text:
Can you help with insect identification? (Outback Australia)
This was in my child's shoe that was left outside. They got it out of the shoe and it went on the wall where they measured it. The body is approx 3 cm and from head to tail it's 6 cm. Any help would be greatly appreciated!
We are in central Australia in the Outback.

It is a cricket very similar to Potato bug found in North America and a female having a long ovipositor.

Wait until somebody else responds, you may get an answer with species level identification.

Could this be related to the "Weta" from
New Zealand ? It looks quite similar to https://en.wikipedia.org/wiki/File:Tree_weta.jpg

This is a member of the family Anostostomatidae, but given its sex is unlikely to be placed further (many Orthoptera are best identified on the basis of males, including this family).  There don't seem to be internet-based identification tools for the group (but the page http://bie.ala.org.au/species/urn:lsid:biodiversity.org.au:afd.taxon:a8042a0a-f34e-4ae3-ab86-5306b9176774#gallery shows a number of specimens and living examples, the latter usually taken only to family); Chapter 5, "Australian king crickets: distribution, habitats and biology (Orthoptera: Anostostomatidae)" in the book The biology of wetas, king crickets and their allies appears to be the best option I've seen that might allow a further identification.

I see that you are answering a lot of entomolgy species ID questions but never provide (internet) references and rarely elaborate much which makes it very hard to tell if your ID is correct or not - this probably is the reason you receive down-votes. To avoid that, please link to sources with images or include these images (depending on photo license) in your post. This will allow others to see the reasons for your ID and give them the opportunity for further reading. Thank you!

The insect you have is commonly known as a Weta. The Weta covers over 70 species, two superfamilies (Stenopelmatoidea, Rhaphidophoroidea) and two families (Anostostomatidae and Rhaphidophoridae).
I believe this is from the Superfamily Stenopelmatoidea and Family Anostostomatidae. Let me let me tell you why.
The two families are separated based in part of their anatomy of the ovipositor - to be non-technical: the stringer-looking projection on its butt. This is a tubular organ through which the female insect deposits its eggs.

Figure 1. Anatomy of Cricket
From “The Biology of Wetas, King Crickets, and their Allies” the main differences between Rhaphidophoridae and Anostostomatidae are as follows:

Anosto-stromatidae are characterized by dissimilar ovipositor - The
  lower part of the upper upper valae are inserted in special furrows of
  the lower valvae.
Rhaphidophoridae  Ovipositor - the lower valvae are covered with the lower parts of
  the upper valvae on the outside (a trait found in both
  Rhaphidophoridae and Stenopelmatidae).

If we take a look at your first picture again, you will notice that there is a furrow going around the ovipositer. This why I believe it is from the family Anostostomatidae.

Finding the correct genus is a little more difficult. Nearly all 70 species of Weta are located in New Zealand and Australia. Here is a pretty good summary of the different Weta Species. I would say this is a female tree Weta, more specifically the Hemideina femorata.

Interesting side note, the Giant Weta is considered to be one of the heaviest insect in the world, with one female weighing in at 2.5 oz!!

Graham Chiu had it right, he's just posted a picture of a male (they are highly sexually dimorphic) - the female is lighter in colour and has an ovipositor, while the male is dark with curved cerci. The book that has been mentioned a few times (The biology of wetas, king crickets and their allies) is a great resource, I have it on my desk at the moment actually. I am studying a close relative of these creatures, the Wellington tree weta (Hemideina crassidens) and the females look very similar to these ones - see my profile pic for one of my girls! We get weta in the city when they belong in the bush, they travel in vehicles, on clothes, on other animals, they're pretty good at getting around, so I wouldn't be surprised if one managed to make its way to the outback.

Please feel free to add some reffereces. :)

Looks like a king cricket, Anostostoma australasiae

http://www.qm.qld.gov.au/Find+out+about/Animals+of+Queensland/Insects/Grasshoppers+Crickets+and+Katydids/Common+species/Giant+King+Cricket#.WIs179XRU0M

Please explain why and how.

And especially explain why the spiny legs and dark color are missing. And how this rain-forest dweller of SE Queensland ended up in the outback...


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What voltage damages a neuron or a group of neurons?
Neurons are stimulated for research and therapy purposes. How much voltage (current, duration, etc) can a neuron or a group of neurons, in humans, take without being damaged?

There are way too many factors involved to give you a simple number, and "damage" is also a very non-specific term. Also, when you write "voltage (current, duration, etc)" it makes it sound like you don't know what terms like voltage and current mean: for example, current is not a type/part of voltage, so you might want to start there first.

i know current and voltage are different but related quantities.  for damage,all three or any one of the three parameters may be enough;that is why i included all. also, yes,damage is subjective,so be it. if you know anything about any type of damage,write about it. are there so many types of damage that it cannot be summarized here? even then, some major ones can be mentioned.

also,another way to think about it is how much is known to be safe.

It probably mostly depends on how you stimulate them, when we probe the ulnar nerve in practical classes with a stimulator on the skin, then 20V seems about fine. Most students will handle 20V 100 ms pulses, but some will flinch.
If you have a neuron connected directly to an electrode (in a dish), then you will get decent responses from 50-100mV square voltage steps. Individual cells will respond after 10-40 mV (depending on cell type), much more than 150-300 mV will probably be problematic (and not physiological) for single cells.
It sounds like you need to read some early electrophys, start with the squid giant axon, then Neher and Sudhof were the gods for the start of my PhD.

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What is the body density of insects on average?
What is the body density (in $\text{g}/\text{cm}^3$) of insects and is there a list of animals and their value of body density?

A recent studya measured the volumes (using a 3D scanner) and dry masses of 113 different insect species. They found the following relationship between the dry mass of the insects and their volumes ($V[mm^3]$ and $m[mg]$):
$\ln (V) = 1.019 \ln (m) + 1.46$
$\Leftrightarrow V = 4.30596 m^{1.019}$
Thus, since $\rho = \frac m V$
$\rho(m) = \frac m {4.30596 m^{1.019}} = \frac {0.232236} {m^{0.019}}
 $
Figure: Scatter plot of the measured dry masses and volumes

Reference:
a Kühsel, S., Brückner, A., Schmelzle, S., Heethoff, M. and Blüthgen, N. (2016), Surface area–volume ratios in insects. Insect Science. doi:10.1111/1744-7917.12362

On the graph the Volume is in $mm^2$ $\ddot \smile$ So the density is a decreasing function of the mass. Below, 0.2 grams, the density becomes very important. To make the graph in R: f=function(m) {0.0346737 / (m^1.34633)}; x = seq(0.01,20,0.01); plot(x=x,y=f(x), log='x', ylab="density (mg / ml)", xlab="Body mass (mg)")

@Remi.b I did not make this graph, it's from the study. Yes, the density function graph is a hyperbola.

Of course. I just wanted to comment on this 'weirdosity' and to offer a code to display the relationship you describe.

@adjan
Thank you. I am new to this site. this was a very cool answer! Do I give gold to the best reply how does this work? (:
I am not very good with math, how do I, if possible, convert the value to a   g/mm3 or a cublic number?

@AndreasJørgensen If you find an answer helpful, upvote using the arrow up button. Additionally, you can mark an answer as accepted by clicking on the checkmark icon. The function gives density in $\frac {mg}{mm^3}$, so just multiply with $10^3$ to get $\frac g {mm^3}$.

*Divide by $10^3$.

$$\log_{10} V= 1.019\log_{10} m+1.46 \rightarrow \log v-\log 28.8403= \log m^{1.019}\rightarrow \log V/28.8403 = \log m^{1.019} \rightarrow V = 28.8403 m^{1.019}.$$ Where does 2.34633 come from?

@daniel from mistakenly assuming my calculator's $\log$ was $\log_{10}$, not $\ln$.

Can anyone clarify why it says: "volume (mm^2)" on the y-axis and not "volume (mm^3)" ?

@AndreasJørgensen i guess it's a typo. there are four charts on that page of this paper, two of them are about area ($mm^2$)

@AlexDeLarge If you had read the edit comment you'd have known that this is a current SE bug and it makes no sense to change all HTML sup's on SE because it just got broken today. I used it in many of my previous answers and the bug only occured today. Wait till the SE team has fixed it!

Uups, must have overlooked that, my bad. I was not aware of that! Sorry. :) I'll delete my comment.

It seems that the maths does not match the plot: The $\log$ should be the $\ln$ (natural log, basis e), then the derived formulas indeed describe the data from the plot. Otherwise the formula yields a volume which is approximately a factor 6.7 too high.

@DominikS I think now it should be correct

I did the following estimate, based on the honey bee, to get an idea of the order of magnitude of the density of insects: According to Wikipedia (sorry for the german), we have:

The average mass of a honeybee is about 80 mg.
The length is 12 mm in average.

In order to estimate the volume, I model the body in three parts (see Wikipedia again):

The head as a sphere with a diameter of roughly 2.5 mm
The torso as a sphere with a diameter of roughy 4 mm
The abdomen as a cylinder of length 6 mm, and a diameter of 4 mm.

This will yield a very rough estimate of the volume, but we can expect it to have the correct order of magnitude. It is:
$$ V \approx \pi \cdot\Big (\frac 43\cdot \Big(\frac {2.5}2\Big)^3 +\frac 43\cdot \Big(\frac {4}2\Big)^3  +\Big(\frac 42\Big)^2\cdot 6\Big)\approx 117\text{ mm}^3 $$.
We have not accounted for antennae, legs, ..., so given the uncertainties of my estimates, the volume of a honeybee should be in the range of 100-200 mm^3. This is also in accordance with the graph in @adjan's answer.
With this the density of a honeybee should be between 80/200 and 80/100 mg/mm^3, so $$0.4\,\frac{\text{mg}}{\text{mm}^3} < \rho <0.8\,\frac{\text{mg}}{\text{mm}^3}$$,
which is interestingly slightly less than the density of water.

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What kind of fish is this (Florida, USA)?
What kind of fish is this? It was caught in Florida (USA) in a canal and was in a group. It was about 5 or 6 inches in size.

