If some humans inherited 3% of Neanderthal DNA, why are we 99.9% same genome? Many sources say that humans are 99.5 to 99.9 percent the same.

Also some sources state that some humans have 3.4% Neanderthal DNA and some don't share those genes.

Why is that?

3% and 99.9% are from different calculation method.

20% (a rough estimation, might be wrong) of neanderthal DNA survived in the modern human genome, but it is 'diluted' by the human population,  which lead to 2 percent of neanderthal DNA in each human genome. This is the number 3%.

But how can we know it's neanderthal DNA?

If DNA fragment contains several neanderthal special SNP (single-nucleotide polymorphism), we will treat it as neanderthal DNA. (Based on linkage disequilibrium, the inference is reasonable.) The fragment might of tens of thousands nucleotides, but the difference are just one or two base.

But when we compare two human, we calculate the difference at nucleotides level, rather than DNA fragment. This is the number 99.9% come from.

If we have the complete genome of neanderthal and human, by comparing them at base level, the similarity might be great than 99%, I suppose.


Etymology of the term monilophyte I would like to know the origin of the term Monilophyta. I know it's from Kenrick and Crane, but where did they get monilo-? It's not in my enormous Liddell and Scott Greek dictionary, nor is there any word starting with ilo- or hilo- that seems at all likely. Is it from the Latin word "monile" meaning necklace?

This is driving me crazy.

Phylogeny and evolution of ferns (monilophytes) with a focus on the early leptosporangiate divergences:

  The monilophytes (= Infradivision Moniliformopses, sensu Kenrick and Crane, 1997⇓) share a distinctive vasculature, having protoxylem confined to lobes of the xylem strand (Stein, 1993⇓), therefore the Latin moniliformis appellation for “necklace-like.”


Do mutant alleles result from mutation of the wild type? The allele that encodes for the most common form of a phenotype in natural population is called a wild type allele and all the rest of the alleles encoding forms other than the wild type are called mutant alleles. Do they result from mutations of the wild type allele?

No, not necessarily!

The terms might be confusing I agree. The most common allele (the wild type allele) might be a mutant of one other type of allele (one mutant allele) present in the population.

The reason we call the least common alleles the mutant alleles is that beneficial mutations are rare compared to neutral or deleterious mutations. If at a given locus most mutations are deleterious, then the mutant alleles will never reach a high frequency. However, if at a given locus a beneficial mutation occurs, then this beneficial mutation will likely rise quick quickly in frequency and therefore there is only a limited time frame under which the most common allele is actually a mutant of a least common allele. In consequence, we tend to call the least common alleles "mutant alleles". This name is often a good fit to the reality but not necessarily.

Note by the way that there are other sorts of selection regime occurring at a given locus that may maintain polymorphism at relatively high heterozygosity such as any form of balancing selection.


How fast does activity affect synaptogenesis? How long does it take for the increased activity due to a novel stimulus to cause an increase in synapse generation?

There are many studies which show that the number of synapses in the brain increases within 24 hours of doing a novel task, so I know the number is less than 24 hours. I'm interested in questions like "If I do yoga for an hour, will the later part of the hour benefit from synapse creation caused from earlier in the hour?" Obviously I don't know if yoga in particular would benefit from said synapses, but if synaptogenesis is not up-regulated in less than an hour, then I can certainly rule such an effect out.

Synaptogenesis at such a fine temporal resolution is currently still best studied in animal models and reduced preparations where the activity levels can be more precisely controlled and advanced imaging methods can be used to monitor morphological changes. A series of studies with relatively high temporal and spatial resolution have been carried out in vitro and in vivo with two-photon microscopy on dendritic spines, which are considered as a proxy for the existence of synapses, since ~98% of them contain one.

The fastest effect after stimulation is the enlargement of pre-existing  or newly-formed spines and their synapses, as fast as ~2 min (Matsuzaki et al. 2004, Harvey et al. 2007, Hill and Zito 2013). Next, immature structures (often called filopodia) are starting to form within the first ~15 min (Maletic-Savatic et al. 1999). It is not yet clear what percentage of those structures bear an actual synapse, however they certainly have the potential to obtain one. A more gradual increase in the number of spines that persist for several hours and are very likely to contain a synapse occurs in later stages, ~30 min after stimulation (Engert and Bonhoeffer, 1999; Nägerl et al., 2004, 2007). However, note that the overall spine density is almost never affected in vivo (Holtmaat and Svoboda 2009), which indicates that compensating mechanisms counter-balance any synaptogenesis, so you should not expect to see an overall increased number of synapses.

References
- Matsuzaki, M., Honkura, N., Ellis-Davies, G. C. R., & Kasai, H. (2004). Structural basis of long-term potentiation in single dendritic spines. Nature, 429(6993), 761–766. https://doi.org/10.1038/nature02617
- Harvey, C. D., & Svoboda, K. (2007). Locally dynamic synaptic learning rules in pyramidal neuron dendrites. Nature, 450(7173), 1195–1200. https://doi.org/10.1038/nature06416
- Hill, T. C., & Zito, K. (2013). LTP-Induced Long-Term Stabilization of Individual Nascent Dendritic Spines. Journal of Neuroscience, 33(2), 678–686. https://doi.org/10.1523/JNEUROSCI.1404-12.2013
- Maletic-Savatic, M., Malinow, R., & Svoboda, K. (1999). Rapid dendritic morphogenesis in CA1 hippocampal dendrites induced by synaptic activity. Science (New York, N.Y.), 283(5409), 1923–1927. https://doi.org/10.1126/science.283.5409.1923
- Engert, F., & Bonhoeffer, T. (1999). Dendritic spine changes associated with hippocampal long-term synaptic plasticity. Nature, 399(6731), 66–70. https://doi.org/10.1038/19978
- Nägerl, U. V., Eberhorn, N., Cambridge, S. B., & Bonhoeffer, T. (2004). Bidirectional Activity-Dependent Morphological Plasticity in Hippocampal Neurons. Neuron, 44(5), 759–767. https://doi.org/10.1016/j.neuron.2004.11.016
- Nagerl, U. V., Kostinger, G., Anderson, J. C., Martin, K. A. C., & Bonhoeffer, T. (2007). Protracted Synaptogenesis after Activity-Dependent Spinogenesis in Hippocampal Neurons. Journal of Neuroscience, 27(30), 8149–8156. https://doi.org/10.1523/JNEUROSCI.0511-07.2007
- Holtmaat, A., & Svoboda, K. (2009). Experience-dependent structural synaptic plasticity in the mammalian brain. Nature Reviews Neuroscience, 10(9), 647–658. https://doi.org/10.1038/nrn2699


Manifestations of open foramen ovale in adults I read that foramen ovale opens in 30% of adults.
I do not know how much of these openings can then close again.
Probably, none.
It is not pathogenic if no symptoms.

It allows blood to enter from right atrium to left atrium (fetal), but from left atrium to right atrium in adults.
Assume that 50% of blood is doing so in adults.
This means that 50% of blood is not oxygenated.
Heart has to pump stronger to get some level of oxygenated blood as before.

Some thoughts about manifestations of open foramen ovale

hypertension
ischemic hypoxia
Clubbing
possible organ failures
higher risk for infections, SIRS and sepsis

Therefore, I think open foramen ovale can be a risk factor for myocardial infarction.

What are the manifestations of an open foramen ovale in adults?

A fully patent foramen ovale (pfo) is rare however a partial or small pfo is present in about 30% of the population.

Now the manifestations you described are partially correct. A pfo causes a left to right shunt in the adult whilst a right to left shunt in the fetus. In the fetus this is normal. In the adult, it is left to right because the left atrium is at higher pressure than the right. Due to this some of your manifestations are the wrong way round but still correct.

For example you mentioned hypertension, but presumably you meant systemic hypertension. It is more common at least in the early stages to get pulmonary hypertension. The pressures in the left atrium cause the pressures in the right atrium to increase when there is shunting. This is frequently seen when pressures in the left are increased due to factors like systemic hypertension. Coronary artery disease can also worsen the shunt and increase pressures in the right atrium and pulmonary pressures because the left ventricle can be stiffer.

Despite all this the more common presentation of a clinically significant pfo is right heart failure. Volume overloaded,the right heart dilates and fails. This will cause the usual presentation of right heart failure i.e. peripheral oedema, ascites and hepatomegaly.

Of course increased pulmonary pressures also causes strain to the right heart and can also cause right heart failure.

They then may go on to develop congestive cardiac failure and the exertional dyspnoea that comes with it. The inadequacy of the right heart can lead to excess strain to the left heart through a number of mechanisms that leads to it also failing. Dilation of the right heart can also lead to atrial fibrillation which in turn leads to stroke all being other possible presentations.

Cyanosis usually doesn't occur at least early in the disease as there isn't a shift from right to left (unoxygenated to oxygenated) but the other way round.

The severity of the pfo will lead to the severity of the clinical manifestation and how early it is picked up. Most people have routine checks of their heart (the murmur is usually pretty loud) so it is frequently corrected before any clinical disease manifests. In patients with small pfos they may never notice unless they become hypertensive or put strain on their heart during pregnancy. Yes they have a slight disadvantage as they lose some oxygenated blood but not anything noticeable.

If anything is unclear or you have more questions, please ask.


Help me identify this Beetle sp? I observed many beetles like this in Pune/India in the beginning of rainy season. It was dark green in color with white spots and not too much shiny like many other beetles. Size is about 2cm to 3cm.

It is certainly a scarab, in subfamily Cetoniinae. It looks very much like a White Spotted Fruit Chafer, Mausoleopsis amabilis http://www.projectnoah.org/spottings/11819281


Do hornets remember and recognize a human? Do they have any (kind of) memory? hornetology
So it happens that a hornet (vespa crabro) flew inside my house today and now is being held in a plastic container (I made some holes to let it breathe). But it also happens not just this once, but twice and I guess it's not over (we live by a small forest, probably it builds its own nest there). I wonder if hornets may have some memory - can it  remember and later recognize a human?
And if I take it to another place of the town I live in and let it go there will 'he' come back, 'cause it will remember where 'he' lived before?
Thanks for any advice, I just don't want to simply kill it... 'him'.

Most studies show that a hornet will give off a hormone that tells others in its hive that you or someone else is target and threat to the colony as a whole. They also are able to remember their surroundings near the hive or nest fairly well.


