text:
Model for fluctuating selection
Is there any mathematical model to predict the behaviour and long-term consequence of counter-acting selection at different time scale?
For example, let's consider the bi-allelic gene A, with alleles A1 and A2. During a long period of n1 generations A1 is slightly beneficial (differential of selection: s1). After this period, follows a short period of n2 generations when A2 is highly beneficial (differential of selection: s2).
What mathematical model describes the frequency fluctuations of alleles and which allele will get fixed at the long term given the initial frequency ( f0 ), assuming infinite population size and random mating.

Unsmooth changes like you describe are normally hard to use in an analytical model. You could build a model of smoothly changing selection using a sine wave or simulations (which would be easy to build).

That remainds me the famous case of Biston betularia

Biston betularia is a moth that lives in England and has a light color in order to mimetize with the bark of trees. However, about 1% of the population presents melanism, and its camouflage fails. During the industrial revolution, the trees became dark as a result of the pollution. When that happened, the proportion of melanistic moths inverted, to almost 99%. During the 20st century, when the industry independized of the coal, the trees got light again, and the proportions restored once again.

This might be a gross oversimplification but could you not use sequential univariate breeders equations, model the response during the s1 phase, this will erode variation in favour of the A1 allele, then you could then apply the univariate equation to the s2 phase. If all variation was lost in the s1 phase then the response in the s2 phase will be 0, and increase dependent on the strength of selection and size of remaining variation.

GriffinEvo's response sounds right. But does the fluctuation continue indefinitely? In that case you might use the idea of step functions from EE to model the process.

Sounds interesting. I welcome you to develop a bit the idea and make an answer out of your comments. I have never heard of the step functions from EE (what does EE stands for?).

I'm going to look at some of your questions over the evenings this week and hope I will be able to answer them - no idea what is meant by EE @daniel

@GriffinEvo: electrical engineering.

The frequency fluctuations will be determined by a standard model of selection as found in any basic population genetics text. In this scenario they take a very basic form: during each long period $i$ the frequency of $A_1$ increases from $f_i$ to $f_i\cdot (1+s_1)^{n_1}$ and during each short period $j$ the frequency of $A_1$ decreases from $f_j$ to $f_j\cdot (1/(1+s_2))^{n_2}.$ Thus over each pair of periods the frequency of $A_1$ changes by $(1+s_1)^{n_1}/(1+s_2)^{n_2}$. If this quantity exceeds 1, $A_1$ goes to fixation; if it is less than one $A_2$ goes to fixation.
More generally, for an infinite population in a fluctuating environment, the allele with the higher geometric mean fitness will go to fixation. Early discussions of these results are due to Dempster (1955; Cold Spring Harbor Symp. Quant. Biol.), Haldane and Jayakar (1963; J. Genetics), and Lewontin and Cohen (1969; PNAS).

Nice answer to a very old question! Thank you. I edited your answer just to clarify that $f_i$ and $f_j$ multiply the thing in parenthesis and are not function of the thing in parenthesis. just in case someone could have a doubt...

If I am not mistaken, this model is a good approximation when the two phases are short enough. If the phases were to be too long then fixation may occur during the first phase and allele frequencies would never be affected by the second phase. This is even more important when $N$ and/or $s$ are high. It might be interesting to have such model for finite population.

Glad this was helpful. In the specific way that you formulated the question, we don't need to worry about fixation because the population is infinite and thus fixation can never occur. But as you note in the real world, or in a finite population model, fixation becomes a major issue. Off the top of my head I don't see how to derive a simple expression for the fixation probabilities of each allele in this case.


text:
Is the fixation rate always equal to the mutation rate for neutral alleles?
Background
A classical result of population genetic is that the rate of fixation of netreual alleles is the mutation rate $\mu$. The reason is that each generation $PN_e\mu$ mutations enter the population, where $P$ is the ploidy number (e.g. 2 for diploids) and $N_e$ is the effective population size. The probability of each neutral mutation to reach fixation is simply its frequency $p$. When the mutation occur $p=\frac{1}{PN_e}$ and therefore the rate of fixation is:
$$\lambda = PN_e\mu \frac{1}{PN_e} = \mu$$
This result s typically very much used in phylogenetic, as assuming a constant mutation rate only, one can estimate the divergence time between two extant lineages.
The above is also explained on wiki>fixation_rate
Question
How robust is the result $\lambda = \mu$?
I understand that the result $\lambda=\mu$ is independent of the effective population size but is it also independent of..

changes in population size?
background selection?
selective sweep?
population structure?
selfing rate?
etc..

It is special case of Wright-Fisher game right ? In that case how it is independent of population size?

What do you mean by Wright-Fisher game? It is independent of $N_e$ (at least for constant population size) as I showed in the background. It is also explained in this wiki article

See Write-Fisher model of genetic drift. And see introduction of these notes.

I know the Wright-Fisher model of genetic drift. We also talk about Wright-Fisher population but I've never heard of Wright-Fisher game.

The answer to your headline question is that no, fixation rate is not always equal to the mutation rate for neutral alleles. For instance:
Fixation rates for neutral alleles are affected by changes in population size, given a constant mutation rate. In general, fixation rates are lower in growing populations (Waxman 2012).
This makes instinctive sense if you consider the single-generation fixation probability of a neutral allele which only exists at all but one copy in the population, i.e., the common allele (A) exists at 2N(t)-1 copies, whereas the less common allele (a) exists at 1 copy. To simplify, let's assume complete random mating. Under negative population growth (say N(t+1) = 0.9N(t)), there will be 0.9*(2N) places that the rare allele could possibly exist at t+1, and it has a 1/(2*N(t)) chance of filling each of them. Under positive population growth (say, N(t+1) = 1.1*N(t)), the rare allele could potentially occupy 1.1*(2N) places at t+1, but still has 1/(2*N(t)) chance of filling each of them. It is clear in this case that A has a reduced generation-wise likelihood of fixation under positive population growth than under negative population growth, simply because the rare allele has an increased chance of doggedly persisting. The finding applies to any allele near fixation.
If I have understood Kim and Stephan (2000) correctly, then overall fixation rates are also reduced by background selection. The main mechanism for this is that background selection purges linked neutral alleles, decreasing overall heterozygosity and thereby reducing the chance that a new, rare allele will become established. The same surely applies to selective sweeps, given linked neutral alleles.

Thank you for your answer +1. I suppose that your answer also suggest that population structure and selfing aren't modifying the result $\lambda=\mu$, right? Is there anything else that you can think about that might affect this result? Thank you!

I didn't mean to imply that population structure and selfing wouldn't modify the λ=μ relationship - I didn't find literature that tested those hypotheses. My instinct is that both structuring and selfing would reduce the fixation rate by reducing population-wide heterozygosity, but I would want to do some more reading (or run some simulations) before I included that in an answer.

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text:
Why do haemophillic females $X^hX^h$ die before birth?
I just came across a statement in my book , while reading genetics, that haemophiliac females do not survive till birth (the reason not mentioned here why) . Before posting this question here I conducted quite a bit searching on the net but couldnt find any document on this. Can anyone tell me the reason why don't haemophiliac foetus make till birth ? I mean where is the problem, when a haemophiliac male having XhY can survive why not an XhXh  female ?

What book are you referring to and can you include a quote?

Dinesh Objective Biology Vol III, ISBN 978-81-7608-229-7 Page no 261 , first paragraph 4th line

I have editedy question and attached the screenshot from the text

Please refer to a standard book on genetics. From CDC website: Females can also have hemophilia, but this is much rarer. In such cases both X chromosomes are affected or one is affected and the other is missing or inactive.  In these females, bleeding symptoms may be similar to males with hemophilia.

This book is also trying to be too modest. Marriage between a carrier female and haemophiliac male it seems. Mating produces children, not marriage :P
@DhrubaBanerjee I am from the same country and I never heard of this book. Always refer to standard books. And now since you have internet you can refer from authentic websites too.

Well, Dinesh Objective Biology is a revolutionary book amongst the community of PMT aspirants. Amyway, I didnt find anywhere in the website you quoted which mentions that "Haemophillic females survive. Its only talking about carrier females. Can you highlight for me please.

@DhrubaBanerjee Entrance exams have destroyed real education. Anyways this is not the right place to discuss such things. You can come to chat if you want. And I quoted the line verbatim from that website. Look carefully

How to join chat here ? I am new to this forum. I am more active in the chemistry forum.

Let us continue this discussion in chat.

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

Correcting misconceptions does not fall within the scope of this site? @WYSIWYG

@CRags Yeah I thought about it. And that's why answered the question.

I also think this question should remain open. It doesn't match any of the close reasons, is narrowly scoped and perfectly answerable. We address incorrect information all the time, that's one of the reasons this site is here.

Haemophiliac females are rare but they can survive just like affected males do. However, the case is slightly more complicated in women because of menstruation.
I could not find an article from any medical journal but this site seems authentic enough for a reference.

Maybe there is some clinical cause which leads to bleeding like breaking if placenta.

authors: عباس حمزة خضير محمد

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text:
How do I find the sequence of the phage BxB1 gene?
Specifically, I'm trying to find the sequence of BxB1 and its att sites.  I have success finding the att site sequences, but I'm having a bit more of an issue with finding the sequence of the actual recombinase.  I've looked through Genebank, but I can't find a definitive sequence of the BxB1 recombinase.
How should I go about looking for this sequence?
EDIT: One more thing I'm concerned about is the validity of the sequences that I do find.  For example, I have seen that Addgene has this pCAG-NLS-HA-Bxb1 sequence.  However, I'm not sure how to verify that this sequence is correct.

The genome has the gene annotated. This plasmid has the gene.

http://phagesdb.org/phages/Bxb1/ here you can click "Locally BLAST this genome" it will give you the sequence in FASTA format and then you can click BLAST if you want additional information about the sequence, alignment, etc


text:
Where’s the flaw in my proposed TB Treatment?
Ten years ago, I emailed a prominent lung specialist with my suggestion for a treatment for Tuberculosis. His lack of response led me to believe that the idea had no merit whatsoever – but I had no idea what the failings might be. I still don’t and I’m hoping someone will enlighten me as to why this is not worth exploring.
The idea is based upon the fact that Mycobacterium Tuberculosis is aerobic – in fact Wikipedia states it “requires high levels of oxygen”. I’d heard that the TB “Sanatoriums” used to practice the treatment of breaking ribs on one side to collapse that lung and “rest” it. It seemed to me that this resting was actually starving the bacterium of Oxygen and killing the infestation.
My suggestion is that we take advantage of having two lungs by inserting a pair of breathing tubes into the respiratory tract and into the head of the two bronchi: it may be necessary to use ultrasound or other imaging to accurately position the tubes.
We feed pure Nitrogen into one tube, and 40/60 Oxygen/Nitrogen into the other – double Oxygen concentration. The patient therefore receives all their Oxygen requirements through one lung. After some period of time, when we judge that the bacteria in the “starved” lung are all dead, we switch the supplies to the 2 tubes and treat the other lung.
Can anyone see why this idea is so flawed?

