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How C. Elegans is used for siliencing genes
The experiment that is using C. Elegans to silence the Genes. I have a question about Why and how C. Elegans can use the DNA plasmid that is generated with the gene of interest in the bacteria by being fed the bacteria?

If you describe your procedure in a little more detail it will be easier to tell exactly what you are doing, but basically the cells of the C. Elegans can be induced to take up the plasmid and that can be transcribed by an RNA polymerase. The Messenger RNA is then translated by the ribosomes to produce a protein that inhibits the transcription of the gene of interest. If it is RNAi, then the RNA produced will hybridize with the mRNA transcripts that are being produced by the gene of interest. dsRNA cannot be translated and even if some of the mRNA is, the protein will be nonfunctional.

If you are actually doing recombination, then you likely linearized your plasmid with a restriction enzyme and the plasmid has homology arms that will allow it to be combined into the genome of the worm's cells. The success rate is usually low without some form of technology like CRISPR or Talens, so if you are using those, then there is likely some form of targeted DNA break that is happening to allow for homologous recombination to integrate the linearized plasmid into the chromosome of the worm.

It sounds like you are performing RNAi... this procedure explains what is going on. http://www.jove.com/science-education/5105/rnai-in-c-elegans They take the bacteria up in vesicles, digest then which releases the RNAi that the bacteria has produced and that intern goes on to hybridize with the mRNA of the gene of interest, as I said above, that binding either stops translation altogether or the protein product is no functional.

If it's what I'm thinking of, you probably have GFP+ worms that end up getting fed some DH5-α E. coli that were transformed using CaCl2. The outcome is your control worms should nicely fluoresce, and the experimental worms will be a noticeably weaker color. The RNAi process is explained nicely in that link provided by AMR.

Thank you AMR and Kendall for explaining this to me!! and Thanks for the video. It helps a lot to understand the concept. Thank you!!!

From the way that you have described your experiment, feeding C.elegans bacteria that are expressing a plasmid that will induce gene silencing, then both @Kendall and I think that you are likely performing an RNAi (interference) experiment.
As @Kendall writes:

If it's what I'm thinking of, you probably have GFP+ worms that end up getting fed some
DH5-α E. coli that were transformed using CaCl2. The outcome is your control worms should nicely fluoresce, and the experimental worms will be a noticeably weaker color. The RNAi process is explained nicely in that link provided by AMR. –  Kendall

The bacteria will transcribe RNA molecules encoded by the DNA plasmid. These RNAs will have complimentary sequences to sequences from your gene of interest.
When the nematode eats the bacteria, they RNA molecules that the bacteria has produced will be taken up by the cells of the worm.
The Dicer enzyme then cleaves the dsRNA into small fragments. These fragments are then able to hybridize with the mRNAs transcribed from the gene of interest. This will either cause the ribosomes not to bind properly or will start translation out of frame or without key amino acids or will terminate translation early.
The net effect is that the cells will either not produce the protein encoded by the gene of interest or will produce a non-functional protein. If, as @Kendall said, the gene of interest is a reporter gene such as GFP, then the result of the interference experiment will be C.elegans that do not fluoresce. If the gene of interest is a structural protein such as actin, then you will see the effects of knocking out the actin gene on the cells of the worm.
This online video protocol from JoVE.com gives a detailed overview of the RNAi in C.elegans experiment and also demonstrates how the protocol is carried out.


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Microinjection method in C. elegans
I have a question about the experiment that using microinjection to inject RNAi into the C. elegans. To prepare the dsRNA for injection, fist have to clone the gene of interest from the worm genome DNA and insert into a plasmid that has either T3 or T7 promotors. To clone the gene of interests, one has to design the primers. There is a paper descripting the protocol of the microinjection. Here is the link to the paper: http://labs.bio.unc.edu/goldstein/dudleygoldsteinmmb05.pdf
It is said that the primer for clone need to add sequence of T7 Promotor, but why? and why just add partial not complete sequence? why is it in the second step of PCR? Is it required to add the restriction enzyme site to both primers? Why?
Also in the feeding experiment, the plasmid(insert) is transformed into the HT115 strain and use IPTG to induce the expression of dsRNA. However, the microinjection is using dsRNA to inject the worm. So after cloning the gene of interest and insert into the plasmid, is the dsRNA expressed in the vitro before injection? And how? Thank you!

What they're doing is called two-step PCR. In step one, some gene-specific primers with tags amplify genomic DNA, but the product has adapter regions now added to each end. In the second step, you add primers that complement the tag/adapter region and have T7 promoter sequences at the ends. Your second product will have the adapter region, and the T7 promoters on the outside. The paper you provided shows they just modified the process: the first product is the gene of interest flanked by part of the T7 promoter, and the second product is the gene of interest, the T7 promoters, and restriction sites for cloning.

Design and implementation of high-throughput RNAi screens in cultured Drosophila cells
It looks like from what they know, adding the partial T7 in the first step is just optimization for their procedure. You want to add those restriction sites to wherever you can imagine you want your insert cut by the endonuclease. In a ligation step for inserting the gene fragment, you'll have cut your plasmid open with the same restriction enzyme you use to cut the insert, so that it ligates in nicely.
The HT115 strain has some nice properties you can read about here like a lack of RNase III that would degrade dsRNA, so it's suitable to produce the actual dsRNA inside of, and for the feeding experiment this is fine. For microinjection, they're using in vitro transcription kits to get dsRNA from the PCR product, which should be a gene of interest flanked by T7 promoters and restriction sites. T7 polymerase will simply transcribe everything downstream of it's promoter, so we don't have to worry about the restriction sites except for the feeding experiment.
MEGAscript® T7 Kit
The above kit comes with a T7 enzyme mix, NTPs, DNase, reaction buffer, a stop solution, precipitation solution, etc. You should be able to follow the manufacturer's direction and get 100 µg RNA per reaction, according to the webpage. Then you purify the dsRNA. It's literally just T7 polymerases transcribing whatever is between the two promoters into dsRNA -and for that kit, linear DNA does work- and then you degrade any DNA, leaving you with the dsRNA.

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Bacteria Replication
I learned this at a lecture, but somehow I have trouble in understanding this. It is said that the bacteria such as E.coli need 20 minutes to divide, but its chromosome require 40 minutes to multiply. It is explained that the E. coli will have copied half of it, which will spend 20 minutes and after divided, it will continue another 20 minutes to complete the chromosome copy. However, it is said that each daughter cell will have one complete and half copy after they divide. I am confused that if the bacteria only spend 20 minutes to copy half of it, how  can each daughter cell could have one and a half?

Referring to the six stages in your diagram as Stage 1 through Stage 6, let's look at Stage 3: At that point, there is one bidirectional replication in progress, having made it about halfway around the chromosome. So it has 2 copies of the first half of the chromosome, and 1 copy of the rest, which is yet to be copied.  To get to this state of replication took 20 minutes.
Now the cell starts two new replications, one at "origin of replication" on each of the two copies of the first halves of partially replicated chromosome.  This is the state shown in Stage 4.  There are now three replications going on: the original, which is working on the last half of the chromosome, and two replications, which are working on (their own copy of) the first half of the chromosome.  All three replications will continue working for about 20 minutes.
We then get to Stage 5: the original replication has finished and the septum forms to separate the daughter cells.  The two replications started in stage 4 are continuing, and are about halfway down the chromosome.
The cells separate, and we are at Stage 6.  But stage 6 is the same state for each daughter cell as we had in Stage 3: a chromosomal replication that is halfway through (thus having one and a half copies).  It took 20 minutes to get from Stage 3 to Stage 6, where we are ready to double again.  During that 20 minutes, only one half of a chromosome had time to be copied, so it takes twice that (40 minutes) for replication of the whole chromosome.  This works out because the cell is doing three replications at once.

Your question has already answered reasoning behind it. Just remember this happens only in rich media. Now I tried to build simple model of this to illustrate how DNA levels are changing over the period of time in given scenario. I will assume very simple (but reasonable) numbers for model. Rules are very simple,

Cell division in 20 min ( Cell will lose half DNA )
DNA replication in 40 min ( Cell will double DNA copy )
Firing of origin of replication in 10 min ( Cell will have one more origin of replication )
At each time point, cell will have DNA replication depending on number of origin of replications

I wrote simple code in python and simulated,
import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
cell_division_time = 20 #min
full_DNA_replication_time = 40 #min
firing_of_new_Ori = 10 #min
origin_of_replications = 1
total_DNA = 1 #initial condition
time_for_simulation = 400 #min
time_coordinates = range(time_for_simulation)
DNA_number_coordinates = [] #This will be updated at each time step
for t in time_coordinates:
    if (t%firing_of_new_Ori) == 0:
        origin_of_replications = origin_of_replications + 1  #Add more origin of replications
    total_DNA = total_DNA + (1.0/full_DNA_replication_time)*origin_of_replications #Add total DNA accordingly
    if (t%cell_division_time) == 0:
        total_DNA = total_DNA/2.0  #At cell division, total DNA will be half
        origin_of_replications = 1  #We will reset origin of replication to 1
    if (t%full_DNA_replication_time) == 0:
        total_DNA = total_DNA + 1 #DNA will be double when you complete one full replication
        origin_of_replications = origin_of_replications -1  #Remove that origin of replication
    DNA_number_coordinates.append(total_DNA)  #record amount of total DNA in cell
plt.plot(time_coordinates, DNA_number_coordinates,linewidth=2, label='DNA copies')
plt.axvline(x=40,linestyle='--', color='red',label='Cell Division')
plt.legend(loc=0)
plt.axvline(x=20,linestyle='--', color='red')
plt.axhline(y=1,linestyle='--', color='red')
plt.axhline(y=1.5,linestyle='--', color='red')
plt.xlabel('time (min)')
plt.ylabel('Total DNA copies in single Cell')
plt.show()

This simple game can give you intuition, check how DNA levels are changing in following image

At steady state, these will be sustained oscillations,

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Transcription when Chromosomes are Condensed
Are genes transcribed just as well when chromosomes are condensed?
I want to design a screen that depends on genes not transcribed when chromosomes are condensed (to identify cells that can't condense).