Why are mosquitoes repelled by smoke? A well known way to have a rest of mosquitoes during camping is to stand in the fire's smoke. Moreover, I learned recently that shepherds in certain regions of Africa use the same tactic for cattle. They make smoky fires and cattle gathers in smoke to get rid of mosquitoes.

Why humans and cattle can stand smoke, but mosquitoes can't? Does this technique work for other kinds of insects?

There is little hard evidence on whether smoke acts as a mosquitoe repellent. A literature review done by the WHO (Biran et al, 2008) on smoke and malaria show that evidence is mixed, at least when it comes to long term protection and protection from blood meals from firewood smoke. Their review also notes that few scientific studies have been done on the topic, and they report results from one experimental and a couple of observational studies. However, they do note that burning particular plant materials (based on traditionally used plants) may be effective (see e.g. Pålsson & Jaenson. 1999).

These results also doesn't preclude that very heavy, temporary, smoke may be effective to get rid of mosquitoes ("... during camping is to stand in the fire's smoke...") - that this can be effective is certainly my personal experience as well.


Suitable introductory book on Bioinformatics for a computer scientist? Do you have any suggestions on a suitable introductory text on bioinformatics for a computer scientist? Any recommendations with pros and cons of different books would be appreciated. I'm mainly looking for a brief introduction since I'm a novice to this field.

I found some books like

Systems Biology by Edda Klipp,
Introduction to Bioinformatics  by Arthur Lesk
Bioinformatics For Dummies
Bioinformatics and Functional Genomics by Jonathan Pevsner
An Introduction to Bioinformatics Algorithms by Neil C. Jones and Pavel A. Pevzner

I would like to develop software related to sequencing applications, so any suggestions should ideally aid in this goal.

Systems biology and bioinformatics are quite diverse subjects, but here are some options:

Biological Sequence Analysis by Durbin et al.: the classic bioinformatics text for people with a CS background. Does not deal with networks.
An Introduction to Systems Biology by Uri Alon: A physicist's view of systems biology, focusing on design principles and networks. Interesting concepts and some math (no algorithms). Doesn't really deal with methodology.
Physical Biology of the Cell by Phillips et al.: Nice introduction to biophysics and quantitative biology (no algorithms). Many parts are relevant for systems biology.
Any diverse Machine Learning text will be relevant and many have examples from biology/bioinformatics.
Probabilistic Graphical Models are also quite popular in bioinformatics (e.g. Hidden Markov Models, Expectation-Maximization, Bayesian Networks). Probabilistic Graphical Models by Koller et al. is a very comprehensive CS book on the subject.

Another suggestion is to look for primers/reviews in relevant journals. This is important because the field is new, so once a new technology is developed, it takes time until the appropriate computational methodology is developed enough to make it into a text book. Also, they can point you to relevant research papers. For example, PLoS Computational Biology has an Education Collection which features a large variety of such reviews.


Why does cold kill humans but not bacteria? Bacteria can continue like nothing happened after being exposed to low temperatures why doesn't this happen to humans as well? Why can't our metabolic machinery continue as normal?

Let's look at what happens when a single cell within a cell wall freezes. We end up with a little drop of ice, within which are encased all the cellular structures. Thaw this ice, and all is well - provided neither freezing nor thawing happen too rapidly.
Now take what happens in a human being.
First, the blood in the extremities gets colder, and cools the interior somewhat. But we have mechanisms to conserve heat in the core, at least for a little while. This doesn't help the extremities much. If the blood freezes there, we get frostbite - the tissues die for lack of blood supply. Fingers and toes and the end of the nose, and other extremities, are compromised.
Now let the core temperature drop. Below a certain temperature, conduction in the heart slows and eventually stops. This is fatal.
There are many other effects, all of them related to the relative vulnerability of different tissues to cold. Freezing is generally bad for animal cells, which will rupture because of the mechanical effects of the expansion of water as it forms ice. Frozen body fluids can't do their jobs. Frozen nerves can't conduct impulses, so muscles won't contract once their temperature drops below the shivering point. And so on.


Is the salt obtained from meat (as the primary diet) nutritionally sufficient? This post is derived from that one, where someone says

  if you meant salt as a nutrient such as carbs, protein and all, there is salt in the stuff one eats already.

The background is "Naked and Afraid", a Discovery Channel survival show, where a group of people survive for 21 or 40 days without any cloth or food.

They are not next to a shore. They are in amazon jungle or Solani River Basin in Africa.

The footage shows that the candidates got food by hunting but never got additional salt.

They are hunting in Africa. Don't they need additional salt? Is the amount of salt they got from animals like impala sufficient?

Hunter-gatherers rarely if ever added salt to their foods, and studies of salt-free Yanomamo Indians have shown these indigenous people to maintain low blood pressures that do not increase with aging (Oliver et al, 1975).

--The paradoxical nature of hunter-gatherer diets: meat-based, yet non-atherogenic. European Journal of Clinical Nutrition (2002) 56, Suppl 1, S42–S52 (PDF link)

(The Yanomamo Indians were/are hunter-gatherers, but that doesn't necessarily mean their diet was mainly meat - plants and fruits are important components. However, meat is likely to be higher in salt than plants, so this just supports the general principle.)


What is possibly wrong with my gel electrophoresis when i don't see bands of DNA ladder? ![enter image description here][1]

What was possibly wrong in my gel electrophoresis when I didn't see bands of DNA ladder?
I'm running a 2% electrophoresis gel (65v for 2h) to confirm the presence of qPCR amplification products, I can see the gDNA bands, is only the ladder that don't appear.

As one attempts their daily Sisyphean challenge of uncovering a new fact there is one truism, or platitude, that informs all of our efforts at troubleshooting an unanticipated experimental outcome.  This can be paraphrased as:

The number one cause is pilot error.

Accumulated experience of bench scientists everywhere shows that their own human errors are the simplest explanation whenever they try to deduce what could have gone wrong.  In the real world this translates into an operating axiom:

Don't waste time and energy coming up with new physical laws, or multi-step explanations that require you to remake and test all of your reagents, just repeat the experiment and see if this phenomenon is reproducible.

With that new information, that it is, or is not reproducible, you can decide if there is any hypothesis to test. But please, don't just take my word for it. Survey experimentalists, and the more experience they have the better.


What is the most-stable gene identifier? I've struggled in the past with designing data(bases) around gene-identifiers that evolve over time.  For example, UniProt and Ensembl change their identifiers for certain proteins/genes and the IDs go stale after a while (years).  HGNC seems possibly better for this?  What I'd like is to have a single unique identifier for each human gene that will remain stable for many years.  I know genes get re-classified occasionally, but you shouldn't end-up with a new identifier for the same locus.

Suggestions?

Thanks

Maintaining IDs consistency is a common problem. I've never seen any reasonable solutions for it and don't believe that there are any. However, there are a few shortcuts.

You can create an extra table with aliases for later renamings and refer them to original ids. Pros - it is flexible. Cons - maintaining is exhausting and you need to figure a way to explain to users why they input one id and receive other.
The solution is pretty obvious - if you'd like to have "a single unique identifier for each human gene that will remain stable for many years" you can just take a snapshot of current state of any database you like and don't touch it for many years. You can release version-specific releases of your database and specify versions of reference database you use. E.g. "Glioblastoma_drug_perturbation_2016_(GRCh38_ENS87)".


the range of interleukin 2 and 12 that can be used to activate nk-92 cells I am one of the biotech students. I want to know the dynamic ranges of interleukin 2 and 12 that i can use to activate the NK-92 Cells.
    thank you

If you have the resources you should ideally titrate your cytokines. You'll find that cytokines from different vendors may exhibit varying stability or availability in vitro, but also that you obtain varying levels of activation. Standard NK-92 culture conditions are 100-300 IU/mL IL-2 in RPMI1640 medium, 10% serum and 2mM L-glutamine (or 1X GlutaMAX, life technologies). Activation levels depend on how much you want to activate them. Interleukin-12 I'm fairly certain is standard at 10 ng/mL, but should also be titrated.

There's actually a relevant paper with a fair titration looking at granzyme expression at different concentrations of IL2, IL12 and IL15, and different timepoints. They note that NK92 cells show response at 100, 500 and 1000 IU/mL IL2, and at 10-30ng IL12.


Ejaculation without orgasm: is this possible to do it at will without external stimulation? I know that ejaculation without orgasm is possible for human males with external stimulations, e.g. prostate massage.

My question is, can a human male perform full ejaculation without reaching orgasm without such external stimulation, i.e. with "ordinary" masturbation? Is this technically possible for the body?

Yes, it is possible. It is all in the brain. One can be sufficiently aroused to ejaculate without any contact.

The most obvious example of this is the case of nocturnal emission

  A nocturnal emission, informally known as a wet dream, is a spontaneous orgasm during sleep that includes ejaculation for a male, or vaginal wetness or an orgasm (or both) for a female. Nocturnal emissions are most common during adolescence and early young adult years, but they may happen any time after puberty. It is possible for men to wake up during a wet dream or simply to sleep through it, but for women, some researchers have added the requirement that she should also awaken during the orgasm and perceive that the orgasm happened before it counts as a wet dream. Vaginal lubrication alone does not mean that the female had an orgasm.

Depending by what you mean by "without such external stimulation", you might want to read about premature ejaculation

  Premature ejaculation (PE) occurs when a man experiences orgasm and expels semen soon after sexual activity and with minimal penile stimulation. It has also been called early ejaculation, rapid ejaculation, rapid climax, premature climax, and (historically) ejaculatio praecox. There is no uniform cut-off defining "premature", but a consensus of experts at the International Society for Sexual Medicine endorsed a definition including "ejaculation which always or nearly always occurs prior to or within about one minute".


How to search for organisms by criteria such as growth substrate and overflow metabolites? I'm looking for a database or a systematic way to search for organisms which meet certain criteria. My criteria descending importance are:

growth substrate
chemolithoautotrophy (on which substrate)
overflow metabolite
methanogen
Nitrogen-fixation

Is there a database / some other means to find this information other than manual digging?

I tried NCBI taxonomy, LINNAEUS, uBio, KEGG, organism-tagger and others, but these don't appear to be capable of this kind of query. They all seem to require the organism name to begin with. But maybe I'm missing something?

thanks for any hints.

