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Relationship between DNA strands and mRNA
Does the sense strand or antisense strand of DNA code for the polypeptide product? I'm confused because I know the antisense strand is the template for mRNA but it has anti codons so I do not know how this would be the coding strand. Ok so what I was confused about is when you are getting the code for the amino acid you can look at the mRNA strand which is the same as the sense strand except uracil replaces thymine, this is why I thought the sense strand could have coded for the amio acid instead of the anti sense strand.(the question I was looking asked if its the antisense or sense strand)

I've tried to clean up your question and its title but, as you say, you are confused, and so is your question. I'll try to answer it.

Antisense/non-coding DNA strand as a template for RNA polymerase => mRNA (being identical to the sense/coding DNA except for T -> U). If the sense/coding DNA strand were the template for RNA polymerase you would get mRNA that is identical to the antisense/non-coding DNA (again, except for T -> U). You would not want that ...

How about: "If the sense/coding DNA strand were the template for RNA polymerase you would get mRNA..." that might be "restriction"-RNA that is able to block corresponding "positive" RNA, as "negative" RNA does exist in human. Actually, positive/negative for sense/anti-sense or coding/template only seem "good terms" if you are into viruses.

I would add this as a comment to your question but do not have enough reputation. A simple look at Wikipedia (which is a very good source for general questions like these) would have provided you with an answer. I just did this to see how long it would take if I did not know the answer. It was about 20-30 seconds.
Protein synthesis: Transcription

In transcription an mRNA chain is generated, with one strand of the DNA double helix in the genome as a template. This strand is called the template strand.

Template strand

Only one of the two DNA strands serve as a template for transcription. The antisense strand of DNA is read by RNA polymerase from the 3' end to the 5' end during transcription (3' → 5').

If I understand your confusion correctly, you also do not understand how the seemingly "non-coding" strand can be the "coding" one which seems to be a paradox. If this describes your confusion adequately you have to think of the semi-conservative replication of DNA. The "non-coding"/antisense strand is transcribed by the RNA polymerase into its complementary RNA sequence. As this sequence is complementary to the "non-coding" DNA strand, the mRNA sequence is identical (with U replacing T) to the "coding"/sense DNA strand.

I don't think your Wiikipedia links are the most useful ones for two reasons. First, the questioner asks about the terms 'sense' and 'antisense', for which there is a specific Wiikipedia page, whereas the ones you reference refer to something called the 'template' strand, which is not the term in the question. Second the diagram of transcription on those pages is quite dreadful: over-complicated with unnecessary and confusing three-dimensionality (which of course bears no relation to reality). Simple diagrams are both more honest and intelligible.

I do not agree. @Maria already said that in her (and that is also the way I see it) view antisense and template are corresponding. I am not a big fan of the sense vs. antisense DNA strand concept and find coding vs. non-coding way more intuitive (good that you mentioned that, though). However, she uses the term 'template' in the question, so I find it more natural to use that term to help her with her confusion (the way I understood it). To your second point: I think she grasped the process of transcription - therefore I did not really care for the diagrams. Point taken, though.

— The poster has modified her question now and I have modified my answer. However I would say that I think ‘template’ is a particularly dangerous term to use in this context. In brief this is because 1. the fact that linguistically templates produce a copy, whereas at best one is producing a reverse complement; 2. DNA strands are actually templates for their complementary strands, rather than mRNA or protein. I will add a longer argument about this to my answer when I have a little time.

Referring to your argument of the bacterial genome I would say that template is the best term to use as both sense/antisense and coding/non-roding, as you say in your answer, are relative terms. The template can be both of those strands depending on the gene. You are right, however, that one needs to make clear that the copy is a reverse complement and not identical. To your second point: I would say that DNA strands are templates for both DNA and RNA. Looking forward to your argument.

"DNA strands are templates for ... DNA" only when DNA is copied to DNA for cell division (DNA polymerase)? - If you rated down the difference between DNA and RNA which  is some "OH"  only you might think of m-RNA and its  coding DNA as "copies", whereas the difference between the two DNA strands in their complementarity would look outrageous.

You ask initially about the “sense” and “antisense” strands of DNA. These terms are explained in the Wikipedia reference entitled ‘Sense strand’. This states what you appear to be already aware of, that:

“The sense strand is the strand of DNA that has the same sequence as the mRNA, which takes the antisense strand as its template during transcription…”

Transcription produces a reverse complement of the DNA strand transcribed, just as the antisense strand of DNA is a reverse complement of the sense strand of the DNA. Thus:
5' ...ATGTTT...TAA... 3' : DNA sense strand

3' ...TACAAA...ATT... 5' : DNA anti-sense strand (template for transcription)

5' ...AUGUUU...UAA... 3' : mRNA (translated)

N     MetPhe...End    C : Protein

Qualifying the use of ‘Sense strand’
There is a danger in using ‘sense strand’ of thinking or implying that it refers to the whole of the DNA — after all, the description of a circular bacterial DNA is that it has two strands. However the genes in a bacterial DNA do not have the same directionality, so one can (and should) only talk about the sense strand of the DNA specifying a particular gene.
Disfavoured alternatives to ‘Sense strand’ 1: Coding strand
In your original question you switched from talking about the sense and antisense strands to talking about coding and non-coding DNA strands, although you later removed this. I would argue against this usage. It is the mRNA that does the coding and is actually translated into protein. The DNA can only be regarded as sense or not in terms of conceptual translation. In practice it either serves as the template for transcription or its complement does. There is also the problem that if you call the opposite strand ‘non-coding’, there is a possible confusion with the use of that term for the untranslated regions of the (coding) mRNA.
Disfavoured alternatives to ‘Sense strand’ 2: Template strand
I dislike the use of ‘Template strand’ because the original and primary use of ‘template’ in relation to DNA is replication (not information content). Further, when used in relation to protein-codoning potential it is not immediately apparent to me (and, I would argue to anyone approaching the topic for the first time) which strand of DNA would be regarded as ‘template’.
In English the term template generally means a pattern, mould or former used as a guide to create objects of a similar shape. Its adoption to the molecular biology of nucleic acids involved a subtle change of meaning, as the article produced from the DNA template (the product strand — DNA initially) was not the same shape as the mould, but a complement to it. However, the complementarity rules of the bases meant that the information in the original was preserved (in a manner somewhat analagous to that of a printing plate), and the metaphor caught on as it conveyed a clear meaning. It should be emphasized that this meaning was in relation to DNA replication and transcription. Thus, generations of biochemistry students read in texts like Berg et al. that:

DNA Polymerases Require a Template and a Primer

(whereas RNA polymerase only required a template). Furthermore they could read (e.g. in Wikipedia) that:

DNA is made up of a double helix of two strands, and each strand of
  the original DNA molecule serves as a template for the production of
  the complementary strand…

So if you start talking about the template strand of DNA you are in trouble already.
But what would that mean in relation to transcription of mRNA? Here it is the anti-sense strand of the DNA specifying the gene that is physically serving as template for the mRNA. However to many it would seem counter-intuitive to call this the template strand, so that those who use the term cannot in fact agree how to do so. To quote S. Malloy:

“…one school argues that the strand copied into mRNA should be
  considered the template strand, but the other school argues that the
  opposite strand which reflects the sequence in the mRNA should be
  considered the template because the corresponding codons are copied
  into protein.”

It clearly makes more sense to use ‘sense’ and ‘anti-sense’.

I've updated my answer in the light of the updated question.

I've now completed my arguments on terminology. A bit OTT, but you don't have to read them to read my answer.

To favour "sense" seems to correspond to Crick's dogma seen as a concept of "genetic code". By code is meant the triplets, thus the protein that may be "sense of life", the end, what  information flows to. Linguistically "coding" has got less connotation to the activity, to what templates do.

Maybe some valid (related) question: Refering to "one can (...) only talk about the sense strand of the DNA specifying a particular gene", does "Okasaki" show that Polymerase always reads from '3 to '5, hence "sense" is '5 to '3, thus talkin of a particular gene  defines the direction: of that particular codon sequence. There is only gene, chromosome is none. And, "gene" has direction 5-3! The term Sense might connotate "direction", codon might connotate the protein. And: promoter/primer rules?!


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How allele is related to trait that is more complex than two cases (ex. height)?
Recently I started to learn about evolution and genetics. Simple stuff at the beginning - some videos, some reading. So far, everything seems to be pretty simple and straightforward. I easily grasp the concept of gene, allele and trait as the basic level. What bothers me is, that all of examples shows allele that has two options, sometimes three - peas yellow or green, blood type IA, IB and i - so on and so on.
But traits usually aren't digital in nature, they are analog. They are gradients. You have no people that are 160cm tall or 180cm tall only - you can have one that is 160 tall and another who's 160.1 and another who's 159.95. Height seems to me as a real number which may provide unlimited results.
Is the Mendelian reasoning about alleles and traits still valid in case of height trait? How does it work in such case?

Welcome to Biology.SE! You are correct in saying that 'traits are not digital in nature' i.e. they present a range instead of yes/no, so the actual biochemical mechanism for their expression is much more complex. I recommend that you keep studying more about genetics because at this stage you might not understand the whole concept properly. Someone here can also recommend some good books for you :)

Thank you. I appreciate any help, good sources included.