I think you are going to need to add a little more detail than this. Do you mean condensed like metaphase condensed, or do you just mean genes normally found in heterochromatic regions of the nucleus? If the latter, then you will want specify the cell type you are thinking of using as different cell types will have different genes silenced in heterochromatin and accessible in euchromatin. A lot of it has to do with the transcription factors reaching the nucleus and also chromatin remodeling complexes. some heterochromatin is more accessible than others.

The compaction of DNA into chromatin is a very complex process that involves not only DNA, but on the histone code. Some may say that the histone code plays more of a role in chromatin state To develop a screen you would have understand the act of methylation, acetylation, ubiquitination, and phosphorylation of all modifiable histone residues. The modification of histone residues determine if the chromatin is in a heterochromatin or euchromatin state and even in which sections of DNA are accessible and transcriptionally active.
It is also important to note that the same modification of any of the 8 histone proteins in any nucleosome (the fundamental unit of chromatin) may not produce the same result.
For example: The methylation of H2 histone in the first nucleosome of a chromatin "string" may cause silencing while the methylation of H2 histone further down the chromatin "string" may cause activation.
It's alot of information but maybe one day you will be the one who solves the pattern! It sure is fascinating.

@cagliari2005 I think that you may need to review your histone tail modifications, which can undergo Methylation, Phosphorylation, Acetylation and Ubiquitination and those modifications are on the Proteins, not on the DNA. And the "string" reference is referring to the "Beads on a String" fiber that is the first level (and only confirmed) of DNA compaction. It yields the 100 Angstrom fiber. And while neither question nor answer is worded that well, I think both users know at least the proper use of the vocabulary. The OPs other question is about mitotic arrest in yeast.


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Measuring optical density with/without re-suspending cells
When measuring absorbance using a plate reader, is it necessary (or better) to resuspend the culture if the plate has been sitting still for 1-2 days?
While this could be a good physics question, I am more interested in the correct biological assay technique.
--
The two options are:
1) growing microbes in a plate inside a static incubator and then put the plate in a plate reader without agitating the liquid
2) growing microbes in a plate inside a static incubator and then put the plate in a plate reader after agitating the liquid
In option 2, the agitation could be achieved by gently pipeting the liquid up and down a few times...

Definitely (2). Clumps of cells will cause a lot of noise in your absorbance measurements (depending on whether the light beam hits a clump or some empty space).
I don't know what your microbe is or what growth medium you're assaying on, but typically it's very important to maintain the culture well-mixed at all times, not just during measurement. If your cells clump to the bottom, you will not get the same aeration as you will if they're well-mixed, and accessibility of other nutrients could potentially be limited as well. Generally the most controlled condition is to maintain good mixing at all times, but certainly this is organism- and medium-dependent.

+1 If a liquid culture had been standing for a few days with no shaking, there must be many dead cells. Shake or no shake, the OD will be misleading.


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Gene vs. Protein Expression Assays
Are the terms gene expression assays and protein expression assays used interchangeably in molecular biology? Or is it expected of you to differentiate between the two terms.
For example, if I replace the DNA sequence of a gene of interest with the GFP DNA; and then subsequently quantify the fluorescence levels, am I measuring the gene expression of the gene of interest OR the protein expression?

Gene expression is the production of a functional gene product from a gene. So protein expression is a functional read-out of gene expression for gene loci that encode proteins.
However, gene expression is frequently, and erroneously, used to refer to measures of mRNA levels. The production of mRNA is a prerequisite step for the production of protein from a gene and it provides information about the transcriptional activity of a gene loci.
Translation of mRNA is a highly regulated process and
global assays highlight that mRNA transcript levels explain less than half of the variation in protein concentrations.

For example, if I replace the DNA sequence of a gene of interest with the GFP DNA; and then subsequently quantify the fluorescence levels, am I measuring the gene expression of the gene of interest OR the protein expression?

You are measuring both gene expression and protein expression from the promoter + GFP gene loci. If you are interested in transcription from the promoter then measuring transcript would provide a more direct measure.

Gene expression and protein expression are absolutely not the same thing. While counts of mRNA levels for a particular gene may give some indication of how much protein is present, many times it does not. Similarly, quantitating protein levels does not necessarily mean the relative levels of mRNA will be similar. There are many points for regulation between RNA polymerase rolling along the gene and creating the pre-mRNA and the protein coming out of the ribosome and being folded and transported to its correct place in the cell. mRNA can be silenced, degraded, or prevented from being translated by a number of mechanisms. Proteins themselves are subject to extensive regulation, with half-lives that can vary from seconds to weeks. Of course, genes are regulated in many different ways as well, from repressor proteins to methylated DNA to chemically-modified histones, and the number of polymerase complexes on the DNA and their relative transcription speed are also under regulatory control.

If I replace the DNA sequence of a gene of interest with the GFP DNA; and then subsequently quantify the fluorescence levels, am I measuring the gene expression of the gene of interest OR the protein expression?

You are quantifying the protein levels of GFP. mRNAs can be subject to sequence-specific regulation (such as siRNA), so you can't just say absolutely that GFP levels are equal to your gene product of interest. Many times they will be proportional, but some times they won't, so you'll need to do a number of other experiments to verify your results.


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Why is GenBank growth slowing down?
https://www.ncbi.nlm.nih.gov/genbank/statistics/ shows the growth of the GenBank database is slowing since WGS (Whole Genome Shotgun) emerged. Is this happening because sequencing centers are submitting their data unannotated (WGS submissions are allowed to be unannotated assemblies)?

It is not really slowing down. The graph that you see in that link is semi-log. So the exponentiality of the growth has reduced. It is not surprising because we have much more data than what we had 10 years back but the rate is not going to increase at the same rate (10 to 1000 is a great change but 1000 to 5000 is not despite the fact the the number of new sequences is greater in the latter). However, new data is being continuously added and the linear growth has not saturated yet.
See these graphs that I replotted from the data in your link.

Nonetheless, the number of new sequences will also slow down in future because we would be approaching the maximum.

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Heteromaternal Superfecundation - Any known cases?
Superfecundation in mammals (fertilization of two or more ova from the same cycle by sperm from separate acts of sexual intercourse) -- Is possible in nature from different fathers (Heteropaternal) as after the first zygote is formed, a second act of intercourse within a certain time span has the potential (of another ovum is present) to form a second zygote.
Has there been any cases where a naturally pregnant mammal was implanted (IVF) with a second zygote from a different set of parents?  Heteromaternal/paternal Superfecundation?

This would be termed superfetation rather than superfecundation. While this extremely rarely happens in humans, superfetation does occur naturally in some mammalian species. These pregnancies occur when the mother ovulates after she is pregnant.
Superfetation consisting of a natural pregnancy and implanted embryo has been done in cattle. In this case, 7-day embryos were successfully transferred to 14-day pregnant cows to produce superfetation. See Joel Carter's dissertation Superfetation in Beef Cattle (2002).
There have also been successful cases of superfetation in cows that were first implanted with a 7-day embryo, and then followed by natural service. See WH Hall, Bovine superfetation by natural conception secondary to an embryo transfer pregnancy, Cornell Vet. 1987 Jul;77(3):282-3.
An excellent summary of the existing literature on superfetation in many species is K Roellig et al., The concept of superfetation: a critical review on a ‘myth’ in mammalian reproduction, Biol Rev Camb Philos Soc. 2011 Feb;86(1):77-95.

I don't think that's what the OP is asking about. If I'm understanding the OP correctly, by "heteromaternal superfecundation" they mean that the implanted zygote's genomic mother is not the same individual as the mother in whose womb the zygote has been implanted. This is emphasized by the later clarification "different set of parents".


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How does Temperature influences the rate of protein turnover?
Question
How (quantitatively speaking) does temperature influences rate of turnover of transcription factors?
Which protein?
As I am not looking for any accurate number I am talking about an "average" transcription factor. I leave to you the choice of answering this question with some very accurate example (Transcription factor GTF II A for example) or with some broad observation on how temperature influences protein turnover.
The organism I'd like to model is a typical unicellular eukaryote such as a yeast for example that lives at "standard" range of temperature (between 5°C and 35°C roughly speaking).
Of course, I am not interested in considering a transcription factor that is directly involved in some response to a change in environmental temperature. I am interested in transcription factors which are involved in developmental pathways that have nothing to do with reaction of the body to temperature.
I am looking for a referenced answer $\ddot \smile$

See this answer

Would you want to close this question as you can find the answer in the other post?

That makes you the first person to close their own post :P


text:
Definition of "structural underdominance"?
In Stathos and Fishman (2014), the authors refer to the concept of structural underdominance. The first time they mention it is in the first paragraph of the second page (left column) and the term is followed by some kind of definition in parenthesis. It is written:

Furthermore, artifical doubling of chromosomes in sterile plant hybrids can sometimes restore normal meiosis and fertility (Stebbins 1950), a pattern diagnostic of structural underdominance (heterozygote inferiority).

In addition to how they use the term "Structural underdominance" in this paper, the above definition is confusing to me.
Is structural underdominance a specific type of underdominance (heterozygote disadvantage)? Is it the evolutionary process by which a population is lead to diminish the average underdominance along their loci? Is it a predisposition of the genetic architecture to display underdominance when a chromosomal rearrangement occurs? In short the question is:
What is the definition of "structural underdominance"?

I understand heterozygote inferiority (also underdominance or heterozygote disadvantage) as the opposite of heterozygote advantage, that is, lower fitness of the heterozygous genotype than either homozygote (as reference, see Hedrick, 2009, p. 119). I haven't seen the term structural underdominance before. However, heterozygote disadvantage can sometimes be seen in species/subspecies hybrids and also chromosomal heterozygotes (see Hedrick, 2009, p 140), and this might be what the term structural underdominance is describing (structural as in chromosomal). This can then lead to unbalanced gametes with low viability, which means low fitness compared to homozygotes. The quote you have included also talks about plant hybrids, which makes this explanation likely, and it also makes sense since they mention artifical doubling as a solution. If I have understood the process correctly, chromosomal doubling should lead to better pairing of chromosomes and lower risk of unbalanced chromosome translocations.
Also note that Hedrick labels heterozygote disadvantage as an unstable equilibrium (p. 140ff), but I haven't looked more closely at the dynamics behind this.