Ingvar

Some of the criteria, I guess are difficult to find (Also for my lack of understanding of those terms). For the rest you can search these databases:-

Growth substrate: I don't really know what you are asking here — growth rate in minimal media/optimal growth medium ? Nevertheless, see the Media Database
Methanogenesis: Ortholog Table - KEGG MODULE M00567
Nitrogen fixation: Ortholog Table - KEGG MODULE M00175


Study case of the inheritance system of Oenothera I've been told some interesting facts about oenothera. Apparently in this species some lineages have been through some translocations and in results to these translocations and in consequence, some chromosomes are inherited exclusively through the female function while some other chromosomes are inherited only through the male function.

Can you please provide a summary description of how things work in this species concerning the meiosis, the haplo-diplontic life cycle and the recombination?

I would recommend looking at this paper, and in particular the section "A SHORT INTRODUCTION TO OENOTHERA GENETICS":

The genetics of Oenothera is a genetics of entire haploid genomes (Renner complexes), which inherit as single units and are entitled with names such as hjohansen, Galbicans, or Gflavens (for terminology, see materials and methods). All loci of a Renner complex are in linkage disequilibrium.

Figure 1 from that paper shows what that looks like in meiosis, in terms of its impact on chromosome pairing- basically chromosome pairing forms rings of chromosomes linked by translocations.

Figure 1.
Additionally, it appears that plastid inheritance is biparental to some extent. These also contain pollen-lethal factors related to autosomes, such that cytonuclear incompatibilities kill pollen recombinants between a Renner complex and plastids (eggs are unaffected, Figure 2, 3):

Consequently, the F1 generation is identical to the parental generation without segregation of traits, since chromosomes separate as a set without intermixing.

The set of plastids ("plastome") will then break down in the F2 such that assortment can happen.

Selfing of appropriate flowers ensures that only plastome I is inherited to the next generation. However, in F2 the nuclear genome splits into the progenies CC-I and AC-I...

Since the ring of 14 chromosomes should inhibit free segregation of individual chromosomes and practically homologous recombination between haploid genomes in the hybrid AC, the coding potential of the A and C genomes is not mixed and a seemingly unchanged, homozygous CC genotype, now associated with plastome I, occurs in F2.

Figure 2.

Figure 3.
So it's rather complex. Hopefully that sheds some light on it, but it's understandable if it's still confusing!


The total numbers of mutations on different branches of gene tree are independent or not? I was reading Tajima's 1989 paper on his test for neutrality.

Tajima, Fumio. "Statistical method for testing the neutral mutation hypothesis by DNA polymorphism." Genetics 123.3 (1989): 585-595.

Here is the question:
Suppose we have three sequences labelled $C,D,E$, and their genealogy follows $\{\{CD\}E\}$  (i.e. $C$ and $D$ coalesce first before they coalesce with $E$). Let $B$ be the most recent common ancestor of $C$ and $D$.

Now, let the random variable $k_{ij}$ be the number of nucleotide differences between sequence $i$ and sequence $j$, then Tajima shows that $k_{BC}$ and $k_{BD}$ have a non zero covariance.

But aren't mutations in the branch $BC$ independent from mutations in the branch $BD$? I was thinking that the total numbers of mutations in the brand $BC$ and $BD$ are two independent identically distributed variables, so $k_{BC}$ and $k_{BD}$ are independent, then why they have a non-zero covariance?

============Update=============

Now I have some basic ideas, but haven't worked out the full answer.

Tajima's definition of $k_{ij}$ is neither independent of the sample size, nor for a fixed coalescent time. (See his 1983 paper: Tajima, Fumio. "Evolutionary relationship of DNA sequences in finite populations." Genetics 105.2 (1983): 437-460.)

For example, in a sample size of 3, if you pick 2 individuals, and condition on that the two coalesce first, their coalescent time will follow:
\begin{align*}
\mathbb{P}(t=T)=p(T)=\frac{3}{2N}e^{-\frac{3}{2N}T}
\end{align*}
Now conditioning on a fixed coalescent time $t$, the number of mutations under the infinite sites model in each branch either from $B$ to $C$ or from $B$ to $D$ will follow a poisson distribution with parameter $\mu t$, where $\mu$ is the mutation rate per sequence per generation. Let this poisson random variable be $\xi_t$ in branch $BC$ and $\eta_t$ in branch $BD$. Then
\begin{align*}
k_{BC}=\sum_{t=0}^{\infty}\xi_tp(t)\\
k_{BD}=\sum_{t=0}^{\infty}\eta_tp(t)
\end{align*}
If we only consider the partial sum of the above series,
\begin{align*}
k_{BC}^{(n)}=\sum_{t=0}^{n}\xi_tp(t)\\
k_{BD}^{(m)}=\sum_{t=0}^{n}\eta_tp(t)
\end{align*}
then $k_{BC}^{(n)}$ and $k_{BD}^{(n)}$ clearly have a zero covariance, because $\xi_t$ and $\eta_t$ are independent poisson variables, hence
\begin{align*}
\mathbb{E}(k_{BC}^{(n)}k_{BD}^{(n)})&=\mathbb{E}(\sum_{t=0}^{n}\xi_tp(t)\sum_{t=0}^{n}\eta_tp(t))=\sum_{i=0}^{n}\sum_{j=0}^np(i)p(j)\mathbb{E}(\xi_i\eta_j)=\sum_{i=0}^{n}\sum_{j=0}^np(i)p(j)\mathbb{E}\xi_i\mathbb{E}\eta_j\\
&=\mathbb{E}k_{BC}^{(n)}\mathbb{E}k_{BD}^{(n)},
\end{align*}
so their covariance is zero.

But as $n\to+\infty$, how $k_{BC}^{(n)}k_{BD}^{(n)}$ converges to $k_{BC}k_{BD}$ is questionable. It will not uniformly converge to $k_{BC}k_{BD}$ because otherwise we can first computing the expectation then take the limit, which gives us a zero covariance. Tajima didn't explicitly show us how he computed the covariance by summing together three infinite series (Line 7, Pg. 448, 1983's paper). I tried directly working on that series but failed in the last sum. His result is correct, though, I hope someone can give some hint on why there is inherent correlation between these seemingly independent random variables.

=======Update: a simple explanation has been posted==============

Here is a simple answer to my question. The reason two numbers of total mutations accumulated in two divergent branches are not independent of each other is because they experience the same amount of coalescent time.

While the stationary Poisson mutation processes are independent from each other as long as they happen in different branches of a genealogy, they are likely to produce a similar number of mutations if two such processes happen together for a same amount of time. Thus, the non-zero part of the covariance between $k_{BC}$ and $k_{BD}$ is not from mutation processes themselves, but from the shared coalescent time $T$.


Does the 'President' have 2 Billion Leaves? The world's second-largest known tree, the President, in Sequoia National Park is 3200 years old and is said to have 2 billion leaves (Source: https://youtu.be/vNCH6uhB_Bs?t=59).

Is this correct? And how was this number arrived at?

In other words, how is such an insanely large number possible?

One way* to come up with an estimate of how many leaves - or needles, in the case of Sequoiadendron giganteum - is simply to count the number of leaves on a twig (or a number, to get a good average), then the number of twigs on a branch, and then count the branches on the tree, after which it's just multiplication.

Now one reason that the number seems so high is the way the needles grow.  Unlike for instance pines, which have long needles arranged in sparse clusters of 2, 3, or 5, or spruce & fir, which have medium needles arranged along the branches, the sequoia has lots of tiny needles arranged on twiglets.

Link with picture of sequoia needles: https://www.monumentaltrees.com/en/trees/giantsequoia/giantsequoia/
Picture of pine vs spruce & fir: https://www.finegardening.com/article/fir-vs-spruce-vs-pine-how-to-tell-them-apart

*But I don't know whether it's the way used to get the number in the link.


What do we mean by MHC molecule diversity? Does each human have a variety of MHC molecule isoforms? I'm going to try and explain what I think I know

From what I understand, MHC/HLA molecules present peptides to T cells. To be able to present peptides from a wide variety of pathogens, they need to have diversity in their peptide binding domains.
My lecture handout tell me that MHC diversity comes due to polygeny and polymorphism.
Polygeny refers to there being 3/6 (handout says 3, textbook says 6) MHC class I loci leading to 3/6 class I isotypes, and 3/5 MHC class II loci leading to 3/5 class II isotypes.
Polymorphism refers to multiple alleles of each gene, meaning a variety of allotypes produced from each gene.
These processes lead to the generation of a wide variety of isoforms of MHC proteins in the human population.
The textbook also states that there is no rearrangement or structural change of the genes encoding the MHC proteins.

So I get that in the population, there is huge diversity of MHC molecules. But in each human, since there is no rearrangement of genes as in the case of antibodies to generate antibody diversity, is there therefore only one type of MHC protein being encoded? So by MHC diversity, we are not referring to diversity in each human, rather in the entire population? And if so, how do our MHC molecules become capable of binding to any antigen from any pathogen?

Please could someone clarify for me if I've misunderstood something, and also if my above explanation is factually correct, with the appropriate use of terminology?

You're right that both polygeny and polymorphism contribute to the diversity of a given gene in the population correctly described what they mean individually.

However, you missed that the polygeny of MHC means that the human genome has 3 different loci/genes (called MHC-I A,B & C) in the haploid genome, meaning that any given human as actually 6 copies of the gene (i.e. 3 copies from each parent). All of these copies perform the same function of presenting peptides to CD8+ cells, but will have slightly different binding preferences for the peptides that they load. This is where the MHC diversity in a single human comes from.

Additionally each of the 3 MHC-I loci/isoforms is polymorphic, meaning that for each of them multiple alleles/variants exist in the human population. Since the number of these variants is pretty big (hundreds to thousands), most humans have different alleles on their paternal & maternal chromosomes and end up with 6 unique MHC-I genes.


