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Do PI-SceI and PI-PspI from NEB work in each other's buffers?
I'm considering a plasmid design strategy that would allow me to use restriction enzymes to exchange plasmid inserts among different backbones. In this case, the plasmids would first be made through MoClo assembly of pL1 inserts into different pL2 backbones. Then, ideally I could exchange the whole complete insert to another backbone at a later date without repeating the GG reaction.
To do this, I was thinking to use homing endonucleases, which have large footprints and are thus unlikely to show up in a given sequence. I already have I-SceI in the plasmids to use for linearization, so can't use that one. That would have been convenient because I-CeuI from NEB and I-SceI both are 100% active in CutSmart.
The other HE options from NEB are PI-SceI and PI-PspI. Neither work in any of the standard buffers, but use similar buffers as each other:
1X NEBuffer™ PI-SceI

10 mM MgCl2
1 mM DTT
10 mM Tris-HCl
100 mM KCl
(pH 8.6 @ 25°C)

1X NEBuffer™ PI-PspI

10 mM Tris-HCl
10 mM MgCl2
1 mM DTT
150 mM KCl
(pH 9.2 @ 25°C)

I'm wondering if anyone has tried using them at the same time in one or the other's buffer?
Alternatively, are there any other good HEs out there I should look into?
Finally, is this even worth it? Or should I just re-run the MoClo reactions into new backbones? Would that be more efficient and reduce hands-on effort?
Thanks for any input!

Have you looked into gateway cloning?

Welcome to Biology.SE. If you look carefully at the NEB site you will find that these enzymes require very different temperatures for activity (37°C vs. 65°C) ...

Oof you're right! PI-PspI only has 10% activity at 37°C. Bad idea....
Yeah Gateway is possible, though I try to avoid it if possible. Would be weird too because transferring in would cause PB to switch to RL or vice-versa. So I'd need BP and RL versions of each backbone depending on which way I wanted to switch. I think the simpler solution is to just replicate the Golden Gate into different backbones as needed. That's very efficient and not that time-consuming (esp with all calculations essentially pre-done).

If you have questions, you can always call NEB's tech support. You'll get to talk to a real person who actually understands the products and the science. (I used to work for a company that was spun out of NEB and has the same tech support model.)


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Intelligence of nervous system vs other human intelligence?
Viral proteins are shown to be used in intelligence such as for memory: https://www.sciencedaily.com/releases/2018/01/180111141450.htm
I wondered since proteins able to form prions are the most logical thing directly controlled by the soul, how intelligent is the nervous system compared with other systems the body uses for intelligence like viral proteins? Has anyone calculated the difference in computing power of them?

What are you implying by the phrase "intelligence like viral proteins"? Could you please elaborate your thoughts on it?

@ANandiΨ Viral proteins are shown to be used in intelligence such as for memory https://www.sciencedaily.com/releases/2018/01/180111141450.htm#:~:text=The%20protein%2C%20called%20Arc%2C%20is,like%20a%20protein%20from%20viruses.&text=A%20protein%20involved%20in%20cognition,like%20a%20protein%20from%20viruses.

@ANandiΨ I wonder how the non-nervous intelligence compares to nervous intelligence

"Arc" is the Activity-regulated cytoskeleton-associated protein. It's one of the "immediate early genes", which are genes whose expression changes very quickly in response to certain neuronal activity. They are thought to be important in mediating the changes in expression of other proteins that accompany learning and memory in neurons.
This is not talking about any other "intelligence" or memory besides what happens in the nervous system. It's about the mechanisms by which the nervous system operates. The paper (Pastuzyn et al 2018) suggests that this protein originally came to the animal genome from a virus rather than evolving from other animal genes, and that it behaves in a virus-like fashion to transfer genetic material from one cell to a neighboring cell. That's definitely interesting from an evolutionary and molecular biology perspective, but it does not mean the body "uses viral proteins for intelligence".
In an animal, these aren't "viral proteins" any more, they are animal proteins, built from DNA in animal cells and evolved alongside those animal cells. The paper is about Arc in fruit flies, though Arc is also found in vertebrates but seemingly from a different lineage; therefore the authors suggest that this has happened at least twice. It's certainly fascinating that such a rare event would happen more than once; I'm not sure if there is additional literature on this because it seems hard to believe, but I suppose it's one more element to how all the genetic variation in modern species evolved.

Pastuzyn, E. D., Day, C. E., Kearns, R. B., Kyrke-Smith, M., Taibi, A. V., McCormick, J., ... & Shepherd, J. D. (2018). The neuronal gene arc encodes a repurposed retrotransposon gag protein that mediates intercellular RNA transfer. Cell, 172(1-2), 275-288.

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What is a lamprey's tongue derived from?
Tetrapods have tongues derived from the 2nd gill arch and nearby muscles. Lampreys are not tetrapods, and lack jaws, yet they have a tongue. What structure was this tongue adapted from?

Are tongues older than jaws? Because jawed fish came from jawless fish. Could have the same origin.

the tetrapod jaw is just the first gill arch.

the "tongue" is just the bottom of the throat. Its not related to the tetrapod tongue nor are their "teeth" related to tetrapod teeth.
https://www.nature.com/articles/nature11794

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What structures does our brain use for a quick indexing of all the data we store in our heads?
What structures does our brain use for a quick indexing of all the data we store in our heads?
From how my brains work (i.e. that I can very quickly recollect something from the past) I would say that my brain does not do a linear scan of all the memories, otherwise it would take a lot of time to recollect something. So, we for sure have indexing structures in our head.
From the time complexity point of view I would say it should be at least logarithmic or even faster. Do we maybe have B-trees or LSM-trees implemented in our brains?
I am curious to learn more about the topic, but so far I was not able to find a good explanation about it.
I am playing around with creating my own database and would like to try to simulate the workings of my brain to get something similar. Hence, the curiosity in the question.

B-trees!  No computer programs apply.  Our brains are essentially entirely parallel and asynchronous, unlike any nontrivial machine man has ever built.

We don't know..

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer.

@Community, please, edit your comment to limit it to a specific problem with enough detail to identify an adequate course of actions for updating my question. Thanks.

Brains are not computers, and do not process information like computers.
The trees from CS you are talking about are ways to run linear information stores through a central processing unit. Even with machines that can sort of do these operations in parallel, they are still very much series computations.
Brains, on the other hand, are massively parallel, and information is encoded in a very high dimensional space, not linearly. There are no "bits" in a sequence to sort through. Information does not just move from "storage" to some "processing" part of the brain, it is constantly being processed at all stages in all places. When a memory is active, that information is linked to all the other related information physically because neurons are connected to each other. That is, when you think of a "cat", you might retrieve a memory of a specific cat you saw in a specific place because there is a physical connection between some of the same neurons that are active when you think of "cat" and the neurons encoding that engram of the specific cat memory. No "search" is necessary; every extremely high-dimensional brain state is followed by another extremely high-dimensional brain state. When you "search" your memory for cats, you are just biasing these future states to be those which involve neurons that were involved in the past during experiences of cats.
I think the most attractive models for understanding how brains index information are attractor networks. There are in silico models and implementations of these sorts of networks, but without the parallel hardware of a biological brain they aren't particularly efficient.


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How are Current Sources and Sinks for Postsynaptic Potentials defined?
I am currently reading "Electric Fields of the Brain" by Paul Nunez, and encountered this passage:

The synaptic inputs to a neuron are of two types: those that
produce excitatory postsynaptic potentials (EPSPs) across the membrane of
the target neuron, thereby making it easier for the target neuron to fire an
action potential and the inhibitory postsynaptic potentials (IPSPs), which act in
the opposite manner on the output neuron. EPSPs produce local membrane current sinks with corresponding distributed passive sources to
preserve current conservation. IPSPs produce local membrane current
sources with more distant distributed passive sinks.

Can somebody explain why EPSPs would produce current sinks instead of sources (and likewise why IPSPs would produce a source)? I was under the impression that EPSPs would propagate a signal, instead of terminating them, making them act more like a source.

Sinks and sources just refer to the sign of the local field potential measured with extracellular electrodes.
Excitation involves positive charges entering cells, depolarizing them. When positive charges move into a cell, there is less positive charge outside the cell where the electrode is, so it becomes more negative. This is called a "sink" because the electrode records a negative deflection.
Inhibition is a bit more complicated because shunting inhibition does not involve much net movement of ions, rather it involves opening chloride channels with reversal potential near the resting membrane potential, which prevents cation channels from contributing to depolarization (sodium coming in the cation channels is balanced by chloride coming in the inhibitory channels).
Charge flows in circuits, so when you get negativity in one place you get positivity elsewhere and vice versa. If you stimulate a cell near its soma such that positive charge enters the cell there, the positive charge will flow into the rest of the cell but also attract negative charges towards it. The result is that membranes out on distal portions of the cell become slightly (because this is over a wide space) more positive inside, which in turn repels positive charge outside the membrane so an electrode near the fringes of a cell but not near the stimulation site will actually record a source. Generally in CSD recordings these types of sources dominate over inhibition, it's very difficult to record a "current source" and attribute it to inhibition.
I attached a few references below; I think the Olejniczak paper is a good place to start. It's focused on EEG but will help understand how what goes on inside neurons affects what we measure outside of them. Nicholson & Freeman talk about the theory behind current source density and is probably a straightforward read if you're familiar with the physics/math of electricity. Mitzdorf is a longer review article that talks more about the information you can get from a CSD and talks about the difficulty in interpreting sources that I mention.

Mitzdorf, U. (1985). Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena. Physiological reviews, 65(1), 37-100.
Nicholson, C., & Freeman, J. A. (1975). Theory of current source-density analysis and determination of conductivity tensor for anuran cerebellum. Journal of neurophysiology, 38(2), 356-368.
Olejniczak, P. (2006). Neurophysiologic basis of EEG. Journal of clinical neurophysiology, 23(3), 186-189.