The proposal is very flawed as pointed out by WYSIWYG, but I generally would like to see more questions like this.

also in tubeculosis, the mycobacteria go into tubecules and can remain in a dormant state for prolonged periods of time.  Its unlikely this will kill those protected and dormant bugs.

Your main flaw is forgetting that HUMAN cells require oxygen. See https://xkcd.com/1217/ for details.

High oxygen concentration can be deleterious; it can induce oxidative
damage.
The systemic blood circulation would supply oxygen to the
"oxygen-deprived" lung.
Moreover, Mycobacteria can survive in anaerobic conditions.

And what if both lungs are infected? There are many flaws in the proposed therapy.
Adding this point from one of the comments below:
There are several cases of extrapulmonary tuberculosis and in these cases treating just the lung would not make sense.

That link is interesting - so possibly they can survive indefinitely without Oxygen - that might explain his attitude. I don't think the oxidative damage side of it appears to be a major factor given that it will only be in one lung for a limited time period...? I deal with treating both lungs in the  text of the question. Yes, the derived lung would be supplied with Oxygen via the circulation - but I assume the bacteria receive their oxygen from the air in the lung - not via the blood supply...?

@Lefty "I assume the bacteria receive their oxygen from the air in the lung - not via the blood supply" : not true. In fact Mycobacteria reside inside the lysosomes of macrophages and there are several examples of extrapulmonary tuberculosis.

just one more question then sorry. Do you think the whole rib-cracking thing was ineffective then - given that "resting" the lung wouldn't have any effect on the colonies present in the lung?

@Lefty I didn't know that such a thing was practised. It seems like an ineffective therapy though.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1079536/ This is the reference I found today but I've read it 2 or 3 times before.

@Lefty You're seriously underestimating how dangerous oxygen is - even at atmospheric concentrations it's very dangerous; twice that means spontaneous combustion for a lot of materials, and of course increased oxidative stress in general - a great way to change your TB into cancer, I'd guess (well, at a very low probability still, but...).

As we know, this is not effective, but if it were, we could simply treat one lung at a time. The general understanding of this principal is important.

The accepted answer is correct but I would like to point out a misunderstanding that has to underly the idea that this would work:
In reality lungs aren't a magical one-way gate for the various gases.  Lungs do not extract oxygen from the air, they permit oxygen exchange between the air and the blood.  Since the air normally has a higher oxygen level than the blood the result is a net transfer of oxygen to the blood--something we see as extracting the oxygen from the air.
However, in an anoxic environment you'll get the reverse--oxygen will move from the blood (admittedly, not too much of it as this is blood that has already passed through the body) into the air.
This is also why too much carbon dioxide is lethal--the lungs likewise have no magic ability to expel it.  It just normally moves from the higher concentration (the blood) to the lower concentration (the air in the lungs.)  Too much and you can't get rid of it, or in extreme cases even get more of it.

Thanks! I see what you mean now. But it was mentioned in @WYSIWYG's answer earlier, so I thought yours would add something.

@Christiaan I'm explaining why WYSIWYG's answer happens.

What a great question! I'm sorry to add another blow to your theory... but... Even if oxygen depletion would be effective, treating the lungs alone is not good enough. True enough, Mycobacterium tuberculosis bacteria usually attack the lungs, but TB bacteria can also attack other parts of the body such as the kidney, spine, and brain (Fig. 1). If not treated properly, TB disease can be fatal. Because the TB bacterium has the potential to infect various parts of the body, a systemic treatment is necessary and long-term antibiotics are therefore the first-line treatment (Source: Center for Disease Control and Prevention).
In fact, there is tuberculosis of the lungs, tuberculous meningitis (infection of the brain membranes), skeletal TB, genitourinary TB and gastrointestinal TB (Source: Medscape).

Fig. 1. Signs and symptoms of TB infection in various parts of the body. Source: Infection Landscapes.

The most evident problem I can see for this TB treatment is that mycobacteria can survive without oxygen. Latent TB (a person is infected but doesn't have active TB) is one of the major problem in the treatment of TB and one-third of the world's population has latent TB! (http://www.who.int/mediacentre/factsheets/fs104/en/). A new TB treatment can only be effective if it targets both active and dormant bacteria.
Of course other aspects need to take into account. Over 95% of TB deaths occur in low- and middle-income countries with reduced access to medications and hospitals. A new treatment needs to have an affordable price, be simple and fast (http://aac.asm.org/content/53/3/849.full). These are other limitations of to the suggested treatment.

Well, the fact is, it would never work, I understand that now, but irritating reality aside, I would have thought it would be massively cheaper than antibiotics and hospitalisation wouldn't it? I can see that imaging would add a lot to the cost but I'm not certain it would be necessary.

@Lefty good heavens, of course not! Even if your theory worked, it also implies extensive hospitalization. More, in fact, than antibiotic treatment. The patients would need to be hospitalized for the full duration of the treatment, the concentrations of the various gases constantly monitored, doctors and nurses hovering for days etc.

@terdon Surely that all depends on exactly how long it would take to kill the bacteria? If they could survive 3 minutes - like humans - then the entire procedure could be over in 10 minutes. Given they can survive indefinitely then yes, I accept that an infinite amount of time in hospital might be quite expensive.


text:
How much genomic variation one usually find within a given bacterial species?
If I find the exact starting position (say 1152471) of the coding sequence of a given gene in the genome of a bacterium, is the genome of the bacterium in general stable enough so that I can expect to find the same position in a different member of the same species?

If you are using the reference sequence from a database, then it is not necessarily the case that you will have a base for base replica for a randomly selected cell. If you were to select two clonal cells from a colony of bacteria, all those cells would have arisen from a single progenitor, so there would be a high degree of homology between the two cells, but they would likely not be exactly the same for every base in the entire genome.

Be careful! As bacterial genomes are circular and we have to write down their nucleotide sequence as linear, the "break point" of the circle does not necessarily have to be in the exact same point for two genomes in the database (as it is kind of based on the assembly where a break would be, unless you manage to end up with a fully circular genome and can decide). Therefor, while the sequence in question might not have changed, the nucleotide in question could still be in a different "position". And otherwise: that depends. Some genomes are more stable than others. Some genes are, too.

There are bacteria with linear chromosome. https://microbewiki.kenyon.edu/index.php/Chromosomes_in_Bacteria:_Are_they_all_single_and_circular%3F#Summary_of_Currently_Known_Bacterial_Chromosome_Organizations

Yes, but are those the species you are working with?

Genetic variation within bacterial species can be much higher than one might expect.
First, this can be a difficult question to answer quantitatively because even just testing whether two strains are part of the same bacterial species is difficult: the "gold standard" method is actually experimental and involves whole-genome DNA-DNA hybridization (with a cutoff of 70% relatedness). Modern sequencing approaches have shown this usually corresponds to around 95% average nucleotide identity (ANI) (see here).
However, an ANI of 95% does not actually mean that the genomes are 95% identical: it means that of the shared sequences, one expects 95% of the nucleotides to be the same. The percent of the sequences that are actually shared in the first place can be much, much lower. For example, this paper compared 61 sequenced strains of E. coli. Out of the ~15K genes observed in at least one genome sequence, only 6% of genes were observed in all strains. Variably-present genes made up around 80% of a typical E. coli genome. This is a high level of variability, but not outrageous: an analysis of only nine P. putida genomes, for example, showed a core of at most 33% (ref).
So, if a gene is indeed indeed present in two strains of the same bacterial species, then it is likely to be highly conserved. But there is also little guarantee of finding the exact same set of genes in two strains of the same species. This means you cannot naively take chromosomal coordinates from one strain and apply it to another: you need to actually figure out which sequences correspond to one another in your genomes.

If all your samples are, say, E,coli K12 MG1655, there will be very little difference between the published sequence and what you have.  If you have another strain of E.coli, you can't count on there being no indels at all between the two strains.

The locations of a gene on a bacterial chromosome is determined arbitrarily, so you would not expect coding sequences to necessarily have the same numerical values. Remember that the bacteria's transcription machinery will use promoters in the genetic sequence to determine where to start transcription, so the actual start location doesn't really matter -- it's pretty easy for random mutations to add or delete a few base pairs between several genes!
Instead, you would search for the genetic sequence of the gene you were interested in on the genome of a closely related species. Since many genomes are annotated by identifying genes from closely related species, it is possible that two closely related genomes start at exactly the same place, but you should definitely not assume that this will always be the case.

not true...genes in bacteria experience some degree of positional conservation


text:
All UniprotIDs of a cancer pathway
I need to download all uniprotIDs of a cancer pathway, say the AKT Signaling. It may be super easy, but I don't know which resource to look at since it is a new field.

How/where do I find these?