Is mate choice in non-human primates MHC-dependent? Whether the major histocompatibility complex (MHC) affects or not mate choice in humans seems mired in controversy at the moment. Without implying that looking at non-human primates would solve this controversy, I'm still curious if some sort of scientific consensus could be reached in non-human primates regarding MHC and mate selection.

tl;dr It's messy for non-human primates too. Winternitz et al. (2017) ("Patterns of MHC‐dependent mate selection in humans and nonhuman primates: a meta‐analysis", Molecular Ecology 26(2)) review studies of MHC-based mate choice in human and non-human primates. Some of the take-home messages, mostly from the abstract:

  [abstract] the overall effect sizes of primate MHC-based mating preferences
  are relatively weak ... calling for careful sampling design in future studies.

There is a

  "systematic trend" for primates preferring MHC diversity (p. 679)

(I think this means "not significant" ...)

  (p. 680) Nonhuman primates tend to consistently prefer MHC-dissimilar mates (Fig. 4a), but our power to detect a significant average effect is limited by our small sample size (N=6) and by the addition of random effects to control for pseudoreplication.

For MHC-diversity preferences:

  Examined separately ...  nonhuman primates had a non-significant trend for mate choice for diversity (primates = 0.110 (-0.207 to 0.456), N=7, Fig. 1b)

Here are some of the key figures (these figures also include data for humans, omitted here). However, note that the overall estimates in this figure do not account for the effects of study ID and phylogenetic relatedness (see Figure 1 in the paper), which tend to make the confidence intervals wider/weaken the statistical significance.

Figure 4a, preference for MHC-dissimilar mates [disassortativity] (overall CI is [-0.01, 0.18], consistent with the "almost significant" comment referenced above)

Figure 4b, preference for MHC-similar mates [assortativity]:

For reference, the species included here are: Rhinopithecus roxellana (golden/Sichuan snub-nosed monkey); Cheirogaleus medius (fat-tailed dwarf lemur); Papio ursinus (Chacma/Cape baboon); Microcebus murinus (gray mouse lemur); Mandrillus sphinx (mandrill); Macaca mulatta (Rhesus macaque).


Deciding a reasonable threshold for copy number variation in a CNV (SNP array) TCGA dataset Is there a methodology to select a reasonable threshold for copy number variation in a CNV (SNP array) TCGA dataset, to define when there is a significative alteration?

Can I download CNV data for normal samples and take the 95th percentile of distribution? Are there better methods?

Update

This is the percentiles plot of the two distribution (Tumor vs Normal) of values, for the same technology (SNP array) and the same genome (hg19).

The tumor distribution has slightly more extreme values, though it is not enough in my opinion. For this reason I think I should not use a percentile score (the 5th and the 95th percentile of the normal samples distribution, for instance) to define the thresholds to call CNV alterations in the tumor samples.

Your suggested approach of comparing to the baseline distribution on a point-by-point basis isn't bad, although it's going to be susceptible to small false positives from noise. You'd probably want to only use events that span a certain minimum number of consecutive observations.

You might also want to look into circular binary segmentation, as described here: http://www.ncbi.nlm.nih.gov/pubmed/15475419.


How do roots obtain nutrition? I have a city garden (see picture below) and yesterday I was nurturing it and I pulled up a small plant. I saw its root system and laid it in the sun to dry a bit and then scraped of the rest of the earth from it. That gave me a better look at the roots.

Then the question appeared to me. How do roots obtain water and nutrition from their environment. I mean what structures are we dealing with and how does the uptake take place?

One thing to remember when you uproot a plant is that some of the smallest structures break off most readily. What you will usually see after uprooting the plant are the largest parts of the root structure, but there are often smaller parts which have broken off.

Root structure is highly variable, but the general idea is that one or more primary trunk-like roots strike out toward the most important water sources, and from those primary roots, smaller roots branch out to more broadly extend the reach of the root system. Depending on the size of the plant, there may be several levels of branching, just like you might find in the top of the plant.

Generally, the nutrients that the roots need to absorb come to the plant with the water. They become dissolved in the water and the roots receive them along with the water. Dirt is chunky, not usually homogenous. So there may be more of the nutrients a plant needs in one area than another, or water may flow more easily through one area than another. The roots are able to grow in the direction of what they need, which is why you will occasionally find strong roots actually breaking into plumbing to get at your water. Mostly, it is water that they seek out, because the nutrients are dissolved in the water, but the plant may also show preference for a more nutrient rich stream over a larger, cleaner water source. The roots seek out what the plants need over the long term as they grow in one direction or another. For many plants, by the way, this means a simple strategy of simply growing straight down (a tap root), because that's almost always where they find more water with more of the right stuff dissolved into it. This is similar to the fact that many plants grow as tall as they can because that's where they will find the most sunlight, though the general idea is to grow leaves wherever that light might be captured.

Wherever the primary roots land themselves, the smaller root branches extend into the space to absorb as much as they can. They have to be greedy, because there may be days or even weeks when the ground gets very dry, so they have to get while the getting is good. If one of these smaller branches finds itself in a particularly sweet spot, the plant grows that branch more than its neighbors, which is part of how it places its largest root branches in the best spots.

Another very interesting part of the story of how the plant covers the maximum area of soil is symbiosis. I recommend further research into mycorrhizae, especially if you are a gardener. It's absolutely fascinating, and an important part of the story of how plants absorb nutrients and water.

I know less about the microscopic porous cellular structure of the roots. They essentially serve the same purpose as our stomachs and there are some loose similarities to be drawn, but of course, plant tissues, made of plant cells, which have a cell wall are very different from animal tissues.


What technique biologists use in order to determine the function of organs? How the biologists were able to determine the functions of body organs? Using a specific example organ for an answer would be ideal.

A very common way of getting information on the function of an organ, part of an organ (such as a region of the brain) or a protein is to look at the outcome (symptoms or phenotype) in cases where it is not functional. E.g., a lot has been understood about brain function for speech production by studying aphasia in stroke patients (see wikipedia) and linking the symptoms with the brain region that is damaged.

This is still the way we mostly study living cells or organisms: mutants defective for such or such protein, or in which external disruption (such as ablation) is used and the resulting phenotype or symptoms are studied.

This is indeed very different from what can be done for research in physics e.g., where reduced systems with simpler functions can be studied. The approach in biology is much closer to reverse engineering, where a given system has to be studied as a whole but a rational approach on some subpart allows to build an understanding of that subpart.


How to calculate the Jaccard index I want to calculate the Jaccard index between two compounds. What is the algorithm? I have searched for it, it just gives the formula but how to apply it on compounds is not known to me. Can you help?

The Jaccard index is a measure of similarity between two sets. Take a look at the Wikipedia article here. It is very easy to compute:

The Jaccard similarity coefficient for sets X and Y is defined as:

J(X,Y) = |intersection(X,Y)| / |union(X,Y)|

Where | | indicates the size (number of elements) of the set. Imagine you have two sets X and Y defined as follows:

X = {A, B, C, D}
Y = {C, D, E, F, G}

Then:

intersection(X,Y) = {C, D} => |intersection(X,Y)| = 2
union(X,Y) = {A,B,C,D,E,F} => |union(X,Y)| = 5

Therefore: J(X,Y) = 2/5

Alternatively, the Jaccard distance would be D(X,Y) = 1 - J(X,Y) = 1 - 2/5 = 3/5

In Biology the Jaccard index has been used to compute the similarity between networks, by comparing the number of edges in common (e.g. Bass, Nature methods 2013)

Regarding applying it to compounds, if you have two sets with different compounds, you can find how similar the two sets are using this index. The elements on the sets, in this case the compounds, correspond to A, B, C, etc. in my example.


Are porins on the inner or on the outer membrane of mitochondria? I've looked at multiple resources and they are saying different things.

This is not my field, but The Transporter Classification Database would appear to be a reliable source and states that:

  The best characterized members of the MPP family are the voltage-dependent anion-selective channel (VDAC) porins in the mitochondrial outer membrane.

Searching through the Protein Data Bank one can find a crystal structure for human voltage-dependent anion channel 1 and the associated paper also states that it is in the outer mitochondrial membrane, so you would imagine that they should know.


Names of different cyclins Different types of cell cyclins are designated as a to y

Why are some letters like m, n, p, q.. etc. skipped?

Source: https://en.wikipedia.org/wiki/Cyclin

Biological nomenclature can be impenetrable. Almost certainly, at some point in history, there were cyclins designated with these letters. Researchers would have discovered apparently novel cyclins which were subsequently determined to be part of an existing family and renamed. For example, this paper reports the discovery of:

  a new cyclin, cyclin M, which appears to be most closely related to cyclin L. Its biological function is unknown, but it is related to cyclins that regulate transcription.

It is now called cyclin L2.

I hope this answer satisfies you to some extent. I doubt anyone is going to sift through the literature and try and determine why all cyclins are are named as they are; that is certainly a losing proposition. The naming of genes/proteins is rather trivial and doesn't generally follow any specific set of rules. Outside of curiosity, the knowledge of cyclin naming doesn't have much, if any, practical relevance.


How does inorganic phosphate inhibit alkaline phosphatase? I want to know how is inorganic phosphate able to inhibit alkaline phosphatase.

When alkaline phosphatase dephosphorylates a substrate one of the intermediates in the reaction pathway is a phosphorylated form of the enzyme in which the phosphate from the substrate has been transferred to the enzyme. This phosphate is subsequently lost by hydrolysis. Under certain conditions alkaline phosphatase will actually catalyse a reverse reaction - the addition of inorganic phosphate on to alcohol substrates, and this also proceeds via the phospho-enzyme intermediate, but proceeds in the opposite direction.

This means that phosphate will inhibit the enzyme as a phosphatase via the formation of the phospho-enzyme, thus blocking the active site to substrates for dephosphorylation.

  Reaction mechanism of alkaline phosphatase based on crystal structures: Two-metal ion catalysis
  Kim, EE &  Harold W. Wyckoff, HW 1991 Reaction mechanism of alkaline phosphatase based on crystal structures: Two-metal ion catalysis. J Mol Biol. 218: 449-464


Seeing strange things in light I have noticed that if you look directly at tubelight (I have only white ones in my home) and close your eyes little, you see little random shaped colourless things sometimes with slow speed and sometimes with falling down.

They are shaped like circles with something in between and in chains of random length.

My father has also seen them. So, I am sure I am not imagining things. What the hell are they?

