with @Mad Scientist. Save yourself the trouble and do this in an in vitro system. At the moment, you don't even know if the HIV-RT will express or will be active in E .coli.
Rather, express mutated HIV-RT in T-Cells or Rabbit Lysate. Purify.
Add in a RNA template with the appropriate primer.
Hydrolyze your RNA
Detect your cDNA.

I like that you are considering a simple and standardized approach. However, there are a number of potential pitfalls to consider with this proposal. First of all, what specific RT activity are you trying to quantify? Is the the transcription speed or accuracy, or are you trying to characterize something else entirely? If you are measuring speed, how and what will you measure, reliably and will be reproducible, for speed? If you are going for accuracy, you will need a whole lot of sequencing to check the bases are correct. Both of these can quickly become expensive.
Also, is it necessary to use HIV-1 RT? Since you mention E. coli, would you want to consider using msr, a prokaryotic RT?
Though I've never heard or tried it myself, is it possible to transform mRNA into bacteria? I would imagine that it would be degraded as a natural defense mechanism. You may need to consider some alternative form of gene delivery, such as a standard expression plasmid. Genomic integration may not be necessary to achieve your goal.
As mentioned, you cannot just have naked cDNA to translate a protein. You need at least the promoter, RNA pol binding site and polyA signal. You could take advantage of viral infection systems (a replication defective HIV) to deliver your GFP and RT genes into a mammalian system (like HEK-293 cells), but this adds a lot of complexity and expense that may not be worthwhile.
The last thing off the top, you would benefit greatest from taking advantage of a directed evolution experiment to generate some potential leads. For example, you may PCR amplify the RT cDNA with an error-prone Taq to purpose create RT mutants for use in your assay.
Keep thinking about this, and maybe check the websites of the some of the RT commercial vendors. It is possible one of these companies have already done something similar.


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What is the significance and method behind Ramachandran plots?
My PI showed a Ramachandran plot in class today with minimal explanation, but I'm interested in finding out more. I understand that the Ramachandran plot shows the relation between the omega phi and psi angleson either side of an amino acid alpha-carbon, but there are a few further points I'm confused about:
a.) What do these angles describe? Are they just dihedral angles that show translation around the bond-axis?
b.) Why are these angles important beyond the scope of identifying a secondary structure? Can they be used instead to identify the amino acid components, or only higher level structural units?
c.) What kind of instrument is used to collect the data and how are angles on either side of a single alpha-carbon correlated?

Proteopedia has a nice 3D interactive visualization of the φ/ψ angles: https://proteopedia.org/wiki/index.php/Tutorial:Ramachandran_principle_and_phi_psi_angles

Ramachandran plots show the relationship between the phi and psi angles of a protein referring to dihedral angles between the N and the C-alpha and the C-alpha and the C-beta. As an aside, the omega angle between the C-beta and the N tends to be fixed due to pi-pi interactions.
Dihedral Angles

There are limits to possible distributions of phi and psi angles due to steric clashes between the side chains. Furthermore other limitations from higher order structure will result in the adoption of defined phi-psi angles. Using data from solved crystal structures, it can be seen that the dihedral angles will adopt specific conformations in a protein.
RAMACHANDRAN PLOT from Lovell et al.

Furthermore, it can be noted that some of these conformations relate to specific secondary structures. As seen above, peptides in alpha-helices and beta-sheets adopt a even more limited set of phi-psi angles. Certain amino acids like glycine and proline, which differ from from canonical amino acids have an unique Ramachandran plot.
The angles from a Ramachandran plot are useful not only for determining a amino acids' role in secondary structure but can also be used to verify the solution to a crystal structure. Furthermore, it assists with constraining structure prediction simulations and helps with defining energy functions.


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How fast will cells lyse under hypotonic conditions?
Routinely, lysis of cells with hypotonic solutions is carried out along with some physical (douncing) or enzymatic (lysozyme) method to break open the cells. If one were not to do any of these and just resuspend cells in water, how long would it take to lyse the cells? I was discussing with a lab mate who claimed it would take hours while in my understanding, salt equilibrium should not take very long (maybe on the order of minutes?) and hence, lysis should be done within 20-30 minutes.

this is more of an anecdotal answer but I put sheep blood cells in pure water in a lab that I use in my organismal bio course and they lyse almost instantly.  I have not timed it but I would say less than a minute.

In the case of red blood cells, hemolysis in pure water occurs at just over 1 minute, 30 seconds, according to this paper. (Osmotic Properties of the Erythrocyte, M.H. Jacobs and Arthur K. Parpart, The Biological Bulletin, 1932)


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What exactly are computers used for in DNA sequencing?
I've thoroughly read the Wikipedia article on DNA sequencing and can't get one thing.
There's some hardcore chemistry involved in the process that somehow splits the DNA and then isolates its parts.
Yet DNA sequencing is considered to be a very computationally-intensive process. I don't get what exactly is being computed there - what data comes into computers and what computers compute specifically.
What exactly is being computed there? Where do I get more information on this?

This article goes through computational processes involved in lining up fragments

@jonsca: That looks like we already have "strings" representing the DNA, but how do we get those strings?

It's not the sequencing itself that is computationally particularly intensive, but the assembly of the sequenced fragments into continuous DNA. Also, even a computationally trivial task will take time if repeated billions and billions of times. To get any decent quality sequence, one has to sequence the DNA multiple times (20+). If you have a genome that's 3 billion bases long...

This is a very good question. Is the computation easier if you have 300,000,000 reads of 100 bp length, or 60,000,000 reads of 500 bp in length?

@leonardo That’s easy, in the second case not only do you have less reads (good), you also have longer ones (also good). Even though increasing read length increases computation time, it also increases the quality of the result. In the “worst” case you could just consider those reads as already-created contigs of several smaller overlapping reads.

@KonradRudolph - in that case, the fewer, but longer reads will make computation time faster?

@leonardo Yes. The extreme case, one read which spans the whole genome. See the pattern? ;-)

Computers are used in several steps of sequencing, from the raw data to finished sequence:
Image processing
Modern sequencers usually use fluorescent labelling of DNA fragments in solution. The fluorescence encodes the different nucleobase (= “base”) types (generally called A, C, G and T). To achieve high throughput, millions of sequencing reactions are performed in parallel in microscopic quantities on a glass chip, and for each micro-reaction, the label needs to be recorded at each step in the reaction.
This means: the sequencer takes progressive digital photographs of the chip containing the sequencing reagent. These photos have differently coloured pixels which need to be told apart and assigned a specific colour value.

As can be seen, this (strongly magnified; the image is < 100 µm across!) image fragment is fuzzy and many of the dots overlap. This makes it hard to determine which colour to assign to which pixel (though more recent versions of the sequencing machine have improved focussing systems, and the image is consequently crisper).
Base calling
One such image is registered for each step of the sequencing process, yielding one image for each base of the fragments. For a fragment of length 75, that’d be 75 images.
Once you have analysed the images, you get colour spectra for each pixel across the images. The spectra for each pixel correspond to one sequence fragment (often called a “read”) and are considered separately. So for each fragment you get such a spectrum:

(This image is generated by an alternative sequencing process called Sanger sequencing but the principle is the same.)
Now you need to decide which base to assign for each position based on the signal (“base calling”). For most positions this is fairly easy but sometimes the signal overlaps or decays significantly. This has to be considered when deciding the base calling quality (i.e. which confidence you assign to your decision for a given base).
Doing this for each read yields up to billions of reads, each representing a short fragment of the original DNA that you sequenced.
Most bioinformatics analysis starts here; that is, the machines emit files containing the short sequence fragments. Now we need to make a sequence from them.
Read mapping and assembly
The key point that allows retrieving the original sequence from these small fragments is the fact that these fragments are (non-uniformly) randomly distributed over the genome, and they are overlapping.
The next step depends on whether you have a similar, already sequenced genome at hand. Often, this is the case. For instance, there is a high-quality “reference sequence” of the human genome and since all the genomic sequences of all humans are ~99.9% identical (depending on how you count), you can simply look where your reads align to the reference.
Read mapping
This is done to search for single changes between the reference and your currently studied genome, for example to detect mutations that lead to diseases.
So all you have to do is to map the reads back to their original location in the reference genome (in blue) and look for differences (such as base pair differences, insertions, deletions, inversions …).

Two points make this hard:

You have got billions (!) of reads, and the reference genome is often several gigabytes large. Even with the fastest thinkable implementation of string search, this would take prohibitively long.