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I would do this through the Reactome database. Searching for "AKT Signalling" returns, among other things, an entry for PI3K/AKT Signaling in Cancer (Homo sapiens) (REACT_147723). Clicking on that link will take you to the pathway's page, and if you click on "Disease" (under "Locations in the PathwayBrowser"), you will be shown a link to the pathway browser page of that particular pathway.
Once there, click on the "Molecules" tab, select "Proteins" and you will get a list of the proteins involved in the pathway and their UniProt accessions. There, you can click on the "Download" link and retrieve this list:
MoleculeType    Identifier  MoleculeName
Proteins    P31751  UniProt:P31751 AKT2
Proteins    P31749  UniProt:P31749 AKT1
Proteins    Q9Y243  UniProt:Q9Y243 AKT3
Proteins    P16220  UniProt:P16220 CREB1
Proteins    Q12778  UniProt:Q12778 FOXO1
Proteins    P98177  UniProt:P98177-2 FOXO4
Proteins    O43524  UniProt:O43524 FOXO3
Proteins    P98177  UniProt:P98177-1 FOXO4
Proteins    O15530  UniProt:O15530 PDPK1
Proteins    Q92934  UniProt:Q92934 BAD
Proteins    P46527  UniProt:P46527 CDKN1B
Proteins    P38936  UniProt:P38936 CDKN1A
Proteins    Q00987  UniProt:Q00987 MDM2
Proteins    P60484  UniProt:P60484 PTEN
Proteins    Q8WWG1  UniProt:Q8WWG1 NRG4
Proteins    P10721  UniProt:P10721 KIT
Proteins    Q9HCT0  UniProt:Q9HCT0 FGF22
Proteins    P15498  UniProt:P15498 VAV1
Proteins    P05230  UniProt:P05230 FGF1
Proteins    Q15303  UniProt:Q15303-1 ERBB4
Proteins    P08620  UniProt:P08620 FGF4
Proteins    P42338  UniProt:P42338 PIK3CB
Proteins    O14944  UniProt:O14944 EREG
Proteins    O15520  UniProt:O15520 FGF10
Proteins    P21802  UniProt:P21802-3 FGFR2
Proteins    Q13480  UniProt:Q13480 GAB1
Proteins    P55075  UniProt:P55075-1 FGF8
Proteins    O00459  UniProt:O00459 PIK3R2
Proteins    Q9UEF7  UniProt:Q9UEF7-1 KL
Proteins    P09619  UniProt:P09619 PDGFRB
Proteins    Q8WU20  UniProt:Q8WU20 FRS2
Proteins    Q86Z14  UniProt:Q86Z14 KLB
Proteins    O00329  UniProt:O00329 PIK3CD
Proteins    P11487  UniProt:P11487 FGF3
Proteins    Q9GZV9  UniProt:Q9GZV9 FGF23
Proteins    P42336  UniProt:P42336 PIK3CA
Proteins    P42081  UniProt:P42081 CD86
Proteins    P35568  UniProt:P35568 IRS1
Proteins    P04626  UniProt:P04626 ERBB2
Proteins    Q02297  UniProt:Q02297 NRG1
Proteins    P12034  UniProt:P12034-1 FGF5
Proteins    P56975  UniProt:P56975 NRG3
Proteins    Q9NP95  UniProt:Q9NP95 FGF20
Proteins    Q02297  UniProt:Q02297-10 NRG1
Proteins    P22607  UniProt:P22607-2 FGFR3
Proteins    P21802  UniProt:P21802-1 FGFR2
Proteins    Q15303  UniProt:Q15303-2 ERBB4
Proteins    P62993  UniProt:P62993-1 GRB2
Proteins    O60258  UniProt:O60258-1 FGF17
Proteins    P11362  UniProt:P11362-1 FGFR1
Proteins    P15391  UniProt:P15391 CD19
Proteins    Q9Y4H2  UniProt:Q9Y4H2 IRS2
Proteins    Q99075  UniProt:Q99075 HBEGF
Proteins    P21583  UniProt:P21583-1 KITLG
Proteins    P31371  UniProt:P31371 FGF9
Proteins    P27986  UniProt:P27986 PIK3R1
Proteins    P22455  UniProt:P22455 FGFR4
Proteins    P04085  UniProt:P04085-2 PDGFA
Proteins    P06241  UniProt:P06241 FYN
Proteins    P01127  UniProt:P01127 PDGFB
Proteins    P21802  UniProt:P21802-5 FGFR2
Proteins    Q06124  UniProt:Q06124 PTPN11
Proteins    P21781  UniProt:P21781 FGF7
Proteins    O95750  UniProt:O95750 FGF19
Proteins    P21860  UniProt:P21860-1 ERBB3
Proteins    O14511  UniProt:O14511 NRG2
Proteins    P01133  UniProt:P01133 EGF
Proteins    O76093  UniProt:O76093 FGF18
Proteins    P21802  UniProt:P21802-18 FGFR2
Proteins    O43320  UniProt:O43320 FGF16
Proteins    P04085  UniProt:P04085-1 PDGFA
Proteins    P10767  UniProt:P10767 FGF6
Proteins    P06239  UniProt:P06239 LCK
Proteins    Q92569  UniProt:Q92569 PIK3R3
Proteins    Q6PIZ9  UniProt:Q6PIZ9 TRAT1
Proteins    Q9UEF7  UniProt:Q9UEF7-2 KL
Proteins    P35070  UniProt:P35070 BTC
Proteins    P16234  UniProt:P16234 PDGFRA
Proteins    P33681  UniProt:P33681 CD80
Proteins    P22607  UniProt:P22607-1 FGFR3
Proteins    P09038  UniProt:P09038 FGF2
Proteins    P10747  UniProt:P10747 CD28
Proteins    P00533  UniProt:P00533 EGFR
Proteins    P55211  UniProt:P55211 CASP9
Proteins    P22736  UniProt:P22736 NR4A1
Proteins    Q6ZVD8  UniProt:Q6ZVD8 PHLPP2
Proteins    O60346  UniProt:O60346 PHLPP1
Proteins    Q9UKV8  UniProt:Q9UKV8 AGO2
Proteins    Q9HCE1  UniProt:Q9HCE1 MOV10
Proteins    Q9UPQ9  UniProt:Q9UPQ9 TNRC6B
Proteins    Q9HCJ0  UniProt:Q9HCJ0 TNRC6C
Proteins    Q9UL18  UniProt:Q9UL18 AGO1
Proteins    Q8NDV7  UniProt:Q8NDV7 TNRC6A
Proteins    Q9H9G7  UniProt:Q9H9G7 AGO3
Proteins    Q9HCK5  UniProt:Q9HCK5 AGO4
Proteins    Q96RU7  UniProt:Q96RU7 TRIB3
Proteins    Q5T1C6  UniProt:Q5T1C6 THEM4
Proteins    Q96B36  UniProt:Q96B36 AKT1S1
Proteins    P49841  UniProt:P49841 GSK3B
Proteins    P49840  UniProt:P49840 GSK3A
Proteins    O15111  UniProt:O15111 CHUK
Proteins    Q9BPZ7  UniProt:Q9BPZ7 MAPKAP1
Proteins    Q6R327  UniProt:Q6R327 RICTOR
Proteins    Q9BVC4  UniProt:Q9BVC4 MLST8
Proteins    P42345  UniProt:P42345 MTOR
Proteins    Q9UBS0  UniProt:Q9UBS0 RPS6KB2
Proteins    P49815  UniProt:P49815 TSC2

Thanks, that's great! Next thing would be to download the full network -> who interacts with whom. That would be great!

Ok, it's the SBML format. Found it.

The European Bioinformatics Institute (EBI) has a tool called "Quick GO", which allows you to search the Gene Ontology (GO) database using specific pathways or terms.
In the "Annotation Download" section (http://www.ebi.ac.uk/QuickGO/GAnnotation) enter your search term (e.g. "AKT signalling") and "search". QuickGO will present you with the search results, which for this search include;

protein kinase B signaling
regulation of protein kinase B signaling
positive regulation of protein kinase B signaling
negative regulation of protein kinase B signaling
...

Select a pathway by clicking the GO ID (e.g. "GO:0043491" for "protein kinase B signaling"). This takes you to the information pages for this pathway.
To download the UniProt information (amongst other things) navigate to the "Protein Annotation" table using the tabs. In the top right you are presented with a "Download" option for the whole table (for this pathway containing 1,337 proteins)!
Hope that helps.

This will not give you the proteins in the pathway, you say yourself there are more than a thousand results! What you are seeing are the many, many proteins that are somehow involved in that biological process, including the various regulatory proteins. This is not the pathway itself which only has a bit over 200 proteins. Remember that GO terms are inherited so if a protein is annotated to a child term of GO:0043491 (e.g.  GO:0051896, regulation of protein kinase B signaling) it will also be annotated to GO:0043491.

@terdon good point about child terms being included as well in GO terms - I have voted up your answer as it seems more appropriate in this context!


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Treatment validation on mouse models
I am struggling to set up a project proposal for validation of a known treatment for metastatic colorectal cancer in mouse models.
I want to see how SNPs in patients contribute to their drug resistance and/or toxicity. For the validation of these SNPs as predictive biomarkers, I will use cell lines and mouse models. But, how am I supposed to "induce" these specific SNPs in the mice? CRISPR/Cas9 can be used for the alteration of bigger parts.
Any idea is a useful idea!


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How did birds survive the KT impact?
As I understand it, the ejecta resulting from the K-T impact (also known as the end-Cretaceous or Cretaceous-Tertiary extinction event) re-entered the atmosphere all over the world; the heat from friction with the atmosphere raised the air temperature to a few hundred degrees C. All organisms all around the World were incinerated, except those that could bury underground or move into water.Now birds don't bury underground, nor do they   bury their eggs. So, how come birds didn't go extinct?
To clarify, I'm not considering the longer term cooling effect (which was in turn followed by a longer term warming effect due the CO2 dumped in the atmosphere). What happened just after the impact was that a sizable fraction of the entire volume involved on the collision would be on ballistic trajectories. Most of these would fall back to Earth, while a small fraction would escape Earth's gravity. Now, these ejecta actually contain a significant fraction of the total energy of the impact and almost all of that in then dissipated as heat when they re-enter the atmosphere. This leads to shock heating of the atmosphere to at least a few hundred degrees celcius, but much higher temperatures are also possible, see also this article.

what is the KT impact? a meteorite?

Are you sure about this: "raised the air temperature to a few hundred degrees C"? I'm not too into paleontology, but I admit I never heard that before. Could you please add a link to support that?

Unfortunately the premise underpinning this question is false. The Cretaceous–Paleogene extinction event did not raise temperatures (other than shortly and locally at the impact site) but rather lowered temperatures and light levels through additional particulate matter in the air. Birds survived due to being small (like mammals of the time) and thus requiring less food. Birds could also travel to where food was, as applicable.

+1 @LateralFractal I heard from non-scientific resource too, that the survival was dependent on the weight.

@inf3rno A faster reproduction rate would have also allowed bird species to adapt faster. Whilst non-avian dinosaurs as egg layers offloaded some of their reproductive burden, each large dinosaur still had to grow (slowly) to maturation for their next generation of reproduction.