What is its size?

5 or 6 inches or so I believe

It looks like an immature bass of some kind. The Shad mentioned below usually have a pigment mark behind the gills and don't have the second set of dorsal spines behind the major. Then again, the split in the tail is not usually that pronounced in bass :(

So after much more time on this than I should have, I am pretty confident this is a silver jenny (Mojarra).
Silver Jenny, Eucinostomus gula

"The Silver Jenny, Eucinostomus gula, whose common Spanish name is
  mojarra Española, is a species in the Mojarra or Gerreidae Family,
  known collectively as mojarras in Mexico. Globally, there are eleven
  species in the genus Eucinostomus, all of which are found in Mexican
  waters, seven in the Atlantic and four in the Pacific."

Dorsal fin structure, tail fin split, location of ventral fins and gill fins all match up, as does color.  So does the faint stripe from top of gill to back of fish. The last clue was the protrusible mouth.
I'm surprised you found it in a canal, as it is a saltwater fish. Were you close to the ocean?  From the link above:

The Silver Jenny are an abundant schooling species that are found
  seasonally in shallow coastal waters over mud bottoms in mangrove
  lined lagoons and creeks in waters that are between 11oC (52oF) and
  28oC (82oF) at depths up to 175 feet. Juveniles are found in seagrass
  beds. They may also enter freshwater. They are known to make seasonal
  migrations to off-shore warmer waters during the cooler months for
  wintering and hibernation returning to coastal waters in the spring
  for breeding. They reach a maximum length of 23 cm (9.1 inches). They
  are benthic feeders that probe the bottom with their protrusible mouth
  consuming bivalves, crustaceans, ostracods and detritus. They are a
  poorly studied species and very limited information is available about
  their behavioral patterns.

Last Link here


text:
What are homologous chromosomes?
I've read that homologous chromosomes are composed of one maternal chromosome and one paternal chromosome.

I want to confirm if this image is for one set of homologous chromosomes:

They have the same size, length, loci and same genes but are not identical.
They have different DNA sequences, so contain different alleles.

Still, I'm confused if it should be one maternal chromatid and one paternal chromatid.

I thought, homologous chromosomes are supposed to be one maternal and one paternal chromosome?

Can someone kindly explain if chromosomes are duplicated as to one paternal and one maternal chromosome or not??

Now is this image a homologous chromosome duplicated? So there are two sets of homologous chromosomes?

A similar question from January.

Wow thank you for the simple way of explaining it.
I got it clearer now.

Part of the problem is that chromosome is a slippery word. Really it should refer to a single DNA molecule, but since chromosomes came before DNA this sometimes gets a little loose.
This explanation refers to the five Figures in your question as 1-5 from the top.
Figure 1 A pair of homologous chromosomes from a diploid cell  drawn to illustrate their relationship in terms of genes, alleles, centromeres etc. This doesn't really correspond to any biological event. Colour coding is to emphasise that they originated from different parents. I suppose this is what you see in a karyotype.
Figure  2 An homologous pair again, different colours again, but they aren't closely side by side. When each one replicates we end up with pairs of sister chromatids joined at the centromere. These are four homologous chromosomes. At mitosis each of the pairs of sister chromatids will be pulled apart with one chromosome going to each daughter cell. So the daughter cell will end up with a pair of homologous chromosomes, one maternal, one paternal.
Figure 3 is very similar to Figure 2, nothing to add really.
Figure 4 is similar to the right hand half of Figure 2 except that the chromatids are shown not joined at the centromeres. This image is being used to show that recombination can take place between chromatids. This would be during meiosis, but the pairs of sisters would actually  be joined at the centromeres
Figure 5 Up to now the images have been designed to illustrate one chromosome either individually, as an homologous pair or as a pair of sister chromatids. But of course most organisms have more than one chromosome. Leaving aside the X and Y chromosomes your cells have 22 pairs of homologous chromosomes or 44 individual chromosomes. When these replicate the cell  will have 88 chromatids, forming 44 pairs of sisters, corresponding to  22 homologous sets of four.

Nice to see you around here again!

Thanks!  I was getting obsessed so needed time in rehab.

Ha! I think I could use that too.


text:
where does genetic material for antibody production come from?
All antibodies are proteins and like every other protein, mRNA codes for them. So acquired immunity, is acquired, which means that information was not previously present in our DNA before exposure to the pathogens.
So my question is, does our DNA in some way get modified or something else? Where does the new genetic material come from?

Does our DNA in some way get modified or something else?

Yes. The DNA gets modified. VDJ recombination and somatic hypermutation are the mechanisms by which this happens.
You can find an entire book chapter/review on these topics. So I shall not elaborate further.

thank you ... i don't mean to delve further into this I just wanted to know the broad concept . thanks a lot


text:
Algae and greenhouse effect
Just a thought: the CO2 concentration is increasing . Due to a different but possible related phenomenon, the algal blooms are on the rise. We humans want to control both. But algae are the major source of O2. Could the rise of algal blooms in the rising concentration of be related CO2 ? I wanted to know if this would eventually be advantageous to the environment, even though algal blooms may be detrimental to some species and directly or indirectly to humans too?

It also may be related to how many trees we cut down too... Just a thought, I have no evidence.

"Rising CO2 levels will intensify algal blooms across the globe" (from http://phys.org), based on this paper in PLOS one.

In most situations the lack of sufficient CO2 is not what is limiting algal growth. In general the limits to growth are set by the availability of nutrients such as iron, nitrogen and silica. They actually touch on that in the paper. For example removing iron limitation has a much more dramatic impact on algal growth or blooms than increasing CO2 by a few percentage points (see here). This also explains why there are more algal blooms, the increase of fertilizer use results in more food for the algae to grow on and all round bad things (see here).
Perhaps some algae will benefit since they will not have to invest much energy/nitrogen in creating carbon concentrating mechanisms. However several species of algae use calcium for their cell walls and these would actually suffer by increased CO2 concentrations as this leads to ocean acidification (e.g. coccolithophores). Taking into account that these are heavy sinking algae that take a lot of carbon with them to the ocean floor and you see that ocean acidification is not likely to be a good thing.


text:
Are there constraints on where intron/exon boundaries occur with respect to the triplet codons of the reading frame?
I did a quick search (here and elsewhere) and couldn't find anything on this subject.
If all introns in a given primary transcript were spliced out in the same way, then this wouldn't matter.  But lots of eukaryotic transcripts have alternate splicing patterns so that one version of the mRNA will contain coding regions that are absent in other alternate forms.
The problem relates to maintaining an open reading frame, avoiding a frame shift and the attendant (and unpredictable) consequences. If a splice donor site occurs within the 3-base codon, it might require that the two (or more) alternate acceptor sites would be in the same relative position in a related codon.
The simplest solution to this problem in my view is to make sure that all splice donor and acceptor sites would be at a codon/word boundary.
Is there any evidence that this is true?

As pointed out by others this is not true. I just verified this for humans (annotations from gencode21).
Methodology:

Obtained the start points of the CDS for all genes
For each exon of each gene, calculated the distance between the CDS start and exon end
Obtained the remainder after dividing this value  by 3 (modulo)

Commands:

Command-1:
    awk 'BEGIN{FS="\t|;";OFS="\t"} $3=="CDS"{print $4,$9}' gencode.v21.annotation.gtf > cdsstart.txt

Command-2:
    awk 'BEGIN{FS="\t|;";OFS="\t"} NR==FNR{a[$2]=$1;next} ($3=="exon" && $9 in a){if($4>a[$9]) q[($5-a[$9])%3]++} END{for(i in q) print i,q[i]}' cdsstart.txt gencode.v21.annotation.gtf

Result:

position | # cases
_______________________
   -2    | 101191
   -1    | 100954
    0    | 99499

As you can see the exons do not necessarily terminate at the third position of the codon.

Here is exon size data of some random gene (human ROR-gamma).
Link: http://www.ncbi.nlm.nih.gov/nuccore/NM_005060.3
It gets cut at all three possible positions of codon:
exon 2  30
exon 3  86
exon 4  142
exon 5  513
exon 6  122
exon 7  133
exon 8  108
exon 9  111
exon 10 110
Alernatively spliced isoform B of this gene gets different first exon. At the junction codon ACA (isoform A) gets replaced with codon TCA (isoform B).

I don't have time to find examples right now but no, it's not true. You often get cases like this (lower case letters represent the intron):
ACCTGTaccttgcaacttgcatAGCTGAC

Which would be spliced to:
ACCTCTGAC

Note that the second codon consists of one nucleotide from exon1 and two from exon2. I'll try and update this with real world examples, but I can assure you it is possible and I have seen it quite often.

As Alex M shows, many lengths of exons are 3n+1 or +2. It seems cells do not care about in-frame.
In some cases, exon insertion by alternative splicing shift the frame and produce a short version of gene product or introduce premature stop codon (PTC). When PCT is recognized in cells, the spliced transcript is quickly degraded. This is called nonsense mediated decay (NMD).
Splicing machinery does not care about frame of CDS, and this makes various gene regulations possible.
http://genesdev.cshlp.org/content/24/21/2343.full
This review shows an example of NMD by alternative splicing. See the description about caspase-2.


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What is the sequence of pPROLar.A plasmid?
I've been looking for the sequence of pPROLar.A122 plasmid but I haven't found it. Where could I find the sequence?
The first link (addgene) on googling reports a plasmid which is reported to have the pPROLar.A backbone. However, this is a modified version with Ampicillin and LuxR. I'm trying to reconstruct it from it and another plasmid.
The plasmid map looks like this:

Thanks!

This is not. pPROLar.A122 plasmid looks like this: http://apps2.bvl.bund.de/vectorwww/image.do?id=427 and this is a modified version with Ampicillin and LuxR. But I'm trying to reconstruct it from it and another plasmid.

The problem is the reliability of reconstructed sequences. If a problem arrives with the cloning maybe was because of that. I've already searched the whole Google, that's the reason because I asked here.

I am afraid the sequence is not available anywhere. You should write to Clontech to ask for it. If you do get a reply then please post it here. It will be useful for others.

