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Over winding vs under winding of a DNA

DNA supercoiling refers to the over- or under-winding of a DNA strand.

Source : DNA supercoil

When a relaxed DNA is subjected to bends, or openings of DNA, over winding or unwinding, its base pairs per turn changes, and the DNA is subjected to stress and strain.  In order to overcome such distortion, which has rendered the DNA unstable, the DNA twist around itself, like a circular rubber band undergoing twisting, such a twists on its own thread is called Super coiling; it is also referred to as tertiary structure.

Source : DNA Super Coiling
What they mean by over winding and under winding of a DNA ?

Imagine a covalently closed circular double-stranded DNA plasmid. In its "natural", or "relaxed" state you could spread it out, flat, on a suitable surface.
Now imagine cutting one of the strands of the DNA (i.e., cutting the sugar-phosphate backbone, the way that an endonuclease would, leaving a nick, the 5'-end of the nick has the phosphate, and the 3'-end of the nick has an -OH group), and rotating that nicked strand in a clockwise direction, several times, around the other, intact, DNA strand.  This does not involve breaking any of the basepairs, or unravelling the strands, you are just twisting it around.
Now imagine sealing that nick, by ligating the 5' phosphate to the 3' OH.  At this point the dsDNA helix is slightly "overwound", and will no long lie completely flat. It has begun to be supercoiled; these are positive supercoils.
If, alternatively, you had rotated the nicked DNA strand several turns in the counter-clockwise direction before re-sealing it then that molecule would also start to be supercoiled, but it would be "underwound" with negative supercoils (and it would also no longer lie flat on the surface).
There is an enzyme called DNA topoisomerase I that cuts, and re-seals, one of the two strands like this.  Another enzyme called DNA topoisomerase II cuts both strands before introducing supercoils.

There are two types of supercoiling:

Positive (right-handed/overwound) : the double helix is twisted to such an extent that it begins to ‘knot’.
Negative (left-handed/underwound) : this type of coil goes against the natural direction of the double helix structure.

Negative supercoiling is a highly regulated process, performed by specific enzymes such as topoisomerases. There exist two types: topoisomerase I and topoisomerase II. The former relaxes the supercoil whereas the latter increases the extent to which the DNA is supercoiled.
In E. coli, there are at least four different types of topoisomerases responsible for regulating DNA supercoiling.
Source : SUPERCOILING


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Gene configuration : Divergent vs convergent
I start reading a paper where they discuss the effect of the divergent promoter/gene and the convergent promoter/gene on the genetic expression of an organism.
So I want to know what is the difference between the two of them ?

RNA polymerase produces transcripts by scanning along DNA, linearly. Simplifying things, genes can thus be thought of as having a start (or 5' end) which is the main site where the polymerase begins to transcribe, and and end, where it stops. Divergent promoters are promoters oriented so that the polymerase transcribes in opposite directions, away from the two promoters (like so: <- -> ). Convergent promoters instead transcribe towards each other (like so -> <- ) . This means, for instance, that the polymerases coming from two convergent promoters could collide with one another.

source: Stack Exchange

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

sort: votes


text:
DNA topology Linking number vs twist?
Background

Linking number: the linking number represents the number of times that
  each curve winds around the other.
Twist, called "twist", refers to the number of Watson-Crick twists in the
  chromosome when it is not constrained to lie in a plane

 I read these explanations on Wikipedia and I understand the concept of this (supercoils have to form to compensate the "tension" etc..) however I'm not able to discriminate between these terms while looking at a picture.

 (source)

Based on the formula I can easily calculate the twists in the right image. But I'm searching for a way to see/count the twists.

Question
What is the difference between the linking number and the twists (not from a formula perspective)?

This article (DNA Topology: Fundamentals by Mirkin SM) probably defines and describes linking number better than I ever could:

The fundamental topological parameter of a covalently closed circular DNA is called the linking number (Lk). Assume that one DNA strand is the edge of an imaginary surface and count the number of times that the other DNA strand crosses this surface (Figure 3). The algebraic sum of all intersections (which accounts for a sign of every intersection) is the Lk. Two important features of the Lk are evident from Figure 3. First, Lk is always an integer. Second, Lk cannot be changed by any deformation of the DNA strands, i.e. it is topologically invariant. The only way to change Lk is to introduce a break in one or both DNA strands, rotate the two DNA strands relative to each other and seal the break... Another characteristic of a circular DNA is called twist, or Tw. Tw is the total number of helical turns in circular DNA under given conditions. Since DNA is a right handed helix with 10.5 base pairs (bp) per turn, Tw is a large positive number for any natural DNA. Take a planar, circular DNA and try to locally separate the two DNA strands, i.e. to decrease the Tw. Since Lk cannot change, a decrease in Tw will be compensated by several positive writhes of the double helix (Figure 4). Writhing (Wr) is the third important characteristic of circular DNA, describing the spatial pass of the double helix axis, i.e. the shape of the DNA molecule as a whole. Wr can be of any sign, and usually its absolute value is much smaller than that of Tw. The above consideration can be formalized by the following equation: Lk = Tw + Wr. Note, that while Lk is an integer, neither Tw nor Wr should be such. Also, neither Tw nor Wr are topological invariants and their values easily change...

Linking number is simply the number of times one strand of DNA passes over the other. Compare this to:

Twist - the number of helical turns
Writhe - the number of superhelical turns

You can, perhaps, think of twist as the passing over of strands within the helix and writhe as the passing over of strands when the entire helix crosses itself. Both twist and writhe involve strands of DNA passing over the other and so both contribute to the linking number. In the absence of writhe, linking number and twist are equal and both describe the same thing: the number of helical turns. However, in the presence of writhe, twist alone is insufficient to describe the topology of DNA because it doesn't account for the passing of the entire helix over itself.
Since twist is the number of helical turns, actually counting it in your image is not necessarily difficult, just time consuming. The image already has the twists numbered, and I've put a red do at every turn of the double helix. I've also circled, in blue, every point where the double helix passes over itself (writhe):

In that image, in may be difficult to visualize (and even understand!) that the strands only cross over each other 36 times (Lk), even though there are 42 helical turns (Tw). While twist and writhe are different modes of strand crossing, it is important to realize that they are interchangeable without breaking the strands. Let's consider a simpler example, where Lk = -1 (Wikipedia: DNA Supercoil):

In the lower image, the strands do not form a helical structure (Tw = 0) but they do both pass over each other together (Wr = -1). Can you imagine that if you were to "unfold" the superhelix (Wr = 0), the two individual strands would still be linked together in a helical structure (Tw = -1)? Neither could I, so I made a video with my shoelaces:
https://www.youtube.com/watch?v=rI3LWIvptf0

I hope that answers your question. Let me know if I misunderstood what you were asking or if anything needs clarification. You may also find my shoelace video on the topology of helicase-mediated DNA unwinding informative.

Would this: "the two individual strands would still be linked together in a helical structure (Tw = -1)? " mean that  even in the relaxed state of DNA (b DNA) there is a twist of -1? @canadianer

@RickBeeloo I'm not sure I understand your question, but in relaxed DNA with one helical turn, twist would be -1 (or 1).

I have one question: DNA is generally underwound in most cells so this means that the linking number is less than in the relaxed state and we have negative supercoils but what causes the lower linking number as in the relaxed state. I see a lot of videos in which people twist a string to lower the linking number but what is the cause of this in the cell? topoisomerases?

@RickBeeloo Yes, topoisomerases. The reasons for maintaining underwound DNA are transcription and replication, which requires ssDNA, and chromatin structure.

For ds DNA
Twist is the number of times a ss DNA turns around another ss DNA in a helix, i.e. simply the number of turns in the ds DNA helix.
Writhe is the number of time a ds DNA wraps around itself.
From the diagram on the right, Writhe= - 6, you'll find 6 times the DNA crosses itself making 7 loops.
[In negative writhe the upper stand moves from right to left around the lower strand (as in canadianer's diagram) and the opposite is positive writhe]
Linking number is a mathematical parameter, i.e. Tw + Wr which defines the topology of DNA. It is a tool to study the change in the topology of DNA.
Reference and Further Reading: Lehninger Principles of Biochemistry

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Why do chickens continuously lay unfertilized eggs?
As per subject: why do chickens continuously lay eggs even if they are not fertilized?
Is this sort of behaviour found in other species of birds (or other egg-laying animals), or only in chickens? Is it natural, or domestic chickens have been specifically bred for it?
If it's natural, what kind of sense does it make to divert energies and nutrients to continuous lay unfertilized eggs which have no purpose other than being possibly eaten by someone else? How could such a wasteful reproductive behaviour have evolved? Even if it has been specifically selected for in breeding, it still seems to make very little sense in the first place.

I do think much of it is selection, like milk production in Holsteins. Some ducks are also great "layers" (the industry term for fowl that lay a lot of eggs for extended periods.) Not like chickens, but yes. Also guinea hens, quail, and probably a few other birds (but I can only speak to the birds I've raised.)

Chickens are domesticated Red Jungle Fowl. In the wild, Red Jungle Fowl live in flocks with one rooster for every few hens (where "few" is probably less than five in the wild, though in zoos flocks may be larger and have a higher rooster:hen ratio).  Since one rooster can fertilize many hens, in the wild virtually all eggs will be fertilized.  Since jungle fowl, of course, lay far fewer eggs than domestic chickens, the cost of the extremely rare unfertilized egg will be low.
In principle, there could be a molecular mechanism that checked for evidence of fertilization before allowing an egg to be laid, but of course such a mechanism would have its own costs, and would almost never actually be useful.

I find the "in the wild virtually all eggs will be fertilized" argument a good explanation to not even bother checking before laying an egg; however,  I don't really understand the "jungle fowl, of course, lay far fewer eggs than domestic chickens" part. Why is this the case?