You are absolutely correct that many traits are not "digital", but "analog". In genetics, these are usually called quantitative traits. Such traits generally do not follow Mendel's laws of inheritance, but are said to have "complex inheritance". Most traits (phenotypes) in biology at the level of whole organisms probably have complex genetics; height is a classic example.
It is thought that complex traits arise by the combined actions of many genes (via their encoded proteins), while Mendelian inheritance occurs when phenotypes happen to correspond to the activity of a single gene. For very complex traits like height, many functions of the body might be involved, so the number of genes that may have some effect on the trait can be very large, but the effect of any single gene on the trait is likely small. In general, it is not understood exactly how genes contribute to the trait in such complex traits, so a phenomenological/statistical approach is used where the trait is modeled as some simple function of the genotype which is fit to data.  Wikipedia's page on quantitative genetics has more information on this.
In addition, traits may of course be affected by environmental factors as well as genetics. Height for example is strongly affected by having access to good nutrition. See this article for some discussion.
For traits with complex genetics, the underlying genes are generally difficult to identify, and for along time we have known almost nothing about the genetics of traits like height, obesity and diabetes. Since the early 2000's, massive efforts have been put into mapping the genetics of such complex traits by brute force --- measuring the effect of all genes on the trait in a very large number of individuals, in so-called genome-wide association studies. These have revealed a large number of genes over the past decade, but as expected each has only a small effect on the trait.

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Perplexing by the way of estimating the shared or different genes between humans and chimps
We share 98.5% genes with chimps (it means we have 98.5% same DNA sequeces ),so there is about one percent difference .It means we can approximately differ from them by one base pair every hundred base pairs on average.
The following is my question.
A human receive 3 billion base pairs from each of parents ,and has six billions in total .Do the math by using one hundred to divide six billions and then it equals sixty millions.
Due to that, The person have ,on average ,sixty-million-nucleotide differences with a chimp.
However,the professor of the online courses I attended said it's thirty-million-letter differences.
Dose that mean it's counted on haploid?Why?
Also ,I'm not sure that about one percent difference is calculated on one base pair or one nucleotide every thousand base pairs or nucleotides .Because he mentioned the both.
This is the course ,my questions occur at 1:58
In another course , similar questions occur at 3:11

I do not really understand your question. What do you mean by 98.5% gene sharing? Do 98.5% of human genes have a homologous gene in chimpanzees? Or is there 98.5% sequence identity in human and chimpanzee genes (and if so, is the difference due to fixed differences?)? Is the one bp per 100 bp difference only related to gene regions? And I can by no means guess what you mean with your last sentence.

Each of us ,on average ,varies from a chimp by about one nucleotide at particular loci every hundred basis.

I'm the first-learner in this realm ,so I can't clearly explain that so much,but as what I learned,the conception could be a bit similar with SNP(Single Nucleotide Polymorphisms),but SNP only apply on a paticular species.

I tried to explain the concepts in my answer. Note that there in fact are SNP between species, so called shared alleles or trans-species polymorphisms.

You might want to read through the answers here: Do apes and humans share 99% of DNA or 99% of genes? What is the difference?

Even though I am not sure I understand your question completely, I want to try to explain to you the genetic difference between humans and chimpanzees. I will work through your questions:

We share 98.5% genes with chimps ,so there is about one percent difference .It means we can approximately differ from them by one base pair every hundred base pairs on average.

It is correct that humans and chimpanzees differ approximately every 100 nucleotides in their DNA sequence. This is does not mean that 98.5% of the genes are shared. It means that humans have about 98.5% (more precisely about 98.8%, The Chimpanzee Sequencing and Analysis Consortium, 2005) sequence identity with chimpanzees, disregarding indels. The main part of this difference (about 85% of the 30 - 35 Mio. different nucleotides) comes from fixed differences: a fixed difference is a position in the haploid genome in which every human has, say, a G and every chimpanzee has a T. Accordingly, the site is different between the two species for every individual of the respective species. The smaller part (about 15%) comes from sites that are either variable (SNP) in humans or variable in chimpanzees, or in both (there is even a small number of very old variants, i.e. shared alleles between humans and chimpanzees, e.g. see Azevedo et al., 2015). Note that the estimates get better the more individuals of the respective species are sequenced and compared.

A human receive 3 billion base pairs from each of parents ,and has six billions in total .Do the math by using one hundred to divide six billions and then it equals sixty millions.
Due to that, The person have ,on average ,sixty-million-nucleotide differences with a chimp.
However,the professor of the online courses I attended said it's thirty-million-letter differences.
Dose that mean it's counted on haploid?Why?

Yes, it is counted on the haploid genome. I would not make any sense to count it on the diploid genome. When looking at my last paragraph you might see why: Remember, we are looking at (i) fixed differences (both copies of a diploid human genome differ from both copies of a diploid chimpanzee genome) or (ii) at variable sites. Assume you find one site in one haploid genome that fulfills either (i) or (ii). If you then look at the same site in the other copy of the genome you already know that the position is either (i) or (ii). This means that it has already been counted as a difference. If you counted it again, in the worst case, over the complete genome, you would count everything twice. In general, you would strongly overestimate the absolute difference.

Also ,I'm not sure that about one percent difference is calculated on one base pair or one nucleotide every thousand base pairs or nucleotides .Because he mentioned the both.

I do not understand this. I had a brief look at the video and heard him talking of one nucleotide per thousand. He compares the sequence difference between human-chimpanzee (98.8% overlap, approx. 1 per 100, about 1.2% fixed differences and SNPS) and human-human (99.9% overlap, approx. 1 per 1000, 0.1% SNP), pairs. Note that in the last case we cannot look at fixed differences as there are no fixed differences between human populations. The 0.1% difference are the percentage of SNP in the human genome.

I'm sincerely appreciated for your detailed answers,after reading the first and second parts ,the third question has been solved . But I am not sure that I really make sense of the difference between sequence identity and genes,can you explain that for me?

According to your second answer ,I have question about "the same site".Does that mean the certain alleles at homologous chromosomes which control a certain gene have the completely same DNA sequences? –

What you seem to be mixing is having (i) homologous genes and (ii) identical sequence. (i) does not imply (ii). You can easily have the same gene but non-identical sequence, i.e. different variants of that gene. Within species we call that alleles, between species homology. Additionally, only a few percent or so of DNA codes for gene products (e.g. protein, miRNA, tRNA, rRNA, ...). So the vast majority of sequence differences between humans and chimpanzees lies outside of genes.

sorry , I have thought for a while ,my third question still exist ,the sentence might look weird , what I want to ask is that "why do we sometimes say one base pair of every hundred base pairs instead of saying one nucleotide of every hundred nucleotides?

To response the comment of  AlexDeLarge ,if the sequence of"the same" site is not identical ",how can we consider the one side by the other ?

@terdon: The Chimpanzee Sequencing and Analysis Consortium treated indels and nucleotide differences separately and "calculate[d] the genome-wide nucleotide divergence between human and chimpanzee to be 1.23%" which includes intergenic regions and introns.

@Snake: A site is one nucleotide. The vast majority of sites are equal between humans and chimpanzees (as you know, about 98.8%). Accordingly, you can easily identify the same site on the homologous chromosome even though the site itself is not identical.

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Is this modification of Livak's 2-delta delta CT method valid?
I have done a modification to include qPCR efficiency in the calculations:

In a given gene I calculate the fold changes relative to an arbitrary sample. That sample will be one and the rest will vary according to 2-dCT (equation 13 in Livaks paper). The efficiency comes into play when 2 becomes 1+efficiency (e.g. 1.9 when efficiency is 90%).
The gene of interest will be normalized by the reference gene:
$$\frac{(1+\text{efficiency})^{-\Delta CT_\text{GOI}}}{(1+\text{efficiency})^{-\Delta CT_\text{ref.}}}$$

This makes sense to me more because it includes PCR efficiency and keeps the all groups in the calculations. But I can't tell if I am missing somethng, since no one has descirbed this approach before.
What do you think?

PCR efficiency is not usually expressed as percentage (or per-unit). Its bounds are [0 2] i.e the maximum efficiency is 2 and the minimum is 0. (Ruijter et al. 2009; also see this post for calculation of efficiency.)
However, I just noticed that some people do express efficiency as percentage or per-unit. In that case your formula would be correct. I realize that there may be a confusion within the community; so you should know what you are calculating. For avoiding confusion lets just call this measure as amplification factor (denoted by E), which would be 1 + per-unit efficiency (as you mentioned).
When the primers have different efficiencies then you can't really use the $\Delta\Delta CT$ method. You'll end up with this formula (pretty much similar to what you have mentioned):
$$\large\text{Fold Change}=\frac{\left[E_\text{GOI}^{-CT^\text{condition}_\text{GOI}}\right]\bigg/\left[E_\text{Ref}^{-CT^\text{condition}_\text{Ref}}\right]} {\left[E_\text{GOI}^{-CT^\text{control}_\text{GOI}}\right]\bigg/\left[E_\text{Ref}^{-CT^\text{control}_\text{Ref}}\right]}=\frac{E_\text{GOI}^{-\Delta CT}}{E_\text{Ref}^{-\Delta CT}}$$
Where:
$CT^\text{condition}_\text{GOI}$ means CT value of the gene of interest (GOI) in a given condition (other than control), and $E_\text{GOI}$ means the efficiency of the primers for your GOI.  Similarly for the reference (Ref).
See this post too.


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Would someone lose some of their traits if they stop using them for some time?
A co-worker of mine told me, that there are some mutations in the genome during the life of a human body. So, the body changes genes to fit better into the surrounding environment.
My thought is now, if it is true, every generation of human beings loses some abilities which the body has not needed till the time.
A hypothetical example: in a time where education takes even more time and importance than now, would human beings lose their mechanical skills because they do little physical work?

You seem to have several major misconceptions about evolution and mutations. I strongly suggest reading through Understanding Evolution from the University of California, Berkeley.

@MattDMo: this is ablolut true, thats why I'm asking.

This question is relatively clear and easy to answer. I disagree with the close votes and with the down votes.