The strings don’t match precisely. First of all, there are of course differences between the genomes – otherwise, you wouldn’t sequence the data at all, you’d already have it! Most of these differences are single base pair differences – SNPs (= single nucleotide polymorphisms) – but there are also larger variations that are much harder to deal with (and they are often ignored in this step).
Furthermore, the sequencing machines aren’t perfect. A lot of things influence the quality, first and foremost the quality of the sample preparation, and minute differences in the chemistry. All this leads to errors in the reads.

In summary, you need to find the position of billions of small strings in a larger string which is several gigabytes in size. All this data doesn’t even fit into a normal computer’s memory. And you need to account for mismatches between the reads and the genome.
Unfortunately, this still doesn’t yield the complete genome. The main reason is that some regions of the genome are highly repetitive and badly conserved, so that it’s impossible to map reads uniquely to such regions.
As a consequence, you instead end up with distinct, contiguous blocks (“contigs”) of mapped reads. Each contig is a sequence fragment, like reads, but much larger (and hopefully with less errors).
Assembly
Sometimes you want to sequence a new organism so you don’t have a reference sequence to map to. Instead, you need to do a de novo assembly. An assembly can also be used to piece contigs from a mapped reads together (but different algorithms are used).
Again we use the property of the reads that they overlap. If you find two fragments which look like this:
ACGTCGATCGCTAGCCGCATCAGCAAACAACACGCTACAGCCT
ATCCCCAAACAACACGCTACAGCCTGGCGGGGCATAGCACTGG

You can be quite certain that they overlap like this in the genome:
ACGTCGATCGCTAGCCGCATCAGCAAACAACACGCTACAGCCT
                  ATCCCCATTCAACACGCTA-AGCTTGGCGGGGCATACGCACTG

(Notice again that this isn’t a perfect match.)
So now, instead of searching for all the reads in a reference sequencing, you search for head-to-tail correspondences between reads in your collection of billions of reads.
If you compare the mapping of a read to searching a needle in a haystack (an often used analogy), then assembling reads is akin to comparing all the straws in the haystack to each other straw, and putting them in order of similarity.

Think about it like this. Suppose you own a hundred copies of "The Lord of the Rings", a 500000 word novel. Unfortunately, you have those hundred copies in the form of several million tiny scraps of paper, each of which contains about ten sequential words from the novel. Your task is to take those several million scraps of paper and put them in order so that you can read the novel from start to finish. Suppose for example you find the fragment
stab that vile creature, when he had a chance!" "Pity?

You could then search the other several million fragments for a fragment that overlaps this in some way. Perhaps you find
chance!" "Pity? It was Pity that stayed his hand. Pity, and Mercy:

Odds are extremely good that those fragments go together into
stab that vile creature, when he had a chance!"
"Pity? It was Pity that stayed his hand. Pity, and Mercy:

But maybe not! Maybe either (1) there is another fragment of the novel that has chance!" "Pity? that is the correct overlap, or oh, by the way did I mention (2) some of those scraps of paper contain errors, and you have to also detect and eliminate them.
That is an extremely computationally intensive job. DNA assemblers have the same problem: millions upon millions of of tiny scraps of DNA that overlap, that might contain errors, and that need to be sorted into order by analyzing their overlaps and gradually building up short fragments into longer and longer fragments.

Good analogy, but I would say DNA assemblers have the same problem, not sequencers.

@DanielStandage: Thanks -- I am a computer guy, not a biology guy. :-)

@DanielStandage: Would it be correct to change the word "sequencing" with "assembling" in my question and on the charts in the genome.gov page I link to?

@sharptooth I'm not sure you want to replace the word "sequencing" with the word "assembly" in the question. The answer to your question is that sequencing and assembly are closely related, and assembly is the part that requires significant computational power.

In a genome, there are usually billions of base pairs. However, it's impossible to read all of them in one go. The DNA is fragmented, and the sequence of the fragments is determined. Next-generation sequencing techniques are faster and cheaper, but produce only short fragments (say, 100 base pairs, this depends on the technology). It's extremely computationally intensive to put these fragments back together.
More info: Genome sequence assembly primer; intro in Nature Methods

As you mentioned in the question, current sequencing platforms split the genomic DNA into many small pieces which the machine then analyzes. The product of a sequencing experiment is millions or even billions of short "reads"---strings of A, C, G, and T representing the nucleotides of a single fragment of DNA.
The DNA reads in this form aren't particularly useful. The idea in the first place was to determine the sequence of the entire DNA molecule. This is where genome assembly software comes in---to determine the original sequence of the genomic DNA by finding the optimal arrangement of overlapping reads to reconstruct the original DNA sequence.
Computers are crucial at 2 stages of this process---first, in the sequencing experiment itself, the platform must record and interpret fluorescent signals to generate the sequence reads in the first place; and second, very powerful computers are needed to assemble the reads back into a contiguous sequence to recover the original DNA sequence.

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text:
On the genetics behind caste marriages
I am in India where it is typically a custom to marry within one's caste. The caste system originated with roots in people's professions - Each of priests, carpenters, troupers, etc had a caste of their own. My question is based on the genetic basis of marriages performed within one's caste.

I know the concept of alleles where there is a dominant allele and a recessive one, like the A and O resp. in blood groups and Rh+ and Rh- in Rhesus factors. Is there similar genetic information based on our ancestral profession in our chromosomes? Is the son of a couple engaged in farming better suited to the same profession unless he receives a couple of recessive alleles from both parents?
Generally, there is a lot of unscientific information floating around about these matters. One of the grapevines is that it is genetically better for one to marry outside their caste to create diversity(?). Is such a thing true?

If genetics or biology have any role to play in these fields, I will be happy to know and learn.

I think a fresh answer is needed based on the current research results.

Is the son of a couple engaged in farming better suited to the same profession unless he receives a couple of recessive alleles from both parents?

Not everything is coded in the genome, environmental cues play a very important role in shaping who you are. Profession is just one of those things that is not encoded in genes.
Many people do not continue doing the job of their parents, but they do very well in life.
Also note that, aside from the fact that there is no "agriculture" gene, having a recessive allele does not mean you will miss a certain phenotype.
What is true is that someone who has higher education will probably be more keen to have their kids studying. On the contrary, the kids of someone who is a poor farmer and is barely able to provide for his family will probably not have the opportunity of going to school (let alone university) and therefore will continue to work the land. It has nothing to do with genetics.

Generally there is a lot of unscientific information floating around about these matters. One of the grapevines is that it is genetically better for one to marry outside their caste to create diversity(?). Is such a thing true?

Continuing to reproduce in the same group of people will limit diversity in the genome, and create an accumulation of mutations, which is generally a bad thing. That is why it is very common to have particular illnesses in closed communities.
For instance Amish people have an higher incidence of genetic disorders such as Ellis-van Creveld syndrome (a form of dwarfism)
From The Gene for the Ellis–van Creveld Syndrome Is Located on Chromosome 4p16 - Ruiz-Perez et al., Nat. Genetics 2000

Autosomal recessive transmission of the disorder is supported by
  multiple affected siblings with unaffected parents in families with
  known parental consanguinity. The largest known pedigree segregating
  with EVC is that reported by McKusick and his colleagues in the Old
  Order Amish (McKusick et al., 1964). The prevalence of living persons
  affected with EVC among the Lancaster County Amish was estimated to be
  2 in 1000, whereas the frequency of occurrence among live births was 5
  in 1000. McKusick et al. estimated that the frequency of heterozygous
  carriers in the Old Order Amish is as high as 13% (McKusick et al.,
  1964). All cases of EVC in the Amish at that time were traced to a
  common founding couple, Samuel King and his wife, who immigrated to
  Pennsylvania in 1744.

This is a well known effect, called the founder effect.
As for India, a study on the genetic behind casts has been done a couple of years ago.
Reconstructing Indian Population History - Reich et al., Nature 2010
From the paper:

Haldane wrote 45 years ago that “if inter-caste marriages in India become common, various… recessive characters will become rarer”. However, it has not been generally appreciated that this applies to groups throughout India, and not only to groups in the south where consanguinity is common. We hypothesize that founder effects are responsible for an even higher burden of recessive diseases in India than consanguinity.
  To test this hypothesis, we used our data to estimate the probability that two alleles from a group share a common ancestor more recently than that group’s divergence from other Indians, and compared this to the probability that an individual’s two alleles share an ancestor in the last few generations due to consanguinity. Nine of the 15 Indian groups for which we could make this assessment had a higher probability of recessive disease due to founder events than to consanguinity, including all the Indo-European speaking groups.
  An additional reason why some diseases are expected to occur at elevated frequencies in India is shared descent from a common Indian ancestral population. An example is a 25 base pair deletion in MYBPC3 that increases heart failure risk by about 7-fold, and occurs at around 4% throughout India but is nearly absent elsewhere.