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Why crystal violet inhibits growth of gram positive bacteria?
In microbiology lab, we use MacConkey agar to selectively grow Gram-Negative bacilli. Crystal violet is used as a component of MacConkey agar for inhibiting growth of Gram Positive bacteria.
However I can't associate this action of crystal violet on Gram positive bacteria specifically. What is the probable mechanism?


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Emotion as a conscious prediction error signal?
At first glance it seems many if not all emotions can be explained as prediction errors: hunger the observed level of energy stores is below expectation, anger the observed level of “respect” was below expectation, fear the observed level of personal safety was below expectation, disdain the observed level of respect afforded another person was above expectation, and so on. In addition, this explains the “motivational” component of emotion, namely to alter beliefs or execute actions to eliminate the prediction error in line with Friston’s free energy principle. Eg in the case of hunger, to eat, in the case of fear fight or flight, in the case of anger either dispute the offense to obtain a retraction or punish the offender, and so on. So I’ve found it surprising that it appears difficult to find research related to explaining emotions as “active inference”. The closest I’ve found are Emotions as computational signals of goal error  and Emotion and the predictive mind: Emotions as (almost) drives.
Is this an active area of research? Any pointers are appreciated.

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer.

Definition of emotion used is somewhat vague: is hunger an emotion? It has to do with real physical needs, like physical pain, whereas the other examples have to do with mental activity/relationships. Also, what about love, hate, curiosity, satisfaction, and many other emotions?

Well that’s the essence of the question.  Can some (or all) emotions be defined as conscious prediction error signals, where the predictions are the brain’s expectations about what it will observe. The expectations include priors like physical needs (which yield feelings such as hunger, thirst, oxygen hunger, salt hunger, pain, etc when they are violated) as well as learned beliefs about the causes of what it observes, which can be very high level explanations. The list is too long for this comment, but for example, embarrassment, my observed level of “competence” is below expectation.

It seems someone could define things this way for at least some emotions, but then....what's next? Why is that useful from a biology standpoint? There are predictive coding models for the brain but these are specified in terms of how the prediction errors propagate information within the brain.

Well, the obvious answer is that it could lead to a principled explanation of emotions in terms of free energy minimization, and if correct eventually to identification of the prediction error units and neuromodulators responsible.

@ChristopherOliver That doesn't make a whole lot of sense to me, but seems to be stretching Friston's ideas further than even Friston would.


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Chromosomal disorders
I was reading about chromosomal disorders and encountered a line stating that

'An individual may lack one of any one pair of chromosomes'

So does it mean that an individual cannot have monosomy of two different chromosome pairs? Or does it has some other meaning. Please Help.

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.

Welcome to Biology.SE. This is not a forum or tutorial service; it is a Q&A site where specific questions relating to biology get specific answers. Please take the [tour] and carefully read through the [help] to learn more about the site, including what is on-topic and what is not, and how to [ask] a good question. In particular, we can't "explain" random quotes — which will be opinion (and thus off-topic). Finally quotes must always include a source!

The only "complete" monosomy that is survivable in humans is Turner syndrome.
So your source is a bit silly.
http://en.wikipedia.org/wiki/Monosomy

Theoretically anything can happen, but you also have to take into account firstly, the probability of such an incident (which is particularly rare in this case) and secondly, if the creature can survive after or even until birth, to be counted as an organism with that kind of anomaly. For instance, the odds of trisomy 21 taking place in humans is not much greater than that of trisomy 11, but almost all fetuses with trisomy 11 would be aborted and never make it to this world.

Please add further details to expand on your answer, such as working code or documentation citations.


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Can viruses grow?
Hey there everybody !
I know that viruses show only one living feature - Reproduction. However they cannot reproduce by themselves so on this basis they cannot be classified as living organisms. They need a host cell to reproduce.
When a virus infects a host cell... and injects the DNA into the host cell... and the DNA merges with the nucleus of the host cell and the host cell starts creating new viruses.
Now my question is, when a new virus is 'made' will it be made in its full size ?
Like- will the virus which is made by a host cell be an 'adult'/mature virus ?
In other words will a newborn virus be like a newborn human baby, where the baby has to grow up to become an adult. Does a newborn virus have to grow ?
I assume NOT, since Viruses don't have any organelles to do any growth and development.
But can somebody confirm this ?
Because there is a weird image in my textbook where we have a virus infecting a bacteria cell and the next image there are 'baby' viruses inside the bacterial cell.
Thanks in advance

Not all viruses are DNA, and not all DNA viruses integrate their DNA into the host cell.

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.

Viruses do not grow. Instead, their components self-assemble inside of a cell to form complete new viruses, which are then released to go and infect more cells.
Here is a fairly accessible review on the subject: Mechanisms of Virus Assembly.  Basically, when the virus reproduces, it manufactures a bunch of parts.  A typical virus may be thought of as having three types of part:

The genome (RNA or DNA) that encodes for the virus
Structural proteins ("SPs"), which form the packaging for the viral genome
Non-structural proteins ("NSPs"), which handle operations within the cell such as replication, packaging, and suppression of host cell anti-viral responses.

In the replication process, the virus makes a bunch of copies of each of these independently. The SPs and genome come together to form new viral particles, and the NSPs get left behind.  Consider for example, this Sindbis virus genome:

Bases 79..7635 encode a "non-structural polyprotein": a collection of four protein elements that assemble in various different configurations to build a "viral factory" out of membranes within the cell and then copy the genome.
Bases 7681..11418 encode a "structural polyprotein" collecting together the five elements that form the capsid that self-assembles around the genome to make a new particle.

Now, this is biology, so there are exceptions and blurry boundaries, but this covers the typical cases pretty well, and even in the non-typical cases I have never heard of a virus that "grew" in a meaningful way.

Short answer - no, they don't grow once they are released from the cell.
I like to think of it as a factory production process. The widgets coming out of the factory assembly line don't grow, they just get sent out.  Sometimes the assembly line makes mistakes and a virus might be missing something (or most things) or might even be just an empty shell and so be smaller. Some viruses are contained in "bags" (enveloped viruses), so sometimes the bag might be defective instead, or even empty. Some viruses (like TMV) "self-assemble" with their protein coat automatically "growing/assembling" around their nucleic acid (RNA in this case), but that's a one-time process in the cell and doesn't continue once the virion is released.

I agree with the answers given by @jakebeal and @Armand. However, the analogy between a newborn virus and a newborn baby, suggested by the OP, is not without its merits. Indeed the virions released by a cell, in which the virus has replicated, are not always ready viruses. They need to undergo the process called maturation. E.g., see here and here.


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Are there any congenital anomalies that cause a lack of epicanthic folds in a child who would normally have them?
Wikipedia lists several medical conditions associated with epicanthic folds. Mount Sinai says that epicanthic folds in a baby who would not be expected to have them is a diagnostic tool that indicates that the baby may have Down syndrome or another genetic disorder and should be examined further. Presumably this means that those disorders are slightly harder to diagnose in populations where epicanthic folds are the norm as it is less visually obvious that there is a congenital abnormality though all the other symptoms would still be present. But are there any congenital anomalies that cause a lack of epicanthic folds and thus would be easier to diagnose in a population where epicanthic folds are ubiquitous?


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Why do chromosome pairs have different shapes and sizes?
When I look at microscopic images of human chromosome pairs I see that they have different shapes and sizes.
Is there a deeper biological reason for that? Is there some evolutionary pressure for them to be this way?

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.

Chromosomes are different sizes - they have different numbers of base pairs in them. That's why they look different...

@MattDMo They are curved at different angles. Why are the angles different? Why are they not all straight lines?

Because the nucleus is crowded, and there isn't enough room for all of them - especially the longer ones - to be stretched out straight. If you haven't already, please read the Wikipedia article on karyotypes.

Think of the chromosomes as a bunch of ropes of different lengths (i.e. size in base pairs). if you quickly try to sort out a bunch of ropes on the ground with a long pole from a platform 50 feet up (basically how karyotype images are created), do you expect the ropes to be straight, or for some of them to have some wiggle?


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Hybrid corn yield vs mass-selected corn
I am a social scientist and I was reading "The political economy of hybrid corn" by Jean-Pierre Berlan and Richard Lewontin.
https://go.gale.com/ps/i.do?id=GALE%7CA4325182&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=00270520&p=AONE&sw=w&userGroupName=anon%7E8cf008c1
They claim that the R&D cost for inventing hybrid corn was much higher than the mass selection of corn varieties (Mendelian selection scheme). One reason hybrid corn was adopted was that farmers had to revisit the seed seller every year to maintain their corn yield because the second generation hybrid corn is much less productive, while the selection of a new productive corn variety will make the seed company obsolete once the productive crops are distributed. It was claimed that Henry A. Wallace, the founder of hybrid  seed selling company and the son of Secretary of Agriculture Henry C. Wallace, pushed for hybrid corn at the expense of using Mendelian scheme.
I was wondering if there is any academic article or experiment result that compare the productivity hybrid corn versus corns that were developed by "Mendelian selection scheme."

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.

Hybrid corn IS a "Mendelian selection scheme". The issue here is more predictability and uniformity of crop growth and yield.
Normally, plants are genetically varied and having different versions of each gene from mother and father usually increases the fitness of the plant (this is sometimes called "hybrid vigor"). When farmers replant with seeds from only their "best" plants, over the generations the plants become more uniform and predictable in that (good) aspect, but also become more and more inbred (having both copies of a gene be exactly the same instead of slightly different). This inbreeding reduces plant fitness (e.g. yield or disease resistance).
With the discovery of genetics in the early 20th century, farmers realized they could get the benefits of hybrid vigor without the drawback of inbreeding. It's a two step process: separately breed two different varieties of a plant, each highly inbred, then produce seeds in a "seed factory" that have one variety as the "mother" and one variety as the "father". Each inbred parent passes on only the one version it has of each gene, but each (offspring) seed ends up with both different versions of each gene, one from each parent.
The resulting hybrid seeds called "F1" are both genetically uniform AND show "hybrid vigor" because each has two different versions of every gene. They just don't breed true, as the different versions of each gene get mixed up again ("reassorted") in further generations.
However, as long as the two original inbred parent varieties are propagated (remember, they remain genetically identical as they are inbred), the F1 hybrid offspring seeds can be recreated whenever desired. This naturally leads to a larger organization (like a company) maintaining the two parent varieties and continually producing reproducibly uniform F1 hybrid seeds for farmers to actually use.