It has been substantially edited since I voted to close, retracted vote now.

A co-worker of mine told me, that there are some mutations in the genome during the life of a human body. So, the body changes genes to fit better into the surrounding environment.

Yes mutations accumulate during the lifetime but they are random. They are not targeted in a way that the organism adapts to the environment. Evolution happens through multiple generations and not in a single lifetime.

... every generation of human beings loses some abilities which the body has not needed till the time.

No. That does not happen.
It was once actually hypothesized by Lamarck that an organism gains or loses traits based on the use and disuse of those traits, respectively.
We now know that it is not true. A trait is not removed from the population unless it imposes a strong survival disadvantage to the population.
For more details see Why do some bad traits evolve, and good ones don't?


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Is there software or a website where I can browse extinct species?
Is there any software/website where I can browse for extinct species? It must be based on real animals that are now extinct. It may be in animated versions.

What research have you done so far?

In your next post please start sentences with a capital letter, and use a capital for 'I'. I have corrected this for you.

fileunderwater's answer is probably the most accurate. I just wanted to add that, depending on your needs wikipedia > lists of extinct species can be a decent source of information.

You can search for species that are "Extinct" or "Extinct in the wild" at the IUCN red list website (International Union for Conservation of Nature and Natural Resources). That list currently includes 903 species, but some of the assessments might be obsolete (see annotations). From that list, you can click and get some basic information about each species.
Also note that many countries have regional Red Lists, where you can find information about regionally extinct species (i.e. species that have gone extinct in a particular country). For instance, 209 species are labelled "reginally extinct" in Sweden (http://artfakta.artdatabanken.se/, site only in Swedish), most of them insects, while still being present in other parts of the world.


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A diagram of a crossover
How can one draw a crossover between ABK and aBk where genes A and B follow the Mendel's law of independent assortment and gene K does not i.e. K is linked to B?

Welcome to BiologySE! Where have you looked for help with this so far? Is this a homework question?

It's just an exercice that I'm interested in

Your question is unclear. What kind of a drawing do you want. Moreover, this questions seems to be primarily opinion-based.

I'm looking for a representation of the genome in a cell

I am voting to close as unclear mainly because we don't know to what locus is gene K not independent.

I'm not sure if this is what you're asking for, but in the following image, allele K (or k) is linked to B while A (or a) and B are independent.

Again, this is just a guess because your question seems a bit unclear to me.

Yes, that was the thing I was looking for

Oh, upvote and select it as correct then...! ;)


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Why does migration distance depend on log of molecular weight in SDS-PAGE?
I really want to know why in the result of SDS PAGE, log of molecular weight(MW) and migration distance (distance from the loading well) have a linear relationship. Why is it log(MW) instead of MW? Thank you!

A newer, related question: How does SDS-PAGE separate based on mass?

An SDS-PAGE standard curve of Rf vs LogMW is linear because the standard you're given is engineered to behave that way. An expanded SDS-PAGE curve would show that the actual graph is sigmoidal: Structues that are too large can't enter the matrix, and too small they pass right through. Your standard has taken into account the % composing the gel, and the size of the proteins which the standard consists of that ensure you get the linear data points on the semilog graph.
If we look at the raw data though plotted linearly, the graph isn't entirely linear. The data is much prettier, and trivial to convert back to MW if we log transform the MW. It's the same data, just mathematically transformed. Some more reading on it here.

Perhaps there is a mathematical derivation for this. I can't find it myself and when I am trying to derive I am getting something else.

@WYSIWYG  I don't think the migration distance is actually logarithmic in mass. The log function is just a simple curved function that fits the data reasonably well in practice, over the relevant range of values. I would expect distance to be proportional to some power of the MW. It's basically a kind of chromatography, so perhaps there is a derivation in analytical chemistry literature.

I think this is just an empirical formula that (approximately) fulfills the non-linear response of the relative migration distance (Mr) with the molecular weight (MW) - an observational rather than mechanistic explanation. The formula Mr ~ 1/(log(MW)) is equivalent to say MW ~ 10^(1/Mr), which is a simple exponential. The exponential function is the simplest solution to this non-linear problem, having the advantage of being asymptotic, that means that it can explain the fact that relative mobility values Mr are constrained between two fixed values, i.e. 0 and 1, for ANY molecule, no matter how large or small it is. If Mr = 0, 10^(1/Mr) predicts a MW -> infinity. If Mr = 1 (dye front), 10^(1/Mr) predicts a MW -> 1 (or actually -> 0 if we consider a parameter a in equation MW = a*10^(1/Mr)).
A linear model would fail to generalize to any MW, since predicted Mr values would not be limited within the given [0,1] range, plus the fact that behavior is really non-linear. (The intuition tells that the bulkier the molecule is, its chances of passing through the gel pores reduce exponentially, as the chance of finding pores 4x the size of the average one would not be half of those of finding pores 2x the size of the average, even though this is perhaps more metaphoric than real).

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Where do transamination and deamination take place?
The only information I know is about deamination is that it occurs in the liver and kidney. But in which part of the cell does deamination occur? To which tissues is transamination specific, and in which part of the cell does it occur?
I have searched Google and Google books and have come across some information like L-Glutamate dehydrogenase occurs in both cytoplasm and mitochondria and transamination occurs in the cytoplasm of all cells. But they were not from authentic sources, so I am asking it here.

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed, https://scholar.google.com

Those processes happen in just about  every single cell in your body

According to David H. Vroon and Zafar Israili aminotransferases (transaminases) are widely distributed among tissues, and are found in both cytoplasm and mitochondria, although this may vary between different aminotransferases:

Aminotransferases catalyze the redistribution of nitrogen between
  amino acids and corresponding oxoacids participating in both protein
  metabolism and gluconeogenesis. They are ubiquitous in their cellular
  distribution.
Tissue activity for AST (aspartate aminotransferase) is as follows in decreasing concentration:
  heart, liver, skeletal muscle, kidney, pancreas, spleen, lung, and
  erythrocyte. Two distinct forms have been identified: a cytoplasmic,
  or soluble isoenzyme, and a mitochondrial isoform...
The distribution and relative tissue concentration of ALT (alanine aminotransferase) is similar
  but importantly different. Highest activity is found in the liver,
  followed by kidney, myocardium, skeletal muscle, pancreas, spleen,
  lung, and erythrocyte. ALT activity is found in the cytosol; organ- or
  organelle-specific isoenzymes have not been demonstrated. The
  concentration of ALT in hepatic cell cytoplasm is comparable to AST;
  however, a mitochondrial ALT isoform is not found. In all other
  tissues, ALT activity is significantly less than AST.

As regards deamination, there is a Wikipedia page for glutaminase, which indicates that it is found in the mitochondria of a variety of tissues. There are two isoforms, one especially active in the kidney, and the other in liver (although both are found in other tissues).

The oxidative deamination takes place inside the mitochondria, because the
glutamate dehydrogenase is localized in the mitochondria.
About the transamination, I'm not sure if it occur inside the mitochondria or in the cytoplasm.
The information about the oxidative damination and the enzyme could be found at this link:
http://www.bioinfo.org.cn/book/biochemistry/chapt17/sim2.htm

Please add citations to support your answers. See the accepted answer to this question for a good example. Scientists (at least good ones) don't accept statements just on their face - they must be supported with evidence. If you are making a claim, back it up.


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In vivo delivery of ssDNA
I am looking for a system with which I can deliver (large quantities of) ssDNA in vivo (say in mice). I do not know whether it is of importance but the 5' end of the ssDNA fragments are assumed to be phosphorylated.
If you could suggest some efficient delivery systems to me I would be very delighted.
Many thanks for your help in advance!

Small ssRNA  can be delivered in-vivo using a peptide from rabies virus (1, 2; it is quite specific to the brain, though). It should work with ssDNA as well but I don't know of an experiment that has tried it.

Electroporation!

Sure, that would be a possibility for cell cultures, but I am looking for a system that can do the job, for instance, in mice.

@Luigi how can someone perform electroporation in vivo?! :O

@user19099 In vivo electroporation is possible but it is very localized.

@user19099 In vivo electroporation is simple for intramuscular application, just inject the DNA, and then zap the muscle with the electrode. I've seen a paper that used an endoscope to do electroporation inside pig intestine with decent results. Not so good with intravenous injection though. What OP is asking is basically an entire research program.

@tobias The answer to this is anything but simple, and doesn't really exist yet. Many groups are working on non-viral methods to protect DNA and/or RNA in the circulation, target it to specific tissues, get it taken up efficiently, and then release the cargo in the right compartment of the cell. It's been challenging, and is far from finished. I would suggest looking at AAV, as its genome is ssDNA.

I would also look at hydrodynamic injection, which is good for delivery to hepatocytes, but not very practical for any other organ.

I agree with @user137 there are no easy answers - especially with 'large quantities'.  ssDNA material may even trigger innate immunity (eg Toll receptors/ interferon).  This recent work gives just one flavor of possible complications.


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how did the domestic dog evolve and was the role humans played in its evolution justified?
Humans have been selectively breeding dogs for a long time. Why do we do it? What are the positive and negative impacts of selective breeding and why do they occur?
I am writing an independent project on the subject >should selective breeding in dogs be allowed<, although I can think of many negatives to artificial selection, from a loss of genetic diversity to health problems for supposedly "pedigree dogs" I am finding it hard to find  positives other than for the development of breeds. I am especially looking for scientific research/papers/books on this theme of selective breeding in order to find  enough scientific information to write a balanced 3000 word essay. I hope this clears up the confusion surrounding the question, I was just looking for help, I did not realise my question would be graded!