They conclude that:

We have documented a high level of population substructure in India, and have shown that the model of mixture between two ancestral populations ASI and ANI provides an excellent description of genetic variation in many Indian groups.
  [...]
  By showing that a large proportion of Indian groups descend from strong founder events, these results highlight the importance of identifying recessive diseases in these groups and mapping causal genes.

It is very important to understand that this results in no way show a genetic basis for the existence of casts, which remain purely social entities. They rather show that an environmental constraint can influence the distribution of genetic traits, due to a restriction in the possibility of mixing genes in the population.

Indian Castes aren't the only place where this is observed - any relatively small group that does not have children outside will. Ashkenazi jews also exhibit several well studied genetic diseases because they tend not to intermarry.

@shigeta: surely, there are many examples of this. The point is: you can have a geographical founder effect, such as that shown by cases like the populations of Iceland, Easter Island, Scilly Isles, Pitcairn Island (see a pattern there?) and Martha's Vineyard. You can have a social/religious founder effect such as Indian casts, Amish people or Askenazi people (and there's surely more). In the first case people are physically isolated, in the second case they are not and the only constraint to marry an outsider is social.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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How do trees manage to grow equally in all directions?
I was walking down a road with these beautifully huge trees when this question occurred to me.
Large trees with many thick branches have to grow equally in all directions, or they would tip over. Is there some sort of mechanism to ensure this uniform growth? Or is it just a happy coincidence arising from uniform availability of sunlight on all sides? If one branch of a tree becomes too heavy due to many sub-branches, does this somehow trigger growth on the opposite side of the tree?
I have seen that potted plants in houses tend to grow towards sunlight. My mum often turns pots around by 180 degrees to ensure that plants don't bend in any one direction. I assume that this is because sunlight increases the rate of photosynthesis, leading to rapid growth of the meristem.
For trees growing in open spaces, this wouldn't be a problem. But there are many large trees that grow in the shadow of buildings without bending away from the buildings, even though this is the only direction from which they would receive any sunlight. Is there any explanation for this?

Lots of questions are nested here - tree growth and its regulation, reaction wood, heliotropism - might be good to focus it

I was asking the same question when I had observed my tropical plant to balance on the very margin of the shelter as it was becoming more and more tilted against the wall. No magic, one day it just fell over.

Growth in plants is tightly controlled by auxins – plant hormones. Auxin itself usually has an inhibitory effect on growth [EDIT: see comments and Richard’s answer for correction]. As far as I know there is no active control to restore plant symmetry once it has gone awry (but I could be wrong!) but the inhibitory effect of auxin synthesised at the meristem and diffusing in all directions causes a symmetrical pattern of inhibition and activation, forming shoots at symmetrical distances around the shoot apical meristem – this is very visible in the symmetry of the romanesco broccoli:

Furthermore, there are several mechanisms involving auxin which shape the general growth of the plant. The most important ones are:

Apical dominance which causes the apex (the stem) of the plant to grow more strongly than other parts of the plant, ensuring a general centring of the growth.
Phototropism causes the plant to grow towards sunlight. Unlike you hypothesised, this isn’t simply due to more photosynthesis and hence faster growth at the front of the plant facing the light, it’s actively controlled.
Gravitropism is a very interesting effect which causes the plant to grow generally upwards. It’s interesting because the mechanism is actually using gravity: the auxin synthesised at the meristem diffuses downwards in the plant due to gravity, inhibiting the growth in lower regions (but note that in the root apical meristem the effect is somehow reversed).
Hydrotropism causes the plant to grow towards water.

All these effects combined cause the plant to grow in a generally upwards, laterally distributed fashion.

This makes sense. The gravity thing is really interesting! Isn't there also a hormone which induces growth? I can't remember what it's called. Maybe that's more dominant in the root. Again, just hypothesizing.

Giberellic acid is another plant hormone that can induces plant cell growth or elongation, among many other functions.

@Amu There are, yes. I’ve forgotten the exact names though. If I remember correctly different types of auxins have different influence anyway.

Konrad you have the role of auxin backwards - it promotes growth rather than preventing it. I'll try to answer with the stuff you've missed about restoring plant symmetry.

@Richard I’m pretty sure there are auxins for both, and their effect differs depending on other factors (which is why I wrote “usually”). Now, I’m sure you know much more about plants than I do (admittedly, that’s not hard). But the specific function I was thinking of is indeed inhibitory. I can’t remember the name of the particular auxin I’m thinking of, I have it somewhere on my other computer. By the way, just saw that you’re about to start a PhD in Cambridge, congratulations & welcome!

@KonradRudolph Thanks, I was actually going to email you as I saw you were at the EBI. With auxin perhaps you are thinking of the fact that high auxin conc. can stimulate ethylene production, which in turn stimulate abscisic acid, which is inhibitory to growth? This helps maintain apical dominance by preventing lateral meristem formation. IAA is by far the most important auxin and is the one which generally coordinates growth, and its specific action is to promote cell elongation.

I'd be interested to see if there is an auxin which inhibits though.

the direction of sunlight changes as earth rotates so the direction of sunlight is varying...then i think the tree bends where the intensity is more. in the whole day.

There are some other good answers which provide part of the picture, but I think there is a fundamental organising principle which has been missed. Konrad has touched on it in his answer.
The reason trees, and most plants, tend to grow equally in all directions is that they have iteratively generated branching and radial symmetry which is controlled in a feedback loop of the growth promoting hormone auxin and auxin-sensitive auxin transporters. This is an elegant biological algorithm which explains all branching growth.
The things Konrad identifies (phototropism, gravitropism, etc.) serve as orientation cues which help the plant determine which axes to grow along, but fundamentally the process is about auxin gradients. There are exceptions, as others have pointed out in their answers, and they usually result from severe imbalances in the orientation cues.
I'll try to explain the growth process clearly (and it gives me an opportunity to try my hand at diagramming again ^_^)...

Auxin is a plant hormone (actually a class of hormones, but mostly when people say auxin, they mean indole-3-acetic acid) which promotes cell elongation and division. The basic principle which allows auxin to act in the organising way it does is that auxin is produced inside cells, and proteins which export auxin from a cell develop on the side of the cell which has the highest auxin concentration (see figure below).

So auxin gets transported up the concentration gradient of auxin! Thus if you get an area of high auxin concentration developing somehow, more auxin is then transported towards that area. An area of high auxin concentration relative to the surrounding tissue is called an auxin maximum (plural 'maxima').
For most of the life of the plant, auxin is produced pretty much equally in most cells. However, at the very early stages of embryo development, it gets produced preferentially along the embryonic axis (see figure below, part 1). That creates a meristem - a group of cells where cell division is taking place - at the auxin maximum at each end of the embryo. Since this particular meristem is at the apex of the plant, it is called the apical meristem, and it is usually the strongest one in the plant.

So by having a meristem at each end, the embryo then elongates as cell division is only taking place at those points. This leads to part 2 of the image above, where the two meristems get so far apart that the auxin gradient is so weak as to no longer have its organising effect (area in the red square). When that happens, the auxin produced in cells in that area concentrates in a chaotic way for a short time until another center of transport is created. This happens, as the first one did, when a particular area of the tissue has a slightly higher concentration of auxin, and so auxin in the surrounding tissue is transported towards it. This leads to part 3 of the figure, in which two new meristems are created on the sides of the plant (called lateral meristems).
Lateral meristems are where branches occur on plants. If you then imagine this process continuing to iterate over and over, you will see that the branches, as they elongate, will develop meristems at the tips and along the sides. The main stem will also continue elongating, and develop more lateral stems. The root will begin to branch, and those branches will branch, etc. If you can understand how this elegant system works, you understand how plants grow, and why they grow in repeating units as opposed to in a body plan like animals.
It also explains why, if you cut off the tip of a stem, it promotes branching. By removing the apical meristem, you get rid of the auxin gradient and enable the creating of multiple smaller meristems which each develop into branches.
So far I've explained regular branching, but the same system causes the radial symmetry which makes trees (usually) grow in all directions equally...

Imagine taking a cross section through a stem and looking down all the way through it (as depicted crudely above). Just as auxin gradients act to coordinate growth along the length of the plant, they also coordinate it radially, as the maxima will tend to space themselves out as far from one another as possible. That leads to branches growing in all directions equally (on average).
I welcome comments on this answer, as I think its so important to understanding plant growth that I'd like to hone my answer to make it as good as possible.