My answer to a related question about aquatic dinosaurs may help, I at least point to a Radio Lab episode where they discuss the KT impact with geologists. Basically, anything that was on the surface of the Earth got cooked, but anything under a few inches of soil would be ok. This favored small mammals, birds, and reptiles that nested underground. While modern birds don't typically bury eggs, ancient birds may have, to hide them from predators.

@LateralFractal I think you're confusing short and long term effects on temperature. While the dust kicked up by the impact would have blocked sunlight and cooled the Earth, that took much longer than the initial firestorm immediately after the impact. Further complicating the issue would be the fires themselves, which would have released smoke that blocked additional sunlight, but also released CO2, which would have caused a longer term greenhouse effect.

@user137 I'm afraid you are going to need to provide a source for the claim that an asteroid impact globally roasted the fauna.

I've added a source in the question.

@CountIblis I can't find the originating peer-review journal article for the claim described on livescience.com. My initial scepticism is driven by 1) Air isn't a good conducter of heat and 2) Oxygen rich wild fires would have been common on that basis anyway.

@LateralFractal While Radio Lab is not a peer reviewed scientific article, they do name all the geologists they interviewed. A quick search on their names gives more information about Kirk Johnson, Peter Schultz, Jay Melosh, and Douglas Robertson who made the claim about temperatures.

Looking at some of the abstracts to the newer journal articles on the subject, there may be some question as the impact in the Gulf of Mexico may predate the KT boundary by a few hundred thousand years. Though if you base the extinction on the asteroid strike, then as described on the NASA JPL http://www2.jpl.nasa.gov/sl9/back3.html The heat and fires would have been local, and the cooling global. The asteroid could have caused immense tidal waves.

The premise 'birds do not bury themselves underground, nor do they bury their eggs' is also false. Burrow-nesting is not uncommon among modern birds, and incubating burrow-nesting birds will often spend extended periods (multiple days, sometimes weeks) attending the nest. Example: https://en.wikipedia.org/wiki/Wedge-tailed_shearwater

Detailed answer given in this article

This article hypothesizes that the surviving avians had large and quite complex brains, giving them an advantage in finding food in the aftermath.

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Why does our body regulate metabolic processes using the thyroid hormone?
People with hypothyroidism do fine when taking medication containing their daily dose of thyroid hormone. This means that the signaling function of the thyroid hormones is, in principle, unnecessary. If a constant signal would do, then there is no need for that signal in the first place, as you could just by default switch on whatever process is now switched on by the thyroid hormone. So, what's the whole point of regulating metabolism via the thyroid hormone, especially considering that it predisposes us to thyroid disease?

Because it evolved that way, and there was not a significant evolutionary pressure to change it?  And possibly not a mechanism to allow the change, once humans' distant ancestor had evolved a proto-thyroid.

@Count I disagree slightly with "...the signaling function of the thyroid hormones is, in principle, unnecessary..." Thyroid hormone (T4 - aka "Thyroxine") has a half-life of 4-5 DAYS. It is essentially a constant level in the circulating plasma that is important - this is why patients with hypothyroidism that take exogenous T4 do fine. It doesn't have anything to do with T4 not being important biologically. If you take exogenous thyroid hormone away from someone with hypothyroidism or who has had their thyroid removed surgically, once their plasma T4/T3 is gone they do horribly.

The answer is in special situations, where a trade-off has to be done between thermogenesis and energy saving. This applies to hibernation of animals as well as to critical illness in humans.
This kind of adaptation is referred to as TACITUS syndrome (thyroid allostasis in critical illness, tumours, uraemia and starvation), NTIS (non-thyroidal illness syndrome) or ESS (euthyroid sick syndrome). In this situation, total and free T3 are downregulated, and, in special cases, TSH and T4, too. See an open review article by Wajner and Maja, which is available from http://dx.doi.org/10.3389/fendo.2012.00008 , for details.


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Do human lungs have more protection against smoke compared to other animals?
Our ancestors have used fire for more than a million years. Wood smoke is not good for the lungs, but our ancestors were depended on fire. Especially in colder regions of the World like in Europe, where people would have been sheltering in closed spaces like caves or tents, the exposure to smoke would have been significant. I've been in Arctic regions and been inside tents used by indigenous people. They use woodstoves inside tents, and while there is a chimney, the concentration of smoke inside is huge. After a while your eyes start to burn.
So, the question is whether after tens of thousands of generations living in such conditions our lungs have evolved to neutralize the damage done by wood smoke to some degree?

Although I am not aware of any scientific evidence regarding the emergence of more smoke-resistent lungs in humans compared to the past, this can by no means be imputed to the "evolution of lungs". This is not how natural selection works. Rather, hypothetically speaking, nature may have selected humans with particular genetic traits that made their lungs more resistant to smoke, and therefore gave them a survival advantage compared to humans that lacked such trait.

I attended a lecture about an adaptation on the aryl-hydrocarbon-receptor gene that's present in all humans but not present in any other extant primates. This receptor senses dioxin (among other things) and triggers a response from the immune system, so they definitely hypothesized a link to our relationship with fire, especially indoor cooking fires. Wish I remembered more about what the actual phenotype of the adaptation was.

That would be nice, but just reflect on the damage smoking does. Chronic bronchitis, chronic obstructive pulmonary disease, different cancers. How in heaven’s name would we know the answer to this question since other animals are not similarly dragging on cigarettes?? (That’s one thing you can research; animals were in fact forced to smoke. We’re they more or less likely to be injured by smoking?)

@anongoodnurse good point, but you have to compare the average human lifespan for most of our existence with the average ages when smoking-related morbidity and mortality become a significant issue. Most of our predecessors likely died from other causes long before the effects of smoke inhalation became a health issue for them.

@MattDMo - I agree that most ancient humans died of “other causes” before smoke inhalation became an issue. The OP would have a different idea. However, smoke is more of an issue in the younger populations than you might think. In kids, it’s related to ear infections, asthma and other problems. If we have developed better lungs, I’d hate to see how earlier humans fared.

I don't know the answer. It may be human lungs are anatomically different than other species' or diverged evolutionarily to be substantially different or more resilient to particulate entry or deposition. They may also be different physiologically, say with respect to clearance mechanisms of particulates that are captured and removed. Soluble particulates are largely cleared by pinocytosis and insoluble ones by mucociliary movement ("ciliary escalator") and this may very well be different between older and modern humans. I think it would be difficult to demonstrate this definitively though.

From a population lineage point of view, I can understand the hypothesis that multigenerational, repeated, endless exposure to smoke may have affected the gene pool by removing the one extreme end of human variation selectively, one that had hypersensitive lungs or issues with clearance of particulates from the lungs. We think the same for those who couldn't run away quickly enough, or spot or hear danger, or store fat reserves for the winter, so why not for smoke tolerance? Of course, whether it happened to a degree enough to have contributed to changing the gene pool is an open question.

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Is there a certain environment where all cellular functions (or at least some) increase their rate?
Is there a certain environment in which all the functions (or some) inside a cell increase in their rate? Would the increased rate cause any damage to the cell?

Increased temperature would be one "environment"

When you reach optimal temperature for certain enzymes, their activity will boost and this can e.g. cause extreme "usage" of nutrient and such (or whatever the function of those enzymes are) and cause rapped growth. Certain stimuli e.g. lactose (and no glucose present) can turn on different cell pathways and thus cause high activity for proteins in that pathway. What do you mean by "burn out" (cell dies?)?

@CuriousTree Yes, cell dies, or functions improperly.

@CuriousTree The lactose part is interesting, care to elaborate on more similar stimuli ? (preferably as an answer )

I changed speed to rate, which is what you mean I believe - also... What do you mean by "burn out"? That's not a scientific term.

@VanceLAlbaugh I mean any malfunction in the cell's internal functionality, any damages that are caused by the increase of rate.

I edited to try to circumscribe the "burn out".

There are optimal temperature, pressure and substrate concentration for each biochemical process. The optimal temperature and pressure for two or more (but not all) processes may overlap. So there is no SINGLE temperature or pressur where ALL of them will be at their maximum. Please note, by mentioning "cellular processes"  I meant all the biochemical(e.g glycolysis), physiological (cellular micro-transport) as well as physiochemical(transcription) processes. But we can try to provide substrates at reasonably high concentration ( keeping in mind negative feedback phenomena); we may reach the maximum achievable rate. All the above conditions follow bell-shaped curve; so I put the word 'resonably', as after the optimum condition is reached further increasing that condition will lead to decline in "speed" of reaction. We have to create an artificial enviornment using that substrate combination at proper concentration; as there is no such natural condition where that happens(cell always decrease one process while increasing another).
But it may seem to be a paradox - does anabolic and catabolic reactions both will increase simultaneously! E.g glycogenesis and glycogenolysis at the same time......well, as I already said this is not a natural condition; we are forcing substrates of one reaction at "reasonable" concentration keeping in mind the 'opposite' (is it??) reaction. E.g glucose produces glycogen by glycogenesis and that new glycogen is used in glycogenolysis; so we have to consider the concentration of glucose only. Isn't that easy! well, not so soon. Doing this requires lot of ATP, of course we'll get some from the glucose breakdown, but the need is even higher. So we have to provide additional ATP. Then there are second messengers (cAMP, DAG, IP3 to name a few of them). We have to nutralize them all( they favours unidirectional process).....this is a very complicated thing(just for example, we are supplying ATP, so cAMP will be automatically produced; so we should select all the enzyme blockers of cAMP production). But then electrolyte concentration will be disturbed and we need to monitor & regulate that also.
Thus it is clear that such condition requires sofisticated laborarory instruments.
N. B.
1. I considered only a single cell while discussing this.
2. The word "exhausted" was taken as progressive deterioration of cellular architecture, that leads to death.


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Is there a karyotype database for human cell lines?
I'm looking for the karyotype of a specific cell line. Some karyotypes are well known, such as HeLa or some carcinomas, but some are very hard to find, such as LG2 (B cells). Is there a database dedicated to karyotypes of human cell lines?