Thanks for the detailed explanation. My understanding of Lewontin's article was that non-hybrid seeds that were properly developed would have been better than hybrid corn. Does that sound outrageous? Thanks

It seems quite unlikely. After all, nothing is stopping farmers from using non-hybrid seeds; if they didn't see an advantage to buying the hybrids, they wouldn't do so. The complexity comes in when you deal with multiple features of the plant. For example, maybe a given "heirloom" (inbred) variety has a special taste that nobody has been able to incorporate into a hybrid, so a farmer is willing to accept a lower yield or less hardy plant because they can get a significantly higher price for the product at market. In home tomato growing both hybrids and heirlooms seem to hold their own.

"Hybrid corn IS a 'Mendelian selection scheme'."

You've missed the point: that true-breeding (and predictable and uniform) vigor might also have been possible to select for, but seed companies didn't bother trying, since it would have let farmers replant seed—unlike the hybrid-corn business model of making farmers buy new seed each year.
(Tl;dr if hybrid vigor is because of heterozygote advantage at various loci, you couldn't select for true-breeding vigor. If it's because of dominant good genes in each parental strain covering up recessive bad genes in the other strain, you could.)

@DavidBahry We've learned a lot in the past 15 or so years of the genome era. One of those lessons is that in real life different alleles of a gene are not all good or all bad; in fact, many genes have multiple functions as part of the same gene! This has supported the assertion that hybrid vigor is due in large part to heterozygote advantage rather than just increasing the proportion of loci with "dominant good genes".  In this case, it seems the business model is indeed supported by the science.


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What antibody targets are being tested for in the publicly offered UK antibody test?
In late August 2021 the NHS (UK) offered people who test positive for COVID what is referred to in this BBC report as a “new antibody test”.
However, I have been unable to find out what exactly is new about this test. I was hoping to find what antibody targets are being tested for, including the virus strains used for them.
From what I understand there are many paths to immunity depending on the antibodies targeting one or more of the viral proteins.

image source: Murphy K, Weaver C. Janeway’s Immunobiology. 9th ed. Boca Raton, FL: CRC Press; 2016. Table 10.27
Q: What exact antibody targets are being tested for?
(What is "new" about this?)

Possibly related questions:

How long after taking a vaccine shot (Oxford–AstraZeneca) could an individual test negative for antibody (IgM)?
Why do antibody tests target different antibodies?

I'm afraid this requires a bit of digging to find what you are actually referring to. The digging itself is not what people do here, so hopefully you'll find a lead to point us to. Otherwise you have to cross your fingers someone knows what exactly you are referring to. Good luck!

It could simply be semantics - the "new" part being that it is now offered, when it wasn't previously.

Yeah, the only thing I find as being "new" here, is that it is being offered for free. But still no clarity what exactly is being offered.

Antibody tests have only been used on people involved in studies or surveys. This is the first time the tests are widely offered to the UK public for the purpose of collecting information about “vaccine effectiveness and the immune response of the broader population”.
This action is what they are referring to as “new” here, not the antibody test itself.

That is indeed unfortunate as T-cells cover a very important part of the overall immunity that is otherwise missed by the currently available tests.


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Asexual reproduction by secondary mycelium in basidiomycetes
I'm studying in class 11 and the the following line was mentioned in my textbook: "Dikaryophase or secondary mycelium may multiply by different types of spores - chlamydospores aecidiospores, uredospores, teleutospores." My teacher told me that in secondary mycelium, karyogamy takes place and 4 basidiospores are formed by meiosis. Where does aecideospores, uredospores etc, come into the picture?

Those spores are produced by different groups. E.g uredospores by Rusts; which have two dikaryotic spores. There are different sorts of spores produced even by the one species at different times.

It’s really complex.

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer.


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Help identifying a mite (?)
I live in Cambridge, UK, and found these mites (probably? not sure) in the attic. There are no bird nests at or around the dwelling, and no traces of rats or mice. There are plenty of those and not clear what they feed on. Body is about 0.7-1mm long, see photo with a ruler for scale.
Can you please help identifying these?

Welcome to Biology.SE. Can you be a bit more specific about where in the UK? This information may not be needed, but since conditions in the Shetlands and Wales (for example) are a quite different that information may help pin down your mite.

Thanks - updated (Cambridge, UK)

Great! If you don't get an answer I encourage you to check out some of the websites such as iNaturalist that specialize in identifications. If you do find an answer elsewhere it would be great if you would post an answer here that includes: discussion of key features that led to the identification, and supporting references or validated images!

In support of Acari, there doesn't seem to be any division on the scute or any elytra, so it is unlikely to be a beetle. Also no obvious separation in to head, thorax, abdomen, though you might only see this on upside-down ones.

This is a mite in the order Oribatida. Like many other oribatids, it appears to be covered with a smooth, dark, hardened, vaguely teardrop-shaped "shell", like a beetle—hence the common name "beetle mites". Its mouthparts and legs, visible at the narrower front end, are flanked by thin, flat plate-like structures called pteromorphs ("wing-shaped"), which you can also see in this photo and this SEM image. It is also the right size for an oribatid (visible to the naked eye, under 2mm).
David E. Walter notes in his key that there are similar heavily armoured mites in other groups. Most of the characteristics that are only found in oribatids, like long sensory hairs just behind their "head", can only be seen with much higher magnification. But I am reasonably confident this one is an oribatid and not a mesostigmatid/prostigmatid mite because of the combination of smooth, shiny hard shell, leg and mouthpart placement, and pteromorphs.
These tiny, harmless mites live in soil, under rocks, etc. Further identification usually requires an expert with a microscope. If you are on Twitter, the British Arachnological Society may be able to hook you up with a mite expert.

Observations from your area on iNaturalist
A checklist of UK oribatids (paywalled)

Please update your answer to explain/describe why these are Orbitid mites. How can you tell? What evidence do you have? Thanks

Amazing, thank you!


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How do we know if a trait is genetic rather than via rearing environment?
In articles like this one, I often read that several "genes variants are associated to a given trait". It is often added: "genetic factors explain (say) 20% of the trait variance."
The way I understand this is the following: researchers regress the trait upon the genome, find correlations between some variants and the trait and give some measure of the fit (or explained variance) like the $R^2$. Is my understanding correct?
If my understanding is correct, I am uncomfortable with the interpretation that the trait is partly genetic. Indeed, it could be due to rearing (that is, from the parents, yet not from the genes). I am aware of the practical difficulty (or impossibility) of finding a trait that we know for sure is from rearing and not genetic, but one can use models (described below) to study my concern. The basic model feature a random trait and the advanced one a trait transmitted by rearing.
The basic model runs as follows: define an arbitrary trait as the indicator of a random subgroup of the (global human) population. Would a study really fail to detect a genetic causality in this model? How common is it to find some gene variants associated to this arbitrary trait, and explaining (say) 20% of the trait variance? More formally, what is the distribution of the variance (apparently) explained, in function of the size of the arbitrary subgroup? I am sure there is a paper (or even a literature) about this: I'd like a reference to get the main insights.
Now, let's turn to the more advanced model, for which I am also seeking for references (I am sure it exists as well but have no clue how to look for it).
The model simulates genomes of the whole population among successive generations. Some trait appear at a given generation (call it t=0, although it is not the eldest generation modeled) among random individuals. The trait is not uniformly distributed at t=0, but has more chances to be found in individuals "close to the spatial location where it appear" (you can think of the trait as "listening to techno", and the location as Detroit). Suppose the trait is not genetic, in the sense that no gene variant influences the trait occurrence in one individual. Instead, the trait is transmitted through rearing environment: e.g. an individual has the trait with probability P if one of their parents has it, and with probability p<P otherwise (we could refine the assumption and say it could also be transmitted by acquaintances, or that it has more chances to be transmitted if both parents have it, but I think such refinements are not needed, and we could perhaps even simplify further and take p=0, P=1). Then, after T generations of breeding (realistically modeled), some biologists try to assess whether the trait is genetic. They will surely find some genetic correlations as (i) the trait has originally appeared in a specific location where people were relatively close genetically, (ii) the trait is transmitted by the parents, like genes, and (iii) there are many many genes, so that the probability is high that those who got the trait at t=0 share some gene variants. Now, let me recall that the trait is not genetic: for example, we could take the babies from their biological parents at t=T and have them raised by randomly drawn couples, it would be the adoptive children of techno listeners who would share the trait, and the (apparent) genetic link would be lost.
Hence my question: how do biologists know whether a trait is genetic or transmitted by rearing, despite the two seeming hard to distinguish in the advanced model? When I read a study claiming that a given trait is genetic, do they employ subtle statistical method to really prove so, or do they mean by that "genetic or reared", in the sense that the trait could fall in the case of the advanced model above? Does "explain 20% of the variance" mean that it is (probably) partly genetic?

Is https://biology.stackexchange.com/a/42280/27148 helpful at all?

Left-handedness is probably a good example: having a left-handed parent, especially mother, increases one's chances to be left-handed, but it is not necessarily genetic.

Thank you @Bryan, it helps because I learned that the "20% of variance explained" notion I referred to in the question is called "heritability" (and interestingly, not "geneticity"). However, the core of my question remains unanswered and I am all the more surprised because in your link, they seem to overlook the issue I mention, because they don't draw a distinction between non-biological environmental heredity and genetic, or at least do not provide a method to distinguish them.