While I am intrigued by this explanation, it has things backwards. As stated, the model implies that apical meristems are consumers of auxin, when it is well known that apical meristems are the primary producers of auxin (ref. Thimann-Skoog). So, apply a '-' sign to the transport vector so everything goes in the opposite direction as indicated and maybe the story still works.

They don't always.  For example, this apple tree grows just outside my window:

So far, it hasn't fallen over yet.  The reason it grows that way is because all the light is coming from the right side of the picture: the tree leans roughly to southeast, while the building is to southwest of it and casts a shadow on the center of the yard for much of the day.  Also, to the left you can see the branches of other, taller trees that block pretty much all scattered skylight from that direction.

I like the tree. :)

that also happens in areas with strong wind

+1 for the tree! :) I guess the roots would also spread towards the southeast, so that the center of mass of the tree remains above the roots.

As shown in the answer by @IlmariKaronen, that is not always the case. most trees grown next to the shady sides of buildings tend to lean away from the building. Some trees can stand more shade than others, and these will send branches into the shade of buildings. They never grow as dense or robust in the shade. The reason for the plants growing toward the light is Phototropism. When light hits the plant stem, the auxins that determine the length of the stem are destroyed, decreasing the amount of growth on that side of the stem. When this happens, the stems bend toward the light source from the imbalance of auxins in the stem. The reason that the shady side is weaker is that all trees rely on photosynthesis for their energy. Of course, the side without direct sunlight will not perform as much photosynthesis, and so has that much less energy to grow with. Also, many large trees are imbalanced, sometimes all of the weight on one side. The roots hold them up.


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How do baby animals that primarily subsist on cellulose get their initial gut flora?
In the case of mammals like giraffes and koalas, is that bacteria common on the plants they eat so when a baby starts to try to stick something besides its mother's milk in its mouth, it can't digest the cellulose at all the first time, but along with the cellulose, into its mouth went some cellulose-digesting flora that then begins a lifelong colony in the animal's gut? Is that about how it happens?

I would not expect this to be any different than other animals - they get the flora from the environment. Key components of the environment for newborns are:

Birth canal
Den / living quarters
Skin / fur of mother, especially near the teats
Diet
Feces of family members (animals sniff this and aren't so clean)

I don't know about ruminants, but baby rabbits (and presumably other lagomorphs) apparently acquire the necessary intestinal flora by consuming their mother's cecotropes.[1]
[1] Johnson-Delaney, C.A. (2006), "Anatomy and Physiology of the Rabbit and Rodent
Gastrointestinal System" (PDF)

We now know that humans acquire not only their initial gut flora but also that of the skin from swallowing and touching mother's vaginal mucus. This doesn't apply to Caesarean birth, however.
For reference, see my answer at skeptics: https://skeptics.stackexchange.com/questions/9994/do-c-section-born-babies-have-worse-immune-systems/10078#10078


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Possible? When a pregnant woman suffers an organ damage, fetus would send stem cells to the damage organ to help repair it?
I am quite sure that there is this blood-placental barrier between the mother and the baby so that nothing (except a type of antibody) can pass through it.
But I remember reading somewhere that when a pregnant woman suffers an organ damage, fetus would send stem cells to the damage organ to help repair it.
Anything to support that?

Lots of hormones, nutritive molecules etc pass the blood-placental barrier.

while this is true, it is also possible that the child's cells, which circulate for years after the baby is born, can also cause autoimmune disorders.  its not a panacea, but on the hand nothing goes to waste in biology either.  If you haven't already heard the radiolab podcast on this, i highly recommend it. http://www.radiolab.org/blogs/radiolab-blog/2012/apr/30/fetal-consequences/

Fetal RNA - mRNA and microRNA - has been detected in maternal blood as shown in this report. Here's a second report showing how fetus gives back to repair the maternal myocardium - fetal cells traffic to an injured maternal myocardium and undergo cardiac differentiation.

The second link is broken :((

I heard that as well and was skeptical at first, but apparently there IS science to support it- http://mblogs.discovermagazine.com/80beats/2011/11/21/helpful-mouse-fetuses-naturally-send-stem-cells-to-mom-to-fix-her-damaged-heart/ Officially found with mice, but it supports how some women that suffered damages while pregnant are sometimes found with their children's cells still in their body, in the formerly damaged organs, many years after birth.

Just to add: I recently discovered that the first published account of "feto-maternal trafficking" was as early as 1893! https://www.ncbi.nlm.nih.gov/pubmed/16620961


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What's the use of DNA sequencing results?
Suppose I sequence DNA of some organism (a human perhaphs) and now I have the entire DNA "string" - the sequence of nucleotides.
What's the use of that? It's just a "string" where nucleotides encode something but I have no idea what they encode specifically. So to me it looks like some raw data, just represented as a sequence of elements.
How is having the entire DNA sequenced useful?

Whoa, quite a complex question. I’ve tried to restrict my answer to a single example (not very successfully).

Just to clarify the question: are you asking what the "man of the street" can learn by having his genome sequenced or are you asking what a team of scientists can learn by sequencing the genome of a species?

@nico: I guess what I ask is "what's the use of the sequence when you don't know which part does what".

It's just a "string" where nucleotides encode something but I have no idea what they encode specifically.

It sounds like you are describing a computer program, represented by a string of bytes on the hard drive.
Unfortunately, the analogy breaks down very quickly because DNA is vastly more complex and a lot of aspects are still poorly understood.
But the basis is the same: a string of symbols encodes information. In the case of DNA, different parts encode different things in a different manner.
The elephant in the room are of course coding sequences: stretches of DNA, contained in so-called “genes” – which code for proteins and other stuff.
Coding sequences use a fairly simple encoding schema that’s known as the genetic code, decoded in 1961. The genetic code has the nice property of being (almost) universal across all species, and easy enough for a child to understand:
Three consecutive DNA base pairs form a codon. Each codon stands for one amino acid (except for a special “stop codon”). Amino acids form so-called polypeptide chains – proteins. There are codon tables, just as you have manuals for assembly mnemonics in computing:

Unfortunately, it’s not trivial to know where genes are on the genome. Just by eyeballing the sequence there is nothing to distinguish one stretch of DNA from its surrounding. But there are certain recognisable stretches of DNA (“motifs”) which we can use to locate genes and other interesting regions.
Grossly simplified, a gene is preceded by a promoter region which is highly conserved between species (but gene-specific). Once you’ve identified one species’ promoter, you know it for other species. Furthermore, all promoters share highly similar elements, for instance the TATA box – literally the occurrence of “TATA” in the genome.
Of course, just looking for occurrences of “TATA” would yield vastly more spurious hits than actual promoters but combined with other information you get a gene model – a statistical machine which can tell you with high confidence where on a genome the genes are located.

Once you have found the genes in a sequence which you can trivially translate to amino acid sequences, you can try to form inferences about the function of the proteins (a protein’s function is an almost-direct consequence of its sequence). Unfortunately, discovering the function of a protein from its sequence alone isn’t possible but we do know the functions of many proteins.
When we now look at a genome and find a mutation in a protein-coding gene we can infer that the function of this protein is probably modified. Most mutations are so-called deleterious mutations (e.g. by deleting a single nucleotide you get a frame shift in the codons, and all the subsequent codons no longer make sense), meaning that they destroy the protein’s function.
Other, much rarer, mutations modify the protein’s function, making it more or less efficient, or giving it another function altogether.
In the simplest case (but these are rare), a single such mutation can explain a complex phenotype. This is known as a Mendelian trait and can be used to explain a phenotypes such as eye colour, but also hereditary diseases.
Usually, though, it is merely one of many adjusting screws which skew your susceptibility to a certain phenotype in one direction. For instance, you might be slightly more susceptible to breast cancer or diabetes.

This is one use of the DNA sequence, there are many more; in the last decade, we have realised that regulation of gene activity plays a much larger role than anticipated, and most research today looks at regulatory patterns on the DNA level. This is also done with sequence data, but there doesn’t appear to be a simple schema analogous to the genetic code to understand regulation. Instead, it’s a complex interplay of many completely unrelated mechanisms.

By the way, this doesn’t even touch on RNA-seq and ChIP-seq which technically are also sequence data results but with a twist.