At the moment you have no evidence to support your answer and in my opinion make little attempt to answer the question beyond some opinion

Jungle fowl lay fewer eggs than chickens because chickens have been selectively bred for 5000 years to lay many eggs.


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Cause of short sightedness/ far sightedness
I recently had gone for an eye test. The doctor told that short sightedness/ far sightedness is caused due to shrinking or expanding of the eye.
One thing i forgot o ask him was what causes that shrinking/expanding.
Can anyone explain it to me?

This answer explains what's going on in more detail, but I'd be interested to know the causes for the change in size too =)

The physical shape of the eye and lens are as @RoryM points out, the reason we become near/farsighted.
The most common cause of farsightedness is pretty well known.  The lens of the eye allows us to focus as a ring of muscles pulls outward and flattens the lens, allowing it to focus on closer objects.  As we get older the lens of the eye becomes stiffer and inflexible, which means that the muscles that pull on the lens can't flatten it as easily and focusing on nearby objects becomes difficult or impossible.  This is why we need to get bifocals or reading glasses as we are older.
The reasons for nearsightedness are 'natural changes in the shape of the eye'.
Mentioned briefly in the WebMD link above is that close work (e.g. reading, web surfing, phone videos, reading and reading, etc) tends to cause nearsightedness.
25% of adults in the US and 40% of adults in Asia are myopic and it does look as if there is a strong genetic component to myopia.  If neither parents have myopia, the incidence is only about 7%.
I'm probably going to get ding-ed for this, but I am going to offer alternative explanation, which makes good scientific sense to me, so hear me out.
This seems like a poor adaptive phenotype for humans who are otherwise so optimized for survival.  Why would we naturally lose our ability so young (often before the fifth grade)?  So many people who have myopia are so impaired that they can't find their way around their own house (or legally drive) without glasses/contacts/corrective surgery.
This is supported by studies which show that non industrial societies have almost no natural myopia compared to industrialized ones.  This is just one example reference, not a survey of all evidence.
Physiologically the explanation for myopia is this: in the relaxed state, the eye is focused at the horizon (infinity).  If one habitually focuses on a book or screen within 1-2 feet from your face, the muscles might well adapt to a set point that is closer than infinity.  This would make myopia an adaptive response to modern life.
Eye exercises are proposed as a way to correct myopia.  This is a bit controversial - some say they help, others say they do not. I would not be surprised that myopia developed in youth (8-15 y.o.) when the eye and body are developing can't be overcome by eye exercises when you are 25-30, but the jury is still out.
There are enough free descriptions of eye exercises out there that you don't really need to pay for them.  Getting young students outside to look around once in a while doesn't sound like a bad idea either, given this.
If you are going to down vote or complain, I would appreciate it if you please cite counter reasoning other than 'this is not a popular explanation'.

Why is that not a popular explanation? What is the popular explanation?

@Armatus  The popular explanation is that this is a geneticly related condition, which happens as a natural course of events.  Its mentioned in the post, but beyond the genetic studies which assume myopia is genetic, I cannot find much supporting evidence except that this has been the assumed reason for treating children with prescription glasses for hundreds of years (glasses have been produced since the 15th century).  Sorry if this sounds paranoid, but there simply isn't much motivation to support preventive care research at least in the US.


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Can anyone identify this plant from Bangladesh?
I have taken the picture from an agriculture university in Bangladesh.

The genus is Lantana, of Verbenaceae. That particular one could perhaps be L. camara. There's a number of papers that exist which study L. camara in Bangladesh, just some examples:
http://link.springer.com/article/10.1007%2Fs11676-007-0060-6
http://www.banglajol.info/index.php/BJB/article/view/1513


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Hardy-Weinberg Equilibrium Question
I have four questions concerning H-W Equilibrium:
(i) In a population of mice, the presence of black spots is the result of a homozygous recessive condition. If the frequency of the allele for this condition is 0.15, what is the approximate percentage of heterozygous genotypes in this mouse population? (Assume that the population is in Hardy-Weinberg equilibrium.)
I thought this implies that $q=.15$, $p=.85$ and thus the percentage of heterozygous genotypes is $2pq = .255$. Online answers seem to yield a ubiquitous $.72$.
(ii) In a population of giraffes, dark brown spots are the result of a homozygous recessive condition. If the frequency of the allele for this condition is 0.10, what percentage of the individuals in the next generation would be expected to be homozygous dominant?
Is this simply $(1-q)^2 = .81$?
(iii)   In a population of monkeys, the allele that causes long hair at the tip of the tail (H) is dominant, while the allele that causes short hair at the tip of the tail (h) is recessive. If 67% of the monkeys have long hair at the tip of their tails, what is the frequency of the dominant allele?
I worked this as $p^2 + 2pq = .67$, so $q^2 = .33$, so $p = 1-\sqrt{q} = .4255$. Again, this seems to come up on the internet as incorrect.
Moreover, in the below picture:

It seems to me that the answer should be $(1-G)^2 = (1-.45)^2$, but this does not appear as an answer.
Any help appreciated.

In a population of mice, the presence of black spots is the result of a homozygous recessive condition. If the frequency of the allele for this condition is 0.15, what is the approximate percentage of heterozygous genotypes in this mouse population? (Assume that the population is in Hardy-Weinberg equilibrium.)

We know the frequency of the allele (0.15) and we're looking for the frequency of the heterozygotes. $2\cdot 0.15(1-0.15) = 0.255$.

(ii) In a population of giraffes, dark brown spots are the result of a homozygous recessive condition. If the frequency of the allele for this condition is 0.10, what percentage of the individuals in the next generation would be expected to be homozygous dominant?

Yes, you are right it is 0.81

(iii) In a population of monkeys, the allele that causes long hair at the tip of the tail (H) is dominant, while the allele that causes short hair at the tip of the tail (h) is recessive. If 67% of the monkeys have long hair at the tip of their tails, what is the frequency of the dominant allele?

Although the notation is wrong ($p=1-\sqrt{q}$), the result is correct.

[last question]

As both genotypes GG and Gg are grey, we know that $p^2 + 2pq ≈ 0.45$ (Rather looks 0.48 from the figure though), where $p$ is the frequency of the G allele. From that you can calculate $p$ and $q$ and therefore calculate the frequency of the double homozygous gg

For the first one, .385 was not an answer choice.

Ha ha I somehow misread the question. Sorry about that, it is fixed now.


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Is there a reference for the composition of viral genomes?
First of all forgive me for the bad written question.
I'm not a biologist. I'm neither a doctor nor a virologist. I am a physicist actually, and I have this question in mind since a long while.
What I'm trying to ask is if there is a sort of text file or a website (or a book) where I may read about viruses "composition".
"Composition" means something like
"This is the rhinovirus, and it's genetic "composition" is ACTGCT" (of course I just invented...).
I don't know how to express myself with good terms because I am not familiar with this field, so please feel free to edit the question if it may appear unclear.
Again, what I'm asking is for a sort of database of genetic sequences about viruses and so on.
Thanks in advance!

NCBI houses a collection of viral genomes at the aptly named Viral Genomes portal. They currently have 5921 viral genomes and by going to the previous link you can browse sequences from the major viral families.
If you have a nucleic acid or amino acid sequence it can be searched against NCBI's sequences here.
Uniprot also have a viral protein sequence annotation project which they describe as such;

The concept of this website is to associate specific knowledge for each virus family with viral protein and genomic sequences. All the available information is presented in a concise and accessible virus fact sheet, associated with the ordered list of reviewed entries. The site covers the whole known virosphere. The database section allows access to UniProtKB protein entries, as well as to specific virology databases.
Our efforts are currently directed towards viral ontology and reference strain annotation. A robust ontology will allow a more precise definition of the involvement of each protein in viral replication steps. The reference strain annotation will become the benchmark for each of the 334 genera.

Their work can be accessed through uniprot.org or through the project portal at; http://viralzone.expasy.org/

No worries. Uniprot or NCBI provide the sequences as flat files but the people who assemble the viralzone do a great job; their linked cartoons tie function to genes to taxonomic groupings with great clarity.


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Proteome patterns between treated and control cells
We did 4 experiments to compare the amount of certain proteins in treated and untreated cells. Each experiment was done separately. Because of the high cost of experiment, we were able to perform only one pair (one treated and one untreated) sample for each experiment. We want to see which proteins are differentially expressed (minimum 1.5 fold up/down).
First approach: We have compared protein levels of all 4 treated (as a group) with the 4 untreated (as a second group). There is of course variability between all experiments, because of the nature of the cells. We have a list of the proteins that are differentially expressed as a result of the treatment, however this list is not very long.
My question is (second approach): Can we compare the proteins levels pairwise for each experiment (treated vs its respective control) and make 4 corresponding lists, and then compare these four list using a statistical tool and find which proteins are consistently up- or down-regulated? DO you think that these two different approach will generate different lists of the affected proteins?

Welcome to SE Biology. Improving this question will help to attract an answer. Currently the questions are difficult to discern as they are buried amongst lots of text. A brief description of how the measurements have been made will also help. Finally, there are lots of typographical errors that should be corrected.

Can you please describe the experiments or just mention how these are different? Are the 4 controls essentially the same sample? If not then your first approach would be incorrect.

From what I understood, and thus based my answer on, the four treated and the four untreated samples are the same, but each pair of treated and untreated samples was done at different occasions.

