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What color was the most recent common ancestor of all swans?
Was the most recent common ancestor of all swans black, or white, or some other color? How do we know, and how certain can we be?

Reptiles are thought to be the common ancestors of birds. Their skin color is not known, as that does not appear in the fossil record.

Your comment made me realise I'd phrased the question imprecisely. I've edited it to put in the words "most recent".

According to the known phylogeny of Anserinae in this paper,

Cygnus atratus (the black swan) is most closely related to Cygnus melanocoryphus (the black-necked swan). All of the other swans in the genus Cygnus are white, or close to white.
Therefore, it is reasonable to assume via maximum parsimony and maximum likelihood that the two genera evolved their blackness from a white ancestor, and not that all of the swans independently turned white from a black ancestor.

authors: user1205901 - Слава Україні


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Is it possible to accurately measure micronutrient levels with the blood volume from a Dermal / Capillary puncture?
I have not been able to find much information beyond what tests are normally done with Capillary puncture sampling, as opposed to what tests are possible.
Could we test for a single micronutrient, or maybe some subset of nutrients with the blood drawn in this way? Is the issue purely volume, or are there other factors?
Thanks!

Welcome to Biology! What exactly do you mean with micronutrient? An example would be best, as trace elements may have very different detection limits than vitamins.

Thanks :) And by micronutrient, I was referring to any nutrient you would see on a nutrition label (yes, I know that's broad). Is there a good resource/chart that has micronutrient specific-info on testing methods / requirements? Or even just a good place to look for that kind of thing (I can do the research, as soon I can find a good place to look :) ).

Detection methods are constantly getting better, requiring lesser amounts of blood to make a determination. In newborns, a heel blood sample (of capillary blood) is used to detect up to 40 (sometimes more) disorders from maple-sugar urine disease and hypothyroidism to hemoglobinopathies and organic acid conditions. If such large molecules can be detected in capillary blood, smaller molecules should as well.
There are differences in central venous sampling and capillary blood sampling, but it could be argued that since the capillaries are the site of exchange of nutrients, this is the most accurate site to determine availability of micronutrients in blood.
One reason labs take more blood than required for the test is to run a second analysis if the first is abnormal. Although it's not done for every abnormal, clinicians often want to confirm significant abnormals before treating a possible lab error.
Newborn screening tests
Newborn Screening
Conditions Screened By State
A Layperson's Guide to Tandem Mass Spectrometry

Hey thanks for the answer and links! Would love to dig more into the specifics on the differences between central venous sampling and capillary blood sampling, re: nutrients and blood content -- any resources you could recommend?

@mattmattmatt - Gosh... I started learning about that, um... in 1977. Google scholar using the words "arterial, venous, capillary blood X" should help! :)

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Mathematical models of lineage selection
I'm interested in the concept of lineage selection (Aboitiz, 1991) as an explanation for why traits would be selected for that enhance the rate at which evolution can occur, rather than directly enhancing an individual's fitness. (Such traits could include gene duplication; body plans that can easily be adapted to new niches; learning (which enhances evolution due to the Baldwin effect) and so on. Questions about the evolution of such traits are collectively termed "evolution of evolvability.") The term "lineage selection" does not refer to group selection or kin selection, but simply to selection between distinct genetic lineages in a mixed population.
What I would like to know is whether a mathematical theory has been developed along the lines of the Price equation that can capture the concept of lineage selection and make predictions about it. Lineage selection does not appear to be modelled by the Price equation itself, at least not in a straightforward and obvious way, because on the face of it the Price equation only directly accounts for the relation between a trait and the number of offspring in the next generation, rather than the number of surviving descendants several generations later, which is what is required for lineage selection.
The reason I'm looking for a mathematical model is that there are a number of intuitions that many people seem to share about lineage selection and I'd like to understand what assumptions are needed in order for them to be true. In particular, it seems clear that large populations are needed for lineage selection to be effective, and I'd like to understand precisely the relationship between population size and the effectiveness of lineage selection. (My intuition is that with a population size of around a million, lineage selection can select for traits that have a beneficial effect around 20 generations later, since $1,000,000\approx 2^{20}$, but this intuition lacks a formal basis.)
A literature search did not turn up anything along the lines of what I'm looking for, but this is not my main field and I may simply not know the most appropriate search terms to use.

Question that is a bit related: Empirical evidence for species selection

I think that there is quite a good agreement among the kin selectionist community that kin selection and group selection is exactly the same thing (see here for example).

You may want to have a look to this post that talks about kin selection and this post that aims at providing an intuitive explanation for why kin selection and group selection are the same thing

@Remi.b I'm pretty aware of that argument (not sure which side I fall on), but lineage selection in the sense I intend it is not the same as either of them - it's not about adaptations that benefit relatives, it's purely about adaptations that benefit your descendants, several (or many) generations later.

@Nathaniel have you  had any luck finding this here or elsewhere?

@sterid I didn't find it in the literature, so I decided to do the research myself. An initial conference paper version of the work should be published soon - I'm revising the manuscript now. I will try to remember to post here once it's available online.

Hi, @Nathaniel, wondering whether the manuscript is complete.  Also, could you explain your 2^20 intuition?

@sterid this ended up being part of a conference paper here, but that didn't include the Price equation aspect. I actually have made some progress on that, and plan to publish it this year hopefully. (But I've not started writing it up yet.)

@sterid the 10^20 intuition turned out to be about right for a well mixed population. The reason is that a neutral mutation will be fixed or become extinct after a time that's approximately the logarithm of the population size on average (multiplied by some constant). You can only have competition between lineages during that the time they both coexist, so fixation time limits the time scale that lineage selection can act upon.

@sterid however, in populations where dispersal is limited, fixation time scales only polynomially with population size, and for that reason the time scales for lineage selection can be much, much longer. This is the main result of the paper I linked above.

I've asked a somewhat similar but narrower question on TCS:  https://cstheory.stackexchange.com/questions/42513/are-there-experiments-in-artificial-life-on-the-emergence-of-sexual-reproduction Crickets to that as well, insofar. Section III of https://www.biorxiv.org/content/10.1101/107847v1.full basically goes over why this is hard to model.

The writings by Samir Okasha (philosopher of biology/science) could be a good starting point. In his book Evolution and the Levels of Selection, he explicitly uses the Price equation to discuss selection at multiple levels (e.g. chapter 2.3: Price's equation in a hierarchical setting), and also derives a multi-level version of the Price equation:
$$\bar{w}\Delta\bar{z} = Cov(W,Z) + E(Cov_k(w,z))$$
where the first part on the right hand side represents collective-level selection and the second part particle-level selection. This is mostly aimed at aspects of group-level selection though. There is also a chapter on "Species Selection, Clade Selection, and Macroecolution" (ch. 7), but this is not directly tied to the Price equation. A note though; I own the book and have read parts of it casually, but I haven't worked with the Price equation myself, and I haven't checked exactly how the extended version of the Price equation is developed and used in the book.
A couple of references that might be useful are Frank (1998) (and other papers by him) and papers by Vrba. The work presented in this recent conference abstract by Rankin, Fox et al (2014), "Using the Extended Price Equation to Analyze Species Selection in Mammalian Body Size Evolution Across the Paleocene/eocene Thermal Maximum", seems to describe exactly the type of theoretical developments that you are looking for (I didn't attend the conference, and haven't heard the talk though).

It's fairly straightforward to expand the Price equation if you fix the genetic operators. This was done in one CS-oriented paper. Bassett et al. (2004) (preprint):

where k iterates over the genetic operators.
But it's not at all straightforward (and I suspect not possible) to do that for an all-encompassing abstract notion of evolvability (of every rule/mechanism that might be evolvable). I mean if the rules/operators are countable, you could write an infinite sum on the right hand side of that equation, but it's not clear how that helps with anything in practice.
If you use the multi-level (= group selection) version of the Price equation (as suggested in the other answer), you still have to decide (a priori) on grouping so basically enumerate over the (potentially evolvable) operators, albeit do that in terms of groups. For example, an operator can be recombination, which is the same as deciding to have groups for sexual and asexual organisms. I think the operator approach may be preferable in some cases because it can be real-valued (i.e. a continuous quantity). Although not using the (above) Price equation explicitly, such research on evolvability of specific (continuous) operators has been carried out, e.g. on the optimal recombination rate (Lobkovsky et al., 2016) etc.

On a different tack, and possibly closer to biology as a general idea, in another CS-oriented paper,  Touissant (2003) proposed a (non-trivial) notion of embedding the evolvability of the parameters of interest into the "normal" genotype space.

In simple cases where the genotype space decomposes (strategy
  parameters) an embedding space of neutral sets is obvious. To generalize to arbitrary neutral sets and arbitrary genotype-phenotype mappings we introduced the σ-embedding, i.e.,
  we embedded neutral sets in the space of probability distributions over the genotype space
  (exploration distributions). [...]
the question of how variational properties evolve has also been raised in numerous
  variations (pleiotropy, canalization, epistatis, etc.) in the biology literature. These discussions aim at understanding how evolution can handle to introduce correlations or mutational
  robustness or functional modularity in phenotypic exploration. Our answer is that variational properties evolve as to approximate the selection distribution. If, for example, certain
  phenotypic traits are correlated in the selection distribution F, then the Kullback-Leibler
  divergence decreases if these correlations are also present in the exploration distribution σ.