Those are floaters. These are objects floating in the vitreous humour that fills the eyeball. They typically look like:


What placement of plasmid parts makes the most sense? If you want to express the largest amount of a certain or a few proteins using a plasmid, does it make sense for the antibiotic resistance gene to come after genes for proteins you intend to synthesize?  So that the promoter and RBS/origin of replication would specifically come before the proteins intended to be synthesized and the bacterium would put less resources into its antibiotic resistance?  But would that be canceled out by bacteria not surviving as much as if the antibiotic resistance gene is downstream of the other proteins?  Or is it roughly the same in either order because they're both being synthesized anyway?

The relative placement of genes on a plasmid should not affect their expression.

Both will be expressed and to what extent is dependent on the strength of the promoters and a few other factors like codon availability.

However where you ultimately plan to express these genes can be an important consideration in plasmid design. For example, if you are designing a binary vector for agrobacterium mediated transformation of plants then positioning the plant resistance cassette next to the left border is a sensible move.


Is mammalian vision processed as a sequence of frames? I often read that people believe that human vision has an inherent frames-per-second rate (FPS) that causes stroboscopic effects - such as seeing the spokes of a rotating wheel apparently rotating at a different speed or appearing stationary when moving.
For example: in a Physics.SE answer to Can a “superhuman” move so fast that an average person cannot see them?

The human eye-brain visual refresh rate has an "effective frame rate" of around 30fps.
Have you never watched the rims of the wheel in a car next to yours? I can clearly recall many times watching as the wheels sped up how it appears to stand still then move backwards.

This surprises me as I would expect there is no synchronisation of neuron firing in the retina, that neuron firing rates would vary widely depending on light levels and that the brain has no need to process the continuous signals in fixed cycles or in cycles whose length is invariant.
I believe this question, or a good answer to it, would differ from What is the equivalent of shutter-speed in Human eye?
Is human vision in any way subject to a fixed frame rate of 30 FPS?

Short answer: no, there is no fixed frame rate or frame-based processing in mammalian vision.

Photons arriving at the photoreceptors at the back of the human retina interact with photo-sensitive pigments called opsins, and modulate their release of the neurotransmitter glutamate . The level of glutamate released from a photoreceptor then changes the membrane potential of the other neurons in the retina connected to the photoreceptor (bipolar cells, for instance). Signals are processed within the retina, then passed through retinal ganglion cells (RGCs), along the optic nerve, through sub-cortical structures and in to visual cortex.

This process occurs continuously, but all of the elements along the way have intrinsic time constants and other temporal constraints (number of photons required for opsin activation; recovery rate of the opsins in the photoreceptors; membrane time constants and refractory periods of neurons; synaptic delays; etc.). Persistence of vision (the effect underlying the perception of a movie as a continuous stream rather than a series of distinct frames) probably relies on the conjunction of many of these time constants.

Concretely, a flashed visual stimulus produces a response in (primate) visual cortex after around 30–50 ms (Maunsell and Gibson 1992). You can recognise and subsequently recall a lot of detail from a sequence of images flashed at around 100–150 ms per image [citation needed]. These are still not hard and fast definitions of the "speed" of vision.

Since we only learnt to produce movies as sequences of distinct frames, it's tempting to guesstimate the speed of human vision in those terms. Biology, as always, is more complicated.

As far as the "spinning rims" issue goes, there are many aspects of cortical and subcortical activity that tend towards oscillatory activity. In a system with an intrinsic frequency (for example, the neurons in the thalamocortical loop between LGN and primary visual cortex), providing an oscillatory stimulus can synchronise the system to the stimulus.

Many of the intrinsic time-constants I described above could result in a tendency to oscillate at some intrinsic frequency, and then be subject to phase locking due to a periodic stimulus close to that frequency.


What percentage of protein isoforms have different functions? I am looking for studies on how many protein isoforms have different functions, preferably in human. We know that a great many, if not most, of human genes are alternatively spliced and that many produce different protein isoforms. Has anyone looked at how many of these isoforms have different cellular functions? If someone could point me to a published paper, that would be great.

If no such study has been made, can anyone recommend a database from which this information could be extracted? GeneOntology is gene based so the information cannot be found there. Genes will be annotated to specific terms, not their protein isoforms. Also, I would need to be able to do this in a high throughput manner, I am not interested in specific proteins but in what percentage of all isoforms have different functions.

Ideally, I would like to be able to extract, for every human gene, the list of the different protein isoforms it encodes and whether their functions differ, or at least what those functions are.

It seems that most functional annotation these days is inferred from sequence similarity to previously annotated genes/proteins: this is certainly true of high-throughput functional annotation. It's hard to know how many layers of inference there are between your query sequence and an actual experiment verifying the (possibly tissue- or condition-specific) function of a gene/protein. But alas, I digress...

One confounding factor for is that alternatively spliced isoforms share a lot sequence in common, which means that they might share best hits when searching against a database of annotated transcripts and end up getting assigned the same GO terms.

But as others have mentioned, I think the biggest limiting factor you will encounter is the low-throughput step: in many cases the experimental work required to characterize the functions of alternative isoforms simply has not yet been done.


Using viruses to treat altered or misconfigured DNA Consider how a Retrovirus can modify existing cell DNA to 'execute instructions' on its behalf.

I wondered: Why can we not utilize lab-generated viruses to infect sick patients with a 'healthy' virus that would rewrite bad segments of DNA with something either correct or non-malus? This of course is assuming that we have a solid understanding of the relationship between genomes and precise viral functions, additionally that we had some sort of gene replacement functionality.

Consider how a Retrovirus can modify existing cell DNA to 'execute instructions' on its behalf.

Not only retroviruses do that. Actually, pretty much all viruses use the machinery of the host cell on its behalf.

  Why can we not utilize lab-generated viruses to infect sick patients with a 'healthy' virus that would rewrite bad segments of DNA with something either correct or non-malus?

We actually do that. We use viruses (incl. retrovirus but not only) to insert DNA segments into eukaryote genome. See vectors in gene therapy > viruses

  Retrovirus to reverse another retrovirus

Note that I don't really understand your title so, I ignored it a bit focusing on the content of the post.


Transformation of coordinates found in PDB According to the PDB guide there are some coordinate translation matrices found in PDB file:
ORIGXn                  Transformation from orthogonal  coordinates to the
                        submitted coordinates (n = 1, 2, or 3).
SCALEn                  Transformation from orthogonal coordinates to fractional
                        crystallographic coordinates  (n = 1, 2, or 3).
MTRIXn                  Transformations expressing non-crystallographic symmetry
                        (n = 1, 2, or 3). There may be multiple sets of these records.

For example, in 10gs complex from RCSB I see:
ORIGX1      1.000000  0.000000  0.000000        0.00000
ORIGX2      0.000000  1.000000  0.000000        0.00000
ORIGX3      0.000000  0.000000  1.000000        0.00000
SCALE1      0.012543  0.000000  0.001805        0.00000
SCALE2      0.000000  0.011055  0.000000        0.00000
SCALE3      0.000000  0.000000  0.014557        0.00000
MTRIX1   1  0.945333  0.099229  0.310644       -5.48795    1
MTRIX2   1  0.099832 -0.994906  0.013998       21.83043    1
MTRIX3   1  0.310451  0.017779 -0.950423       27.67516    1

I want to do 3D voxel reconstruction of some part of the complex stored in PDB. What is the purpose of those matrices, do I need to apply any of those translations to the coordinates stored in PDB to "standartize" the data and obtain the same coordinate system and same grid for different PDBs? Or they are just related to the data which was submitted by authors and are needed for inverse translation? Or something else? Thank you very much!

The purpose of these matrices is to reconstruct the crystal lattice from the coordinates, which only contain one copy of the repeating structural unit found in the crystal. In other words, they represent the affine transformations required to convert one copy of the repeating unit to its neighbors.
To a biologist (as opposed to a crystallographer), these are not useful except if one of the crystallographic symmetry axes happens to also be a biological dimer (or other multimer) axis. However, in this case, the PDB usually gives an option to download the "biological unit", which includes the coordinates for all neighboring copies that associate in the cell with the copy specified by the original coordinates. I should point out that sometimes the biological unit is in fact smaller than the crystallographic unit, if multiple copies of a monomer or dimer or whatever occur in non-equivalent spatial contexts within the crystal. There is no substitute for biological knowledge to know what the relevant structural unit in the cell is.


Why are nausea and dizziness such common side effects from medication? Why are nausea and dizziness such common side effects from medication?  If you go through your medicine cabinet and look at side effects, those might just be on every single bottle.  Is there some system in the human body that is very sensitive to any disturbance and causes nausea and dizziness?

Some medications because they are taken orally do cause nausea. Many medications, because they have an effect on blood pressure, or are central acting in some way, do cause dizziness. However, nausea and dizziness in particular are two highly subjective symptoms which are difficult to quantitate or verify, and which can occur with simple anxiety or stress. Several more such highly subjective and difficult-to-verify symptoms are numbness, tingling, headache, insomnia, fatigue and difficulty concentrating, all of which can be brought on by stress.

Switching for a moment to a drug with a measurable side effect of beta-blockers: erectile dysfunction (ED). In a study of men treated with beta blockers, the patients were separated into three groups with the following results:
a) the group who were not told the name of the medicine nor informed of the ED side effect had the lowest incidence of ED (3.1%)
b) the group who were told the name of the medicine but not informed about the ED side effect had a 15.6% incidence of ED
c) the group who were told the name of the medicine and informed of the ED side effect had the highest incidence of ED (31.2%)

Hypervigilance is an increase in attention to bodily cues or symptoms for any reason. It has been well documented in many studies that if you give one group of people a list of possible negative side effects, and another group a list of possible beneficial effects, then give both groups placebos (usually a small coated sugar or cornstarch tablet), the first group will experience negative effects while the second will feel better. The negative expectation producing a negative side effect is called the nocebo effect (the opposite of the placebo effect).

Interestingly, recent studies where anti-anxiety medications were administered before the nocebo dramatically decreased the nocebo effect.

For ethical reasons, in all clinical trials of drugs, patients in the treatment group and the placebo group must be given an extensive list (standardized) of possible negative side effects, introducing a negative expectation into both populations.

Two of the most common negative side effects in both groups are dizziness and nausea. Therefore, they must be reported as possibly occurring side effects with the medication.

This is not to say we're all imagining things. Nocebo effects have been correllated with reproducible effects on functional MRIs. They have a basis in reality, even if it's caused by negative expectations.