There is a whole lot you can do with genome sequences, I'll focus on a specific example here.
A gene encodes for a protein, but as long as you have only the DNA sequence of that gene you can't easily find out what exactly the protein that is encoded by the gene does. There are ways to predict certain characteristics of the protein, but you really want to have large amounts of the protein itself to be able to examine it in detail.
Having the sequence of a gene allows you to put that gene into other cells, often bacteria but also yeast cells, insect or mammalian cell lines. Using those you can then mass-produce the protein, purify it and start to study its structure and function.
Getting the protein without a sequence means you need to extract it from whatever organism produces it. This is only feasible for proteins that are produced in very large amounts, and even then it probably means you'll have to process a large amount of material to get enough protein. Having the sequence available enables us to study a lot more different proteins than we could by purifying them from their original source.

As the others mentioned, identifying and annotating protein coding genes is an important part of any genome sequencing project. However, there are a variety of other things you can do with a complete genome sequence. You can annotate other types of features, such as transposable elements and repetitive sequences, you can sequence mRNA and map it back to the genome to get a measure of gene expression for a particular tissue, and you can look for variations in the genome such as single nucleotide polymorphisms (SNPs), copy number variations (CNVs), and other large scale variations. If other related genomes are available, there are a lot comparative genomics questions you can ask about large-scale conservation (synteny), DNA substitution rates, relative DNA composition, etc. We are really just beginning to scratch the surface as to the wealth of information a genome contains and how that information is biologically processed.


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What is the highest competency possible for E coli?
I am looking to find a highly competent E coli strain.  I am making a library of a ~6.6kb plasmid and I am not getting high enough efficiency.  Does anyone have a suggestion of a strain/protocol with ultrahigh efficiency (>1010).

What strain did you decide on? Have you decided on an accepted answer?

This is a great question as I just made my own "homebrew" chemically competent cells.
There are a vast variety of E. coli strains that are commonly used for cloning. They may be transformed chemically by heat shock method, or electrically by electroporation (a brief summary may be found here). These can be made in the lab manually, or purchased commercially from reputable vendors (I recommend Invitrogen/Life Tech, NEB, Promega).
Chemically competency is achieved using Hanahan's method or some a variation thereof. The method involves washing the bacteria in a series of buffers containing various di-valent cation chloride salts (CaCl2, RbCl2, etc). Commercially available E. coli are sold as "regular" and "ultra" competent, ranging from 106 to 106 for regular, and the highest I've seen is 1010 cfu/µg DNA. For maximum efficiency, especially since a small plasmid such as yours will be easy to transform, electroporation is a more efficient technique, but requires specialized equpment. Electroporation can yield >1010 cfu/µg. For standard cloning practices, regular or high efficiency chemically competent E. coli are perfectly adequate. Since you mentioned you are creating a library, you certainly want to go with ultra high efficiency chemical transformation or, if you have the necessary equipment, electroporation. I have not seen electroporation efficiencies reported > 5x1010.
Transformation efficiencies are standardized by reporting a rate as the number of colony forming units (cfu) per µg of some control plasmid, typically pUC19. Transformation efficiency is very sensitive to many factors, including heat shock time, cooling times, thawing time, amount and size of plasmid DNA. All things being equal, the size and quantity of DNA are important for your purposes. Transformation efficiency generally increases with quantity of DNA, but there is a saturation point, and evenetually having too much DNA decreases the yield. Also, efficiency decreases linearly with plasmid size. For example, pUC19, the control vector, is ~2.7 kbp, and your library plasmid is ~6.6 kbp, so you should expect for the same mass of DNA you will have lost 60% transformation due to plasmid size. This loss is due to the physically larger size of DNA being more difficult to move into the bacteria.

I have heard that Epi300 electrocompetent cells (1) from Epicentre are very efficient: > 1 x 1010 cfu/µg of pUC19. Dan Gibson used them in his paper for the synthesis of the mitochondrial genome (2). We were also thinking of using them for our assemblies, but they are pretty expensive.
1. TransforMax™ EPI300™ Electrocompetent E. coli
2. Chemical synthesis of the mouse mitochondrial genome, Gibson et. al.

That's quite the downside to electrocompetent cells. They're very expensive (so are ultra high chemically competent cells). Then again, they're only recommend for libraries and assemblies, so next to all the screening, purification, genetic manipulation and sequencing you will be doing, this is a minor cost.

still this is the better answer - sometimes you have to pay a bit more if you are on the cutting edge.  chemically competent cells are usually not as efficient.

@shigeta - actually there are chemically competent cells that can achieve 1x10^10 cfu, and they're just as expensive as electrically competent cells.


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Is it possible to grow any kind of plant soilless (hydroponics)?
Hydroponics is a subset of hydroculture and is a method of growing plants using mineral nutrient solutions, in water, without soil. [wikipedia]
My question is if is it possible to grow any kind of plant soilless (hydroponics)?

Carrots and other root vegetables do not do well in hydroponics with LE(CSG)A ( light expanded [clay, shale, glass] aggregates).  Its not an issue of them developing but being drowned out.   The solution in industry has been to use dual-zone beds ( half peatmoss/potting soil and the other half LECA with a canvas sheet divider and careful attention to water levels ).

Are you asking about "all kinds of plants" or "some kinds of plants"?

Yes, There are a few i know of, a quick "air plant" google search will get you quiet a lot.
wiki 1
wiki 2
Edit: I just glanced through the hydroponics article, and now I wonder if my answer actual answers your question.

Thanks for quick reply, I didn't know about the title Epiphytes. I still think, there are maybe for some reason  "impossible to grow without soil plants" but I don't know. I want to wait and search a little more.

from what i have read so far, plants do not need soil to grow. You can grow potatoes in a pot just filled with water, they don't need the soil as long as they get the nutrients and oxygen from their surroundings.

....so I dont understand what you are trying to ask. @pikk

Yes it is possible, and as far as I can see, there should not be any plant which would be impossible to grow in a such an environment, just more or less difficult, although this is just my speculation.
I have myself grown tomatoes from only a liquid solution of minerals and nutrients, but you have to change the solution from time to time to prevent bacteria and fungi growing starting to grow in it. The reason why this is not a method used in industrious growing is because it is a lot more expensive than using soil and fertilisers, and more work.

Do you have a source for the fact that it is a lot more expensive and requires more work ? Thanks.

No, I was just thinking in general terms. Small scale use I'd say definitely (based upon my own experience) more work as you'd have to refresh the water constantly and probably more expensive depending on your sources of the required minerals. But I would assume that there are a lot different relationships if you scale things up enough.

Aquaponics ( aquaculture w/hydroponics ) dramatically simplifies water treatment/maintenance at the cost of not being able to grow high acidity or high potassium plants.  Otherwise 1000 gallon systems take only 15-30 minutes a day to keep maintained.


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Source of DNA sequences
I'm working on a project where I am taking DNA sequences and translating the codons into musical notes. I have some good ideas of how to do this, I'm just not sure what sequences to work with. My case study and a lot of my initial research showed that anything larger than a protein is too much to work with for now.
So my question. Where can I find protein DNA sequences in some standard format. I've looked at NCBI but I have no idea what I'm looking at or if I'm downloading the right stuff. Is there a link that I can go to that will have a listing of a bunch of difference protein sequences that I can download?

Huh, interesting idea. Might be a good way to flesh out some patterns, since humans are better at hearing patterns in music than seeing them in abstract symbols.

I just noticed the question is from 2 years ago. Are the results of your work available somewhere online?

GenBank and RefSeq have a huge collection of DNA sequences that can be downloaded in Fasta format. GenBank makes it very easy to search for sequences (for example, using the organism name) but will often have redundant data and varied types (everything from whole chromosome sequences to mRNAs to gene sequences to ESTs). RefSeq has much cleaner, non-redundant data but might take a little more effort for you to find the sequences you want. Depending on whether this has any effect on your project, you might want to consider that. On the RefSeq page, under the FTP menu you can click Genomes to see which genomes have RefSeq data available. The Fasta sequences for a particular genome will be stored in a dedicated directory, possibly subdivided into further directories by chromosome. What you want are the Fasta files (ending in .fa, .fasta, .ffn, or something like that), keeping in mind they may be compressed (.fa.gz, fasta.gz, etc).
Alternatively, if you already have a specific organism in mind, then you could do a Google search to see if the genome for that organism has been sequenced. If so, there is almost always a dedicated website where you can download DNA sequences for that genome.

I've been to those sites, I just don't know where to go to get a list of sequences. I want a wide variety of sequences so a list or the root of a directory would help the most. I'm not looking for a specific sequences. I just need a lot of them.

In GenBank for example, if you search for Vitis vinifera, you get 131k reults. If you click the "Send to" button, select file, and then Fasta format, it will allow you to download a Fasta file with the sequences. If that's not what you're looking for, you're going to have to provide a little bit more detail before we can help you.