Alas he doesn't derive anything resembling a Price equation using his approach. (He does have a twin notion of evolution and σ-evolution, but there's no hierarchy/grouping.) Whether this notion is actually biologically useful, probably depends crucially on the embedding.
There are some papers in actual biology research that are closer to this idea of "embedded" evolvability. For example one paper (Lehman and Stanley, 2013) which looks at (actually defined evolvability in terms of) phenotypic variability.

one widely-held conception of evolvability as the capacity of an organism to “generate heritable phenotypic variation” [...], which is also the definition adopted in this paper. While evolvability is also sometimes discussed in relation to adaptation [...], the chosen definition reflects a growing consensus in biology that phenotypic variability in its own right deserves study in the context of evolvability

So this is one kind of concrete embedding. But no Price equation based on this idea that I could find in there...
On the other hand Rice (2008) does propose a stochastic extension of the Price equation, based on this idea that variability matters (or is all that there is to evolvability according to some):

A number of studies have shown that when fitness is treated as a random variable, meaning that each individual has a distribution of possible fitness values, then both the mean and variance of individual fitness distributions contribute to directional evolution. Unfortunately the most general mathematical description of evolution that we have, the Price equation, is derived under the assumption that both fitness and offspring phenotype are fixed values that are known exactly. The Price equation is thus poorly equipped to study an important class of evolutionary processes. [...]
I present a general equation for directional evolutionary change that incorporates both deterministic and stochastic processes and applies to any evolving system. This is essentially a stochastic version of the Price equation [...]
This [new] equation shows that the effects of selection are actually amplified by random variation in fitness.

Finally, (as acknowledged in this latter paper) all variations on Price equation are over immediate successive generations. If you want to iterate forward (to infinity) you need to use a diffusion equation/model. (See chapter 7 in Durrett's book, for instance.)

Thank you, this is a very helpful answer with some great references, which I will work through in detail.

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Can bioluminescence be used for cancer or tumor detection?
What diagnostic applications, if any, are there in using bioluminescence to detect cancer or tumors (in vivo)?

Could you elaborate on your intenstions? E.g. are you talking in vivo labeling (patients) or in vitro (cell cultures).

A list of all possible applications would make a very long textbook. If you could narrow that down to just diagnostic applications for example, that would help greatly.

Not in human but you can use this technique with genetically modified model organisms as described here.
The procedure is quite simple, you express the luciferase enzyme under the control of a specific promoter (specific for your cell type, like cancer) and provide luciferin via intravascular or intraperitoneal injection. The targeted cell type (for example cancer) will light up.
If you want to use that as a diagnostic tool in human you can't as the organism must express an enzyme catalyzing a bioluminescent reaction. Actually with the advance of genome engineering tools you might be able to do that even in humans (e.g. using CRISP/Cas9).
What is the advantage of bioluminescence over fluorescence? I might be wrong but I don't think there are any. I would rather express a fluorophore rather than an enzyme that requires a substrat.

What would a cancer specific promoter be? You could target a particular cell type, but how would you distinguish between tumorous and healthy? They have the same promoters. You could, perhaps, use promoters that are only active in proliferating cells but that limits the usefulness of the approach. More importantly, how would you detect the bioluminescence in, say, the liver?

@terdon several exist. See this list for example. I agree you can't detect bioluminescence of internal organs but strictly speaking you can use bioluminescence to detect (some type of) cancer cells which was the question (can it be used?). I also don't think bioluminescence is a great detection tool but this would be my opinion and not actual facts.

Huh, I stand corrected, thanks. I didn't know there were tumor-specific promoters.

@terdon, well you are not completely wrong :) Some promoters are more/less express (which give them the "specific" tag) in tumors than normal cells but there are, as far as I know, no promoters totally OFF in normal cell and totally ON in tumor cell or vice-versa. Still that should be sufficient to apply that technique.

Ah OK, that makes more sense. I was having trouble imagining how a promoter could be completely specific to tumor cells.

@terdon. biology has a special usage of the term "specific"...

I don't think CRISPR would be appropriate to insert an entire luciferase gene. The luciferase gene is just too large, and if you could get the luciferase template DNA into the cell, why not just deliver the whole working plasmid instead of relying on CRISPR to correctly insert it?

As far as using mice goes, you can get expression of luciferase/GFP through something like lentiviral transfection to a subconfluent tumor cell culture. Non-invasive imaging equipment like IVIS 200 can then be used to view luminescence in vivo. We're generally detecting grafted tumor cells, however, so i don't believe the process exists to simply detect new tumors, especially in humans.

@Kendall Agree. I am also quite certain it does not exist in human. My answer is tailored to the question which is "using bioluminescence to detect cancer or tumors (in vivo)?". Does not speak about any organisms or about native, induced or graphed tumors so I just went as general as the question is.

@user137 I just mentioned that as an eventuality to apply that to humans one day. For model organisms I agree any ways of delivering the construct should do. This goes way beyond the question but CRIPSR/Cas9 actually might be required as if you want to do genome engineering in humans you need to insert the gene in a very specific location in the genome as you probably cannot directly target only tumors cells but likely just some closely-related cell types. In a more general view, to be one day applied, genome engineering will have to be very specific in the genome modifications provoked.

@Kendall This paper shows that existing tumors in mice can be transfected with mRNA. It's not high level expression yet, but you could use something like this to make cancer cells express luciferase, or a suicide gene.

In vivo, none.
Bioluminescence is cool, but it's not a powerful light source. Even if you could tag a cancer cell (all of them), unless it were on your skin or in your eye, you wouldn't be able to see it, even with some kind of scope.

Wrong you actually can.

@cagliari2005 Can you then elaborate your comment?

@chris writing an answer right now

Bioluminescence could not be used but it is possible to 'tag' with fluorescence to better view pathways within the body. Tagging is often used in research, a simple google search should produce a plethora of results.


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Can other animals see black differently?
I am not sure if this is the right place for this question, but this is a debate that has been going on between two colleagues for days and I need a resolution because it's driving me crazy. So any help would be appreciated.
It is a common philosophical argument that it is impossible for one person to know if another person is at the same place on the colour wheel (e.g. how I see blue and how you see blue could be different, and we will never know). By that reasoning, it is possible that some species see colours differently to us. However, black and white are not the colour wheel because they are not colours. So essentially, the question is, could another species that "sees" by sensing light with their eyes as humans do ever see an "absence of light" as a colour OTHER than black.
I am not quite sure what these two imbeciles are debating, but I believe they are arguing as follows:

Party 1: Black and white are shades not colours, and therefore, even if another species saw colours differently, they would always see black as black, white as white, and all shades of grey relative as usual to the colours they see.
Party 2: Black is only inserted into our vision by our brain to resolve the "problem" of not receiving any light. So, therefore, it is equally possible that another species could deal with this problem" differently, and they will see something other than black.

As to how humans define shades and colors is irrelevant. we can never look into the brains of an animal. We can't even verify if between-human differences exist between black and white. They are perceptual constructs. it's all in your brain. Therefore party 2 is the least incorrect.

Yes, my point exactly. Party 1 is arguing that it is impossible for such between-human differences between black and white to exist, because they simply indicate the "raw amount of light" I guess.

Or are you simply saying we don't know enough about how the brain works to answer that question?

What is incorrect about party 2's argument? Or is that the bit we can't tell? Sorry if I'm going round in circles..

it states "They will see something differently" - we can't tell. what experiment would tell you what an animal sees? we can't even tell apart what two humans perceive.

Yes, animals can see 'black' differently, in terms of different shades, similar to what you stated about humans perceiving different hues of 'blue'. It is all relative to the cones in the eye of the referenced animal. Animals that see in black-and-white see several different hues of both, black and white. Animals that depend on color to judge the ripeness of a food also see in several different hues of black. For example, a parrot differentiating between seeds that humans may perceive as both being 'black'. Here is a color chart showing the colors that bees can perceive in juxtaposition to humans; it indicates high differentiation between hues of black, as opposed to humans' low differentiation.

Hues of black? That is grey shades. I don't see grey shades in the figure. If you are referring to the 340 nm peak in bees, that is ultraviolet... . -1

So, would the statement "Any animal that sees light as we do will see black just as humans do", be incorrect? If so, then in this sense, black is a colour like any other?


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Homology ratio comparison between different species
I found the following homology ratio:
protein coding genes of the organism with an homolog in mouse / all protein coding genes in the organism
I have done this for all protein coding genes between several organisms and mouse using a phylogenetic-based approach. I have noticed that the ratio found between an organism and mouse is greater than the ratio between another organism and mouse! On the other hand the second is evolutionary closer to mouse than the first.So:
1.Is such an approach trying to quantify homology? Which i know is not correct as homology is qualitive measure.
2.Can we compare the ratio of homology between the above 2 couples od species or such a comparison is biased?
3.Shouldn't the ratio of homology be proportional to the evolutionary distance of the organisms (according to conservation)?
As you can understand, in the way i calculate the above ratio, i don't take into account the one-to-many or many-to many relationships! I just take into account the genes that have at least one homolog in mouse..is that the bias of my calculation?

You want to compare the homology of proteins between species? To do so, see how phylogenetic trees are built.

There is the path of gene trees and species trees though! I am checking genes so i should care about the gene trees,correct? For example :  It is very possible that in my analysis of gene X, species A is closest to mouse, while for gene Y species B is closest to mouse and that's where a bias is introduced!

I don't understand your example, sorry.

Phylogenetic trees are usually much more complicated statistically/mathematically than simply ranking based on coding DNA homologies. Not going into the details (because I don't know enough about it) but in essence they try to reconstruct the best fitting tree amongst multiple organisms taking in account effects such as horizontal gene transfers and sequence conservations. Bottom line it is not a simple pairwise comparison between two organisms coding sequences and I am not too surprise you see an organism being closer than you would expect. My advice to you is trust the phylogenetic tree.

1.Is such an approach trying to quantify homology? Which i know is not correct as homology is qualitive measure.

A common approach to identify orthologs (homology between two genes resulting from a speciation event) it 'best bidirectional match': if you blast gene A (in species 1) against all genes of species 2 the best match is gene B, and if you blast gene B against all genes of species 1 the best match is gene A.

2.Can we compare the ratio of homology between the above 2 couples od species or such a comparison is biased?
3.Shouldn't the ratio of homology be proportional to the evolutionary distance of the organisms (according to conservation)?

Not necessarly. The fact that two genes diverged a very long time ago does not prevent them from being homologous. Homology is about shared ancestry (here of two genes) and not about evolutionary distance.
Could you clarify how you get the homologies? Did you compute them yourself (if so how) or did you use a specific database?