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Mutation-drift equilibrium and among loci variance in heterozygosity
At mutation-drift balance, the increased heterozygosity brought by new mutations is exactly equal to the loss of heterozygosity due to genetic drift. At equilibrium, the expected heterozygosity for a given locus is:
$$\hat h = \frac{4Nu}{1+4Nu}$$
The expected heterozygosity is only the first moment of the whole distribution of locus specific heterozygosity. What is the (among loci) variance in heterozygosity?

In The Distribution of Gene Frequencies in Populations, Sewall Wrights derivates a continuous approximation to the probability distribution for the frequency of an allele in a panmictic population under the pressure of drift and mutation on a bi-allelic locus. In his paper, he reports several version of the same equation. Below is one of them, where $\phi(q)$ is the probability density of the one specified allele to be at frequency $q$.
$$\phi(q) = C q^{4N\nu -1}(1-q)^{4N\mu -1}$$
, where $C=\frac{\Gamma(4N\mu+4N\nu)}{\Gamma (4N\mu) \cdot \Gamma (4N\nu)}$ is a constant, $\mu$ and $\nu$ and the forward and backward mutation rate The heterozygosity is then a simple one-to-one function of the allele frequency.


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Assessing probability from a pedigree
This isn't exactly homework but I'd like to treat it as such. I'm asked to find the probability that both (III: 2) and (III: 3) are carriers given that (II: 7) and (III: 1) exhibited the recessive trait (affected individuals are marked black in the pedigree below).
Denoting the affected individuals with $aa$ (and so the dominant allele is denoted $A$), I was able to determine the following:

Both (II: 1) and (II: 2) are carriers.
Both (I: 3) and (I: 4) are carriers.
At least one of (I: 1) and (I: 2) must be a carrier.
The probability that (II: 6) is a carrier is $\frac{2}{3}$.

The answer is supposed to be $\frac{1}{3}\times\frac{1}{4}=\frac{1}{12}$.
I'm mostly confused as to how to approach this one case at a time. Suppose (II: 6) is indeed a carrier. Then if (II: 5) is homozygous for $A$, then (III: 3) has a $\frac{1}{2}$ probability of being a carrier; if (II: 5) is also a carrier, then (III: 3) has a $\frac{2}{3}$ probability of being a carrier.
Since the event that (II: 5) is homozygous is mutually exclusive from the event that he is heterozygous, would I just add these probabilities (i.e. $\frac{1}{2}+\frac{2}{3}$)? Then multiply by the $\frac{2}{3}$ of (II: 6)? This would give $\frac{7}{9}$, which doesn't seem to get me any closer to the right answer.
A different approach I tried was multiplying the respective probabilities for the (II: 5) events above, which gives $\frac{1}{3}$ and thus one factor of the provided answer. If this is right, and it seems to be, I'm not sure how to apply this to the (III: 2) side of the pedigree.

I can probably post an answer later, but here's some a hint in the mean time. In these problems, it is generally assumed that the disease allele is rare. Individuals like II-5, which presumably have no affected relatives, are assumed to be homozygous.

II:6 has a $2/3$ probability of being a carrier Aa.
II:3 has a $1/2$ probability of being a carrier Aa.
Assuming, just like canadianer
suggested, that the recessive gene is rare, autosomal, and
non-x-linked, this means II:5 and II:4 are both homozygous (AA).

If parents of III:2 are therefore Aa and AA, this gives III:2 the probability of being a carrier of $1/2$. However, we must multiply this value by $1/2$, because III:2's father has a $1/2$ probability of being Aa. Therefore $\frac{1}{2}\frac{1}{2}= 1/4 =$ probability of III:2 being a carrier.
Similarly for III:3, if her parents are Aa and AA, this gives III:3 the probability of being a carrier of $1/2$. However, we must multiple this value by $2/3$, because III:3's mother has a $2/3$ probability of being Aa. Therefore $\frac{1}{2}\frac{2}{3}= 1/3 =$ probability of III:3 being a carrier.
The probability of both III:2 and III:3 being carriers is the product of both their probabilities: $\frac{1}{3}\frac{1}{4}= 1/12$.

Thanks to everyone that helped. I wasn't aware that making such an assumption was permissible, the textbook makes no mention of that kind of approach.

Does the same method work if I have to find the probability that neither III-2 nor III-3 are carriers? I'm told the probability is $\dfrac{2}{3}\times\dfrac{3}{4}=\dfrac{1}{2}$ this time. Clearly, the $3/4$ is a stand-alone factor (I can't multiply two fractions to get this product), but I don't see where it originates from. Would I make a different assumption about the uncertain individuals? Aa instead of AA?

@user170231, where did you get that answer? Was it for either III:2 or III:3 or both being AA?

@user170231 If it makes it clearer, your new question can be rephrased as "find the probability that both III-2 and III-3 are not carriers?" You already have the probability of each being a carrier: 1/3 and 1/4. The probability of each not being a carrier is then 1-1/3=2/3 and 1-1/4=3/4.

To additionally clarify the answer, it also needs to be assumed that one and only one of I:1 and I:2 is a carrier, for the same reasons canadianer gave (the recessive allele is rare). Otherwise, the question cannot be solved without knowing the allele frequencies.

The answer of 1/2 is given in the back of the textbook, and the way their pedigree is set up makes it apparent that the 2/3 comes from the woman's (III-3) side and 3/4 from the man's (III-2). @canadianer Thanks for pointing that out. I wasn't sure whether subtracting 1/3 and 1/4 from 1 respectively gave the probability of the complement, but I realize why that works now. (I thought the genotype aa would be involved, but we know that unaffected individuals possess at least one A.)

I can answer your question from the comments. In the second case, we have that one set of parents carry the following probabilities: $AA=1/2$, $Aa = 1/2$, and $AA = 1$. The second set of parents are the following: $AA = 1$, $Aa=2/3$, and $AA = 1/3$.
For the first set, we have the probability of $AA = \frac{1 + 1/2}{2} = \frac{3}{4}$. For the second set, we have $AA = \frac{1 + 1/3}{2} = \frac{2}{3}$. Now the probability of a child being $AA = \frac{3}{4}\frac{2}{3} = \frac{1}{2}$.

In the first set probability, I understand that $AA=1$ comes from II-4, and the $1/2$ probabilities for $AA$ and $Aa$ come from the possible genotypes for II-3, but which $1/2$ probability contributes to the resultant probability $\frac{1+1/2}{2}$? Is this $[P(AA){II-4}+P(Aa){II-3}]\times P(AA){II-3}$, or $[P(AA){II-4}+P(AA){II-3}]\times P(Aa){II-3}$? I can't seem to make sense of this setup...

If we are calculating AA, we take the 1/2 from AA and the 1 from AA giving us a total 3/2 AA out of a total of 2. Then we divide by the total the for probability.

Oh okay, that makes much more sense now! So the Aa probability isn't directly involved, we're only concerned with the events that the parents are AA. I appreciate the clarification!

@user170231 it is involved when we divide by the total of 2 = 1 +1/2 +1/2.

Right, I meant the 1/2 for Aa is involved in the total sample space (denominator) but not the numerator

authors: Ксения Арефьева


text:
How do I make conclusions from the autoradiograph of a Southern blot?
Here's another question taken from "Concepts of Genetics," Klug et al (10ed), revolving around a paternity test. PCR and a Southern blot were carried out in order to determine whether 3 chimpanzees (lanes 3, 4, 5 in the blot below) were the "legitimate" offspring of 2 potential parents (lanes 1 and 2).
The question makes a point of saying that the primers used to bind to the chimp DNA originates from humans, and that they "flank highly polymorphic sites in human DNA that result from variable numbers of tandem nucleotide repeats." My first question is what exactly does "flanking" mean in this context? It sounds to me like the human DNA "mirrors" the chimp DNA, and so makes it good enough to use as a primer, but I'm not sure.
I've come across a few other examples not in the text about how to infer whether a potential parent is indeed a parent based on whether the offspring's lane contains bands found in both the maternal and paternal lanes, which leads me to believe I can rule out the chimp in lane 5.
I'm given five answers to choose from to decide which of the offspring, if any, are legitimate:

None
A only
A and B only
Not enough data; more polymorphic sites should be examined
No conclusion can be made because "human" primers  were used

Main questions: Does that fact that we're using human DNA as primers cause any problems? Do we know enough from this blot to determine paternity?

For your first question, the sentence could be rewritten as: "are on either side of highly polymorphic sites in human DNA that result from variable numbers of tandem nucleotide repeats."

Okay that makes much more sense, thanks for clarifying.

A Southern blot needs to be probed with labeled DNA. It is not clear from your description what the origin of such a probe would be. Nor are Southern blots typically used to resolve and detect such short pieces of DNA--in fact you would need an extremely high percentage of agarose in a gel to achieve this resolution. That suggests it is actually a polyacrylamide gel, and therefore unlikely to be a Southern blot.  The fact the the primers match sequences in the Human genome is irrelevant.  The question is about using VTNR as dominant genetic markers to "fingerprint" genomic DNA samples.

As @canadianer pointed out in the comments section flanking sequence is a sequence that is immediately near the target on either side. Since chimps and humans are closely related and the sequence different is minimal (according to this paper its approx 4% for the entire genome)  so using human primers is totally fine.  Now if take a look at the picture of the gel:
 The answer is 2. only A because only this offspring has a variant in large amount (that can be determined from the width of the band) that can be acquired from both parents and in this case chimp A actually did inherit the 136bp variant from both parents.
For chimp 4 either parent can be the same (as for chimp A) from the two because it has the 136bp variant as well ( that can be inherited either chimp one or two), but has a different one that cannot come from chimps 1 and 2.
As you said chimp 5 can be ruled out instantly because it has a large band that cannot be found in either of the two parents.