The pPROLar.A112 sequence is:

CCATGGGTGA ACAGAAACTG ATCAGCGAAG AGGATCTGGG TGGAGATGAC GATGACAAGG
  TGGTCGACAA GCTTGGATCC CTGCAGGCCT CAGGGCCCGA TCGATGCGGC CGCTTAATTA
  ATTAATCTAG AGGCATCAAA TAAAACGAAA GGCTCAGTCG AAAGACTGGG CCTTTCGTTT
  TATCTGTTGT TTGTCGGTGA ACGCTCTCCT GAGTAGGACA AATCCGCCGC CCTAGACCTA
  GGGGATATAT TCCGCTTCCT CGCTCACTGA CTCGCTACGC TCGGTCGTTC GACTGCGGCG
  AGCGGAAATG GCTTACGAAC GGGGCGGAGA TTTCCTGGAA GATGCCAGGA AGATACTTAA
  CAGGGAAGTG AGAGGGCCGC GGCAAAGCCG TTTTTCCATA GGCTCCGCCC CCCTGACAAG
  CATCACGAAA TCTGACGCTC AAATCAGTGG TGGCGAAACC CGACAGGACT ATAAAGATAC
  CAGGCGTTTC CCCCTGGCGG CTCCCTCGTG CGCTCTCCTG TTCCTGCCTT TCGGTTTACC
  GGTGTCATTC CGCTGTTATG GCCGCGTTTG TCTCATTCCA CGCCTGACAC TCAGTTCCGG
  GTAGGCAGTT CGCTCCAAGC TGGACTGTAT GCACGAACCC CCCGTTCAGT CCGACCGCTG
  CGCCTTATCC GGTAACTATC GTCTTGAGTC CAACCCGGAA AGACATGCAA AAGCACCACT
  GGCAGCAGCC ACTGGTAATT GATTTAGAGG AGTTAGTCTT GAAGTCATGC GCCGGTTAAG
  GCTAAACTGA AAGGACAAGT TTTGGTGACT GCGCTCCTCC AAGCCAGTTA CCTCGGTTCA
  AAGAGTTGGT AGCTCAGAGA ACCTTCGAAA AACCGCCCTG CAAGGCGGTT TTTTCGTTTT
  CAGAGCAAGA GATTACGCGC AGACCAAAAC GATCTCAAGA AGATCATCTT ATTAATCAGA
  TAAAATATTA CTAGATTTCA GTGCAATTTA TCTCTTCAAA TGTAGCACCT GAAGTCAGCC
  CCATACGATA TAAGTTGTTA CTAGTGCTTG GATTCTCACC AATAAAAAAC GCCCGGCGGC
  AACCGAGCGT TCTGAACAAA TCCAGATGGA GTTCTGAGGT CATTACTGGA TCTATCAACA
  GGAGTCCAAG CGAGCTCTCG AACCCCAGAG TCCCGCTCAG AAGAACTCGT CAAGAAGGCG
  ATAGAAGGCG ATGCGCTGCG AATCGGGAGC GGCGATACCG TAAAGCACGA GGAAGCGGTC
  AGCCCATTCG CCGCCAAGCT CTTCAGCAAT ATCACGGGTA GCCAACGCTA TGTCCTGATA
  GCGGTCCGCC ACACCCAGCC GGCCACAGTC GATGAATCCA GAAAAGCGGC CATTTTCCAC
  CATGATATTC GGCAAGCAGG CATCGCCATG GGTCACGACG AGATCCTCGC CGTCGGGCAT
  GCGCGCCTTG AGCCTGGCGA ACAGTTCGGC TGGCGCGAGC CCCTGATGCT CTTCGTCCAG
  ATCATCCTGA TCGACAAGAC CGGCTTCCAT CCGAGTACGT GCTCGCTCGA TGCGATGTTT
  CGCTTGGTGG TCGAATGGGC AGGTAGCCGG ATCAAGCGTA TGCAGCCGCC GCATTGCATC
  AGCCATGATG GATACTTTCT CGGCAGGAGC AAGGTGAGAT GACAGGAGAT CCTGCCCCGG
  CACTTCGCCC AATAGCAGCC AGTCCCTTCC CGCTTCAGTG ACAACGTCGA GCACAGCTGC
  GCAAGGAACG CCCGTCGTGG CCAGCCACGA TAGCCGCGCT GCCTCGTCCT GCAGTTCATT
  CAGGGCACCG GACAGGTCGG TCTTGACAAA AAGAACCGGG CGCCCCTGCG CTGACAGCCG
  GAACACGGCG GCATCAGAGC AGCCGATTGT CTGTTGTGCC CAGTCATAGC CGAATAGCCT
  CTCCACCCAA GCGGCCGGAG AACCTGCGTG CAATCCATCT TGTTCAATCA TGCGAAACGA
  TCCTCATCCT GTCTCTTGAT CAGATCTTGA TCCCCTGCGC CATCAGATCC TTGGCGGCAA
  GAAAGCCATC CAGTTTACTT TGCAGGGCTT CCCAACCTTA CCAGAGGGCG CCCCAGCTGG
  CAATTCCGAC GTCTGTGTGG AATTGTGAGC GGATAACAAT TTCACACAGG GCCCTCGGAC
  ACCGAGGAGA ATGTCAAGAG GCGAACACAC AACGTCTTGG AGCGCCAGAG GAGGAACGAG
  CTAAAACGGA GCTTTTTTGC CCTGCGTGAC CAGATCCCGG AGTTGGAAAA CAATGAAAAG
  GCCCCCAAGG TAGTTATCCT TAAAAAAGCC ACAGCATACA TCCTGTCCGT CCAAGCAGAG
  GAGCAAAAGC TCATTTCTGA AGAGGACTTG TTGCGGAAAC GACGAGAACA GTTGAAACAC
  AAACTTGAAC AGCTACGGAA CTCTTGTGCG TAAGGAAAAG TAAGGAAAAC GATTCCTTCT
  AACAGAAATG TCCTGAGCAA TCACCTATGA ACTGTCGACT CGAGCATAGC ATTTTTATCC
  ATAAGATTAG CGGATCTAAC CTTTACAATT GTGAGCGCTC ACAATTATGA TAGATTCAAT
  TGTGAGCGGA TAACAATTTC ACACAGAATT CATTAAAGAG GAGAAAGGTA C

It was sent to me directly from Takara Bio.


text:
Trypsin and cell culture
I am doing an experiment where I have treat the cells with a drug and calculate their counts. I would like to know if is bad to trypsinize the cells in consecutive days i.e. twice within 48 hours. How much time do the cells need to attach again on the surface of the flask? I want to know if I can treat them with drug the same day I add trypsin for counting.
Thanks.

Your question was unclear and I edited it a bit. See if this is what you really wanted to ask.

Can you specify the cell strain? It really depends on it. I have done for example trypsinization on RPE1 cells (human fibroblasts) twice in 48h without troubles.

It would be stressful for cells to be trypsinized 24 hours after seeding. After cells are plated, there is a lag time to start growing. Perhaps, during the lag time, physiological state of cells is stabilized. They have to express proteins digested by trypsin and display on the surface etc. Then you could disturb the state again by trypsinizing cells again if you replate cells after 24 hours.
I would not deny some cells are not affected by trypsin much, but you should be carful.

if I can treat them with drug the same day I add trypsin for counting.

It is not preferable, but in some cases, such a way is taken actually. If you could, you might want to give us more information about which cells and drugs you are going to use.
PS
If you trypsinize cells to count and do not replate them, you do not need to worry about the cell condition, as WYSIWYG says.

It is not advisable to trypsinize the cells too often when you have to maintain them. However, in your case the situation is different.
Time required to attach depends on cell type. In any case while performing an experiment, your cells should not be already under stress. Therefore you should seed the flasks/culture plates with a smaller concentration of cells such that they reach around 60% confluence in 24 hours. 24 hours is generally considered to be enough for cells to recover from stress due to trypsinization. (You can have a look at this post for doubling times of some cell lines).
After doing the treatment you can count cells whenever you think it is fine; this actually depends on your experiment and you can treat the cells for the time that suits the drug's pharmacokinetcs. Trypsinizing is fine now because you won't be using these cells again.
However, there are methods to calculate cell numbers without trypsinizing. Assuming that your flask is homogeneous, you can choose a section of it and calculate cell numbers manually using microscope. You may also use software like ImageJ to make the task easier. GFP expressing cells will also make the task easier.

Might be considered "not answering the question" but:
Option 1:
Depending on the type of cells you are using, you can use milder methods to detach cells.  Example include Versene which is essentially PBS + EDTA.  Milder still is to just use PBS that has no Mg or Ca (no chelation).
Option 2:
Duplicate your setup - instead of two dishes - one with drug, one without, you make 4 dishes (dispensed from a common source - i.e. if your dish is a 6cm dish with 3ml media, you make 4.5x3mls of cells at the final dilution you want) each plate gets 3mls from the same source so you know they have the same number of cells.  Two dishes you add drugs, two you don't.  On the day you want to count, you take the replicate plates and count them.  This way, you get the count without touching the final dishes at all.
As a side experiment, if you put those trypsinized cells back on two dish (and replace the drug media in the drug treated replicate), and you count all plates on the last day of your experiment, provided cells are not at 100% confluency, any difference you see from your trypsinized vs untrypsinized can be viewed as potential error that you would have introduced if you went through your original methodology.


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How to find suitable qRTPCR reference gene for a inflammatory response experiment?
I have tried several housekeeping genes – Hprt, β-actin and GAPDH, to analyze the relative expression of a cytokine for measuring the inflammatory local response in mice ears. However, all these housekeeping genes show significant variation in both within and between different experimental conditions.
I really don't know how to solve this. I take the same amount of RNA (quantified by  nanodrop) to make cDNA so I guess I have the same concentration in all the samples.
Any suggestion of what can happens and how to solve it? Could I use something different to measure the relative quantification? (My cytokine of interest is TNF).