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Are free-nuclear division and endomitosis the same?
As far as I understood it, both are cases of karyokinesis, not followed by cytokinesis.

No. If you google the terms you'll get a lot of sites with definitions. For example:

Nuclear division
Definition
noun
The process by which a nucleus divides, resulting in the segregation of the genome to opposite poles of a dividing cell.

source: http://www.biology-online.org/dictionary/Nuclear_division
Edit:
or

free nuclear division    mitotic division of nuclei without accompanying cytokinesis, i.e. nuclei divide in a common cytoplasm, the cells walls only forming around each later

source: http://ecflora.cavehill.uwi.edu/bio_courses/bl14apl/Gloss.htm
versus

endomitosis
mitosis taking place without dissolution of the nuclear membrane, and not followed by cytoplasmic division, resulting in doubling of the number of chromosomes within the nucleus.

source: http://medical-dictionary.thefreedictionary.com/endomitosis
or a bit more revealing:

Duplicated chromosomes produced by endomitosis exist as discrete units
in a single polyploid nucleus or may be packaged into separate nuclei,
depending on the phase at which mitosis is aborted

source: http://en.wikipedia.org/wiki/Endoreduplication
So as you see by definition nuclear division is part of a bigger process (cell division), and accoriding to the first source karyokinesis is a synonim for nuclear division (karyo = nucleus kinesis = moving, both come form greek language).
Edit:
If you check the definition above, you can see that free-nuclear division is a mitosis without cytokinesis, thus chromosome separation still occurs.
In endomitosis the can end up with a polyploid nucleus, in contrast to the other two aforementioned mechanism where no polyploidy occurs.

I was talking about free nuclear divisions, not just nuclear division - which is just karyokinesis. Free nuclear divisions happen for instance during formation of the female gametophyte from the megaspore in angiosperms - the nucleus divides but separate cells don't form.

Oh I see, I missed that part sorry. I will look into that

I have a doubt though: in case when endomitosis is aborted in between anaphase (i.e. centromere splits but chromatids are not segregated) then in that case I thought nuclear membrane has disappeared in prophase, and now reforms to enclose 4n chromosomes. But one of these definitions says the nuclear membrane does not disintegrate - so how can spindle fibres attach to the chromosomes? Then again, since chromatids don't separate, spindle fibre formation isn't needed and may not occur.

Errors / failures / abortions in during mitosis results (most of the time) in pausing the process to try to fix the problem and if its not possible than the cell undergoes apoptosis to avoid having cells with abnormal genome. If somehow the cell still gets through (cell) division, then you get abnormal cells with chromosome trisomies, missing chromosomets etc.

In the cases of pollen grains free nuclear division occurs. entering into the s phase the chromosome no remains as 46 but the DNA doubles ie 4n condition occurs. During the anaphase the sister chromatids separate and reaches both ends. And when telo phase occurs nuclear membrane is surrounded around 2 genetic material. But cytokinesis is blocked there. But when again this cell enters s phase there again the genetic material replicated ie 2 nucleus having 4n condition is formed.this is free nuclear mitosis. These chromosomes doesn't separate in anaphase due to failure in attachment of spindle fibres. So karyokinesis also get stopped resulting cell to 8n condition or polyploidy. This is endomitosis

Welcome - can you add your sources here so people can background read on your answer?


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Can a woman possessing 1 mutated allele show attenuated color-vision deficiency?
Women possess two X chromosomes. However, during development, when the embryo has about 32 - 64 cells, one of these chromosomes is randomly inactivated (in each cell) by an lncRNA named Xist. As a consequence, females are mosaics.
I was interested if this might affect phenotypes of X-linked genetic diseases, for example...
1) Is it possible for a woman who is heterozygote to color vision deficiency be "partially" color blind, considering that some of her cones will only possess the mutated allele?
2) Is it possible that a heterozygote female who carries a dominant allele for a X-linked disease be asymptomatic?
Any references on these issues are welcome.

Short answer
Skewed X-inactivation may lead to phenotypic manifestation of X-linked color blindness.
Background
What an interesting question!
In a study by Jorgensen et al. (1992) two female identical twins that were heterozygotes for X-linked deuteranomaly were investigated. Phenotypically, deuteranomaly refers to anomalous trichromacy, i.e., reduced perception of a color. Note that deuteranopes are totally color blind. Deuteronomaly in the twins was associated with a defective gene derived from their father. Interestingly, while monozygotic twins are genetically identical, one of the twins was phenotypically deuteranomalous, while the other had normal color vision.
Analysis of skin cells of the color vision-defective twin revealed that almost all skin cells had the paternal abnormal X chromosome active, explaining her color-vision defect. In contrast, skin cells from her sister with normal color vision had predominantly the maternal X chromosome active. Hence, deuteranomaly in one of the twins could be explained by an extremely skewed X inactivation.
As pointed out by @mdperry, extreme skewed X-inactivation is rare, and most heterzygous females for color blindness (carriers) are indeed asymptomatic (Jordan & Mollon, 1993). Regarding your second question, all gene mutations leading to color blindness are recessive (NIH).
References
- Jordan & Mollon, Vis Res (1993); 33(1): 1495-1508
- Jorgensen et al. Am J Hum Genet (1992); 51: 291-8

Your theoretical understanding of the ramifications of X-chromosome inactivation is excellent (e.g., the two situations you described).  However, it is important to consider the size of the resulting clones. At that early stage of embryogenesis only ~ half (or less) of those cells will go on to contribute to the fetus, the rest will form the placenta. Also at this stage each cell is likely totipotent, and capable of contributing to all of the different tissues, but eventually the daughters of these cells will become committed, or determined in their developmental lineage. Depending on how much mixing of cells occurs prior to determination, I think it unlikely that within one retina the cone cells would originate from more than a single clone--so I would think that either they all are + or the all are mutant. Since there is L-R symmetry between the two optic cups that will give rise to the developing eyes, I think it is more likely that one female could have one eye that is mutant and one eye that is +.  Given that the prevalence of red-green color-blindness in males approaches 7 % of the population, we can infer that heterozygous females are very common, yet to the best of my knowledge there are not millions of females with partial color-blindness--they either have it (m/m), or they don't (+/+ & m/+). So I think a mosaic female with one eye color-blind and one eye normal must be exceedingly rare.
Re: autosomal dominant diseases, it all depends on the tissue(s) and the affected developmental stage. The OMIM, Mendelian inheritance in Man database may have some discussion of this interesting point(?).

Although a nicely approached answer, it seems to be build from assumptions rather than facts. -1 With some references it would be an excellent answer


text:
Can encoding of miRNAs in introns not cause dysregulation of gene expression?
For example, consider a gene X which has an intron which encodes a miRNA that downregulates expression of another gene Y.
When the gene X is translated, this miRNA will appear as a byproduct of splicing, then expression of gene X will inhibit expression of gene Y, which could be deleterious.
How did the mechanisms of gene expression evolve to avoid possible unplanned interference in gene expression?

Deleterious effects on gene expression are selected against.

evolution does not think. The ones with any interference would have a disadvantage during selection.

Agree with the two above comments, selection will select against such a deleterious effects.

i understand that evolution is not planned, but how enconding of miRNAs in introns could be used as a regulatory mechanism? For example, are there patterns?  miRNA enconded in the intronic sequence of the gene regulating the expression of the same gene, or a related one? Because if miRNAs occured randomly in introns they would not be good regulators.

I think this might constitute part of the epistatic effects that are being discovered as simple variations turn out to be insufficient in explaining phenotypical differences. So, yes, there must be patterns. There are two recent papers showing that many more miRNAs exist and are expressed in tissue dependent manner. My guess is the patterns will be slowly established by looking into the new intronic miRNAs and their targets.


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Possible genotypes for blood types?
If I am blood type B, what are all the possible genotypes that could be expressed by my parents?
I think it might be 16 but I was reading online and saw this:

Similarly, someone who is blood type B could have a genotype of either
  BB or BO.

So if someone can help me answer this, that would be great.

Parent 1 and 2 have each 5 possible genotypes (OO, AO, BB, BO and AB).
Here a Punnett square with each possibilities. I highlighted the possible parent genotypes.

The total number of possible crosses is exactly 21. Note that here A = Ia, B = Ib and O = i.

OOxBB,OOxBO,OOxAB
AOxBB,AOxBO,AOxAB
BBxOO,BBxAO,BBxBB,BBxBO,BBxAB
BOxOO,BOxBB,BOxAO,BOxBO,BOxAB
ABxOO,ABxAO,ABxBB,ABxBO,ABxAB

This is starting from the information based on your blood type only (i.e. no information about your genotype).
Some background information. Antigen expressing alleles (here referred as Ia or A and Ib or B) are dominant. Not expressing an allele is notated i or O. Being of blood type O is when you don't express both alleles so it is a recessive trait (only possible genotype is ii or OO genotype).

You probably shouldn't call an AB individual homozygous.

@canadianer thanks for pointing that out. Modified the table.

Your answer is better, so I'll just delete mine to avoid confusion.

@poka.nandor was getting messy without a table ;)

@cagliari2005 yeah I should have done the same to avoid missing possible crossings. I feel bad about it... I mean not about you having a better answer, but about me being careless.

21 crosses could be many more if you considered minor types as A2, A3, B3 or hybrid alleles as Ax, Bx or chimera AB alleles as cis-AB, B(A). These rare phenotypes break standard 4 type rules, for example, Ax/O genotype could be both type A or type O. It depends if you talk about genetcis or blood compatibility.


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Are Gram negative bacteria classified as such because of their negative membrane potential?
Does the membrane potential usually quoted for Gram negative bacteria (e.g., E. coli) refer to the potential across both membranes? - If yes, then does the potential fall more over the inner or outer membrane? Are there any studies that estimate/measure the relative fraction for each membrane?
I assume that the measurements of potential are usually carried out by inserting an electrode inside the cell and measuring the difference with the outside, this would make the answer to the first question yes.

There is probably a clue in the context. Generally though potential refers to the intra-extra cellular potential (i.e in this case both membranes). Is there a particular source you can cite that is ambiguous?