It's a problem being discussed a lot now by medical ethicists.

The influence of the nocebo effect in clinical trials
Avoiding Nocebo Effects to Optimize Treatment Outcome


Growth mediums required for human cell cultures So i would like to try a culture some of my keratinocytes just to see if i can do it. Ive read about a few different types of growth medium such as DMEM and RPMI but i am not sure about when to use which medium. So I am asking how do i detrimine which growth medium i need to use to culture human cells

So this paper probably has what you need.
Isolation and cultivation of human keratinocytes from skin or plucked hair for the generation of induced pluripotent stem cells

The first part of that paper covers just the cultivation of keratinocytes.
It's actually moderately difficult to culture keratinocytes, so if you just want to try out cell culture I wouldn't recommend this as your first step.

A good first step to learning the techniques of cell culture would either be bacterial, fungal, or yeast cultures because they are cheap, hardy, and don't require expensive equipment. Yeast culturing would be closest in technique to mammalian cell culture among the three  Yeast culture info here


What is the main general difference between Mitosis and Meiosis? I found such a clause:

  The general principle is that mitosis creates somatic cells and
  meiosis creates germ cells.

However, I cannot agree. Each gametogonium needs to go through mitosis before it can enter meiosis I. So in that case mitosis is happening with germ cells so the clause is false.

I would rephrase the sentence to be

  The general principle is that meiosis creates only germ cells with the possibility of a decrease in chromosome number, while mitosis can create both somatic and germ cells while the ploidy stays constant.

Ok, not perfect.

How would you say the main general difference between mitosis and meiosis?

If the question is about the one and only most important difference between mitosis and meiosis, then the answer "meiosis reduces ploidy" is probably correct. But if the list of important differences is open, it would be critical to add that mitosis generates identical cells (identical to each other and any ancestral cells, barring rare new mutations), while meiosis generates genetic diversity by creating cells, which are all different from each other and from any ancestral cells. It does so by independent segregation of homologs and by crossingover within chromosomes.


What is the difference between gene and CDS annotations? I have a bunch of sequence files fetched from the EBI ENA and I'm trying to find the end of the 5' UTR for specific genes.

The UTR itself doesn't seem to be annotated in most sequence files I have. My original idea was to simply use the CDS annotations, as the start of those should clearly identify the end of the 5' UTR. But I also noticed gene annotations in many of the sequences, most of them starting and ending at exactly the same locations as the corresponding CDS annotation. But there are also cases where there are small differences between the gene and the CDS annotation.

So I'm wondering how exactly the gene annotation is defined (if there is actually an agreed definition) and how the gene and CDS annotations are used in practice.

Which annotation would be the most reliable to identify the end of the 5' UTR?

CDS is based on ORF prediction and unless the protein product is known it is classified as an mRNA for a hypothetical protein (Refseq id: XM_*).

As Devon Ryan said sometimes UTR ends are not accurately annotated. If you are interested in finding the 3' end of 5'UTR then the problem is basically to find the translation start site. You can have a look at ribosome profiling experiments or try doing eIF2 CLIP-RNAseq (I don't think it has been done); peptide sequences may not be of help because N-terminal region in many cases, gets clipped.

If you are interested in finding the 5' end of 5'UTR then the problem is relatively simple. You just need to do a 5'-RACE followed by Sanger sequencing (this would work in most cases or you can do a deep-RNAseq).

There are official GTF files that provide the most reliable annotations. For human I would recommend GENCODE.

In the annotations the term Gene denotes the entire DNA region that is responsible for all of its RNA products (splice variants, alternate start/termination etc). Other features include Transcript, Exon, CDS, UTR and in some cases translation start site is separately annotated. CDS comprises of just the protein coding region.

You should read more about the GTF/GFF annotation format.


Tubing connector identification request this may not be on topic but I'm hoping someone here can tell me the name/manufacturer of the connectors used with the thin teflon tubing in this picture:

Try looking for "Luer valves" or "Luer fittings".

For instance, we buy this kind of supplies from WPI.


Is there something that makes flies slower at high altitudes? At first glance, higher altitudes equal lower temperatures, which would likely slow down cellular metabolism.  However, while backpacking in New Mexico in ~90 degree weather, I experienced the same thing -- the flies were slow enough I was able to catch them easily in my hand, as well as with chopsticks.

Is this related to air density?  Why are these flies so much slower to react and move about in the mountains.

Also, does this question even belong here?

The atmospheric density may not be the only factor, but from a physics standpoint, flying animals should in general move more slowly at high altitude.

As an example, New Mexico's Wheeler Peak is at an altitude of ~4 km above sea level. For a back-of-the-envelope air density calculation, a good estimate of scale height is 10 km, i.e. $\rho(h) = \rho_{sea}*e^{-h/10km}$ , which means the air density at Wheeler Peak is about $2/3$ the density at sea level (other air conditions being equal).
For wing-flapping animals, the power required to maintain flight is inversely proportional to the air density. I'm not confident about how flies' wing movements would be affected (this is where an entomologist should step in), but in any case their air speed should be reduced at high altitude.


What is the scientific name of this plant that is possibly called ogre ears? I already did a reverse image search and came up with "ogre ears" as a name for this plant. However, this name is associated with other plants: Crassula argentea and Crassula ovata. What is the scientific name of this plant?

Thanks

This (lovely) succulent is Crassula ovata variety "Gollum", known also as "gollum jade" or "finger jade".  Search for the name and you'll find lots of commercial sources.  One informative source is here.


How did plaques form in Salvador Luria's Bacteriophage experiment (discovery of restriction enzymes)? I was watching Eric Lander's lecture online describing Luria's experiment (see below for link), and I couldn't understand how plaques form. From my understanding,

Bacteriophage infect strain B
Viral DNA is incorporated
Restriction enzymes cut out viral DNA (mostly)
Some viral DNA is methylated before step 3 occurs.

At this point, to replicate, we would need the infected bacteria to produce more bacteriophage to infect nearby virus. However, due to step 3, the newly incorporated viral DNA will be cut out through restriction enzymes. So in my mind, we only have one bacteria with viral DNA (along with its descendants).

So how does the plaque form?

https://youtu.be/_TdJBLu6hPc?t=890

This indeed a very interesting experiment. In the lecture, you can see that the obvious explanation for the initial inhability to grow in strain B indicates that the bacteria is resistant to the virus. However, ocassionally, a virus is able to form a plaque in strain B, which initially seems to indicate that it mutated. However, in a second passage from Strain A to Strain B of this initial "mutant", we observe that there are no plaques in Strain B. This indicated that something beyond the DNA (unlike a mutation) was at play, and eventually led to the discovery of these epigenetic markers (methylation) that are made by the machinery of the bacteria (thus, Strain A lacked such machinery, so it maintained the viral DNA but did not mark it as 'viral').

Because these experiments occurr in Petri dishes, where there are millions of cells (billions, in fact), there is always some probability that the restriction machinery does not work. This probability (small, but detectable) of no detection is what is observed in the "original" plaque formed in Strain B. In addtion, when the virus is just added, it is still not marked, so it needs some time to be marked (more cell replication cycles), and during this time the virus can be infective. Either of these possibilities will produce a small fraction of plaques in Strain B.


How does a polymerized TruSeq adapter affect sequencing reads? I am trying to build a NGS library on enriched DNA (DNA length = 93 bp).  I am using PCR amplification with two overhanging primers, both containing Illumina adapter sequences (Universal Adapter & TruSeq Adapter w/ barcode).  My final library should be (~182 bp):

Universal Adapter (-), Enriched DNA (+), TruSeq Adapter(=)

------------------++++++++++++++++++++++==================

After PCR amplification and QC by gel, I am seeing fragments of larger size.  Analysis by Bioanalyzer indicates that I am might be getting some polymerization of the TruSeq adapter on the library.  This is most likely due to bad primer design, with the primer containing two recognition sequences (21-nt), one at the 3' end and one at the 5' end of the TruSeq adapter

My question is:

How would the NGS analysis be affected if a library is submitting for sequencing, containing a mixture of single and dbl TruSeq adaptors?

Single:

Universal Adapter (-), Enriched DNA (+), TruSeq Adapter(=)

------------------++++++++++++++++++++++==================

Double:

Universal Adapter (-), Enriched DNA (+), TruSeq Adapter 1(=),  TruSeq Adapter 2(=)

------------------++++++++++++++++++++++==================\==================

Would the sequencing info from the "double library" be lost or would those fragments be read, just fine?

Thanks,

In short, you stand to lose information from your library due to the length of the fragments you're sequencing.

When you set up your sequencing run, you'll set the parameter for the number of sequencing cycles, which will determine the length of the reads to be sequenced. The longer the fragments contained in your library, the less they'll be fully sequenced.

A good idea would be to sequence your suspected polymerized fragments to verify that primer polymerization is really occurring. Just send your sample for normal sequencing, as you would for plasmids and PCR fragments.

If your primers are polymerizing because of inefficient design, you should fix this before loading your library into the Illumina device. If the primer-dimer effect comprises a significant portion of your library, this will only get amplified during the run and can definitely lead to a significantly less complex library. Sequencing a low-complexity library is a really expensive mistake whose one guaranteed result is to enrage your advisor and make him/her loudly question your competence. Trust me.


Is there a biological neuron that spikes in response to hyperpolarizing currents? As some background I've been building Electrophysiological models of neurons, and in the process stumbled upon a model, that in all respects is biologically plausible, but has a bizarre property I didn't think happened in nature. It spikes in response to hyper polarized currents.

My particular model has only one ion channel which is has similar properties to Hodgkin-Huxley's transient sodium channel. It has one activation gate and one inactivation gate.  The reason I only use a single Ion Channel was I was exploring If I could create a minimal spiking neuron with just a single channel. The answer is yes, but has different properties then I expected.

Basically when I inject a hyper-polarizing current it spikes and depolarizing current causes it to stop spiking.

I know that Depolarization block can occur, my current isn't that High, in fact its no current produces no spikes. It has a normal rest potential around -55 mV and Fires upward to about +40 mV.

Also note that If I change the parameters around I get a more normal neuron that spikes in response to depolarizing currents. So the property must be somehow related to the ion channel kinetics.

The question is: Are there biological neurons that spike when hyper-polarizing currents are injected?