I can't find the LG2 cell line that you mentioned but often times you can find karyotype information on ATCC or COSMIC (for cancer cells)

Have you checked the following link? It is focused on epithelial cells though. http://old-www.path.cam.ac.uk/~pawefish/

As far as I know and have found, there is no one master database for karyotypes of all human cell lines. They are usually grouped into subsets either by some commonality (e.g. being cancers) or simply because of who/where they were developed and how they chose to share the line. Some good databases/resources are:

ATCC - A great repository that has cell line datasheets, references, images, and culturing info. I highly recommend using ATCC as your first stop when looking to learn more about a line.
NIGMS Human Genetic Cell Repository - A very robust repository that contains far more than just cell lines. It's good, but the wealth of info can be a bit difficult to sift through.
COSMIC - A great collection of info on cell lines and mutations found within them. Good if you want to look for/understand particular genetic aspects of a line.
Cellosaurus - A fantastic database on cell lines! I particularly like the info Cellosaurus hosts on different names and common misspellings of names for cell lines. It also provides info on hierarchies of cell lines- that is, when multiple cell lines are derived from a parent line. This is super helpful when trying to parse literature with confusing references to similar lines. It also provides references and cross-references. I cannot recommend this one enough.

To get back to your particular cell line, I have only been able to find one reference to a line called 'LG2'- even with the help of the resources listed above and PubMed, so I, unfortunately, can't give you much info on that specifically. If there really is so little info on this line, I would suggest contacting the source (colleague, lab, excel sheet associated with your storage system, etc.) for your cells to see what info they have. If you can't find anything that way, it may be best to just submit a sample for sequencing yourself and get that info out there.


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How many abdominal sclerites would be there in a cockroach?
Every tegmina of a cockroach has sclerites which are analogous to the bones of humans.
Every abdominal segment of cockroach consists of two lateral sclerite plates called pleura along with a dorsal terga and a ventral sterna. But what will be the case with the last body segment where 10th sternum is absent?
I mean will, there be any pleuron in the tenth segment because, following our textbook, pleura serve for articulation among sterna and terga and also spiracles are present in the first eight abdominal segments but the 10th sternum is absent in Periplaneta americana.
Actually there is no evidence of the presence of any pleurons in the last segment in our text book.
Moreover, there are no abdominal spiracles in the 9th and 10th segments so there is no particular reason to say that pleura are present in the 9th and 10th segments as well.

Tergal plates:
There are ten tergal plates. The $8^{th}$ tergum in the male and both $8^{th}$ and $9^{th}$ terga in the female are not visible  as they are overlapped by the $7^{th}$ tergum.
The $10^{th}$ tergum extends beyond the posterior end of the body and has a deep groove in the middle of its free end.

Sternal plates:
Only nine sterna are present as the $10^{th}$ sternum is absent.
In the male, nine sterna are visible whereas in the female, only seven sterna are visible.
In females, the $7^{th}$, $8^{th}$ and $9^{th}$ sterna together forma brood pouch. The brood pouch has two parts: the anterior – genital chamber or gynatrium  and the posterior – gothecal chamber.
[![][1]][1]
(source: lander.edu)
[![][2]][2]
(source: lander.edu)
[![][3]][3]
(source: biologydiscussion.com)
![][4]
Sources:

http://www.slideshare.net/prof_aarif/animal-types-cockroach
https://learnzoology.wordpress.com/category/periplaneta-americana/page/15/
http://zoologybaburao.in/pdfs/7.%20Unit%20VII.pdf (Best)
http://www.eskool.com/files/subject/ppt/103_11_07_04_01.pdf
http://www.sakshieducation.com/(S(clpea355rwddux55iuci1cer))/Inter(New)/Material/IstYearEM/Zoology/07_01_ARTHROPODA_COCKROACH_UPTO_LOCOMOTION.pdf

Update:
Youtube links for Cockroach dissection:

https://youtube.com/watch?v=ZwvG69ICnps
https://youtube.com/watch?v=wF7ew2w24as
[1]: https://i.sstatic.net/RvH9a.gif
[2]: https://i.sstatic.net/uJLDh.gif
[3]: https://i.sstatic.net/lyOQK.jpg
[4]: https://bugguide.net/images/cache/LKP/K0K/LKPK0K2KGKA01QT0PQB0GQC0EQZSVQRSXKHSWQZSGKDK4KUK4K1KLK10KKUKHKBKAQAKMKLSMK307K6K4QD0BQLSEQ.jpg

my question was about the presence or absence or lateral pleurites in the 8th and 9th body segments of a cockroach and your answers does'nt says anything about those and more over the cockroach species which i am studying about is periplaneta americana

i am asking about the pleurites not about tergites and sternites. i too know about the sternal plates and tergal plates in abdomen but the description of pleurites or pleura is not so elaborate in our textbook

No, The $10^{th}$ tergum extends beyond the posterior end of the body and has a deep groove in the middle of its free end.. because of this they lack the pleura as the upper structure directly comes down. You can check if you cut a cockroach.

you seem to be right in this context but the ting is that we do not have dissection of a cockroach in our syllabus this year while it was included untill the last 32 years

what would be the case of 9th abdominal segment??

Check out these youtube links: 1.) https://www.youtube.com/watch?v=ZwvG69ICnps 2.)
https://www.youtube.com/watch?v=wF7ew2w24as


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Why is it cool near the trees?
I can understand that trees produce oxygen in daylight but why is the area with vegetation much cooler than the environment's temperature?

Is there evidence that this a general phenomenon?

Why it can feel chilly close to trees in the evening:

Water coming out of Stomata vaporises, reducing the surrounding temperature.
There is normally no direct sunlight reaching the ground beneath the tree, hence the moisture content of soil is higher, giving it the "chilly feeling"
If there is other vegetation (e.g. grass) growing beneath the tree, then point the first point is repeated for the other vegetation, consequently the combination of point 1 and 2 decreases the temperature noticeably.

An empirical study that estimates the cooling effect of trees from evapotranspiration can be found in Konarska et al (2016). Transpiration of urban trees and its cooling effect in a high latitude city.. In the study, they specifically find a cooling effect at evenings, but less so during nights and at daytime:

With an estimated night-time latent heat flux of 24 W m(-2), tree transpiration significantly increased the cooling rate around and shortly after sunset, but not later in the night. Despite a strong midday latent heat flux of 206 W m(-2), a cooling effect of tree transpiration was not observed during the day.

Why is it more noticeable during the summer?
If the temperature is warm, the atmosphere has a greater capacity to hold water in its vaporous state than if it was cold.
Relative humidity
The ratio between the actual amount of water vapor present to the capacity that the air has at a particular moment. For any given temperature, the air has a particular capacity for water vapor. If that capacity is exceeded, the excess spills out as liquid water.

When you meant "the excess spills out as liquid water", I guess you are meaning there will be a state change when water molecules get cohesive.

I added a reference to your answer that felt suitable. Hope that's ok.


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Why Crocodiles don't eat Hippos?
I have been following documentaries about crocodiles and amazingly, crocodiles and hippos apparently seem to live happily in the same pond together without attacking each other.
Why is it so? Like no matter how strong hippo is, its soft skin is no match to the brutal jaws of a crocodile?

Can a crocodile's jaws actually bite into something the size of a hippo?

Skin
First, you are being misled by your wrong assumption that hippos have soft skin. Hippos have a 5 cm thick skin! For fun, here is a picture of a hippo skin.

They are big and pretty fast
An adult hippo weighs on average 1.5 and 1.3 tons for males and females respectively (with a record at 4.5 tons) and can run up to 30 km/h on land and up to 8 km/h in water (according to wikipedia > hippopotamus).

They have an aggressive nature
Hippos are aggressive animals (esp. males). Hippos kill about 500 people a year (against 1000 for crocodiles) according to this BBC article (but estimates seem to vary quite a bit from source to source).

They have serious teeth
Hippos have a big mouth with very long teeth. Lower canines are 50cm (19.7 inches) long (see wikipedia citing Estes 1991)!

Hippos live in herd
As suggested by @ChinmayKanchi in the comments, because hippos live in a herd, a crocodile that attacks a hippopotamus might have to deal with more than one enemy.
Videos
You can find here a video fight between a crocodile and a hippopotamus (thanks to @TahlaIrfan) and here is a video of a lion waking up a hippo. You will easily find other videos on YouTube.

@Remi.b Can you please cite the reference about the speed and weight? Thanks.

My reference is simply wikipedia (wiki does not give further reference).

@Remi.B First video link no longer works -- could you find an alternative source? 2nd video link is great :).

They don't look like prey animals. This is one of the most impressive skulls to stand beside of any living animal:

The skin weighs about 270 kilos for an adult hippo of 1.5 tons, ranging from 12 to 35mm thick.

on page 3 https://physoc.onlinelibrary.wiley.com/doi/pdf/10.1113/expphysiol.1964.sp001695

Hyenas are really badass. I saw a video last week when they killed even a hippo.

The skin look more than 35 mm thick in your last picture...

I know, I was puzzled by that so I checked an anatomy document which states 12-35 cm epidermis so presumably it's fat, on the hyperlink.

As Remi.b explained above, the average hippo is just too big and dangerous for the average croc to handle. That said, there were cases that very large crocodiles (such as the infamous Gustave) attacked and ate juvenile hippos (or very old or sick hippos). But usually the two practice a mutual "respect and awe" relationship with tense tolerance to each other, which may turn into a brutal fight if one of the sides gets too close to the other.

Could you add references to backup your answer?

For Gustave: https://en.wikipedia.org/wiki/Gustave_(crocodile), see also Google


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Are the genes for transcriptional factors close to their targets in the genome?
Transcriptional factors (activators and repressors) are proteins which regulate transcription. Being proteins, they themselves are also made from expression of certain DNA sequences/genes.
For example, the lac operon repressor is coded for by the lacI gene. Now, in the case of the lac operon, the gene for the transcriptional factor is next to the promoter sequence. It is, in fact, a part of the lac operon. Similarly, the trpR gene is a part of the trp operon.
Is this always the case? Is the gene coding for the transcriptional factor always present next to (or close to) the transcription unit?
The two mentioned operons are only in prokaryotes. Could it be that this fact is valid for prokaryotes only, and not eukaryotes' DNA?

Is the gene coding for the transcriptional factor always present next
  to (or close to) the transcription unit?

Not necessarily. You can find several counter-examples. Even for prokaryotes this is not necessarily true. The genes regulated by a common factor are called regulons and though the target genes need not be proximal to the regulator, it has been observed for E. coli and B. subtilis that operons within a regulon are clustered in the genome (Zhang et al, 2012). In the same study, the authors note that small regulons have the regulator proximal to them (See the figure below).


