text:
What do red ants secrete while marching in a line, one after the other?
Red ants often move in a group, and seem to follow a trail one after the other.
Once, I rubbed a part of the path along which they were moving and surprisingly found that the successive ants roaming around the rubbed region became confused as to where to go. It seems that the preceding ants secrete some kind of chemical (hormones, excretory wastes or body secretions) which guide the other ants to follow it. What is this secretion?

Possible duplicate of https://biology.stackexchange.com/questions/56654/how-do-ants-follow-each-other

The simple answer is that ants secrete a substance called trail pheromone as they forage for food and each ant follows the trail of trail pheromone that is laid down by the preceding ant.
The term 'trail pheromone' can be a bit indistinct, however. Rather than consisting of a single chemical, trail pheromone is composed of many different chemicals, the exact compositions of which appear to be used deliberately to deliver complex information about the details of a given foraging site.
In the linked paper, the authors suggest that the

use of several trail pheromones that differ in their persistence
  provides memory over differing time scales. In particular, a
  non-volatile pheromone can provide a longer-term memory, while a
  volatile pheromone can allow rapid choice among potential feeding
  locations by quickly ‘forgetting’ depleted locations.

This means that ants may be able to use pheromones to assemble a sort of "collective memory" for the colony, concerning the locations of food and the quantity of food found at each location.

Do all the ants marching secrete this 'trail pheromone'?

From what I've read, most ants secrete 'trail pheromone', but can vary the chemicals that are in each secretion of trail pheromone, to tailor it to their particular need.


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How to compare diversity between different ecosystems?
I've used the Shannon Wiener Diversity Index for a single ecosystem (species as categorical variables). Do you know any alternative indices, especially ones that compare diversity between different samples/ecosystems ?

You should have a look at Magurran. 2003. Measuring Biological Diversity

Have a look at the Wikipedia page on Diversity Index
Here are the indices that the wikipedia page describes

"True Diversity" Index
Species Richness
Shannon Index
Rényi entropy
Simpson index
Inverse Simpson index
Gini–Simpson index
Berger–Parker index

The article also links to related concepts such as

$\alpha$ Diversity
$\beta$ Diversity
$\gamma$ Diversity
Isolation Diversity
Relative Species Abundance

The literature is important on the question of measuring species diversity, ecosystemic function diversity and genetic diversity. What you want to use very much depends on your interest. Just to cite one other example: In the conservation literature, total sum of branch length over a phylogeny is sometimes used as measure of diversity and is sometimes used for prioritize populations (see for example Curnick et al. 2015). This method implicitely assume that more distantely related branches have different ecosystemic functions and keeping many of these functions is good for conservation purpose.

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/

sort: votes


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At what age does the mouse skull stop growing?
Unless otherwise mandated, neuroscientific research on mice is done with ~7-week old animals. There is a sort-of mantra that at this age their skulls stop growing.
However, recently, I noticed a rather robust difference in how I have to place ~4-month old mice in a scanner versus 7-week old ones. I am pretty sure this is due to skull size, since I am fixing all my animals relative to the ear canal, and there should be no fat/hair accumulation in the inner ear. Also, if there would be, I am quite certain I would feel it.
This made me try to look up the source of the 7-week recommendation, but up until now I found nothing. Do you know whether it is correct that the mouse skull "stops growing" at 7 weeks of age, and if so, what studies support this observation?

Apparently there's a really nice paper with some very informative figures on Cranial Base and Craniofacial Development in Mice. They measure the distance between key landmarks of the cranium over a period of 112 days.
The paper does not specifically look for landmarks that allow a good positioning of the brain relative to the ear canal, but from their data on Cranial Base length, one may conclude that:

The position of the brain relative to the ear canal is highly variable during the first 28 postnatal days.
The position of the brain relative to the ear canal, along with most measures pertaining to the neurocranium become more stable after about 56 days of age.
There are small but significant changes in the neurocranium between 56 and 112 days of age. The position of the brain relative to the ear canal could for instance become around 0.5 mm more rostral between 56 and 112 days of age.

My observation indicates the same tendency, though I would say the shift in position was greater (perhaps 2mm) - but since they did not choose the ear canal proper as a landmark, it is difficult to compare.

This doesn't fully answer the question, but for those mouse skull sutures that do fuse, fusion is complete by about 45 days of age, according to Studies in cranial suture biology: IV. Temporal sequence of posterior frontal cranial suture fusion in the mouse.  That suggests that most cranial expansion is more or less complete by about 6 weeks of age.  I think there is still the potential for remodeling of the skull, especially bone thickness and so on, but since your interest is on the internal size of the cavity, this may help address it.

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If our skin is burned by the sun what causes the red color of the skin?
Mostly it is not a good sign we are burned because too much UV light has damaged our skin and increases skincancers.
But the red color we get after a few ours, what is the exact cause of it and why is it red? Is that our blood we see or other changes in skincells or our immunesystem reacting?
And why does it takes a while before it gets red?

Sunburn causes damages in the skin which further triggers an immune reaction.
This immune reaction causes a dilation of the capillaries in the skin to allow a higher transport rate towards the inflammation site. This dilation and the higher blood flow in the area causes the "redness" of inflamed tissues. See the image for illustration (from here):

The delay in the appearance (for more severe cases also the swelling) is caused by the time it takes for the body to react and to develop an immune response. For further information you can look here and here.


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Is the increased/decreased enzyme activity (tyrosinase) caused by an environmental factor (UV radiation) considered to be gene expression?
My AP Bio assignment asks that I research the effects of UV radiation on melanin production, but the directions and questions suggest that UV radiation influences gene expression. From what I could find, such as on this university site or this abstract on NCBI, it seems that UV-B radiation directly affects the enzyme tyrosinase, which is responsible for producing melanin from tyrosine. So here is what I'm wondering: is our lesson wrong in stating that UV radiation affects gene expression, since it seems that it actually affects enzyme activity?

Since @anongoodnurse already nicely covery the effects of UV radiation on the cellular level, I will only have a look on the molecular level.
UV radiation of the skin causes increased DNA damage and thus activity of p53 in the keratinocytes of the skin. This causes (amongst others) the production of Kitl (Kit ligand, binds to the Kit receptor) and POMC (Proopiomelanocortin) which is later processed to ACTH (Adrenocorticotropic hormone) and the different MSH-forms (Melanocyte-stimulating hormone). These act on the MC1R (Melanocortin 1 receptor) on the surface of the melanocytes and induce pigmentation. See the figure below from reference 1 as illustration:

In the melanocytes the binding of these ligands activates different signal transduction pathways which all finally lead to the activation of the transcription factor MITF (Microphtalmia-associated transcription factor) which then upregulates the transcription of tyrosinase.
See the figure from reference 1 as an illustration about what goes on in the cell:

So the activity of the sun directly influences the signal transduction and later on the gene expression of Tyrosinase by a specific transcription factor. This translates a external stimulus (as UV light) down to the gene expression level. The stimulus does not affect the activity of the enzyme, only the amount available.
This upregulation stops when there is no further signalling down from the keratinocytes and eventually the Tyrosinase will be degraded due to normal turnover of the enzyme. Since no or only little is made without the right stimulus, this causes a stop or reduction in the pigment production. This happens when you get less UV light on your skin which happens for example in the winter time in Europe. Shedding of the upper layers of the epidermis then leads to the loss of the pigmented keratinocytes which makes persons lighter.
References:

The melanoma revolution: From UV carcinogenesis to a new era in
therapeutics
The roles of microphthalmia-associated transcription factor and
pigmentation in melanoma.

Awesome, this is exactly what I needed. If only I could select two answers. By the way, I'm a visual learner, so those diagrams really helped. Thank you, Chris!

@AleksandrH - Please feel free to accept Chris's answer. It directly answers your question, and is frankly a lot better than my answer. +1. This kind of answer makes me appreciate how much I've lost touch with molecular biology.

@anongoodnurse Alright, thanks to both of you for your thorough answers & the references :)

Unless there's a feedback mechanism shutting off gene expression (which controls the proteins made by a cell), activation or deactivation of an enzyme is not in itself a matter of gene expression, it's a matter of external factors controlling the enzyme's activity. You need to decide on what exactly causes skin pigmentation: the enzyme or cell proliferation, and what is under the control of gene expression and what isn't.
Most of what you find on ultraviolet light and melanin will be somehow related to melanomas, the formation of which does involve gene expression, so it's important to keep the two separated.
Ultraviolet light does cause proliferation of melanocytes, which cause the skin to darken. Melanocytes impart melanin to keratinocytes; these cells then are what give you a tan. The keratinocytes undergo constant turnover, so are eventually shed, and in the absence of continued exposure to UV radiation, there is no need to keep producing melanin-heavy keratinocytes.

The keratins and proteins within the stratum corneum act mainly by scattering and absorbing the UV. UV-R sets in action an integrated mechanism for the formation and delivery of melanin within melanosomes from melanocytes to keratinocytes. This mechanism is probably triggered by keratinocytes, which respond to UV-R with bursts of mitoses and with increased production of ET-1 and POMC, thus creating a new demand for melanosomes. The mitotic rate of basal keratinocytes increases a day after UV exposure, reaches a maximum 2 days later, and maintains this level for ∼1 wk. It then declines, and the skin regains its original thickness after 1–2 months if there has been no subsequent exposure.

Continued exposure to UV light stimulates the melanocytes to grow. This increases the chance of the development of melanomas. Since skin cells containing melanin are shed (there's no getting around that), in light-skinned individuals, keeping a tan is to keep injuring the skin and risking carcinogenesis.
Melanin Pigmentation in Mammalian Skin and Its Hormonal Regulation
Human skin pigmentation: melanocytes modulate skin color in response to stress
Mechanism of UV-related carcinogenesis and its contribution to nevi/melanoma


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Measuring Gross Primary Productivity (GPP) using Light and Dark Bottle methods: Sample Question
The following question is taken from my Cliffnotes AP Biology 4th edition practice exam and it deals with the light and dark method for measuring gross primary productivity.