When you say, "[they differ] from each other significantly", do you mean between replicates under the same experimental conditions or between conditions? It wouldn't be useful to normalize to a housekeeping gene expression level if it doesn't change between conditions.

They differ between diferent conditions and also under the same experimental conditions. I have checked the DNA concentration of the samples and they are the same.

You don't say how you're measuring but I'll guess that you're using quantitative PCR. A typical approach to handling housekeeping gene normalization in qPCR experiments is described in
Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.

We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data.

There is an R package called NormqPCR that implements this approach (publication here).
Briefly, the approach required measuring multiple housekeeping genes and iteratively removing the ones that are most variable, ending up with two genes that are jointly least variable, and making a sort of pseudo-housekeeping gene from them with which to normalize your other genes.
This doesn't magically turn bad data into good data, but it helps clean up some intrinsic problems with housekeeping genes.

House keeping genes are not necessarily constant.
Another way to measure gene expression change is RNA-seq. It normalizes counts against the whole transcriptome instead of against certain housekeeping genes.

Finding a suitable reference gene is tricky. It depends on your prior knowledge about the system. You may start with the same amount of RNA but errors can accumulate many other steps. That is why you use a reference gene to minimize the effect of those errors accumulated during sample processing. So unless you are very precise, you cannot say that everything was constant and the expression is the source of variation. Once you test a putative reference gene thoroughly you can "believe" that it would not change when you repeat the experiment.
Having said that, I would insist that a much better (and quite easy) method is to use a "spike in". It is a synthetic nucleic acid that you add to your samples. Similar concept can be used for proteins and metabolites too. You can spike in the same amounts of  the synthetic RNA in your different RNA samples. If you keep the volume constant then the concentration of the spike-in would be the same in different samples. So, instead of a housekeeping gene you would now use the spike-in as a reference. Spike-ins have been found reliable for even single cell RNAseq studies (Lun et al., 2017).

If there was no established robust protocol, you could follow Eissa et al. 2017, Scientific Reports. They faced the same problem in another inflammatory model system in mice, and outline a strategy on how to find robust housekeeping genes (and then wrote a publication about this).

Can you include a brief description of the strategy?

I believe to possibly do more harm if compressing the full paper into a paragraph.

It's hard to tell if OP is running an array or qPCR with carefully selected targets. If it were an array I'd suggest the OP take the genes across all samples, calculate %CV and use the lowest CV genes as normalization genes. He'd just have to cut them from the analysis. It's harder to determine what you should use one at a time. Perhaps some RNAseq, microarray or Nanostring data exist in his model, somewhere, he can use to do this.

Why downvote? The above answer is correct. The publication describes a general protocol to deal with the question of OP.

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


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Does testosterone weaken the immune system?
I was reading this articles here that states that the higher the blood level of testosterone is, the weaker the immune system gets.
I read another article about testosterone here that focuses on the positive side of high testosterone blood levels and avoids the effects on the immune system.
So my questions is: Does testosterone really weaken the immune system?

this may help http://www.sciencedirect.com/science/article/pii/S0008874915000313?via%3Dihub


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Pregnancy from two parents with incompatible blood types, can it lead to complications?
Let's take Alice and Bob, both healthy adult human specimens. Alice is (A-). Bob is (B+).
If they decide to have a child, would Alice's pregnancy involve any additional risk or complications compared with, say, Abraham and Abigail's pregnancy (both AB+)?
Background
I overheard claims that pregnancies from parents with different blood groups can lead to complications in pregnancy due to interactions between the mother and the child's blood. (These claims were not officially backed, otherwise I would have brought them up on Skeptics.SE). The explanations and my Google browsing went beyond my biology knowledge. I know these pregnancies must be viable, since the AB group exists, but I do not know if there are edge cases that lead to complications that would not happen with same blood type parents.
Related question
Can the mating of a couple with Rhesus positive and negative blood types result in miscarriage? This question only asks about Rh+ and only if it leads to miscarriage.

Thanks, @AlexDeLarge. I overheard claims that pregnancies from mixed parents can lead to complications in pregnancy due to interactions between the mother and the childs blood. (This claims were not oficially backed, or I would have taken it to Skeptics.SE) The explanations and my Google browsing went beyond my biology knowledge. I know these pregnancies must be viable, since the AB group exists, but I don't know if there can really be some significant (>0.1% maybe?) edge cases that lead to complications that wouldn't happen with same blood type parents.

The rhesus factor (the + / - part of the blood group) can cause complications with pregnancy under certain conditions and lead to the so called Rh disease:
If the mother is rhesus negative and the father, rhesus positive; then the birth of a child with Rh+ blood group (inherited from the father) can cause the mother to build antibodies against this blood group. Therefore, a second pregnancy with a child that also has Rh+ blood group can have complications if no precautions are taken at any other point.
If these specific conditions are not all met, then no complications should arise from the blood groups.

The only complications that will occur will be in the birth of the second child, and that too if the second child is conceived soon after the birth of the first.
Let me explain.
Rh factor is an antigenic protein found on the surface of the RBCs of some individuals( rather, 'most individuals').

If the factor is present, the blood group is written with a positive(+) sign, and if it is absent, the negative sign(-) is used with the blood group. Therefore, in your example, Bob, Abraham and Abigail have the said factor on their RBCs whereas Alice does not.
As a matter of fact, our body has a mechanism because of which it produces antibodies against foreign antigens. Antibodies are simply substances released by our specialized cells to counter toxins and foreign antigens. These antibodies bind with the specific antigens (against which they are released) to render them harmless.

The fact is that these antibodies, once produced in our bodies, remain in the bloodstream for a certain interval of time, and there presence protects us from future infections by those antigens(This is the principle exploited in vaccination).
Let us relate this knowledge of antibodies and antigens to the Rh factor. Let's say that we make a blood transfusion from an Rh positive person(like Bob) to an Rh negative person( like Alice). Since for Alice, the Rh antigen is a foreign antigen(because it is naturally absent from her blood), she will get sensitized and develop antibodies against it. However, these antibodies will not attack the antigens immediately. They will come into action only if the antigens are again brought into the bloodstream, i.e. another transfusion is made sometime later. These antibodies will then  bind to the RBCs carrying it, and result in agglutination, or clumping of RBCs. The clump of RBCs thus formed blocks the passage of blood to the heart, resulting in death.

So, if Alice and Bob conceive a child together for the first time, the fetus will be Rh positive(because if the factor is present in any one parent, it will also be found in the child), and it will sensitize the blood of the mother. At this point, if you know some basics of biology, you will think that since the blood of the mother and the fetus never comes in contact, the fetal blood should not be able to sensitize the mother's blood. If you think so, you are absolutely right! The placenta does not allow their blood to mix. However during the parturition, rupturing of placenta often occurs, causing just a small amount of the fetal blood to mix with that of the mother. Even this small amount is enough for the mother to be sensitized and develop antibodies against Rh factor.
Now, if the second child(who will also,obviously, be Rh positive) is conceived soon, there will be a problem. The placenta is permeable to antibodies, and as a result, the anibodies developed earlier will enter the fetus and cause agglutination in the fetal blood, leading to excessive anaemia or even death. This is called erythroblastosis fetalis, or hemolytic disease of the newborn(HDN)
Thus, you can see that Alice and Bob will have a problem with their 2nd child, whereas Abigail and Abraham will not, since they are both Rh positive and Abigail won't be sensitized.
FACT The Rh factor was first found, and named after, the common Rhesus monkey!!


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Are males taller than females in humans?
Is there any scientific evidence that in humans males are taller than females? And if so, what is the reason that they are taller (please include genes or hormones that accounts for human growth and how they are affected in males and females)?

I assume that you are talking about humans only, and would suggest to edit the question accordingly - I do not think this is entirely clear from the wording of the actual question. This is relevant, as in many other species, females are taller/bigger than males.

@Gerhard the question was migrated from the health website. My questions is comparing human males and females.

Ah, that explains it ;) But I'd suggest to edit the question anyways, eg. by using "women" and "men" instead.

Are males taller than females?
Best data I could find come from the Statistical Abstract of the United States (1999) > Section 3. Here is a table reporting the percentage of the male and female population which height is lower than a given threshold

Note that this data collection was done among students in US universities and is therefore not representative of the whole world or even the whole country.
Does height follow a bimodal distribution?
A difference in height between males and females is often used as a classical example in introductory statistic class to exemplify a bimodal distribution as seen in this picture

and on these (a priori fake) data

However, Schilling et al. 2002 argued that while the difference in mean height between the sexes is real, this difference is too small relative to the variance in height within each sex to be clearly depicted on a graph.
Note that I found this non-peer-reviewed paper which shows real data that display a truly bimodal distribution of height.

Genetics of height
The question why are they taller? is very broad. I will just focus to give you some hints about the genetics of height in humans. First, you want to make sure you understand the concept of heritability.
Evoy and Vissher 2009 report a heritability coefficient of 0.8. This estimate is impressively high - only a few phenotypic traits have such high heritability. They also review articles discussing that 50 loci are correlated with variation in height (actually, today, more than 500 loci are known to contribute to height, see the link in AlexDeLarge's comment to this answer). However, these loci are not sufficient to explain the whole heritability observed (common missing heritability issue). Yang et al. 2010 provide evidence that the remaining heritability is due to incomplete linkage
disequilibrium between causal variants and loci of weak effects. In short, height is a highly polygenic trait.
Related post
You should have a look at Is there a genetic reason explaining the difference of the height of male and female? for more information.

+1 for the answer to the first part of the question, but the second needs work; differences in height due to sex are probably primarily due to development rather than genetics (males and females are fairly well-mixed populations...). This paper describes one developmental mechanism (sex-based differences in GH-dependent STAT5b regulation of IGF-I expression): http://www.ncbi.nlm.nih.gov/pubmed/15506072. It also discusses selective pressures for sexual dimorphism in humans versus other species, which could be another part of the answer to the "reasons" part of the question.

@shnisaka: You might also want to take a look at my answer to this question about the genetic basis for height difference in human males and females.

@AlexDeLarge Thanks for the link. I added it to the answer.