I was doing some more research and stumbled upon this paper here by Dr. Izhikevich that describe neurons as a system that can exhibit resonance. The author built a model that he calls the resonate and fire, which is a linear piece-wise model of a neuron.

The interesting thing, and why I bring it up, is it can respond to a "two inhibitory pulses, that if timed correctly will cause the neuron to fire. but neither inhibitory pulse alone can cause the neuron to fire.

Following some of the citations in the article (found here), apparently thalumus neurons can exhibit resonance and thus theoretically can fire in response to the right frequency of input. However it is important to note that they thalamic neurons are close to threshold, and are not receiving the double inhibitory input that Izhekivich talks about in his paper. The second paper uses a ZAP protocol.

A Zap protocol is injecting a Sine wave into a neuron and slowly change the frequency linearly in time.

$$I_{ZAP}(t) = \sin((\omega_0+\omega t) t) $$ where $\omega_0$ and $\omega_1$ are constants.


How Do Large Ocean Viruses Form Their Own Organelles? Several large viruses (Arslan 2011) form their own organelles within the amoebae they invade.

How do these organelles form?

Reference:

Arslan, D., Legendre, M., Seltzer, V., Abergel, C., Claverie, J-M. (2011) Distant Mimivirus relative with a larger genome highlights the fundamental features of Megaviridae. PNAS 108(42): 17486-17491 [DOI]

The organelle form in the same way they would if they were coded for by the host's genome, except in this case the virus uses its own genome to specify the type of organelle.

The article you link to indicates this.  The "systems" in the quote are in part the organelle that it needs

  A study of the giant virus’s DNA shows it to have over a thousand genes, the biochemical instructions it uses to build the systems it requires to replicate once inside its host.


What do you mean by non cellular matrix What do you mean by the non cellular matrix in which connective tissues are embedded?

You're looking for the extracellular matrix:

  In biology, the extracellular matrix (ECM) is a collection of extracellular molecules secreted by cells that provides structural and biochemical support to the surrounding cells.

Its main component are fibers, that can be strongly interlaced as in the case of the dense connective tissue or more loosely distributed as in the loose one.


Examples of real biological applications of the Keller-Segel system I am working on a model of aggregation behavior modeled with the Keller-Segel PDE system. I recently gave a talk on this and was asked what other examples there were of the Keller-Segel system. Since this is an obvious question, I was embarrassed to have no example other than my model and the aggregation of cellular slime molds (the application for which the Keller-Segel model was originally devloped). So I did some googling and came up with bupkis. There are hundreds of papers about the system by mathematicians, but I failed to find any other biological examples.
What about it? Is the Keller-Segel model mostly just a mathematical curiosity, or is it a model with many real applications to biology?

This looks like a good starting place: Painter, K. J. “Mathematical Models for Chemotaxis and Their Applications in Self-Organisation Phenomena,” June 22, 2018. https://arxiv.org/abs/1806.08627v2 (published in Journal of Theoretical Biology, 2019). Lists examples from Dictyostelium (of course), bacterial aggregation, development, physiology and disease, ecology, social science.

In this review, I evaluate the use of PKS [Patlak-Keller-Segel] models in describing chemotaxis (and other taxes), particularly focussing on examples of pattern formation/self-organisation. I do not review the numerous excellent studies
that primarily concentrate on their mathematical analysis: a number of reviews already cover these aspects in depth [...] Next, the fundamental modelling that led to (1) is reviewed and an overview given regarding its patterning behaviour. I then proceed field-by-field, beginning with its motivations in microbiology and sweeping across areas including developmental biology, immunology, cancer, ecology and the social sciences. For each case, the historical justification for chemotaxis is described and models are discussed; a compendium
that contains many of these models is provided in the Appendix. Finally, I demonstrate how PKS models can continue to penetrate new areas, via a novel application to explain clique formation in research.


When is the second polar body extruded from the egg nucleus? When does the second polar body gets expelled from the egg nucleus during oogenesis ? I know that it occurs after the entry of the sperm into the secondary oocyte but does it occur before the fertilization or in the period between the entry of the sperm and fertilization ?

As stated in the answer by @CDB, these polar bodies don't last too long, and the second polar body which forms as the result of meiosis II, extrude only after fertilisation. The secondary oocyte is arrested in metaphase II until it becomes fertilised, so meiosis II can only by completed after ovulation and fertilisation (see e.g. UNSW Embryology: Meiosis at https://embryology.med.unsw.edu.au). This means that meiosis II, which actually forms the second polar body, occurs as a result of fertilisation. The secondary oocyte becomes a mature oocyte (ovum) by the expulsion of second polar body into perivitelline space.

The metaphase arrest is caused by the presence of two types of cytoplasmic activity
1. MPF - maturation promoting factor
2. CSF - Cytostatic factor that inhibits APC/C

  Only when MPF is present, stabilized by CSF, and active will the M phase persist. However, this complex is very sensitive to calcium, such that a rise in calcium tilts the equilibrium away from complex synthesis towards destruction.

Capcitated spermatozoa that have undergone an acrosome reaction is capable of fusion and Calcium mediated calmodulin is required for this process. When fusion happens spermatozoon ceases to move and the nuclear with parts of mid piece and tail passes to the ooplasm. So sperm initiate Calcium release at fertilisation this helps in the completion of the 2nd meiotic division.
For further detail on these processes you could read the article Penetration, Adhesion, and Fusion in Mammalian Sperm-Egg Interaction
Increased Calcium activated Calpain (calcium dependent cysteine protease which causes CSF to disappear thereby activating APC/C which in turn causes dissociation of MPF. This results in completion of 2nd meiotic division.

For further details I recommend you to read Johnson and Everitts Essential Reproduction (6th edition), cell cycle chapter in The cell by Bruce Albert (5th edition)

  During oocyte–sperm fusion and second polar body expulsion, the cytoplasmic contents of the sperm cell membrane (now fused with the oocyte membrane) pass into the oocyte cytoplasm. Between 4 and 7h after fusion, the two sets of haploid chromosomes each become surrounded by distinct mem- branes and are now known as pronuclei (see Fig. d). The male is usually the larger of the two. Both pronuclei contain several nucleoli. During the next few hours, each pronucleus gradually moves from its subcortical position to a more central and adjacent cytoplasmic position. During this period, the haploid chromosomes synthesize DNA in preparation for the first mitotic division, which occursabout 18–24h after gamete fusion. The pronuclear membranes around the reduplicated sets of parental chromo- somes break down (see Fig. e), the mitotic metaphase spindle forms and the chromosomes assume their positions at its equator. The final phase of fertilization has been achieved: syngamy (or coming together of the gametic chromosomes) has occurred. Immediately the first mitotic anaphase and telophase are completed, the cleavage furrow forms, and the one-cell zygote becomes a two-cell conceptus.


Strange behavior of a DNA gel I ran a PCR product of ~300 bp on a 2% TAE-agarose gel for 30 minutes. I used Sybr-safe as a DNA stain. Voltage was 80V.

When I imaged the gel, the DNA on the bottom half of the gel, including the ladder had disappeared (it showed no bands). The DNA in the top half looked-clear and well-separated, but the bands on the bottom were somehow missing.

What could be the reason? I've never encountered this before.

I know it's not due to gel overheating - I ran the gel in the cold room and when it was done it was cold to the touch.

If you use pre-staining, the stain migrates as well in the electric field and this can lead to some parts of the gel being unstained. This would look pretty much like you describe, the ladder being invisible as well points strongly to that part of the gel just being no stained properly.

It sounds a bit unlikely with your running parameters, I've only seen that with a very long running gel, but I also haven't used pre-staining for quite a while now. Ethidium bromide is positively charged and migrates in the opposite direction as the DNA, I have no experience with Sybr-Safe though and don't know if it behaves the same as EtBr in this regard.


Productive turnover and generations in the fruit fly I was reading about the Lenski experiments on the evolution of E. coli bacterium and Dr. Elders's experiments on the evolution of the guppy.
These two experiments absolutely fascinated me, and seemed to happen relatively quickly by evolutionary standards. It was mentioned in the book that the fruit fly's productive turnover time is especially short.

I am extremely interested and would very much like to conduct an experiment into the evolution of the fruit fly, in much the same way as the Lenski and Elder experiments when I'm older.

Just so I can get a good idea, as I can find nothing on the internet, how long would it take for the fruit fly to get through, say, 10 generations?

Also, what would be the best way to go about beginning an experiment like this? Would there be certain people to contact? Would you need certain qualifications?

What do you mean by you couldn't find anything on the internet? Drosophila generation time is explained here?

Your other question is a bit off-topic here but I'll give all advice I have heard myself:

You can leave out a banana skin and catch some fruit flies, then do the experiment in your kitchen :) Joke aside, unless you perform the experiment independently it will probably take a long time and it's well possible that you won't be able to do it at all (unless you become some famous scientist). I'm not familiar with the experiments you mention, but if you require equipment and/or funding, you will need a qualification and/or a good explanation why people should give you money or let you use their equipment for this experiment.

I don't know what stage of education you are at, but it sounds like you are still at school ("when I'm older")? Most countries have some schemes where students (below uni) can apply for young researcher kind of things, so you could try and google that. Apart from that, the best bet is probably to try and get into a uni with good facilities and research programmes for their students. What you study shouldn't matter so much as long as it's science.

In response to Marta's commment: if you understand the experiment and you think you can gather everything they used at home, nothing speaks against just doing it on your own. Just make sure you don't let those flies swarm your house ;)


What species of mulberry is this? I have several mulberry seedlings that have popped up in my garden.

What species (or hybrid-species) are they?

Details:

The location is Toronto, Ontario
The date is July 18th, 2019
I have several different kinds of cultivated and uncultivated mulberries in the surrounding area that could have been the parents. I would list their cultivars and species names, but to be honest, I don't have much faith in them (I think they might just taint our analysis/identification).