If I understand you did a treatment to some cells and compared them with non-treated ones. Instead of running the four experiments at the same time, you did one treated and one untreated at a time. Then you did proteomics for each sample. Is the treatment the same in all four experiments?
Edit after the further comments of the OP: So, since the four treated samples are the same and the four untreated also (same conditions except from the treatment and the treatment is the same), then the way to go is as what your collaborator did.
Identification and quantification of the detected proteins is one thing and every sample of the four are replicates. Comparison between the two conditions is another thing.
The software he uses for ID can combine the same samples and already perform the statistical analysis, so the list you have now has higher credibility in terms of the proteins it includes and their levels for your cells when they are treated or not.
Using only one of your replicates, although it might give you different number of detected proteins or different amounts of each, has lower credibility, because it's only one sample out of four. In plain words, the presence or absence or the amount of a protein might be an artifact or insignificant.
What has to be clear is that the comparison between treated and untreated conditions is done after you have received the statistically correct list of detected proteins.
Thus, and in accordance to what I had said before the edit, if you take the list for each treated sample and compare them with any of the lists of the untreated ones, it will lead to conclusions that won't be as statistically significant as when you combine all treated together and all untreated together (as your colleague did). In plain words, your conclusions will have a higher chance to be wrong.
Every statistical analysis you do yourself for each sample should eventually lead to a similar consensus as your colleague got using the statistical analysis of his software.
As a sidenote, considering how many types of proteins are in a cell, now that you have a quite short list might not be a bad thing at all and you can proceed by:

Concluding that the treatment had minor effect in the proteins that you expected it would affect (if they are not present in your lists as significant different)
Trying to understand, identify and hypothesize on the role of the proteins that made it in your comparison threshold, as they have a much higher probability of being indeed different between the two conditions.

Splitting the samples in your analysis might have a point if the conditions of the experiment were not exactly the same or the treatment level is different etc. In that case you could split the samples accordingly, but that would definitely reduce your certainty level for your conclusions.

Thank you for your reply.
It was impossible to do 4 replicates at the same time. Technically impossible. Therefore, we did 4 different experiments where we treated cells and we had an untreated control.

Usually, we did proteomics for each experiment separately. Well, because we wanted to know our results ASAP. However, last time, we gave our samples - 4 pairs (i.e., 4 separate experiments of treated vs. untreated) to our collaborator who performs proteomics for us. He is doing HPLC - QqOrbitrap analyses for us.

He always did the comparison between pairs of treated vs, the corresponding untreated, but last time when we gave him our 4 sets (4 pairs) he did something different, without our consideration - he somehow compared these samples as a two groups (this his explication), and thus he cannot extract the data for separate pairs (individual experiments).

He wrote: "Fold changes are computed with all replicates and compared statistically. Extracting the data for individual replicate would decrease the ID power. Also, I would have to reprocess all the data files." When we insisted that we would like to have the list of the identified proteins that are up- or down-regulated for each experiment, he said that this is too difficult because of the way how he set up the software for this analyses, and that will take several months.

My concern is that the "cumulative" list of the proteins that we have now because of this unexpected way of the performed analysis (two groups vs. 4 sets of treated and untreated) is much shorter. I am wondering if we perform the 4 pairwise proteomic comparisons and then will apply statistical tools  - can we expect a much longer list of the identified affected proteins or no? Thank you for sharing with me your expert opinion.

The comparison is a different step to the identification and the quantification of the proteins present. The more samples, the more certain you are that indeed these proteins are there. After you have a higher confidence on the proteins present, then you move to the comparison of your high confidence results. If you compare everything pairwise, then your results and later your comparison will not be as confident as in the other case. But the statistics are applied to the proteins detected and when the confidence is high, then you can compare them


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Factors for sensitivity to electric shock
I'm frequently getting electric shocks in my office when touching things. I basically know why this happens and how to avoid it.
Still I started to wonder what would be the best way to touch something if you knew you will be shocked. I know that fingertips have more nerve endings but I guess they also have more callus. What are factors for sensitivity to electric shock and what part of the hand is therefore the least unpleasant to be shocked?

Practical advice: Take a metal thing (pen, key, etc.) in your hand and ground yourself over it. Then the current will flow through the metal and not hurt you.

I've built a lot of electric fence in my youth. If you MUST touch an electric fence, use the back of your hand, so if you get shocked you'll pull away instead of grab on. Also, a leather wallet makes a decent insulator to push down on a wire so you can step over. To this day I can't touch a wire without testing it first even if I know it's cold. Don't know if these tips apply to your job, I haven't seen an office building with electric fence.

@user137 the problem is static charge. Maybe it's the carpet or something. So it has nothing to do with touching things that actually carry an electric current.

@AndréStannek Can you put a humidifier in your office? The humidity will help dissipate static charges.

@user137 it's in the office of a customer so no big influence on anything there. To avoid long discussions in the comments I'd like to point out that this is not what my question is about. Of course I still appreciate your concern and help :-)

The dorsum of your hand is less sensitive than the palmar surface. It's hard to touch or pick up things with the dorsum of your hand, though.

I synced the title and body and made some additional changes to make the question more clear. Please feel free to roll back if it is not to your liking.

Inspired by this study on bee sting pain, you could do your own study involving electric shock. This piezo electric lighter claims to deliver 10,000V shocks at safe currents, and if you do the experiments on just yourself you usually don't need approval for human subjects.

@ChrisStronks I changed the title again because that's the part of the question I'd like to emphasize. Otherwise your edit is fine, thanks!

@user137 that would answer the second part of my question. Still I'd like to know the reasons. Does it only rely on the number of nerves or are there other factors? See my last comment for the emphases of my question.

@AndréStannek This may be a nobody knows (for now) question. I would certainly be curious if there is research on this and more so why said research was carried out! Who would fund this? The only electric-pain experiment that springs to mind is the (in)famous Milgram experiment. This still doesn't even begin to answer your question.

authors: хиханьки - хаханьки


text:
Which of these components has C-H and COOH groups
A) Amino acids and triglycerides that have a carbon-carbon double bond
or
B) proteins and fatty acids
I think they are both true, but I should choose only one
I think that because since amino acids have COOH and C-H group, proteins do too and fatty acids have these groups too just like triglycerides with a double bond. But since I have to choose one I would choose B. Am I right?

This is a homework question and off-topic unless you show some effort to solve it yourself.

I tried to edit the question to correct the spelling and chemistry terms. Please look over the edit and make sure I didn't change your meaning. Still a homework question though, and you should add your reasoning for believing both are true.

Answer A is wrong because triglycerides are esters not carboxylic acids so they have -COOR group, not -COOH. Amino acids and fatty acids have -COOH groups and proteins too - on C-termini and in side chains.

And some amino acids will have COOH on their side chains, adding to the number of COOH groups on the protein, but this depends on the particular protein sequence.

Yes, of course.


text:
What's the difference between an embryo and a fetus?
The most I've been able to come up with is that fetuses are embryos slightly farther along in their development. Is that correct?

Yes, you are correct. You can read the wikipedia article about an embryo:

An embryo is a multicellular diploid eukaryote in its earliest stage of development, from the >time of first cell division until birth, hatching, or germination. In humans, it is called an >embryo until about eight weeks after fertilization (i.e. ten weeks after the last menstrual >period or LMP), and from then it is instead called a fetus.


text:
What determines the amount of data you would get from a sequencing experiment?
When someone performs a sequencing experiment, what determines how much sequencing data you get from the machine (Illumina, PacBio, Nanopore, etc). Or maybe, put differently, how does the machine know that it is done?

On an Illumina machine, the instrument runs as many cycles as you tell it to.  If you tell it to run 150 cycles, you will get 150-mers as output.

Thanks for this, that explains read-length to an extent but what explains sequencing depth?

Having more reads for your sample, which you get by giving your sample a higher % of the space on the flow cell.


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What's keeping living species from rotting?
Why do only corpses of species rot and be eaten by bacteria? What is keeping us from rotting?
Just like fruits, and foods we eat; meat and vegetables rot when left uneaten. Like food, corpses rot and get eaten by maggots. Why?
Why don't these apply to living species?

One can calculate that there are more non-human cells (mainly bacteria) inside human body than there are actual human cells. Why those bacteria don't eat us from within? Epithelium is pretty good barrier between outer world and internal systems. It is essentially one-cell thick layer that protects internal organs and infrastructure. In cases when epithelium breaks, bacteria can get into blood stream and start very bad infection, which can cause necrosis (effectively, rotting, tissue decay). Natural cell death is fought by natural cell proliferation so that there are no gaps in defense layers.
Also one should not forget about immune system that is looking for invaders or anything that should be where it is. In healthy person immune response will close gaps in epithelium and kill bacterial infections pretty quick.
Dead people, as well as dead plants, have their skin and epithelium, immune system destroyed by cell death or infection. Then bugs start to eat vessels, tasty nerve tissues, muscle and cartilages, blood cells filled with proteins and everything eatable.