I really don't understand this question.  How can a trait be genetic OR hereditary?  Genetic IS hereditary.

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.

How could I make it clearer? I thought the title said it all: "How do we know if a trait is genetic rather than hereditary?" I don't understand what isn't clear :-/
@jamesqf hereditary (transmitted by the parents) encompasses genetic (transmitted by the genome) but not the other way around. Or am I not using the correct definitions?

Does this answer your question? Why is a heritability coefficient not an index of how "genetic" something is?

@bixiou: I may be wrong, but my understanding is that genetic == hereditary.  You seem to be asking about genetic versus environmental, which could include prenatal influences such as chemical exposure (fetal alcohol syndrome comes to mind, or being taught something by parents &c. Acquisition of language would be an example of the latter: humans have the genetic ability to learn language, but what particular language(s) they learn is environmental.  A child of Chinese parents adopted as an infant by an English-speaking family will grow up to speak English, not Chinese.

I've tried to rewrite the question to avoid the redefinition of "hereditary", which I think even with your explanation in the first paragraph will mostly confuse or frustrate readers. Hopefully I've kept the meaning you intended. If in a population rather than a single family lineage we might call this "culture". "Environment" would be broader and would include all of these factors.

Thank you all, in particular @BryanKrause. I learned the word "rearing" thanks to you :-) Indeed, I had a wrong definition in mind for heredity. Your edits were fine, I just changed "influenced by rearing" into "transmitted by rearing".

It's purely and simply that there is no single answer - as in the linked paper, there's no "gay gene", there is a group of identified genes that contribute, but not all the variance in the population seen can be attributed to those genes. i.e. you can have some or none of those genes and still be gay, or indeed all the genes and not be gay.
This could mean that there are other genes still to be identified as playing a role, or it could mean that environment, epigenetic factors (e.g. methylation, some of these seem to be hereditary too!), expression levels etc. play roles in this trait, but as it is multi-factorial, we don't know the answer(s) yet. It may well be that we will never know, or that there are more than 1 answers to the trait.

I am sorry but this does not answer the question nor does it add information with respect to it.

@bixiou - yes it does - if you want me to spell it out explicitly - your "models" make some assumptions that are simply incorrect. There are heritable traits of which we know no genetic component - e.g RogerVadim's handedness in comment above, and this is partly because we don't fully know what all of our gene products do and how they are regulated. Have a look at the functional interactions of p53 at stringdb - keep clicking the "more" button. We've known and heavily studied this protein for ~50 years and are still finding interactions...

@bixiou ...there are about 25,000 genes in the genome, each would need to be studied to the same level and we would need to be able to work out the undoubtably multi-factorial models to explain some of these traits. We don't have the technology yet, though we are just starting to scratch the surface. We are also finding new ways in which we regulate genes and gene products - M6A (6-methyladenosine) in RNA is a good example of this, known for 30+ years, only now being identified as to what it does.

That's interesting that we are not able to study all genes at the same level, it shows that my understanding (as I have defined it at the beginning of the post) is wrong. I'd like to know how they do though, because knowing that I am wrong does tell me the correct answer.

@bixiou why they aren't studied has many answers, partly funding, partly man-power, partly reagents, partly we haven't looked for that interaction (yet). p53 is heavily studied because it is a cancer gene, one of the more common changes, it also happens to be a cell cycle regulator, so it is easy to get money and thence man-power to study it. A lot (almost all) of the interactions at a protein level are determined empirically and 1 by 1, so you can see that it takes a long time and a lot of work to get it done.

General remark
One does not necessarily need to use a subtle statistical method, but one does need good understanding of the experimental design and statistical analysis in order to draw reliable conclusions from the data (or know when not to draw such conclusions). It is for a good reason that statistics is a field of its own (just like biology) and there exist a dedicated stack exchange community (by far more active than biology). Pubmed is also full of articles explaining why this or that approach needs to be carefully - just try to search for spirious correlations and see how many articles come up.
Correlations and non-correlations
Closer to the point: the model in the OP assumes that certain trait can be a consequence of the location (or other non-genetic factor, not necessarily hereditary) and the genotype. The co-occurence of certain genotypes and locations confounds the problem. Moreover, it is possible that this co-occurence actually leads to real correlations between these two factors.
One thing to look for is the appropriate sampling procedures, especially the sample size. As an extreme example, let us consider preference for wearing warm clothes in winter - is it a function of location (Moscow vs. Miami) or a trait coupled with Y-chromosome? We could do the analysis of variance, proposed in the OP and easily prove that there is no correlation with the presence of Y-chromosome... unless most of the individuals sampled in Moscow were men and most of those sampled in Miami were women, in which case we may erroneously attribute the preference to warm clothing to possessing Y-chromosome.
It is clear what has gone wrong in the example above:

the experimental design was not balanced
statistical analysis was not corrected for this lack of balance

One can thus expect improvements along these two axes: by designing experiments that allow disentangling undesired correlations and by employing the approrpiate methods of analysis. Let me however add a few more remarks:

not all correlations can be disentangled - sometimes creating appropriate design is difficult or even impossible. This is especiallyw hen we are talking about complex genetic traits.
there may be genuine correlation between the traits - e.g., the trait of interest and settling at a certain location may be both functions of genotype.
In regard to the correlations that may arise after several generations, as the OP suggests, it is worth keeping in mind that such correlations require evolutionary timescales - they are a real issue when comparing Native Americans and Chinese, but less of a problem when comparing populations in New Yorkers and Detroit.

Suggested Reading
I suggest starting with the Wikipedia article on the Experiment design or an equivalent chapter in a biostatistics textbook. Statistics community Cross Validated is rather welcoming to biostatistics questions. Finally, there are many good statistics and biostatistics textbooks - the obstacle is usually not the availability of materials, but the level of math and abstraction.

The reason why I am asking on a biology forum is because 1. geneticists have for sure thought about that (and master the relevant statistics), 2. I am interested in what geneticists do, what statistical methods they use, whether and how they are able to distinguish heredity from genetics. I am sorry but your answer does not really help answering the questions I raised.

@bixiou you asked a very general question - one cannot describe all possible statistical methods used in genetics in a short answer. Try to ask a more specific question, and also give an idea on how much background you have in genetics and statistics. Alternatively, you may consult books, such as https://www.springer.com/gp/book/9780387953892

I have a good background in statistics but close to none in genetics. Thank you for the reference! Don't you know a reference that studies more specifically the problem I am talking about? I guess there must be some papers about the models I described.
As for a more specific question, it would be the following: when an article claims that a trait is (partly) genetic (because some share of the variance is explained by genetics), should we interpret this literally? Or could it be that the trait is hereditary but not genetic? And if it is truly genetic, how do we know it's not just hereditary?

PS: your book may contain the answers to my questions, but I don't have time to read an entire book, so I'd like to know what chapter to read. That's the reason why I am on this forum: I don't know what keywords to search with on Google Scholar, and similarly I don't know where to look at in the book.

@bixiou three people tried to answer your question, but it seems that none of us understands what you are really asking. You know better what your question really is, so try reformulating it, and adding some references, so that we can have a better idea of what you mean.

I think I got the source of the confusion. I checked the wikipedia page of 'heredity' and in turns out it does not mean what I thought. I don't know what word to use then: what I mean by 'heredity' is "transmitted by the parents" (including adoptive parents), but that can be socially rather than genetically transmitted, genetic for me is just a subset of hereditary.

@bixiou - that's environmental, language is a fine example. The reason for our confusion is that often biologists have a very strong understanding of genetics and heredity and use those terms to mean specific things... hence my answer talking about factors that we don't know about yet.

@bixiou Re: "when an article claims that a trait is (partly) genetic (because some share of the variance is explained by genetics), should we interpret this literally?" Sometimes yes, sometimes no. As Roger points out, It depends on how well the experiment and statistical analysis were designed and executed. If you don't feel you can evaluate this yourself, you might want to stick to review articles and textbooks, where someone has already done at least some evaluation and vetting.

Thanks @Armand. Suppose it is well done. How is it done?

Some papers that should help and provide further info in their refs:
An oldy but goody:
"Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results" (1995) Eric Lander & Leonid Kruglyak
Here's a discussion of techniques involved, with an emphasis on linkage analysis but discussing association studies as well:
"Genetic linkage analysis in the age of whole-genome sequencing" (2015) Jurg Ott, Jing Wang, and Suzanne M. Leal
A more recent example:
Höglund, J., Rafati, N., Rask-Andersen, M. et al. Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers. Sci Rep 9, 16844 (2019).

Thank you @Armand! These references should answer the question. I'll probably accept this answer once I have read them.


text:
How do evolutionary forces influence the number of copies of the p53 gene?
p53 is an important tumor suppressor gene. Around 50% of cancers are associated with loss of function in p53.
Humans have only two copies of p53 in their genome (one on each homologous chromosome). Elephants on the other hand have 20 or so copies of p53, and they also rarely die of cancer.
From an evolutionary point of view, I find it very curious that humans (and most other animals, I guess) haven't evolved more copies of p53 on their genome. Duplications of genes happen all the time, so there is variation in copy number for natural selection to work upon.
Are there known to be evolutionary forces at play (e.g. positive or balancing selection) which determine the differences in number copies of this gene between species?

Natural selection can only work on variability already present. Since there is only one copy of p53, I would suggest that perhaps a duplication of this gene is incredibly rare to start with, and even if we accept the premise that having an extra copy of p53 would prevent certain cancers, why would that measurably affect reproductive fitness? Remember that a part of natural selection involves surviving to pass on beneficial gene variants, or on the other hand not surviving to pass on detrimental ones.