Note: Here are some close-up photos of the plant in the bottom-right of the above photo:

https://i.stack.imgur.com/qi6dJ.jpg
https://i.stack.imgur.com/JlNh0.jpg
https://i.stack.imgur.com/rP2M8.jpg
https://i.stack.imgur.com/yWQGg.jpg
https://i.stack.imgur.com/vkH80.jpg
https://i.stack.imgur.com/ZJTx2.jpg

Even if we restrict ourselves to Morus rubra, the native species, versus Morus alba, the species introduced from China, and ignore possible hybrids, I think you may have to wait for the trees to be larger for an ID.  I found a relevant paper (Nepal, M.P., M.H. Mayfield, C.J. Ferguson. 2012. "Identification of eastern North American Morus (Moraceae): Taxonomic status of M. murrayana." Phytoneuron 2012-26: 1–6.) which contains the following paragraph:

  Salient features for correct identification of M. alba and M. rubra

  Morus rubra can be easily distinguished from M. alba using
  morphological characters of the leaf, bud, branch, bark and
  infructescence. Leaf characters present a challenge because of the
  tendency for leaves of juvenile shoots to converge in morphology among
  these species. Nearly all of the unique characteristics of M. rubra
  fail in juvenile leaves. Leaves of M. rubra (5–40 x 3–28 cm) are
  larger overall than those of M. alba (2–20 x 1.5–18 cm). In M. rubra
  leaves, the adaxial (upper) surface is rough and dull green (vs.
  smooth and lustrous) and the abaxial (lower) surface is usually
  densely hairy with erect trichomes evenly distributed (soft to the
  touch); the base is often cordate (heart-shaped); the apex is acute,
  acuminate to subcaudate; marginal teeth are often pointed; and the
  color of the main veins is more or less like the color of the lamina
  on the underside. Leaves of Morus alba are usually deep green and
  lustrous adaxially and have few hairs concentrated along the main
  veins on the abaxial surface; the base is rounded (vs. cordate); the
  apex is obtuse; the marginal teeth are fewer, relatively larger, and
  rounded; and the primary veins (underside) contrast more with the leaf
  surface than in M. rubra. The winter buds of M. rubra have bud scale
  margins with a darker (almost black) apical band, while in M. alba,
  the bud scale margins are uniformly brown. Morus rubra has grayish
  bark with flattened, thin plates that peel outwards in age. Morus alba
  bark has thick and solid ridges that are more of a reddish tan
  coloration. The orientation of branches in a mature M. rubra is
  somewhat planar (flat) and spreading like an umbrella. In M. alba the
  orientation of branches is more erect or spreading, and the plants
  appear more rounded or bushy as a result. The fruit of M. rubra is
  longer and narrowly cylindric, while in M. alba it is typically ovoid
  or ellipsoid.

This might be very useful for mature trees, but note the line "Leaf characters present a challenge because of the tendency for leaves of juvenile shoots to converge in morphology among these species. Nearly all of the unique characteristics of M. rubra fail in juvenile leaves."

There is also a recent, purely genetic analysis of the mulberries freely available at PLOS One but I don't think it's too helpful in this context other than it confirms that hybrids are common.

The Phytoneuron paper and a number of internet sites generally point to M. rubra being densely hairy on the underside of the leaves as one of the more important characters.  Your specimens appear glabrous, but the pictures though excellent may still not show tiny hairs well.  If we trust this character in the young plants then we would lean toward M. alba but as stated above, you may have to wait and see.


Gene Therapy for Cystic Fibrosis I have another question regarding cystic fibrosis.

I understand that gene therapy is currently being talked about in the cure for cystic fibrosis. I know that Eric Alton at imperial college London is working on delivering genes using liposomes and viruses like lentiviruses but I am confused over the advantages and disadvantages of those two methods.

In addition, is there an alternative 3rd method for injecting genes that don't involved viruses or liposomes. (An alternative type of vector) ?

Thanks

There are many other methods that are used for transfecting cells in culture. These include:

Cationic lipid mediated (as mentioned by user137)
Calcium Phosphate mediated transfection
Biolistic methods
Electroporation

Newer techniques include optical transfection (using lasers to bore a hole through membrane) and impalefection (using nanotubes). Wikipedia page on transfection nicely summarizes these techniques.

Induced pluripotent stem cells can be cultured from a patient, transformed using the plasmid and transplanted back to the tissue where it can replace the old cells with "corrected" cells.

There is another somewhat recent technique called in-vivo electroporation using which Nucleic Acid can be delivered directly in to the desired tissue.

However, to fix a mutation or introduce a transgene, just transfection is not enough; you have to make sure that the desired gene is inserted in the chromosome at the right location. Faulty gene can be replaced by the transfected functional gene via homologous recombination(HR), but rates of recombination are generally very low. Targeted gene insertion methods using genome editing tools such as Zinc-Finger Nuclease (ZFN), TALEN, and Crispr-Cas can increase this rate by introducing a break in the DNA at that region; this causes DNA repair systems to "repair" the break using HR.
There is another type of DNA repair system called NHEJ (Non-Homologous End Joining), and this is not what we are interested in. NHEJ can, in fact cause mutation through indels. Presence of the transfected DNA would shift the preference towards HR, however it has also been shown that different stages of cell cycle have different preference towards HR and NHEJ (cant find the reference as of now but I am sure about it because I was thinking at some point of time, to work on this).

Having said that, I would add that it is essential to screen the cells to see if the gene is incorporated or not. If some optimal protocol is devised then one can proceed to in-vivo electroporation.


Should there be separate Ramachandran plots for an amino acid in different contexts? I understand the nomenclature of the phi and the psi angles of the alpha-Carbon atoms in protein stucture, but I am confused by the Ramachandran plot. Each alpha-Carbon atom (magenta) makes two peptide linkages and has two corresponding neighbouring alpha-Carbons (cyan) and side-chains. I would expect the psi and phi values to depend on the interactions of these side-chains, so I would expect that for a single amino acid one would need a separate graph for every possible combination of neighbouring amino acids.

I am not clear whether this the case. The following graph (1) from Harper, Biochemistry, is for “many non-glycine residues from many proteins”. So, suppose a set of phi and psi is allowed for a right-handed helix (a value or data set taken from the plot) does it mean that it is allowed for any amino acid with any other amino acid? I woud expect an alanine adacent to an alanine to have a different interaction to an alanine adjacent to a bulky amino acid such as isoleucine.

I have also seen plots for specific amino acid and their allowed angles, such as that for proline (2), above. This suggests that the neighbours are not being taken into account. If this is so, why not?

The phi and psi dihedrals describe the dihedral on both sides of the c-alpha of a single amino acid, and do not involve any angles of the neighboring amino acid.

The Ramachandran plot is something generated from a set of protein structures, an empirical data set. The top graph represents the dihedrals found for all non-glycine residues in a set of structures. You can filter this for proline only, and you'd get the bottom graph. The top cloud of dihedrals represents those found in beta-sheets, and the bottom cloud those for alpha-helices. Sequence (the amino acid before or after) doesn't really matter that much for what's allowed (although we cannot directly deduce this from the data in those graphs).

If you look a little bit more into the structure of helices and sheets you'll also find out why that's the case. In beta sheets the sidechain of the +1 residue is pointing completely the other way, and also in helices there's little interaction between the sidechains of subsequent residues. Secondary structures are built using the amides, not with the sidechains.


Is there some branch of biology that deals with the entire organism? I'm reading about various parts of the human body and brain and started to wander if there's a branch of biology that deals with the entire human? I know that there are branches various -biologies, from neurobiology to something like heliobiology or chronobiology. All of them look at different organ systems or parts of an organism, but from different points of view.

Then there are sciences that deal with behavior and cognition of humans.

As I read about these, I notice that there's quite a lot of overlap, particularly when neurotransmitters and hormones are involved. For example Melatonin, a hormone has functions in both the brain and the gut.

I'm wandering if there's some form of biology or science that deals with the entire organism, its behavior , as well as its parts? Am I thinking about Biology or Medicine or something else?

I was thinking of Systems/Integrative/Predictive Biology reading your question. Studying the wikipedia entry it looks like a research approach with many problems trying to understand organisms from a biochemical perspective, identifying control circuits and macro-quantities like temperature and its relation to such biochemical control circuits. Basically you have to give up reductionism and use holistic/systemic perspectives and methods. While physics was successful with such research approaches (climate simulation, many particle systems,...), biology is lacking very accurate and proven mathematical theories to implement and test reasonable models of an organism, not surprising when biological systems have so many degrees of freedom compared to something like a ideal gas in physics. The wikipedia link doesn't show a lot of proven knowledge that this field/research approach has already created.


What are the effects of enzyme exposure to high temperatures? Question: After enzymes are exposed to high temperatures and undergo denaturation, then returned to their optimal temperature and renatured, can the enzyme's active site return to it's original shape and will it function at the same level of efficiency as it did before being denatured and renatured?

Some background I wrote to the question:
I am just beginning to learn Cell Biology, I hope what I've written is correct.

When you raise the temperature of an enzyme, at first it will increase the efficiency of the enzyme's activity, but eventually as the temperature rises, the enzyme with stop functioning and undergo denaturation, which means that the 3D formation of the protein is unraveled, so it doesn't function anymore. From what I've managed to research, the high temperature changes the shape of the active site in the enzyme, which is what allows the enzyme's activity in the first place.
I know that some proteins cannot be renatured (like adding heat to an egg will fry it and there is no way to unfry it), but some can be renatured (like heated milk, when it cools down the protein bonds will reestablish themselves).

But will the enzyme's active site return to it's original shape and manage to function at the same level of efficiency as it did before? Or is the damage permanent?

The answer is that it completely depends on what specific enzyme you're talking about; some of them will and some of them won't. What you wrote is correct, that increasing temperature of most enzymes (although there are exceptions) will increase their activity to a certain point, after which the proteins lose their 3D structure and become unfolded.

Upon cooling, it all depends on whether the enzyme can re-fold by itself or not. Some proteins when heated form aggregates, which are more stable than the original conformation, and so generally won't refold with cooling. Some proteins are able to fold into proper conformation by themselves, while other require assistance from chaperone proteins in order to fold correctly. Many of these chaperones are called heat-shock proteins, which are upregulated in response to thermal stress. That points to the fact that many proteins can't just refold on their own, and require help to regain their original conformation from these HSPs.

So the real answer is that it all depends on the specific protein. It also depends on how much you heat the enzyme, and how much of its 3D structure you affect, if you only partially denature an enzyme, it's more likely to refold than one that's been completely denatured. However, if you want an answer about enzymes in general, I'd say that most enzymes after denaturation aren't able to refold properly and regain their enzymatic activity, so the damage is permanent.