What's rotting mean?
The stages of rotting or decomposition are Fresh, Bloat, Active decay, Advanced decay and Dry/remains.
Fresh decomposition is first and is typically required before the other stages. It is caused by failure to remove carbon dioxide (which makes things acidic) and provide oxygen to tissues (because the hearts stopped for example). There's lots of bacteria in us but they're kept in check by our immune system and also the presence of oxygen (a lot of them are anaerobes which dislike too much oxygen). They start eating are carbohydrates, fats, protein and making chemicals such as acids, gases like methane and ammonia. Multiplication of these bacteria and continued production is called putrefaction and leads to the next stages.
So in summary it's the cell barriers, the oxygen and the immune system stopping this first stage from happening (which let's the next insect stages occur).
Rotting in living organisms
Sometimes this can happen in living organisms such as in gangrene where parts of the body (typically the toes or fingers) aren't getting oxygen and then rotting can occur in a living organism. It's a great idea to then chop off the affected part before these bacteria eat into a blood vessel and spread throughout the body.


text:
What are the trade-offs between polymerase chain reaction (PCR) vs Loop-mediated isothermal amplification (LAMP)?
I've heard that LAMP could be a good alternative to PCR for DNA strand amplification and detection because the equipment required is cheaper, more portable, and the amplification is faster since all happens at a single temperature.
Since this system has clear advantages, I'm curious what are the downsides that prevent it from completely overtaking PCR/qPCR?
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862059/ mentions some disadvantages:

However, this technique has some limitations. Complexity of multiple primers’ designs for multiplication of new gene regions and selecting the suitable regions in the gene sequence for efficient design of primers, complicated product having cauliflower-like structures with different sizes, lack of commercial kits based on LAMP technique and complexity of this method mechanism are some of its drawbacks limiting its popularity among the researchers; and it not as common as PCR-based method.

but they just don't seem that important compared to the large benefits for diagnostic usage.
For example, from this video https://www.youtube.com/watch?v=L5zi2P4lggw I understand that more primers are needed, but is it that hard to "just create a few more primers"? Aren't those just deterministically determined from the target DNA of interest in this  case?
I can see why the cauliflower structures matter for certain applications, e.g. I guess those messy strands are not going to go through an Oxford Nanopore pore for sequencing, but do they matter when we just want to know if the DNA of interest is present or not?
Related articles:

https://www.researchgate.net/post/What_is_the_difference_between_a_PCR-RT_and_loop-mediated_isothermal_amplification_LAMP
https://www.ncbi.nlm.nih.gov/pubmed/22051073

I later learnt that there are other isothermal amplification amplification schemes out there as well, maybe  I knew about those I would have asked a more generic isothermal question:

RPA
which is apparently used in Abbot ID NOW system according to this and is being used for Covid-19 diagnostics.
HDA
NASBA
NEAR
Strand Displacement Amplification

Having to use more primers is definitely one of the big reasons. Primer design is difficult and time-consuming, and even more so if you're dealing with similar targets. For instance, if you're trying to differentiate closely related bacterial strains, having to design primers for 6 or 8 regions instead of just two is going to lower your ability to differentiate the strains. It's even worse if you're working with viruses - these mutate quickly and therefore your LAMP primers will fail to amplify the virus sooner than normal PCR primers.
LAMP is good because it's cheap and portable, but there are portable PCR thermocyclers starting to be produced (eg. miniPCR, Biomeme) and so diagnostically speaking, it's a lot easier to just use existing PCR primers that have been validated and are widely used, instead of creating new primers that you'll have to validate all over again.
The primers again are important if you're trying to amplify multiple targets - it's a lot easier to create degenerate or consensus primers for a standard PCR than it is for LAMP, and also easier to distinguish multiple target bands on a gel, which isn't possible for LAMP.
It can vary, but in my personal experience, I have always found Taqman-based PCR to be more sensitive than LAMP. You can't use Taqman probes with LAMP. You also can't use LAMP for cloning, and melt-curve analysis isn't possible with LAMP, which is useful for detecting primer dimers and diagnostically for distinguishing between targets.
So, LAMP is good because it's cheap, requires less equipment, can be done in the field with minimal reagents, and tends to be more robust than PCR as it is less prone to be affected by inhibitors. This means it is great for in-field diagnostics in developing regions. But there is a range of things PCR can do that LAMP can't, and the complex primer design alone will prevent it from overtaking PCR.

Nice answer teaelleceecee.  Conventional PCR primers ultimately misfire against a mismatched exclusive target especially if it is at high copy #.  Multiply exclusive mismatched LAMP primers won't do that. True that viral mutations may stop such a LAMP assay.  Design in conserved sequence may help with this. Microfluidic systems will allow for "multiplexing" using geographic separation, which could allow for multiple amplimers to overcome the former challenge.  There are tricks to achieving single copy LAMP.  PCR suffers from inhibitor retarded polymerase being slowed down such that it doesn't reach the opposing primer site before denaturation.  In LAMP, there is no denaturation step, which mostly explains its robustness to inhibition.

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


text:
Are vertebrate wings and fins considered vertebrate limbs?
I have come across many articles which seem to suggest (but do not explicitly state) that limbs refer to arms and legs. My confusion stems from the fact that does the term vertebrate limb also include vertebrate wings and vertebrate fins or only refer to arms and legs of vertebrates. I would be grateful for clarification.
A simple google definition states that it does include the wings of birds however I would like to know if this is also the case in evolutionary biology or not.
I also refer you to this article
Yano, T., & Tamura, K. (2013). The making of differences between fins and limbs. Journal of Anatomy, 222(1), 100–113.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3552418/
Are vertebrate wings and fins considered vertebrate limbs?
Based on other articles I have read wings are included in the definition of limbs but I am not sure whether fins are included.

There is no alternative definition of "limb" in evolutionary biology. Legs, arms, wings and fins are all limbs. Note that a prehensile tail can also be called a limb. From wikipedia > limb

A limb (from the Old English lim), or extremity, is a jointed, or prehensile (as octopus arms or new world monkey tails), appendage of the human or other animal body.

You can have a look at Cohn et al. (1997), where the term limb is used to refer to legs, arms, wings and fins.
Apparently some authors (as OP has shown examples in the comments) use the term differently. I think it is always made clear so as to not yield to any possible confusion. If you've ever been confused, you might want to let us know which article got you confused.

This article seems to suggest otherwise: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2408990/ . The title clearly implies that fins and limbs are different

It is a book review, not a peer reviewed article. This book review indeed uses the term differently. I think it should not yield to confusion about the meaning of what is said or does it? If anyone use the term differently (as it si the case in this book review), hopefully it should be clear enough as to not yield to any possible confusion. If you've ever been confused, you might want to let us know which article got you confused.

https://www.nature.com/nature/journal/v466/n7303/pdf/nature09137.pdf This article again implies that there's a difference between fins and limbs. Zhang et al. (2010) Loss of fish actinotrichia proteins and the fin-to-limb
transition. doi:10.1038/nature09137

Remi is right, authors are free to use limb how they please. Note nature articles are prone to imprecise language becasue they are written with a wider audience in mind. In the last case the author is using limb as short hand becasue writing "non-fin limb" each time starts to get grammatically messy.

In the article you link, they are clearly using the term 'limb' as excluding fins. It looks like the expression limb-to-fins is quite leading many authors to exclude fins from the term of limbs. I don't think this yield to any confusion though, does it? You will just have to accept that different authors may use different definitions

Thank you for your clarification. So basically the term limb in an article is that as defined by the article but in a broader view of the term in biology outside a specific article it includes fins?


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Is there a relationship between efficiency of cellular metabolism and warm-blooded-ness?
My BIO 101 book states that when human cells convert glucose to ATP, the process is only approx 35% efficient, and much of the potential energy is lost as heat.  However, that heat is useful to us in maintaining our overall body temperature.
Cold-blooded animals (reptiles, for example) are not as effective at maintaining their own body temperature.  Does that imply that their cellular metabolism (conversion of glucose to ATP) is more efficient than humans, and thus doesn't produce as much heat?
Or is cold-blooded- / warm-blooded-ness completely unrelated to heat released during cellular metabolism?

As far as I know the difference is not in the efficiency but rather the simple amount of catabolism of nutrients. Cold-blooded animals ingest less but also burn much less and generally expend less as well. I'm not entirely sure about this though. The central metabolic pathways are pretty much the same in most animals.

While heat is lost during glycolysis, a lot more heat can be lost during chemiosmosis.  This is the movement of H+ (protons) across the inner mitochondrial membrane.  The energy potential of having a greater concentration of H+ on one side of the membrane usually powers ATP synthesis through ATP synthase.  In mammals, however, special proteins called uncoupling proteins (UCPs) can make the membrane 'leaky' to H+, so the energy is lost as heat, instead of being used to make ATP.  This is called non-shivering thermogenesis, and usually happens in brown adipose tissue (because fatty acids are used to enable UCP production).
It is not that glycolysis in ectotherms is less efficient (as far as I'm aware), but that ectotherms have different levels of different types of UCPs. Some UCP genes may have their expression altered in response to colder conditions (e.g. UCP2 and 3 may be upregulated) or the genes may not be present at all (e.g. UCP1 is not present in birds and crocodiles).
A better summary of UCPs in reptiles etc. can be found in this abstract:
http://rspb.royalsocietypublishing.org/content/275/1637/979.long


text:
Why do males have more birth defects?
I taught in elementary school for 20 years and noticed that males were far more likely to be classified as handicapped than females.
More males than females die at birth and are more likely to have birth defects. Why?

Do you have a reference that supports these claims?

I guess you mean "taught" elementary school. I am taking the liberty to edit that. However, you have to provide or cite a well documented data for making such a claim.

Welcome to Biology.SE Wendy.
Issue in your post
There are a few issues in your post.

You made a personal observation that males tend to more often be diagnosed with a handicap than females (in frequency). You probably did not keep track of the numbers and you probably did not make any statistical analysis. So there is really no reason to trust this observation. The idea that males are more often classified as handicapped than females is opinion-based for the moment and you will need a reference for this before asking why it is true.
You also claim that most birth defects occur in males and not in females. You should also include a reference.
You are talking about gender difference in "handicap frequency" and "birth defect frequency". It is a little unclear what the question (your last sentence Why) refers to. Maybe both. In such case, why would you expect that a common mechanism explains both observations? You should probably restrict your question to one or the other only.

For these above reasons, the question cannot be correctly answered in its above form. But below is something that may already help you.
Birth defects
It is true that birth defects is more prevalent among males than among females (in humans). According to Lary and Paulozzi 2001:

The overall prevalence of major defects at birth was 3.9% among males and 2.8% among females.

Reading their abstract only, one can see that they go on saying

Defects of the sex organs were eight and one-half times more prevalent among males and accounted for about half of the increased risk of birth defects among males relative to females. Urinary tract defects were 62% more prevalent among males, and gastrointestinal tract defects were 55% more prevalent among males.

In consequence, it seems at first sight that the difference in birth defects frequency is very much related to the development of sex organs. In their abstract they announce that they discuss the mechanisms that account for such difference.
I currently don't have access to the paper (I am not on campus) to report more details of their findings.