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Design arbitrary degenerate primers (with non-binding criteria)
I would like to design a number of arbitrary degenerate primers (primers with variable bases, e.g. NGATWGCTSATNGC) for a TAIL-PCR.
I would like to be able to specify the following parameters for the design function:

Annealing temperature (ideally 44°C)
Degeneracy (how many variations of the AD primer there are (ideally 128 or 256)
Binding frequency on (mouse) genome (ideally 1/3000) - though this may be contingent on the degeneracy, and vice-versa.
Non-binding area (of course I would not like any variation of the primer to bind to the known-sequence area in between my specific primers and the unknown area which I want to sequence)

Any ideas of any tools that can help me with the above steps? For Primer design I have used eprimer3 thus far (with invariably satisfactory results) - but it seems to not support the concept of arbitrary degenerate primers.
Ideally, if I had a function which could sort out the first of the above criteria, I could use Biopython and BLAST to script the rest myself. Though the binding frequency would take hours if not a day or two, for BLAST to determine it. It would greatly help if anybody already wrote something more elaborate for this.

Do you know the sequence that you want? I mean, the degenerate places marked as N but the rest present. I don't know of a program that does it. But I can suggest you a workflow that would use simple scripts and existing bioinformatics tools.

go, ahead, suggest! As for the question, no, the sequence itself is completely irrelevant to me. what I care about are the criteria mentioned above. Any sequence that fulfills them would suit my purposes.

Regarding the 4th point: I am assuming that the exact primer is of same length as the degenerate ones. Do you want primers with variable lengths? That will be more complicated.

By the "exact" primer you mean the specific primer(s) for the TAILPCR? if so, no, they are ~20bp, the AD primers should be around ~14bp (though I guess that can be varied a bit to account for binding frequency and annealing temperature).

If you already know the basic sequence i.e. the fixed regions in the primer; for e.g. the known nucleotides in the sequence -  NGATWGCTSATNGC, then you can implement your algorithm like this:

Fix the max length of the primers. Lets say 20nt.
Generate all combinations of primers (20nt): that is pretty straightforward. You will have  4N × 2(R+Y+S+W+K+M) × 3(B+D+V+H) number of combinations, where each alphabet denotes number of such instances. Chek this site for the nucleotide codes.
Calculate the Tm of the primer-template pairs. UNAfold has a nucleotide hybridization Tm calculator. You can specify parameters like salt concentration etc. There are other such tools too. These can be run on the commandline.
Discard all primers have Tm below the acceptable limit.
For those that exceed the acceptable Tm, keep dropping a base from the 3' until the Tm reaches within the range.
If primer length goes below 14nt then discard the primer.
Now with all these selected primers check for parameters like self hybridization, GC clamp etc (OPTIONAL). You can use primer3 for these purposes by running it on the primer_check mode.
Download the nr/nt BLAST database.
Adjust BLAST parameters for short nucleotide search: Decrease the word length, increase e-value cutoff etc (See this biostar post and BLAST help).
BLAST your primers against the database in plus-minus mode.
Worry only about cases where there is significant alignment at the 3' of the primer as only these can cause extension.

These instructions can be automated using any language or shell script.

Questions on script writing would be off-topic in this site. You can ask specific doubts about coding in stackoverflow.


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What causes anorexia nervorsa?
I've heard of anorexia nervosa being a severe loss of appetite. I'm wondering what causes such disease in humans?

People with anorexia usually tend to have high levels of cortisol, the brain hormone most related to stress, and decreased levels of serotonin and norepinephrine, which are associated with feelings of well-being. But you may want to ask this question on the Cognitive Sciences Stack exchange

Definitely a good target for CogSci, but dependent on the answer also here. If @gone.'s comment holds, it's definitely ontopic here too. One way or another, nice question +1

"Is there a physiological underpinning for anorexia?" would be on topic here. "Why do people become anorexic?" might be more cogsci. It's semantics though and I like the question. +1

What is anorexia nervosa?
Generally, it is an eating disorder which is characterised by a tremendous fear of food as well as an extreme weight loss.
Patients with anorexia nervosa do not necessarily lose their appetite but rather obsessively control and restrict their food intake.

Anorexia Nervosa as an inherited disease/genetic factors
There has been a lot of research proposing that eating disorders are often biologically inherited and tend to run in families.

Recent research suggests that inherited biological and genetic factors contribute approximately 56% of the risk for developing an eating disorder. Individuals who have a mother or a sister with anorexia nervosa are approximately twelve times more likely to develop anorexia and four times more likely to develop bulimia than other individuals without a family history of these disorders. Studies of twins have shown a higher rate of eating disorders when they are identical (compared to fraternal twins or other siblings).

The hormone serotonin
There has been found that anorexics have an overproduction of serotonin, which can cause a continual state of acute stress and anxiety.

Researchers are still puzzled as to why, if anorexics already have high levels of serotonin, then SSRIs (medications like Prozac which raise serotonin levels) are successful treatments for some individuals. These scientists speculate that that there may be different subtypes of this disease, and that different groups of anorexics may have different neurochemical characteristics.
Researchers have also noted that abnormal eating behaviours and the resulting changes in the body can actually cause a disruption in serotonin levels, thus contributing to an already existing problem. Abnormalities in serotonin levels can lead to depression and anxiety. Studies also suggest that there are genetic predispositions to serotonin disruptions that appear to run in some families.

The hormone dopamine

Research suggests that women who develop anorexia nervosa may have altered levels of dopamine in their brains. Dopamine disturbances can cause hyperactivity, repetition of behaviour (such as food restriction), and anhedonia (a decreased sense of pleasure). This neurotransmitter also affects reward-motivated behaviour.

The hormone cortisol/hydrocortisone

Numerous other hormones in the brain have also been linked to eating disorders. Stress triggers the production and release of a hormone called cortisol; chronically elevated cortisol levels have been observed in patients with anorexia. Cortisol can inhibit appetite.

The hormone leptin

Leptin is a protein hormone produced by the body's adipose tissue. Leptin is regarded as a hormone which can regulate fact storage and appetite. If individuals with anorexia nervosa lose extreme amounts of body fat, their levels of leptin drop which is known as hypoleptinaemia. The side effects of hypoleptinaemia can include amenorrhea, impaired metabolism, and bone loss.

Also, if people receive treatment, their leptin levels do not immediately return to normal. Initially during the treatment, leptin levels rise through the sky, which is also the reason why most patients are most susceptible of relapsing back into an eating order, since very high levels of leptin may cause a weight gain.

Sources:

ENGEL, BRIDGET, NATALIE STAATS REISS, and MARK DOMBECK. "Causes Of Eating Disorders - Biological Factors Continued." Mental Help Causes of Eating Disorders Biological Factors Continued Comments. 2 Feb. 2007
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3010958/
http://www.apa.org/monitor/mar02/genetic.aspx


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Sodium hydroxide grade in library denaturation for NGS
If the NaOH, 1N which I bought does not have the label of molecular biology grade can it be used safely for library denaturation in NGS? Thank you!

The "molecular biology grade" is just a gimmick in many situations. The reagent grade NaOH is quite pure (≥98%). The usual impurities (major being Na2CO3; ~1%) are also chemically insignificant (See the Sigma-Aldrich products 1 and 2). For the product that you have, read the label for details. It should be more or less the same.
Just prepare your solution in MilliQ water and pass it through a 0.2µm filter.


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Do any RNAs directly inhibit transcription
In eukaryotes, microRNAs and small interfering RNAs, as part of protein complexes, can attack specific messenger RNAs with complementary sequences, thereby inhibiting translation. However, RNA can also complement DNA. So, do any regulatory RNAs directly bind to DNA (with a protein complex or alone)?
I am only interested in regulation, not modifying DNA (like CRISPR does). I assume that means I am asking if any regulatory RNAs persistently bind to DNA, blocking RNA polymerases?
This question is for either or both eukaryote and prokaryotes.

Yes there are reports of RNA directly inhibiting transcription.
RNA induced transcriptional silencing (RITS) is a well known pathway in Schizosaccharomyces pombe (fission yeast). Initial heterochromatinization is dependent on the RNA (as a DNA identfication module) that guides other functional proteins to the target (Also see Djupedal et al., 2009).
piRNA in higher eukaryotes are known to cause methylation of target DNA regions and thereby the repression of genes at these loci (Aravin and Bourc'his, 2008).
Some classes of small RNAs in C.elegans (such as 22G RNA) are also known to cause transcriptional silencing.
Many lncRNAs are known to inhibit transcription of their target genes. The most famous example would be that of XIST which causes epigenetic silencing of one of the X-chromosomes in the female.
On a purely biochemical note, RNAs can also form triplex with target DNA regions and impede transcription and replication (Bacolla et al., 2015).


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How significant is the genetic component of homosexual behaviour?
From some basic googling, I found that nobody has ever proven that people are born gay and that environment plays a great part in homosexuality.
I wish to know if there is a genetic component to homosexual behaviour. If so, how significant is that component (in some measure such as percentage contribution to the behaviour). What are other factors that play a role in homosexuality i.e. what constitutes environmental factors?

There is some argument about whether or not homosexuality can be connected to genetics, as I have found two opposing references: http://www.osti.gov/scitech/biblio/5957271
http://www.sciencemag.org/content/284/5414/665.short
(though these are experiments conducted on males)

With reference to the original post, how was your friend in a heterosexual marriage surprising? She could simply be a bisexual.

Possible duplicate of How can homosexuality evolve despite natural selection?

Not a duplicate: One is about whether or not there is a heritable component to homosexuality, the other is about whether selection does/would act against such a heritable component to homosexuality

Related: Is homosexuality an adaptation in humans?

This is not an area I know well, but I'm familiar with a couple of studies that have tried to estimate the heritable (genetic) component of homosexuality in humans. A review paper by Rice  et al (2012) points out that:

Pedigree and twin studies indicate that homosexuality has substantial heritability in both sexes, yet concordance between identical twins is low and molecular studies have failed to find associated DNA makers.