I think this could easily be reframed into a very interesting question along the the lines of 'Do evolutionary forces determine the number of copies of the p53 gene in different species'. It seems a shame to be closed.

https://elifesciences.org/articles/11994

With the upvotes and edits I think there's too much community support for this question to have my unilateral close stand, so I've reopened. I'd hope that answers to the question would focus on the evolution of copy number of these gene in other species, and upregulation experiments in humans, rather than rehashing what we have already answered in https://biology.stackexchange.com/questions/35532/why-do-some-bad-traits-evolve-and-good-ones-dont

I agree with user438383, but think this needs more work on your part. In particular, a summary with references of what is known about variation of p53 copy number (and cancer prevalence) throughout animals seems needed. I think you should show that duplication of p53 is relatively easy and that increasing p53 copy number does suppress cancer (or at least correlates for more than one exceptional species). As a start I would read about this on wikipedia, in the paper linked above, and at Nature.

@BryanKrause I think you were right originally to close a question that is only answerable by opinion or challenging its premises, as has already been done for questions of a similar type.


text:
How did we do the COVID PCR after its first appear?
I recently learned about the PCR testing and its idea of using primers to replicate the DNA or RNA. By this I assume that we need to know the sequencing of the DNA to make our primers. If that is true; then how did we do the COVID PCR in the early days of the pandemic? Is it possible to do the sequencing on a sample without amplifying it first with PCR?

Indeed, one can sequence genome directly without prior amplification - this is usually referred to as shotgun sequencing. Obviously, this is a time-consuming and costly approach. Therefore, once the biomarker of interest is identified, one focuses on amplifying and detecting only this biomarker.
Note also, that there exist generic sequencing primers, which could, with high probability, initiate DNA synthesis for preferred type of organism/virus.
Remark
@bob1 has pointed in the comment that what we call time consuming and costly is relative: e.g., sequencing human genome costs <\$1000 per sample, and takes a couple of hours to run - in this sense it is not too costly to be done in a research lab, but it is still quite costly in terms of everyday testing of millions of people. The cost of commerically available PCR tests for covid-19 is about \$50-\$100.

These days people just do whole genome sequencing for something like this. It's not particularly costly (<USD$1000/sample), and sequence agnostic - a bunch of blunt-end ligations to get the library prep done, then put it on the machine. ~2h-3d later you get the results, 1h analysis.

@bob1 I added a clarification, taking into account your comment.

I was more meaning in the context of the OP's question which boils down to "how did we get the initial sequence to design the primers" The answer is: it was done by whole genome sequencing. I've just had a look at the cost of a miSeq run, and it's about $2000 - you can get 96 samples on that, so about $20/sample, but not as simple as quick or as automated as PCR can be.

@bob1 I understood the question as asking whether we could sequence without amplification. But to identify the specific sequences corresponding to the virus one probably had to sequence everything that was in the sample - this is probably what you mean.

You can't sequence 96 full human genomes on a MiSeq.  I don't think you can do one.

As an extension of Roger Vadim's answer and bob1's comment, note that preparation of DNA libraries for shotgun sequencing often does involve PCR, but the PCR does not use primers that are specific to the sequence of interest. Rather, the primers are either random or specific to so-called adapter sequences that are appended to the ends of genomic DNA fragments in a mostly random fashion. An example of such a workflow would be...

Obtain genomic material from a pure culture of your organism / virus of interest
For genomic DNA, fragment genomic material to a desired insert size. For RNA genomes, use random primers to carry out reverse transcription.
Treat your DNA/cDNA libraries with a pool of enzymes that makes the fragment ends amenable to ligation of adapters. This process is often called "blunting and A-tailing".
Ligate adapters to the ends of treated fragments.
PCR amplify your DNA libraries using primers that recognize the specific sequence of the adapters. This creates DNA fragments that contain genomic DNA flanked by the sequences of your choosing. Often, this appended DNA will include sequences needed by your sequencing platform (read up on bridge amplification in context of Illumina sequencing) as well as short "barcodes" that identify your DNA library as being associated with a specific biological sample.

Once you've got your "reads" from the DNA sequencer, you can use those reads to construct a complete genome in a process known as de novo assembly. If everything goes right, you now have a genome against which you design primers for faster, targeted PCR detection.


text:
why do some trees have trunks that branch out and others don't?
I've never seen a bald cypress that had a tree fork but oak trees have them all the time.
Any ideas as to why this is?
Bald Cypresses are usually found in very wet areas whereas oak trees tend to be found in more comparatively arid areas so maybe having lots of tree forks and a very wide crown helps catch precipitation in the leaves so that it might fall at a more controlled pace onto the soil below and be less likely to run off, away from the trees root system?

All conifers tend to have a primary leader , less pronounced in other trees . Although no rules- eg. pin oak will tend to be pyramidal with a primary leader.

There are apparently growth "rules" imbedded in the genome.  These determine branching patterns, among other things.  These rules can be quite simple, yet give rise to complex morphology.
You might look at L-systems, which are rules (or perhaps one might regard them as programs) that can be used to reproduce the growth patterns of plants on a computer.  The classic work, I think, is "The Algorithmic Beauty of Plants" by  Prusinkiewicz et. al.  It can easily be found as a free pdf.


text:
What is this very tiny insect that was in my bedsheets?

I found it in my bedsheets. I'm in Bordeaux, France. It is 3mm long and is the only one that I found.
Should I be worried that there might be others? If so, what should I do?

Related: Can anyone help confirm this tiny insect larvae?, Bug Identification: Is this small tubular, black bug..., How to protect my mounted insect specimens..., Varied Carpet Beetle Larvae, What is the name of the critter depicted..., What small insect is this?, What bug is this...

That is almost certainly the larva of a carpet beetle, likely the Furniture Carpet Beetle (Anthrenus flavipes). They are distinctively hairy and striped.

(image from wikimedia)
Carpet beetles are found world-wide and are a pest of homes, workplaces, museums, basically anywhere that textiles, paper, or foods are contained. They will happily eat wool, silk, fur, hair, bone and shell (e.g. tortoise shell, not sea-shell).
Getting rid of them is difficult - you need to clean out any areas where they can live, this includes all your clothes (hot tumble-dry for 1 h, or keep in sealed bags for 2+ months), any natural-fiber carpets, cupboards, furniture - literally anywhere dust can accumulate. Often easiest to get a pest-control expert in to deal with them.

Although for items that are small enough, keeping in the freezer overnight would be more than enough, no need to ruin your clothes. They do not cause as much damage (relative to their population density) as clothes moths in my experience.

@CaroZ True, freezer should work, but the internets are telling me at least 48h, and that dry-cleaning and ironing should also work.


text:
Extrapolating rarefaction curves
I am interested in methods for extrapolating rarefaction curves and/or estimating the true species richness. The ecosystem of interest is the gut microbiome and extrapolation is to higher sequencing.
Chao estimator
The ubiquitous approach is the one based on Chao estimator (see Eqs. [7] and [17-19] in this review). However this approach has been recently criticized, since it assumes that the undetected species have the same abundance as the rarest detected species - therefore, at best, it gives only the lower bound for the diversity.
Hill numbers
I am not convinced that using other diversity metrics (most fo which can be represented via Hill numbers) solves the problem. Indeed, most of these metrics have better statistical properties than richness (=number of species), since they give more weight to observe species over the unobserved ones - essentially, they hide the problem under the carpet.
Alternative 1: Using Relative abundance distributions
Making an assumption about actual species abundance distribution (e.g., assuming it to be log-normal or Fisher log-series - whatever is applicable) seems promising. However I have not found any solid publication describing such an approach.
Alternative 2: Comparing rarefaction curves
Alternative approach, employed in package MOMR, is using the rarefaction curves for many samples to extend the other rarefaction cruves.
Question
I am looking for guidance (preferably references with sufficient mathematical details) regarding the two approaches listed above, as well as for possible other alternatives.

Quick question: Are you interested in developing a novel method of estimating true richness, evaluating different methods, or are you simply analyzing your own data and trying to find the best estimates to report? For a community like the gut microbiota, the methods used in sample collection, storage, DNA extraction, sequencing technology, and sequence assembly/curation etc., will probably impact the richness estimates more than the specific diversity metrics used in the final analysis.

@MikeyC I am interested in evaluating different methods. Ultimately, these estimates will serve as a biomarker (one of several) for specific health conditions, so it will be used with extensive amounts of data. For a moment I see that the estimates vary rather wildely... (even though I agree with your assertion that there are plenty of other sources of errors).


text:
What is this bug? Singapore

enter image description here

Around 1 inch in length

is this all the information you have? one inch long and lives in singapore :)

I have the pictures. What more should I include?

please take a look here https://biology.stackexchange.com/tour

does the bug live in water or on land,what type of habitat,indoors or outdoors,did you see it at night or during the day.simply any details you can provide will help us help you.

Looks like an Orthoptera species.

This is an orthopteran insect. Well known members of this insect order are grasshoppers, locusts and crickets.
You can recognize them by their

greatly developed femurs specifically adapted for jumping,
hardened forewings (called tegmina), which protect the membranous hindwings folded beneath them,
long, filamentous antennae,
two cerci (appendages at the tip of the abdomen),
chewing mouthparts (with which they chew on plant material such as leaves and stems) and
prominent compound eyes.

Orthopterans undergo incomplete metamorphosis, progressing through egg, nymph and adult stages. Nymphs closely resemble adults, but lack fully developped wings and reproductive structures. As this specimen has fully developped wings, we can conclude it must be an adult.
Moreover, I assume this specimen belongs to the suborder Caelifera as antenna are shorter than the body (as opposed to their sister taxon Ensifera which have more-than-body-long antenna).


text:
Ensuring all individuals are genetically identical before experiments
I am a beginner in experiment design so please correct me if I made any mistakes. If we want to study the behavioral changes after a particular mutation of a gene, it seems to be a must for all individuals to be genetically identical before we induce the mutation (otherwise those changes may not be caused by the mutation, but other genetic variants)
For example, if we are using fruit flies for genetic study, we need to enclose them (with food and air) such that they can only mate over many generations in that container.
Question: After many generations, supposedly a very large number offspring which has very similar genetic makeup can be generated ready for mutagenesis. However, may I ask how to test whether they are 100% genetically identical? I have thought of gene sequencing, but is highly impractical since there is a very large population involved.