What is your question? You are actually asking for a textbook. Please add some details to narrow down to the actual issue.

Welcome to Biology.SE. Why are we performing selective breeding in dogs? is more a question of sociology and human culture than biology. good and bad. The terms "good" and "bad" are subject to personal interpretation and it is therefore impossible to give a scientific answer to this question. For these reasons, I am voting to close as off-topic.

I think if '(both good and bad)' was removed it could be answerable. It does sound like a homework question to me (although of course that doesn't in itself mean it should be closed). I think the biggest problem is there's no evidence of research by the OP before posting.

Selective breeding, or artificial selection, by its very definition is the selection of desirable traits over less desirable ones. Individuals more like the desired phenotype are allowed to reproduce while others are not. Therefore, the reason a breed is selected in a certain way may be because of certain aesthetic characteristics, or speed, or hunting ability etc. For example, Schnauzers might have their beards/moustaches because for many generations breeders have wanted to accentuate this feature.

Artificial selection often causes problems because of inbreeding (an increase in homozygosity) and poorly imposed selection (only the desirable trait is considered, not other bad traits). This is why many dog breeds have associated diseases or health problems.

Image source

The question is of poor quality and it is impossible to offer a good answer to it (IMO). You did a good job at offering some pieces of info that may help the OP though (+1)

there's obvious weaknesses in the question (even after my edits, I wanted to make the question clearer, but the issues of opinion remain because I didn't want to interfere with the OP's intent), there's really not much needed to answer such a question - why do we select for desirable traits? .. because selecting for undesirable traits would be stupid. Hopefully it gives the OP somewhere to start reading about it.


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How is the size of a gene defined?
Is there an agreed definition as to how many nucleic acid bases constitute a gene?
If not, why not? I'm not sure I understand how the exact sizes of genes are defined.

@user19099 Surely there's a range though. From XX Mb to XX Mb.

yeah the range is from 76 (tRNA) to 80781 (titin) bp in humans.

In what species? Using what definition of gene? I think what you're really asking is precisely what the definition of a gene is (you may be surprised to learn that it isn't a black and white concept). If that's your question, please clarify.

I have changed the title because it was not the poster's original and whoever changed it previously did so to one which doe not reflect the question's content. The questioner is clearly not asking  what the average size of a gene is — although one of the answers would have wished this. Rather he seems to want to know  the basis of defining the limits of a gene. (Initially I thought he assumed all genes had a specific size, but that would really be too naive. It's surely just limited command of English.)

@David The title of the original post was "what is the average length of an allele". It is not about answerers wishing for this title so that is is probably easier for them to answer. However, because of your edit some answers seem like "not an answer", now. Why not let the OP clarify the question themselves?

@WYSIWYG Be that as it may. The title did not reflect the question — nor did the answers you mention. In particular they do not address the last sentence. I shall be rewriting my own answer to clarify this. As for the questioner giving clarification, I hope he will.

You asked a question, the question has been answered and then you changed the question. Please, just edit back, accept of the current answer and open a new post for your other question.

@terdon Let's concentrate on humans first.

@user19099: The number for the titin gene is not entirely true. TTN (gene coding for titin) itself is about 300 kb long.

In fact, TTN is not even the biggest gene. The biggest I found is CNTNAP2 with approx. 2.3 mb.

@alexdelarge thanks for that info! I didn't actually search for biggest gene, but just looked for size of titin :)

Is there an agreed-upon definition as to how many nucleobases constitute a gene?
If not, why not?

There is no such definition. A gene is a region of the DNA that is transcribed. Typically a gene should have a transcription start site dictated by a promoter and a transcription stop site marked by termination signals (like terminators and poly-A signal etc.)
There are some little RNAs (~18nt) that are produced from TSS of usual genes but are probably products of failed elongation. These are not really considered genes as they are heterogeneous in size and are not marked by any boundary.
There may technically be a minimum cutoff on gene length which could be the length of DNA necessary for the RNA-polymerase to sit and also include the termination signals. As indicated in the comments, the smallest gene may be the tRNA. However, the smallest annotated gene from the GENCODE annotations is TRDD1 (just 7nt long!!!). This is not based on gene prediction; it is manually annotated by the HAVANA team.

What is the average length of a gene?

I just did a rough calculation from the GENCODE human genome annotation file (version 23).
The average transcript length seems to be around: 1.5kb
The average gene length seems to be around: 29kbp
The genes would be longer than (or equal to) their corresponding transcripts because the latter gets shortened due to splicing.
I made a histogram plot of these lengths for convenience:

Transcript length distribution

Gene length distribution

Note the sharp peaks at 100bp. Quite interesting!

Remi has user19099 have mentioned that the longest gene in humans is titin. It seems that it is the longest gene in many other diverse animals. See What's the longest transcript known? for more details.

Methodology (so that limitations can be identified)
To calculate gene length distribution: I parsed the GTF file for "genes" (third field i.e. feature) and subtracted the fifth field (stop) from fourth (start).
To calculate transcript length distribution: Got the transcript fasta file from the annotated locations. Calculated their lengths. Plotted the distribution.

I hesitated to do that but was too lazy! Good job. Note however that your average is twice as high as Strachan and Read (1999) average. Do you know what is causing these different estimates?

@Remi.b Well, one obvious explanation could be that we have more annotated genes now compared to 1999.

...and we disproportionally annotated small genes in 1999. It is possible indeed. Would be interesting to open a post on the subject.

@Remi.b Or possibly the entire genes were not annotated. With better sequencing technology we can map the genes better.

Very informative and especially the spike at 100bp is so interesting.

@Remi.b yeah, remember that the human genome wasn't sequenced in '99, so those estimates could only be on what they had. Also note that WYSIWIG is referring to transcripts and we had even less information on alternative transcripts in '99 than we do today. Finally, consider long, non-coding transcripted regions which might be included in the dataset that WYSIWIG used (I don't know) and which wouldn't, really, be considered "genes" as such. Well, depending on how you define it... :)

Oh..ok that makes more sense now. Thanks for following up on this issue. +1

@WYSIWYG Thank you for this! I am so happy to see a distribution of what constitutes a human "gene".

@WYSIWYG this is really neat. Can you show me the source code for your gene length graph so I may recreate this graph in another model organism?

@Tom I got a vector of lengths from the GTF file. It's fairly easy. Just take a difference of start and stop. For histogram, I used MATLAB. This can be done in R and python too.

How are gene size defined?
DNA is made of 4 nucleotides A,T,C and G. A series of such nucleotide make up any section of the genome including the genes. The number of nucleotide in a gene is what we call the gene size. Of course, one might discuss on the definition of the exact beginning and end (and methods to determine them) of a gene but this is a discussion for another time.
Because, DNA is double stranded, instead of talking about a sequence of 10 nucleotides, we often talk about a sequence of 10 base pairs (bp). When dealing with longer sequence, we can use the prefix "kilo (k)" to indicate one thousands base pairs. For example: 12 kbp = 12,000 bp. For even bigger values, prefix "Mega (M)" is used to indicate one million base pairs. For example: 7 Mbp = 7,000 kbp = 7,000,000 bp.
Average and median gene size in humans
There is a lot of variation in gene size among genes within a species but also among species. So much so, that an average does not convey much information. But here is the average and median gene size in humans:

The average gene size in humans is 10-15 kbp (kilo base pairs) (Strachan and Read 1999)
The median gene size in humans is of 24 kbp (Fuchs et al. 2014).

The extremes in the human genome
As @user19099 said, the longest gene in the human genome is TTN coding for the titin protein. TTN is about 100 kbp long. tRNA are typically very short sequences (76-90 nucleotides) but please not that these sequences will never be translated into proteins.
Book recommendation
The book A Short Guide to the Human Genome by Scherer is very good to give a feeling of what the human genome looks like.

We could also discuss what a gene actually is and if an entity like the gene as we see it even exists. Good answer though!

Thank you! Yes, the mean and median size of a human gene is roughly what I was asking (one of the questions anyway).

Interpretation of the question
You ask two things: 1. the number of nucleic acid bases that constitutes a gene, 2. (implied) how the size of genes are defined. The first question appears strangely naïve, but the second suggests this may be a misunderstanding. I therefore intend to start there.
How are the limits of a gene defined?
Genes are defined in terms of their information content — most obviously to specify proteins which may confer a phenotype, but also in specifying structural and regulatory RNA molecules. The extent of genes, or the length of DNA they occupy, is therefore determined by their information content.
Are genes contained in similar size DNA ‘boxes’?
Your first sentence suggests you think all genes have a fixed number of nucleic acid bases. This idea seems strange as, at the simplest level (e.g. in bacteria), their information content differs in size with the size of their protein or RNA products. However perhaps you have the idea that the genome is divided into similar sized regions with a discrete start and finish into which the information is accommodated (the rest being packing, as it were). This is not the case.
Genes occupy different lengths of DNA
In fact, the lengths of different genes differ within a species and between species. In simple prokaryotes this is mainly because they encode proteins (or RNAs) of different lengths. In eukaryotes (where the genes are generally much larger) this is further complicated because of the varying number and size of their introns, which do not (normally) encode protein.
How are the end-points of a gene determined in practice?
A simple answer to the above (appropriate to the level of your original question) would be that genes extend from the promotor regions, where the RNA polymerase binds for transcription, to the transcription termination point. Thus, at a first approximation, they can therefore be defined in practice by the regions of DNA that specify mRNA (or pre-mRNA) or other RNAs. The modern method for doing this would be RNAseq.
(The situation is more complicated than this in practice because there may be regions of the DNA that affect the expression but are not transcribed. But I wouldn’t worry about that at the moment.)