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Why are plants referred to by their Latin species names, and not by their popular names?
Often the names of herbal ingredients in certain cosmetics products are given by their scientific names like Anthemis nobilis instead of chamomile or Lavandula angustifolia instead of lavender.
Is there any reason why this practice is followed? Wouldn't those who have allergies to certain plant materials be better off reading "coriander leaf extract" instead of scratching their heads over what "Coriandrum sativum leaf extract" is? Why put something more complex when something simpler would be more beneficial to the consumer?

Maybe because it sounds fancy. I do know that there are labeling regulations that companies have to abide by for cosmetics via a google search. http://www.fda.gov/Cosmetics/Labeling/Regulations/ucm2005194.htm

The use of a genus-species notation gives more exact information. For example there are multiple species of chamomile: There is Roman chamomile (Chamaemelum nobile), German chamomile (Matricaria recutita, or Chamomilla recutita) and Dyer's chamomile (Anthemis tinctora). The first two species are appraised for their medicinal properties and help to calm upset tummies and to aid sleep, among other things. The latter species, however, does not have these properties and is used for dyeing. This illustrates the fact why 'chamomile' alone is insufficient.
Popularly, classifications of living organisms arise according to need and are often superficial. Anglo-Saxon terms such as 'worm' have been used to refer to any creeping thing including snakes, earthworms and intestinal parasites. The term 'fish' is used in shellfish, crayfish, and starfish. However, there are more anatomical differences between a shellfish and a starfish than there are between a bony fish and man.
In science it has been the convention to use the genus-species notation since Carl Linnaeus introduced it in the 1700's. This formal classification serves as a basis for a relatively uniform and internationally understood nomenclature. A uniform classification system simplifies cross-referencing and retrieval of information. The Linnaean taxonomical system aids in this purpose and is widely used. The genus-species system can be extended by including subspecies and varieties. Many (plant) species don't even have an (English) trivial name. Taking your lavender example: there are some 39 Lavendula species known and obviously, many of them don't have a trivial name. Here one has to fall back to the Latin names to be sure what it is.

If chamomile is sold as an herbal supplement I think it's safe to assume they're not packaging the variety meant for dyeing. It really seems like a marketing ploy to me.

@canadianer I strongly disagree. It's note safe to assume anything; the labels should be clear and unambiguous.

Why assume it will be called chamomile and not Roman chamomile, German chamomile and Dyer's Chamomile? Your first paragraph seems to counter itself by providing unique common names that could be used then saying you must use only the base term for some reason.  I actually think it is--as you later suggest--scientific convention over user interface, scientists don't typically consider usability very important.

@Ajasja There's a big difference between what should be done and what is done.

@BillK - good point - I added a few sentences on lavender that illustrate why relying on trivial names is not always reliable

@canadianer US law requires cosmetic labels adhere to given lists of ingredient names.

The Latin names are known in all countries. The "popular" names are only popular in one or maybe two languages/countries. So, learning the Latin names, enables you to communicate international more easily.

It generally won't be more helpful.  Not only will the names be different in different countries, there may be different types of the same species with different properties, or even different species with the same common name.  If you have an allergy to something like coriander, being able to read the label and see what contains actual coriander and what contains curry leaf is essential.
Lavender is a great example.  Any gardener could tell you that English lavender (angustifolia) is a very different plant from French lavender (dentata), even though they're the same family.  I've no idea what the essential oils will smell like, but I'm pretty sure they won't be identical.  And more importantly, if you're talking allergies then I'm pretty sure they won't have the same chemical composition.
Even worse, consider bergamot.  Bergamot oil should come from the skin of the bergamot orange, but there's also a species of flower (monarda) which is commonly called bergamot because its scent is similar to bergamot orange.  If your contents just said "bergamot", which one? And even worse, there are two types of monarda which are completely different plants.

Ditto on the "multiple species with the same common name". I was really worried the other day when I was reading about the risks of consuming the plant "fireweed", until I realized that my "fireweed" was a completely different plant from the "fireweed" the author was talking about: https://en.wikipedia.org/wiki/Fireweed_(disambiguation)


text:
Are the number of base pairs in a given chromosome same between different individuals?
This is a basic question but I couldn't find an answer through a web search; hopefully this is the right place to ask. Is the number of base pairs in a
particular chromosome the same in all individuals? For example if I take an
X-chromosome from two random humans would I count exactly 155,270,560
base pairs in both cases? or are there mutations that would make one longer than the other? If they're not exactly the same, what's the range in length variation?

Not only is it not the same in two different individuals. It's not the same in one individual (over their lifespan or two different cells at any given point). https://en.wikipedia.org/wiki/Telomere  Also see https://en.wikipedia.org/wiki/Insertion_(genetics) and https://en.wikipedia.org/wiki/Deletion_(genetics).

@Adam make an answer out of that

If anyone would like to use my comment to formulate an answer (or improve on the existing answer please feel free). I don't really have the time right now to put together a well referenced answer I would be happy with.

@ Adam, I will add it.

Welcome to Biology.SE.

if I take an X-chromosome from two random humans would I count exactly 155,270,560 base pairs in both cases

No, you would probably not find the exact same number of base pairs because mutations do no only change one nucleotide to another (what we call a substitution) but sometimes add or delete few (or sometimes many) nucleotides.
note, btw that you don't need to take two different individuals, you can just consider the two X chromosomes of a female (or any other pair of chromsom in any gender) and find this difference in the length of chromosomes.

what's the range in length variation?

Good question (+1)!
Telomere issue
Before I start, I want to make clear that I consider the length of those chromosomes at the moment of conception. Chromosomes will vary in length during the lifetime due to telomere reduction. I will not consider this in the following calculations. Also, some mutations directly introduce (or delete) a large number of nucleotides (transposable elements for example), I am not considering those mutations here, assuming they are rare in comparison to to single insertions and single deletions (this assumption might not hold!). So please really take the following with a grain of salt.
Let's make some messy calculations
In classical theoretical population genetics, we tend to consider mostly substitutions. But I can maybe try to make some extrapolation out of this work if you allow me to make some strong assumptions, use poor estimates of actual true values and using some non-rigorous mathematics! This is going to be ugly and not extremely trustful $\ddot \smile $.
Not explaining why this is true (it is a result coming from Coalescent Theory), the expected number of pairwise differences between two neutral sequences for a diploid population is $E[\pi] = 4\cdot N\cdot \mu$ (quite an impressively simple result), where $N$ is the population size (assuming panmictic population) and $\mu$ is the mutation rate for the whole sequence. Assuming a constant per site mutation rate of $\mu_s = 10^{-9}$. Knowing the length of the sequence of interest (chromosom X) $L ≈ 1.55 \cdot 10^8 $, the mutation rate for the whole sequence is $\mu = L\cdot \mu_s = 0.155$. Let's consider a population size of $N = 5 \cdot 10^7$ (the equations assume a panmictic population so I just took some value that felt more or less reasonable to me much smaller than the actual worldwide population size). Therefore the total number of substitutions should be $E[\pi] = 4 \cdot 5 \cdot 10^7 \cdot 0.155 ≈ 10^7$.
Now, let's assume that only a fraction of $\frac{1}{100}$ of the mutations bring variation in the number of nucleotides, we might want consider the value $\frac{1}{100} \cdot 10^7 = 10^3$. And because a mutation that deletes a nucleotide from a long sequence will rather diminish the number of variant in sequence length that increasing it, let's say that will divide this number by 10!... so I'd say that two typical X chromosome would differ in length by about 100 nucleotides.
I am sure that with some work one can come up with more rigorous calculations and a more accurate expectation. Intuitively, the result of 100 nucleotides doesn't sound totally crazy (it is not 1 nor 10^6 at least).
Also, one could probably use available sequence data to estimate this value.

In some sense yes but it is kinda misleading the way you put it. Mutations can bring variations in the length of chromosomes. Then, within the lifetime of an individual chromosome length varies a lot becuase at every mitosis, chromsomes can shorten (you'll need to read about chromosoomal replicate, telomeres, DNA strands direction, Okasaki fragments to understand why). So one such mechanisms explain variation as a function of the age of the two individual you sample while the other mechanism in independent of age and explain variation in the length of chromosomes that are present in the egg.

Thanks for the explanation. So it seems there are (at least) two different mechanisms that can change the length of a chromosome :  (1) telomere reduction and (2) random base pair deletion (is addition also possible?). From what I read so far the first involves removing parts of a repetitive sequence of bases at the ends of the chromosomes. This seems like a more deterministic process than the second. I think the calculations you made account for the second type. If correct (100 out 155 million) the range is  pretty small.

I calculated the expected difference in length between 2 chromsomes sampled at random from eggs (without considering telomere shrinkage during lifetime, which would force us to consider the distribution of age, the distribution of the number of mitosis given age and the expected telomere shrinkage at each mitosis). The expected total range of length in a given population is necessarily greater that the expected pairwise difference in length....maybe 10 or 100 times as much I'd say intuitively.

Also please, again, don't take those numbers too seriously as the calculations are not really rigorous. I was happy to see that I ended up with a value that felt intuitive to me.

There are also transposable elements that can change loci in a genome. In various microbes, they can take up or remove plasmids. Retroviruses can incorporate their DNA into their hosts.

I understand these are really back of the envelope type calculations; but
still they're useful enough to guide the next level of detail. A next step
for me is to learn how these variations are accounted for when creating,
updating, and processing databases of chromosomes.

It's usually easier for
me to learn something if I have a concrete problem with real data to work
with. If I pick a single short chromosome from a simple organism and I just
want to do some simple statistical analysis on the variations of that chromosomes;
What would be a good introduction material on how to access an openly available
database and do some simple calculations.

You should open a new post for your new question and check an answer if your question in this post has been answered (or just don't check anything if your question hasn't been answered yet). I am not quite sure what exactly is your question but if you haven't yet, you might want to first follow a course of bioinformatics.

"find this difference in the length of chromosomes."  That was never shown before because we only got gapless genome in January 2022. How does crossingover work then? As for telomeres... Just consider stem cells only.

You would never count 155,270,560 bp in X chromosome. 7 years ago gapless (status complete) human genome did not exist, this is from GRCh37.p13. That is info about genome that had fake gaps inserted. But in January 2022 we finally got all genome (Y chromosome too) and perfect number is 154,259,566. All other numbers for other chromosomes are in wikipedia taken from here. https://www.ncbi.nlm.nih.gov/assembly/GCA_009914755.4
P.S. You literally did not know the basic of it. 155,270,560 is a number with inserted fake gaps, you can see it here: https://www.ncbi.nlm.nih.gov/grc/human/data?asm=GRCh37.p13 The number you wanted was on tab Ungapped lengths, at the time it was 151,100,560. So that means at the time of GRCh37.p13 some of it was not known.