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Herbicide resistant crop plants

Consider the above multiple choice question. I can't seem to understand why the answer is B. How does genetically modifying the crop plant have any effect on the weeds?
The way I understand genetic engineering is that we insert a desired gene into the crop plant that allows it to become herbicide resistant. So how would this gene make its way to the weed? Could someone please explain how the two effect one another?

Why would you want herbicide resistance in the crop? How would you grow the crop to make use of the herbicide resistance? What is the treatment that you're presumably applying to both the crop and the weed? What are long-term results of that treatment? Try searching the internet a little bit; we usually ask that of people posting questions here, to show some evidence of research effort.

"So how would this gene make its way to the weed?" That doesn't really matter for your question. (Evolution - selective pressure - is the answer to that concern. It is exactly like antibiotic resistance.) Just looking at the information presented, look at the advantages. What are they? What would interfere with the advantages? That's your answer.

@MaximilianPress Herbicide resistance is desired so farmers can wipe out weeds without damaging crops. So we apply the herbicide to both the weed and crop so over the time the weed may mutate to become resistant? Could this be right?

@user73245 can you find any supporting evidence for that chain of logic on the internet, wikipedia, scholarly articles, etc.?

I am pretty sure that the gene is not transferring directly from the crop into the weed. Instead, the idea is that you would never engineer an herbicide-resistant plant unless you were planning to apply herbicides to it. Since weeds will experience the effects of the herbicides along the GM plant (this is what kills them, after all), they will experience a selective pressure that may cause them to become herbicide-resistant.

What makes you sure that horizontal gene transfer doesn't occur in this case? Could you add a reference - else risk downvotes/deletion. (I'd assume the same thing as you because of the timing of the application - if before flowering and seed development, but we like references.)

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


text:
Ordering Primers: When to choose wet vs dry delivery format?
Whenever ordering primers, I'm always asked to specify which delivery matrix I prefer to have the oligos delivered in: wet (in water or some kind of TE buffer) vs. dry.
My understanding is that when stored dry, the primers can last up to 24 months in the freezer. However, for the primers to be useable, one needs to rehydrate them into the appropriate concentration.
So I'm wondering, what are the pros/cons of having primers shipped wet vs dry?

Pros of wet:

No need to rehydrate to use.
For e.g. 96-well plates, this can be a big deal as it's a pain to do this for large numbers of samples.
More accurate concentrations (oligo manufactureres are better at rehydrating oligos with e.g. accurate volumes than most people).

Pros of dry:

last longer (until rehydrated)
cheaper

This is great summary of the pros/cons. Thanks!


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Acid-base balance in plants
Question: How do plants extrude excess acid/alkali, at the level of the whole organism?
I have no expertise in botany at all. I come from a medical background and sought to find a similar treatment of acid-base physiology in plants, but to no avail. The specific issue that is bothering me is this: in humans, the lungs and kidneys are the ultimate regulators of acid-base homeostasis, extruding excess acids in the form of expiration and urine, respectively. Note that this statement makes no mention of cells at all; at the level of the whole organism, an excess of acid intake over alkali intake must be balanced by a net excretion of acid. The lungs and kidneys can be understood to provide this function.
In the case of plants, however, I could not find any organism-level discussion. I get that plant cells extrude H+ via PM-ATPases, but where do all those ions go eventually, if there isn't an botanic equivalent of urine?
I managed to find the following quotes.

Abrupt pH shifts are first curbed by buffers and then reversed by membrane transport. The latter predominantly involves the apoplast or the vacuole as either final or temporary sink (...) Due to the small volume of apoplastic fluid, minor ion translocation across the plasma membrane will alter the ion concentrations and activities quickly and considerably, leading to potentially unfavourable conditions for the surrounding cells. Therefore, protons net exported into the apoplastic space will have to be taken up by neighbouring cells or must be transported elsewhere within the plant body. Where the H+-exporting cells are embedded in a tissue, not all protons exported may readily flow away but will acidify the apoplast (as demonstrated with fusicoccin)[.] (Felle HH, 2001, Plant Biol. link)

To reduce the intracellular acid load, net H+ transport out of the cell or tissue has to be the ultimate goal. Organisms may differ considerably in their ability to accomplish this. Whereas a (fresh-) water plant may find it easy to get rid of exported protons, a tissue cell within a terrestrial plant must export the protons into the
apoplast, a rather thin layer with a volume comparable to that of the cytoplasm. Since this provides a poor H+ sink, a stimulated pump will rapidly acidify the apoplast (...) This will cause either thermodynamic stalling of the pump or favour H+ re-uptake into the cell and thus generate futile H+ circling. For this reason, H+ pumping into the apoplast of terrestrial plant tissues will have to be low to limit excessive acidification. (Felle HH, 2005, Ann Bot. link)

Such passages seem to suggest that the H+ exported into the apoplast must again be moved to somewhere else, in order to maintain homeostasis. Common sense suggests that these routes must comprise guttation + root exudation, but I cannot find any sources that explicitly state this. Is my understanding correct? If so, are there any papers that I could consult regarding this issue?

I was able to find several papers discussing rhizosphere pH regulation, driven in one study in wheat by exudation of acidic compounds. Rhizosphere exudate is probably the closest thing to the urine analog you are looking for:

We propose that the secretion of multiple types of metabolites with a –COOH group is an important pH regulation strategy for alkali-stressed wheat plants.

This seems to have been shown in various experimental studies in some alkali-tolerant grasses:

To identify the physiological mechanisms involved in this plant’s resistance to alkali stress, the relative growth rates, the quantities and compositions of organic acids accumulated and secreted through the roots into the rhyzosphere, the concentrations of inorganic ions, proline and other solutes accumulating in the shoots were measured. The results show that the organic acid constituents in the shoots and roots were much the same. These were predominantly malic acid, oxalic acid, citric acid and succinic acid. The total concentration of organic acids in the shoots increased strongly with increasing alkali stress.
...
The main organic acid accumulated was not only an important organic osmotic regulator, but also an important negative charge contributor, playing important roles in ionic balance and pH adjustment.

One notable conclusion from this is that the external abiotic environment is a much more import pH stressor than internal pH homeostasis. Plants go to a lot of trouble to regulate in response to environment. Regulation of external soil pH also has the nice side effect of increasing the bioavailability of various inorganic ions like K+.
Root organic acid exudates are also a mechanism for symbiosis with beneficial microbiota. For a review discussing several of these benefits, see here.


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Are there any mutagens that can undo the mutations they cause?
I was reading a section from my textbook about tautomeric shifts, and it seems to suggest that there are some mutagens that can be directly responsible for the phenomenon. The section is mainly describing spontaneous mutations as opposed to induced mutations, and examples of mutagens are mentioned. However, the author explicitly states that the sort of changes made to DNA due to spontaneous mutations also occur at a higher rate during induced mutagenesis.
If a tautomeric shift can occur due to mutagenic activity, is it possible for the mutagen to undo and "correct" the mutation by reversing the shift? If so, what kind of chemicals or physical mutagens (e.g. radiation) would be involved?

It is possible but extremely unlikely.
When a base undergoes tautomeric shift the DNA does not contain a mutation yet, just an unmatched pair. The mutation will only becomes inscribed into the DNA permanently after the DNA is replicated or wrongly repaired.
In order to reverse the mutation you would need to provoke a chemical change to that specific base using the same or another mutagen and as most of them are unspecific the likelihood of obtaining both the correct mutation to reverse the effect AND at that specific location is extremely low. Just for the location itself (i.e. that base pair), in human you have ~0.000000033%  chances (1/3 billions) to mutate that base. This is assuming equal probabilities across the genome and a single modification event which is of course not true but shouldn't modify much the conclusion. I am not even speaking about provoking the chemical modification that will reverse it which will even further reduce that probability.
Such induced or natural mutations will actually only rarely appear in the genome permanently as the cell has multiple DNA repair mechanisms (see this wiki). So in this case the modified base does not need to be reverse as the cell will make sure to repair it directly but using mechanisms not based on mutagenesis.

So near-zero probability aside, the mutation reversal can occur. Would this require the mutagen to be nonspecific (like UV or gamma rays)?

The opposite. If you have an insanely specific mutagen that only mutates one base in particular it's about 1/8 or so probability to undo its own mutation, but a nonspecific mutagen has a much lower chance. Real specific mutagens don't really work like that, but the same principle applies.

I just finished reading a section describing photoreactivation as a means of repairing a mutation. In addition to this, the wiki page linked by @cagliari2005 mentions that the enzyme involved in the process can be activated by light in the blue/UV range. However, the page on photolyases says they require visible light for activation. Any ideas as to the discrepancy? Also, thanks for the replies, much appreciated!

@user170231 Post a new question ;)

No need, I just answered my own question after a bit of reading :) Thanks again


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What statistical test would you recommend to compare two animal behavior sampling methods?
I am doing a lab where I am comparing the scanning method and focal animal method. Each method will give me the following:

Scanning method: occurrence frequency for each behavior (%),
focal animal method:the occurrence frequencies (%), as well as the duration for each behavior.

I was thinking a chi-squared test or a t-test somehow but I'm not sure which to do or how to format them. Should I somehow compare the occurrence frequencies?
Not sure if this info is useful, but I normally use R for my statistical test but have never used my own data, only example data. I was going to record my data in excel and import it into R. Thank you in advance.

What do you want to compare between the methods? If you want to decide which is the correct method to measure, statistics isn't the answer. You need to consider the accuracy you obtain with each method, the objective, the data achieved, the resolution and your sample size. among other paremters

I agree with @Hachiloni that you seem to compare apples and oranges. The two methods provide you with different information, i.e., you measure different things. Perhaps, you could give more background about what you are doing, which could help to understand your problem better.

Also agree with Hachiloni. I think that we need more details about your experimental setup or study system. The question is not how to analyze the data but which addresses your study question. For example, I might ask why you don't take a video of the whole population and then do a focal analysis on each individual at every time point. Likely there is some technical difficulty with this, but it's really hard for us to tell!