Here is a selection of papers that should be of interest to you:

Pillard & Bailey. 1998. Human sexual orientation has a heritable component. Hum. Biol.
Bailey et al. 2000. Genetic and environmental influences on sexual orientation and its correlates in an Australian twin sample. J Pers Soc Psychol.
Kirk et al. 2000. Measurement models for sexual orientation in a community twin sample. Behav Genet
Rice et al. 2012. Homosexuality as a consequence of epigenetically canalized sexual development. Q Rev Biol.

Kirk et al (2000) find a rather strong heritable component (30-60%), which also differs between males and females (stronger in females).

Abstract
  Multivariate structural equation modeling techniques have been applied to examine the causes of individual differences in responses to several items concerning sexual orientation. To minimize potential ascertainment and response biases, the study sample involved a large (N = 4901) community-based cohort of Australian twins aged 18-52 who answered an anonymous questionnaire on sexual behavior and attitudes. The statistical power of the analysis was increased by the availability of multiple measures of sexual orientation (behaviors, attitudes and feelings), providing stronger evidence for the existence of additive genetic influences on this phenotype than in a previous analysis (Bailey et al., 2000). Estimates of the heritability of homosexuality in this sample ranged between 50 and 60% in females but were significantly lower (heritability of approximately 30%) in males.

Note however that is it often difficult to separate genetic and environmental components in these types of epidemiological data, especially when twins have grown up in the same environment. I'm also not in a position to judge or comment on the quality or methods of these studies.

Be careful about the term 'environment' in these studies. In the breeders equation, which is the model used in most twin studies, "Non-shared environment" is just a miscellaneous bin used to account for all the variance not explained by the other terms. It therefore includes measurement error, developmental noise, etc etc. So even if environment as we usually think of it plays zero role, and it's all chance events during embryonic development, 'non-shared environment' will suck up that variance.

There is a 'genetic component' to homosexual behavior in that genes do predict it to some extent. They don't determine it though. As usual it's an interaction between many factors, most of which we don't understand.

For those you are not familiar with the definition of heritability ($h=\frac{V_A}{V_P}$), you might want to have a look at this post.

I doubt that there is a gene or group thereof directly responsible for homosexuality.
Rather, if there is genetic correlation, it would be something like, a gene which makes it more likely for the mother to not produce enough sex hormones during pregnancy, or for the fetus's brain to react differently or not at all to them. Other causes of an unusual chemical composition of the womb are malnutrition in the mother or environmental causes.
And thus the tendency of the brain of a male to be aroused by female forms, or vice versa, is limited, and this makes it more likely, but not pre-determined, for homosexuality to develop.
(Educated guess)

Please add some references to your answer.


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Can both the overlapping genes (in opposite strands) produce proteins?
I have recognized that both the forward and reverse transcripts from a genomic location code for protein products. Both do occur/express in the tissue of interest. In order to eliminate by chance probability, I have screened my entire list of genes and there are 6 different examples. I would appreciate if anyone having the knowledge about such exceptions could guide me further.
Is this phenomena of protein being coded from both directions (of a given genomic location) possible? Are there any known examples?

Maybe this can help you? It is about what regulates the directionality of a gene and they seem to include 9% of the genes are translated in both directions. Although it is hard to say without knowing about the organism you are talking about (seems to be eukaryotic, since you mentioned splicing).  http://www.sciencedirect.com/science/article/pii/S1097276514010077

Many thanks, I have read this paper and its really helpful

While overlapping antisense RNAs are quite well known, there are very few examples in which both the RNAs from the pair can code for proteins. However, it is not impossible. I can cite one validated example: RU2S (DCDC2) and RU2AS (KAAG1) pair.
While RU2S is constitutively and ubiquitously expressed, RU2AS is specifically expressed in kidney, bladder, liver, and testis. It is also expressed in certain tumours (Peltz and Dougherty, 1999).

 Peltz SW, Dougherty JP. Antisense Translates into Sense. The Journal of Experimental Medicine. 1999;190(12):1729-1732.


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What evolutionary reason is there for having the urinary duct and reproductive organs so close together?
As the old joke goes, "God must have been a civil engineer. Who else would put a waste facility straight through a recreational area?"
But maybe it wasn't God. Is there any evolutionary reason (or background for) having the urinary duct and reproductive organs right next to each other (in both humans and many other vertebrates)?
To be clear, I'm not asking why isn't it elsewhere. I'm asking where the original "design" came from that spread everywhere.

Looks to me evolution aims to minimize the number of holes in a body since these are - in general - the parts with the largest risk of getting an infection.

Yes, there is.
In order to reproduce, material has to leave one organism and enter another and, in species with internal fertilisation, the eggs need to leave later. Think back to a worm-like organism: it's basically a tube with an opening at either end, those two openings are the easy options for where you can locate your reproductive transfer (and possibly egg-laying). Positioning it at the head end has obvious drawbacks in terms of accidentally consumption, so that leaves positioning it at the excretion end.
Once evolved, there is no compelling reason to fundamentally alter this bodyplan, particularly as other animals show little or no sign of sharing our revulsion at bodily excretions.
Edit: It's been a few years since I wrote this answer and I'm not really sure it is correct anymore. I've moved to working with C. elegans, which is the kind of organism that would meet that "worm-like organism" idea I was talking about, but here's the thing: they don't have their reproductive opening near either gut opening, but with its own opening located half way down the organism. If extant organisms don't follow the bodyplan I suggested, does the argument really hold?

The reason lies within our wormy chordate ancestors - an orifice used to eliminate waste can also function as an orifice to eject eggs. My vertebrate zoology is a little bit rusty so I would suggest picking up any first-course book on the subject, most of them cover the evolution of urinary/reproductive organs extensively.

I actually like this answer best - the body plan is ancient and mostly hasn't changed...

Is there any evolutionary reason (or background for) having the urinary duct and reproductive organs right next to each other (in both humans and many other vertebrates)?

Because it works.
Evolution doesn't grow things or remove things because they might be funky or useful, Evolution is dictated by the survivability of organisms. If a change helps an organism survive to pass on its genes, it's kept. If it doesn't, it's eliminated from the gene pool over time. As long as a change doesn't significantly help or harm, it can be kept for hundreds, thousands, even millions of generations.
Evolutionarily speaking they are where they are because we're mammals that were formally quadripeds that became bipeds. The stereotypical quadripedal design has the reproductive organs located near the pelvis. Probably because they're best protected there. Powerful hind limbs for kicking, and nasty teeth and claws up front. It also gives easy access for mating, which is pretty important if you want to continue the species. On quadripeds it could be pretty darn awkward if the genitalia were located near the ribcage
Really, you could come up with a lot of reasons why the organs are located where they are. There are a lot of advantages, and a lot of disadvantages, but in the end the simplest explanation is going to be "Because we can survive with them there." The advantages have outweighed the disadvantages for our species' history thus far, and until that changes they'll probably just stay where they are.

your middle paragraph explains why the reproductive system is located where it is.  But why is the urinary system located here as well, not say on the abdomen of the quadruped.

@Chris Could you clarify? The kidneys and bladder are located within the abdomen of quadrupeds (and us).

Yes I meant urinary duct, not system, which is located where the reproductive system is.  That is, why are these located in the same spot as each other.  Your second paragraph explained for the reproductive system, but not the urinary duct.

Nice job giving an answer that avoids the pitfalls of naive adaptationism. The presence of a trait doesn't mean it's a good idea, just that it's not bad enough to kill anyone (and/or kill their chances at reproducing).

I was asking where it came from in the first place, not why it didn't change.

@JoeZeng - That's fine. Next time make that your first question instead of the question that's asked nearly three weeks after the fact via an edit. We can only answer what's on the page, we're not psychic.

I thought it had been clear enough in the initial ask, but apparently I was wrong.

Human body has three channels for excretion of substances, one for each of the three physical phases of matter: lungs for gaseous substances, such as CO2, anus for solid substances such as feces and urinal channel for liquid substances.
It turned out that sperm is liquid, so it uses the same channel as liquid urine.

Excretion of substances is a great reason for them to exist, but not for their positioning. Just because sperm is a liquid isn't a great reason for the penis to be located between the legs.

Anixx, one word - beans.

@MCM, the question doesn't ask why the penis is located between the legs, but rather asks why the urinary duct is close to the reproductive organs.  Anixx is trying to say that it is more efficient to utilize the one pipe for both liquids, just as we use our lungs to both breathe in oxygen, and expel carbon dioxide, rather than have two separate systems.

@Chris - I understand your point, but my critique was that there are pretty common examples of organisms that don't put the excretion of phases of matter together, so I didn't find Anixx's argument as full as it could be.

Then why when one vomits, do we use our mouth? Looks to me that vomit is liquid as well.


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Why might you NOT observe a tradeoff between two life-history traits?
I have traditionally thought of and heard about life-history traits (e.g., size at first reproduction, number of offspring, size of offspring, survival, etc., etc.) as drawing from a finite pool of resources that an organism has, and therefore exhibiting tradeoffs. So, for instance, an organism that invests in a lot of offspring would experience a decreased probability of survival.
It has recently come to my attention that this is not always the case, and I'm not sure why. I have been directed to the work of David Houle, who wrote extensively on the topic of life-history traits, but some of his work is inaccessible to me intellectually. I was hoping that somebody had a more digestible explanation or was maybe more familiar with Houle's work.

Could you link to a few works in particular, or where you first read that?

The name of the paper I've read is, "Genetic covariance of fitness correlates: what genetic correlations are made of and why it matters". David Houle from the journal Evolution, 1991, Vol. 45. Issue 3. Pp 630-648.

It apparently has something to do with the number of loci influencing ability to obtain resources versus the number of loci influencing how those resources are allocated...

For those willing to answer: Here is David Houle's article

The simple explanation is that there are three (or more) traits drawing from the pool, and you're only looking for trade-offs between two of them. The unobserved third may show the effect of a trade-off.

Can you explain some more with references?


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Is the sex of siblings mutually independent?
I am studying probability, and one of the lectures I came across (Skip to 52:00) states that the sex of siblings is not mutually independent and that there is some correlation.
Can anyone tell me why? And if so, where is the evidence?