For fruit flies one usually wants pure lineages for specific alleles, corresponding to distinct phenotypes. One cannot arrive to such a state by merely enclosing the flies for many generations - in this case one will quickly end up in the situation of Hardy-Weinberg equilibrium, where all the alleles are present in constant proportions, not changing with time. Of course, in a finite population one expects that eventually one allele fixes  itself, but that may take a rather long time in absence of selection. Thus, in practice one separates the desired phenotypes in every generation, and and makes them breed among themselves. In fact, this is pretty much what Mendel did with peas to obtain pure lineages - it is worth reviewing this chapter.
Now, it is always risk that the population is not 100% pure, just as there is always a possibility that other genes contribute to the trait of interest. Here is where the (bio)statistical analysis comes in: testing for significance of the effect and filtering out random effects.
Update
Just to provide a quick calculation: suppose that we have alleles A and a, with A being the dominant one. In every generation we remove the undesired genotype aa. Initially we have the genotype frequencies of  AA,Aa,aa given by $P, H, Q=0$,
where $P+H=1$. The allele frequencies are $$p=P+\frac{H}{2},q=\frac{H}{2}$$
After crossing we obtain the allele frequencies $p^2, 2pq,q^2$, which after removing the aa genotype give:
$$
P'=\frac{p^2}{p^2+2pq}=\frac{p}{p+2q}, H'=\frac{2pq}{p^2+2pq}=\frac{2q}{p+2q}
$$
The new allele frequencies are
$$p'=\frac{p+q}{p+2q}=\frac{1}{1+q}, q'=\frac{q}{p+2}=\frac{q}{1+Q},$$
where I used the fact that $p+q=1$.
More generally, the frequency of the unwanted allele in generation $t+1$, in terms of the frequencies in the previous generation, is given by
$$
q_{t+1}=\frac{q_t}{1+q_t}
$$
The solution to this difference equation is
$$
q_t=\frac{q_0}{1+tq_0}.
$$
Now, if we want the frequency of the unwanted allele to be below teh desired threshold $\alpha$, we must solve inequality $q_t<\alpha$, obtaining
$$
t>\frac{q_0}{\alpha}-1
$$
generations. A good choice of $\alpha$ is $1/N$, where $N$ is the number of individuals in the population (than after $Nq_0-1$ generations we are likely to have no more than one individual carrying the minority allele).
Remark
A similar calculation can be found in connection with strong selection, under conditions of complete dominance: if $s=1$, the aa genotype is completely eliminated at each generation. See, e.g., Introduction to Quantitative Genetics by Douglas Falconer.

People have already done the inbreeding over sufficient generations for plenty of fast-breeding model organisms, and you just buy your initial stock from a company, with the understanding that some small amount of genetic drift may occur over time.

Normally the companies/organizations that supply inbred animal strains take precautions to minimize drift, such as keeping a large stock of frozen founders and periodically refreshing their working populations from those.  They also monitor their working populations' genomes, these days presumably by whole-genome sequencing.  Details vary by species and organization.


text:
Difference between heritability on the scale of liability versus the scale of observation
I was reading a paper on disease heritability ("Estimating Missing Heritability for Disease from Genome-wide Association Studies") and it struck me that I don't have a great understanding of the differences between heritability on the liability scale and the observed scale. The main thing that I've read about is how the liability scale operates on an assumption of normality (since traits are treated as being continuous) making it unimodal and only appropriate for multifactorial disease. However, I'm not sure if I've caught on to the full extent of the difference.
Any input would be appreciated, even if it's just pushing me in the direction of a useful resource :)

Welcome to Biology.SE. Does this page from our sister Bioinformatics site help? OR maybe this page?


text:
Evolution of Aging according to Weismann
Several authors agree to the fact that August Weismann was the first to propose an explanation to biological aging (Kirkwood and Cremer, 1982; Gems and Partridge, 2013).
A lot of hallmarks (and some contradictory) are pointed out about Weismann along his life, which I am reflecting only in these

When he suggested that group selection was the answer of aging;

August Weismann and Alfred Russel Wallace proposed that aging has evolved to remove worn-out older individuals, thereby reducing competition for scarce resources and resulting in benefits for the species. However, such an evolutionary mechanism would require group selection of a sort that makes this an untenable scenario. (Gems and Partridge, 2013)

the reason suggested by Weismann for the evolution of ageing was an adaptive one, namely that ageing is beneficial in ridding a species of old and decrepit individuals which would otherwise compete for resources with younger ones. Thus, by natural selection the somatic cells of the organism would have come to lose their capacity for unlimited survival, and ageing of the organism as a whole would have appeared. (Kirkwood and Cremer, 1982)

I don't understand how any of those arguments can justify the evolution of aging

they claim that group selection was responsible for the evolution of aging but it doesn't explain how older individuals get old.. they are just removed from the population because they got old, it doesn't  seem to explain the evolution of ageing.

When he developed the concept of panmixia to reshape his nonadaptive theory (or neutral) of biological aging.

The central component of Weismann's non-adaptive theory of ageing was the principle of panmixia which he developed [...] In brief, this principle states that as soon as any character becomes useless to an organism, natural selection ceases to operate upon it and it begins to disappear. (Kirkwood and Cremer, 1982)

How the concept of panmixia is related to the evolution of aging?

is that because since post-reproductive period does not contribute to the evolution of the species, the potential of immortality of somatic cells desapear? It doesn't make much sense..

References

Gems, D. and Partridge, L. (2013) ‘Genetics of longevity in model organisms: Debates and paradigm shifts’, Annual Review of Physiology, 75, pp. 621–644. doi: 10.1146/annurev-physiol-030212-183712
Kirkwood, T. B. L., & Cremer, T. (1982). Cytogerontology since 1881: A reappraisal of August Weismann and a review of modern progress. Human Genetics, 60(2), pp. 101–121. https://doi.org/10.1007/BF00569695

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.

think I got it..
if I may I would like to answer this question since it could be helpful to anyone who's interested in this field of research.

Regarding the first question: " how any of those arguments can justify the evolution of aging "
Weismann presented a notion of group selection as a possible answer to biological aging, proposing that such mechanism becomes advantageous for the species by removing the most geriatric individuals.
how those arguments can justify the evolution of aging:  on the hypothesis that if all individuals were immortal, they would be competing with the younger ones for the available resources.

if individuals did not die they would soon multiply inordinately and would interfere with each other's healthy existence. (Weismann, 1891)

Thus, by natural selection the somatic cells of the organism would have come to lose their capacity for unlimited survival, and ageing of the organism as a whole would have appeared. (Kirkwood and Cremer, 1982)

Regarding the second question: " How the concept of panmixia is related to the evolution of aging? "
essentially it is used to justify the aforementioned concerning somatic immortality, that is, the cause of cellular aging.
when applying this concept of panmixia to the post-reproductive period, aging can arise, as this is a period that does not contribute to the evolution of the species. Thus it can be considered as an inert physiological interval, such that the potential of somatic immortality starts to disappear.

[Weismann speaking about reproduction] As soon as the individual has performed it’s share in this work of compensation, it ceases to be of any value to the species, it has fulfilled its duty and may die.
(Weismann, 1891; p. 10)

As soon as natural selection ceases to operate upon any character, structural or functional, it begins to disappear. As soon, therefore, as the immortality of somatic cells became useless they would begin to lose this attribute.
(Weismann, 1891; p. 141)

it's also important to mention, as a side note, that for Weismann, natural death arises due to the absence of cell renewal, which causes the wear of the histological tissue and thus the concept of panmixia justifies the limited number of cell division.

References
Kirkwood, T. B. L., & Cremer, T. (1982). Cytogerontology since 1881: A reappraisal of August Weismann and a review of modern progress. Human Genetics, 60(2), pp. 101–121. https://doi.org/10.1007/BF00569695
Weismann, A. (1891). Essays upon heredity and kindred biological problems. Volume I. Oxford: Clarendon Press.


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Why Account for Phylogeny when using Relative Brain Size as a Surragate for Intelligence
This paper tries to relate intelligence, life history, and urban fitness of birds. They use relative brain size of each species as a surrogate measure of intelligence. Although this may not be the most accurate method, I understand why they used it. What I do not understand is why they used the method to calculate relative brain size that they did.
Rather than using the absolute relative brain size, they used "residual from a log-log phylogenetic Generalized Least Square regression... of absolute brain size against body mass". This means that relative brain size of a species is regarded as how large its brain is compared to its body size, compared to other species in its taxon. So if a species has a large brain and is part of a taxon that in general has larger brains could get a lower score than a species that has a small brain and is part of a taxon that in general has smaller brains.
Why is this not a problem?

It seems they were attempting to correct for other behaviors/ecological niches that were correlated with brain size, but were not related to "urban tolerance". Their work includes much data on niches, behaviors, breeding strategies, etc, not just "urban tolerance".  Presumably, related species would share similar brain-size effects from these confounders, so residual differences could be correlated more specifically with "urban tolerance".
The authors comment:

Because brain size correlates with these traits, failure to properly
account for such additional drivers may mask the effect of brain size
on urban tolerance. For example, if a large brain affects tolerance to
urbanization by facilitating broader niches (Ducatez et al., 2015; Sol
et al., 2016), including a measure of niche generalism in the model
can block the effect of the brain on urban tolerance.

They are trying to correlate a quite crude measure (brain size) with a specific behavior ("urban tolerance"), which as you suggest raises all sorts of methodological questions.

