text:
Can epigenetic changes affect reproductive success?
This is prompted by niallhaslam's answer to this question [Since Darwinian times, has there been any striking/notable effects of evolution on humans?]. A comment by Alan Boyd asks whether epigenetic changes count as evolution.
Transgenerational epigenetic inheritance can occur, and does increase the natural variation of a species (although this review is more about plants, this does apply to animals too) [1]. Based on this alone I'm inclined to say that epigenetics can affect the fitness of a species, and thus could contribute to evolution.
I am interested to know if, in practise, this does occur, and whether epigenetics have been shown to affect the reproductive success of a species? Because the changes are not permanent I could imagine that they actually have very little impact "species-wide", as environmental effects (infections, toxic exposures) also affect epigenetics. So, is there any evidence for epigenetics affecting the reproductive success of a species? This also includes whether epigenetics can influence traits enough to create a new sub-species.

Becker, C., & Weigel, D. (2012). Epigenetic variation: origin and transgenerational inheritance. Current opinion in plant biology. doi:10.1016/j.pbi.2012.08.004.

This article deals with the effect of phenotypic variation brought on by epigenetic patterns, and how these are inherited to the next generation. Their conclusions?

Our results show that epigenetic variation is inherited in chickens, and we suggest that selection of
favourable epigenomes, either by selection of genotypes affecting epigenetic states, or by selection of methylation
states which are inherited independently of sequence differences, may have been an important aspect of chicken
domestication.

However, I personally prefer this article, as it has a more profound implication on reproductive success and addresses your question specifically. They found the there is a species-level difference in DNA methylation between humans and chimps, but more importantly that this difference is responsible for the causation of numerous lethal diseases/conditions, which has a direct impact of the fitness of the species as a whole.

Finally, we found that differentially methylated genes are strikingly enriched with loci associated with neurological disorders, psychological disorders, and cancers. Our results demonstrate that differential DNA methylation might be an important molecular mechanism driving gene-expression divergence between human and chimpanzee brains and might potentially contribute to the evolution of disease vulnerabilities. Thus, comparative studies of humans and chimpanzees stand to identify key epigenomic modifications underlying the evolution of human-specific traits.

In summary, evidence has shown that epigenetics does seem to play an active role in the evolution of species, although the exact mode of inheritance of DNA methylation from generation to generation is unknown.

References

Nätt, Daniel, Carl-Johan Rubin, Dominic Wright, Martin Johnsson, Johan Beltéky, Leif Andersson, and Per Jensen. “Heritable Genome-wide Variation of Gene Expression and Promoter Methylation Between Wild and Domesticated Chickens.” BMC Genomics 13, no. 1 (February 4, 2012): 59.

Zeng, Jia, Genevieve Konopka, Brendan G. Hunt, Todd M. Preuss, Dan Geschwind, and Soojin V. Yi. “Divergent Whole-Genome Methylation Maps of Human and Chimpanzee Brains Reveal Epigenetic Basis of Human Regulatory Evolution.” The American Journal of Human Genetics 91, no. 3 (September 7, 2012): 455–465.

Very welcome, nice timing for the question too. The second article came out less than a month ago.


text:
Why can't we call dog breeds different species?
I understand this question might fall into opinion based, but I'm trying to write it so that it meets the "Many good questions generate some degree of opinion based on expert experience" part and not get closed.
A closed creationist question about directly observing the evolution of new species made me think about just declaring dog breeds as new species just to provide an answer to that question. Turns out I'm not the first one to think of it, and to be honest I probably read that article and forgot about it.
That article quotes geneticist Jerry Coyne as saying:

“If somehow the recognized [dog] breeds existed only as fossils,
  paleontologists would consider them not one species but
  many—certainly more than the thirty-six species of wild dogs that live
  in nature today.”