Are there mutations that would make one longer than the other? If they're not exactly the same, what's the range in length variation?
As pointed out in the other answers, there can be mutations that change the length of the DNA between individuals and even single cells of the same tissue.
There are different processes that can change the genome length. The most common ones are:

micro-indels (insertion and deletions) or sometimes just simply indels: Small changes (1-50nt) [1]. Usually happen during imperfect DNA repair via Non-Homologous End Joining post a double-strand break.
Copy number variation (CNV): bigger variations that generally happen due to deletions and duplications of DNA segments >50bp.
Transposon expansion
Chromosomal translocations

We can ignore microindels and chromosomal translocations for the moment because the former impart only a small change to the genome size and the latter are usually rare and in most cases, are extremely deleterious.
With a stringent mapping, CNVs are known to cause 4.8% variation in the size of the human genome [2]. It is to be noted that this information does not account for the frequency of the changes; this is just a sort of maximum limit. It can also be noted that deletions have a greater contribution to variation compared to insertions.
LINE-1 retrotransposons are known to be quite active in the human genome. They accounts for ~17% of the human genome and are one of the major sources of inter-individual variation [3]. They are especially noted for promoting somatic heterogeneity in differentiating neurons [4]. Since LINEs expand by copy-pasting, their activity is correlated with increase in genome size. Transposon activity is generally suppressed in germ cells by a class of small non-coding RNAs called piRNAs [5].
I haven't found an article that exactly describes the variance in the genome size due to LINE-1 or other transposable elements. I'll add a reference if I find one.

Interesting numbers. If one mechanism alone (CNVs) can cause 4.8% variation in length and some claim "in terms of DNA sequence all humans are 99.5% similar to any other humans" (https://en.wikipedia.org/wiki/Human_genetic_variation) then either some very loose definitions are being used or these variations have odd statistics –

@secretlyfamous Note that CNVs need not disrupt homology i.e. "similarity" between two genomes. When we talk about similarity we generally refer to sequence homology. And the statistics presented are for the upper-bound of the length of CNV regions. The variation is therefore an upper-bound and not the standard deviation.

thanks for the explanation. It's a little hard for me to accept that (unrestricted) insertion/deletion does not change homology; but I'll save the details for a future question.

@secretlyfamous imagine duplications, it just creates an extra copy of the genomic region which would again be homologous to the reference. There is a chance of homozygous deletions too. Another point to be noted is that when people say that the genome is 99% similar (or even when comparison between different species is made; for e.g. chimpanzee and human genomes are 95%(?) similar) then the non-transcribed (intergenic) regions are not considered.

authors: Валерий Заподовников


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Are fully vaccinated people more likely to not get infected at all with COVID-19?
I've found some papers which describe that the viral shedding does not decrease during infection (for fully vaccinated people). But the overall shedding time does decrease. Therefore it is possible to say, that the vaccines could have a positive effect on the whole pandemic. (They lead to a reduced spread of the disease.)
My question is now: are vaccinated people more likely to not get infected at all?
I've read that the vaccines lead to a shift from severe cases to mild cases, but is there evidence that the vaccines can actually protect people from getting infected?
If someone knows more, could you provide me a source?

You need to define "not get infected at all" more precisely.  Being vaccinated does not stop the virus from entering your body, and may not prevent some of your cells from being infected. However, it (almost always) ensures that enough targeted anti-viral molecules and cells are circulating in your body that they can quickly clear virions and infected cells, resulting in no noticeable illness.

@Armand Wouldn't it be safe to assume he means not get an active infection?

The CDC puts the rate as 5x more likely to be infected if unvaccinated: https://www.cdc.gov/mmwr/volumes/70/wr/mm7037e1.htm

@Armandt, its hard to come up with a definition. But than I would say something like "not beeing able to infect other people, because the virus is not able to increase within the host."

Yes, this is the effect of the vaccine. A reduction of infections of over 88%, a reduction of severe cases and death by 95% and higher. See reference 1 for the details. Data from the ReCoVAM Study from Malaysia (unfortunately only not yet published, so see here) shows a reduction of infection by 88% and a reduction of admission to ICU/death by up to 96%. So yes, the vaccination works pretty well.
Although symptomatic cases have a comparable viral load in the first four days of their infection this decreases very fast after day four. The figure below (from reference 2) shows this nicely.

The curves show the Ct-values of the PCR from infected patients. The Ct value is the cycle at which the PCR machine can detect a signal from the amplification reaction for the first time. Due to the nature of PCR, the Ct value is inversely proportional to the log of the amount of DNA set into the reaction. The lower the Ct value (the fewer cycles to first detection), the higher the amount of target DNA originally in the sample.
Please note that this comparison is done by PCR and does not give any evidence how infectious the virus from vaccinated people really is. There is evidence (unfortunately from an underpowered study, so results should still be taken with care) that the viruses coming from symptomatic vaccinated people are not as infectious as from unvaccinated persons. See reference 3.
References:

Impact and effectiveness of mRNA BNT162b2 vaccine against SARS-CoV-2
infections and COVID-19 cases, hospitalisations, and deaths
following a nationwide vaccination campaign in Israel: an
observational study using national surveillance data
Virological and serological kinetics of SARS-CoV-2 Delta variant
vaccine-breakthrough infections: a multi-center cohort study
Longitudinal analysis of SARS-CoV-2 vaccine breakthrough infections
reveal limited infectious virus shedding and restricted tissue
distribution

Comments are not for extended discussion; this conversation has been moved to chat.


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Turning publicly available genome data into proteins
I'm a computer scientist who is starting to dabble with biology. My eventual goal is to model different kinds of cells with a computer program. As of right now, I'm just trying to take some smaller steps.
First, I downloaded a complete human genome from http://hgdownload.cse.ucsc.edu/downloads.html#human  There is a FASTA file for each chromosome.
Then, I wrote a java program which can convert FASTA DNA sequences into the appropriate amino acid chain.
Next, I made my program look for the "start" code (ATG) and "stop" codes (TAA, TAG, TGA).
So, now I have sequences of amino acids which might theoretically end up folding into proteins. But, before I start diving into protein folding, I wanted to try to verify that the steps I took so far were done correctly. I looked up some important human genes in an online database and found their amino acid sequences. I then searched through my program's data for those sequences and confirmed that they were there. However, the gene was in a different base-pair location than the database said that it should be in.
This led me to some questions, which, so far I have been unable to answer and hopefully people here will be able to help shed some light.

I know there are a lot of different publicly available genomes. Maybe the UCSC one that I downloaded is different from the one used by the gene database. How much does each genome vary from each other genome and in what ways do they vary?
In attempting to answer that first question, I was going to download a bunch of genomes from the 1000genomes website and do some comparisons, but I wasn't sure which files to download. Each of the files begins with either ERR or SRR and I'm not sure what that means. This is the folder I'm currently looking in ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/data/HG00239/sequence_read/
Lets say I'm trying to model a white blood cell. How do I know which parts of the genome get turned into proteins for that type of cell?

Sorry if anything I said doesn't make sense. As I said, my expertise lies in programming, not biology/genetics.

I think that you need to be more specific than "I downloaded a complete human genome". Was this an entire genome sequence, or a set of FASTA sequences corresponding to predicted proteins?

An entire genome sequence. There is a FASTA file for each chromosome.

A comment on your third question: Which genes are expressed depends on the state of the cell, and this is especially complicated for immune cells. These can go through different state of activation which are all different. You can try to find data from gene expression experiments in such cells and use this data. Datasets are available in the "Gene expression omnibus".

You completely ignored Central Dogma of Life.
You haven't considered the RNA.

Devashish, I have a mapping from DNA codon to amino acid. I don't think I need to do anything with the RNA.  For instance, whenever I see the TGC codon, I map that to cysteine

Have you considered introns? Also, not every start/stop codon is transcribed.

As a general note, please don't ask multiple questions on a single post. In future, please split each question into it's own post instead. I have answered all three here since in this particular case, your questions are basically irrelevant since the main problem is a huge underestimation of the complexity of the task you are attempting. Good luck though!

which organism are you studying?

No, your approach will not work, you are taking a very simplistic view of an extremely complex system. Some of the problems you are ignoring are:

Genes (eukaryotic genes anyway) are spliced to produce mRNA, a process that removes introns and leaves only the exons. If you just translate the entire chromosome file you will get noise.

Splicing also changes the frame a gene is read in, you don't mention frames at all in your question but you can't work with sequences unless you deal with them.

Many genes (most even, in some species) are alternatively spliced. One gene can give rise to multiple protein sequences. Which one is produced at any one time can depend on a multitude of factors ranging from pure chance, through environmental conditions to the cell type where the gene is expressed.

Genes can be present on both strands of DNA and a gene on the + strand can overlap with a gene on the - strand. In some cases they can even overlap on the same strand (nested genes). You need to check both strands for coding sequences.

You're assuming that all coding sequences start with ATG (most do, not all) and you seem to be assuming that an ATG always starts a coding sequence. A given gene can have dozens or hundreds of ATG codons, how can you know which one is used as a START codon?

The process of identifying the parts of the genome that get translated into protein is not trivial. It is the subject of countless PhD theses, mine for example. There are many programs (gene predictors) that are designed specifically to detect genes in genomic sequences. Having spent many years working with them I can assure you that they're not something you can just whip up one afternoon. They tend to involve very complex models of coding vs. non-coding sequences and are way more sophisticated than simply looking for START and STOP codons. Trying to write one without knowing a lot more about biology than you seem to is just a waste of time.
Your specific questions are basically irrelevant because of the points mentioned above. Nevertheless, the answers are:

They vary but not much. For well annotated genomes like the human one, the differences will be negligible. That is not why you have strange results though as I explained above.

All public FTP sites tend to have a README file that explains what the files provided are. You should read the relevant README from ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/

Answering that question will get you a Nobel prize. There simply is no way of predicting what genes will be activated in a particular cell. We're not even close to that level of understanding of how a cell works but I can tell you that it will not depend on the sequence, you will never be able to predict whether a gene is active in a particular cell based on its DNA sequence alone. It will depend on various things including the gene's methylation state and is largely an emergent quality of the cell's complexity (think of various proteins interacting with one another, leading to the activation of a gene).  The best you can do is get a list of genes that are known to be active from the literature.