I understand why they included factors such as niche breath in their model, but that does not explain why they used this calculation of relative brain size during data collection. I see no reason they could not have used absolute relative brain size and these other factors in their models.

I would think it's because they wanted to account for even unknown factors, but am not sure. Why not write the authors and ask? Researchers usually welcome intelligent questions about their work.


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Is Haemoglobin a positively charged Sol?
My book NCERT(Class 12, Surface chemistry) claims that hemoglobin is a positively charged sol.

The cytosolic pH in human cells is around 7.4, but fluctuates through the cell cycle
according to this article the isoelectric point of Hemoglobin behaves as follows:

The more nearly free a preparation of hemoglobin is from
nonhemoglobin protein the more nearly does the isoelectric point
approach 6.8,

So if the isoelectric point is 6.8 for Hemoglobin and pH of cytoplasm is 7.4 so wouldn't be Hemoglobin a negatively charged sol?
As we know in blood, proteins exist as negatively charged species so blood is termed as negatively charged sol, so is there a point I am missing?

This may be more appropriate for chemistry.stackexchange.com.

@MaximilianPress protein structure of membranes  is determining the charge here, as biology is more concerned with things like protein structure, I thought it might be better to post here

It's a bit of a value judgment. For the record, I would suggest looking into the different forms of Hb (oxy, deoxy, carboxy) and their ternary structure as oxygenation reduction status etc. should play a role. I am not a chemist but there are a variety of publications in chemistry journals investigating isoelectric behavior of these different forms: https://www.sciencedirect.com/science/article/pii/S0021925818745547/pdf?md5=e2e6c1800015a0907b237e8b32f49569&pid=1-s2.0-S0021925818745547-main.pdf, https://www.jbc.org/article/S0021-9258(18)61920-9/pdf, https://pubmed.ncbi.nlm.nih.gov/7324711/

There is a major problem with the item list, hemoglobin is not the same as "blood". In blood, hemoglobin is contained with RBCs  and not floating everywhere. Let me show how this can cause a HUGE difference:

Whether hemoglobin is negatively or positively charged will not affect the blood; because it is contained with RBCs whose membrane is negatively charged and doesn't depend to a large degree on its contents. However, blood is actually negatively charged and the main contributor to this is Heparin (negatively charged anticoagulant protein), the RBCs membrane is negatively charged preventing adhesion to themselves and negatively charged membranes of other cells (anti-coagulation mechanism)
intracellular pH of RBCs is around 7.1 (1). the isoelectric point of haemoglobin is a bit of trouble to agree on because actually the alpha chain of hemoglobin has isoelectric point of (7.5–7.8) while beta subunit is (6.1–6.7) (2). I didn't find a source assessing the in-vivo charge of hemoglobin or electrophoresis at physiological pH, even though if electrophoresis at physiological pH is present, it won't be a good indicator because isoelectric point can vary in-vivo as there are many acids other than H+. I would like to quote the following paragraph from National Academy of Sciences (US) and National Research Council (US) Division of Medical Sciences. Conference on Hemoglobin (3):

Near the physiological pH probably all of the charges on hemoglobins
come from their constituent amino acids. Neutral amino acids
contribute one terminal carboxyl and one terminal amino group to each
polypeptide chain which is not a ring. Additional positive charges are
contributed by the nitrogenous groups of the three basic amino acids,
Rb. Additional negative charges are contributed by the second
carboxyl group of aspartic and glutamic acids, Ra

pH at which several amino acid in Hemoglobin ionize:

References :

Swietach, P., Tiffert, T., Mauritz, J. M., Seear, R., Esposito, A., Kaminski, C. F., Lew, V. L., & Vaughan-Jones, R. D. (2010). Hydrogen ion dynamics in human red blood cells. The Journal of physiology, 588(Pt 24), 4995–5014. https://doi.org/10.1113/jphysiol.2010.197392
Devineau, S., Inoue, K. I., Kusaka, R., Urashima, S. H., Nihonyanagi, S., Baigl, D., ... & Tahara, T. (2017). Change of the isoelectric point of hemoglobin at the air/water interface probed by the orientational flip-flop of water molecules. Physical Chemistry Chemical Physics, 19(16), 10292-10300.
National Academy of Sciences (US) and National Research Council (US) Division of Medical Sciences. Conference on Hemoglobin: 2–3 May 1957. Washington (DC): National Academies Press (US); 1958. THE STRUCTURAL BASIS OF DIFFERENCES IN ELECTROPHORETIC BEHAVIOR OF HUMAN HEMOGLOBINS. Available from: https://www.ncbi.nlm.nih.gov/books/NBK224284/

Ok ,then can you explain then if the isoelectric point of haemoglobin in 6.8 , how can it have a net positive charge at physiological ph of cytoplasm of 7.2, Is the data of isoelectric point for Haemoglobin incorrect?

@Samardeepsingh, I edited the answer


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Damselflies: which exact species of Coenagrion
I recently took the following pictures of Coenagrion spp.(6th of June, in Versoix forest (small pond), Geneva area, Switzerland, Alt: ~450m).
Picture detailed & cropped:

For the identification, I hesitate between two species:

Coenagrion pulchellum
Coenagrion puella

The male one seem to be Coenagrion puella while the female one has black patterning like a Coenagrion pulchellum.
I read in a book (Les Libellules de France, Belgique, Luxembourg & Suisse from Jean-Pierre Boudot, Daniel Grand, Hansruedi Wildermuth et Christian Monnerat) that the male Coenagrion pulchellum can have very similar field marks to male Coenagrion puella (for example the typical black U-shaped marking).
Which species are these — is it possible that the two species can crossbreed (male = Coenagrion puella and female = Coenagrion pulchellum) or are the female field marks a more reliable indicator of the species for both (male and female = Coenagrion pulchellum in this case)?

I corrected the formatting for the scientific names — if you are interested, this is an introduction to scientific naming conventions and these are the complete "rules". I also edited your post for concision and clarity.

Yes, thanks for your edit, in fact I never know how to format latin names in SE sites (I often make a draft in an external text editor before), but for sure my question looks better now. Also, I am not a native English speaker, then thanks for the corrections/rephrasing :).


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Relative abundance and action of 5p and 3p microRNAs
I am a beginner in genetic research and am currently conducting a project concerning microRNAs. Let's say we have miR-1-5p. If miR-1-5p is upregulated in a disease, will miR-1-3p always be downregulated in the same disease? Or will it also be upregulated?
In addition, will miR-1-5p and miR-1-3p have any difference in functions? Or will they always target the same target genes and induce the same cascades with the same resulting effects?
I have been reading some sources but keep getting confused.

Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.

The reason I think you have not received any answer to your question yet is that it is unclear. What precisely is your research project? When you talk about mir-5p being upregulated, are you describing actual RNAseq results or are you just considering a  hypothetical situation with increased transcription of the precursor? You talk about targetting genes, but it is the mRNA that is targetted, answering your second question. See also here.

It's best to think of miRNAs on a case-by-case basis. Canonically, miRNAs are thought of as negative regulators of their mRNA targets via the RISC complex, but some miRNAs can have a protective effect on their targets in some contexts.  As with much of biology, there aren't any hard-and-fast rules concerning miRNA function relative to their target site.


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does more biomass mean more energy?
I am a high school student and I am very confused about ecological pyramids. My textbook states that the biomass of zooplankton in an aquatic ecosystem is more than that of phytoplankton (I don't know why?) But if I just memorize it then I think that their energy pyramid should also be inverted because more biomass would mean more organic matter {food} and hence more chemical energy available to the next trophic level. This should be true if we are considering all organisms present at a trophic level and not a single organism at each trophic level, right? So why is the energy pyramid always upright? Shouldn't it be the same as the biomass pyramid?
Please explain in simple language using examples; it would be very helpful.

Can you please provide a quote or other source? I suspect you might be misreading your textbook, since phytoplankton is so incredibly abundant.

tl;dr I think you're right and your textbook is wrong. It would be interesting to know (a) what textbook this is (maybe it's the same as the one I quote below?) and (b) what your teacher says if you ask them this question.
In general the energy content of a trophic level is roughly proportional to its biomass (although in going from terrestrial plants to animals we might expect the energy/gram to increase, since terrestrial plants contain a lot of energy-poor structural material). Both energy and biomass would also be proportional to numbers if individuals in each trophic level were approximately the same size (this can go in either direction; whales are much bigger than the plankton they eat, beavers are much smaller than the trees they eat ...)
For oceanic phytoplankton and zooplankton respectively, some reasonable mass/energy conversions are phytoplankton: 2-3 calories per milligram (cal/mg) dry weight (Platt and Irwin 1973); zooplankton: 3-9 cal/mg dry weight (Davis 1993). (ZP are about 3x more energy-rich than PP.)
In my view energy pyramids as well as number pyramids can be inverted, despite what this open-source biology textbook (ref below) says:

Pyramids of energy are always upright, since energy is lost at each trophic level; an ecosystem without sufficient primary productivity cannot be supported.

As detailed below, I think this statement is wrong. The energy loss tends to make energy pyramids a little bit less top-heavy than biomass pyramids, but they can be inverted for exactly the same reason that biomass pyramids can.
The book shows an inverted biomass pyramid:

And explains it as follows:

However, the phytoplankton in the English Channel example make up less biomass than the primary consumers, the zooplankton. As with inverted pyramids of numbers, the inverted biomass pyramid is not due to a lack of productivity from the primary producers, but results from the high turnover rate of the phytoplankton. The phytoplankton are consumed rapidly by the primary consumers, which minimizes their biomass at any particular point in time. However, since phytoplankton reproduce quickly, they are able to support the rest of the ecosystem.