I don't know a lot about biology. I'm researching different ways to encode data to help with perception of the data. So I know alot about information, just not DNA. I need a bunch of sequences to use as tests on my DNA to music tool.

Is 131k sequences enough?

Ok this is a good answer I did what you said and have exactly what I wanted, actually a little better now that I see I can search specific organisms.

A standard format would be the FASTA format.
If you have a few proteins of interest that you would like to look at you can simply select 'Nucleotide' at the top of the NCBI page, enter your protein's name and then press the FASTA button below each result you are interested in.
If you just need a large dataset of DNA sequences that code for proteins you could for example use the 'nt' blast database.
(I believe this is only protein sequences not entirely sure though, I thought it would be easier to get)

I've seen that format too, is there a place I can go and download a lot of sequences in that format?

good answer. I'll download the 10 gb file and get to work haha. Thanks

Since I can only add comments here: I agree with Daniel Standage that Genbank is the more suitable ressource but how do you ensure there that it's only protein coding DNA? You could limit your search for mRNA on the right which should throw out some non-protein results however then you have mRNA sequences which of course differ from the DNA sequence they originate from. If that is not an issue I'd say go for that.

This suggestion helped a lot

This is more of a comment, but too long to put in a comment box, so I'm putting it here.
This is a fun idea you're doing. I have a half baked idea (assuming you're looking for input) if you want to explore it further -- or not ... by the time I finish writing this, I might realize it's too silly, but still ... let's see.
It might be fun to take the sequence of two organisms, let's say mouse and human and align certain regions to each other -- imagine this is like playing a piano where the "left hand" might be the mouse sequence, and the "right hand" is human.
So, say you take a gene that are shared in both, like CCND1. You can align them against each other and you'll find large portions of the sequences are common (with some mismatches, obviously). In these regions, the left and right hands are playing together (different octaves.
You'll also find gaps in the alignments where you'll have a stretch of "mouse only" or "human only" sequence, and in these regions the left or right hand play alone (solo).
For instance, say the two alignments look like this:
mouse: CGTGGGAGGCTCTTGAGCCTGGAAACACTATCGCAGTTTGTACGGAATGCACTTGTTCTTTACAAAAGG
human: CTTGGGCGACA---GAGC---GAGACTTTGTCTCAAAAAAGAAG--------------------AAAAG

In this case, you see stretches of the alignments where the mouse (left hand) will be playing a solo, and other times the two hands play in "harmony."

The tool I'm making can be used to do this without any modification. Cool idea though. I may make a blog for it once I finish the hard parts and post it to this QA just for reference.

Here's the tool http://dnasongs.brandonhamric.com. The alignment part is left out because of some bugs in playing multiple parts at once, but oh well.


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Is there a dominant gene for right-handedness?
Has there been any definitive research about handedness being genetic? Also, why is right-handedness clearly dominant in humans? I'm interested in evolutionary theories, as well as any molecular explanation (if known).

I'd also curious as to what degree other mammals/animals show any handedness. Should it be a different question altogether, or should I edit this one?

You might as well ask a new question.

@LanceLafontaine yeah I'd be inclined to keep them separate :)

There is a lot of information at OMIM  - too much to summarize here - regarding the genetics of handedness and links to which hemisphere of the brain dominates (in an individual), to schizophrenia (slight association with non-right-handedness), and to hair whorl patterns on the scalp. References are provided at the above link. Basically, hand skill appears to be a complex multifactorial phenotype with a heterogeneous background.

OMIM (online mendelian inheritance in man) is a good example to explain how complicated heritability usually is.  Simple Mendelian traits, where smooth or wrinkly peas will have wrinkly offspring, allow us to segregate individuals with pure dominant / heterologous and pure recessive traits.  When we have done so the chance of inheriting the trait can be predicted precisely (i.e. 25/50/25%).
The number of simple mendelian traits which are observed in an individual are pretty doggone rare. Even things that are dominant like dark hair are usually more complex.  I'm of 100% japanese descent, but my son was born with blonde hair and it looks like it won't go darker than mousy brown - black hair is not really dominant, he will have a color between my wife's and mine.
I also need to make a distinction between mendelian traits, which are observed in the individual organsim as opposed to specific DNA variants like a single site mutation (A->T, C->T etc)  which are usually mendelian.
The rarity of mendelian inheritance is because there are so many checks and balances in our gene networks that no single gene is solely responsible for any function.  Medical research has discovered many single mutation (Mendelian) diseases, but they are very rare in practice.  There are single mutations that cause diabetes like systems (called MODY diabetes) for instance, but more than 99% of diabetes are not caused by these mutations.  A single mutation advantage is quickly adapted so that single mutations cannot nullify the advantage.
Common mutations that cause diseases or other disadvantages are likewise relatively quick to disappear through adaptations.
I once saw the old text bound copy of "Mendelian Inheritance in Man" It was not a small book, but it seemed to me that when I paged through it, when you look at traits like 'handedness'. there were only a few hundred simple mendelian traits identified.  Most of what we are is the result of the interplay of several or even many of our ~30,000 genes.
For an example of how this works, see this article about what happens to new fly genes.


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How extensive is CD47?
CD47 aka the "don't eat me" signal has recently been claimed to be expressed on all tumor cells. This doesn't seem to corroborate with other cell-biology experiments. On what other cells is CD47 expressed?

I don't know how extensive. Let's run a simple data query and find out: Go to GEO at NCBI. In the "Gene profiles" window, type CD47, and hit enter to launch the query. At the top of the resulting page, use the link labeled "Limits" to restrict the 7000+ results to human by entering the term "human" in the "DataSet organism" window. So, there are 3700+ results. Look through them to get an idea of which cell types and under which conditions CD47 is expressed.
Let's try a second method. Go to the BioGPS portal. Enter CD47 in the appropriate window and run the query. From the results, select the row with ID # 961 as this represents the human gene CD47. The resulting gene expression/activity chart for Hs (human) will show you in more general terms where CD47 is expressed.

I can't give a comprehensive answer to this, but the CD proteins are found on white blood cells of various types.  If you think about it its impossible that a surface protein could be only observed on cancer cells as cancer is a cell line which is a reproductive dead end.   You can see on the geneatlas box on the lower right side of the page - its gene is expressed, at least to a small amount, on nearly every major tissue type.


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Measuring the density of surface antigens
I'm trying to get a sense of the variety of methods used for determining the number of cell surface antigens and receptors. This is notably different from determining the affinity of these surface markers.

Are you looking for extraction techniques, or techniques to analyze your extracted molecules?

Do you mean to count numbers of both antigens and receptors in live cell?
Possible ways:

FRET (unlikely to work)
imaging of receptors with single molecule resolution
western blot to roughly estimate amount of receptors
single cell proteomics techniques (not very suitable)

FRET could work. He'd have to tag both the antigen and antibody, though He probably would be better off with standard fluorescence spectroscopy.


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Solution based measurement of Solvent-Accessible Surface Area of macromolecules
The Solvent-Accessible Surface Area (SASA) is a valuable metric for looking at protein folding and protein-protein interactions. However, this measurement is typically done by calculating the SASA from a solved (and generally static) structure.
Chemical probes like diazirine and hydroxyl radicals show some bias regarding where they tend to bind. I'm realizing while I'm writing this question that NMR is a perfectly valid method to determine a solution based structure and then calculate the SASA. Similar strategies has also been used to examine structured RNAs. I'm curious about the variety of these methods and how accurate they are.

Determining an NMR structure is a lot of work, it's not something you would do just to get that information. There are ways to identify which residues are solvent accessible by NMR (e.g. SEA-TROSY), but they don't give you the area.

I only know of one method, but here it is.  You create a sphere the diameter of the VdW radius of water, and then 'roll' it along the surface.  I know this as a Richards-Lee surface, wikipedia has another name for it.