Although this isn't the determining factor in why males have more birth defects but it should be noted that the the fact males have only one X chromosome means they are very susceptible to X-linked recessive diseases.
As females receive two X chromosomes the chance of them obtaining an X-linked recessive disease is reduced significantly.
(And not all X-linked diseases produce cognitive impairment in individuals but if you sift through all the X-linked diseases it is easy to see the relationship.)


text:
What is violet color?

We have 3 color receptors in our eye, so assuming the above picture is precise we are checking for 3 wavelengths: 450nm, 540nm and 700nm.
Pink for example has an RGB value of

R (700nm): 1
G (540nm): 0
B (450nm): 1

Violet has an RGB value of

R (700nm): 0.5
G (540nm): 0
B (450nm): 1

However Violet has a wavelength of 400nm which is lower than the Blue receptor. So how can it activate the red receptor when red is clearly not active at that frequency?
Does that mean Ultraviolet appears blue to the human eye? Why is it constantly painted as violet in all frequency graphs?

The question was first duscissed here (https://physics.stackexchange.com/questions/486560/what-frequency-is-pink-color) but did not receive the answer I need.

related question. https://biology.stackexchange.com/questions/51870/can-red-cone-cells-actually-see-much-red-light

Ever see a rainbow, or sunlight that's passed through a prism?  The high-frequency end of the visible spectrum is painted as violet because that's what it looks like.

this is a chart of the light activation of the light sensitive cells in the human eye.

see that little blip up on the tail end of the red cone, that minor ranges means the extreme blue end of the spectrum activates blue cones but also has a chance to activate red cones. That is why you can sometimes see magenta tinges in bluest of blue light. There is also a sensitive issue as blue cones are the least sensitive of our cones so it requires a stronger blue light source to activate it than the equivalent light on other cones, since red is more sensitive a strong blue and a weak red source will blend to about equal as far as our eyes are concerned so at the bluest end of the spectrum, where the blue activation is at its weakest it does not take much to activate the blue and red "blip" equally meaning all sources at that extreme end blend into magenta.
Also magenta itself is not actually part of the spectrum, it can be produced in two ways, the first I discussed above, hitting the far end of that little blip perfectly. The second and most common requires light from two disparate and different parts of the spectrum in other words not a single wavelength. It is blue light and red light without green light, it is not a real color but an artifact of how our eyes see light. Your cones can't tell how they are activated just that they are. Yellow and cyan (and every other common human color)on the other hand can be produced by a single wavelength, which may or may not activate multiple types of cones.
You can find more information here

Really impressed by the straightforwardness of the linked article. I quote Einstein here "If you can't explain it simply, you don't know it well enough" Thanks for that!! Fascinating!!!

This is incorrect. There's no bump in the sensitivity of the L cones. This misconception arose from a bump in the X function of the CIEXYZ colour space. But X, Y and Z were never meant to correspond to cone sensitivities.

@OscarCunningham I see... can you edit the answer or write a new one? I am in no position to do so.

So what is the answer to this then? I have never seen that activation spectrum from any other source. If there isn't that hump in the red cone's spectrum, then it seems the OP's question remains unanswered.

@joel then you need to look a little harder, here is 2 in five minutes. https://webvision.med.utah.edu/book/part-vii-color-vision/color-vision/27/ and https://link.springer.com/chapter/10.1007/978-1-59745-374-5_14

@John, if I had University access to Springer, I wouldn't be looking for answers on StackExchange, and I still don't see that chart you posted in the first link you gave. It looks like you got it from Wikipedia's article on the CIEXYZ color space, so I would encourage you to read Oscar Cunnigham's comment above, as X, Y, and Z don't correspond to cone sensitivities.

@OscarCunningham, which is why I am using the ones that ARE based on the cone sensitivity. https://en.wikipedia.org/wiki/LMS_color_space CIExyz is not the only way to define a color space, and is not a great one for talking about the actual biological effects, while the CIE LMS is not very useful for technological uses. they have diffrent uses, I am talking about the biological effect. I do see the confusion I used the rgb terminology when I should have used the LMS.

@JoelCroteau if you want a detailed description of how human color vision works you can ask for that, it complex because there are both excitation and inhibitory aspects to color vision. The first link https://webvision.med.utah.edu/book/part-vii-color-vision/color-vision/ is very good for it. scroll down to fig 14 you will see where the chart comes from.

@John Figure 14 is not the same chart as what you posted in your answer. It doesn't show the same structure, with a pronounced hump on L cones (which you call H cones) and only on L cones. Did you make your own version?

@JoelCroteau oh you want the exact source, after 5 years I have no idea what the source for that exact image is, but you can find simliar ones everywhere such as https://www.researchgate.net/figure/left-Cone-spectral-sensitivity-functions-for-an-average-normal-trichromat-after-Smith_fig2_38015459 and http://www.cvrl.org/gallery/Cmfs-cones.htm  they are just linear transformations to produce diffrent ways of visualizing the same data.

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


text:
If one of eyes is blind, can that eye still feel pain?
I was wondering this when I touched my bare eye (my eye was open) and since I'm not blind I was wondering if an eye is blind, can it still feel pain?

Blindness can be due to a damage of the lens, retina, optic nerve or the visual area at the occipital lobe of the brain, for example.
Sensitivity of the eye cornea is enabled by a different nerve - the ophthalmic nerve, which is a branch of the trigeminal nerve (Yale Journal of Biology and Medicine). As long as this nerve, somatosensory cortex at the parietal lobe of the brain and other neural structures involved in pain sensation are intact, you should be able to feel pain when touching the cornea of the blind eye.


text:
How to annotate a .broadpeak file with 9 columns?
I have this peak file I retrieved from an ENCODE chip-seq matrix. Its .broadpeak file looks like this:
chr22   16096195    16096367    .   517 .   8.245591    1.4 -1
chr22   16191942    16192481    .   374 .   4.452878    1.7 -1
chr22   16192350    16192560    .   480 .   7.273034    1.3 -1
chr22   16848326    16848437    .   687 .   12.776952   3.4 -1
chr22   16849900    16851299    .   374 .   4.444921    12.8    -1
chr22   16851301    16851828    .   394 .   4.968297    3.2 -1
chr22   16852259    16852459    .   514 .   8.182164    2.4 -1
chr22   16853163    16855156    .   328 .   3.229621    7.6 -1
chr22   16856415    16857273    .   374 .   4.450283    5.9 -1
chr22   16857361    16857946    .   375 .   4.475713    2.4 -1
chr22   16857760    16857903    .   637 .   11.443585   4.2 -1
chr22   16858449    16858683    .   645 .   11.655504   11.1    -1
chr22   16860284    16860823    .   382 .   4.655282    2.4 -1
chr22   16861104    16862410    .   370 .   4.343772    10.8    -1
chr22   16928019    16928525    .   385 .   4.743283    2.2 -1
chr22   16928388    16928554    .   602 .   10.515230   4.4 -1
chr22   17066663    17067190    .   487 .   7.452445    12.6    -1
chr22   17076317    17076417    .   699 .   13.091462   2.8 -1
chr22   17079512    17087549    .   1000    .   29.157293   13.6    -1
chr22   17105156    17105287    .   582 .   9.993482    1.6 -1
chr22   17162805    17163461    .   763 .   14.801068   100.0   -1
chr22   17198501    17199415    .   615 .   10.861807   15.1    -1
chr22   17228872    17229131    .   713 .   13.478983   15.7    -1
chr22   17229147    17229434    .   621 .   11.023589   13.2    -1

I want to make the annotation and have the entrez ids for the nearest genes. I'm new to this I keep trying some tools but nothing seems to work. I used peakanalyzer a lot but it keeps saying that this file is missing columns it needs to be 12 column file but I don't know how to do it. If I add more columns would that change the annotation.

Have a look at the GTF/GFF3 format which are standard formats for genome annotation. You can find proximal genes by mapping these peak locations to the genome GTF file. If you are specifically interested in using peakfinder then I would suggest that you read the manual carefully for what the input format is supposed to be like.

i have read the manual of peakanalyzer i need a bed file with 12 columns although thw first 3 are needed for the annotation. I cant find a way to convert the file i have in another format so i can use it .

This is what the columns of broadPeak format mean (from UCSC):

chrom - Name of the chromosome (or contig, scaffold, etc.).
chromStart - The starting position of the feature in the chromosome    or scaffold. The first base in a chromosome is numbered 0.
chromEnd - The ending position of the feature in the chromosome or   scaffold. The chromEnd base is not included in the display of the    feature. For example, the first 100 bases of a chromosome are defined
  as chromStart=0, chromEnd=100, and span the bases numbered 0-99. If
  all scores were '0' when the data were submitted to the DCC, the DCC
  assigned scores 1-1000 based on signal value. Ideally the average  signalValue per base spread is between 100-1000.
name - Name given to a region (preferably unique). Use '.' if no name is assigned.
score - Indicates how dark the peak will be displayed in the browser (0-1000).
strand - +/- to denote strand or orientation (whenever applicable).    Use '.' if no orientation is assigned.
signalValue - Measurement of overall (usually, average) enrichment for the region.
pValue - Measurement of statistical significance (-log10). Use -1 if    no pValue is assigned.
qValue - Measurement of statistical significance using false    discovery rate (-log10). Use -1 if no qValue is assigned.