This argument should apply equally well to energy.
In other words, the amount of biomass or energy present in the lower trophic level (phytoplankton) at any moment in time (also called the stock or standing stock) is less than the energy present in the upper trophic level (zooplankton), but the flow of energy is constant (minus losses due to conversion inefficiency).
In particular, if we take the English Channel values (4 g dry mass/m^2 PP; 21 g/m^2 ZP) and convert (g/m^2 * (1000*cal/mg) = cal/m^2) we get at most 3*4*1000 = 12000 cal/m^2 for PP and at least 3*21*1000 =  63000 cal/m^2 for ZP, so the pyramid is still inverted. (In fact, since ZP are generally more energy-rich than PP we would expect the energy pyramid to be more top-heavy than the biomass PP; here I have used the most conservative numbers possible, the top end of the range for PP content and the bottom for ZP content, which happen to be the same.)
For example, suppose individual phytoplankters (yes, that's the word for an individual organism in the phytoplankton) and zooplankters are the same size/contain the same amount of energy (not true, but an OK simplification here), and that there are 10,000 phytoplankters and 90,000 zooplankters per cubic meter of water. The phytoplankters reproduce so fast that each ZP can eat 10 PP over the course of its lifetime without depleting the PP population. In one ZP generation (= 10 PP generations), 100,000 units of energy come into the PP (through photosynthesis) and are eaten by ZP (with a 10% loss due to trophic inefficiency); that's enough to maintain 90,000 zooplankters.

Ecosystems. (2021, March 6). Retrieved September 3, 2021, from https://bio.libretexts.org/@go/page/12640
Davis, Nancy D. “Caloric Content of Oceanic Zooplankton and Fishes for Studies of Salmonid Food Habits and Their Ecologically Related Species.” Fisheries Research Institute, University of Washington, 1993. https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/4192/9312.pdf?sequence=1.
Platt, Trevor, and Brian Irwin. “Caloric Content of Phytoplankton.” Limnology and Oceanography 18, no. 2 (1973): 306–10. https://doi.org/10.4319/lo.1973.18.2.0306.


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Spider of the American continent spotted Europe. Is it expected?
While hiking in a nature reserve in Bulgaria I saw a big yellow and black spider. I took some pictures and when I went back home I did some searches and identified it as an Argiope, common name is Yellow and Black garden spider.
The description matches, the body was almost as big as the upper phalanx of a thumb. But the Wikipedia page states that it is native of the American continent. Is it an invasive species? Is it common to find it in Europe?

Argiope is a cosmopolitan genus (the link is for the genus, not the individual species you linked).
Argiope species A. bruennchi, and A. lobata are found in Europe in particular. Based on your photos I think this is likely to be A. bruennchi rather than A. lobata, as it has strong yellow and black bands and lacks the lobed edge of the abdomen of A. lobata.

Yes, may be an A. bruennichi. One small doubt is that the body size was about the double of the average size of the female.


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When doing crosses (Punnett square) with drosophila, how can you be *sure* your parents are *pure lines*?
In plants, when someone wants to confirm that the parents are pure lines (homozygous) for the alleles studied, the person can self pollinate the plant to make sure that the descendants are identical to the parental plant. (See How to confirm pure-breeding parents)
In drosophila, self-reproduction is not possible so how to make sure that the parental strains you are breeding are indeed homozygous for an allele (in an efficient way, I don't want to breed drosophila for 'a lot of successive generations')?
E.g., assuming N is dominant and n recessive, if I have a male (NN) and a female (NN), then the F_1 is all (NN). But, if it happens that I have females that are (Nn) then, all offspring will look like (phenotype) their parents (NN and Nn), but they will have different genotypes. To make sure that the parents are homozygous, should I also verify with the F_2 or the F_1 is good enough? In other words, what is the most efficient way to verify that the parents are indeed homozygous?
F2 of F1 (NN) cross from parents (NN) = (NN) (should I be doing a third cross to make sure?)
F2 of F1 (NN and Nn) cross from parents (NN and Nn) = (NN, Nn and nn) => some males (Nn) will mate with females (Nn) giving (NN, Nn and nn) thus confirming that I didn't start with pure lines.
Thus, it really seems to be a long process to find the homozygous parents in the first place as you never know in advance if you have homozygous parents when you breed them. You have to pick individuals that you think are homozygous and test them until all the offspring are identical to the parents no matter how long you do it. Is that correct?
Another point here would be to calculate the level of 'confidence' in which we have a pure line. Can we calculate that (and what would be the test to verify that)?

A very similar question that came up yesterday: https://biology.stackexchange.com/q/104329/59521

I looked at the answer and it says 'it is always risk that the population is not 100% pure'. My question therefore is how can we calculate our confidence in assuring that we generated a pure line? Basically, how many generations would be needed to be 'convinced' that we have a 'pure line'. Basically, how could I 'confirm' that I indeed have a pure line in an efficient way? Another answer was 'buy it from a supplier' but that is not the type of answer that I expect! I'm curious in knowing whether there is a systematic way for testing a pure line (with relative certainty) What is the standard?

One is usually acting on the assumption of random mating, which implies a sufficiently big population to avoid genetic drift - this includes such rare situations as you described (when all the males are NN, but an substantial part of females are Nn). As for the calculations - I suggest that you ask more specific questions, and show how you tried to do this calculation.

I added a simple calculation to the linked question. It is not exactly what you ask, but I hope it helps.


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Viruses in human history
How much do we know about ancient viruses and the viral evolution throughout the human history?
To my knowledge the HIV history has been rather well documented for about hundred years back (e.g., see here and here) - via the phylogenetic reconstruction, massive study of this virus since it was discovered, and the analysis of the records and blood samples from the countries where the virus first spread (before arriving to the West and being discovered).
Ebola has been well documented as well over the last half a century or so, although it hasn't changed much, since the repeated outbreaks are spills of very similar strains from the nature.
Finally, there have been obviously many viruses well documented since the advent of massive sequencing.
The question is thus about the viruses with longest history:

What are such well-documented viruses?
How much do we know about them?
How do we know this?
How much have they changed ? ( In terms of their danger to humans, e.g.)

Disclosure: the question is motivated by this one. Here is a somewhat similar question (but rather limited in scope).
Update
The article on early HIV spreading along rail- and waterways, mentioned in the comments.

I'd reckon that the evolutionary history of retroviruses can be traced back pretty far given their persistence and co-option in the genomes of their hosts.  I'll link sources if I can find any.

https://www.nature.com/articles/d41586-020-02083-0

Could you maybe be a little bit more specific about the sources of evidence you're interested in/would accept (e.g. archaeological/ancient DNA vs phylogenetic)?

@BenBolker thank you for this nature article - it is great! I am mostly interested in epidemiological angle: how the virus spread and how it evolved in human population. I think one cannot go far back without ancient DNA... but I may be wrong. (I recall that for HIV one could even trace its spread along the rail- and waterways in colonial Africa.)

Smallpox - not origins, but history, evolution are reasonably well known. Not really human, but also Orf virus (sheep, goats, also PoxV). No time now for full answer, will try to come back and write a more complete one later.

Influenza of course

@reuns could you give a reference? I mean genetic evidence.

@RogerVadim https://nextstrain.org/community/neherlab/allflu/h1n1_ha?m=div https://www.ncbi.nlm.nih.gov/genomes/FLU/Database/nph-select.cgi?go=database https://www.pnas.org/content/pnas/suppl/2009/07/13/0904991106.DCSupplemental/0904991106SI.pdf mostly for H1N1 but there are also strains such as A/FPV/Dutch/1927(H7N7) A/chicken/Brescia/1902(H7N7) A/chicken/Rostock/45/1934(H7N1)

We don't know a whole lot about the direct evolution of the genomes of many viruses yet, though as methods for recovery of ancient nucleic-acid sequences improve, I would expect to see increases in this sort of information over the next few years.
We do know the history and evolution of a limited number of viruses. Included in this are some of the common-cold coronaviruses, such as the OC43 type, which as been dated by molecular clock methods to have evolved all the current genotypes since the 1950's(1) (see fig below from paper).

One example that we do know about is Polio (Poliovirus, Picornaviridae), where we know for instance that it affected a number of people in ancient history. The most famous of these is probably the stele below from ancient Egypt, which shows the classic withered leg and crutch used by the subject of the stele. We don't have any genetic information about these cases though.

Compared with:

It is fairly likely that localized (e.g. city wide) epidemics of polio occurred prior to recent history, but there are no credible reports of mass epidemics beyond the early 20th century in Europe and northern America. Which may be an indication that, while it was a problem, until the advent of rapid travel and high density populations, polio was a localized event and possibly only limited numbers were exposed to it.
However, one virus that we do know a fair bit about genetically is Smallpox (Variola virus Poxviridae). This, as you probably know, was the basis for the very first true vaccine (cowpox for cross-protection), and was also the subject of variolation, a primitive form of vaccination using dried smallpox scabs, for some centuries before the advent of Jenner and Jesty(2).
In 2016 smallpox was found in a Lithuanian mummy dating back to the 1600's(3), at the time this was the oldest DNA evidence for smallpox, but a recent report in Science(4) provides complete genomes for smallpox dating back as early as AD 600 in Viking individuals, meaning that we can compare at least these viruses with those present at the time of elimination.
In addition for smallpox, we know that there were two forms, Variola Major and Variola Minor (alastrum). These differed in pathogenicity and survival rate, having ~1% for the minor form vs 30% for the major. It was thought by some that the minor form was the virus adapting to its host, but more recent analysis indicates(5) that it was likely merely phenotypic variation.

Lau et al. J Virol. 2011 Nov; 85(21): 11325–11337.
Hamarstein et al. Trans Am Clin Climatol Assoc. 1979; 90: 44–55.
Duggan et al. Curr Biol. 2016 Dec 19;26(24):3407-3412.
Muhlemann et al. Science. 2020; Vol 369, Issue 6502
Li et al. PNAS October 2, 2007 104 (40) 15787-15792