This is a good answer to the first part of the question. My motivation for asking is partly that I would like to understand the membrane potential experienced by a trans-membrane protein present only on the inner membrane.
Even a rough educated guess (with reasoned argument) would be helpful. For example: Would the presence more proteins that are driven by membrane potentials being located on only one of the membranes be a good indicator that the the potential would be likely to fall mostly over that membrane?
If no literature exists, is it reasonable to construct an argument in this way?

I suggest you edit this question to ask only about Gram-staining and open a new question that asks about Gram-negative membrane potential.

Short answer
The distinction between Gram positive (Gram+) and negative bacteria (Gram-) has absolutely nothing to do with membrane potentials; it is all about the Gram staining procedure.
Background
The Gram staining was named after the Danish bacteriologist Hans Christian Gram, who originally devised it in 1882 (Gram, 1884). Gram staining is a common technique used to differentiate two large groups of bacteria based on their different cell wall constituents. The Gram stain procedure distinguishes between Gram+ and Gram- groups by coloring these cells violet or red, respectively (Fig. 1).
Gram+ bacteria stain violet due to the presence of a thick layer of peptidoglycan in their cell wall, which retains the crystal violet these cells are stained with. Gram-, on the other hand stain red, which is attributed to a thinner peptidoglycan wall, which does not retain the crystal violet during the decoloring process.
Gram staining procedure
The procedure involves staining the cells with a crystal violet dye. Next, an iodine solution (iodine and potassium iodide) is added to form a complex between the crystal violet and iodine, which is insoluble in water. Then, a decolorizer, such as ethyl alcohol, is added to the sample, which dehydrates the peptidoglycan layer, shrinking and tightening it. The crystal violet-iodine complex is not able to penetrate this tightened peptidoglycan layer, and is thus trapped in the cell in Gram+ bacteria. In Gram- bacteria, however, the thinner peptidoglycan layer does not retain the crystal violet-iodine complex and the color is lost. Lastly, a counterstain, such as the weakly water soluble safranin, is added to the sample, staining it red. Since the safranin is lighter of color than crystal violet, it does not disrupt the purple coloration in Gram+ cells, but it does stain the decolorized Gram- cells red.

Fig. 1. Gram+ bacteria (left) and Gram- on the right. source: Lab Tests Online
Reference
- Gram, Fortschritte der Medizin (1884)

Good answer to the question. However it's a classic XY problem. OP is actually looking for the membrane potential for the periplasmic space to the cytosol.

@James Thanks! Regarding your point, I agree and that's why I upvoted the other answer here.

The following is not an answer to the original question: "Are Gram negative bacteria classified as such because of their negative membrane potential?" but to the questions later in the text.

Usually the membrane potential is given for the inner cytosolic part and the extracellular space, for E. Coli it is around -120 mV; see also this article.
Due to the small size of E. Coli it is very difficult to reliably and accurately measure the membrane potential.
For the periplasm only the Donnan potential is reported, it ranges between 5 and 100 mV, typically around 25 mV.
I don't know about any report measuring the relative contribution but I would guess that the inner part makes up most of the total potential.


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DNA polymerase in PCR (polymerase chain reaction)
Can the DNA polymerase in PCR (polymerase chain reaction) recognize both DNA and RNA for use as a template?
I want to know is it possible if my primers bind to contaminant RNA and then any DNA polymerase like Taq DNA polymerase use this strand as the template for elongation?

Do you want to know if a PCR reaction is possible with different enzymes for DNA and RNA?

Hi Chris, I want to know is it possible if my primers bind to an contaminant RNA and then any DNA polymerase like Taq DNA polymerase use this strand as template to elongation and continue reaction?

I have edited your question to make it clearer, please roll this back, if this is not ok for you.

No, this does not happen, as the DNA polymerases used for PCR are DNA dependent. This means that they only synthesize DNA when it is bound to DNA. Even if your primers bind to the RNA, the polymerase will not starting new strands here. To use RNA as a template for PCR you first need to reverse transcribe it.

And one more that may 3-HO end of binded nocleotide contaminant(small crashed RNA ) lead to give unwanted fragment?

@M007 I don't get your second question, sorry.


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How do BCAA's promote faster muscle recovery?
I am aware that ingesting Branched chain amino acids (BCAA's) prior, during, and after workouts has an effect on muscle recovery due to their difficulty of metabolism. However, how much more efficiently do they speed up recovery versus whey proteins for example?

What are BCAAs? Please define acronyms when posting questions (and answers) here.

"Branched chain amino acids" (valine, isoleucine, leucine) is the general understanding.

Branched chain amino acids. @MattDMo


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Cationic lipid mediated transfection optimization for 150mm dishes
I need to optimize a transfection protocol to transiently express a plasmid encoding a chimera of  eyfp attached to the c term of a Golgi apparatus signaling molecule) in hela cells and hepg2 cells and get as high expression as I can get.
I need enough protein for about 100 wb's. I've seeded hela cells to 12 150mm dishes. And the same with the hepg2. I've prepped mg's of plasmid.
I'm using invitrogens original lipofectamine reagent; not the 2000, or ltx or any of that stuff.
Any suggestions on a protocol here for hela and hepg2 plasmid dna and lipofectamine mediated transfection on such a large plate size.
I figure just scaling up should work but there's some pitfalls here. Look at this table for example when you go from 60 to 100 mm you about double the area, so you also about double the culture volume. However when you go from 100 to 150mm you triple the area, but only increase the culture volume two fold about. This is making my scale-up calculations for transfection look really off:

Despite what the numbers look like, across all values going from 100mm to 150mm you're scaling up by a factor of ~2.76: (a) 152/55 = 2.76, (b) 1.52e7/5.5e6 = 2.76, (c) |avg(30.4-45.6)/avg(11-16.5)| = 2.76.

Ahhh! I should have crunched the numbers cause you R correct. It's a weird concept because when you scale up in vessel size you want all parameters, ideally I would think, to increase at the same rate. However the depth of media can reach a certain point where I believe it hinders growth. When the volume gets to be too much it can take too long for those needed soluble factors to build up in the environment. Also increase in medium depth can delay delivery of soluble oxygen to the cells.  Thank you for seeing through

All my nonsense to make that comment. I think this ? Is a little scatter I'm going to reword it to focus it on the ratio, area and volume if you want to post an answer its yours. I'll post a seperate ? On the hela optimization

@Kendall please post your comment as an answer to close this question. Thanks!

So, for every row on the dish protocol, the entire process is scaled up a discrete value. In the case of 100mm to 150mm, the values are scaled up by about 2.76 across all values:
(a) 152/55 = 2.76, (b) 1.52e7/5.5e6 = 2.76, (c) |avg(30.4-45.6)/avg(11-16.5)| = 2.76
(as answered in comments)


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Can the absorption of vitamins be enhanced?
Are food additives like vitamins better absorbed when you mix them among fruits?
I heard that secondary substances in fruit promote the absorption.

There are two types of vitamins:

Fat soluble vitamins - Vitamins A, D, E, K
Water soluble vitamins - B complex Vitamins and Vitamin C

Fat soluble vitamins get better abosorbed when fat content of food is good. The bile secretion is also very important. These vitamins form miscelles with the fat molecules and get absorbed as such. The absorption of these vitamins can be enhanced by taking fatty diet.
The water soluble vitamins are absorbed freely and they are also excreted freely - Excess are expelled through urine.
There are inter-vitamin competition and some food biomolecules can inhibit vitamin absorption. For example avidin in the egg would bind to biotin and prevent its absorption. The articles below deal a little with such inhibitions.
For more see:

http://healthyeating.sfgate.com/improve-bodys-absorption-vitamins-2898.html
http://www.ncbi.nlm.nih.gov/pubmed/17023940
http://health.howstuffworks.com/wellness/food-nutrition/vitamin-supplements/body-absorb-vitamins.htm


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Why do home-grown fruits tend to taste better than mass-produced consumer fruits?
It is often heard that home-grown fruits and veggies are a lot tastier than the produce found in the supermarket. Although this question may contain a skeptics element in it, it is so often heard there must be at least some biological ground behind it.

Your whole question is built on a supposition that hardly anyone can truly prove.  Even if you narrowed this down to an objective measure of taste under "organic" versus "non-organic" techniques, it's still driven by opinion.

I'm voting to close this question as off-topic because it is based on an unsupported presupposition.

I must say that home grown stuff (fruit, veggies) always taste better (bar the stuff is not overripe and the likes).

Welcome to Biology.SE. Your post might have better to be reformulated to something along the lines of: "it is common knowledge (hope you'll agree) that home grown stuff are better than industrial ones. Why is that? Intuitively, I would think that biotechnology should allow to make fruits that are much more tasty than what a random individual can do in its garden."

"Industrial" fruits and vegetables are not grown as much for flavor as for convenience, pest resistance, appearance, resistance to peel problems, resistance to bruising, etc. etc. Profitability is the main consideration.
There are many varieties of apple grown in orchards that taste wonderful (better than my grandmother's gnarly green apples) but don't hold up to shipping and storage well.
Finally, please don't get your information from fantasy tales. There are so many good sites for attaining information.


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Hand-eye coordination in 3D space
A simple daily event has amazed me and triggered this question. I have read and heard about hand-eye coordination. It quite straightforward when you e.g. want to open a door or play Xbox. In this case either your hand is in your view or your hand will feel the buttons of your Xbox.
But when it comes to catching a ball or try to catch a falling object, our hand is totally out of our view since we are closely following the trajectory of the moving object. But meanwhile our hands moves in a 3D space and align it self perfectly in the path of trajectory correctly. This is what amazed me.
If you can see your hand and the object/ball simultaneously, its just a matter of moving our hand in the path of that ball/object. But having hands totally out of sight but catching the ball/object perfectly every time is amazing piece of nature's engineering.
How humans have achieved such a amazing piece of coordination in a 3D space without seeing where the hands are located?