This looks complicated, but its not.  you move the probe sphere along the surface of the molecule in the XY plane until it just touches the vdW radius of the protein, keeping the center of the sphere as the surface, all the way around the molecule.  If you like, you can color the surface by the charge of the position too, which is useful for discussing solvent interactions.
Then you translate along the z axis and do another contour until you run out of protein.  Apparently jmol and other packages will do this for you.
Wikipedia references a more mathematical method LCPO, which I am not so familiar with.
Is this accurate?  As usual with such calculations its more of a guess than an answer.  You can do the calculation on any structure or any ensemble of structures (like NMR gives).  It doesn't understand how the molecule might be flexible or dynamic.  If you read up on your physical chemistry you see that proteins breathe and can allow diffusion into the core rather readily.  If I recall right, you can get rather large molecules quenching heme flouresence in hemoglobin at room temperature.
If you are looking to dock 2 proteins, SAS might be more useful.  Its an important piece of information, but not an ultimate answer.  I'm afraid with proteins that doesn't happen so easily.
@bobthejoe asked about SAS for which no structure exists.
This is an extremely difficult thing to even guess at.  The non helpful answer is that the surface of the protein goes as the cube root of the molecular weight of the protein.
By getting a solution of the protein and shooting it in a syhcrotron, you can get a mean radius of gyration pretty easily which will give you an ellipsoidal volume (and surface area) for a protein.  Again most of the particulars would be lost and this could easily be off by 25% for an irregularly shaped protein.  For a regular globular protein it might give an answer similar to the power law above.
I have seen physical chemistry experiments that look for changes in osmotic pressure when the salt concentration in a solution of the protein changes substantially (Adrian Parsegian's work at NIH in the late 80s).
I doubt you will find any of these answers useful as their mean error is going to be very large (20-200%) and also assumes the protein is soluable and amenable to the experimental conditions.
Solvent probes can help too.  For instance exposing the protein to D20 then doing mass spectroscopy on the protein. This is still only going to give you a general idea of how much of the peptide is surface exposed.  Protein structure is still pretty necessary to getting any accurate measurement of SAS I think.

This is the mathematical calculation of SAS. Unfortunately, it doesn't get to the answer of how does one measure SAS sans X-ray/NMR structure.

sorry i missed this.  i have added something about this.  this is difficult to do as you might have guessed.

I don't think SAS is a well-defined observable. (I like the work by Bertil Halle on this and related problems.) You can measure correlates to SAS that have been calculated according to known structures, using something like the rolling sphere algorithm that @shigeta describes.
I think the best-parametrized approach would be differential scanning calorimetry. Because a lot of proteins have had their folding studied with this technique, a DSC curve can be directly converted into changes in polar and nonpolar SAS. The total SAS would be a sum of those two quantities.
The only ready reference I could find for this is here: https://web.archive.org/web/20100228041032/https://www.bio.cmu.edu/courses/03438/LecS00/DSC.html
I think most of the analysis was worked out by Ernesto Freire. Basically, the idea is that surface accessible hydrophobic areas organize more solvent (and have a larger entropic footprint) than the polar areas. Since a DSC trace (for a two-state folder) can be deconvoluted into $\Delta$H and $\Delta$S components, it can be mapped onto $\Delta$ASA$_{folding}$. I wouldn't trust this for anything that was non-two-state or that bound cofactors.


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Has there ever been an attempt to create nutritionally tailored food for adult human consumption?
For all domestic animals, and for all animals kept in laboratory, complete and precise composition of perfect food is figured out (cat food, dog food, cattle, rats, laboratory monkeys and apes) -- which contains precise composition of carbs, fats, proteins, aminoacids, minerals and vitamins. Everything is known. Convenient dry cat/dog food contains exactly that. Animals are healthy on this food.
The composition is also known for human babies. This is manufactured as "baby formula". Everything baby's organism needs to be healthy (and to grow).
How let's take human adults.
Was ever attempt made to create "dry human 'dog-food'"? This sounds stupid, but there are emergency situation in which such food can come very useful.
So my question is, is there anything special in human biology that prevents creation of complete "dry human food" that contains everything our organism needs to be healthy ?
Or it was created but tasted so disgusting that nobody would eat it ?
Or it actually exist somewhere ? Just curious.

Why would it have to taste disgusting? Dog/cat/rat/etc. food does not seem to taste disgusting to dogs/cats/rats/etc. Anyway, soldiers have rations and astronauts too!

The Monkey Chow Diaries may be a relevant, if not entirely scientific, experiment.

Military must have tried to develop such things. What about military energy bar type rations?

@Memming: see links in my comment

Military has meals ready to eat (MRE) that come in a variety of flavors, but are quite far from the granule type dog food that you are thinking of

I think "monkey chow" is the answer. Note that in real labs and zoos, monkeys get a lot of their calories from monkey chow, but are still fed fresh vegetables to provide fiber, obscure phytonutrients, and entertainment.

Re: baby formula (aka "baby milk"), you should know about the Nestle boycott.

I know this post is quite old, but more recently Huel appeared. This claims to be a complete food for humans.

Yes.  Rob Rhinehart has developed what he refers to as "a food substitute intended to supply all of a human body's daily nutritional needs, made from powdered starch, rice protein, olive oil, and raw chemical powders" which he calls Soylent.
It was developed and tested largely in 2013, crowdfunded late 2013, and is expected to start shipping in 2014. Tests of at least 30 days with no other food intake have been performed, though this is being marketed as a food and not a medical aid of any sort, so does not require FDA testing.
Even if this didn't exist, there are numerous "complete" human diet foods meant for medical use.  These are mentioned in an article about soylent:

Jay Mirtallo is a professor of pharmacy at Ohio State and the immediate past president of American Society for Parental Enteral Nutrition, which focuses on the science and practice of providing food to patients through both intravenous injections and feeding tubes. His main concern with Rhinehart's plan is that he's making the concoction himself, rather than buying it from reputable suppliers.
"He basically made medical food," Mirtallo says. "If he wanted to switch to a liquid diet, those are already available."
Indeed they are. Companies like Abbott Nutrition and NestléHealthScience sell dozens of medical food products, intended to be used by patients under medical supervision and administered intravenously, orally, or through an incision in the stomach.
"They’re very complex products, in terms of making sure you get them in a form that’s palatable but that stays in a form that’s bioavailable to the body," Mirtallo says. "Some of the products are very difficult to get into a liquid form and may lose their potency when they do that, or could interact with other substances that keep them from being absorbed completely."

Rob appears to be attempting to make a consumer version, and so far reports are positive.
But even if you don't trust Rob's mixture, there are countless medically complete nutritional foods that are FDA approved, though not generally available at the supermarket.

I'd like to know the difference in price between Soylent and the proper medical food from "reputable suppliers."

Shortest answer: there's nothing special in human biology, you could totally make it
Short answer: Bachelor chow!

I would totally buy this stuff if they made it. The closest I have now to bland, flavorless, zero thought/effort food is Wheaties.
longer answer:
Seriously though, dogfood for humans wouldn't be that hard to make. If you just took everything from the RDI guidelines (the Recommended Daily Intake from which they calculate the percentages you find on food labels) and mashed it all together into a thick brown paste you would get all of the macro and micro nutrients that you theoretically require. Precise proportions are irrelevant because:
a) everyone is a little different, and
b) to some extent, our bodies are able to fine tune our digestive tracts to fit our specific diets (presumably this tuning would occur even faster if you ate the exact same thing for every meal). You're a mammalian omnivore. Enjoy it!
You probably shouldn't try to live on something like this for the rest of your life, since there's plenty of research suggesting that there are other micronutrients, such as phytocompounds (i.e. plant stuffs), that are poorly understood but may be beneficial to humans. One thing to note here is that any health claims about any antioxidant that is not on the list of essential vitamins (vitamin C is an antioxidant on the list) are almost certainly bunk and/or hokum.
The upshot is that you would only need, at most, utterly minuscule quantities of these miscellaneous micronutrients. You would be fine(ish) for at least a few months. For related reasons, your statement:

The composition is also known for human babies. This is manufactured as "baby formula". Everything baby's organism needs to be healthy (and to grow).

is largely correct but somewhat flawed. While it is true that many babies are raised solely on formula and subsequently turn out just fine, there are some things that you can only get from mother's milk. For example, the mother passes on components of her own immune system to her baby through her milk, which then help to strengthen the baby's own immune system. These are the kind of subtle but useful compounds which are encountered in a "natural" diet but which could never realistically be included in people chow.

I think you do not cover the aspect of whether such thing would be bearable -- by taste.

@Andrei By asking about the "bearability" of the taste you're veering away from biology and towards psychology. Here's how I think about it: I don't know if you've ever owned a dog before, but they like people food. A lot. And the more devious members of the species will scheme quite a bit to get at it. In general, though, their only two options are dogfood or starvation. Under those conditions I'm sure that most people would also grow acclimated to the taste.

@Andrei Getting into the psychology side of it, the current consensus among researchers these days is that it takes about two months of daily repetition for a human to establish a behavior as a habit. At that point, even if the behavior is somewhat arduous/painful, it becomes more natural for the person to continue with it than to cease.