In a classroom investigation, students filled two bottles with pond water containing only photosynthesizing organisms. They used a dissolved oxygen (DO2) sensor to measure the amount of dissolved oxygen in each bottle. One bottle was put under a light. The second bottle was wrapped with aluminum foil to block all light and was put under the same light. AFter 24 hours, pond water DO2 in the two bottles was again measured. Average values for DO2 from all students are provided in the following table.

Calculate the gross primary productivity for the observed sample. Express your answer in mg fixed carbon/L/day to the nearest hundredth.

Okay, so I know that net primary production (NPP) is the difference between gross primary production (from photosynthesis) minus Autotrophic respiration (Ra):
NPP = GPP - Ra
I also understand that the light bottle is measuring NPP, because it allows for both photosynthesis and cellular respiration. The dark bottle measures Ra because it only allows for respiration. Therefore, GPP can be calculated by rearranging the formula:
GPP = NPP + Ra
Calculating the difference in the final and initial values for both bottles, I get the following:

Light: 0.15 mg O2 / L   <-- NPP
Dark: -0.08 mg O2 / L   <-- Ra

Next, I plugged these into the formula:

GPP = 0.15 - 0.08 = 0.07 mg O2 / L

Using the conversion formulas provided on the College Board's AP Bio Appendix (essentially just multiplying the mg O2 / L value by 0.374128 to get mg Carbon fixed / L), I get the following:

0.07 mg O2 / L * 0.374128 = 0.02618896 mg C fixed / L

But according to my review book's solution, I was supposed to add 0.08, not subtract it. This seems a bit strange to me. Is this a mistake in the book or am I not understanding something?

The dynamics are:
Light bottle: GPP - Ra = 0.15
Dark bottle : Ra = 0.08

Then GPP = 0.15 + 0.08.
The amount of O2 used in the respiration is 0.08 mg O2 / L, not -0.08 mg O2 / L.

If you think about what is going on in the light bottle, this should make more sense.  Oxygen is being produced by photosynthesis, but respiration is using up the oxygen being produced.  Therefore, the total amount is NPP.  So if you want to find out how much oxygen was originally created through photosynthesis (GPP), you need to put those losses due to cellular respiration back into the light bottle (in other words, add the R amount to the light bottle amount).

Your wish to help the poster is admirable, but as you are a new user, may I suggest you check the dates of questions. This one was posted in 2016, so I imagine the poster has moved on to other things. You may wonder why it has resurfaced after three years. This happens when a question hasn’t had an answer with enough votes to be “put to bed”, and the reposting is to give people an opportunity to review and vote for the answers.  (Unlikely for this sort of homework question.)

I have moved on to other things! But it's okay, lol.

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text:
First life forms to evolve controlled flight
What was the first living organism able to fly in the skies and control their direction , not just Aeroplankton like bacteria and viruses carried by the winds but something  like an winged  insect or fish  or  something  similar,  and when did it evolve?

It was probably an early Pterygota (winged insect).
To my knowledge, the phylogeny of Pterygota is not completely resolved.

Hennig (1981) describes the following phylogeny

Boudreaux (1987) describes the following phylogeny

Wheeler et al. (2001) offers good evidence for this phylogeny

Odonata encompasses dragonflies and damselflies. Ephemeroptera are commonly called mayflies. The origin of pterygotes was about 300 million years ago.
The very first flying(ish) insect had three pairs of wings (Kukalova-Peck, 2005). The pair present on the first segment of the thorax (counting from the head) was then lost in all extant species. Note however than membracidae are using the developmental pathway for this third pair to make elaborate display (mainly for defence; see below).

Some clades further lost both pairs of wings and one clade, the Diptera (flies) lost only the last pair of wings. This last pair is replaced by halteres that are particularly visible in crane flies (see below)

Re "Some clades further lost both pairs of wings...", does this mean that the ancestors of all present-day insects once had wings, but some lost them?  Or were there other lines that never developed wings at all?

There are lines who never had wings such as collembola, archeagnates and silverfish who never had wings. Most lines people generally think of when talking about insects either have wings or had wings in their ancestry.


text:
Genomic DNA extraction protocol by salting out with NaCl, how to improve yield
In these papers

A rapid non-enzymatic method for the preparation of HMW DNA from blood for RFLP studies
A simple salting out procedure for extracting DNA from human nucleated cells
Modified salting-out method: high-yield, high-quality genomic DNA extraction from whole blood using laundry detergent.

In brief, red blood cells are first reduced/removed. Nucleated cells are lysed in the presence of SDS and genomic DNA are released. The resultant lysate are gooey. Addition of NaCl results in protein precipitation which is then removed by centrifugation. The genomic DNA is believed to not be precipitated by salt and thus remain in the supernatant which is recovered by ethanol/propanol precipitation.
Typically, ~30 µg of DNA is obtained per mL of blood.
I tried the salting out method recently and the yield is quite low (~ 10 µg per mL of blood), so no where near the published figure. In comparison, I obtained ~ 30 µg using phenol/chloroform from the same blood sample. I have tried using NH4Cl and still get a low DNA yield. I believe one of the reasons is that a lot of genomic DNA get trapped in the protein precipitates after addition of salt.
What can be done to prevent or minimise genomic DNA being trapped with the protein precipitate?


text:
What is the meaning of the verb "lines" in this context?
What is the meaning of the verb "lines" in this context?

"Epithelial tissue covers body surfaces, lines body cavities and
  form glands"

I searched in the dictionary but I found a lot of results and I'm not sure which one is matched.

(transitive) To cover the inner surface of (something), originally especially with linen.

I'm voting to close this question as off-topic because   it's english language, not specific biology terminology

You've already had another question closed for this exact reason. Please use one of the English sites you're already a member of to ask basic English grammatical questions.

Lines in that context is the verb form of the noun lining which is a surface that forms an inner boundary of an object. Here's a dictionary entry.


text:
Real unipolar neurons do indeed exist in human?
I studied that the unipolar neuron in human body are not really unipolar but they're pseoudounipolar neurons. On the other hand according to what I understood from wikipedia (neuron) there are real unipolar neuron.
In fact, I'm confused (if unipolar cell does exist in human body or doesn't) and I would like get you help about it.


text:
Are the destruction of Olfactory Receptor Neurons (ORNs) permanent?
I lost the ability to smell a particular smell due to an exposure to solvents years ago.  It has never fully come back.  I had always assumed that simply meant I had permanently destroyed my ORNs for that smell.  However, I have recently read that ORNs are replaced every 60 days.
Is it possible to lose all ORNs for a smell and have them never come back?  I'd love to know whether my long term loss of smell is due to something cognative, or whether it is a complete lack of inputs from the nose.

I'm confused by what you mean when you say "something cognitive". Do you mean central nervous function?

@anongoodnurse I am referring to something dealing with the processing of the information, rather than the part which generates the information from the stimulus in the first place.

I would suggest that you remove all personal references and simply focus on the question on "whether ORs regenerate"

@WYSIWYG Is that a preferred way to do things on this stack exchange?  On some of the SE's I frequent, the personal reference content can be useful for trying to work through any mistaken terminology that might come up in the objective part of the question.

@CortAmmon Yes; when you explain the context of a terminology that you might have encountered but personal experiences such as this one do not provide any context. It is not necessary for others to know about the incident in order to answer your question on olfactory receptors. Whatever your sensory perceptions are, after the said incident could be simply idiosyncratic and are therefore considered as an anecdotal evidence. Your personal reference just makes the reader think that you are just asking about what happened with you, which I believe is not really the case. Hence the suggestion.

You can add a line on your personal observations IMO it is better if you do it after explaining the question properly. For e.g. I read that ON regenerate [cite reference]. Are they always regenerated such that an odorant perception is never lost... ... I have not come across any study but based on my personal experience ... and so on.


text:
difference between transcriptional activator and general transcription factors?
What is the difference between transcriptional activator and general transcription factors? Are they same or different, and do the transcriptional activators first attract general transcription factors or the RNA-polymerase also, at the same time?

Activators turn genes on - they help or promote RNA transcription of the gene.  Other Transcription factors may turn genes off (prevent or reduce RNA transcription).  Some transcription factors may promote or inhibit RNA transcription depending on their environment/context.
Transcription factors is such a generic term that anything can happen in practice.  They are generically supposed to interact with the polymerase, but if some were found to interact by attracting other transcription factors that would not be a surprise.
I think 20+% of human genes are transcription factors (that is just a guess we haven't been able to characterize more than a few of them.

You here! +1, just to share my gratitude :)

As Shigeta mentioned, transcription factors are proteins that regulate gene expression which can be either positive (activation) or negative (repression). Sometimes the same transcription factor can act as a repressor or an activator under different conditions. Transcription factors have specific target genes.
General transcription factors (GTF), however are ubiquitous proteins that are generally needed by the RNA polymerase to initiate and carry out transcription. TATA-binding protein and TAFs are some examples of GTFs.
Specific transcription factors can act via different kinds of mechanisms: as you said they can recruit RNA-polymerase (but may interact with GTFs— this has not been explicitly shown, in my knowledge). Some help in altering the chromatin structure to facilitate transcription.