Body self-awareness?

sight is not the only sense that tell us how our limbs are moving - otherwise blind people wouldn't be able to move

Short answer
Proprioceptic receptors provide a feedback mechanism from the body to the brain, telling the brain what our limbs are doing and where they are with respect to the body without visual feedback being needed.
Background
Muscles, skin and joints contain proprioceptic receptors. They sense position and movement of our limbs and trunk, they register force as well as heaviness. Examples of such receptors are limb tendon organs and possibly also muscle spindles, which contribute to the senses of force and heaviness.
Proprioceptive sensations are influenced by visual input, but operate without it. The proprioceptive system is responsible for the ability to touch your nose with your eyes closed and the examples you have given related to catching a ball while not paying visual attention to the position of your hands.
Afferent signals from these receptors are combined and processed in the brain. Together they form information about limb position and movement. This information is mapped relative to a central body map to determine the location of the limbs in space.  The proprioceptive senses, particularly of limb position and movement, deteriorate with age and are associated with an increased risk of falls in the elderly.
Reference
Proske & Gandevia, Phys Rev 2012; 92:1651-97


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Location of embryo development in angiosperms
What floral organ does the development of the embryos of angiosperms occurs in? Is it the ovary? The pollen tube grows down through the style and double fertilization occurs and the embryo begins to develop in the megasporangium.


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Why introduction of an extra copy of a gene related to pigmentation causes RNA interference in Petunia?
RNAi became famous after Fire and Mello experiment in C.elegans; however, it had been observed before. In the 80's, Jorgensen was trying to increase pigmentation of Petunia flowers by introducing extra copies of chalcone synthetase gene, which encodes an enzyme involved in anthocyanin synthesis.
However, this experiment lead to post transcriptional gene silencing (PTGS) by a mechanism that was not understood at that time, called RNA interference.
Here
you might find more information about the experiment (including the vector used to introduce the gene).
I know how RNAi works by the classical pathway; however, I didn't understand how an extra copy of the gene could generate gene silencing. Introducing of DNA sequences has been used to knock downs target genes, however, generally these sequences are planned so that they will form a hairpin which is recognised by Dicer; probably, the researcher did not use such a sequence. Moreover, exogenenic genes are widely used without resulting in unplanned RNAi.
Does someone know more information about what possibly happened in the experiment to produce RNAi?

The answer is in the slides you provided a link to. The key fact is that Craig & Andy did careful controls to show that it was the presence of dsRNA in both the sense control, and in the anti-sense experimental sample that was responsible for the RNAi-mediated knock-down.  Actually, Ken Kemphues showed this earlier in a Nature paper (the control also knocked down gene expression) but did not pursue the mechanism.
Therefore, I infer that the transgenic gene expression construct introduced into the petunias must also give rise to dsRNA. I am less familiar with the consequences of introducing foreign DNA into a plant cell (e.g., does a single copy become integrated, multiple copies?, is it maintained extrachromosomally?)


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Simplified molecular-input line-entry system
This may be a bit abrupt/vague question, but I didn't know how to proceed the search to get the answer.
What are the properties of a 3D biomolecule which gets ignored when a 3D biomolecule is converted to 1D representation in SMILES(Simplified molecular-input line-entry system)? two properties I found that gets neglected are linkages,interaction properties. By properties I meant isomeric count,isomeric threshold etc. Are there anymore properties that gets neglected?

Hi, could you define 3D biomolecule and provide some reference to SMILES I'm not familiar with these.

http://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system

http://en.wikipedia.org/wiki/Biomolecule

Shame on me for thinking that biomolecule would refer to something special....

A 3D model of a (bio)moelcule represents a physical 3-dimensions. For an experimental structure, each atom has a 3D coordinate (x, y, z) and, if determined by crystallography, an additional isotropic or aniosotropic B-factor (that models atom fluctuations).
A '1D' SMILES is not a physical 1-dimensional representation, and can be converted to a graph (mathematics) representing the chemical structure. The specification of SMILES CAN retain information about structural isomers, stereoisomers (cis/trans; D/L), but not conformers/rotomers, which, unlike smaller chemical structures, IS restricted to certain favorable regions for larger biomolecules.
By "linkage" if you mean chemical linkage such as a disulfide bond, then SMILES can retain such information. By "interactions", if you mean hydrogen-bonding, salt-bridges and even hydrophobic interactions etc., then SMILES does not code in such information, but neither does a 3D model explicitly -- they are implied from the 3D coordinates for each atom.
Thus, converting from a 3D model to SMILES, you would lose

Unusual bond length and bond angle: they are necessarily specified from the 3D coordinates, but in SMILES (or the subsequent graph), they are taken as 'ideal'.
B-factor or temperature factor
Rotomers: e.g. Proteins have favored dihedral angles in both backbone and side chains, which is not specified in SMILES.
"Interactions": certain intramolecular interaction that is inevitable (e.g. salicylaldehyde) is implied in both SMILES and a 3D model. Most others can only be inferred in the 3D model.

can you please tell me how you came to know about these facts?? I tried to find the properties of a 3D biomolecule but couldn't find it.. Is there any book I should follow?

I happen to be a structural biologist. You could check out some books on 'Structural bioinformatics' or 'Chemical Informatics', and download visualization software to play with the 3D coordinates from one of Protein Data Bank(s). (http://www.wwpdb.org/) RCSB hosts a very good overview http://www.rcsb.org/pdb/101/static101.do?p=education_discussion/Looking-at-Structures/intro.html

Okay, I have something to say if you don't mind, can I get your email so that I can contact you when I am stuck with something?

I don't mind. My email is on my profile. There should be many experts here on the forum, too.


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Horns in animals and birds
Are there any carnivores with horns (whether extinct or currently alive)?
Do any flying creatures have horns?
By horns I mean horn like structure.

Why do you want to know, and what do you know from before? Are you aware of the distinction between e.g. horns and anthers (and other types of hornlike structures)? What types you include as "horns" make a big difference to your question.

honestly, @OneFace this is a bit of a 'let me google that for you' question :)   http://lmgtfy.com/

Males of the carnivorous Jackson's chameleon (Trioceros jacksonii) have three hornlike structures on their heads (also found in a couple of related species). From what I know, these are true horns, which means that they are pointed keratin-covered protrusions that have a core of living bone, see e.g. this website from Toronto Zoo (this page also claims that their horns show annual growth rings). However, there are many definitions of horns (some only consider the horns in Artiodactyla to be "true" horns), so you need to be specific in what you are asking for. Used casually, the antlers of Cervids or other similar structures, are often considered as horns.

As for birds, the closest thing to a horned bird I can think of are species of the Australian Cassowary (Casuarius). They have a bony crest on the top of their heads, which is covered by keratinous skin. However, the bony crest is supposed to be relatively soft and spongy, and can hardly be counted as a horn is the strict sense of the word.

(Southern cassowary, Casuarius casuarius, from Wikipedia)

As far as alive carnivorous land animals go, there are non. But let's search in the sea:

Narwhal (Monodon monoceros)

 courtesy: http://i.huffpost.com/gen/1625488/images/o-NARWHAL-facebook.jpg
Longhorn cowfish (Lactoria cornuta)

 courtesy: Wikipedia

They are omnivourus and feed mainly on microorganism. There are loads of sites claiming them horned puffer fish.

Extinct

Carnotaurus (Carnotaurus sastrei)

 courtesy: https://img1.wikia.nocookie.net/__cb20141130153854/dinosaurs/images/e/ed/084d14_0ce4968fba228be913b757cc8ba15f88.gif

Horned Flying Bird

Gread hornbill (Buceros bicornis)

 courtesy: http://www.livepterosaur.com/LP_Blog/wp-content/uploads/2011/05/Lip-Kee-Malaysia-Hornbill-5110157612_e1e078296f_z.jpg

What definition of "horn" are you using? The included examples represents different types of structures with different functions, and several of them are not horns in the strict sense of the word. Based on your examples, you also seem to use such a wide definition of "horn" that your own first sentence is factually incorrect.

Great horn bills do have a horn shaped bill, but its not a horn.


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Why proteins are not visible on my membrane after ponceau staining?
I have a problem in western blot that I can't resolve by myself.
When I am use to add 100 microgram of proteins for each sample but after running and transfer its impossible to me to see bands of protein.
What can be the reason of that?
Thank you for your help

What kind of protein are you using: Whole cell extracts or purified samples? What are your running and transfer conditions? Have you tried to stain the gel with coomassie blue to make sure you have sample on the gel? How do you measure your proteins? What are the buffers in which you measure?

so I need to quantify globin which is protein of 16 kda. I extracted my proteins from MEL cells after treatment by using buffer lysis and protein inhibitors. I do the running at 80volt in running buffer ( tris,glycine) and then I do a wet transfer for an hour with transfer buffer ( tris, glycine, methanol).  I didn't think to stain the gel but it's actually a good idea that will proof if my problem in the running or transfer step... To measure my protein I am doing Bradford method when my Lysats are in 200 micro liter buffer lysis .

Did this blot ever work before? What is in your lysis buffer, by some chance SDS or something like DTT?

I was first using a tris-triton buffer lysis then I use a buffer lysis that contain tris, triton, NaCl,EDTA and . I try to to use in an other blot and same result: I can see proteins band in the upper side only...

What do you mean by seeing proteins only in the upper side?

I see bands after ponceau staining only on the top of the membrane

What percentage has your gel?

It's a 15% gel .

Did you boil or denature your samples before loading them?

Yes i boiled my samples for 5 minutes after adding sample buffer

From what you say, I can only give a few advices:

For the quantification, make sure your sample does not contain any substances which disturb the assay. The Bradford assay is for example sensitive against SDS or DTT. See here for more details. This prevents you from loading a sample without enough protein.
Make sure that you really have protein on your gel. Run a gel as normal and then stain it with Coomassie Blue (it cannot be used for western afterwards).
Don't loose your sample - this happens easier than most people think.
Make sure your transfer works. This can either be done by using pre-stained ladders (which are helpful anyway) or by doing Ponceau Red staining. This can be washed off with water and doesn't disturb downstream applications.
Depending on the type of membrane you are using, they might need pre-treatment. PVDF membranes are extremely hydrophobic and need to be activated in methanol.