@ShanZhengYang — I have tried hard to understand what you were asking in your question. If I have not, could you please clarify.

"Your first sentence suggests you think all genes have a fixed number of nucleic acid bases." Sorry, that was not my intention.

Within my question, I asked multiple questions, which has caused some confusion. Thank you, "How are the end-points of a gene determined in practice?" was in fact one of my questions above. We are still researching how parts of the genome give rise to phenotypes, so it wasn't clear to me how we could be so sure of the boundaries of "genes" which result in "phenotypic traits".

"there may be regions of the DNA that affect the expression but are not transcribed"  This hits at the heart of my question. So...how could these boundaries of genes be so clearly defined? RNA-Seq data is not that clean...

@ShanZhengYang — Thanks for your clarification. Apologies if I my answer was too simplistic. As regards the problem of 'fuzzy boundaries' I imagine that people adopt a particular approach that allows quantative comparisons (between species, between genes) which is indicative even if it is not perfect. For bacteria it may be easy to identify promoters and termination signals and use those; for mammalian genes an RNA seq approach with an annotated genome may be most practical. Different assumptions may be made in different cases.


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DNA replication in E.coli
What is the difference between replication and to divide? My A level bio book says that it takes 20 min for E.coli to divide and in next page it's written that E.coli completes replication within 38min.
Moreover, there is a diagram (shown below) which contradicts as what I thought.
Please explain the difference between replication and division.

Your question is unclear. The diagram you show has nothing to do with replication time per se, but with the mechanism. It shows the Messelson-Stahl-Experiment. So please clean up your question and make clear, what your question is.

This diagram shows that to divide frm 1st  gen to 2nd gen it took 20 min but then  i read "E coli completes the process of replication within 38 min, average rate of polymerisation being 2000bp per sec. " but then that dig says that it took Ecoli 20 min to divide... And that is my confusion.. Is replication nd to divide different

Here, replication means DNA replication, while division means mitosis.

There is no mitosis in prokaryotes. This term applies only to eukaryotes. Say simply "cell division".

I am unsure if I really understand the question. Are you wondering how the rate of DNA replication can be slower than the rate of cell division if every daughter cell needs a chromosome copy?
If so, keep in mind that prokaryotes have different origins of replication on their chromosome so that DNA replication can actually be parallelised. Cooper (1968) presents a mathematical model that is consistent with experimental findings and indicates that when the DNA replication step becomes limiting for cell division, E. coli switches to multiple replication forks, thus decreasing the net time needed for complete DNA replication.
According to that, it is no contradiction that DNA replication per se takes longer than cell division.

Replication refers to DNA replication and division refers to the cell division. Yes it is true that, in E.coli replication can be slower than the division time. This is a well known problem in molecular genetics.
The bacterium copes up with this by having a partially replicated genome during the beginning of the "cell cycle". So there are actually two origins of replication when a new cycle starts. When the replication proceeds you have multiple forks (from the replicated origins). Because of these multiple forks (forks within forks), the replication time speeds up. See the figure below:

 From Fossum et al. 2007
For more details see:
Fossum, Solveig, Elliott Crooke, and Kirsten Skarstad. "Organization of sister origins and replisomes during multifork DNA replication in Escherichia coli." The EMBO journal 26.21 (2007): 4514-4522.

The picture that you have shown is something totally different. As mentioned by Chris, the picture illustrates the Messelson-Stahl experiment to demonstrate the semiconservative nature of DNA replication. Do not confuse that with the above problem. As for the 40min shown from generation-1 to generation-2, in this picture, I feel that it is a misprint.


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What is the meaning of a reported OD600 value?
I can't find a reference that explains what, for example, OD600 = 0.1 means.
For example, Wikipedia states

OD600 is an abbreviation indicating the absorbance, or optical density, of a sample measured at a wavelength of 600 nm.

In other words, the OD600 value reports (a function of) what percent of light goes through a sample. But that depends on the thickness of the sample. More light will go through 1 millimeter of fluid than through 1 meter of the same fluid. So what is the thickness of the sample involved when reporting OD600? Or is the OD600 independent of that, so that it actually has units that people simply omit? In that case, what are the units? What is a precise physical interpretation of what is meant by the measurement OD600 = 0.1?
Suppose OD600 = 0.1 for some sample. I shine 1 mW of 600nm laser light through a 1 cm path length of the sample. What is the transmitted power?

related: http://biology.stackexchange.com/q/47973/3340

For most laboratory spectrophotometers the path length in cuvette that holds your sample is 1 cm, and unless another path length for the light is specified you can always assume that the Beer-Lambert Law for absorption of light is using 1  cm.
When growing a bacterial liquid culture in an incubator, the OD (wavelength is usually 550 nm or 600 nm) is a approximation of the number of cells, or colony forming units, or cfu, per mL of culture.
The recipe, or protocol, will normally specify the bacterial strain to use, and the desired OD (at which point one either harvests the growing cells, or possibly adds something else to the culture, like a drug, or a viral stock).
To actually know the number of cfu/mL for a specific bacterial strain one needs to construct a growth curve by taking aliquots at defined time points, and reading the OD, and also plating out some serial dilutions.  After incubating the plates at the correct temperature one can count the number of cells per mL and plot cfu/mL vs. OD600 (for example).

Nitpick: I believe that OD600 correlates better with total biomass than with the number of cells (e.g. growing but non-dividing cells do show continued increase in OD). This also makes more sense intuitively (at least to me).

OD600 is usually used in molecular biology as a measurement of the density of bacteria in a sample.  That frequency of light typically has little other scattering and the bacterial bodies
The interpretation of a specific absorbance is by Beer's law:
A = abc
a = specific absorbance of the light at that frequency by the specimin
b = the concentration of the specimen
c = the path length; the length of sample along the path of light shining through the sample
In practice for OD600 an absorbance of 0.1 is usually not converted but is understood as a low concentration of bacteria in the sample.  Typically E coli and most bacteria will start growing in logarithmic fashion, dividing regularly so the OD600 doubles in a period ranging from 10 minutes on up, depending on the bacteria.
Around OD600 = 1.0 the bacteria will stop dividing, which is called 'stationary phase'.  In practice most measurements of OD600 are not accurate above this level in most instruments since Beer's Law is only accurate in linear form in dilute samples.

Suppose OD600 = 0.1 for some sample. I shine 1 mW of 600nm laser light through a 1 cm path length of the sample. What is the transmitted power?


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Is Valerian extract a diuretic or an antidiuretic?
I am trying to determine if valepotriates (valerian extract) is a diuretic or an antidiuretic. Some individuals take valerian as an herbal supplement for anxiety disorders. Some individuals claim that valerian extract can act as a diuretic, while others claim that it is an anti-diuretic. I am trying to determine which it is - diuretic or antidiuretic?

I couldn't find credible sources on the effect of valerian on the kidneys. One case report mentions hyponatrema (due to excessive diuresis), but relates it to excessive water consumption instead.

where have you seen these claims that is has diuretic or anti-diuretic properties?

Without a source, this question is unclear.

There is one study that I can find that has been cited in the medical literature that examines individuals taking valerian extract for generalized anxiety disorder. In this paper, there do not appear to be any claims that valerian has any diuretic or anti-diuretic properties. However, that's not to say that those properties don't exist. Additionally, there is no indication that the extract is associated with hyponatremia or hypernatremia, which are two other signs of disorders affecting salt/water balance. Overall, it sounds like if there is a diuretic or anti-diuretic effect of valerian, it is not well-described (yet).

The Natural Medicines Database monograph for Valerian includes a pooled adverse effects analysis of more than 20 clinical trials with Valerian for various indications.  No diuretic effects were identified in any trials.
Natural Medicines Database monographs are available by subscription only and are considered by the vast majority of healthcare professionals to be the gold-standard source for any natural supplement, herbal or food supplement evidence-based information.  www.naturaldatabase.com
Professional Opinion (Pharmacist):
The specific mechanism of Valerian is unknown.  Valerian is possibly effective for insomnia and it is suggested that it is also helpful for anxiety, depression and stress (insufficient reliable evidence to rate).  A large number of pharmaceutical products that have similar uses (tri-cyclic antidepressants, mirtazapine, trazodone) can cause urinary retention, sedation and dry mouth by anticholinergic effects.  If I had to guess whether it would have diuretic or antidiuretic properties, I would go with antidiuretic effects secondary to anticholinergic effects.

Welcome to BiologySE - thanks for your answer. It would definitely strengthen your answer if you could add some links to the database that you mention so other users can read about your answer. Also, you may want to check out the help center for how to write a good answer for some additional pointers - it will help you gain more reputation points in the community. Link: http://biology.stackexchange.com/help


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Need Help Identifying this Critter (Insect?)
This creature is hanging out on my kitchen window. I live in Western Maryland, US, near the Potomac River. The creature is about 3 inches long (measured from tip of mandibles to tip of tail). Does anyone know what it is? Is it dangerous? Rare? I've been living here about a year and have never seen one before.

It looks like an adult Dobsonfly (Corydalidae), where the adult males have huge pincher-like jaws. Apparently, the jaws are the result of sexual selection and, even though they look scary, males cannot use them to bite.
I'm only vaguely familiar with the group though, and cannot say what species this is.

(Picture from bugguide.net)


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Why is your taste affected due to sinuses?
I heard someone say "My sinuses are acting up, I can't taste the food." I don't think the person is lying, they probably believe this but I'm having trouble seeing how the sinuses would affect the taste buds. I realize smell helps identify foods, but it seems like not smelling a food wouldn't affect taste so severely as people make it sound.
I don't have sinus troubles much and haven't experienced this, so I'm not claiming it's fake, I'm just curious to understand how that works.