There is also this question about breeds of dogs being different enough they can't breed. The answer posted to that question discusses attempts to breed beagles with irish setters, and having great difficulty.
I'm aware that the commonly used definition of different species is individuals who can't interbreed and make a fertile offspring. However the Scientific American article I referred to above mentions that animals are often classified as separate species because they are separated by a geographical barrier, and if they could mingle they would make fertile hybrid offspring. The same articles mentions fruit fly research that bred two different species of fruit fly and made fertile offspring, even though they would never interbreed in the wild.
This is speculation, but let's imagine taking an island and putting several breeds of dogs on that island. Many of those breeds would easily interbreed and create mutts. But I'm pretty sure there would some sorting, the large dogs like st. bernards and great danes aren't going to easily interbreed with tiny dogs like chihuahuas. If we came back to this island after 50 or 100 years, we'd probably see small dogs and large dogs (assuming the island had decent ecological niches for both sizes of dogs to survive in)
Creationists like to ask why we haven't observed the evolution of a new species and don't want to listen to arguments about the fossil record or DNA sequences. If we just define some dog breeds as different species, we'd have an easy answer. I think some dogs would at least come close to meeting that definition for these reasons:

Dog breeds with large size differences would have great difficulty breeding.
Some pairs of breeds seem to have trouble interbreeding (Beagles + Irish Setter).
Some animals recognized as different species can create fertile hybrid offspring.

So why don't we recognize some dog breeds as different species?

Your island thought experiment is very interesting.  One thing to consider: how would natural selection act on these breeds?  Would large or small breeds be selected against?  What breeds have genetic issues the reduce fitness (eg, hip problems are common in large breeds).  I suspect that the size differences most likely to result in "species" would not be stable in a more natural environment.

@NBrouwer It would have to be a very special island. This points out that wild dog populations don't include the more extreme breeds like bulldogs, and tend to be more like their wolf and coyote relatives.

Interesting island experiment, but with intermediate sizes they may eventually all interbreed to produce a single population of mutts. What about introducing only two breeds of dogs - one very large and one very small.  If the island has sufficient resources that both can survive, would they effectively develop into different species?  Might they evolve in ways that pushed them further apart?

A side note: if you're looking for an example of observable speciation to use in arguments with creationists (and are willing to consider non-mammalian examples), it is worth noting that a substantial proportion of plant speciation events are 'ploidy events. 'Ploidy events generate new species essentially instantaneously by producing an offspring that is self-fertile, but not capable of back-crossing to close relatives.
http://www.pnas.org/content/106/33/13875.full

I don't enjoy the idea of comparing people to dogs, but this is a bit akin (please note the bit) to asking if people who are genetically short (or "little people", both proportionate and disproportionate dwarfism), pygmies, short people, normal sized people, tall people, very tall people, and people with acromegaly (gigantism) can be called different species. I compare because it's fairly clear to most individuals that we are all the same species: homo sapiens. About breeding, it is very likely that a reproductive specialist would be quite concerned (I certainly would be) about a woman with drarfism carrying the child of a very tall person (who had very tall parents), but not the opposite pairing.
Below is a photograph of the wedding of Tom Thumb and Lavinia Warren. That union produced no children. Her bridesmaid Minnie, (her sister), who was only 27 inches tall, also married a little person (Edward Newell). She became pregnant with a normal-sized child, but died during the birthing of a 6 pound baby (her baby died as well).

Are they a different species? No. A paleontologist (a good one) would be able to tell that the bones of a little person was actually of the same species based on certain conformations, just as I believe paleontologists today could distinguish prehistoric small cats from very large cats. Size matters, but not nearly as much as the type and distribution of teeth, the shape of the jaw, etc.  In other words, I strongly disagree with the following:

If somehow the recognized [dog] breeds existed only as fossils, paleontologists would consider them not one species but many—certainly more than the thirty-six species of wild dogs that live in nature today.