Thank you I will check for the buffer lysis . How can I be sure that I will not just loose  the proteins?

Hi Chris, i have joined to the question a picture of my membrane after ponceau if you can take a look.

I will have a closer look later. Can you tell me the size of the marker (bottom 4 or 5 bands are enough).

It's a 10-250kd marker of 10 band

I don't see any bands here, but only a smear. I would first suspect degradation of your sample. It would be really important to simply run a gel and stain it to see how this looks like and to find out the problematic step here. It's probably already the gel...

I also thought that the problem was in the samples but don't know where is my problem... To prepare my sample I first wash my cells with pbs .After removing the superior liquid I am adding buffer lysis and then do a freezing/ de freezing of my samples in liquid nitrogen and then centrifugation at 14,000rpm for 20 mn....

Do you use protease inhibitors in your lysis buffer? If not, this might be the reason the sample is degraded. As I wrote, I would run a gel, stain it, and see how it looks like.

Yes I am adding pmvf and a cocktail of protease inhibitors ...

Thank you very Much Chris I plan to stain the gel with coomasie blue today !

After I had check so many possibilities I finally resolve the problem. It turns out that ph of the tris 1,5M for gel preparation was too many basic...which explain a smear of the proteins into the gel


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Change solvent of bacterial solution
I have to perform an RNA extraction that should start with 900 uL of 2%SDS bacterial solution. The problem is that the sample is in 900 uL of PBS.
I thought about centrifugation of the sample at 5ºC, remove PBS and then add the 2%SDS.
DO you think bacterial RNA quantities will vary?
Thanks!

PBS is isotonic to most cells, so in this buffer your bacterial cells are intact. Centrifuging them to remove PBS won't harm them it is quite standard procedure. You have to be careful after adding 2% SDS because it will lyse your cells and then the RNA contained within them will become "free" and RNAs are fragile molecules.

I'm assuming that you have a solution of bacteria in your buffer directly after growing them for some time, and without performing a lysis step yet. The 2% SDS step looks like it is for lysis of your cells.
In that case, centrifuging the bacteria and resuspending them in lysis buffer is a very common step in many protocols. Separating whole bacteria from medium or buffer by centrifugation is pretty easy and should just work. But if at any of your previous steps you already lysed your bacteria, this won't work because the cells aren't intact anymore.


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How to quantify the Abundance of a particular gene in Bacteria and Archaea?
For 16s rDNA metagenomic analysis, do I need to do the following steps?

DNA extraction-> Purification-> PCR amplification-> Clone -> Pick every single
  colony-> PCR amplify -> Sequence -> Phylogenetic Analysis

For the abundance of a particular gene abundance, what steps do I need to follow? Is it necessary to clone?
`

16S rDNA? You mean 16S ribosomal RNA, right? If yes then no you don't need to do a library in bacterial clones anymore. With next generation sequencing technologies the library is made In-Vitro followed by PCR-like step (e.g. Illumina Nextera XT kit). What you would do is RNA extraction -> Reverse-transcription -> PCR amplification -> library building using a kit -> Sequencing -> Phylogenetic analysis.


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Incremental denaturation of protein mixtures
When a protein solution is heated above the denaturation temperature, it seems that denaturation does not happen at the time the temperature is reached, but it takes some time.
I assumed that Brownian motion degrades the protein structure more and more. But I noticed that, in practice, one has a mixture of proteins, and I wonder whether they may behave differently, causing some macroscopic effect?
As an example, taking the clear part of a chicken egg:
No doubt it contains multiple proteins. When heating it slightly above the denaturation point, it coagulates slowly.
I would like to understand in which way that is caused:

by proteins that denature at some temperature dependent rate - where all proteins behave very similar
by different proteins denaturing at different temperatures at a much higher rate than others, so that partial coagulation means some proteins are coagulated, and some are not
of course, it could be both combined, or a completely different way.

Related: How does protein denaturation work?


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Behavioral change in dolphins during different hemispheres activity periods?
It is known that dolphins never sleep in the sense that we do, instead they have one hemisphere of the brain sleeping while the other one is awake. I wonder, do they show observable changes in behavior in regard to this, depending on which hemisphere is active? Do their hemispheres even have a specification similar to ours (logic and emotion)?

Sleeping is a biological stage which we presume as a relaxation period but its really a highly functional stage for brain. Most of the memory related processing such as management of working memory and cognitive functions such as decision making, reasoning, and episodic memory are closely related with sleep.
Dolphins never sleep in the sense that we do, CORRECT, because we close our both eyes and enter into a stage of decreased ability to react to a stimuli. But in the case of dolphins they need to breath, so by fully entering into a sleep stage like us is suicidal in their case.
Dolphins have a specialised way of dealing with this problem, they do a "unihemispheric slow-wave sleep". They only sleep with one hemisphere of the brain while the other being active, when the right hemisphere is sleeping the left eye is closed and vice-verse, as the right hemisphere controls the left part of the body. The observable change in their behavior is visible from the closed single eye.
Humans and dolphins had a common ancestor that lived 95 million years ago. During the last 50 million years dolphins have been evolving in water and their brain evolution had taken a different route. The neocortex, the outer most layer of brain which is considered as the recent evolved part of brain. The neocortex is actively developing in both humans and dolphins, one of the most striking features among them is that human neocortex is having large thickness and dolphins are having thin one with more folds than ours. The folding in neocortex is a technique to increase its surface area. This substantial difference is due to the evolutionary divergent way both the species took.
Dolphins have a complex echolocation system and binocular eyes, they need to create the visual and sonar image of their surroundings and studies shown that their increased brain size is due to the tremendous volume of data they need to process for these purposes. Also being a social animal their neocortex consists of connections like us but as we both are evolutionary separated for about 95 million years ago most of the brain areas are diversified and evolved.

Dolphins showed that they can understand a symbolic, human-based
  language, where the words are either whistles or hand gestures. And
  the dolphins could easily understand that we use different word orders
  to mean different things. So they understand syntax. The dolphin brain
  is arranged in a completely different way from ours, and yet they can
  still understand what we are trying to teach them. Lou Herman also
  showed that dolphins are right up there with humans and chimpanzees in
  being able to understand that when we point at something or look at
  something, we’re meaning “Don’t look at me; look at what I’m looking
  at.” He’s done all kinds of really fascinating things, and his work
  has contributed the most to our understanding of what these animals
  can do.Reference

"The observable change in their behavior is visible from the closed single eye." Here you have stated that an answer to the question is possible. But other than that sentence, your response does not even attempt answer the question.

@Qubei: yes, I wish there was a more descriptive answer, like does their behavior become more logic or emotional, with examples, if possible.. but strangely looks like there are no people who can say anything like that about the subject..

@noncom:  What do you mean by "does their behavior become more logic or emotional"


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Any good website/book to understand protein folding and enzymes?
I'm looking for a good, understandable and simple explanation about protein folding, mechanisms and function, and their relationship with enzymes.
I understand that the protein is a polypeptidic chain, I know its composition, but the part that I really can't figure out is "the folding of proteins", I mean "How a straight polypeptid chain turns into a complex folded structure?"

Could you please specify what is you are looking for exactly?

As I wrote down, I'm searching for a good resource that explains how proteins fold (Mechanism), and causes of proteins folding.

Have you tried googling or wikipedia? There are many levels of explanation and they require different levels of knowledge. If you want to start from the very beginning try searching for university textbooks or as I said try wikipedia. If you're a biology student then you can go for articles maybe.

I'm a beginner. I've checked many websites and books and I always find high level explanations that I can't figure out yet.

I see. Well then, what are the things that you can't figure out? I not trying to screw with you, but protein folding and enzymes in general are large topics, it takes books to explain everything, so if you can share what you already understand and what you cannot understand then we can help you more by explaining the things you need.

I understand that the protein is a polypeptidic chain, I know its composition, but the part that I really can't figure out is "the folding of proteins", I mean "How a straight polypeptid chain turns into a complex folded structure?". That's my question for instance.

https://www.youtube.com/watch?v=O5gN-IK6uKs
Khanacademy has a lot of resources for just about anything

Okay, so for introduction the 4 levels of protein structure (each level influences the levels after it):

primary (1st): the order of amino acids.
secondary (2nd): alpha-helicies and beta-sheets
tertiary (3rd): complex 3d structure
quaternary (4th) : 3rd+ non-protein elements (ions, co-factors etc)
and / or multple subunits interact. Not every protein has this kind
of structure.

I think the first does not need any explanation.
The secondary structure is where amino acids form 2D structures: alpha-helices or beta sheets. From wikipedia on a-helix and b-sheet

The alpha helix (α-helix) is a common secondary structure of proteins and is a righthand-coiled or spiral conformation (helix) in which every backbone N-H group donates a hydrogen bond to the backbone C=O group of the amino acid four residues earlier (i+4 \rightarrow i hydrogen bonding)
The β sheet (also β-pleated sheet) is the second form of regular secondary structure in proteins. It is less common than the alpha helix. Beta sheets consist of beta strands connected laterally by at least two or three backbone hydrogen bonds, forming a generally twisted, pleated sheet.

Pictures are from here, that is a great site that explains basic protein strucutre in a quite understandable way.