Scent and taste are intimately connected. Try tasting something flavorful, rinsing your mouth out with water, then holding your nose and tasting it again - it will be much "duller". Taste buds and scent receptors signal to the same part of the brain.

The first thing which is important to note is the difference between taste and flavor.
Taste refers to the chemical sense performed by taste buds present on the tongue, and to date there have been identified 5 tastes: sweet, bitter, sour, salty and umami. Thus I understand obstructed nose and sinuses should have no significant effect on taste.
Flavor, on the other hand, is the final sensation that conveys the information about the food we're eating, and involves not only taste, but also smell, mechanical sensation (like that smooth flavor from cream) and pain and temperature pathways (hot and spicy food, like peppers). Part of the signals from all these receptors located on the mouth (and nasal) cavity ultimately converge to the same location in the brain, where they are processed to create the final flavor (I know taste and smell do converge to the same region, cannot tell the others with full certainty).
So, having obstructed sinuses and nasal cavity can interfere with the smell detection (by not allowing molecules to bind to receptors on the olfactory epithelium), and thus interfere with flavor.
You can check this site which I think explains very well what I am trying to pass on, it is very clear and covers all the physiology that I talked about, allowing you to go deeper into details if you are interested: http://www.cardiff.ac.uk/biosi/staffinfo/jacob/teaching/sensory/taste.html and also http://www.cardiff.ac.uk/biosi/staffinfo/jacob/teaching/sensory/olfact1.html (you have to scroll down to the main text)

any sources to add?

@AliceD I wrote based on what I have been studying over time, from neuroanatomy and anatomy to physiology, and also some autonomous research, but if you search it on google you will probably get the same information, maybe even in Wikipedia!

@Filipe I suggest you search through those sites (and preferably more reputable sites as well) and add some sources to your answer. Otherwise, it will be closed/deleted. See here for a guide to writing good answers on Bio.SE.Thanks

@theforestecologist i feel as if we are giving way to much importance to reputation. I am simply sharing part of the knowledge I have been accumulating over time, from what I have studied in Medical school to what I have read in my personal researches and life experience. That is how it should be taken, as me trying to share what I know with another person, and not the whole and absolute truth - and that's science, in my opinion. I don't think reputation should be so impactful, but rather the facts that are behind what I'm saying.

@FilipeRocha - everyone can claim to be an expert and start babbling away. Although I don't doubt your expertise in this area I'm downvoting your answer as you're blandly ignoring the advice of hi-rep users. Please understand - reputation on this site is a reflection of nothing more than user effort; even laymen can gain a lot of rep here simply by quoting wikipedia. The reason we ask for sources is that it allows users to background read on the topic and get in-depth understanding of your answer.

@Filipe and all that experience makes finding proper sources easier because you already know some sources, you know the proper keywords to find new ones and you can better recognize their validity. Anecdotal information is interesting for sure, but on this site we require that you back up your answers with sources b/c other users don't have the experience to know what is valid or not. If you want to share anecdotal info/answeres on Bio.SE, it is best shared (and welcomed) in the comments.

@theforestecologist thank you for the explanation, it does make sense and if it was me I would also like others to show me where can I find something that I can use to verify or further learn about the topic.  So I went looking for such and found this site which I think explains very well what I was trying to pass on, it is very clear and covers all that I talked about: http://www.cardiff.ac.uk/biosi/staffinfo/jacob/teaching/sensory/taste.html
I hope you find it useful (you have to scroll down to the main text), and once again thank you

@AliceD the answer above is also for you :)

@Filipe Great! Just one last thing: we ask that answers be complete (i.e., not needing comments to "fill-in" further information). Please incorporate your link into your answer. Further, providing context for the link is super useful because some links break over time; as a result, it's useful to provide a bit more than just the link (.e.g, what does the link contain, what part of your answer is it pertinent to, etc.). Copying (and citing) a photo (which that site has numerous) would be a great addition to your answer as well :). Thanks for putting in the effort to improve!

@theforestecologist done :)


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How do molecules signal pre synaptic neurons to activate?
How do molecules signal pre synaptic neurons to activate? and also is it more the structure or the elements in the molecule that allows it to activate the neuron also how do molecules bind to receptors and same as last time what is more important to do so the elements in the molecule or the actual structure? please answer I cannot find the answer anywhere else expert answers are appreciated!
-Gus

Read about neurotransmitters. This question is too broad and would be put on hold unless it is narrowed down.

Activating a neuron generally means depolarizing the neuron, sometimes depolarizing enough to trigger an action potential. In general, molecules activate neurons by binding to their cognate receptors in the neuron cell membrane. Sometimes the receptor is, itself, an ion channel. Other times the receptor initiates a cascade of events in the neuron's cytosol that end up modifying the cytoplasmic portion of an ion channel and thus opening the channel. In both cases, the channel is usually specific for positively charged ions (cations) (e.g. Na+ or Ca2+) whose concentration is greater outside the neuron than in the neuron's cytosol. Activation results when these cation channels open and allow positively charged ions to flow into the neuron. This entry of positive charge reduces the neuron's cell membrane potential, making the potential less negative. If enough positive charge enters, the neuron may be depolarized enough to trigger an action potential on the neuron's axon. This is what is usually meant by activating a neuron. It depends on the three-dimensional structure of the molecule (often a neurotransmitter) and the structure of the receptor. The binding of a signaling molecule to its receptor is usually non-covalent, often mediated by hydrogen bonds.

You've given a nice answer, but references would be much more appreciated. Please add some citations in your answer to make it more helpful.


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How to Determine Sufficient Time for Melanoma Survivor to Be Considered Low Risk?
Regarding melanoma, how do we determine the minimum amount of time that a patient is disease free for them to be considered low risk? We are attempting to do survival analysis on RNASeq data from melanoma patients.
We are at the stage where we need to adjust the threshold that dictates how long a "Disease Free" patient needs to be disease free to be considered a low risk case. Is 5 years a good parameter or is it too conservative?
Academic sources for protocols, or similar examples are encouraged.

From undergraduate courses of cancer, the 5 year survival rate is common. However I have no idea where that value comes from.

Do you vaguely remember any literature that you can point me to?


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What´s the origin of junk DNA?
Most eukaryotes posses a certain amount of junk DNA in their cell nuclei. What is (are) the origin(s) of this junk DNA, And is it realy junk (superfluous)?

There is nothing like junk DNA. Originally we thought this would make about 90% of our genome, but since then we learned a lot of functions for it: Regulatory, miRNA genes, etc. Carrying so much "junk" around would pose a massive evolutionary disadvantage.

You wrote that "all organisms...in their nuclei". Two of the three kingdoms of organisms do not have nuclei, so I have edited your question. I am also unsure whether all eukaryotes have junk DNA. I would advise you to think carefull before writeing "all" in relation to biology.

@chris - You're flat-out wrong.  Many functions have been ascribed to regions once believed to be "junk", that's true.  But if you add up all those now-functional regions, you're still left with about 90% of the genome being junk, because each of those new functions is only a tiny fraction of the genome.  Don't read media reports, and don't even read the press releases from the teams who find functions -- go and actually do the math, and it still turns out that 90% of genomes are junk

@iayork Not junk - non-coding. That's a big difference.

@iayork You are voicing very strong opinions here. Try to replace "junk" with "of unknown function" in your statements and you'll realize why the term junk DNA is so misleading and is very rarely used by scientists (as opposed to journalists).

Most scientists are virtually ignorant of the whole field of junk DNA.  There are people who actually do study junk DNA, and they call it, yes, junk.  The less people know about the field, the more absolutely confident they are in their claims about it; and that includes scientists in unrelated fields, who rarely other to read the literature of the specialists.

"Junk DNA" is more aptly named noncoding DNA. This is defined as any DNA region that does not encode for a gene or more precisely is not within an open reading frame. In the human genome over 98% consists of noncoding DNA. However the more we learn about molecular biology the more we understand the biological function and importance of noncoding DNA. Examples for important functions are:

Regulatory regions that control the expression of a gene
Regions coding for regulatory RNA
Regions where epigenetic regulation takes place

However, there are also regions which likely do not have beneficial biological function, which may rightfully be called junk:

Transposons are genetic regions that can copy themselves (either by an enzymatically active RNA or by encoding for the protein transposase). They are believed to have evolved as "selfish genes" and several known defense mechanisms against rogue transposons exist (siRNA, RNAi). Transposons and the defense mechanisms have now become powerful tools in molecular biology research.
Endogenous retrovirus sequences which are remainders of retroviruses which have inserted themselves into the germ line and become inactive through mutation.

However, even these "junk" regions are believed to have important evolutionary functions such as protection from mutation through retroviruses: Because there are large DNA regions where the precise order and function is not important, a retrovirus that inserts itself at random positions of the genome is less likely to cause permanent damage.

"Junk DNA" is more aptly named noncoding DNA.  I don't agree with this. Much non-coding DNA is functional, and there is no reason in principle that non-functional DNA couldn't produce at least a (non-functional) transcript - as ENCODE showed directly.  Trying to make "non-coding" synonymous with "junk" confuses the issue.

@iayork Did you read beyond the first sentence? I am saying exactly what you are saying. The reason I open with this particular sentence is that most people do use junk DNA and noncoding DNA synonymous. In fact, if you search google or wikipedia for junk DNA, the first hits you find are all about noncoding DNA.

Since you agree that junk DNA is not non-coding DNA, why confuse the issue by saying the junk DNA is "more aptly called" non-coding DNA? The two are very different in concept and practice.