General transcription factors are needed for binding of RNA polymerase and also for attachment to promotor regions of genome since most of the regions of genome is tightly bound with histones promotor region and varoius other sequences necessary for attactmant for general transcription factors might not be available.As the name suggest general transcription factors are general and common for all genes.The principle that there exit vast differentiated cells arising from a single cell sharing same genome suggest that preferential gene activation is the key to differentiated cell type,each cell has its own group of mRNA and protiens.Definitly there must be other mechanism that ensure that specific a gene is activated/deactivated in cells specific transcription factors serve this purpose as mentioned above by altering the structure of genome by chromosome remodelling enhancement of transcription or deactivation  is obtained this way the transcriptional activators pave the way for prper attactment of general transcription factors and RNA polymerase to set the play for next stage recent research also suggest transcriptional activators give particular three dimensional shape to genome like protiens, to ensure gene activation by creating isolated neigbhourhoods(young et al)('rethinking transcriptional factors and gene expression' an article in MIT biology website might give deeper insight) To sum up transcriptional modulators are necessary for activation of particular genes but general transcriptional factors are necessary for all genes.


text:
What is the path taken by an oxygen molecule as it passes into the lungs to a muscle cell in the body?
My teacher tried to describe this question to me, but I just don't  get it.

If you have anything specific to ask after looking at my answer below, please refine your question. Note that I voted to close because of the textbook-nature of the question and lack of research effort. See the help center on homework for assistance in asking good homework questions.

See the figure below:

source: Human Anatomy


text:
Conservation Ex Situ
This came up in my biology diversity course and I wanted to raise a question about it.
On the topic of ex situ, one of the presentations that a speaker mentioned that one of its disadvantages is that 'endangered habitats may be fragmented and each small area may not be large enough to ensure survival'. Unfortunately, she left before I could ask anything of this statement.
Can anyone clarify what this means?

She was probably referring to ex-situ conservation as a way to complement in-situ conservation. Indeed, if a population is endangered and fragmentation it thought to be one of the main factors causing the decline, it can sometime be hard to restore the habitat in a way that would permit the population reestablishment (in-situ conservation). Ex-situ conservation can therefore permit to protect some individuals. Then, we could reintroduce individuals to their natural habitats later on, and this could give us more time to restore the habitat.
If you want a good example of how hard it can be to restore the habitat to permit population reestablishment, have a look a the Caribou situation in the north of Québec.
If your question is about how fragmentation is affecting species then it's a very very large subject... it can reduce gene flow, induce stress that could leads to lower reproductive success, etc.
Hope this helps.


text:
Do all cells produce the same proteins?
If DNA is more or less the same in all cells, and DNA is used to produce proteins from aminoacids, then do all cells produce the same proteins or are they specialised/controlled by something?

Close-voters - I can't straightforwardly answer this question - what determines the expression profile of a cell? I mean, let's say it's different transcription factors (?), what determines the expression profile of those? I think this is actually a great question. +1

Direct yourself here, there's quite a robust survey of the topic.

@Christiaan In that case the question would be too broad. You have to start from maternal inheritance, morphogen signalling to the structure of the gene regulatory network. I guess question need not be closed and can answered in a very few lines but it is quite trivial (unless you go to the how of it, in which case it would be broad).

Each cell will indeed have the same DNA sequences and ability to produce any given protein. However, there are certain factors (transcription factors) and cellular conditions within a cell that dictate which proteins are produced. If the conditions are right then only certain proteins will be produced depending on what type of cell it is. This process by which a cell continues to express selected proteins and becomes specialized for a specific function, is called differentiation. Expression of proteins that are not required can be prevented by transcriptional repressors (or by epigenetic mechanisms such as methylation of DNA sequences). So to answer your question, while cells contain the instructions (DNA sequences) to produce potentially any protein, not every type of protein will always be produced.
Keep in mind that my answer is very basic; the answer isn't as simplistic as I'm making it out to be.

Could you add some references & supporting material to your answer please?

I didn't use any references per se.. everything was straight from memory from what I learned in college. I have two science degrees, one in Biomedical Sciences BS and the other in Medical Laboratory Sciences BS. If you give me a little time I could probably find some supporting data.

It seems someone edited your post since, just FYI here is a useful meta thread about why citations/external material are requested here. Welcome to biology SE!

I noticed the edits and I like the additions, I think they definitely add to my answer and provide more clarity. I'll definitely include references next time. I quickly answered while I had some free time at work and didn't think to do so.

Protein expression in cells is majorly governed by a concept called RNA splicing. This also forms the basis of different types of cells which has different proteins expressed at different levels, but from the same nuclear material: DNA, which can be visually seen here. Differential splicing leads to various isoforms of the mRNAs, which are precursors of protein expression in cell. So, based on how the splicing occurs in different types of cells, different proteins are expressed at different levels, which constitute to the different phenotypes. This is just a brief introduction to these concepts following the previous comments, but I thought it would be a good time to mention these as these are pertinent.
I am new to this site, so may be not giving the best and most comprehensice answers, but I hope this is useful.

if you sequence deep enough and add single-cell sequencing you will also find cell to cell differences in the DNA which will add an other layer of heterogeneity in protein expression between cells.


text:
Can we say it's hybridisation if it's the same species?
If we mixed two population of the same species into the same environment and then they reproduce together, can we say it's hybridisation?
The wikipedia definition is the following:

Hybridisation (biology) the process of combining different varieties of organisms to create a hybrid

The question boils down to the definition of species and hybridization.
In general, we use the term hybridization to talk about mating between individuals from different species but really the term species does not mean as much as most people would think it does. Some people may use the term hybridization to talk about mating between lineages that are usually considered belonging to the asme species.
Have a look at How could humans have interbred with Neanderthals if we're a different species? for more information on the problems of definition of species.
Edit
Here are terms and concepts that are related and may help you

gene flow
introgression
interspecific mating
secondary contact
partial reproductive isolation

What do yo call a "Darwinian definition of species"? Do you refer to the so-called "biological definition of species" (which is based on reproductive isolation). Using the biological definition of species, you cannot hybridize different species (by definition).

Thank you for your answer, I know the definition of species is only arbitrary for the purpose of our mind.
If we use a Darwinian definition of species so basically a heritable morph then hybridation because interesting.

But if we refuse loosing variation and assume every ecotype is a species then we speak of hybridization between ecotype but is it really relevant ? Indeed, when hybridization is used too wide it then loose it's signification... The whole concept of hybridization is based on the idea of two variety (or species or what ever you want to call it) that breed together and produce a intermiedate morph, no ?

Sorry, I don't understand your comment and the point you are trying to make. Note that the hybrid does not necessarily have an intermediate morph. Note also that in english (unlike in french) there are no spaces before the "?" (another thing that Biology.SE taught me some time ago) $\ddot \smile$

I was just saying that basically , your answer dosen't answer mine since you refer to the species definition debate. I guess there is no proper answer to this question since the species definition is fuzzy. Then, I guess your right and it comes down to the species definition. Sorry for the ''?''...

Hum... not sure I follow the whole thing but you will be free to decide what you estimate answers your question. No problem for the "?", I am happy to see that I am not the only french speaking dude over here who did not know about this syntax difference between french and english.

Haha.... I am revising a text and this person use hybridization to speak of the reproduction between the natural population and the reintroduce population. My question was is hybridization really the good term, I would have use increase gene flow or something like that to be more precise. But since, hybridization can be applied to almost anythings I guess the use of the words is allright.

I agree with this conclusion :)

If you think the answer has been answer, you can check the answer. If you think the question makes little sense, you can delete it. If you think the question has not been answered, you should make sure that other people will understand what is missing to answer the question (or answer the question yourself). Cheers!

You might also consider whether the term 'introgression' is appropriate in this instance. Like 'hybridization' itself though, 'introgression' is used in different ways...


text:
Does the change in eye color (melanin concentration) affect the iris pattern?
In cases of acquired heterochromia, is there a quantifiable change in the iris pattern; the clefts , furrows, etc.
If yes, what changes are observed?
And if no, are there any diseases or acquired conditions that cause a change in iris patterns?


text:
Based on this diagram, how do you deduce the keystone species?
How would you figure out what the keystone species is in the following textbook question? (questions 1 and 2 at the bottom of the image)
Based on my knowledge, a keystone species helps to maintain biodiversity therefore I think it is either the otter or the kelp that is the keystone species. I say this because when either one of them decreases in number, the other species decreases in number as well (less biodiversity).

What book is the picture/questions from?

From http://education.nationalgeographic.org/encyclopedia:

A keystone species is a plant or animal that plays a unique and
  crucial role in the way an ecosystem functions. Without keystone
  species, the ecosystem would be dramatically different or cease to
  exist altogether.
  [...]
  The sea otter is an example of a keystone species in the Pacific
  Northwest. These mammals feed on sea urchins, controlling their
  population. If the otters didn't eat the urchins, the urchins would
  eat up the habitat's kelp. Kelp, or giant seaweed, is a major source
  of food and shelter for the ecosystem. Some species of crabs, snails,
  and geese depend on kelp for food. Many types of fish use the huge
  kelp forests to hide from predators. Without sea otters to control the
  urchin population, the entire ecosystem would collapse. 1

The organism I would therefore hypothesize to be the keystone species is the sea otter.
The data supports the hypothesis as when there is an decrease in the number of sea otters there is a increase in the biomass of sea urchins, which is accompanied by a decrease in the density of kelp. The lack of otters feeding on sea urchins causes an increase in their abundance, and this leads to an increased consumption of kelp by the sea urchins, which leads to the decrease in the density of kelp. Therefore, the sea otter is the keystone species since a change in their abundance has a significant impact onto the ecosystem and the organisms living in it.


text:
When touch and pain are caused by heat/cold or pressure how are the nerve cells triggered?
I suppose that when your skin is smoothly touched by any cold/heat or pressure we feel that because our AB cells notice this due to a kind of change in the nerve cell.
But when you touch something hot but not noxious how is that registered different from something what is cold or puts pressure on the skin. How works their mechanisms differently?
A step further is when due to heat/cold or pressure inflammation is started. I read that there are for each stimuly different receptors available. But what is the difference between an inflammation caused by heat/cold and pressure. How can heat create a different cascade of enzymes compare to pressure while both are inflammations and not adding any chemicals of themselves?