These secondary structures are important because they can from motifs with specific functions like DNA binding, interaction surface with other proteins. The aforementioned wiki sites have detailed info. These secondary structures and motifs serve as building block for higher order functions. Between motifs "loose" non-structured parts can be found to allow for flexibility.
Tertiary structure:
This is the level where complex 3D geometric structure is defined. The aforementioned 2D structures are packed into domains - a single functional element of a protein. A single protein can have multiple domains and the relative position of these domains result in the tertiary structure. The domains themselves are connected with loose regions that do not show any high order structure and provide flexibility between the domains. Flexibility is necessary for conformational changes.
The quaternary structure is where non protein elements and / or multple subunits are involved. For example the positioning of the heme group in hemoglobin. Or when monomers from dimers, trimers etc. so in general when mature proteins get together to form a larger complex.
Here is a great image about the different structure levels:

source: https://dopeahmeanbio.files.wordpress.com/2013/03/333.gif
So now onto the "how" part :)
As I mentioned in the beginning all levels influence the levels after it. So the amino acid sequence predestines the 2D structures to be formed. The secondary structures themselves are formed by amino acid forming hydrogen bonds with each other. This process occurs "naturrally", so by the inherent properties of the amino acids. At the third level disulfide bonds stabilize the structure. This is also a naturally occuring event. Also binding ions, co-factors, etc also stabilizes the protein strucutre.
The folding process can also be supported by chaperon proteins, These proteins can actively "twist" the polypetide chain using ATP as energy source. They can "sense" if there are hidrophobic amino acid chains facing the outer surface of the protein, a thing usually avoided because these amino acids need to face inner surface of the protein where they can avoid water - this is energetically better. This signal (outward facing hidofobic AAs) indicate that either the protein is un/misfolded or it is damaged because of for example heat - that denatures ("unwinds") proteins.
Finally the wiki page on protein folding if you need more. I hope this helps.

This is not a book / website recommendation but I hope it helps :)

Finally, an awesome explanation. Thanks dude :)

All the information can be found here:
http://www.ncbi.nlm.nih.gov/books/NBK21054/
The whole book is there, you simply have to search whichever part interests you or you can also find the paper version in a library. The part on protein structure is Chapter 3.
It's a textbook used in some biochemistry and cell biology introductory courses at my university, so it will cover the basics as well as some more detailed things.

For basic knowledge I would recommend the 5th edition of "the cell" and "Lehninger Principles of Biochemistry" 6th edition (3rd and 4th chapter). Even Lippincott's Biochemistry (chapter 2) and Biochemistry by Stryer (6th edition, chapter 2) is good. You can find the 5th edition of Stryer here http://www.ncbi.nlm.nih.gov/books/NBK21154/
If you have access to a library you could try out the latest editions. If not older editions are available online. Protein folding should be among the first few chapters.

IMO, this is by far the best introduction to enzyme mechanisms and protein folding, by a leading researcher in the field.
Structure and Mechanism in Protein Science: A Guide to Enzyme Catalysis and Protein Folding
by Alan Fersht


text:
Will a store bought cabbage kill my Pieris brassicaes?
About 4 days ago I found a large amount of caterpillars (Pieris brassicae) in my radishes, I took them aside for seeing how they grow and I am out of radishes to give them. I bought a cabbage in the supermarket to give them as food but I am concerned it could be GMO anti pests which to my understanding could kill the caterpillars.
I took one of them aside and it is happily eating the cabbage, if this cabbage is designed to resist pests how long would it take for the caterpillar to die since she started eating?
Thank you so much for the info :)

I wasn't aware GMO cabbage was available at grocery stores. A quick search for GMO cabbage gave some hits for a scorpion venom gene being added to cabbage, but I couldn't find anything suggesting it was being sold for food yet. Do you have more information?

Can you please provide some more information on the GMO cabbage?

I am not sure the cabbage has gmo, but I naturally think it might have because usually chains like LIDER (Chilean Walmart) where I bought the cabbage works with massive producers. any ways… the caterpillars are still eating and are not dead yet hehe :)


text:
Expected time for a neutral allele to reach a frequency of $p_1$ when starting at frequency $p_0$
Kimura and Ohta (1968) showed that the expected time for a neutral allele to reach fixation (given that it will reach fixation) is
$$\bar t(p_0)=-4N\left(\frac{1-p_0}{p_0}\right)\ln(1-p_0),$$
where $p_0$ is the initial frequency and $N$ is the population size.
From their work, can we generalize this result to calculate the expected time to reach a frequency of $p_1$ (given that this frequency will be reached at some point), where $p_1$ is not necessarily equal to $1$?

In the above paper, a key quantity is u(p,t), the prob. that an allele fixes at time t given starting freq. p. They cite a previous paper showing that u(p,t) satisfies a certain PDE. In your case, you want to modify u(p,t) to be a sort of first-passage-time probability (i.e. the prob. that the allele freq. reaches p1 for the 1st time at time t given initial freq. p). In this case, u(p,t) may no longer satisfy the same PDE as before (check that other paper). In order to proceed, you need to find the PDE that your new u(p,t) satisfies. Look up first passage time problems, it may help.

Plain English Answer:
I have written a computer function which simulates neutral evolution to solve this problem. It's not an exact mathematical answer, but it is basically the same approach as Kimura and Ohta took in (the second half of) their paper, except that my computer is more powerful than their one, so I could get far more precise estimates by simulating more populations than they did.
Figure One is a lattice plot of the relationship between P0 and the expected time to reach P1, for different values of P1 (by column) and different population sizes (by row). It is clear that the same relationships between P0, P1 and expected time to get from P0 to P1 are seen in every population size, but with larger populations, you should expect a longer time to get from P0 to P1.
When P0 and P1 are close together, you generally expect a smaller time to get from P0 to P1 than when P0 and P1 are far apart. You might think of this as a rule like 'it takes a longer time to travel further'. Expected time taken to get from P0 to P1 is smaller when P0 and P1 are on the same side of 0.5 as each other and P1 is further from 0.5 than P0 is, than when P0 is further from 0.5 than P1 is. You might think of this as a rule like 'it is quicker to travel when you're closer to fixation or extinction, than when you're in the middle frequencies'.

Figure One: Expected time for a neutral allele to go from frequency P0 to frequency P1, given differences in P0, sub-plotted by P1 and population size. Modelled frequencies of P0 and P1 are 0.1, 0.3, 0.5, 0.7, and 0.9. Modelled population sizes are N = 10, N = 50, and N = 100. Each sub-plot represents one combination of P1 and population size, with P1 increasing from left to right, and population size increasing from bottom to top. All expectations are estimated from 10,000 simulated populations.
Some populations take longer than others to go from P0 to P1. Generally, most populations take a small number of generations to reach P1, and a smaller number take a long time – but a very few can take a very very long time.
I've attached my code, so if you know how to use R you can use it to estimate the expected time to get from P0 to P1 for any combination of P0, P1, and population size.
Additional details and assumptions for the technically inclined:
Relevant theory:
In a diploid, sexually-reproducing population of size $N$, there are $2N$ copies of a given locus. Each locus is occupied by some allele. All variation at our locus of interest is selectively neutral. For our purposes, we can consider that each locus is occupied either by our allele of interest ($A$), or another variant ($a$), ignoring variation in the 'other' alleles. The number of copies of $A$ in the population at the start of the process, $A | t=0$, is given by  $2N*P0$.
Let us assume that population size is constant ($Nt+1 = Nt$ for all $t$), and that mating is random. Let us further assume that generations are distinct. Let $t = 1$ be the first generation born, and so on.
The expected number of copies of $A$ at time $t+1$ then follows a binomial distribution:
$At+1$ is distributed $Binom(2N, At/(2N))$
Since we have a transition rule for $At → At+1$, it is a fairly simple matter to simulate populations undergoing this form of evolution. I have written the R function neutralFPT to carry out this simulation and estimate the proportion of all populations which reach $P1$ at some point in their history, the expected time for a neutral allele to reach $P1$ from $P0$, given that it will reach $P1$, and the distribution of lengths of time taken to reach $P1$, given that a population will reach $P1$. The script is given in the final section of this answer.
Probability densities of first-passage times:
Probability densities of first-passage times over plausible values of $P0$, $P1$, and $N$ follow a similar structure – unimodal near the left margin, with a long right-tail of longer first-passage times (Figure 2).

Figure 2: probabiltiy-densities of first-passage times from P0 to P1 under different values of P0, P1, and N. A: P0 = 0.5, P1 = 0.9, N = 50; B: P0 = 0.9, P1 = 0.5, N = 50; C: P0 = 0.5, P1 = 0.9, N = 500.
Function: neutralFPT, with examples of use.
 ## this function simulates the number of generations taken for a
 # neutral allele to go from a starting proportion, P0, to a final
 # proportion, P1, in a random population, given that it will at some
 # point reach P1. Allele frequencies are not modelled after the point
 # when P1 is reached.
## neutralFPT was generated in response to Stack Exchange user Remi.b, at
 # http://biology.stackexchange.com/questions/30812/expected-time-for-a-neutral-allele-to-reach-a-frequency-of-p-1-when-starting-a
## neutralFPT was written by Shane Baylis, 2015
 # for R version 3.2.2

neutralFPT <- function(P0, P1, N, niter) {

tOut <- c(rep(NaN, niter))
 # create a vector of blank t-values
statOut <- c(rep(NaN, niter))
 # create a vector of population status values (reached P1, or didn't)

if(P0 == P1) stop("P0 and P1 are set to the same value!")
if(P0 == 0 | P0 == 1) stop("P0 is set to zero or one, so its frequency
                           cannot change!")
if(P0 < 0 | P0 > 1) stop("P0 must be between zero and one")
if(P1 < 0 | P1 > 1) stop("P1 must be between zero and one")
## work out whether you're heading upwards or downwards
if(P1 > P0) { # i.e., our target is above us
    for (i in 1:niter) {
        NAllele <- round(2*(P0*N))
        Target <- round(2*(P1*N))
        t <- 0
        while (NAllele < Target && NAllele != 0 && NAllele != 2*N) {
            t <- t+1
            NAllele <- rbinom(1, 2*N, (NAllele/(2*N)))
        }
        if(NAllele >= Target) {
            statOut[i] <- 1 ## 1 indicates that P1 occurred
            tOut[i] <- t
        }else{
            statOut[i] <- 0
            tOut[i] <- Inf
        }
    }
}else{ ## i.e., our target is below us
    for (i in 1:niter) {
       NAllele <- round(2*(P0*N))
       Target <- round(2*(P1*N))
       t <- 0
       while (NAllele > Target && NAllele != 0 && NAllele != 2*N) {
           t <- t+1
           NAllele <- rbinom(1, 2*N, (NAllele/(2*N)))
       }
       if(NAllele <= Target) {
           statOut[i] <- 1 ## 1 indicates that P1 occurred
           tOut[i] <- t
       }else{
           statOut[i] <- 0
           tOut[i] <- Inf
       }
   }
}
successes <- sum(statOut) # the number of populations in which
                          # P1 was reached
propSuccesses <- successes / niter # the proportion of populations
                                   # in which P1 was reached
successTimes <- subset(tOut, statOut == 1)
expectedFPT <- mean(successTimes)
medianFPT <- median(successTimes)
outs <- list(successes=successes, propSuccesses=propSuccesses,
             successTimes=successTimes,expectedFPT=expectedFPT,
             medianFPT=medianFPT, trials=niter)
return(outs)
} # function close