@iayork Sorry pal, but your definition of junk DNA is just different from how most people understand the term. Therefore this discussion will lead nowhere. I am just going to say that I will stick to using junk DNA and noncoding DNA synonymously since that is what most people do (as you can see if you look at the top 10 hits for "junk DNA" from google).

@Thawn I liked your description , you can refer to this paper as an example http://www.nature.com/nrg/journal/v6/n12/full/nrg1756.html

@Learner That is indeed a good article describing the evolutionary role of non-coding DNA. However, unfortunately, nature does not offer that article free of charge which means most people will not be able to read it. Therefore, I will not add the link to my answer.

Briefly, we know of many mechanisms by which genomes can get larger.  Tetrapods had at least two complete genome doublings in their history; transposons expand; retroviruses insert; partial duplications lead to pseudogenes.  And these expansion mechanisms can be fast -- full genome duplications double size in a single generation.
But we know of very few mechanisms by which genomes can get smaller, and most of those are very slow, and very few are targeted.
From an mechanistic viewpoint, it's very difficult to imagine a targeted way to remove useless but harmless DNA quickly, and with 100% accuracy.  If accuracy is not 100%, then the pathway would be more harmful than the DNA it seeks to remove.
The key is that if extra DNA is either harmless, or nearly harmless, there's no reason to eliminate it, and there are reasons (errors in removal) to not try to remove it.
So the short and simple answer is that genomes can accumulate useless DNA much more readily than they can get rid of it. It's just common sense, which matches 30 years of experimentation.

This is a good explanation why evolution tends to favour "bloated" over "streamlined" genomes. However, this is only true for higher, multicellular organsims, where fast replication is not key to survival (in multicellular organisms, most of the cells are not replicating throughout large portions of the organism's life). For single celled organisms this is definitely not true and they quickly loose genes unless there is selective pressure to keep them.

@Thrawn Agreed that the genomic dynamics change in different groups.  The theoretical arguments are the same, but the "cost" even of non-functional DNA becomes higher.  A trivial cost for multicellular organisms, that's not sufficient to select for genome shrinkage, may be a significant evolutionary cost for others.

You know, for someone who so vociferously and adamantly claims to know what the "true scientists of junk DNA" are doing and saying, there is a rather obvious lack of citations in your answer.

@MattDMo which part don't you understand? Most of this is pretty basic stuff.  As I say, it's just common sense.


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How do heredity and regression to the mean work with respect to intelligence?
I am trying to understand the heredity of intelligence between generations in general, and how regression to the mean works in detail in particular. The answer I'm looking for should preferably answer some of the following questions.
When looking at the genetic basis for intelligence, it seems to me that the additive contribution of the genes should not be subject to regression to the mean, and that regression to the mean should rather be due to recessive genes and emergenesis. Is this correct? If so, what do we know about the extents to which these two mechanisms contribute to intelligence?
Towards which mean will a specific child be expected to regress? I have seen various suggestions here, ranging from the mean of the racial groups of the parents, to that of the child's grandparents.
Is it even possible to write down an (approximate) equation for the expected intelligence of a child, in terms of for instance the intelligence of parents, siblings and gransparents?
If someone coould answer these questions, that would be awesome!

I don't think you need this question to be specific to intelligence - you are asking really about regression to the mean and additive genetic variation as a general problem

As @rg255 said, this question has not reason to be specific about intelligence. I think the question is on-topic and not too broad but a very good source of information is the chapter "quantitative genetics" in A short guide to population genetic by Gillespie.

Thank you for your comments, and the reading suggestion. I agree that parts of this question could be answered in a more general framework, but for instance our knowledge of additivity vs emergenesis could be trait specific, no?

Your comment make me think that you might want to start by reading the definition of heritability (see this post). I never heard of the term "emergenesis" before. Reading from wikipedia, it seems to be the equivalent of what we call epistasis in biology. I will try to formulate an answer a bit later today.

I think the question mainly highlight either of two misunderstandings:

misunderstanding about the definition of heritability
misunderstanding why the slope of the regression line is equal to heritability (in the narrow sense).

Definition of heritability
Please have a look at the post Why is a heritability coefficient not an index of “how genetic” something is?.
Notation
Please note that, here I use $h^2 = \frac{V_A}{V_P}$ to designate the heritability in the narrow sense, where $V_A$ is the additive genetic variance and $V_P$ is the (total) phenotypic variance. If anything of what I just said is unclear, please refer to the aforementioned post.
Without any loss of generalization, we will set our scale so that the average phenotype in any studied case is equal to zero. From this starting value, we note X (with a subscript) the contribution of a given haplotype (or allele) to deviate the phenotype of an individual. We will note $E$ (with a subscript) the contribution of a given environmental state to deviate the phenotype of an individual.
An individual phenotype
Let's consider an individual O (stands for offspring, it will makes sense later). The phenotype of this individual is given by the addition of the contribution of each haplotype and of the environment. The expected phenotype of O (called $P_O$) is therefore
$$P_O=X_m + X_p + e_O$$
, where $X_m$ is the contribution of the maternal haplotype, $X_p$ is the contribution of the paternal haplotype and $e_O$ is the contribution of the environment.
Just a note
It might be worth skipping this note and coming back to it once you understood the below calculations (but I did not want to move this note to the end).
In the above calculation, one must assume absence of epistasis and dominance effect. I am not exactly sure how this might eventually cancel out later or whether results would then differ. I would welcome a follow-up in the comments to clarify this point but it might be worth its own post. As the question refers to the heritability of intelligence (assuming this term is defined), I would like to highlight that it is unlikely that we have much understanding about the exact pattern of epistasis underlying this trait as measure of epistatic interaction are often difficult to achieve.
Phenotype of O's parent
Let's note $P_P$, the phenotype of one parent of O'. The below notation applies to the mother but calculations would be the same for the father.
$$P_P = X_m + X_m' + e_P$$
, where $X_m'$ is the haplotype of the mother that has NOT been transmitted to the offspring and $e_P$ is the contribution of the environment experienced by the parent (mother).
Covariance between $P_O$ and $P_P$
The covariance between $P_O$ and $P_P$ (noted $cov(P_O, P_P)$ is just the sum of the covariances of all contributions, that is
$$cov(P_O,P_P) = cov(X_m,X_m) + cov(X_m,X_m') + cov(X_m,e_m) + cov(X_P,X_m) +\
 cov(X_P,X_m') + cov(X_P,e_m) + cov(e_O,X_m) + cov(e_O,X_m') + cov(e_O,e_m)$$
I let you take a few minutes to think about the values of each of these covariances.... They are almost all equal to zero (are independent). There are only two covariances that (under a simple model) can potentially be different from 0; $cov(X_m,X_m)$ and $cov(e_O,e_m)$. $cov(e_O,e_m)$ is teh correlation between the environment experienced by the mother and the one experienced by the father. For simplicity, we will make the assumption that these two environments are independent and therefore $cov(e_O,e_m)=0$. The above, long and hairy equation therefore reduces to
$$cov(P_O,P_P) = cov(X_m,X_m) = var(X_m) = \frac{V_A}{2}$$
Correlation between $P_O$ and $P_P$
By definition the correlation (which is the slope of the regression line) is just the covariance divided by the total phenotypic variance. Therefore the correlation between $P_O$ and $P_P$ (noted $cor(P_O,P_P)$) is
$$cor(P_O,P_P) = \frac{V_A}{2} \frac{1}{V_P} = \frac{h^2}{2}$$
Generalization to any correlation
Following the above logic, one can show that in general the correlation between any two individual phenotypes $P_X$ and $P_Y$ is
$$cor(P_X,P_Y) = r h^2$$
, where $r$ is the coefficient of relationship. For parent-offspring $r=\frac{1}{2}$.
Particular case of mid-parent vs offspring relationship
This is just a study case to show that when consdiering a made-up phenotype such as a hypoethetical mid-parent phenotype, then the math are just a little bit more tricky. If you consider the mid-parent phenotype $P_{mid}$, then you must consider that the total phenotypic variance is half the actual phenotypic variance. The correlation therefore becomes
$$cor(P_{mid},P_O) = \frac{cov(P_{mid},P_O)}{\sqrt{\frac{V_P^2}{2}}} = \frac{h^2}{\sqrt{2}}$$
Conclusion
All of the above mean that if you plot the phenotypes of a series of individual pairs, where each pair is related by $r$, then the slope of the regression line is $r h^2$. For example, if you plot the phenotype of the mothers with their offspring, then the slope of the regression is equal to $\frac{h^2}{2}$. If $h^2=0.4$ (which is a typical value of heritability), then the mother-offspring regression will have a slope of $0.2$.

This is a great answer. You could improve it by explaining some of the equations in more detail and give a conclusion in the end.

I can probably make a conclusion from the last paragraph in ** Generalization to any correlation**. Can you tell me exactly what equation would deserve more details you think? Details about the logic behind the equation, the algebra or the underlying mathematical statistics such as the definition of a covariance? Thanks

Maybe conclusion was not the right term. I was pointing in the direction that it would actually make sense to not stop with a correlation equation but give a sentence or two what this verbally means with regard to the question asked. With asking for more detailed explanations I was thinking of the terms 'covariance' and 'correlation' that make sense to statisticians/population geneticists but maybe difficult to grasp for a more general readership. I also corrected a typo in the cor(P_o,P_p) section. Please re-check as I am not an expert in the field. :)

Thanks a lot for the elaborate answer! As Alex observed, things got a bit abstract though, so before I accept could I perhaps ask you to help me work out an example? Say, if h^2=0.6, and we know that both parents are 2 standard deviations above the mean, if I understand things correctly that would make the expected value of the child 0.6*2=1.2 standard deviations above the mean, correct? What about if we have the additional information that all grandparents are 1 standard deviation above the mean? How would the expected value change?