The receptors (and the sensory neurons) for different stimuli are different.


text:
What type of mushroom/fungus is this?
I had someone gift me some old firewood along with some other wood I had purchased from them.  I was told the wood in question is popple.  However, it was in pretty bad shape and much of it had a mushroom/fungus growing on it.
Does anyone recognize this fungi?  The trees lived in central Minnesota, and sat close to a lake for a year or so.

These are shelf (or bracket) fungi. They love dead or diseased wood, and are as common in woods as dirt.
Yours are kind of in rough shape (it looks like they're experiencing some problems of their own.) It's hard without examining a specimen to determine exactly which it is.

Some are edible, some are beautifully colored, some are hard, some soft, some plump, etc. But they are all shelf fungi.


text:
Heritability of trait stronger from one sex over another?
Given a trait that can be expressed (and measured) in both parents (e.g weight, height, strength, speed), are there ever traits in the child that correlate better with one sex parent than the other? If so, can you give some examples. This could be in any species.

It has been shown in Drosophila that cross-sex heritability is low for lifespan, where within-sex heritability was three times greater than cross-sex heritability. This means that, sons more closely resemble their fathers and daughters more closely resemble their mothers. This could be considered one such example, if you consider the trait to be a sex-specific thing, i.e. that fathers have a greater influence on lifespan in sons than mothers do.
In humans (and numerous other species, e.g. Indian Meal Moth), it has been shown that several traits have small cross-sex genetic correlations, suggesting that (in such traits) the parent of the same sex is a better predictor of a child's trait value.
It is common (in quantitative genetics circles) to consider homologous traits in two sexes as separate traits (e.g. male lifespan and female lifespan are separate traits), and analyse them in a multivariate framework such as a G-matrix. They often have some genetic covariance between the sexes because of pleiotropy and linkage disequilibrium (though covariance by LD is generally more transient: see books on quantitative genetics by Lynch & Walsh, Falconer & Mackay, or Roff, for more reading).


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Why does the gc content deviate from 50% in prokaryotes
I have read quite some articles but I can't figure out the main reason for gc content deviation in prokaryotes. In eukaryotes I can understand it, because the genome isn't composed at random, like TATA boxes and CpG island, because they are important for functioning in the production of proteins.
However in prokaryotes there is such a variety, GC% is ranging from 20% up to 70%. Most of the time it depends on the environment, high temperature needs a stable genome (= high gc content).
I also read the answer to this question How does GC-content evolve? however it's still not clear to me. I hope someone can explain the deviation a little bit more.
Question
Prokaryotes have an AT drift, but what mechanism causes some of these bacteria to higher their GC% instead of lowering it.

Possible duplicate of How does GC-content evolve?

I have already read How does GC-content evolve, I even mentioned in mine question @Forest

Sorry, I should have seen that, @Rick Beelo!

GC content is not related to optimal growth temperature. This theory has been refuted 15 years ago by many authors. The GC content of structural RNA (like 16S RNA) is indeed correlated to OGT, but not the GC content of the genome. See for example Galtier & Lobry (1997) http://www.ncbi.nlm.nih.gov/pubmed/9169555.

I wonder whether it is just some sort of functionless drift. I don't know about bacteria, but think the example of some human viruses may be instructive. The human herpes simplex 1 virus (causes cold sores) has a very high GC content, whereas the quite closely related (in terms of gene repertoire and organization) human varicella zoster virus (causes shingles) has a bias towards AT. Now these viruses depend completely on the host cell's translational machinery, which will be similar (e.g. distribution of tRNA species) in the cells these two viruses infect (as will temperature, ionic strength etc.) (The viruses encode their own DNA replication enzymes but not the systems for transcription or translation.)
So if there is a functional reason for the differences in these alpha-herpes viruses, it is difficult to discern, and one might assume that the situation in bacteria might well be similar.
Clearly, there must be mechanisms for the accentuation in a GC bias once established. One imagines there could be a selective advantage in either replication, transcription or translation, but molecular explanations do not jump to mind (at least not to mine).

Interesting point about viral GC content, I never thought of that. As to bacteria, I could imagine a scenario, in which random drift affects DNA stability or replication/transcription efficiency, leading to a sub-population that's now better suited to some environment and in turn leading to speciation. Between genetic drift & selection pressure, though, we can paint a nice picture of evolution in general. =P

There may be other factors involved with viruses of course. Perhaps what's important there is for the DNA to be different from the host for some reason.

If we are talking about viruses, most of the time there is an bias towards A/T on the third position of the codon right? So the virus can adapt it's self to the tRNA pool of the host to speed up production of new virusses. @Forest

I don't know about the overall picture. Just those wretched herpesviruses which were such a pain to sequence. I think you need to be careful drawing conclusions as to why. Or at least recognize that a rationalization may seem plausible but have no experimental evidence to support it. And these herpesviruses show that tRNA availability need not be limiting.

@RickBeeloo - I didn't know about the codon usage bias, so thanks for the TIL. Perhaps there's an evolved mechanism for codon usage bias in bacteria that affects GC content in different species. I found this paper (http://www.ncbi.nlm.nih.gov/pubmed/14659556) on the topic, which I won't have time to really read for a day or so. Might have some useful insights, though.

Interesting question. I think that bacterial GC content diversity boils down to a mix of mutational biases, such as using different polymerase and replication/repair gene isoforms, and environmental pressures, such as temperature and salinity, that have placed different selection pressures on the various microbes.
I would read over the linked papers for more detailed info, but at least in broad strokes, I think that the two mechanisms listed above account for most of the observed variance.
NB: This isn't my main field, so you might get a more detailed answer if an actual microbiologist weighs in. :-)

You're welcome! Don't forget to vote up helpful answers. :-)

Hahahha I'm new here :) @Forest


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DNA to Binary Distance Computation
If I represent DNA as binary values, what is the best way of computing distance between them.
So :
A = 00,
T = 11,
G = 01 and
C = 10
Hamming Distance between ATGC and TAAC is 3, however their binary representations give a different answer:
Hamming Distance of 00110110 and 11000010 = 5.
Whats the best way of distance computation if the DNA bases are represented in this way?

It is a question of theoretical computer science, not biology. I am voting to close. You should give it a try on cstheory.SE.

Agree with @Remi.b. But before you leave us, "Why would you want to do that?" as IT Support used to say.

Ask this question on StackOverflow not cstheory

I found a solution, I'll answer it when you ask it again on StackOverflow

This is a relevant question for biology.se, I think. "what is the best way of computing ..." phrase in the question is misleading, however. The question is not about how to perform a computation, but rather how to represent some biological entity formally, in a biologically meaningful way. This is a question about theoretical biology, not about cs.

I encountered this problem when studying M.A.Nowak's book called Evolutionary Dynamics. There, the author introduces the concept of a sequence space, where he attributes "imagination" of it to John Maynard Smith.
Nowak's discussion is very superficial and does not include your question, and I don't have an answer to it, either.
But i think I can make the question a bit clearer.

A sequence space is a L-dimensional space for sequences (of DNA or whatever) of length L. Each sequence is a point in that space, and position of the point is determined such that, value of each position within sequence determines the coordinate of the corresponding dimension in the sequence space. Author suggests then the Hamming distance of sequences within this sequence space as a metric for similarity between sequences.

These definitions make perfect sense, when the sequences have binary elements. And also any sequence can be represented by a corresponding binary sequence, says the author, implying that the rest is straight forward, if we want to extend the definitions to any biological sequence.
But this is not a straight forward task, as the example in the question demonstrates.

Each coordinate, or position, in the sequence will be represented by 2 bits. But some of the bases differ in one of their bits (A and G for example), whereas some of them (A and T) differ in both of their bits. Of course plenty of speculations can be done about how to do it conveniently, but there is no obvious way, as far as I can see. A good answer could provide some examples from the evolutionary dynamics literature for example, about how it is done.

A last note, this more of a evolutionary dynamics / theoretical biology question, than a bioinformatics question. It is relevant, when a formal representation of biological sequences (mostly for simulation purposes) is needed. For more practical purposes, about calculating distance between actual sequences, Jack Aidley's answer provides some good foundation.

Thanks for telling me why you want to know. I imagine that comparing two alphabetic strings is not the same as comparing two binary strings even though you have 'converted' one to another. Which should one use for evolutionary comparison? No idea! To answer that I'd need to understand the Hanning distance to decide whether or not it is applicable to the problem. So I still think you need a computing scientist with some molecular genetics to discuss this with.

I didn't ask the question by the way.

The best way is to choose a distance that represents what you want it to rather than necessarily relying on the Hamming distance.
If you simply want base-by-base difference then calculate that (this may help) but you may also want a difference that depends on the likelyhood of mutating between different bases in which case you want to define a function that translates the mutation into a score for each transfer, i.e. you might want to score a deamination from 5-methylcytosine to thymine as the most likely occurrence. Expressing the relative likelyhoods of different mutations is not an easy problem but there are a number of widely used options.
The important thing is to ensure you represent the underlying biology not ensure that you have the fastest implementation. Decide on this first, then on the algorithm that gives you the best speed (also, deciding on that algorithm is on-topic for Stack Overflow not this Stack Exchange).

This encoding doesn't make sense as nucleotides are not in the Hamming space. Hamming distance between every two nucleotides is constantly 1, but in binary encoding, it varies from 1 to 2.