## neutralFPT examples #################################################

sim <- neutralFPT(0.5, 0.9, 500, 10000)
sim$expectedFPT # Numeric. shows the expected (i.e., mean) first-passage
                # time from P0 to P1, in generations, given that a
                # population reached P1.
sim$medianFPT # Integer. Shows the median first-passage time from P0 to P1,
              # in generations, given that a population reached P1.
sim$propSuccesses # Integer. The proportion of simulated populations which
                  # reached P1. Other populations reached fixation
                  # or extinction of A without reaching P1.
sim$successTimes # Vector. The number of generations taken to reach P1,
                 # for all populations which reached P1.
hist(sim$successTimes, xlab="First passage time (generations)",
     main=paste(sim$successes, "successes from", sim$trials,
         "populations"))  ## histogram of first-passage times

PZero <- c(rep(c(0.1, 0.3, 0.5, 0.7, 0.9), 15))
POne <- c(rep(c(rep(0.1,5),rep(0.3,5),rep(0.5,5),rep(0.7,5),rep(0.9,5)),3))
PopSize <- c(rep(10,25),rep(50,25),rep(100,25))
FPTs <- c(rep(NaN, length(starts)))
testFrame <- data.frame(PZero, POne, PopSize, FPTs)
testFrame <- subset(testFrame, starts != ends)
for(s in 1:nrow(testFrame)) {
    sim <- with(testFrame, neutralFPT(PZero[s],POne[s],PopSize[s],10000))
    testFrame$FPTs[s] <- sim$expectedFPT
}  ## estimates expected first passage times from P0 to P1 for a variety
    # of values of P0, P1, and population size. Outputs the estimates to
    # a table called testFrame.

require(lattice)
with(testFrame, dotplot(FPTs~PZero|POne*PopSize,
   main="Expected First-Passage Time by P0, P1, and Population Size",
   xlab="starting frequency (P0)")) ## generates the lattice plot used as
                                     # Figure One.


text:
Proving time travel
Consider this answer to an interesting question. It's not possible to prove completely that someone is the descendant of someone else, there's always a nonzero probability that the results are a coincidence.
How confident can you get that genome T is the descendant of four unrelated grandparents? How would you tell?
Restrictions: You're not allowed to sequence all other humans and rule out other possible parents. Time traveller is has the normal number of chromosomes. You can test people's parents if that would help.
The maternal grandmother would share mitochondrial DNA, and the paternal grandfather would share the Y-chromosome, or the paternal grandparents would have one X chromosome between them. I'm not an expert on SNP accumulation but would there be enough information to conclude this person was from the future? Would there be too much mutation in two generations to pick out the relationships under it?

This should be pretty easy to demonstrate. Over the two generations, there would be 200-300 mutations in the entire genome of 3.3*109 base pairs, i.e. about 1*10-7 of the base pairs should be altered. If Time Traveler is male, for example, imply sequencing the Y chromosome and mitochrondrial DNA and comparing to the paternal grandfather and maternal grandmother should be adequate to decisively validate the claim.
If this isn't sufficiently satisflying could then move on to the autosomes and note that only about 200-300 base pairs max should be different from the union of the four grandparental genomes. The chances of this occurring given random set of four unrelated genomes will be vanishingly small.


text:
Understanding conclusions that functional regions are under negative selection?
I am reading in notes for a comparative annotation lecture that :

all DNA is subject to mutations
most functional regions are under negative selection (ie., mutations are often deleterious)

The conclusion was:

that pieces of DNA with specific functions (especially genes) tend to be conserved against mutation more strongly than a DNA region with no specific function.

So if i understand it properly, since all DNA can accumulate mutations, the regions of genes that provide some fitness benefits avoid the negative selection of random mutations and are preserved (conserved?).
Also, the author placed in parentheses, (especially genes), therefore are there non coding regions that can provide benefits? Is he referring to "Selfish DNA" like Transposable elements that can have regulatory functions (or so i have heard).

Your second to last paragraph is worded wrong. Deleterious mutations are negatively selected against.

Lets assume for simplicity that DNA is globally subjected to the same mutation rate (which is probably not a fully correct assumption).
Now let take a DNA region which is functional (what you meant by giving a fitness benefit), mutations in this region will occur as anywhere else in the genome. Some mutations will be deleterious and reduce the fitness of (or kill) the cell therefore, on the long run, cells that do not carry those deleterious mutations will propagate. This means that now if you look at the genome in the cell that propagated, certain genomic regions will contain less mutations than other because of the negative selection. They were "protected" against deleterious mutation.
Similarly, In multicellular organisms any mutations that reduces the fitness of the germline cells will be negatively selected (again functional regions will be more conserved).
The author was likely referring to regulatory regions. These are regions that do not encode proteins but are very important for gene regulations. Regulatory regions include enhancers, silencers, insulators and locus control regions (Maston GA, 2006). These regions will also be more conserved as deleterious mutations in regulatory elements could reduce the fitness of the cell/germline.


text:
Why does allele linkage cause disproportionate phenotypic ratios?
I was learning about allele linkage in Biology class and I got confused by the resultant phenotypic ratios.
Say you have a dihybrid cross BbGg x BbGg.
The Punnett square would look like the following (sorry for bad formatting):
     BG...... | Bg.... |  bG.... |  bg

BG   BBGG       BBGg      BbGG      BbGg
---  -----------------------------------
Bg   BBGg       BBgg      BbGg      Bbgg
---  -----------------------------------
bG   BbGG       BbGg      bbGG      bbGg
---  -----------------------------------
bg   BbGg       Bbgg      bbGg      bbgg

So:
This would result in a a 9:3:3:1 phenotypic ratio. (Dom/Dom : Dom/Rec : Rec/Dom : Rec/Rec)
However, if the alleles B/b and G/g were on the same chromosome, the ratios turned out to be around 4:1:1:4 in an example (still Dom/Dom : Dom/Rec : Rec/Dom : Rec/Rec)
The stated reason was that there would only be Dom/Dom and Rec/Rec, and the Dom/Rec and Rec/Dom only showed up due to crossing over. However, this begs the question: Why could Dom/Rec and Rec/Dom not have occurred prior to recombination? My reasoning is that just because the alleles are on the same chromosome does not mean that they must both the autosomal chromosomes for the allele must have either a dominant genotype or recesssive phenotype. That is, before crossover, there should still be a 9:3:3:1 random distribution between phenotypes represented by genotype sets (BbGg/BBGg/BbGG/BBGG):(Bbgg/BBgg):(bbGg/bbGG):(bbgg).
Note: when I say dom/rec for example, I mean that for the first allele the character represented by BB or Bb was expressed, and the "rec" means that for the second allele the character represented by gg was expressed. I am assuming autosomal dominance for simplicity.
If anything is unclear, don't hesitate to comment. I'm pretty tapped out right now. Thanks, hob

What do you mean by "if the alleles B/b and G/g were on the same chromosome"? Are you saying that the parental genotype is BG/bg? Chromosomes are inherited as a unit. Without crossing over, if the parental genotype is BG/bg, only either BG or bg can be passed on. This means the offspring could be BG/BG, BG/bg or bg/bg.

No, I mean that allele1 that encodes for B or b and allele2 that encodes for G or g are on the same chromosome. Thanks!

I think you have the wrong terminology. You,re saying that the genes which encode for B or b and G or g are on the same chromosome. This is the situation I described in my first comment. The answer to your question depends on what the parental genotypes are.

Could you be more specific as to what your question is?

I found the explanation at this site helpful:
http://www.ndsu.edu/pubweb/~mcclean/plsc431/linkage/linkage1.htm
I don't have a clear sense of what you mean when you ask about assorted phenotypes occurring before recombination ("crossover"). All of your examples deal with diploid organisms. If they are multicellular then the cells that can undergo meiosis are highly specialized, and eventually become haploid. As the chromosomes are prepared they tend to become compact, and are often not expressed. So it is difficult to assess the phenotype of those haploid cells. The rest of the cells in the organism are diploid  and at least some of them can express the alleles that give rise to the phenotypes that you are scoring.
At the moment of fertilization there is no further recombination, as the zygotic cells undergo mitosis.  There is no segregation, no independent assortment, no linkage (that you can measure--the genes are still arrayed along their chromosomes). Each mother cell divides to give two perfect copies of itself. Then the daughters divide, etc. Even in the cells that are going to become germ cells, they divide by carbon copy mitosis right up until they enter meiosis.
So there is no mechanism that would lead to genotypes different from the genotype of the zygote (until meiosis).

But in the genotype of the zygote, it would be possible for it to be bG, for example, right? Therefore after meiosis, bbGG would occur without crossing over, which means that the thing I was taught about BBGG and bbgg being the only possibilities before crossover would be false, right?

As your Punnett square shows, when a bG sperm fertilizes a bG egg then yes, 100% of the viable zygotes will also be bG.  In the notation you are using, to indicate both alleles of each gene, you would write it as bbGG as you have. IF the B gene and the G gene are not on the same chromosome (unlinked), THEN you could draw it like this: b/b; G/G. In contrast, if the B gene is linked to the G gene on the same chromosome, then you could draw it like this: bG/bG. The bbGG notation you have been using does not distinguish between these two different situations.