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Overly stabilised population dynamics model
My project aims to model population dynamics of a 3 trophic levels system: primary producers, herbivores and predator. I try to predict how changes in the vegetation abundance might affect higher trophic levels. My herbivores are described through juvenile and adults compartments, with the first "supplying" the other, after a maturation time. My predator only has an "adult" life stage.
Currently, I'm a bit struggling, because no matter what vegetation biomass or initial densities I put in the system, it always converges toward the same densities. The system reaches an equilibrium stable point, no matter the amount of food available for my herbivores, which is quite a problem for my study.
Could anyone enlighten me with some ideas of what to test/look for to resolve my issue?
Of course, I can give more details about my simulations (done with R and Rstudio, with the deSolve package) and the structure of my equations (Lotka-Volterra).
Thanks a lot in advance.

If you're still interested in the answer, can you edit your questions to include the actual equations (either a R code or as mathematical notation, ideally in LaTeX but text would be OK -- just not an image/screenshot in either case) you're working with?

Hi @BenBolker, Yes I'm still interested! I'll try to edit my post as soon as possible. Thanks a lot

In a deterministic system, there are 2 options: equilibrium or collapse. It sounds like you've found an equilibrium. This is probably expected!
Classic Lotka-Volterra makes specific deterministic claims about the equilibrium population levels:

Secondly, the population equilibrium of this model has the property that the prey equilibrium density (given by $x=\gamma /\delta$) depends on the predator's parameters, and the predator equilibrium density (given by $y=\alpha /\beta$) on the prey's parameters.

As long as your inputs are consistent with the model (e.g. nonzero), they should come to equilibrium. You are basically finding the abundance states where change in frequency over time is zero.
I don't know much about the deSolve implementation, but I'd suggest varying not the initial densities but the other parameters ($\alpha, \beta, \delta, \gamma$) to see how that changes your solution.
If you are interested in exploring error bounds beyond the classic model, I'd suggest exploring a stochastic version of the model or a different modeling regime.


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Is kranz anatomy not a defining feature of $C_4$ plant?
In NCERT Class 11 chapter 13 it is written that

The particularly large cells around the vascular bundles of the C4 plants are called bundle sheath cells, and the leaves which have such anatomy are said to have ‘Kranz’ anatomy.

In Chapter 6 it is written for dicot leaf that

The vascular bundles are surrounded by a layer of thick walled bundle sheath cells.

So we can infer that every dicot is $C_4$ plant but when I searched on Google I found that it is not.
Where am I missing? Is the kranz anatomy not a defining feature?

Your conclusion doesn't follow logically.
Statement 1: C4 plants have photosynthetic bundle sheath cells arranged in a Kranz anatomy. (I was actually not able to find your quote in the linked chapter, maybe my mistake.)
Statement 2: Dicots have bundle sheath cells.
It does not follow that Kranz anatomy isn't a characteristic of C4, because the presence or absence of bundle sheath is not the same as Kranz anatomy.
Looking at a different educational site (I have no opinion about this site, but it seems fine):

Kranz anatomy is a specialized structure in C4 Plants where the mesophyll cells are clustered around the bundle-sheath cells in a ring-like fashion. The number of chloroplasts in the bundle-sheath cells is more than that in the mesophyll cells. This is found in C4 grasses such as maize and a few dicots.

So Kranz anatomy is not presence of bundle sheath, but rather a specific arrangement of the bundle sheath with regard to the mesophyll.
Note that C3 and C4 aren't nearly as binary or distinct as we might pretend they are- C4 has in fact arisen multiple times from C3 in evolution, so C3/4 are not even taxonomically groups, but rather grouped based on a characteristic metabolism. A few C3 species therefore seem to share some of the anatomical arrangements.
However, the anatomical arrangement is obligate for C4 plants, whereas it is a rarity in C3. See the beginning of this paper:

Kranz anatomy and C(4) vein pattern are required for C(4) biochemical functioning in C(4) plants...

In conclusion:

Don't trust your textbook completely. Seek out other sources of information. Wikipedia is quite good for this, these days.
C4 and C3 are distinguished by relatively subtle features, some of which are convoluted with the features of e.g. grasses, which can be either C3 or C4.
I found your textbook somewhat confusingly written. However, note that at no point did it make strong statements of classification about C3/4 (that I could find). Instead, it simply aimed to describe some anatomical examples. Know when you're doing description, and when you're doing classification! Ideally the book would have a direct comparison of features laid out very clearly, maybe like this, for the task of doing classification.


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Larval abalone devlopmental times - what does ~ °C.days or °C hr-1 mean
I'm looking a number of papers on abalone larval development and the term °C.days or °C hrs-1 keeps coming up. The numbers before these terms are much larger than they would be if this term actually meant days or hrs. For an example of a publication, see here.
for example one source said larvae are competent to settle at 100 °C.days, however they most likely settle at around 7-10 days
Just wondering if anyone knows what this °C term means in terms of time

Welcome Dr Who Fan. :) Could you find a way to link to a source for this seemingly odd notation, to let us see context in case there's some clue?

From e.g.
Fukazawa, H., Kawamura, T., Takami, H., & Watanabe, Y. (2007). Oogenesis and relevant changes in egg quality of abalone Haliotis discus hannai during a single spawning season. Aquaculture, 270(1-4), 265-275.

Oogenesis of abalone Haliotis discus hannai was examined histologically during a single spawning season using broodstock of various maturation conditions, which were controlled by effective accumulative temperature (EAT)

Once adult abalone have experienced an appropriate EAT, they can release gametes when they are stimulated by environmental spawning cues, such as storm events (Sasaki and Shepherd, 1995)

The units on their figures are given in units of "temperature x time", such as "°C x days". This would be integrated temperature over time. In units of °C x days, you would say that 1 day at 20°C = 2 days at 10°C = 10 °C days.
In this context, we're talking about a mollusc that has a seasonal reproductive pattern where temperature controls reproduction, but not simply via hitting some key temperature one time (which would likely be unreliable and lead to spawning in the wrong season given the possibility for temperature extremes), rather by integrating temperature over time. Once the threshold is reached, other cues trigger the actual spawning behavior.
I presume "°C hrs-1" would be "°C hrs-1" which can also be written "°C/hrs" or read "degrees celsius per hour"; that would be a rate of change of a temperature, but you'd need to provide context to verify.
The authors of the paper I link to write in their methods:

EAT was calculated using the formula defined by Kikuchi and Uki (1974).

...but the paper they refer to is in Japanese. It's not clear to me exactly how EAT is defined, but it's quite possible it involves subtracting a reference temperature that is somewhat above 0°C. Hopefully some of the papers you are reading are more clear about this.

(+1) Things are a little clearer here, maybe.  "EAT (effective accumulative temperature) is expressed in
degree days (◦C-days) and calculated by subtracting the BZP from daily
water temperature and summing this value over the rearing time (in
days).  The effect of temperature on gonadal development is cumulative above a certain
threshold temperature that varies between species. This threshold
temperature is termed as biological zero point (BZP; a theoretical minimum temperature at which gonad growth and development begins)"


text:
Paternity testing using gel electrophoresis
When using gel electrophoresis to determine the father of a child, each band of the child must match with either the mother or the father. So half must come from the mother and the other half from the father. However, that does not seem to be the case in the picture below, where does the band 6 come from?

Perhaps the actual father is not included in the tested group?

Can you confirm or deny that "1" is actually the child's father? An explicity description of what is shown on the gel would be helpful here. Can you think of any explanations other than genetics for unexpected bands on gels?

This is a very bad question for a scientific site because it contains no explanation of what is being subject to electrophoresis,  not even whether it is DNA, and certainly not how it has been treated. When this question was posted originally this information should have been demanded of the poster. Certainly the question is unanswerable from the information given. It should be closed.


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What is the relationship between stress granules and circular RNAs?
I have read that circRNAs act as sponges for miRNAs and that stress granules help reduce chronic cellular stress and they are composed of proteins and RNAs. I'm interested in the relationship between these two phenomena in Alzheimer's disease. They both seem to be important to mark the disease and there is possible evidence of circRNAs in stress granules.
Is there a specific relation between the two? I would like to know even if it doesn't actually relate to the disease or not.

Can you cite/link the references that you have read that state this?

Stress Granules source : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256948/

Circular RNAs source: https://pubmed.ncbi.nlm.nih.gov/30259371/

I've added these citations as links, as well as a potentially useful citation for the relationship to Alzheimer's.

Thanks! That link is pretty useful.


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What is a random piece of DNA called?
If I picked up a DNA molecule and randomly snipped out a piece with scissors what is the scientific name for the resulting piece?
I'll confess right up front that I am not an academic or professional. I am retired and write science fiction for a hobby but I like everything in my stories that can be true and correct to be so.
In my current novella I have AI searching through the entire human DNA molecule (coding and non-coding) for a piece of DNA not related to grains but to a grain viroid. I am aware that viroids only infect plants but for my story I need a piece of this viroid to have spliced itself into the DNA of grains. That will then be found in the DNA we share with grains. Like the DNA we share with chickens, fruit flies, and bananas.
In my novella the reason for this is that it is a part of the trigger sequence for human metamorphosis which then takes place over ten thousand years. Just as things like body weight, food scarcity, etc. are triggers for metamorphosis in other animals, eating large amounts of grains is the trigger for human metamorphosis in my current story. Eating large amounts of grains means the development of agriculture and thus civilization. In my fictional universe where earth-like humans are not unique but common (due to convergent evolution) the birth of a new civilization means the beginning of their end unless they can escape the confines of their planet of origin before they destroy themselves via some version of the great filter.
Metamorphosis in other animals is an evolutionary strategy that is believed to have developed for similar reasons.
The metamorphosis that is triggered in humans leads to the development of AI and robotics and the next stage of life for the species. It enables them to spread to other worlds (which our organic bodies can't do in time) just like dragonflies leaving their pond.
"Why is humanity so compelled to create artificial life in its own image? Perhaps the caterpillar feels the same as it builds its chrysalis and for the same reasons." -- quote from my story, Metamorphosis And The Messenger.
So that's the big idea. As I was writing a paragraph about this search I wanted the correct word for a random piece of DNA. Google's AI only responded with names for specific pieces of DNA like genes, bases, exons etc. So since Google's AI is not smart enough to handle my question here I am. Maybe it's just called a "piece" but if there is a proper, scientific name I would prefer to use it.