That statement is based on a fairly profound error in thinking: a cognitive bias that is mistrustful of science in general due to a lack of familiarity with the rigors involved in the scientific methods of paleontologists in particular. I say this without rancor or animus of any kind; where I settled down (in the deeply religious region), the vast majority of my children's friends' parents are creationists, and the vast majority of our friends are fundamentalists. We argue about science all the time; I know the basic arguments. I'm familiar with their websites. I personally find myself in the camp of Christian thinkers like geneticist Francis Collins, M.D., Ph.D., the director of the Human Genome Project, who understand genetics and find no threat to their faith in evolution or science. (E.g. Creationists reject all science which indicates the age of the Earth is >~6000 years.)
The truth is that the definition of a species is not that easy, even for prokariotes. Difficult as well is a pure definition of life.
Finally, about size. The domestic dog exhibits greater diversity in body size than any other terrestrial vertebrate. This is due to a small number of (or perhaps even a single) alleles: the IGF1 Allele. It's hard to argue difference of species on the basis of a small number of alleles: we allow much more variability for other alleles without wanting to classify as different species: eye color, hair color, hair length, straight vs. curly coat, degree of tail curl, ear morphology, etc.
A Single IGF1 Allele Is a Major Determinant of Small Size in Dogs
Lessons learned from the dog genome
A species definition for the modern synthesis
Single-Nucleotide-Polymorphism-Based Association Mapping of Dog Stereotypes
Canine Genetics Facilitates Understanding of Human Biology
How many species of prokaryotes are there? (PNAS)
Ernst Mayr and the modern concept of species (PNAS)
Hybridization, ecological races and the nature of species: empirical evidence for the ease of speciation
Is it Useful to Have a Clear-cut Definition of Life? On the Use of Fuzzy Logic in Prebiotic Chemistry

I think the size diversity would throw paleontologists off though. Dog diversity is a result of selective breeding, not natural selection, so you can get a much greater diversity in less time. If you didn't know what a dog was, much less that it had been artificially produced by humans, you might not realize that dobermans and chihuahuas are the same, especially when so many different species are separated by subtle differences.

Have you ever read any paleontology papers? Size doesn't matter. Elephants belong to the family Elephantidae, the sole remaining family within the order Proboscidea. Their closest extant relatives are the sirenians - dugongs and manatees- and the hyraxes, with which they share the clade Paenungulata. Have you ever seen a manatee or a dugong, or, incredibly, a hyrax? Please, give paleontologists credit where credit is due. I have opinion supported by sources. Where are your sources? I think you're wrong isn't an effective argument.

I'm not saying they wouldn't recognize the dogs as related, just as different species instead of different breeds. If the current breeds of dog had developed naturally instead of artificially, I think we would have classified them as different species. And dog breeds are different by more than size, a chihuahua is not a scaled down doberman, dogs have differently shaped skulls and different proportions for limb length.

Any sources to support that opinion? Did you compare the hydrax to the elephant to the dugong? Why do you think they'd be different species? Please support.

The wikpedia page on the hyrax explains why the hyrax is similar to elephants, and the page on paenungulata describes other features of the group. Both pages mention information about the placement of soft tissue such as the testes and DNA evidence, information that usually is not available from fossils and had to be obtained from living members of the group. Furthermore, these diverse species are members of 3 orders. Dogs would members of 1 genus.

@anongoodnurse: Since you mention elephants, consider the recent 'discovery' (or IMHO redefinition) that there are three existing elephant species, rather than the two (African and Asian) that've been accepted throughout history.

I don't think taxonomy works as precisely as one would hope...NOT that they don't have standard approaches but they are often working with inadequate information.  Rightfully, if a population of chuahuahuas and St Bernards lived side by side in the wild, they would, from a biological standpoint be considered a different species because they could not interbreed.  IT would be physically impossible.  And, in short time, behaviors of both would tend them to start staying away from each other.  NOT that evolution works preemptively, but as behaviors vary...those tiny dogs that simply stayed away from the massive males would tend to survive (NOT die in child birth) while those that inadvertently got pregnant by the massive male DID die in childbirth...any inherited tendency toward the safer behavior would be selected for.  The "example" of dwarfism...when it is known, does not apply to finding fossils in rock strata.  Through testing and actually experience we know very small people can interbreed with very tall people.  Often the pregnancy doesn't end well.  But for now and for reasons other than pure science, no one is considering re-naming human taxonomic groups...and they shouldn't IMHO.   But with dogs, with sometimes completely different structures and sizes of skulls and other body parts and the recognition that the massive dog's fetus would not life and be birthed from the tiny dogs womb would incline them to be described as different species.  Size AND VARIATION in structure does matter in taxonomy.

I don't think this really answers the original question.