And this is how the BED format looks like (from UCSC):

chrom - The name of the chromosome (e.g. chr3, chrY, chr2_random) or    scaffold (e.g. scaffold10671)
chromStart - The starting position of the feature in the chromosome    or scaffold. The first base in a chromosome is numbered 0.
chromEnd - The ending position of the feature in the chromosome or    scaffold. The chromEnd base is not included in the display of the feature. For example, the first 100 bases of a chromosome are defined
  as chromStart=0, chromEnd=100, and span the bases numbered 0-99.
name - Defines the name of the BED line. This label is displayed to    the left of the BED line in the Genome Browser window when the track is open to full display mode or directly to the left of the item in pack mode.
score - A score between 0 and 1000. If the track line useScore attribute is set to 1 for this annotation data set, the score value will determine the level of gray in which this feature is displayed (higher numbers = darker gray).
strand - Defines the strand - either '+' or '-'.
thickStart - The starting position at which the feature is drawn    thickly (for example, the start codon in gene displays). When there is no thick part, thickStart and thickEnd are usually set to the chromStart position.
thickEnd - The ending position at which the feature is drawn thickly    (for example, the stop codon in gene displays).
itemRgb - An RGB value of the form R,G,B (e.g. 255,0,0). If the track    line itemRgb attribute is set to "On", this RBG value will
  determine    the display color of the data contained in this BED line.
  NOTE: It is    recommended that a simple color scheme (eight colors or
  less) be used    with this attribute to avoid overwhelming the color
  resources of the    Genome Browser and your Internet browser.
blockCount - The number of blocks (exons) in the BED line.
blockSizes - A comma-separated list of the block sizes. The number of items in this list should correspond to blockCount.
blockStarts - A comma-separated list of block starts. All of the blockStart positions should be calculated relative to chromStart. The number of items in this list should correspond to blockCount.

So, first six columns are basically the same. The 7th and 8th column of your new BED file should be same as 3rd and 4th columns respectively. Since columns 4-12 are actually optional for a BED file you need not actually fill the rest of the columns. In any case blockCount would be zero for your case. RGB value is also not necessary. However, if whatever software you are using is asking for a 12 column file then set these:

itemRGB (column 9) = 0,0,0 (black)
blockCount (column 10) = 0

You can use whitespace in rest of the two columns.
You can easily use any scripting language to do this. I am not going to explain how to do that because that is off-topic here.

How to find nearest genes without using Peakanalyzer?

Download the GENCODE annotation GTF file and decompress it.
Read the broadPeak file and store the locations of the peaks.
Define what the minimum level of proximity is (for e.g. 2kbp up/downstream)
Parse only those lines of the GTF where the third column="gene"
Subtract the downstream window to start and add the upstream window to stop position of the gene. Columns 4 and 5 respectively.
Gene information is stored in 9th column.
If the stored peak position falls within the modified start/stop positions then print the 9th column.

Again, this is has to be done programmatically. It is not very difficult. To explain how to do that is off-topic in this forum. I explained the algorithm which you can implement in your favourite scripting language.

Thanks a lot for your answer i have found a way to make the .broadPeak file(6+3 bed file) to a 6 bed file that was accepted by the peak analyzer with this command in cmd
cut –f-6 total_pooled.broadPeak > final.bed i dont know if the genes are correct i assumed that they are because i read somewhere that to annotate and find the nearest genes you need only the first three columns of my .broadpeak file? The second solution seems interesting i  will look it and try to implement it in R after i solve some other more important issues with the ENCODE API.

@XanthoulaAtsalaki awk is a very nice scripting language for these kind of jobs. For something like printing selected columns it is as easy as awk -F "<column separator>" '{print $i, $j, $k}' inputfile > outputfile (where i, j & k are column numbers).

thanksss a lot for the precious informations you are giving me really you are so helpful , i just started to study bioinformatics and R for a master. i want to find a subject for a doctoral i want to try in this field, im so confused i keep reading and reading and there are so many tools and software and papers in this field i feel constanlty like a first grade student  . I will look into this scripting language definitely. Thanks from my heart for your time and the information.


text:
What is this insect that showed up after I left food out? How can I get rid of it?
These bugs showed up after I left some food out. I noticed a significant reduction after I cleaned up my place, but now they're back again. They're pretty small, but can you guys help me identify these bugs. I need to look up how to get rid of them.
I live in the Midwest.
I realize the quality is not the best.

What kind of food was it?

It looks like it could be some type of fruit fly.  Without clearer pictures it would be difficult to say what kind.

I don't recall, it was a long time ago. It seems to like my trash can very much.

@Kurt Uploaded a clearer pic

It is likely a fruit fly, a Drosophila melanogaster.

I've tried different methods to trap then but the most effective way I found is this. You need a container (pan, jar, bowl, whatever), vinegar (I use any type), a drop of dish soap, and plastic wrap over the top with holes poked in. Then the flies cannot stand on top of the liquid but also have issues escaping through the holes in the plastic wrap.

If it looks like the picture below it is some sort of fruit fly.  I've also attached a link telling how to get rid of them.


text:
Can proteins structure change depending of alimentation of an organism?
In my understanding protein are built using information caring by RNA. So a given protein should always have the same structure in a given organism has the DNA of this organism does not change.
I'm asking this question because peoples told me that "cow milk protein become longer because how we feed them today". But I don't understand how a protein can become longer or shorter.
Info: I have no background in biology. I do not try to solve a problem, but simply have a better understanding.

Hi gagarine, to me, for this question to be reopened it would at least require a more solid basis than "people told me". So, if you can cite some paper or news report or something like that at a minimum, it could direct someone to what exactly your question is about versus what is getting transformed between what you heard and what you translated that to write in your question (like a game of telephone).

@BryanKrause thanks for the pointer. Jill Hoyt mentioned it was a hot topic in the 90s, and certainly taken in the mainstream, there is a bit of history there and "legend". Removing altogether the "people told me" part would be ok also?

While it is theoretically possible for a protein to change size (based on length) because of nutrition, I don't think that's happening here.
You are right-- DNA encodes information that is transcribed to RNA which is translated into proteins. Proteins are made of a finite number of amino acids, which are the building blocks of proteins. Proteins can be modified (and can be cleaved to make the protein shorter), but I think this claim of "cow milk protein becomes longer" is a misunderstanding because there is not a single "cow milk protein", but rather many.
There are many different proteins in cow milk, and most of them are casein proteins. source
The milk protein likely at the root of this claim is beta-casein. It was a hot topic in the 1990s, because there are a dozen different variants of this beta-casein protein. Two of these variants are the most common in milk have been studied a lot: variant A1 and A2. The only way these are different is a single amino acid change at amino acid position 67 (remember that proteins are made of amino acids). Variant A1 has a histidine amino acid but variant A2 has a proline. What does that mean? That means that A1 can be cut (in your body) to produce a smaller protein bit (called a peptide). Because of the proline in the A2 variant, it cannot be cut like the A1 variant. The peptide resulting from the A1 getting cut is called BCM7.
In short:
beta-casein variant A1: can be cut to produce BCM7
beta-caesin variant A2: gets cut way less than A1 so way less BCM7 is produced.
So, what is BCM7? It had been reported to been linked to some different diseases but the European Food Safety Authority (EFSA) published this report which concludes that there is no link between BCM7 and non-communicable diseases. Despite this, there is still a lot of talk about A1 vs A2 in the dairy community. While websites such as this appear compelling, remember the EFSA report!
this paper is open source and has the information about these variants that is summarized above.
So what does all this have to do with "cow milk protein" changing size? Maybe more cows used as dairy cows have the A2 variant, which would not produce as much BCM7 (the small peptide). Since A2 is not cleaved to produce BCM7, it could be thought of as "longer"... at least relative to only a few thousand years ago.
The beta-casein A2 variant is thought to be the original version of beta-casein from undomesticated cows.
So, if this claim was originally about beta-casein, you can respond that "yes, the beta-casein protein can be thought of longer because it is not cut to produce the BCM7 peptide as much as the A1 variant is, but it is also the original beta-casein size." Whether it was 10,000 years ago or just now, the A2 beta-casein variant is the same size.
tl;dr / Good reading from the California Dairy Research Foundation.

Variation of components in milk related to different factors. Again, it's not about changing the protein structure depending of alimentation. https://extension.psu.edu/milk-components-understanding-milk-fat-and-protein-variation-in-your-dairy-herd


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What is the point in the Neuromuscular Junction?
Surely a direct connection (i.e. an electrical synapse) between motor neurone and the sarcolemma would allow for much faster neuromuscular transmission? It is my understanding that chemical synapses are only useful in facilitating spatial summation of action potentials from multiple presynaptic terminals... muscles have no need for this as they are innervated by a single motor neurone only?

The motor neurons develop from one germ layer, the muscles from another.  They are different cells. Are you asking why evolution didn't happen in another way?

@kmm An electrical synapse can be between any cells.

@kmm I am essentially asking whether there is any advantage in having a chemical synapse at a neuromuscular interface over having a electrical one (and from my understanding I can't see any). It seems strange to me that evolution would result in such a seemingly convoluted mechanism for neuromuscular transmission; I feel like there must be a good reason for having a chemical transmission

@BryanKrause Can be, but generally aren't: hence my question for the OP about why evolution didn't happen another way.

My point was just that them being different cell types doesn't exclude electrical synapses; maybe you weren't trying to imply that but your comment seemed to. Both chemical and electrical synapses are highly complex structures, chemical synapses arguable more so, so there's no a priori reason they couldn't form between dissimilar cells

After much searching on the internet I've found an answer to this question: the neuromuscular junction facilitates amplification of the motor neurone potential to generate a large enough current to depolarise a muscle fibre as muscle fibres have a much larger area of membrane (ie a larger capacitance) than neurons.
Source: Encyclopedia of Neuroscience: Volume One

The reason is the tremendous amplification of the neuromuscular junction. The amplification occurs since a small current is generated in a nerve can rekease large amounts of molecules of the transmitter acetyl-choline ($\require{mhchem} \ce{ACh}$), each of which can open channels in the much larger muscle membrane and can create much larger currents. In addition, a motor nerve fiber often branches profusely to innervate hundreds of muscle fibers, thus providing further amplification.
Finally, the capacitance of the muscular membrane has long been known to be much greater than the capacitance of the nerve membrane, because of the additional membranous systems, such as the transverse tubules in muscular fibers. Thus the capacity of the muscle to store charge is much greater than that of a nerve membrane and much more current must be supplied to depolarize muscle cells directly.