Not in reference to this specific question necessarily, but it occurs to me you might like our [worldbuilding.se] stack. It exists for the express purpose of helping writers, artists, game-designers etc. design their fictional world. (Take their tour, read-up in their help centre before posting.)

Hi NetCentric, and thanks for posting your question. A few things: (1) you say "the entire human DNA molecule" -- the diploid human genome is comprised of 23 chromosome pairs, so 46 individual molecules (92 if you consider dsDNA to be composed of two interacting ssDNA strands). (2) I agree with Jiminy that your question is likely a better fit for the worldbuilding stack.

Thank you for suggesting the Worldbuilding stack. I was not aware of this resource but will check it out now.

If you were to literally chemically remove a piece, as with restriction enzymes or physical disruption, that would be a "fragment".
If you just mean a focal region of a genome, then "locus" or even just "region" would do.
I'm aware it's a SF premise and not meant to be super robust scientifically, but how do you see a pattern of descent in which a viroid that infected a grain (a plant) gets into a human (an animal that diverged 1 billion years ago, long before there was such a thing as multicellular plants)?
It's formally possible via horizontal gene transfer when people eat grasses I suppose, but then it's not part of the commonly inherited regions that we share with the other organisms you mention, as those branched off long before.
I suggest looking into work on ultraconserved genomic elements as relevant to the mechanism by which the "AI" might work. These methods are relatively commonplace though, not sure that they merit the buzzword though.

Thank you for for answering my question. I really appreciate it. Also thanks for pointing out the pattern of descent and  horizontal gene transfer issues. As I pointed out I like things to be scientifically correct as far as possible so I will see if I can come up with another way to make the connection with agriculture. That part of the story is not yet written. If I can't find another mechanism well that's when the fiction part comes in. Thank you again.

To be clear, the "piece" OP is looking for should probably just be called a "gene". It would be reasonable to say that the AI is checking fragments of DNA for a gene introduced by a viroid, if taking all the premises as reasonable.

It's not clear to me why the AI would need fragments, though; given modernish technology they might as well operate on the whole genome. It seems they're looking for something suspiciously conserved from wheat to humans despite having no known function in either.

@BryanKrause I like "locus" in context as being a bit noncommittal about what exactly the piece of DNA is. If it's a viral genome/viroid relict, then "gene" isn't quite accurate. Yes, I agree that the work on ultraconserved elements could be relevant here; i will update to include.

@MaximilianPress I think of "locus" as a position in a genome rather than something functional. Even if the product is unknown (or if it's unknown that there's even a product vs a regulatory role) wouldn't gene be better?

@BryanKrause We commonly refer to "the YFG1 locus", where YFG1 is a gene. TAIR has genes under "locus" heading: https://www.arabidopsis.org/servlets/TairObject?accession=locus:2043520. I think of "gene" as meaning something rather specific as a defined transcriptional unit. I don't think this is what OP means, since "viroid" or "piece of viroid" is not necessarily transcriptional, and if it is, it is probably not a single unit. If we wanted to look for something in the archaic Johannsen sense of a generic, heritable-material-agnostic "unit of heredity", maybe then "gene" would be appropriate.

@MaximilianPress I think I'm leaning newer, rather than older, the definition that eg Wikipedia captures as "a broad, modern working definition of a gene is any discrete locus of heritable, genomic sequence which affect an organism's traits by being expressed as a functional product or by regulation of gene expression"; specifically that final 'or'. But I suppose it's still unclear whether OP's chunk should be a single gene, or multiple, or what... I still think of "locus" as being a bit more like a street address with reference to a chromosome.

Of course there's a lot of overlap there, too, because if a building is on fire at 11 Wall St., whether you refer to the building or refer to it by address you still mean the same fire.

@BryanKrause Yes I think that we broadly agree, I find the wiki def'n to be a bit too vague but that's really a matter of taste. When we talk about the kind of algorithms that people use for this purpose I think that a "street address" is certainly appropriate, to follow your analogy.

@MaximilianPress Yes, I suppose as long as you phrase it as "you are looking for the place in the genome where this viroid-origin DNA exists" then a "locus" is fine; I still don't think that the thing you find there can be a "locus", but as you say, these can be somewhat interchangeable practically.

@MaximilianPress Thanks for the tip re: ultraconserved genomic elements. It looks like a promising alternative for the story given the pattern of descent issue you pointed out.


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Reference for standardized histology rating criteria of microscope images
I am looking for a reference to a standard protocol for assessing the visual quality and diagnostic potential of a tissue sample that has been processed and stained for viewing under light microscope. What kinds of things are important to look for? For example the overall morphology, cellular outline, integrity of structures, nuclear details, lymphocytes and erythrocytes, etc...
I am looking for a paper that explains what things to look for in a well processed sample. Thank you

I think this question would be a better fit in Biology.SE because histology is much broader than medicine.

Consider the 1951 USAF resolution test chart (inline below). It has arrays of progressively smaller spatial frequency features. Just find the smallest feature that can be resolved and use this as a metric to compare to other brightfield microscopes in your facility.

Such charts are available from Thorlabs, Newport, and Edmund optics. Edmund also has a calculator to use with it which provides the resolution in line pairs per mm.

I have edited your answer to direct include the image and a link to wikipedia for the item, and the additional info you provided by comment. This is the kind of thing that I meant. Also note that while you have addressed issues of resolution, you have not really addressed the more relevant (IMO) biological side of the question.


text:
Are introns conserved among cells?
To elaborate on the title: Among somatic, post-mitotic cells, would the same intron on a given chromosome have the same sequence among all cells descended from a progenitor cell?

Welcome to SE Biology! See here for some advice on ways to ask questions that are likely to get a helpful answer. Have you looked at any examples of introns on the same chromosome? Can you cite any sources suggesting what you ask is the case?

Hi I'm just asking out of curiosity. Not sure how, if I got a sequence, I would know whether that would be the same for each cell in a sample, given that genomes are assembled from several reads and sometimes individual bases are averaged, right? Just off the top of my head, I figured that since introns are not coding for proteins but do regulate gene expression, there would be less of a force for their sequence conservation between divisions from a stem-like progenitor, but that's why I'm asking.

Could you perhaps edit your query to include those details with any appropriate references as comments are ephemeral in nature and we want to questions to be self-contained and last over time. Please also take our [tour] and refer to the [help] for guidance as to our ways.

I think that ignoring genome assembly for now may clarify the issue. I still don't understand the question. Are you referring to the same intron across different cells, or different introns on the same chromosome? Your comment makes it sound like the first, but your question makes it sound like the second.

Sorry for being unclear. I meant the same intron, on the same chromosome, in different cells. Also changed the question to reflect this.

I believe that the kind of mutation that you are interested in is somatic mutation, as opposed to germ-line mutation.
Any given genomic locus (intron, exon, intergenic region) probably doesn't mutate most of the time. In the case of somatic mutation, it is yet more likely that no mutation happens.
Nonetheless, such mutations do happen, in all of those different regions. For example, here is a study that catalogs somatic mutations in introns that lead to a particular phenomenon called intronic polyadenylation; here is another that catalogs intronic mutations that mess up splicing.
The same is true for protein-coding somatic mutations, one can find similar catalogs of mutations for those.
Such mutations in different regions (intronic, exonic, and otherwise) are all of interest as events that can lead to cancer.
None of this should distract us from that fact that usually mutations don't happen at any given site. But it's a question of probabilities, not of absolutes.

OK humor me this. What if you were trying to engineer, using some DNA editing technology, several cells in a sample at once, and wanted to precisely introduce a double-stranded break at some intronic site. Would the risk of somatic mutation ever be a concern? Thanks

@UD22022 Somatic mutation is always a possibility. But, frankly, the efficiency of gene editing technologies is (at a guess) a 2-3 orders of magnitude higher than the rate of somatic mutation. You could not exclude the possibility without recovering and analyzing the edited cells. But you generally have to isolate, select, and culture edited cells anyways. I would say that it is a theoretical concern worth keeping in mind examining data, but likely not a regular practical concern for gene editing compared to e.g. the rate of off-target effects of editing.


text:
quiescent stage (G0) occurs at the end of M phase or G1 phase:
I know that G0 phase occurs when certain cells exit the cell cycle during G1 phase but that means it goes to G0 phase after M phase right?

Welcome to SE.Biology! It is often helpful to do a little internet research such as e.g. googling your question.
I googled it and it gave me this image, which tells me that G0 cells leave from and re-enter G1 phase.


text:
I need to identify the genus of this colony just by its morphology, can somebody help me?

it was grown on TSA
it's a mesophilic bacteria.

(it was contaminated by E. coli, so ignore the clearer and smoother colonies).

Do you have any more information? Is this a school project? why only the genus? "mesophilic" --> what exact conditions did you grow it under?

@MaximilianPress yes it was supposed to be a lab work in my uni, but because of the virus I don't have more information about it and still have to write a report and the task is to identify the genus just by its characteristics. I only know that it was grown on TSA, under mesophilic conditions (~30 C) for a week. My guess is this is Bacillus genus since the biofilm is wrinkly, but I want to hear other opinions.

Perhaps you were to do a Gram stain as well; which was cancelled. I had thought Bacillus also.

@PolypipeWrangler yes, I'm sure gram staining was planned too. Thank you for your response!

Maybe present  an analysis based upon each of the possible results of a Gram stain also.


text:
How does the immune system find the DNA code for antibodies
There are millions of possible antigens. To respond to each antigen, the immune system must quickly produce an antibody by modifying the DNA of a B cell.
I have no idea how this process works, but surely it can't be by trial and error.
So I thought how I would do it:

The part of the pathogens DNA that codes for receptors is copied
then an algorithm is applied that transforms this code into an antibody code.
This code is then pasted into the DNA of the B cell. So the B cell has antibody receptors that fit on the antigen.

But how does it work in reality?

Please read up on clonal selection and V(D)J recombination.

And yes, it happens through trial and error.

Thanks, that answers my questions. Apparently we have 10^12 B-cells predefined in our body generated by a random process. Amazingly that the correct antibody is found in relative short time of a few days.