I don't hink this either. Can you please edit your question accordingly, add some references and also remove the personal part against anongoodnurse?

Don't under estimate @anongoodnurse's answers :-) -1 If you think you can do better, do better. Don't try to be better by downgrading others. Instead, try to build on previous answers and use them to provide superior material.

source: Stack Exchange

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

sort: votes


text:
How do small animals make loud sounds?
Walking past the park today, I heard a cicada so loud I thought at first it must be some sort of large power tool. How is it that that very small animals like cicadas (crickets, etc.) can make such loud sounds? It seems intuitive that larger animals should be able to make louder sounds, but perhaps:
a) I just fundamentally misunderstand the physics involved
b) A theoretical larger animal should be able to make louder sounds, but cicadas are just extremely efficient, making up for their small size
c) ?

c) might be 'they can make louder sounds, but usually choose not to'. Blue(?) whales can be heard for thousands of miles underwater. I imagine alerting every lion for thousands of miles isn't a great thing to do if you're an elephant.

It is true that the total energy budget for smaller animals should be smaller. Perhaps it's because cicada sounds are spectrally narrow? The total power of the sound might be small, but it's concentrated around a specific pitch. Just a hunch.

Also note that size isn't everything here. Cicadas broadcast at a high frequency because they are moving so fast (which does take up a relatively large amount of energy).  If you could get an elephant to move as fast you could probably make some defining sounds, but the energy requirement would probably be to large.

I know that "high frequency" affects pitch - does it affect loudness too?

Yes, since high frequencies have higher energies. Low frequencies can travel further, though.

Large animals (which tend to be mammals), have vocal chords rather than some insects vibrating/rubbing membranes, and possibly vocal chords are less efficient.

The Cicada
A careful study of the noise-making apparatus of the cicada can be found in a 1994 paper by Young and Bennet-Clark.$^1$ The authors generated sounds at about 0-16 kHz at peaks on the order of 100 dB using cicadas in various stages of deconstruction.  The cicada uses a resonant organ-system called the tymbal which buckles and unbuckles rapidly to produce sound. The buckling-in is caused by muscle contraction and is louder than the buckling-out (relaxation) phase. Air sacs (a feature of many other small noisemakers) serve to amplify the sound.  The tymbal itself, for the species in this paper, has a resonant frequency of about 4kHz (Young, page 1017). The song of the cicada as modified/amplified by air sacs and other structures, is often around 10kHz.$^{2}$
Pure Tone vs. Diffuse Tone?
The vocalizations of large vertebrates are a complex superposition of waves that in the frequency spectrum are somewhat spread out. To the extent that a frog or a bird emits a pure tone, the energy will be confined to a narrow frequency range and this may be a strategy for achieving greater amplitude. Given comparable audio sensitivity, however, the intensity of pure tones will depend on amplitude (intensity), regardless of frequency.$^{3,4}$
Other Small Loud Animals
While the songs of cicadas are intense, especially in concert, on an individual level there is competition from other species. According to a Gizmodo article quoting assorted scientists, the snapping shrimp produces a transient snap that is around 200 decibels, a level that one site describes as "deafening." For perspective, dolphins can emit short chirps of 220 dB but these are outside the range of human hearing. The lion emits a roar of 115 dB which is sustained and audible 5 miles away, according to the article. Elephants also are capable of 117 dB cries, as are howler monkeys.
Both the shrimp and the cicada use non-vocal vibration to create their sounds. The shrimp uses a "spring-loaded claw" (the spring is muscle). The localized force of one part of the claw hitting the other generates a bubble (this is known as inertial cavitation). When the bubble collapses it generates a shock wave (noise) that stuns fish (prey).$^5$ The noise of frogs is produced as air passes from the lungs through the larynx, amplified by distended air sacs which resonate. Birds can produce up to 135dB (the Mollucan Cockatoo). They generally force air past (membranes and) a specialized organ called the syrinx located at the bottom of the trachea (see the Wikipedia note on bird vocalization).
Micronecta scholtzi, a 2mm-long aquatic insect, is for its size the loudest known animal. It creates a sound of 99.2 dB intensity which (despite being largely lost in transition from water to air) is audible to humans ashore. According to the Wikipedia note it creates this sound by "stridulating a ridge on its penis across corrugations on its abdomen." The area involved is about 50$\mu m$ across. Details of the mechanism are poorly understood. The article's comparison of the sperm whale's 236 (underwater) dB song gives perspective, as a sperm whale can weigh 14 metric tons.
A Common Aspect of Sound Intensity: Cavity Resonance
Descriptive studies of sound-creation by small animals (with the possible exception of the snapping shrimp) do not fully explain why a one-gram bug can make a bigger noise than a lion. Purely vocal methods of larger vertebrates produce sustained noise on the order of 100 dB but the non-vocal instruments of smaller creatures are capable of short bursts of amazing intensity.
It is difficult to generalize but because air sacs are part of many sound-making schemes, cavity resonance probably plays an important role. Like spring-mass systems or RLC circuits, cavities have resonant frequencies at which amplitude of a signal may be increased (the policeman's whistle is a familiar example). Another paper by Bennet-Clark and Young gives a sketch of a theory along these lines. At resonant frequencies the impedance of the instrument falls sharply and instead of being dissipated (generally as heat) the energy emerges as sound.$^6$