I am reluctant to answer with code, but it seems that the community decided that was an appropriate question for Biology.SE. So here is my solution.
The idea is to "compress" the two bit that represent each nucleotide, such that each nucleotide will contribute 0 or 1 (not more) to the distance.
You could use binary operations to do something like this (in Java, but you can apply the logic in any language):
int seq1 = 54, seq2 = 194;//ATGC and TAAC
int evenBit = 0xAAAAAAAA, oddBit = 0x55555555;

int pseudoDist = seq1 ^ seq2; //Integer.bitCount(pseudoDist) is 5
int dist = ( (pseudoDist&evenBit)>>1 ) | (pseudoDist&oddBit);
int finalDist = Integer.bitCount(dist);//output 3 not five

The idea is to get the total number of bits that are different with:
seq1 ^ seq2

But you can't just count the bits yet, because you will get the hamming distance instead, so you have to compress all the bits that correspond to the same nucleotide to the same bit using: (pseudoDist&0xAAAAAAAA>>1) and pseudoDist&0x55555555. The first one keeps the bits on even positions and the second the ones on odd positions.
Now you use evenBits | oddBits, and you can count the bits.

The original question conflates mathematical operations with the edit distance between two strings. A hamming distance is a measure of the number of changes you have to make to convert one string into another string. Converting the the alphabet into binary digits and then adding or subtracting the numbers is not going to tell you how many edits were required.

@mdperry The fact that you don't understand it, does not invalidate it... You say it's impossible, but have you looked at my answer, have you tested it? Look it says that the hamming distance between ATGC and TAAC is 3, which is the right answer.

If your approach and solution is correct then it should be straightforward to apply your code to the examples on this page: https://en.m.wikipedia.org/wiki/Hamming_distance.

@mdperry this is not meant for any string, the fact that there are only four states possible allows you simplify it into 3 lines of code, that works for this particular problem

Actually, I now agree with you: my comment is incorrect, my apologies.


text:
Data on Recombination rate and Gene Positions in Humans
I am looking for estimates of per base pair recombination rate in humans and indication on gene positions. The goal is to be a able to plot recombination rate in the y-axis and position (in bp) along all chromosomes in x-axis. Then add the genes on the graph.
I have never had to search for this kind of data. Can you give me some hints of where I could find these data into a simple format like the simple table presented below?
> Gene Positions
from       to
1145146    1147112
1568742    1570012
...

> Recombination rate
from   to       r
1      156787   1.2*1e-9
156788 256888   2*1e-8
....

A good baseline for this type of research in human genetics is Standards and guidelines for the interpretation of sequence variants from ACMG. It is a guideline for clinicians, and it gives a good sense of good variants data, bad variants data and setting up confidence level.
Try to consolidate data from:
Population databases

GWAS databases

Exome Aggregation Consortium
1000 Genomes Project (there is data in vcf format which is pretty much what you need)

SNV databases

dbSNP (it is uncurated so you got to be hypercritical)

Disease databases

ClinVar (be aware "12% of interpreted variants have ≥2 submitters in ClinVar , and 21% are interpreted differently")
OMIM
HGMD (it is a gold standard as it is curated, but you could only search for variants but not collect data because you could not download it unless you pay for it)


text:
Why is there no symmetry in pigmentation when comparing people north and south of the equator?
If you are at the equator and start moving north, the further you travel, the lighter the skin of the indigenous peoples. Considering that we live on a ball, why do we not find the same traveling south from the equator? This relationship does not hold for individuals as you move south from the equator.  At the very least, one could say there are no blond hair blue eyed peoples south of the equator.

Welcome to BiologySE...interesting question... if you could cite some examples online to back up your statements in the question it would make the question much better

Because there are no significant land masses that far south of the equator that have been occupied by humans long enough for selection to have had an effect?  Africa doesn't extend that far south (and the southern tip is relatively small), and has plenty of opportunity for admixing/invasion by peoples to the north (see e.g. Zulu history), Australia doesn't extend far south, South America was only settled ~10K years ago, and like Africa, the southerly portion is small.

I rather would say that the lack of North/South Symmetry in pigmentation is that we forget how quickly human beings have spread. In prehistory, people have come to populate every continent over perhaps the last 60,000 years.
While in that time its clear that several mutations have popped up to influence skin color, they are pretty rare compared to the speed with which we migrated over the globe.  The dark color of our earliest ancestors has been lost and regained more than once, but not so often that the selection pressure of latitude have made indigenous in the tropics of south america or south east asia uniformly as dark as africans. Or for that matter have lightened the skin of pre-colonial South Africans.
One might guess that clothing and shelter have reduced the selection pressure on pigmentation further over the past few thousand years.
Individual cases should be studied - this is just a sketch - but the general thought here is that the pigmentation of human beings have more to do with where they have been and how quickly they have recently come from in their migrations.
Summarizing the comments below: There is a correlation between pigmentation and latitude.  The answer is really a combination of latitude, how long a people has been there, and the speed at which pigmentation mutants show up. It doesn't change so quickly that all people are equally dark at the same latitude or so slowly that you find completely pale people at the equator.

The dark color of our earliest ancestors has been lost and regained more than once That looks interesting, can you please add some references?

Just remembering some of the south pacific and australian aborigines being so dark sometimes.... no strong reference. I did find this reference that pigmentation is correlated to latitude. To the extent that it is symmetric or not depends on how perfect you expect the symmetry to be... sciencedirect.com/science/article/pii/S0047248400904032

If the dark color of our earliest ancestors has been lost and regained more than once and pigmentation is correlated to latitude, does it mean that our ancestors traveled several times between the equator and poles?

It means that the answer is really a combination of latitude, how long a people has been there, and the speed at which pigmentation mutants show up.  It doesn't change so quickly that all people are equally dark at the same latitude or so slowly that you find completely pale people at the equator.

@shigeta: But as I noted above, the mass of Australia isn't that far south.  Excluding Tasmania, the southernmost point is only 39°08' S latitude, and the mass of the continent is quite a bit closer to the equator.  It's also a mostly desert climate with lots of sun, unlike most of Europe north of 40° or so.

Its true but remember I'm not really trying to justify that latitude is the perfect correlation with skin pigment, just noting that the skin tone for some first nations people is darker than other neighboring peoples.


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Has the human body the greatest total length of nerves of all animals?
I've read that a human body contains about 150,000-180,000 km (Pakkenberg et al., 1997; 2003) of nerve wiring in the whole body. But does this length increase with the size of the animal? For example, an elephant is much bigger than a human and perhaps even his brain is bigger but is an elephant also the animal with the longest nerve cells in total?

Of course this length increases. Elephants are bigger than humans, so they need longer nerves to reach distant parts of body (say, tail) which obviously increases total nerve length. But I doubt whether anyone would have calculated total nerve length of elephant/any other big animal.

There is no reason to believe that total nerve "wiring" (or combined length) does not increase with the size of the animal, although the number of neurons in the brain (and the number of connections they make via dendrites) matters as well.
Animals with long necks, legs and tails have long nerves. Ancient sauropods may have had the longest nerves (referring not only to nerve bundles but single neurons) in history. Their brains were not as large compared to their body size, however, as humans.
But whales - the largest animals on earth - do have larger brains. Modern cetacean brains are among the largest in both absolute size and in relation to body size of all mammals. The brain of an average adult sperm whale weighs 8 Kg; by comparison, the average adult human brain weighs about 1.3 Kg.
Blue whales are the largest animals in existence today. With a large brain (3.6 Kg) and a long body, I can't see a particular reason to believe that the total amount of "wiring" in a blue whale doesn't exceed that present in a human.
[Normal weight of the brain in adults in relation to age, sex, body height and weight]
Normal organ weights in men: part II-the brain, lungs, liver, spleen, and kidneys.
Cortical complexity in cetacean brains


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What is the cause that angina pectoris is felt in your left arm?
When someone has heart problems sometimes they feel pain in their left arm. But why is the left arm painful?

Just off what I can remember from anatomy and physiology classes and wikipedia, but the pain that's associated with heart attacks comes from the fact that the nerves from the heart and which ever body part feels the referred pain converge at some point, leading the brain to figure that it's where the stimulus is from. So it's the same idea as something cold on your palate causing brain freeze

I know the nerves associated with heart pain are shared with the arm.  A hypothesis (no citation offered) is that the brain has likely never had a need to identify the exact source of heart pain, because those neurons don't fire often enough to make sense of them.  Thus, when the pain neurons in the heart fire, the brain has to make sense of new signals, with little to compare them to, so it does the best it can.

It has mainly to do with the embryonic origin of organs, with the heart being a typically left sided organ, it develops sharing some nerves with the left thorax and left arm.
There is however high variability, typically among patients but also among coronary vessels. For instance, right coronary stenosis may lead to abdominal pain, whereas left circumflex artery stenosis may lead to no pain at all.
References:
Essentials of Medical Physiology
Cardiac Pain. Anatomic Pathways and Physiologic Mechanisms
Changing Features of Anginal Pain After PTCA Suggest a Stenosis on a Different Artery Rather Than Restenosis

Thanks! You can find other references just looking at Google: http://www.healthhype.com/angina-pectoris-heart-pain-meaning-and-different-types.html, and https://books.google.it/books?id=tdODr5fpxEAC&pg=PA633&lpg=PA633&dq=angina+pain+embryonic+heart&source=bl&ots=7dQcfjyzZ2&sig=434B_K1VhNUPCs9x9i_qCKQa0mw&hl=it&sa=X&ved=0ahUKEwiy9-TUju7LAhXGYQ8KHc8aARQQ6AEISzAG#v=onepage&q=angina%20pain%20embryonic%20heart&f=false

Our pain-sensing neurons work in useful ways only when they inform about skin areas or muscles. When nettles sting your left hand, you want to retract your left hand right away. This is in part an educated reaction, because your brain ca re-learn what sensing neuron corresponds to what side of you hand when surgeons stitch together broken nerves.
With internal organs, it is not the same. You can't really retract your heart or your liver, and you can't look inside you to figure what organ is actually struggling. Our brains make sense of pain from internal organs by projecting them onto nearby skin or muscle. This is why doctors never write down "heart pain", but "pain projected to the area anterior to the heart" (in short, "precordial pain"). For them, it is never certain that the heart hurts. It could be even the pectoral muscles. (This is also why hypochondriac types are mocked when the complain about "stomach pain".)
Heart projects into many neighboring places. Some people complain about pain in the hand, but other describe pain in the throat or even the jaw. We feel something is not right, but we can't tell precisely where. The left hand is often the place where we project heart pain, because it is close to the actual trouble.
Pain from the internal organs is often, although not always, projected on the muscles and skin portions covered by the same nerve as the troubled internal organ. A more technical explanation describing which nerves cover the heart, and what skin / muscle structures these nerves are shared with, is given in Medical Physiology by Boron and Boulpaep.