@Jacq: consider answering your own question with what you found, that might make it easier for future users to use the answer.


text:
Is there any reliable data about the correlation between the size of a species and number of individuals that belong to it?
I'm curious to know if such a collection of data exists, so I could visualize it with a graph, and see how humans compare to other spieces of similar size.

I don't think this question is meaningfully answerable, since the number of individuals that belongs to a species changes dramatically over time as its environment changes. Consider for example, the change in the population of the passenger pigeon during the past 200 years.

@jakebeal, I think that any graph/data is accompained by the year(s) it was collected.

I think that you are interestd in scaling laws https://physicstoday.scitation.org/doi/10.1063/1.1809090#:~:text=In%20biology%2C%20the%20observed%20scaling,the%20mass%20of%20the%20organism.

There might be something in the field of Macroecology, e.g. J. Brown's Princeton Monograph (??) on the topic ...

What exactly do you mean by the “size of a species” and how could it possibly be different from the number of individuals that belong to it?

@Wrzlprmft help me reword it. I mean the body size of the (average) individual belonging to that species.


text:
Inheritance simulator not working properly
I created a python program to simulate inheritance (a simplified version of it) to better understand how it works. A person is represented by a class that contains a chromosome property, a method for reproducing with another person, a method for generating gametes (through recombination), and a method for calculating how similar a person is to another person (by comparing the chromosomes).
The problem with my program is that cousins are not as similar to each other as they are supposed to be. My program says that 2 cousins about 75% similar when they should be 12.5% similar. I don't understand why this is. I think it could be down to 2 things

My similarity function is wrong.
The way I am representing a chromosome is wrong.

Here is the code:
    import random

    CHROMOSONE_LENGTH = 1000
    NCHROMOSONES = 22

    class Person:
        def __init__(self, chromosones = None):
            self.chromosones = chromosones
            if  chromosones is None:
                self.chromosones = []
                for i in range(NCHROMOSONES):
                    self.chromosones.append ((self.get_random_dna(),self.get_random_dna()))

        def get_random_dna(self):
            #return [random.random() for x in range(CHROMOSONE_LENGTH)]
            return [random.choice(["0","1"]) for x in range(CHROMOSONE_LENGTH)]

        def get_gamete_meiosis(self):
            gamete = []
            for i in range(len(self.chromosones)):
                gamete.append([])
                for a,b in zip(self.chromosones[i][0],self.chromosones[i][1]):
                    gamete[i].append(random.choice([a,b]))
            return gamete

        def reproduce(self,mate):
            chromosones = []
            my_gamete = self.get_gamete_meiosis()
            mate_gamete = mate.get_gamete_meiosis()
            for i in range(NCHROMOSONES):
                chromosones.append((my_gamete[i],mate_gamete[i]))
            return Person(chromosones)

        def get_similarity(self,other):
            sim = 0
            for s,o in zip(self.chromosones,other.chromosones):
                for a,b,c,d in zip(s[0],s[1],o[0],o[1]):
                    if a == c or a == d:
                        sim += 0.5
                    if b == c or b == d:
                       sim += 0.5

            return sim/(CHROMOSONE_LENGTH*NCHROMOSONES)

    grandmother = Person()
    grandfather = Person()
    child1 = grandfather.reproduce(grandmother)
    child2 = grandfather.reproduce(grandmother)
    grandchild1 = child1.reproduce(Person())
    grandchild2 = child2.reproduce(Person())
    # Should be 12.5%
    print(grandchild1.get_similarity(grandchild2))

A chromosome is represented by an array of 2-tuples. Each tuple represents a chromosome pair. The number of pairs is set by the NCHROMOSONES variable. There are 22 pairs in the above code.
The actual genetic data is represented by an array of 0s and 1s. The number of 0s and 1s in a chromosome is set by the CHROMOSONE_LENGTH variable.
The similarity function takes two people and compares them at each position of each chromosome. If the two people have the same number at a given position, then it adds 0.5 to the sim variable. It then averages this across all positions. The reason I add 0.5 is because two people can either be 0%, 50% or 100% identical at a given position on a chromosome. 0% occurs when neither pair is identical, 50% occurs when 1 pair identical, and 100% occurs when both pairs are identical.
I noticed that as I use more symbols than just 0 and 1 to represent genetic data, the similarity actually approaches 12.5%. But I don't understand why this should be.
So my basic questions are:

Is my way of calculating the similarity correct.
Why can't I use just 0 and 1 to represent genetic data?

There are a couple of things going on here, I think. Let's start with simple conditional probability:
import random

sim1 = [random.choice([0, 1]) for x in range(1000)]
sim2 = [random.choice([0, 1]) for x in range(1000)]
for locus in range(1000):
   if sim1[locus] ==sim2[locus]:
     match+=1
print(match)
# prints 492

In other words, even two completely independent samples from [0,1] with uniform probability are expected to match about half of the time (492 / 1000 ~ 50%).
So you are correct, the problem lies in your fashion of encoding the data. When you are talking about "similarity", what I think you mean is "identical by descent". This is distinct from "identical by state", meaning what actual alleles you have.
Two individuals can be identical by state at a large number of loci without any significantly close family relationship, if they are members of a population without a lot of common alleles. This is close to what we mean when we say that humans are all 99.9% identical to each other- this is because most of the positions in the genome have very little variation. So, if you choose two people who have no common ancestors in the last 1000 generations, they will still be identical by state for >99% of their loci. This is the real lesson that your simulation is showing you, I think!!
If you want to show identity by descent, you will have to choose a different encoding. Using e.g. nucleotides will still run into the problem that very frequently the nucleotides will be identical by state in unrelated individuals, whereas what you actually care about is "did this allele originate from the exact same ancestor". So you want some way of guaranteeing (or nearly so) that every ancestor contributes a distinctive, unique allele that you can always distinguish. For example, the following code will produce a "unique" identifier that could be used for each founder individual (e.g. every time you call Person():
import uuid
unique_id = uuid.uuid4()

So really, what your Person.get_random_dna() method should do is something like this (minimal modification to your code):
        def get_random_dna(self):
            unique_id = uuid.uuid4()
            return [unique_id for x in range(CHROMOSONE_LENGTH)]

You may need to fix something else as well, I have not actually run this.

What would be the equivalent of my 0s and 1s for actual dna? Would it be a,t,c and g? So that means I should only need 4 symbols? Excuse my ignorance, but I don't know much about this.

@user1235598399 It depends a bit on what your application is, but the nucleotide symbols won't fix this- they will merely change the error to one in which the probability distribution is somewhat different. If I am correct and your goal is to understand "identity by descent", then you might consider coming up with a unique hash for each "founder" individual and using that as the signifier for its genotypes. I'll update answer to reflect this.


text:
Difference between Processing and Preprocessing
In the wikipedia article of emotion lateralization it is mentioned:

The right hemisphere is important for processing primary emotions such as fear while the left hemisphere is important for preprocessing social emotions

So I am wondering what exactly processing and preprocessing mean? What happens in preprocessing that they use this distinct word instead of mere processing?

They cite a source for that sentence, you'd have to go there. They probably talk about some later step that they think of as "true" processing, but there is no standard neuroscience answer to your question.

@BryanKrause you mention that they "think", so is it not well established?

I take it to be purely their opinion and narrative description. It does not have other meaning unless they define it.


text:
Do SILK fibres let light pass through it?
The reason given by Wikipedia for silk fibres being lustrous is that:

Silk fibres have triangular prism-like structure, which allows them to refract the incoming light at different angles.

By my understanding, refraction takes place only when light enters another medium. (This is only for reference)
My question is: Do silk fibres allow light to pass through them?

If the question is not suitable for this site, I would like it to be transferred to the another site. Thanks!

Nobody bothers to reply.....

Patience, many of us are asleep or at work.

How is this about animal husbandry?

@MattDMo I beg your pardon, but you all are making fun of someone who is not as experienced and knowledgeable like you.

Welcome to Biology.SE! Please take the [tour] and then go through the [help] pages starting with [Ask] questions effectively on this site and [edit] or delete your question accordingly. MattDMo was pointing out a mistake in your post — constructive criticism is encouraged on this site. ——— Also, note that as written this question doesn't appear to be about biology, but instead about the optical properties (physics) of a biological material and so would seem to be off-topic for this site. Please consult the above links and [meta] for details.Thanks!

@user100323 you tagged the question animal-husbandry and I simply inquired how this question and that tag were related. You are a member on enough other Stack Exchange sites that you must surely know how the tagging system works, so your plea of ignorance doesn't hold any water. The other comment was in reply to your complaining about no one commenting on or answering your post yet - not making fun at all. Here's a hint: when joining a new community, educate yourself about how it works instead of complaining about everything.

@user100323 as for your actual question, if the reason for silk fibers' being lustrous is that they diffract light, then of course light can pass through them. The Biology.SE community has agreed that questions that show little or no prior research effort are off-topic on this site unless you have shown your attempt at an answer. Please see our homework policy for more information. Additionally, as indicated above, this is not even about biology, it's about physics. Please read the [help] to learn more about this site.

Yes, silk allows light through.
I did a google scholar search using terms:
optics of silk
Lots of articles, the article below measures a refractive index of about 1.54
Paywalled except abstract and figures.
Bucciarelli, V. Mulloni, D. Maniglio, R.K. Pal, V.K. Yadavalli, A. Motta, A. Quaranta,
A comparative study of the refractive index of silk protein thin films towards biomaterial based optical devices,
Optical Materials,
Volume 78,
2018,
Pages 407-414,
ISSN 0925-3467,
https://doi.org/10.1016/j.optmat.2018.02.058.
Found at:
https://www.sciencedirect.com/science/article/abs/pii/S0925346718301241


text:
Statistics for ratios to wildtype growth
I have a large dataset that represents a library of yeast deletion mutants and their growth under treatment from a compound. In the library alongside the mutants is a wild-type strain and I want to express each mutants response to treatment as a ratio to the WT response in order to highlight mutants that show abnormal sensitivity to the compound (hyper-sensitive or resistant) . So far I have settled on a formula to calculate the ratios but am struggling to think of a way to test for significance of results.
For example (not actual data, just for demonstration of data structure):

where I am calculating corrected ratio as:
((growth of mutant treated)/(growth of WT treated))/((growth of mutant at control)/(growth of WT at control))

i.e correcting the ratios with treatment to account for difference in growth at control condition
This then allows me to define sensitivity as corrected ratio<1 and resistance as >1
Is there a way to incorporate a simple statistical test into this to highlight ratios that show significant difference from the WT (where the ratio will always equate to 1)? I have replicates for each mutant and WT (typically N=4) so can easily calcutae SD/SEM etc.