$^1$ Bennet-Clark and Young, The Role of the Tymbal in Cicada Sound Production, J. of Experimental Biol. (1995) 198, 1001-1019.
$^{2}$ The frequency of cicadas is variable, mostly on the order of 10kHz but occasionally very low (< 1kHz), mostly due to body size. See this article.
$^3$ Sound--essentially a compression wave--diminishes with distance. So when the Wiki article on noise levels compares noise levels it includes the distance from the object. For example, 100 db (comparable to the cicada) is the level of noise associated with a jack-hammer at 1 meter away.
$^4$ Audible range for humans is roughly 15 Hz-16000 Hz. As mentioned below, the dolphin can emit very intense high-pitched sounds that we don't hear at all, so the analogy to EM waves (higher frequency = higher energy) doesn't help predict perception. See Pfaff and Stecker, Loudness and Frequency Content of Noise in the Animal House, Lab. Animals (1976) 10, 111-117.
$^5$ M. Versluis, B. Schmitz, A von der Heydt & D. Lohse (2000). "How snapping shrimp snap: through cavitating bubbles". Science 289 (5487): 2114–2117.
$^6$ Bennet-Clark and Young, Short Communication, The Scaling of Song Frequency in Cicadas, J. Exp. Biol. 191, 291-294 (1994).

intuitively, I would say that small creatures are not seen easily. therefore they need audible lighthouses to signal to others their location
big creatures don't usually have this need, though some do such as whales which can emit sounds heard hundreds of kilometers away

This is an interesting point, but note that I'm specifically interested in how small animals make loud sounds, not why.

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


text:
SNPs in the Human Genome
I read online that they have found around 10 million single nucleotide polymorphisms (SNPs) across individuals in the human genome [1]. However, this number includes all SNPs found in all people who have been sampled and does not tell us much about SNPs in any single person.
I was wondering instead how many SNPs there are in a single person on average. I had trouble finding trustworthy evidence about this question.

I was wondering how many SNPs there are in a single person on average

A SNP is a polymorphism in the population, it is not a thing a haplotype can carry. Each individual has a given variant for any given of the SNPs (except for cases of sequence deletion).
It is possible though to say how many SNP a diploid individual in between its two haplotypes but I doubt this is where you interest was. Ewens smapling formula gives expectation and distribution under an infinite alleles model, panmictic population and absence of selection.
Other statistics that make sense include the average number of deleterious mutations pre individual or a few other things or how many new mutations a couple transmit to their offspring,... But asking how many SNPs an individual carry on average makes little sense.
Note as @Chris said, by stating 10k SNPs in the human genome, you seem to under-estimate the number of SNPs.
EDIT
In the comments, you further

Would it make more sense to consider a rough minimum and maximum?