In summary, if you want to do something as complex as modelling a cell I suggest you first take the time and study some basic biology so you can understand the system you are trying to model a bit better. The cell is not only an extremely complex system that we don't fully understand yet, it is also not wholly deterministic and contains a lot of stochasticity that you seem to be ignoring completely.

Thanks for the detailed post. I'm going to use this as a reference going forward and look into the topics you've mentioned.

@nether you're welcome and sorry to piss on your parade and all. I really recommend you find a biologist to collaborate with. You are greatly underestimating the complexity of the task you want to attempt. First of all, it is simply impossible with the knowledge available today. Even if it were possible though, you are looking at several years work from a team of highly qualified experts. You may be a brilliant programmer but that is not enough here. Also, you are reinventing the wheel, there are already many programs that do what you have written (identify genes and translate sequences).

Because there's an xkcd for everything...http://xkcd.com/793/

@terdon I was expecting the piss-on-parade / what-your-doing-is-impossible type post, but I'm happy that yours also contained useful information in addition. People told me things were impossible when I was trying to make software for the financial sector. Now my software is used by banks all over the world. It's not like I sat down in a room and made it by myself -- many experts in the financial world helped make it possible. I plan to do the same thing here which is why I've been reaching out to experts in computational biology and already have some meetings set up :)  Collaboration is key

@nether ah, good, I'm glad to hear that. There is actually a lot of work being done in the subject. What is impossible (today) is to create a full working model of a cell. Impossible not because you're not good enough but because we simply don't understand the cell well enough. That could change in the future, what will never change is that the DNA sequence will never be enough for this. The sequence is only a subset of the information necessary to model a cell. By the way, you might want to look up BioPerl or BioPython if you're going to be working with this type of data.

@terdon BioJava for me ;)    And what about this?  http://www.cell.com/abstract/S0092-8674(12)00776-3

@nether that's exactly what I'm talking about. Note that i) they used M. genitalium, the simplest organism known to man, which is orders of magnitude simpler than a "white blood cell" (there's no such thing by the way, there are dozens of cell types called that) ii) they used a hell of a lot more information than the DNA sequence and iii) despite all this, the model is extremely limited. It can predict certain behaviors but cannot be considered a "true" representation of the living cell. My main point is that expecting to model a cell by using its DNA sequence is impossible.

I'll just explain a bit on why it is impossible. You can predict a protein sequence from a DNA sequence. It is very hard to predict the protein structure from its sequence. More difficult it is to predict what the folded protein will interact with. and so on...

Why bother predicting proteins badly from DNA sequence when you could have just as well downloaded the manually curated human proteome?
As to your questions:

Are you asking about human genomes or genomes in general? The vast majority of the variance in human genomes is in non-coding sequence. As to genomes in general, they vary in pretty much every imaginable way.
I think those files are quality filtered Illumina reads. SRA = Sequence Read Achieve. SRR = SRA RUN accession. ERA = EMBL SRA. ERR = ERA RUN accession.
You should look into transcriptomics data. Predicting such stuff in silico is currently pretty much undoable.

I think the OP meant differences between different assemblies of the same genome. For example, differences in gene coordinates between UCSC and EnsEMBL.


text:
When does DIFFUSION occur and not OSMOSIS, and the otherwise?
For example, I do know that red blood cells have both the Na+/Cl- co-transporter and Aquaporin (water channel) that allows both Na/Cl and water molecules to pass through. But why in biology textbooks they imply that osmosis occurs instead of the diffusion of Na/Cl molecules, though red blood cells have the channels for them, too? (that leads into crenation or lysis of the cells)
NOT ion PUMPS, but ion CHANNELS (those that don't require energy). The Na+/Cl- co-transporter works along with the gradient (not against!).
If an RBC is to put in a hypertonic solution, why wouldn't it absorb the excess NaCl using this channel instead of letting the water out?
I do know in the case when we put cells in a hypertonic/hypotonic glucose solution, osmosis will occur instead because the cells need insulin to allow glucose in (via GLUT4).
But when does exactly osmosis occurs instead of diffusion?

But when does exactly osmosis occurs instead of diffusion?

These processes are not mutually exclusive. Both can happen simultaneously. Their rates depend on different parameters such as permeability of the membrane towards water and the solutes. A semi-permeable membrane has different permeability for different molecules. There are cases when one of these two processes may happen but not the other (again, a function of the parameters):
Osmosis+/Diffusion-
When there are no solute transporters expressed in the membrane of the concerned cell. For e.g. RBCs do not express the Sodium-Chloride symporter. It is expressed in the distal convoluted tubule of the nephron.
Osmosis-/Diffusion+
When the osmolarity of the cytosol is same as that of the ECF and the cell expresses ion channels. The action potential in a neuron would be an example of this phenomenon.

I think you could address more specifically why some cells lyse in hypotonic solutions when they contain substrate channels. I think the answer is that in most cells the various channels are gated, but I have no idea what "RBC" is.


text:
Modelling insecticide net efficacy loss
I am currently doing some work on modelling the effects of treated nets usage on mosquito populations. Nets do not retain their maximum efficacy forever. They lose their chemical efficacy after about three years and all that is left is the physical protection offered by the net which I estimate to be 20% of the original efficacy.
I am trying to model this behaviour. I need continuous function over the interval $[0,1095]$ which decreases slowly  from 1 when $x=0$ and asymptotically approaches 0.2 when $x \rightarrow 1095 $.
I tried an ellipse of the form $y=\sqrt{1-\dfrac{x^2}{(1095)^2}}$, but i realized the function is equal to zero when $x=1095$ which is not what i want.
Any help will be appreciated. Thank you.

This is more suited for math-SE. The term "asymptotically" is used to denote value that will be reached in $x\to \infty$. You can rather ask for a condition in which the system reaches within 99% of the desired value i.e. 0.2 at $x=1095$.

Can you describe the shape you are after more clearly, and what you mean with "continuouos cap shaped function"? Would a simple negative exponential function similar to $y(x) = e^{-bx+c}+0.2$ be insufficient? Do you have data that will be used to fit the parameters of the function?

@WYSIWG, I agree the word asymptotic is not appropriate. What I meant was a concave function which has value 1 at $x=0$, and has a value of 0.2 at $x=1095$, beyond 1095, the function should not have a value below 0.15.

@fileunderwater I meant a concave function. I have no data to fit the parameters. I am hoping to generate a function such that the net loses efficacy gradually to about $65%$ in two years, then the chemical protection ebbs  completely over the last year. The remaining protection level is $20%$ of the original protection.

I'm voting to close this question as off-topic because it is about mathematical functions and does not involve any biological principle. Moreover, many functions can be constructed that can fulfil OP's criteria and hence this question is broad.

As @WYSIWYG suggested, this is probably more suitable for Math-SE.
From you question, it is unclear exactly what shape you are looking for, and there are many functions that could describe the behaviour you're after, i.e. a continuous, smooth decrease towards an asymptote. However, two possible options could be the negative exponential and a negative gompertz function. Possible forms of these could be:
Negative exponential
$y(x)=e^{−ax+ln(1-b)}+b,$
where $b=0.2$ and a is a rate parameter.
Negative Gompertz
$y(x) = 1-\alpha e^{-\beta e^{-\gamma x}},$
where $\alpha=0.8$ (describing the asymptote), $\beta$ in an inflection parameter (given a displacement along the x-axis), and $\gamma$ is a rate parameter.
These functions can give results such as:

In these examples, $a = 0.005$ for the negative exponential and $\beta = 150$, $\gamma = 0.008$ for the gompertz v1 and $\beta = 5$, $\gamma = 0.005$ for the gompertz v2.
An alternative parametrization of the Gompertz, which might be easier to understand, is:
$y(x) = 1-\alpha e^{-e^{-\gamma (x-\beta)}},$
where the inflection point ($\beta$) is directly related to the scale of the x-axis (so $\beta = 400$ would give an inflection at x = 400).
Are these examples interesting for your application? Hopefully they can provide a starting point for you.

I think the OP is looking for a concave-down function with no inflections.

@fileunderwater the gompertz look very interesting, v2 especially. Could you please explain to me how the various parameter affect the concavity of the curve?

@canadianer I thought so as well, but this will be very hard to achieve continuously if the loss during the first two years is only 35% and the rest (down to 20% protection) is lost in the last year

@Ozymandais the parameters $\beta$ and $\gamma$ interact to produce the shape. If you increase $\gamma$ the loss is more rapid (almost a step function if $\gamma$ is very large), and $\beta$ sets the inflection point of the function.

Actually one can make many functions that can fulfil the criteria. Because the OP has just mentioned the initial and final behavior of the function, there can be infinitely many shapes. For example one can use a linear combination of polynomials.

@WYSIWYG I agree, and the idea was to give the OP a bit more to work with.

I think, mechanistically, that loss of activity should be negative exponential (assuming first order degradation kinetics).

@WYSIWYG Spontanously, that was my feeling as well (hence my initial comment). However, the OPs description of a 35% loss over two years followed by a further 45% over the third year doesn't fit with this.

@Ozymandais See the updated answer for an alternative parametrization fo the gompertz.


text:
How can I isolate live Wolbachia endosymbionts from Drosophila
I am interested to culture Wolbachia bacteria in cell line.

Welcome to Bio.SE! Could your add some details on what kinds of approaches you are thinking? Perhaps some more info on characteristics of Wilbachia?

If I had to close then I would vote to close this as homework because a simple google search fetches relevant answers. I am not voting to close, however, because Wolbachia is not such a common topic. -1 for lack of effort

You can see this protocol for Wolbachia isolation:
See this protocol for infecting cell lines with Wolbachia.
In this study the authors have established a cell line from a Wolbachia infected tissue of Aedes albopictus. You can have a look at that too.

Why downvote ??

I downvoted because I thought it to be somewhat of a link-only answer. Removed. If you add some details I am totally happy to upvote, but likely the question needs work before a proper answer is possible.

@ChrisStronks Cannot paste the protocol here. Since the OP is asking only for the protocol, I provided the link (all links are to published articles and are not likely to be broken in future). To add anything more, the question needs to be refined

Agreed, totally. Again, after question refinement I am happy to upvote.