See this answer on Stats.SE for an appropriate significance test. Unfortunately, it's not 'simple', in that you'd have to implement it yourself - I don't know of any software that has it built-in - and you'd also have to modify it to be two-sided. The plus side is, because it's a permutation test, it's appropriate for your small sample sizes, unlike most parametric tests.


text:
Frogs stop croaking at same time
I know frogs start croaking at the same time to attract a female.
Why do they all stop at the same time?

Calling is a risky activity because it makes the frog conspicuous to predators. When calling in a group, the risk to any given individual is minimized to the point that the minimal risk is outweighed by the advantage of attracting a mate. However, a single frog calling on his own is assuming all of the predation risk. So, the frogs are playing a bit of game theory and when too few are calling simultaneously to make the risk worthwhile, they will all tend to stop.


text:
Database of unique attributes of biological model systems
I am interested in deviations from standard eukaryotic biological mechanisms:

Sperm chromatin lacks nucleosomes, and are instead highly condensed by protamines. (most eukaryotic chromatin has chromatin with nucleosomes).
Camelid and cartilaginous fish antibodies are single-domain (most vertebrates have heavy chain + light chain antibodies).
Drosophila homologous chromosomes undergo transvection and are tightly paired. (Transvection is not usually observed in eukaryotes.)

These are some of the unique peculiarities I've found among model systems that deviate from "expected" biology. Is there a running database that catalogues unique attributes of different model systems? If not for trivia, I find them extremely inspiring for mechanistic studies!

I find this to be a very interesting question, but I think that it's critically important for you to be clear about 2 things: 1) what is the taxonomic level of focus? 2) for any given taxonomic level, what is the "expected" biology that is deviated from? I have edited to try to reflect this better.

No database that I've heard about. But you can add achiasmy to your list (absence of homologous recombination in some drosophilid and lepidopteran males). I've always found that intriguing and sometimes a useful exploit for genetic crossings.


text:
How is a haploblock defined with only one SNP location?
I am reading Impact of estrogen receptor gene polymorphisms and mRNA levels on obesity and lipolysis – a cohort study and am looking at Figure 1. I understand that haplotypes are associated with higher levels of linkage disequilibrium and that the intensity of the red indicates a high level of linkage disequilibrium. How then is a haploblock determined for Block 2 where only one SNP location is given? I am thinking linkage disequilibrium is a measure between at least two SNP locations.

In Figure 2 how are haploblocks determined when all SNP locations compared are displaying high linkage disequilibrium? Also, why are locations 5 and 6 excluded?

Reading the methods
In the methods, it is stated that haplotype blocks were inferred with the software Haploview:

Genotype information for ESR1 and ESR2 and regions
approximately 10 000 base pairs up- and downstream of
these genes were downloaded from HAPMAP in May
2005 [33]. Genotype data for the population of individuals of European ancestry were visualized using Haploview
[34]. We initially selected tag-SNPs defining all haplotypes with frequency > 5% from the block-by-block tags
displayed in the HAPLOVIEW "Haplotypes" window.
However, sometimes these tag-SNPs were exchanged to
other SNPs on the same haplotype due to difficulties in
designing genotyping assays. In addition, in regions not
covered by common haplotypes we aimed to select one
common SNP (allele frequency > 5%) every 5 000 base
pair. No non-synonymous SNPs full-filling these criteria
were detected in the ESR genes.

Haploview documentation writes:

Blocks
Haploview generates blocks whenever a file is opened, but these blocks can be edited and redefined in a number of ways. In the Analysis menu, you can clear all the blocks in order to start over, define blocks based on one of several automated methods or customize the parameters of those algorithms. Additionally, the blocks can be edited by hand.
Confidence Intervals [DEFAULT]
The default algorithm is taken from Gabriel et al, Science, 2002. 95% confidence bounds on D prime are generated and each comparison is called "strong LD", "inconclusive" or "strong recombination". A block is created if 95% of informative (i.e. non-inconclusive) comparisons are "strong LD". This method by default ignores markers with MAF < 0.05. The MAF cutoff and the confidence bound cutoffs can be edited by choosing "Customize Block Definitions" (Analysis menu). This definition allows for many overlapping blocks to be valid. The default behavior is to sort the list of all possible blocks and start with the largest and keep adding blocks as long as they don't overlap with an already declared block.

So, assuming that they used default parameters, you can reconstruct their methodology from the default method documentation and their description:

Take that default haplotype block output.
Where that default output didn't describe a block, select a common SNP every ~5Kbp in the unblocked region.

Answering your questions
In figure 1, the SNPs displayed are all tag SNPs. They are not the only SNPs in the block, but rather the tag SNPs used to represent the block. I am not clear on why multiple SNPs are used in some cases and single SNPs in others, unless they just try to have 1 SNP every ~5Kbp in general. I don't think that's what they did, judging from the figures.
In Figure 2, presumably the blocks are the output of the Gabriel et al. 2002 algorithm using D'.
The single SNPs that are not part of any block are presumably derived from the "every 5Kbp" procedure for regions not labeled with haplotype blocks.

Thank you, Maximilian Press, for your very helpful response! I am very excited to finish reading this paper.


text:
What allows diverse ecology to thrive despite forces reducing species diversity?
Ecology and business are a useful model for understanding one another. One species fills a niche until it is outcompeted by another just as one business fills a niche until it is outcompeted by another. Businesses adopt successful strategies and traits from others, roughly akin to horizontal gene transfer, and fail should they become no longer able to compete.
The breakdown of this duality reveals interesting questions about differences between the two where one would expect similarities. One big example of this, and the topic of this question, concerns the trend of de-diversification in business. Over time, competitive industries tend toward a decrease in number of companies (species) filling a niche, with major shocks (like COVID-19) tending to cause smaller businesses to go extinct, and the strengthening of bigger players. Once a powerful oligopoly is established, it is almost impossible to overturn.
Yet in Earth's history, there have been countless major and minor extinction events, and countless highly successful species dominant in their niche that have been successfully displaced by smaller, newer competitors. Why is it that new competitors can compete with entrenched incumbents in biology, maintaining species diversity in biology where it fails in business?

You are incorrect about the business part of this, as there are numerous examples of near-monopoly businesses being displaced by new competitors.  For instance, the US "Big Three" automakers losing market dominance to foreign companies, on-line retailers taking market share away from malls, cell phones replacing land lines...  And have you tried to buy an incandescent light bulb lately?

There's a lot to unpack here. I'll try to leave an answer later. I'll share one initial observation: You seem to strongly emphasize the inmpact of competition or competative exclusion, perhaps because it's so ingrained in the philosophy of capitalism. But there are a number of factors that go into determining diversity in an ecosystem besides just competition. Related keywords: Niche partitioning, cross-feeding, mutualism, community succession, niche construction, intermediate disturbance hypothesis.

I have found that when learning about a new area starting with a relatively accessible and reliable source like Khan Academy is very helpful. Wikipedia is also generally a good starting point and you can then check their references. Online platforms called MOOCs offer free (or very low cost) courses on a wide variety of subjects — two I am familiar with are Coursera and edX. Finally, textbooks with a good level of detail are also freely available online e.g. from NCBI.

I agree with jamesqf. It is not at all clear to me that ecology and business show any fundamental differences based on the information that you've presented, which is only a series of assertions. If jamesqf's counterfactuals are insufficient to convince you, it would be helpful to understand why not. If you have such information, it would be helpful to share it or link to it if you want a meaningful answer to the question.


text:
Are there any organisms that are made of more than one (~5-12) cell?
Prokaryotes and eukaryotes are unicellular, made of one cell. Great. Eukaryotes are unicellular or multicellular. But the typical examples of multicellular eukaryotes we have are made of, often, trillions of cells, like us humans. Ants must still be made of many millions of cells. Are there known eukaryotes with very few cells that make them up? Like, 5, or something? Or maybe a dozen cells making up the whole organism in its fully developed state?

Well, there are multicellular prokaryotes too but they are not obligately multicellular. You may find the case of Caulobacter cresentus interesting. You can describe it as a bicellular bacteria however it exists as a single cell in one of the stages of its life cycle.

Does this answer your question? Are there oligocellular organisms in nature and, if so, what are they like?

It seems like there's overlap, but they are not the same. That question is about what oligocellular organisms are "like", whereas this thread seems to simply involve listing them out, as many as we can, and focusing on just how small, really, they can get. I think it's valuable to have both of these up.

There's Trichoplax adhaerens, a Placozoa, made of a few thousand cells. Then there is Dicyema japonicum, a simple mesozoan, made up of 9 to 41 cells. Arguably, the simplest multicellular organism is the algae Tetrabaena socialis, whose body consists of 4 cells. Then, there's the parasitic Myxozoa which have 7 cells.

An interesting follow up question would be: at this scale, how do we draw the line between unicellular and multicellular? E.g. can you kill a Myxozoa by splitting up the cells? What would that tell us?

This nematode always has either 959 or 1031 cells.
https://en.wikipedia.org/wiki/Caenorhabditis_elegans

An interesting note is that the nematode is the smallest multicellular organism with a nervous system.

Species from Gonium genus are typically 4-16 celled. Gonium pectorale is 16 celled.
Arakaki, Yoko et al. “The simplest integrated multicellular organism unveiled.”, vol. 8,12,  e81641. 11 Dec. 2013, doi:10.1371/journal.pone.0081641
Also, there is four celled Basichlamys sacculifera. See this picture for reference

There is a whole class of organisms called "oligocellular" organisms, see also here on SE.