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Alignment of sequenced fragments in Next Generation sequencing (sequence assembly)
The NGS (Next Generation Sequencing) involves fragmenting the DNA to be sequenced. This is followed by attachment to beads or flow cells and then a localized PCR is conducted. Modified bases are added and with addition of each base, a detection is made (by fluorescence for instance) for the type of base bonded. After complete sequencing of all the fragments, how are these reads of fragments assembled in the way they were in the original non-fragmented DNA? (in short: How sequence assembly works?)

There are different methods of sequence assembly. To get an overview you can read this: http://www.nature.com/nrg/journal/v14/n3/full/nrg3367.html

Possible duplicate of What exactly are computers used for in DNA sequencing?

Assembly and alignment are generally used to refer to two different algorithms that work in two different ways.
Alignment takes your sequence fragments, and compares them to a reference genome, and tells you where that read aligns and how closely it aligns.  For a while, popular aligners used Burrows-Wheeler transform algorithms to make special indexed versions of the genome, this made alignment to the index far faster.
Assembly is when you have no reference, and use the overlap of the reads to build large contigs.  For a while De Brujin graphs were a popular algorithm for that.


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Lab experiment: Enumeration of Leukocytes
The images below were obtained in an experiment to enumerate leukocytes in a blood sample using Neubauer counting chamber.
The following solution was prepared and added to the Neubauer chamber and viewed under a compound microscope:
100 microlitres of acetic acid (acidic reagent to haemolyze RBCs) + 50 microlitre of Leishman's stain + 1-2 drops of blood.
Are these granular transparent circular objects in the images the leukocytes? If yes, do these include the smaller ones too? I am unable to decide which ones to take into account.
Moreover is this count normal (for instance, I counted around 250 (excluding the very small ones and applying the margin rule) in the top left box of the grid (Image 3))?

the amount of blood should be taken quantitatively ,not without measuring, so one or two drops of blood will not give correct calculations .

First I'd make sure all the RBC were gone just by visually inspecting. What should remain are your WBC and platelets at this point, and platelets are tiny so you can probably count anything between 5µm and 25µm. So for me that would include basically everything I can see minus background or debris.
So the problem now is with quantifying your count. You should know what the volume of your blood is, and here's why: What you're doing with a hemocytometer is counting #cells in a given volume, but you also diluted your whole blood with 150µL before you counted. So for example if a drop is ~60µL, and you diluted it with 150µL your dilution factor is 3.5, and it's important because your cell density equation is
For reference, you typically end up with 4-10 million leukocytes per mL of blood, however.


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Is it possible to artificially select for flight in pigs?
After reading this rant by Fodor, as a layperson, I was idly wondering whether it would be possible to artifically select for flight in  pigs. Of course by that time the porcine lineage will probably comprise an entirely new species, but what would be the first step in our breeding experiment? And how would it develop thence, hypothetically speaking?

If this is a classic breeding experiment the answer is: nobody can tell. Mutations are (more or less) random. You will have to wait what you get to decide what you can select for.

Nature/environment selects. Would you put selection pressure on pigs by throwing them off of buildings and selecting those who don't hit the ground?

@anongoodnurse : that would be one way but it might take longer than thinking about it a little first, deciding what changes you think you need to achieve flight in pigs & then working out the pre-adaptions & steps you think you'll need to get there then breeding for those stage by stage, which still takes a long time of course.

A comprehensive molecular analysis between pigs and bats, being both mammals, could inform an artificial design. However, an easier theorisation could use an in silico simulator such as keiwan.itch.io/evolution to gain an idea of the feasibility of such endeavour, time-scale being the most pressing issue

Intro course to evolutionary biology
I doubt you can get much from the below answer. At the end of the day, the only thing that would really allow you to increase your knowledge is probably an intro course to evolutionary biology such as Understanding Evolution by UC Berkeley for example.
Question

Is it possible to artificially select for flight in pigs?

If by 'artificially select' you refer to selection on available genetic variance, then No, it is not! You'll need plenty of new mutations and it would take a very long time.
Selection
You cannot select for something that does not exist. Selection requires pre-existing phenotypic and genetic variation for the trait of interest. No pigs are flying today, so you cannot increase the frequency of individuals flying by selection.
You will need to wait for mutations that confer such flying ability. Of course, there won't be a single mutation that turns a pig into a flying pig. Simply because flight is really not a simple adaptation for a pig! There are few species you could have chosen for which flight would be harder to think of! You are going to go on a long step-by-step procedure, fixing mutations one at a time by selecting every one of them and that will probably take hundreds of thousands of years or maybe millions of years.
Step-by-step procedure
I suspect you would consider using their front limb for flying. Here is a potential and extremely simplified step-by-step procedure. Of course, if you were thinking of pigs flying using their ears, the procedure wold be drastically different!
You should probably start by attempting to modify their limbs then. You can maybe try to start by selecting for individuals that are better able to manipulate objects with the front limb. Also start selecting for lighter bodies. Also, remove any selection for the ability of fast displacement or moving in the mud as that would select for their current front limbs. Start with some very very simplistic manipulation and increase up to eventually ending up with individuals that have pretty flexible front limb. Make sure to select for front limb that can move perpendicular to the body axis.
Then I don't know if you should aim to make wings out of skin or out of hair-feather like structure. If you're aiming with feather-like structure, you can try play it out with sexual selection just like it evolved in birds. Let's say you're choosing skin wings. Then, maybe selecting for those having broad and thing front limbs might be a good way to go. In the meantime, you've reached anything like that, you probably managed to reduce the body size of your pigs to the size of a mouse with a very elongated body.
Select for jumping abilities and then slowly for flying abilities. You've got flying organisms who's ancestors were pigs! Be aware nobody is going to fund such a useless and incredibly long experiment.

"If by 'artificially select' you refer to selection on available genetic variance, then No, it is not! You'll need plenty of new mutations and it would take a very long time." hmm. "Yes, it is! But you'll need plenty of new mutations and it would take a very long time" there, fixed it for you :)

Evolution really is all about random rolls of the dice, with natural selection deciding the outcome. The question of pigs flying has a precedence. Birds evolved from therapod dinosaurs (one of which is T-rex). But birds have an awful lot of adaptations for flight, including many that must have functioned for some other purpose before they could fly, such as feathers for thermo-regulation. The first wings must have served some function other than flying.
Artificial selection is different from natural selection in that it is accelerated through selective breeding. But the principles are the same. You would first breed for small size and light weight. All three tetrapod species that evolved flight did so with their forelimbs. So you would need to look for long forelimbs, and skin in the armpits...Keep in mind these changes would be random. It would require a staggering number of generations. But perhaps, and entirely hypothetically (as you asked), one could try, and it could be done.

I think you have to consider constraints imposed by embryology in this case. Mutations are "random" in the sense that you can't look into the future and plan what would be good for the organism.  It doesn't mean that absolutely anything is possible. Wings could only evolve if the process of development allows them to.  So you could try with all your might to artificially select pigs that you think might have qualities that allow other flying animals to fly, but wings are never going to appear unless embryological processes are susceptible to this kind of modification.


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Practical Question about Evolution, Population Genetics and Speciation
North American cicada male of the genus Magicicada sing depending on the species at different times of the day and attract the females of the corresponding species. The species are very similar, but when crossing they have sterile (infertile) offspring.

In the species M. tredecim the time of the song is determined by the gene locus EARLYBIRD in an intermediate inheritance: The allele EARLYBIRD leads in the homozygous state to morning singing, the allele earlybird leads in the homozygous state to evening singing, heterozygotes sing at noon.
How does the frequency of the earlybird allele in the species M. tredecim change when the number of females of M. tredecassini increases? Does it increase, decrease, or does it remain the same?

I think it would not change the frequency of the earlybird allele, because they don't have a evolutionary advantage. But maybe it could also decrease the frequency, because infertile descendants sounds like a disadvantage? But I'm totally not sure and can't provide a real 'biological' reason since my thoughts are more like intuition.

Homework questions are off-topic on Biology unless you have shown your attempt at an answer. For more information see our homework policy. 2

@Remi.b : Thanks for the hint. I have written down my own thoughts about this question.

Good. I am retracting my close vote. +1

Infertile descendants indeed sound like a disadvantage. Individual must invest a fair amount of resources into making an offspring. Making sterile offspring is just a waste of resources as those offspring aren't going to pass on any gene further to any grandchildren.
If there is an increase of the tredecdssini females, then male tredecim that sing quite late are going to mate with many tredecdssini leading to the production of sterile offspring. There is therefore selection against the allele 'earlybird' leading to an increase in frequency of the 'EARLYBIRD' allele.


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Dilute DNA plasmids with distilled water
I just extracted the DNA plasmid from E.Coli and dilute them in EB buffer. However, I've just figured out that the next step, which is electroporation, required that the DNA plasmid be diluted in Distilled H2O. Can anybody help me to know how to transfer the DNA plasmid from EB buffer to Distilled H2O?
To be clear, the EB buffer I used is from Qiagen. It contains 10mM Tris-Cl, pH 8.5.
https://www.qiagen.com/sg/resources/faq?id=d8ef773f-6a37-4993-908b-8bbc7bc5c8d6&lang=en

EB buffer is just Tris isn't it? I don't think that would interfere with electroporation. If you must change, you could precipitate or dialyse.

Please define EB buffer. In general avoid lab slang. I have edited your question to do so regarding distilled water, but I have no idea what EB buffer is and if it is not defined will vote to close your question as unclear.

Buffer EB is simply 10mM Tris buffer, ph 8.5. I think you are worried about the ions present in your electroporation. There are two things to consider:

What is the concentration of your DNA and how much do you need for the electroporation?
In which final volume is the electroporation taking place?