There is at least one paper that claims this:

A test for heritability of the sex ratio in human genealogical data is reported here, with the finding that there is significant heritability of the parental sex ratio by male, but not female offspring.

--Trends in Population Sex Ratios May be Explained by Changes in the Frequencies of Polymorphic Alleles of a Sex Ratio Gene. Corry Gellatly, Evolutionary Biology 36:190-200, 2009 DOI: 10.1007/s11692-008-9046-3.
In other words (simplistically) some families are more prone to have male offspring, which implies that the probability of male offspring is not independent.  However, this is a hypothesis, not a proven fact, and I think it's not a very strong hypothesis.
A non-scholarly, but apparently careful, discussion is here:

The odds of having a girl seem decrease after having each boy, but only very slightly. Even after 3 boys, you are only 6.4% more likely to have a 4th boy than a girl.

What are the odds of having another boy or girl?

Has anyone just simplistically looked at how the sex of your first born impacts on your likelihood to have further offspring of the same sex?

I updated the answer to point to a non-peer-reviewed site that looked at that.


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What legal possibilities exist to get access to articles behind paywalls?
Many publications, be it in high-profile journals, proceedings, book chapters or any other medium, cannot be accessed without subscription alongside substantial costs, even though most of the published work has been financed publicly. I was asking myself if there are options to get legal access to these publications and if so, what these options are.
As a concrete example I would like to give the following. I am
searching for the following article that has been published as a book chapter in Molecular Biology that is behind a paywall:
Protocol
DNA Repair Protocols
Volume 314 of the series Methods in Molecular Biology™ pp 183-199
Quantitative PCR-Based Measurement of Nuclear and Mitochondrial DNA Damage and Repair in Mammalian Cells
Janine H. Santos, Joel N. Meyer, Bhaskar S. Mandavilli, Bennett Van Houten

What possibilities are there to get access to this?

You have all the information ready to easily find it. Is a paywall the problem? If so, probably nobody will infringe copyright (be it ethically valid or not) here and you should try to get access by your/an institution/library or contact one of the authors to see if they are willing to share their work.

This is not really a question.

I edited the question for making it interesting for many biologists. It, of course, is not a question about biology per se but is still relevant to many, if not all, biology researchers. In a way it is about techniques that biologists have to deal with in their research life.

There are several ways you can try to get legal access to publications that are not open access.
First, and most simple, subscribe to the medium or pay for the single publication. This is usually very expensive, so you might want to look for other ways.
Second, you can try to get access by your/an institution by logging in over your institutes network. They might have access to publications from that medium. If not, ask your institution if they can get that access (some libraries offer this based on requests).
Third, go to a public library or a university library and see if they have access to the medium. If so, you can register to the library and then have access as a library member. There might be fees involved but these should be substantially lower than paying for the article directly.
Fourth, you contact one of the authors to see if they are willing to share their work, either as copyright holders or in form of drafts/pre-prints (in that case you should write to the corresponding author, the last author or the first author, maybe include all these three to your email as cc).
This leads to fifth, look at pre-rint servers like the bioRxiv, maybe you are lucky and the publication has been put there by the authors.
Sixth, closely related to four and five, look for the authors on scientific networks like Research Gate. Many scientists share their public articles there or allow requests for sharing their work.
In your special case example you are lucky ... You can find the first author (Janine H. Santos) on Research Gate and she has the article downloadable. If your are not a member you can register without fee and just download the article.


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How is signalling disturbed in trophoblastic cancer cells?
Trophoblastic cancer seems to be a form of growth that no longer responds to the neural signals which try to inhibit them. Can someone please explain whether experiments have been performed as to how exactly cancer cells manage to "shut off," these neural signals?

Welcome to Biology.SE. I edited your question so that it now includes a reference to the Wikipedia article of the disease. I also tried to make it more clear and changed the title accordingly. However, I am not sure what you meant by "trophoblastic hypothesis of cancer". As the only trophoblastic cancers I am aware of are GTD (see link) and they are very rare, I would doubt that this is a general hypothesis for the various cancer forms. Then again, all cancers are a form of growth (this is one of the defining characteristics for tumours), so I am not really sure what you mean. Please clarify.

I just want to know why they dont respond to normal neural signals like other cells.

If that has already been discovered

@Lelouch have you done any research at all on the subject? Tumors don't respond to normal growth inhibition signals because they have been highly mutated. Please read up on cancer, what it is, and how it arises - it is very well known why tumors don't respond to inhibitory signaling. Also, the neural system doesn't carry growth or growth-inhibitory signals. A system of protein-based cytokines and growth factors does that, as well as hormones.

Thank you very much. Can you provide a link on the topic? I would be grateful.


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If I stop consuming protein, will I still excrete urea?
Will an animal that is not eating any aminoacids stop excreting urea (or whichever other form of excreting nitrogen)? If the body is not in a position to lose nitrogenated compounds, in which processes is nitrogen inevitably turned into waste products like amonia/urea?

A hypothetical question from a new user who hasn't taken the Tour looks suspiciously like a homework question for which there is a specific policy on SE Biology. For all questions, but especially homework questions you are required to show evidence of trying to answer the question yourself. In addition your standpoint seems unclear. Your "why not?" seems to be responding to some unspoken answer. Please clarify.

The reason I am asking is because I am looking at the optimal protein intake from ratios of macronutrients for a healthy low-empty calorie diet. I want to understand what the smallest replacement amount of protein is that won't trigger autophagy and why even under autophagy one will still lose protein. I am sorry if I posed the question in a way that begs for a specific answer, but I could not really find a concrete answer to why it is that there is always some urea around even under nitrogen deficit. Seems to be because aminoacid reactions produce byproducts like ammonia that can't be reused.

Yes, you will still excrete urea, but the amount you excrete will be diminished. As you might expect, when the body is low on protein, there's a physiologic drive to hold onto as much nitrogen products as possible, in order to conserve the limited supply.
Normally, your kidneys excrete approximately 40% of the urea that is filtered through the glomerulus. (It's slightly more complicated, because there's both secretion and reabsorption that happens along the nephron, but that's approximately the end result.) However, in protein malnutrition, the kidneys reabsorb more of the urea, and that number can drop to excreting only 10% of the filtered urea. (Source) It appears that this is an active process to reabsorb the urea, rather than a passive effect from other effects that malnutrition has on the body.
However, the body isn't capable of stopping excretion of urea completely... there will still be some that is excreted. Urea transporters in the kidney aren't 100% efficient, but probably the bigger issue is that the body needs to use that urea to regulate other functions. Urea is important to the body's ability to concentrate urine, which in turn is related to the body's regulation of blood volume and sodium concentration. And in general, the body cares more about maintaining proper blood volume and tissue perfusion than anything else.

also not eating protein will not stop proteins in the body from wearing out and having to be recycled.

Despite the title I would have thought the biochemical tag indicated an interest in whether urea was actually synthesized in starvation. Irrespective I find the information you provide about urea resorption interesting — I was not aware of it. Do you know whether the resorbed urea can be converted to useful biochemical intermediates either by reversal of the urea cycle or by other means (urease?).

What I don't understand is why when a protein is recycled, it won't just return to being made of its original aminoacids. Can't the body keep those aminoacids around for further usage? What is the specific reaction family that releases ammonia/urea (not the ones triggered when the body runs out of energy storage and has to use aminoacids as an energy source). Essentially, where does deamination occur in the aminoacid cycle and how can it be reversed?

If an animal that is not eating amino acids is still eating enough nucleic acids to degrade some, that will produce ammonia and urea.
Plus some amino acids will still get degraded.

The scenario I was thinking of is one where you have plenty of sugar/fat around, so no energy deficit, but you are eating too little protein, so that the losses of nitrogen can be somehow reversed. If they can't, why is such a reaction necessary and irreversible, even with availability of energy to reduce entropy increases from protein degradation into aminoacids?


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Interpretation of qPCR results for low expression genes
I am attempting to validate existence of a transcript using 40 cycle qPCR. I designed primers for a unique feature of this transcript, and also designed primers for a sequence in the transcript that is common to several transcripts of this gene, and finally I used GAPDH as a control. I already knew beforehand that this transcript has very low expression.
For the unique region, my ct values for primer 1 were between 31-34.8, and my ct values for primer2 and primer 3 were all consistently 35, and primers 4-6 gave no result at all.
For the region that is common to several transcripts of this gene, the ct values were between 30-34 for one primer, and consistently 35 for another primer.
For GAPDH, ct values were around 22.
Can I use these results to indicate that my transcript exists (or even may exist?) in the samples I tested? Is the fact that the ct values for the region unique to the transcript I am targeting and the region in common between several transcripts are quite close indicative of anything? On the graph from the qPCR, there are distinct rises respectively around 33 and 35 for the unique region amplicon.
EDIT: I was doing a bit more research, and it appeared that this study: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4296690/
also had results that came up "late cp call last five cycles has higher uncertainty" and considered these results positive if they could be replicated in a duplicate - if I were to show this as well, can I use this data in a paper?

What have you done to validate the conditions of your reverse-transcription and real-time PCR with respect to these transcripts? Can you get more input mRNA (say, enough so that $C_t$ values for GAPDH are well under 20)? Is the final PCR product for your transcript-specific primers at least the correct size based on your predicted transcript? Note that $C_t$ values differing by 4 units represent 16-fold differences in transcript abundance.

@EdM Well the mRNA was converted to cDNA quite a long time ago, and I simply ran a qpcr on the cDNA- the transcript I am trying to validate is a novel predicted one, so I guess I have not done anything to validate the conditions of the reaction specific to this transcript. The concentration of cDNA I used was 100 nanograms / microliter, so I guess I could try to increase the cDNA amount. How would I know if my product is the correct size from a qPCR? I am planning on establishing a concentration curve next Monday for the primer that seemed to work the best.

@pMarkov you validate PCR product size by running regular old-fashioned PCR with your primer pair of interest, and run the reaction out on a gel with a ladder for reference.

@MattDMo, ah silly me, thank you, I'll be sure to do that as soon as possible.