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optimization of density gradient centrifugation
I'm trying to isolate a ~320kD protein (in oligomeric form) using density gradient ultra centrifugation technique.
Can any one tell me that what gradient (sucrose or glycerol or trehalose or etc) I should use and why ?
Any references regarding the optimization of gradient cutoff for macromolecules will be highly appreciated.

Have you tried size exclusion chromatography (SEC)? It's a lot easier to set up, perform, and analyze than gradient centrifugation.

Yes it is. But if you are trying to separate between  240kD and 320kD then it is not proving to be much of a helpful technique as both is coming in void volume in Superdex column. I have tried but not helpful in this scenario.

Have you tried different columns? If your analyte is coming out in the void, try altering the particle size in the column.

Yes, but given the availability of columns it is not being possible to resolve in this range using SEC procedure. That's why I was trying for density ultra centrifugation.

OK, I understand. Unfortunately, the only experience I have with density centrifugation is in purifying white blood cells from whole blood using Ficoll gradients, so I'm afraid I can't help with this. Good luck, though!


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Energy coupling between two spontaneous reactions?

This diagram describes energy coupling between a nonspontaneous reaction (the formation of glutamine from glutamic acid and ammonia) and a spontaneous reaction (the hydrolysis of ATP). I can see that if you add reaction 1 ($\ce{Glu + NH3->Glutamine}$) and reaction 2 (ATP hydrolysis), then the overall ∆G will be negative, and this reaction will be spontaneous.
My question is this: why can’t you add the reverse of reaction 1, which would on its own be spontaneous, to reaction 2? Would that not make an overall ∆G that is even more negative (more spontaneous)? This would be even more favorable than what we got from the energy coupling shown in the diagram. Yet it seems that energy coupling can produce the reaction presented in the diagram. How does the universe know to add the nonspontaneous reaction to the spontaneous reaction rather than the spontaneous reaction to another spontaneous reaction? It seems to me that the latter would be more probable.

Hi lightweaver. Is it you who down voted my answer below? If so, I would be interested to know why. Thank you.

@TheQuark It wasn’t me, sorry.

Points to bear in mind

That the biological coupling of an energetically favourable and unfavourable reaction (I would avoid using the term spontaneous†) is done through a composite reaction involving all the components of the two separate reactions. The reactants and products are the same as in the sum of the separate reactions — so it is valid to calculate the overall free energy change from the separate reactions — but we are talking about a different reaction or serious of reactions that occur on the enzyme. For example in the glutamate synthetase reaction that you mention there are the two reactions shown below. Gamma-glutamyl phosphate can be considered as an activated intermediate to which the free energy of hydrolysis of ATP has been transferred, rather than dissipated in heat, as would occur in the isolated reaction with inorganic phosphate as the product.

Such coupled reactions are no different from non-coupleld thermodynamically favourable reactions in a cell in that they require an enzyme to catalyse them. They do not proceed spontaneously† because there is an activation energy barrier.  If you regard this as “forcing” a reaction, then the answer to the question you pose in your comment to @VonBeche is ‘yes’. However I would describe it as an enzyme having evolved to ‘permit’ or ‘facilitate’ a reaction. It does this by providing binding sites for the substrates and (often) a different reaction pathway that involves a lower activation energy.

So why no reaction Gln + ATP ➞ Glu + NH3 + ADP + Pi ?
This can be regarded in two ways.
(1) Why hasn’t an enzyme evolved to do this sort of thing?
Either there is no selective pressure on an organism for an unneccesary enzyme to evolve, or (in this case) if the organism needs an enzyme to deaminate glutamine one evolves, but this enzyme (glutaminase) doesn’t need to involve ATP as the reaction is already thermodynamically favourable.
(2) Why doesn’t the glutamate synthetase enzyme catalyse this reaction
From your comment, this seems to be your concern. There are three binding sites on the enzyme, one for glutamate, one for ATP and one for ammonia; and I presume you are thinking why can’t glutamine bind to the glutamate site (after all it leaves from there) and react with ATP to form γ-glutamyl phosphate. The answer to this is the chemistry of the reactions shown above. The mechanism of the glutamate synthetase reaction is complex, but at the simplest level the first stage is the nucleophilic attack of the negative acid oxygen (yellow) of glutamate on the γ-phosphate of ATP:

In glutamine there is an amino group instead of the negative oxygen, so the reaction will not occur.
Furthermore, you should be aware that the enzyme is an active participant in the reaction, and the various substrates and products are oriented specifically in relation to residues at the active site of the enzyme to allow the reaction to proceed. To give a flavour of this I reproduce a portion of the summary of a paper by Liaw and Eisenberg on the mechanism of action of glutamine synthetase. I don’t expect you (or anyone else) to digest this — it merely serves to illustrate that enzymes are highly sophisticated machines in which many components participate in producing a specific product.

I still don’t understand how an enzyme can specifically couple two reactions in those fixed directions—the nonspontaneous with the spontaneous ATP hydrolysis. What is it about the enzyme that doesn’t couple the spontaneous reaction with the ATP hydrolysis? Enzymes can recognize both the reactants of a reaction and the products, so what gives it their specificity to couple the formation of γ-glutamyl phosphate from glutamate with the conversion of ATP to ADP, rather than the formation of glutamate from γ-glutamyl phosphate with the conversion of ATP to ADP?

@lightweaver — I've now modified my answer to try to deal with the question you ask in your comment. I didn't include a 3D model of the active site as the answer is already rather long, but I can add one if it will help.

Interesting. I’ve learnt that enzymes can always catalyze reactions in both directions. Sucrase can break down sucrose into glucose and fructose or it can build sucrose from those two. It is a catalyst, after all, and catalysts usually speed up both forward and reverse reactions so as to not alter the equilibrium position of the reaction. Is my conception wrong, then? Your answer seems to indicate that enzymes catalyze only the forward reaction.

@lightweaver  Not at all. Enzymes do catalyse reactions in both directions. But what you are proposing is not the reverse reaction. The reverse reaction is Gln + ADP + Pi ➞ Glu + ATP + NH3, whereas you are asking why Gln + ATP ➞ Glu + NH3 + ADP + Pi does not occur. That is a quite different reaction! (And of course the reason that the true reverse reaction does not occur is thermodynamics — the coupling will ensure that the reverse reaction has a positive deltaG.)

Ahh. I think that was my main source of confusion. Thanks for clearing it up!

Keep in mind that there needs to be an enzyme present to "couple" two reactions. You can imagine it like the energy from the ATP hydrolysis pushing the enzyme to a high energy state, and from that high energy state the enzyme can push the secondary reaction against the equilibrium.
You could do this, and there might even be examples (maybe for some reactions that are just barely exothermic), it's just that enzymes coupling two spontaneous reactions did not evolve that often as there's not much pressure to do that. A spontaneous reaction could just be sped up by a single enzyme, no need to build a big coupling enzyme for that. Coupling this to ATP hydrolysis would just lead to useless energy consumption and extinction.

So it is the enzyme that forces a reaction to occur the way it does?

There is just no point to consider the reverse of reaction 1 if the goal is to synthesize glutamine. The coupling with reaction 2 is just that: to make favourable the synthesis of glutamine from glutamate and ammonia by "encapsulating" it in an overall favourable reaction.
Now, theoretically, nothing prevents in principle that two spontaneous reactions be used concurrently to make spontaneous a 3rd reaction that would require more free energy than each could provide. In "practice" it is probably evolutionary (and mechanistically) easier to obtain a similar result by using a mechanism in two steps (two successive coupled reactions) and by passing through an intermediate (provided such an intermediate can be formed).
A case where two ATP molecules are hydrolysed simultaneously has recently been shown for the dimeric human alcool dehydrogenase enzyme (ADH1A):
Energy transfer along Müller cell intermediate filaments isolated from porcine retina: I. Excitons produced by ADH1A dimers upon simultaneous hydrolysis of two ATP molecules, Igor Khmelinskii  and Vladimir I Makarov, Spectrochim Acta A Mol Biomol Spectrosc. 2021 Apr 5;250:119361.


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How are unnatural amino acids modelled using insilico tools?
When the structure of an unknown protein containing amino acids other than the 20 known natural amino acids is modelled which method is primarily used in bioinformatics to solve the structure? what is the significance of such model obtained??

when you say "unnatural amino acids" do you mean those not found in humans or just non-protein coding, or something else? can you clarify?

You use the words "modelling" and "solve the structure" and refer to "bioinformatics tools" and an "unknown protein" but it's not clear to me what you mean, and I suspect you are not clear either. Presumably you have the sequence of the protein and it contains something like selenocysteine. Are you talking about prediction of the structure de novo from the sequence or trying to impose the sequence on a similar protein of known structure? Why do you think a modified amino acid would cause a problem? You'll have to explain if you want an answer.

An amino acid is an organic molecule containing a carboxylic acid ($-COOH$) group on one end and an amine ($-NH_2$) on the other end. There exist in nature many more amino acids than the 20 proteinogenic α-amino acids. Examples include selenocysteine, pyrrolysine, and carnitine. The structure and character of these are all known, so there would be no difference in the computer model from a "standard" amino acid like threonine. They are not "mysterious" or "unnatural" at all.

In nature we have only 20 amino acids, but there is one more amino acid which is synthesised in laboratory

@Nik did you even read my answer? I defined what an amino acid is in chemistry terms, and provided evidence that there are 20 proteinogenic amino acids, and many more that occur naturally. There is an essentially infinite number of amino acids that can be chemically synthesized, varying the length of the carbon backbone, its structure, and the nature and chirality of the side chain(s).