In my experience, usually you add a very small amount of DNA (a few microliters) to 100, 250 or 400µl (depending on the cuvettes used) final volume. Here a tiny amount of Tris does not interfere or cause a short circuit.


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Why do most plants reflect green and others other colors?
I have read that chlorophyll absorbs red and blue.

As shown in detail in the absorption spectra, chlorophyll absorbs light in the red (long wavelength) and the blue (short wavelength) regions of the visible light spectrum. Green light is not absorbed but reflected, making the plant appear green. Chlorophyll is found in the chloroplasts of plants.

It did not mention what the difference in chlorophyll between a red leafed plant and a green plant?
Does chlorophyll only come in green?
 So what in chlorophyll determines if other colors than green are reflected in plants that are naturally red? If chlorophyll needed can only be green would not the color green and the red from a " pigment" look brown?
Japanese Blood Grass

Blue Selaginella

Solenostemon scutellarioides

Please provide some examples of plants that naturally - that is, not as a result of human selective breeding - have red leaves.

@jamesqf i made one working on more

@Procreator: The examples so far seem to be the result of human selective breeding.. Plants have other pigments in their leaves, as you can see when leaves change color in the fall.  That's caused by the breakdown of chlorophyll, allowing the other colors to show.  In the first two of your examples, you can see that there is clorophyll showing in parts of the leaves.  It's just that the intense pigment in the blood grass and the internal structure of the blue leaves masks the green of the chlorophyll.  I expect something similar would be true of the coleus.

Are you sure all the example are selective breeding? I didn't check either, but if there is presents of chlorophyll as in normal plants the color green and the red pigment would blend to make brown.

@Procreator: Fairly sure, as they're all garden plants.  The coleus, for instance, has been bred into many different cultivars with different colors & patterns in the leaves: https://plantcaretoday.com/colorful-coleus-plants.html  The best way to show that they do have chloroplasts would be to examine leaves under a microscope.  Can't do it myself, since I don't grow them (they're tender, and need more mosture than I have), and it's winter here anyway.  Google "coleus leaf chloroplast" for info.

@jamesqf then answer and i will up vote you

Here's an example of a plant (common to the mountains hereabouts) that doesn't have chlorophyll, the snow plant: https://www.fs.fed.us/wildflowers/plant-of-the-week/sarcodes_sanguinea.shtml  But it doesn't use the red pigment to photosynthesize, having become parasitic on soil fungi.

@jamesqf make sure to include what the pigments are composed of and what purpose they serve.

@jamesqf do you want me to compose an answer using your comments?

All photosynthetic plants contain chlorophyll, and chlorophyll is green (leaving out various algae).  Plant leaves often contain other pigments, which can mask the chlorophyll's green, or be masked by it.
A common example of the latter is the color of autumn leaves.  The leaves contain various pigments such as xanthophylls, anthocyanins, and carotenoids that are generally masked by the green of the chlorophyll.  As the trees prepare to drop their leaves in the fall, the chlorophyll decomposes, allowing the other pigments to become visible.  Exactly what purpose(s) these other pigments serve isn't entirely clear.  Some are thought to make photosynthesis more efficient, others might have functions where the color is irrelevant.  See e.g. http://www.usna.usda.gov/PhotoGallery/FallFoliage/ScienceFallColor.html
Some plants may have a larger than average amount of other pigments, somewhat masking the chlorophyll's green, and giving rise to different shades of leaf color.  Human selective breeding can increase these differences, giving rise to e.g. the purple-leaf plum or the almost golden color of some honey locusts: https://www.thespruce.com/trees-and-shrubs-with-purple-leaves-3269731
Other plants, like the coleus, may have chloroplasts only in certain zones of the leaf, allowing other color combinations, which can be wildly amplified by human breeding:  plantcaretoday.com/colorful-coleus-plants.html
Sometimes the colors can be structural, as with the Blue Selaginella pictured in the question, or the grayish colors of desert plants that are produced by protective hairs: http://mojavedesert.net/plants/plant-adaptations.html
Finally, there are plants that don't have chlorophyll at all, but these don't photosynthesize.  An example (common to the mountains hereabouts) is the brilliant red snow plant:  fs.fed.us/wildflowers/plant-of-the-week/… But it doesn't use the red pigment to photosynthesize, having become parasitic on soil fungi.

Can you eat it?

@Procreator: Eat what?  The snow plant?  Supposedly yes, but they're illegal to pick.  Supposedly because they're rare, but they seem quite common in the mountains around here: https://www.scenicwonders.com/blog/rare-snow-plant-in-yosemite-west

In a survival situation.is why I was asking.


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Is it PSI-BLAST or BLASTP if I use PSI-BLAST for only one iteration
In my case, I used PSI-BLAST in the local BLAST+ to search queries against the self created database. After the first search, I added the searched result to the database and then conducted the multiple sequence alignment myself with MUSCLE to get the conserved parts. Then, I searched the queries against the consensus sequence obtained from the multiple sequence alignment (without gap). In this process, I did not calculate a PSSM, while the first iteration of PSI-BLAST uses a constant matrix, which is much similar to BLASTP. So what did I actually use in the process – PSI-BLAST or BLASTP?

You simply used BLASTP against a consensus sequence. The first iteration of PSI-BLAST is identical to BLASTP.


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ChIP-seq data Analysis Database
Where can i find already analyzed ChIP-Seq Data? Is there any database or any web tool that takes ChIP-seq raw data and automatically analyzes them? Or is there any database that provides some API to analyze the raw data it provides. I am new to ChIP-seq data analysis and i really need these to create a web-based platform for mapping ChIP-seq data. Thanks in advance.
I found some interesting data in genome.edu. Is there another database?

do you mean UCSC genome browser by genome.edu? It actually incorporates data from the ENCODE ChIP-seq experiments.

The largest database of curated ChIP-seq data is currently Encode and it supports an API.  You can use JSON to get at all tracks.
That page will have a link to Getting Started that should get you going. You can visualize raw data, normalized data, and processed data tracks in genome browsers that load in ENCODE data.  My favorite genome browser is:
WashU Epigenome browser


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Can exposure to blood make pathogens resistant to the immune system?
If a drop of my blood is dropped into a pool of pathogens. Does that act as "reverse-vaccination" for said pathogens?
I see this it as a potential risk for bacteria/viruses to compete or get acclimated with the weakened/dormant/key-specific of the immune system.
Please correct me if I'm wrong.

You have got the concept of vaccination a bit wrong. Pathogens have to evolve to acquire resistance to immune system (or antibiotics). Technically, the white blood cells also evolve to acquire resistance against pathogens if they don't have a strong innate immunity. Development of immunity after vaccination is also not instantaneous. The pathogen population has to "grow" in the blood for at least a few generations to become resistant. A drop of blood would probably not give the pathogen enough time to evolve. Moreover, your white blood cells will die quickly outside the body unless they are cultured in a controlled environment. Therefore, the selection pressure to evolve would also not be there.


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Is there an evolutionary advantage for coconut oils to be rich in saturated fats?
I know that coconut oil is composed of multiple saturated fatty acids, but is there a reason why this would have increased the fitness of the coconut plant?

Are you asking about coconut oil, the consumer product you can buy, or coconut oils, the fats found in coconuts that are pressed into coconut oil(the first kind)?

The product inside a brown coconut is called coconut milk and it is liquid.

I am referring to the unrefined consumer product(not coconut milk), but the first kind might also be interesting.

Possible duplicate of If a trait would be advantageous to an organism, why hasn't it evolved?

I think that's the converse of this question, isn't it? The generic form of questions like this is "given weird feature A in organism B, are there likely fitness advantages to weird feature A or is that coincidence?" not "given the fitness advantages to feature A, why doesn't it exist in organism B?". The first is sometimes answerable, even if the answer is sometimes 'dunno', but the second is always answerable with 'that's not how evolution works'. Furthermore questions like this are precisely how evolutionary adaptations are discovered.

This is entirely speculation, but the part of seeds that is pressed for oil(the endocarp) is enriched in saturated fats and long fats in ocean-going fruits. The coconut is 91% saturated fats, the oil palm is about 50%, etc. The tamanu or 'ballfruit' produces monounsaturated long-chain fatty acids in the endocarp, about 75% C18 oils, mono- or di-unsaturated.The calabash is astonishingly 20% saturated and 78% C18 oils, and is also sea-distributed(these seeds are called disseminules).
It's not a totally straightforward correlation. Peanut oil is 75% C18+ and 15% saturated and the oil palm mesocarp is only 50% saturated, but the endocarp is 81% saturated fats.
There's an additional consideration here: longer chain fatty acids are slightly more energy efficient per unit mass than shorter chain ones.
Without better data on energy density or spoilage rates on different blends of long-chain fats I can't conclude conclusively that spoilage and energy density are why disseminules tend to have longer-chain oils and more heavily saturated fats, or even that they definitely do. But it looks like they do, and that would make sense.


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Will a mother praying mantis stay with the egg sack?
We caught a pregnant praying mantis (without knowing it was pregnant). It made an egg sack on the underside of a cardboard bridge in its container.
It is in Pasadena, California. It kind of looks like the one in this link, except that it is paler green color (kind of tan brown/green). In the past I have seen some with red eyes, but I think this one had eyes that were black. I'm not sure if the eye color changes in the light, though.
Not knowing how to care for babies, we left the container outside in the shade with an open lid (so that the mother can climb out any time she wants, and so can the babies when they hatch). The mother climbed out immediately but remained on the outside wall of the container (near the egg sack) for hours.  However, the mother is no longer there.  Is it normal for a mother to abandon the egg sack?  Can we expect the mother to return?

Do you know what species of mantis — this matters because some species do provide care but most don't ...

@tyersome : I had responded to your question, and now I find that someone removed it from the comments and put my response in the question itself (which makes sense, except you may not notice it). I likely also forgot to @ you in my comment, so I am doing that now (in case my added info is helpful).