The answer is no, it would not make more sense. Consider the definition of SNP by wikipedia

A single nucleotide polymorphism, often abbreviated to SNP (pronounced snip; plural snips), is a variation in a single nucleotide that occurs at a specific position in the genome, where each variation is present to some appreciable degree within a population [My emphasis]

The term population is key here. The concept of SNPs (or of polymorphism to be more general) makes only sense if you can make comparisons. A single individual does not have any polymorphism (to the exception of the one between his two sets of chromosomes).
If we step back and think of different species it might become more intuitive. Think of the number of pairwise differences between two species. It does not make any sense to ask "how many pairwise differences is there between a blue whale?" You need to say "how many pairwise differences is there between a blue whale and a wolf". Similarly, you cannot say "How many SNPs is there 'between a single individual'" (to the exception again of the consideration of the differences between the two sets of chromosomes), you need to consider a group of individuals.

"But asking how many SNPs an individual carry on average makes little sense." It does make sense. Heterozygosity in individuals is a useful proxy for genetic diversity in the population.

We can sure compare the two haplotypes (as I said in the second paragraph). This is not heterozygosity (nor observed heterozygosity) but just an average number of pairwise differences between haplotypes within each individuals. I just doubt this is what the OP was after but maybe I am wrong in the OP's intentions.

My field of expertise is Computer Science. I have started a bioinformatics project which input would be a vcf document of SNPs (of a human individual). I'm interested in the average for practical and optimisation reasons, rather then biologic scientific reasons. But as you stated, it makes no to consider the average. Would it make more sense to consider a rough minimum and maximum?

@BARJ Please see edit. Hope that helps.

There was only one source I was able to find, It stated that each genome contains 1 SNP every 1000bp. (Take a look here). However I have no idea if this source is reliable

Your number is too low, the 1000 Genomes project lists roughly 15 Mio SNPs (see reference 1). To find out how much SNPs humans have on average (this depends of course on populations, where this can differ), you often find that on average 1 in 1000 nucleotides is altered if you compare two human genomes (or the other way round: They are 99.9% identical).
The problem with this number is that it is quite old and can be traced back to a publication from 1991 (see reference 2), which compared 75.000 sequences nucleotides from 49 loci. Since this was before the complete sequence of the human genome was known, I would treat this number with some caution.
The newest number I found on this is from publication of the human genome. They estimate the number a little bit lower, at about 1 in 1300 bases (see reference 3).
What could be done with the data from the 1000 Genomes Project is to download the data from the individual samples, map it against the reference genome and see, how many SNPs per individual occur. I am not sure if nobody did that or if I simply overlooked that.
Based on this data there are somewhere between 2,3 and 3 million SNPs (1:1000 or 1:1300 respectively) present in each human genome. According to the 1000 Genomes project (reference 1), the rate of newly occurring SNPs is $1\times 10^{-8}$, meaning that there are between 20 and 30 new SNPs occuring per generation.
References:

A map of human genome variation from population-scale sequencing
Low nucleotide diversity in man.
Initial sequencing and analysis of the human genome.

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


text:
Improving contrast between dot and paper in dot blot
Currently using dot blot to attempt to determine if a serum contains antibodies for some reagents I am testing.

I pipetted samples as 10-5ul dots on whatman paper.
Incubation steps were for 1 hour with light shaking.
Blocking solution is composed of 1mg/ml BSA in PBS.
Wash steps were 3X PBS for 10 minute each.
Solution for incubating the blot in primary antibody was 1ml of serum per 9ml of blocking solution.
Solution for incubating the blot in secondary antibody was 100ul of IgG in 10ml of blocking solution.
Then a 1:10 DAB substrate mix was used to develop the blot. Products used for the test listed below.

Currently, the whatman paper is a light brown with vague outlines of the dots where the samples were pipetted. Samples that should trigger more antibodies than others (like serum positive control) tend to be a bit darker, but it's not nearly as clear as we'd hope for.
I have also blotted the IgG which usually forms a darker smudge, rather than a clean, dark dot. Does anyone have any advice on how to improve the developing process? I have also tried using TBS, adding Tween to the PBS or TBS as well as trying nitrocellulose instead, but none of these have impacted the results.
Reagents:

secondary antibody
DAB kit

In the absence of another answer, I'll transition my comments to an answer.