@tel: related (unanswered so far) question: http://skeptics.stackexchange.com/questions/7985/does-it-take-21-days-to-form-a-habit

According to @Ilmari Karonen's comment and link, I have the answer. Such food does exist. However a person who tried to eat it and nothing else could bear it for only 7 days. He had cravings for "normal" food. The link was http://www.angryman.ca/monkey.html. Apparently the guy had weak will, but that's normal.

there are of course foods for bodybuilders and for weightgainers and losers, never seen just one food containing all (and I activly searched for it) but you can create your own mix if you buy some protein suplements (that are usaly made from whey and other byproducts that have a good ratio of the various essencial aminoacids) or just soyabeans that also have good aminoacid ratios and is cheaper; some carb rich foods and those complete vitamin/mineral suplements + essencial fattyacids (ie: cods liver oil). only problem is finding a trully complete vitamin/mineral supplement. I've searched in vain thus far.

It's absolutely doable. Humans aren't magic and their nutritional needs aren't unknowable. Taste would be an issue at the first generation, but that wouldn't be a issue going forward anymore than it was for early immigrants leaving old foods behind and learn to love the foods their new environment offered. Legal issues would inevitable arise when statistically significant variations among different groups eating different formulations are found, i.e. formulation 1 eaters have more arthritis than formulation 2 eaters while formulation 2 eaters live slightly shorter arthritis free lives. You get the idea. Ultimately, it will be the only way to sustainably support our ever increasing population. And, just like some pregnant women eat clay, man will occasionally add other nutrients to their own diet. It's important to understand humans don't have the most complex nutritional needs compared to our entire bionomy. We just have the ability to create the most diverse tastes to meet our completely normal needs.

Welcome. Can you add sources to your claims? It looks more of a personal opinion than a scientific answer.


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What advantage would the initial 'donor' in horizontal gene transfer by conjugation have received?
I am struggling to think why horizontal gene transfer between bacteria would have persisted during the course of evolution as surely it puts the 'donor' at a disadvantage?
For example, consider a hypothetical situation where only one species of bacteria has a gene to resist a new (almost) omnipotent antibiotic.  When growing on this medium, this species of bacteria has nil inter-specific competition for the resources it needs.  Yet if it passes on the plasmid containing the resistance gene via conjugation to individuals of a different bacterial species, they then too are able to grow on the medium and potentially out-compete the first species - thus the conjugation could possibly be extremely detrimental to the survival of the original population.
I'm obviously missing something as the feature has persisted, so what is the advantage to the donor species of conjugation?

The donor bacterium, viewed as a unit, may well gain no advantage from sharing its genes.  The genes that are shared, however, may gain a very substantial reproductive advantage from being able to spread to other strains.  If some of the genes that are capable of being shared also promote sharing, they may be selected for by evolution.
This is a good example of the basic principle of the gene-centered view of evolution, famously popularized by Richard Dawkins is his book The Selfish Gene: evolution selects for genes that are good at spreading themselves.  This may, but need not always, imply helping the organism containing the gene to survive and reproduce.

Excellent point. I'm working with a collaborator that specializes in social insects. One of the things I remember her discussing is that when the level of cooperation in a colony reaches a certain level, evolutionary forces begin acting on the colony rather than (or in addition to?) the individuals within the colony. So although we often think of evolution in terms of populations of organisms, there are cases when it makes sense to look at it in terms of populations of genes or populations of colonies, etc.

This is also a good example why the “selfish gene” view does provide new insight, contrary what is often claimed by detractors. Without such an explanatory framework, LGT would indeed be much harder to explain (parasitism might work, but would probably result in some sort of evolutionary arms race which we would expect to observe).


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What happens to snakes that swallow rodents as a whole?
As we all know, a few species of snakes swallow rodents as a whole. My question is what happens to the teeth and bones of these animals? Won't they cut into the flesh of the snake and hurt it? Are the digestive acids strong enough to dissolve bones and teeth? Even so, I'm sure the process takes time, and during this period won't the snake get injured?

Almost everything the snake eats is completely digested. They have a very efficient digestive system. Things that wouldn't be digested would be the rodent's claws and hair and feathers of birds. And during digestion, the snake's intestines go into overdrive mode and expand when necessary. When the snake isn't eating, the intestines are usually dormant.
If something goes wrong though, or if the snake is threatened, the snake regurgitates everything in order to increase its mobility.

It would be a nice complement to this answer to add some references.

Owing to their narrow structure, no chewing mechanism nor limbs, a snake has to swallow its prey as a whole. In fact, their success and diversity is partly due to their ability to swallow  prey relatively larger than their own body size. So inevitably, they need to process the parts like teeth, bones, exoskeleton and things of such nature.

Snake saliva not only eases swallowing by lubrication, but also
  contains powerful enzymes to break down tissues and even egg shells.
  But snakes generally cannot digest keratin (claws, hair) or chitin
  (arthropod exoskeleton). Many prey are covered with tough hide and if
  a snake relied solely on its digestive juices, it would take a long to
  time to get through to the nutrients. So this is speeded up by snake
  venom. Venom not only immobilises prey but also starts digesting the
  prey from the inside. A study showed that when a fer-de-lance
  (Bothrops asper) is deprived of its venom it took 12 days to digest
  a rat instead of the usual 2-3 days.

However, there is no consensus among different theories arguing the utility of a snake's venom. The above mentioned opinion is based on digestion hypothesis of venom utility.
Please refer to this excellent review and a summary of a snake's eating habits

It is not acceptable to copy and paste directly from another site without indicating that you have done so by using inline quotation marks/blockquote and stating your source with a link.

I have no idea about the convention. I shall follow it in future if I were to cite an external website.

Please follow the instructions Rory M gave it right now. You are given the option to edit your post, so please do so for this post as well. Don't ignore this post, and give due credit to every source you are using.


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Could someone recommend an introductory book on epidemiology?
I'm hoping to learn the basics of epidemiological methods, terminology, etc. I come from a background in statistical economics, and I'm moving into the economics of public health. I don't know if epidemiology uses separate statistical methods, but I presume it does. I know discussion questions aren't recommended, but please list any reasons you have (personal experience, ease of introduction, etc.) for texts you would recommend.

There are two books I'd highly recommend for someone starting to dabble in Epidemiology. The first is Kenneth Rothman's Epidemiology: An Introduction, which I'm affectionately going to refer to as "Baby Rothman" from hereon out for reasons that will become obvious.
Baby Rothman is an excellent "getting your feet wet" book. It's simplistic, and clearly designed for someone with no background in Epidemiology, so it starts from things that, if you have a statistical background, you might find a bit dull. But it accomplishes two key tasks:

A basic treatment of the subject from a pre-eminent methodologist and advocate for the field that doesn't make some of the sloppy slight-of-hand mistakes many introductory books do.
An introduction to the "vocabulary" of Epidemiology as a field - what we call things, how we thing about effect estimates, etc.

The second book I would buy would be Modern Epidemiology: 3rd Edition by Rothman, Greenland and Lash. This is the definitive reference book for most epidemiological methods  currently used in the field. As I said on a related CrossValidated question, ME3 is the only epidemiology book that has always come with me, regardless of what project I'm doing, and which I have routinely found invaluable.
The other benefit of the book is that it's "platform agnostic". It's not going to try to teach you a statistics package - its going to teach you the science and philosophy of Epidemiology, the actual doing of the science, rather than the toolkit. Without that kind of methodological rigor, you can be a wizard at your language of choice and still do bad science.
If I were only going to buy one book, it would be ME3.

Excellent answer. The other post you linked is also extremely helpful. I actually had Rothman's beginner introduction in the stack of books I borrowed from my uni's library already, and upon first read I quite like it. Thank you!

Here is an online book of epidemiology for the uninitiated. I used it to get a basic understanding of epidemiology.
http://www.bmj.com/about-bmj/resources-readers/publications/epidemiology-uninitiated

I don't suppose that book is available as a PDF too, correct?

@pythonscript no, but it should be simple to cut and paste into a libre office doc and export to pdf. Or if you need it in epub not sure how to do that.

I found Clinical Epidemiology by Robert and Suzanne Fletcher extremely useful  to gain some quick insight in to the broad area of epidemiology during my first year of post-doc. It covers a wide-range of topic in clinical research and epidemiology in an accessible format with several examples and extensive illustrations.

That may be a bit advanced for me, since I do not come from a pharmacy or medical background, but I'll take a look at it for good measure once I gain a stronger understand of the field.

Leon Gordis' "Epidemiology" was my textbook in undergrad and it was quite easy to follow. It's a small textbook as well so you can read through in no time.

Small textbook with a hefty price! I may look into it, though.

If you look around you can find it used or by electronic means.