This answer doesn't explain the mechanism of referred pain in any serious way. "The left hand is often the place where we project heart pain, because it is close to the actual trouble." How do we project the pain? The left hand isn't closer than the left scapula, or the jaw, or other sites of referred pain from cardiac ischemia. References would be nice, as would a better explanation.

The association between a heart attack and arm pain appears to be strange since the arm is usually not harmed. The reason for the pain in the arm is that the pericardium is innervated by the phrenic nerve and there may be some neuronal connections to left sided intercostobrachial nerves. During myocardial ischemia, the signals can overlap creating a false impression that the pain is coming from the left arm or jaw. The brain essentially gets confused about the source of the signal and this can often result in the pain from a heart attack being felt as pain in the arm with no sensation of pain in the chest. This is what is known as referred pain. You can check out this post on Wikipedia for more detailed information.


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Genomic distribution of tRNAs in eukaryotes
The title says it all. I'm doing a literature search trying to see what is widely known and/or well established. I've found a couple of mentions that tRNAs are dispersed throughout the entire nuclear genome. Does this mean they are isolated from each other? Or do they occur in clusters? Is this true across eukaryotes? Or is any of this even well studied?

The positions are annotated but I don't think anyone did a comparison.  Surprisingly, the gencode GTF does not have the tRNA annotations!! Have a look at this database of tRNAs.

In Drosophila, at least, some are clustered (e.g. these), but there are many tRNA genes in eukaryotes, so overall they are dispersed. You might find the Genomic tRNA Database useful, and the paper describing it.


text:
How to construct tumor phylogenetic tree?
I would like to know if anyone has tried any software that constructs tumor evolution trees where the trunks represent the common mutations and the private alterations are noted on each branch. I can do it manually but the sample size is too big (nearly 100 patients). Here's a good example of what I'm after here on Figure4 http://www.nature.com/nm/journal/v21/n7/full/nm.3886.html
Any additional computational model suggestions are welcome.

I do not know if this is exactly what you are looking for. The ETE toolkit for python is possibly worth a look.


text:
Omnivore vs Carnivore territory size
Edit: Large carnivores require lots of territory. What about bears? They're omnivores. How much does that count?
Is there anywhere I could find weight/territory ratios for mammals, depending on diet? Does necessary territory matter so much depending on the diet of a large mammal?
Thanks

Bears (depending on species) are omnivorous

Yep. Realized I was wrong. But the territory size is still something I'd like to find an answer for, if possible

Also consider that elephants, giraffes, rhinos etc. Are large herbivores and have large territory/ranges

Any answer is going to vary quite a bit, depending on the productivity of the land in question.  It would take much less area to support a bear in say the lush forest/stream environment of southwest Alaska, than in the near-desert eastern Sierra.


text:
Do any fish have to hold their urine in deep water?
I know this is going to sound really weird! But I was confronted with this claim and the person strongly had faith in it! I said faith since he couldn't provide any evidence.

Is there any kind of fish that is forced to hold his urine when in deep water ?
If yes, is there any relationship between the case with fish's scale ?
Does that make the fish's meat not proper (poisonous) to eat ?

I don't know what depth would be proper to define here but I guess the matter to be rare and not so important to define.

Is there any rational for which a fish would be forced to hold its urine in deep water?

In a salty environment there is the risk of loosing water by osmosis.
There are different strategies to prevent this.
One of them is to hold the salts of the urine (not the urine itself) by reuptaking them from the kidney.
The resulting high internal salt concentration prevents the water loss.
This strategy is used by Sharks and rays/ skates, they take up urea and TMAO from the kidneys. Those metabolites are highly concentrated in their blood, which makes them unhealthy to eat, when fresh. However, after fermenting they are edible: Hakarl is an icelandic dish of fermented shark. The linked Wikipedia-Article gives more details about the topic.
I guess your friend was referring to this phenomenon, but his memory was a bit imprecise.

Fishes have urinary bladder too. It would be hard to hide from predators with an urine trail pointing towards you. I don't think this is size dependent.

 - ref
Urine is usually not that dangerous and we remove inner organs, like urinary bladder by the preparation of the meat, so this is not a problem.


text:
Confluency or confluence, which term is correct to describe the % area covered by cells?
I noticed that both of them are used in many scientific papers. Are these two terms, or can they be used interchangeably?

I'm voting to close this question as off-topic

@rg255 Why is this off topic? It seems to be a valid terminology question.

Because it's an English language problem as far as I cam tell

also possibly duplicate http://biology.stackexchange.com/questions/29857/what-does-confluency-mean

Does this answer your question? Origin of term ‘confluency’ in cell culture

Searching Google Scholar for cell confluence returns 239000 hits, while searching for cell confluency returns 75000 hits.
A look at the context in which they are used supports my gut feel, which is that
1:  "confluence" should be used in contexts of "% confluence"
2:  "confluency" should be used in contexts where you describe high or low levels of confluency.

I have conducted a thorough examination of this and find nothing to support your gut feeling, I am afraid. I have documented this in a late answer to an earlier question on this topic.

I have documented the history and current usage of the terms confluence and confluency in cell culture in an answer to another question specifically about the term confluency. As the current question has not been marked a duplicate of that one, and I believe the one answer posted to be incorrect, I am providing a brief answer here and direct the reader to my other answer for full supporting evidence.

Q. Are confluence and confluency two [different] terms, or can they be
used interchangeably?
A. Confluence and confluency, as used in cell culture, have exactly
the same meaning, and usage is a purely a matter of personal preference.

Confluence is a standard English word dating from the fifteenth century, and used as an abstract concept or applied to different phenomena in various fields. Confluency is a term almost exclusively used in relation to cell culture. In this respect, the definition from the short Wikipedia entry on confluency (sic) is pertinent:

In cell culture biology, confluence (sic) refers to the percentage of the
surface of a culture dish that is covered by adherent cells. For
example, 50 percent confluence means roughly half of the surface is
covered, while 100 percent confluence means the surface is completely
covered by the cells, and no more room is left for the cells to grow
as a monolayer.

While there is no guarantee that this Wikipedia entry is correct, it reflects the fact that (1) since the 1960s some authors have used one term and other authors have used the other term to mean the same thing (2) that the same authors have used their preferred term in relation to both the concept itself (without any numerical qualification) and with a percentage qualifier.
I have inspected recent papers in the Journal of Cell Science (referenced in note (9) of my other answer and found that both usages, as above, are still current, as well as mixed usage of both the type prescribed by @MarchHo (confluency, but 50% confluence) and the opposite (confluence, but 50% confluency).
Both terms are accepted by all journals I have looked at, and I have failed to find a pronouncement on the topic by any standards organization or professional body.
Recommendation
Use whatever the people with whom you work use. If you are starting out on your own, make your choice depending on your attitude to the English language or the respect you have for a particular pioneer of cell culture. But, whatever you choose, never tell anyone else that they should do the same.


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What kind of cell has the most different receptors?
All hormones and neurotransmittors has their own receptor. Now some of the cells has a few different receptors but others has many sorts of receptors. So what are the most receptive cells? Are that the some braincells?

I think this is difficult to answer. What is meant by "most receptive" ?  The number of receptors on a cell's surface is known only for a few well studied cases, and many cell surface receptors are not characterized at all, or have not even been discovered. And more receptors does not necessarily translate to a more "sensitive" cell, as receptor sensitivity can be modulated in other ways too.


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Enzyme Inhibitors: Using in vivo in yeast
I find listed on the Sigma-Aldrich site a large list of enzymes & corresponding inhibitors. e.g. For the enzyme squalene synthase the inhibitor listed is "Zaragozic acid A trisodium salt"
Would this mean that if I added the right amount of this chemical to, say, a Yeast cell culture I might expect to get reduced activity of Squalene Synthase which is native to yeast and catalyses the transformation of FPP to Squalenes.
Would this even be a reasonable thing to try if I had a goal to block Squalene synthase? Or am I interpreting how these inhibitors ought to be used incorrectly? Can they be used with in vivo cultures at all?

This is usually the way this kind of inhibitors are used. There needs to be a way that they come into the cells (if they stay in solution and cannot reach their target they will be useless), but then they inhibit their targets.
What usually needs to be done is to determine which concentrations are needed in the cell culture (or the medium) to be effective for the inhibition but not to harm the cells. Therefore I usually use different concentrations of the inhibitor in culture and then measure the outcome.
To find the right concentrations, see if there are some recommendations from the manufacturers. Otherwise you will probably have to dig through Pubmed to find some starting point.

Thanks! Any thoughts on what concentration range might be reasonable to attempt with Zaragozic acid for inhibiting Squalene synthesis in yeast? Also, do you think yeast cells would pick it up?

Honestly: I have no idea. Are there any recommendations by the distibutors? Otherwise you will probably have to dig through Pubmed to find suitable concentrations. If there is nothing, you need to try it.