If you can't replicate the biological experiment, all the re-analysis of old cDNA isn't going to be good enough. Reproduce the conditions that led to the hypothesized production of the novel transcript, at a scale that allows better control of PCR conditions.

No prob. Sometimes we get too caught up in all the technology in the lab and forget about the simple stuff...

@EdM- could you elaborate a bit on the scale that would give me greater control on the PCR conditions? What types of parameters could I look into altering? The cDNA I am using is derived from the same phenotype that produced this "novel" transcript- I'm trying to validate existence of the transcript (/if primers work) in this abundant cDNA before I proceed to the more precious cDNA from samples I originally detected the transcript in. I was wondering if the results above were indicative enough to proceed testing, or what I could do/parameters to change to get stronger results before I move on

Transcripts from the same gene, and the gene itself, are notorious for low expression- I truly appreciate the advice/help!

To validate the existence of transcripts could be done by sequencing of PCR products amplified if you can deny contamination and amplification from genomic DNA.

When you have one copy of your target cDNA in a PCR tube, theoretically  Ct would be 34 around in an ideal condition: the PCR efficiency is 100%. You might want to check the efficiency of these primer sets.

@243- I'm guessing I would have to clean the qPCR product before I submit it for sequencing?- Usually we design a completely new set of primers from a different software for sequencing. I have not checked primer efficiency- good idea, another test to run next week. Can anyone speak to what (if any) conclusions may be drawn from the results above?

@pMarkov as MattDMo said, do a conventional PCR. Also do a 3'/5' RACE to confirm the actual size.


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What are some (bioinformatic) methods to characterize potentially novel gene transcripts?
I am working with a few novel transcripts of genes- before I confirm their existence experimentally, I would like to perform some bioinformatic analysis. I have already considered coding potential, protein domain prediction, transcription factor binding sites, sequence homology, and RNA secondary structure (still a little unsure how to use this one). These transcripts were discovered using RNA-Seq. Are there any other elements of genes/confirmed transcripts that I should look for in the sequence of my transcripts and corresponding softwares? (I can find the software myself if necessary, but I have run out of characteristics to search for). I would like to characterize these transcripts structurally and functionally as completely as possible, including potential protein function, mRNA degradation, etc - some new features for what to look into would be appreciated.

The current version of your question is unclear. The RNA-Seq reads you are analyzing clearly exist (otherwise there would be nothing to analyze) yet your question makes it sound like the transcript does not exist. If the transcript does not exist then what is your alternative hypothesis? Where could the reads come from?

Thanks for your response! Let me clarify: these transcripts are created by alternative splicing, and are unique in that they contain retained introns. Their expression levels are quite low, and I have been told that there is significant likelihood that they are merely artifacts ( I am not too familiar with rna-seq to understand where this may arise) -"novel" transcripts with intron retention apparently do not often hold up to experimental validation. I want to gain evidence that they exist in silico before I move on to qpcr.

Furthermore, I would like to characterize these transcripts as much as possible - gain insight into whether they would just be noncoding transcripts or be of some interest- I attempted to look into what types of protein domains may arise, whether the transcript retained introns have coding potential, and new tfbs. Essentially I want to gain as much insight into the structure and potential function of this transcript as possible, using only the sequence. I am merely a student, so please ask for further clarification! *I edited to question to match my responses here.

@mdperry- As an example, I am currently looking into potential miRNA binding site introduced to the transcript through intron retention - I am open to investigation of any interesting features that these transcripts may bring!

You might want to check the genomic sequences and how the transcript is spliced so that RNA-seq data could be confirmed. You may also find alternative splicing isoforms. You could check poly A signals in the genomic sequence.

How was the library prepared? Poly-A or Ribo-minus? First of all you should validate the novel transcripts. Sometimes you may end up with false positives.

@WYSIWYG The library was prepared Poly-A. I am currently awaiting the necessary primers for validation (about a week), and in the mean time I wanted to characterize the transcripts as fully as possible (predict function, structure, etc) and was looking for more ideas on how to do so. I have read a number of papers performing in silico analysis and have done many of their methods and was looking for a few more.

It sounds like you have considered most of the obvious alternatives (and thank you for clarifying the question).  I suppose the first question in an alternatively spliced transcript with a retained intron is whether the open reading frame of the protein is maintained.  If there is a termination codon that now becomes in-frame due to the intron then the protein would ordinarily be truncated.  The mRNA could also get targeted for degradation due to the nonsense-mediated decay pathway (i.e., from introducing an early stop-codon).
If the alternatively-spliced transcript lacks any significant ORFs, or if there is an ORF but no suitable translation initiation codon then you have entered the realm of non-coding RNAs, of which there are two loose categories, microRNAs (there are several classes) or long non-coding RNAs.  most miRNAs have recognizable sequence motifs, may be contained in mir-Base, and may be complementary (in part) to a regulatory target elsewhere in the genome. lncRNAs are less well-defined. Perhaps the best criteria are transcripts that are stable enough to be detected, but lack noticeable protein coding features.  I don't even think there is a consensus on the minimum length of a transcript to be considered an lncRNA.
What sort of databases have you searched? For example the ancient dbEST contains all kinds of short cDNA reads from all over the planet, dating back to 1992 (or so).  Evolutionary conservation of exons and splice-sites, or reading frames can all be used to support the hypothesis that a transcribed region has a biological function.
For a really deep fishing expedition you can use tblastn, etc. to take a potential translated ORF and search all 6 conceptually translated reading frames of all the sequences in a database--it takes longer, and there can be many spurious matches that you have to search through, but if you are studying something that has never been annotated it might be worth considering.
RE: folding RNA (secondary structure) every sequence can be folded into some kind of structure (try it and see), but structurally conserved compact loops typically fall into one of a small class of selected families (like GNRY). Stems are easy to find, but if the single-stranded loop is huge, how likely is that structure to fold up in real time?
RE: TFBS not clear to me at all what you mean by this. Transcription factors bind dsDNA not ssRNA. There are families of protein domains that bind RNA but not typically with such sequence-specificity.  So unless this alternatively spliced transcript is being transcribed from some type of alternative promoter, I am not sure where you would even be looking for TFBS.  It's true that some large introns can indeed contain regulatory regions for the gene as a whole (cf. immunoglobulin heavy chain enhancer is conveniently stored in an intron), but it is not clear to me if that would have an affect when transcribed into RNA.
I do like your idea that a retained intron could now contain a binding site for a regulatory miRNA, but if I understand the theory this would lead to the transcript being degraded--so it would be more difficult to detect.

Thanks! Again, I believe I have not shared all necessary information; in some of the transcripts, the alternative spicing generates an alternative 5' UTR, in which I am searching for TFBS (these alternate 5' UTR's appear to be retained introns). The miRNA idea comes from that these transcripts are actually differentially expressed in the disease phenotype I am analyzing, so I was looking into  introduced miRNA binding sites as a potential reason. The ORF analysis is interesting-I had not considered the meaning behind a lack of orfs within the retained intron. Thanks for your time!

Some suggestions.
For identifying function do a homology search. There is little functional annotation of lncRNAs. So homology based information can be obtained only for protein sequences. So you can try these:

Check the coding potential. Find ORFs (perhaps set a minimum length cutoff). To be stringent you can also check for Kozak consensus sequences (for eukaryotes) in these novel transcripts. This program apparently includes the Kozak rule in start codon prediction.
Translate the RNA and run psi-BLAST. Psi-BLAST is better than normal BLASTp in identifying distant homologs.
You can obtain the GO (functional annotation) data for these homologs and relate them to your novel transcript.
For lncRNAs, you can find if they overlap with any other known transcript. Many lncRNAs seem to have overlapping loci with their target genes (both sense/antisense).
Search for RNA motifs. This article reports an extensive study towards identification of different RNA motifs (RBP binding sites) in humans and Drosophila. Other interesting motifs include quadruplex forming motifs and ARE.
If you have the genome sequence then you can map your transcripts to the genome and identify the introns. Actually your RNAseq assembly, if reference guided, would produce a GTF file. You can extract introns using the GTF. You may check for potential miRNAs in these introns, based on stem loop predictions. However it is better to have a small-RNAseq data for predicting miRNAs reliably.
As you had already considered, you can check for miRNA binding sites. For this purpose miRanda is the best for novel transcripts (TargetScan is a pain). You can use RNAhybrid too and take a consensus of miRanda and RNAhybrid results.
You can do other kinds of analysis based on just the sequence of the transcripts. These include checking for codon usage (for potential protein coding RNAs), GC richness (comparison with the known transcripts) etc.


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Periodic Muscular Growth in Humans
If a healthy human is at a certain muscle state and then experiences muscular atrophy solely due to disuse/lack of exercise, is it easier to gain that muscle back than if the human had never reached that certain muscle state. If so, is there a name for this effect. The reason I'm wondering is because it seems like muscle mass was definitely periodic in ancient times when food would become scarce during the winter, and that an increased ability to put back on muscle might have developed evolutionary-wise. I thought that this would fit best in biology, let me know if this isn't the case.

What are we assuming caused the atrophy?  Because the correct answer would be "depends," which isn't very satisfactory.  From your example, do you mean in the case of malnutrition?  You also have injury, illness, senescence, lack of exercise, or parasites--though they can be put under the others.

Good point see edit

Muscle memory specifically in the effects of hypertrophy. There is also muscle memory for skills which shares some factors but mostly differs.
When muscle hypertrophies or "gets bigger" extra nuclei are recruited to make more sarcomeres or proteins involved in muscle action. Once these nuclei have been recruited and essentially activated once, they're much more easily activated again.
Above is an answer based on my knowledge, but you can wait for Atl LED if you need references.

Disuse and lack of exercise are actually exceedingly new problems when considered on an evolutionary scale.  The bigger evolutionary pressure for the last few million years has been not starving to death, therefore not maintaining expensive muscle fibers unless they were absolutely necessary.
I haven't found any evidence of previous musculature effecting growth, but I'm going to look into it more (only some quick pubmed searches), and edit this answer.  If someone else knows more immediately, please feel free to answer.