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Different Effects of Detection Probability Between Presence and Count Data at the Same Location
I'm modeling habitat suitability for a large, mobile animal using occurrence data (presence only - I have no true absence data in this case) collected from camera traps (stations with automatic motion/heat sensing cameras). At each camera trap location I have 0 to several occurrences recorded.
Typically, when such data is modeled, they are modeled as count data, and detection probability is included in order to mitigate for covariates that affect detection, which otherwise may be identified as covariates that affect suitability. For example, an area where detection is less likely due to, say, dense vegetation, may be mistaken as less suitable due to that vegetation structure when in fact that may not be the case (or even the opposite may be true).
My question is, if the count variable were to instead be used as a detection/no-detection variable (so, a binary) would the probability of detection have less of an effect on the model (*when modeling relative suitability, not probability of occurrence)? i.e. if you didn't account detection probability, would using a binary response variable give you a less biased estimate of habitat suitability than if you were to use count data? And if so, why? It doesn't seem like probability of detection would change, or would be more homogeneous across the study area with this change, but it seems like the effects would be smaller in magnitude by not reinforcing differences in detection probability with multiple occurrences.
Also, I understand that it's not desirable to toss out all the other occurrences assuming you can calculate detection probability. I'm asking this in an attempt to better understand the possible differences in outcome between these two modeling approaches when using such data, as I've seen both methods in the literature, but have not seen this question specifically addressed. If you could reference any publications that may shed light on this, I'd be very appreciative.

Do you in any way have the option of estimating the detection probability over a season, e.g. from being able to identify the individuals in the pictures? Do you have data for several years or only a single year?

yes, that actually has already been done. the data i'm talking about was used to model occupancy with a capture/recapture model. capture probability was 0.05.

Disclaimed: Not really an answer, but too long for a comment

If I understand you correctly, this must depend entirely on the accumulated probablity of detection over the entire detection period (the time the cameras were out). If the accumulated probability of detection across all habitat types is high (approaching 1, given that the animal is present), then the detection probability shouldn't be a problem for the binary occurrence variable. An indication of this would be if you have sites (cameras) with either zero or a very high number of occurrences, which should indicate that the binary occurrence is rather robust. On the other hand, if sites have 0-4 occurrences in total it will be extremely difficult to separate non-occurrence from random factors or detectability. I assume that the detection probability across habitats is unknown though (as well as the accumulated probability of detection), but you might be able to make an educated guess. Also, by using a binary response, you will completely exclude the possibility to estimate e.g. an effect of habitat quality (for instance a difference in abundance between habitats), since counts of 1 or 13 will both be represented by 1 in the binary detection variable. In the Q, you talk about "modeling relative suitability" which indicates that you are indeed interested in something similar to this (relative habitat quality). In that case, I think that a binary response will be too coarse to provide useful information.
One possible toy scenario could be that you have two habitat types A and B (10 camera locations/sites of each) with a binary detection variable as:
A: 1 1 1 0 1 0 1 1 0 1  (species found in 7 sites)
B: 0 1 0 0 1 0 1 1 0 0  (species found in 4 sites)
In that case, the species can obviously exist in both habitat types (as you have categorized them), so the higher amount if zeros in B can represent (among other things) 1) lower occupancy of this habitat (in a metapop perspective), 2) that the quality of B is heterogeneous which is not captured by your habitat categorization (so parts of B is just as suitable as A), 3) lower population abundance in B compared to A (but the same detectability), or 4) lower detectability in B compared to A (but the same abundance). I don't really see how you can separate between these cases with only the binary variable, and I don't believe that using a binary detection variable will solve any specific problems compared to using the count data.
This is all very hand-wavy, but can hopefully give you some useful ideas/perspectives.

thanks for the thorough reply. i was thinking along the same lines as your first point - that cumulative detection probability over the detection period might be high enough to not cause any major issues using binary data. detection period was 20 days, using 300+ traps, and generated 100+ occurrence locations (~180 detections). counts range from 0-5. the only specific problem using binary data would solve is the problem of time, and user expertise. the question was raised as to whether a more user friendly method (e.g. maxent) could be used with this data to make meaningful inferences.

To be able to separate abundance from probability of detection, you need to have marked animal. If this is the case, you can then build a history of capture for each animal and model the probability of detection.
Have a look at this article : http://www.sciencedirect.com/science/article/pii/S0006320712005071. For some recommendations on the use of spatially explicit model when using camera traps to estimate population parameters (abundance...).
To answer your question, theoretically if there is independence between the detection at one site, using binary data will underestimate the probability of detection but if your detection are dependent let say animal moving in a group so each times you detect an animal you have a strong chance of detecting more than one then using binary data would make sense.
Hope it helps !
Cheers

Nico - I understand the relationship between detection probability and abundance, mark-recapture, and why it needs to be accounted for.
My question however, is if you didn't account detection probability, would using a binary response variable give you a less biased estimate of habitat suitability than if you were to use count data? And if so, why?

It all depend if your detection are dependent or independent ? What is the animal you are studying ?

Assume they are independent, and it's a large felid.

and in your model you ''y'' variable is the occurence of the felid you are studying ? And your question is : Is there more probability of detecting an felid in a specific habitat ?

not really, i guess you could frame it as a question of "probability of detection". but let's frame it as a very basic habitat modeling question: given this set of occurrence locations, what is suitable habitat for this species? i know probability of detection can bias that estimate. my question is whether the bias would decrease if using binary data.

Ok, then in this case I would say using binary data vs count data would underestimate the probability of detection since you assume independence between your detection. But the only way you could affirm that is if you had marked animal. When you get ''station'' with more than 1 detection are they close in time ? Like do you detection two felid in the same hour or in 12 hours ?

Nico - I'm not talking about estimating the probability of detection, i'm talking about estimating habitat suitability, and how these two data types effect that estimate given imperfect detection.


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Behavior of plant guard cells: open or closed stomata
On an exam of mine, I had the following question:

The interaction between the guard cells and stomata in a plant leaf can be seen in the diagram below.

In which scenario could the guard cells and stomata be in situation 2?
(A) High humidity
(B) High light intensity
(C) Low temperatures
(D) Nighttime

The answer choices aside, I was thinking the answer should be along the lines of "a scenario in which the temperature is really hot", since an open stomata on a very hot day would cause a plant to lose a lot of water. The only answer choice that seems to fit this is "high light intensity" (although I'm not sure if high light intensity would necessarily cause high temperatures, but this seems to be the closest thing to what I predicted). However, the exam key is saying that "D", nighttime, is the correct answer. My teacher explained that since plants don't need to do the light reactions during the night, they apparently close their stomata because they don't need to intake CO2. But this doesn't make sense to me: why would a plant close its stomata during the night instead of keeping it open to stockpile CO2 for use in the day? If I'm not mistaken, this is precisely what CAM plants do (although there's no mention of whether the plant in question is a CAM plant).

I found a paper and this is the link https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3258058/  it says that Stomatal opening is induced by low CO2 concentrations, high light intensity and high humidity. By contrast, closing is promoted by high CO2 concentrations, darkness, drought and the plant hormone ABA.
Another paper, Open or Close the Gate – Stomata Action Under the Control of Phytohormones in Drought Stress Conditions https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652521/
During the night, elevated levels of CO2 in the leaves were observed due to respiration. It has been proved that CO2 has a positive effect on the stomatal closure process


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Y285 Yeast Strain: Where to obtain from?
Often I see yeast strains mentioned like Y285 or Y301 etc. in papers. Is this some sort of universal notation? (Link to poster: https://ddd.uab.cat/pub/tfg/2014/119349/TFG_narcisferrerledo.pdf)
How does one go about locating such a strain to try in an experiment; are there repositories where you can get a strain from?
e.g. I tried searching the strains databases at Yeastgenome.org & DBVPG but these names ("Y285") don't produce any hits. Is there another canonical name I should be using to search them by?
http://wiki.yeastgenome.org/index.php/Strains
http://www.dbvpg.unipg.it/index.php/en/database
I even tried searching in the "National Collection of Yeast Cultures" but no luck. Any tips?
https://catalogue.ncyc.co.uk/catalogsearch/result/?q=Y285
Edit:
Found this related thread on SE-Biology that gives links to other useful Repositories.
Sources for common laboratory Saccharomyces strains?
Am I just searching with the wrong name? Is it common to refer to Y285 by some other name?

Y285 or Y301 sound like specific mutants (at tyrosine 285/301 of a particular protein) but we can't really be sure without the paper you're referencing [and I'm not very familiar with yeast strain nomenclature]. Could you provide a paper link?

@Luigi Thanks. I've added the link to the source in the post: https://ddd.uab.cat/pub/tfg/2014/119349/TFG_narcisferrerledo.pdf


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Genomic DNA resuspension after ethanol precipitation
I am having trouble resuspending purified human genomic DNA.
The genomic DNA is purified using phenol:chlorofom from ~ 1 mL of blood. After ethanol precipitation, I normally see a large pellet which is then resuspended in 150 uL of TE (10 mM Tris pH 8.0, 1 mM EDTA).
But the resulting DNA solution is extremely sticky.
There are the options I have tried:
1) Incubation at 37C for 1 hr to overnight
2) Incubation at 50C for 1 hr to overnight
3) Incubation at 65C for 1 hr to overnight
The 65C incubations for up to 3 hours do make the DNA solution less sticky, but in the mean times, cause increasing DNA smearing when running on agarose gel. After overnight incubation at 65C, the DNA solution is no longer sticky but shows extensive smearing on gel, indicating DNA degredation/fragmentation at high temperature.
I have also tried resuspending the DNA in 8 mM NaOH, then neutralise it with Hepes, but this doesn't help either.
I am thinking to try silica/glassmilk beads based methodology. Will genomic DNA captured in silica beads be easier to elute and resuspended without the "sticky" issue.

Sounds like an impurity in your prep as opposed to they way you're resuspending. If silica worked it wouldn't be because solubilization of the DNA was easier, but rather because impurities were more efficiently removed. It's not like if you have completely pure DNA on a column vs. in a pellet the pellet could be more sticky upon solubilization; the end product of dissolved DNA would be identical. Have you checked the OD260/280 of the sticky stuff? Or, maybe the DNA is just too concentrated; maybe try more solvent? Some people on the internet are saying they have this problem from over drying.

Purified DNA have a good 260/280 (~1.85) and a nice graph (nanodrop). I don't think the DNA is over dried, as soon as it's washed in the 70% ethanol, I aspirate all the alcohol and put TE into the bottom of a tube immediately.

When you say 'sticky' do you mean viscous, a solution with high viscosity? That is precisely what you would expect, or predict, for purification of intact, high molecular weight, genomic DNA.  Your own data reveals this to be the case, as assayed by agarose gel electrophoresis, when the viscosity of the solution decreases the DNA fragments in the tube get shorter. It follows that longer fragments of DNA are likely causing the increase in viscosity. The question is, what do you need to do with the DNA?

What about proteinase K? You mentioned the phenol/CHCl3 extraction, but that is typically preceded by a digestion with proteinase K at 65 C in the presence of SDS and EDTA.

'Viscous' in the word. I tried with and without proteinase K and noticed that proteinase K can be omitted without affecting the quantity nor quality (absorption spectrum). The DNA is for next gen sequencing. It's true that DNA will be fragmented in most sequencing platforms. But we want to keep the DNA as long as possible for something like pacbio which requires long intact DNA

What kind of concentrations are you getting in your DNA resuspensions? If you are getting DNA concentration higher than 1µg/µl, you should consider diluting the DNA. Otherwise, the viscosity is unlikely to be related to the concentration.

Just a thought, have you tried eluting the DNA in Molecular Grade Water instead of TE?

For DNA which are supposed to be used in downstream applications like sequencing or transformation, elution with Water instead of TE buffer is frequently done.
I agree longer genomic DNA can be sticky upon elution, but if by chance the DNA is not entirely dissolved when you add the eluant (you see some very small clumps of flakes instead of a homogeneous clear solution) , that may be because of the presence of low amounts of alcohol (organic solvent). That's why it is recommended that after aspirating the alcohol, you should leave the tube opened for ~10 minutes for the trace amounts of alcohol to dry out before you add the eluant.

Sorry if you have done these things already, just wanted to be sure.
Hope this helps!

It's true that water is sometimes recommended for elution. But in general TE is better for (1) resuspension as the alkaline pH is better at "solubilising" DNA and that the pH of water can be fluctuating between 5 ~ 7; (2) stability as the EDTA prevent extraneous nuclease, Qiagen has a related note


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Are women smaller to optimize cloth needs during pregnancy?
Current life events made me wonder: Is it possible that female humans evolved to be on average smaller than males, so that they can reuse their partner's cloth during pregnancy?
At least in my culture, males prefer smaller females, which would suggest some selective pressure, but I'm unsure whether this is cultural or actually makes biological sense.

For how long do we wear clothes and possibly recycle them to partners? I would say this is not longer than for one generation. So it is quite unlikely that evolution plays a role here.

No.  Making of cloth is only perhaps 30,000 to 40,000 year old (History of clothing and textiles), and body coverings of any form, e.g. animal skins, only around 100,000 years old (based on body lice).
Females being smaller than males is much, much older than this. Chimpanzees, our closest relatives, similarly have smaller females (and don't dress in cloth); their line and our line separated around 4 million years ago.  Our next closest relatives, the gorillas, have an even greater difference between the sexes, the females being half the size of the males.  They separated from our line perhaps 6 to 8 million years ago.  Further back, most all our anthropoid primate relatives also show smaller female size (but the most distant primates, like lemurs, do not).  For more information see Sexual dimorphism in non-human primates.


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Why does the blood not clump and result in death?
In this question's accepted answer, it is said that the blood type will slowly change to that of the donor's.
When the blood in the person is about 50% his own and 50% that of the donor's.
i.e, 50% A group blood (his own) and 50% O group (donors blood),won't the antibodies in the O group react with the A-antigens and clump?

Some people do die from graft vs host disease after bone marrow transplants involving ABO incompatibility, but not usually from blood clots.
Foreign red blood cells don't usually form significant clumps (or clots) as a result of an antibody interacting with a surface cell antigen. They can form tiny clumps, however, that are not life threatening, but simply plucked out of the bloodstream by macrophages.
The typical reaction consists of foreign red blood cell detection and destruction (broadly called hemolytic anemia.) So anemia is a problem, but normally not significant clumping/clotting.
Safety and impact of donor-type red blood cell transfusion before allogeneic peripheral blood progenitor cell transplantation with major ABO mismatch.
Blood transfusions and the immune system
Consequences of ABO incompatibility in allogeneic hematopoietic stem cell transplantation.


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No. of genes in chromosomes. phenotype
Why do cells need all the genes of all the 22 pairs (excluding the 2 X- or Y-chromosomes) of autosomes in every somatic cell, when each and every cell which is specialised for its function does not manifest all the phenotypes that are encoded by the genes present? Aren't the genes other than those whose phenotypes (& hence some chromosomes) are expressed by that cell, redundant?

Somatic cells require genes on all chromosomes, regardless of their specific phenotype.

This may have to do with the fact that the cells require 'housekeeping genes', which are typically constitutive genes that are expressed in all cells of an organism under normal and patho-physiological conditions. Housekeeping and other essential genes are distributed uniformly across different chromosomes thereby making any chromosome indispensable.
"Housekeeping genes are genes that are required for the maintenance of basal cellular functions that are essential for the existence of a cell, regardless of its specific role in the tissue or organism. Thus, they are expected to be expressed in all cells of an organism under normal conditions, irrespective of tissue type, developmental stage, cell cycle state, or external signal."
http://www.cell.com/trends/genetics/pdf/S0168-9525(13)00089-9.pdf
Intriguingly, chromosome X lacks housekeeping genes. A recent study suggested a possible explanation for this, as follows: "In the end, we have found the answer to be quite simple. Whereas most chromosomes operate in pairs, meaning there are two copies of each gene in every cell, in contrast, we only have one active copy of the X chromosome. This means it is not sustainable for highly active genes to be on the X chromosome. Housekeeping genes tend also to be highly active – they just couldn't survive on the X.”
http://www.bath.ac.uk/news/2016/01/12/x-chromosome/
Gene expression is regulated through transcriptional and translational regulation of genes to generate tissue-specific mRNA. Moreover, through alternative splicing a gene can code for multiple types of proteins. Alternative pre-mRNA splicing is widely used by (higher) eukaryotes to generate different protein isoforms in specific cell or tissue types. This means that the same gene can have different gene products in different cell types.
"Alternative splicing is a mechanism for generating a versatile repertoire of functionally different proteins within individual cells. The significance of alternative splicing is clearly evident in highly specialized cells such as neurons. For example, all of the main neurotransmitter receptors contain subunits that are alternatively spliced, which influences their localization, as well as their ligand-binding, signal-transducing and electro-physiological properties."
http://www.nature.com/nrn/journal/v2/n1/full/nrn0101_043a.html
http://nar.oxfordjournals.org/content/30/17/3754.short
http://genomebiology.biomedcentral.com/articles/10.1186/gb-2004-5-10-r74
Protein-coding sequences account for only a very small fraction of the genome (approximately 1.5%), and the rest is associated with non-coding RNA molecules, regulatory DNA sequences, LINEs, SINEs, introns, and sequences for which as yet no function has been determined. Furthermore, gene expression is controlled by regulatory elements that can be located far away along the same chromosome or in some cases even on other chromosomes. Genes and these regulatory elements physically associate with each other resulting in complex genome-wide networks of chromosomal interactions.
https://en.wikipedia.org/wiki/Human_genome
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2653627/
The genome is very intricate and consists of elements that interact with each other to regulate gene expression and to carry out various functions. Loss of any of these elements may affect other elements and disrupt cellular homoeostasis, resulting in cellular dysfunction, death or cancer.
I hope this somewhat answers your question.

Perhaps you can add a note that the housekeeping and other essential genes are distributed uniformly across different chromosomes thereby making any chromosome indispensable.


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DNA replication : binding
Regarding an activator, does the C amp cap complex, bind to the coding strand, the template strand, or both?

Your question makes it sound like the coding strand and the template strand are single-stranded when the cAMP CAP protein is bound. In fact, the recognition site for transcriptional activators and repressors are usually double-stranded, so the answer is both.

I agree with you but it's technically possible for a protein to make meaningful contacts with only one of the strands, although this is probably not what he meant.

*she .... you can't edit comments?

Both. You should note that activation in this case involves recruitment of RNA polymerase to drive transcription, and that this process is irrelevant to DNA replication. B in the figure shows amino acid contacts (from CAP) with specific nucleotides in the DNA duplex.
DNA binding by CAP: structure of the CAP-DNA complex.
(A) Structure of CAP in complex with its consensus DNA site (PDB 1RUN) [14], showing primary- and secondary-kink sites. CAP is in cyan; DNA and cAMP bound to CAP are in red. The crystallization DNA fragment contained a single-phosphate gap between positions 9 and 10 of each DNA half-site (Fig 1b).
(B) Summary of CAP-DNA interactions. Shaded boxes indicate positions at which CAP exhibits strong sequence preferences [11,15,16,17]. The black circle, black rectangles, and black diamonds indicate, respectively, the two fold-symmetry axis, the primary-kink sites; and the secondary-kink sites. The black vertical lines indicate the positions of single-phosphate gaps present in the crystallization DNA fragment. The cyan ovals and cyan circles indicate, respectively, amino acid-base contacts and amino acid-phosphate contacts.
Figure from:
Catherine L. Lawson, et al. 2004. Catabolite activator protein (CAP): DNA binding and transcription activation. Curr. Opin. Struct. Biol. 14:10.