Please label your images.
Both an Abcam guide and a Thermo troubleshooting document suggest using a kit or DAB protocol including metals such as nickel or cobalt to intensify signal. I notice that the kit spec that you link doesn't seem to have these. Have you tried different DAB kits?
They also recommend carefully monitoring staining over time under a scope and removing as early as possible. This may help to reduce background.
I'd try a few different combinations of conditions, stain + wash times, to see if any have an effect. I don't have a great sense of where your protocol came from, I'd suggest clicking through those documents above or searching the literature to find more DAB protocols that you might try.

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


text:
Help troubleshoot multiple Bands on gel (Conventional PCR)
I designed sequencing primers (Sanger) for MPL gene. The length of the product is 543 bp. Checked the parameters of primers with Multiple primer analyzer (Thermo), NCBI- Primer Blast, Oligo evaluator (Sigma). Checked for specificity of primers with software ( Ncbi- primer blast, Genome tester, UCSC genome browser Insilico PCR). All the parameters were within the range specified. No self complementarity or hairpins/dimers.
On amplifying it and running a gel, multiple bands were seen on the gel (@1200bp, 300 bp, 400bp). There was no band corresponding to the 543bp size. ran a gradient PCR. used PCR additives. I still see multiple bands. any advice on trouble shooting ?
Protocols
DNA template
Extracted use spin-column method.
primer design
Primers designed for MPL gene on chromosome 1.
PCR protocol

26ul of platinum master mix (hot start polymerase)
2+2ul of primer (forward and reverse)
5ul of DNA extracted from peripheral blood
15ul of nuclease free water
Cycling
Initial denaturation 94 for 10 min
32 cycles of:
denaturation - 94 for 1 min
annealing - 50/52/54/56/58/60 for 1 min (GRADIENT PCR)
Extension - 72 for 1 min
final denaturation - 72 for 10 min hold -4 degrees

I didn't add mgcl2 separately. it was one of the ingredients in the master mix.
When i used DMSO, it was 1.5ul.

what is your template? see also here. Can you show complete PCR protocol including e.g. [MgCl2]?

DNA template. Extracted use spin-column method. Primers designed for MPL gene on chromosome 1.
PCR protocol
26ul of platinum master mix(hot start polymerase)
2+2ul of primer (forward and reverse)
5ul of DNA extracted from peripheral blood
15ul of nuclease free water
Initial denaturation 94 for 10 min
32 cycles of
denaturation - 94 for 1 min
annealing - 50/52/54/56/58/60 for 1 min (GRADIENT PCR)
Extension - 72 for 1 min
final denaturation - 72 for 10 min
hold -4 degrees
I didn't add mgcl2 separately. it was one of the ingredients in the master mix. When i used DMSO, it was 1.5ul

thanks- added to your question. It would help potentially to have a positive control primer set (that you know to work) to confirm that the primers are the issue rather than the DNA or the master mix.

Will do . Thank you

It could be loads of things. When I've worked on these issues (bioinformatics) it's always been complex primer design frameworks, specifically using data engineering practices for metagenomic primer design (proprietary contract - can't talk about it). However, it's a multi-pronged process. Here's the basics that should help you. The wet-lab talked through the other issues, i.e. where there was more to molecular biology than bioinformatics, here's a summary of the things usually done.
Primer Design
Even though tools gave the green light, sometimes subtle issues slip through. This stuff isn't really for this site in any case BUT ....

Specificity Check:
Reassess primer specificity using updated databases like NCBI Primer-BLAST. Small genome updates can reveal unintended matches.
Annealing Sites:
Map your primers against the MPL gene region using a UCSC Genome Browser or Insilico PCR tool to ensure no off-target regions align.

Template DNA Quality
The template can be a sneaky culprit!

DNA Integrity:
Run your extracted DNA on a gel to check for degradation or contamination. Smearing indicates degraded DNA, which affects amplification.
Contaminants:
Residual proteins, salts, or phenol from DNA prep can inhibit PCR. Purify your DNA again with a column-based cleanup kit or ethanol precipitation.

PCR Conditions
Optimization might save the day.

Annealing Temperature:
Gradient PCR was a great step! If still no luck, lower the annealing temperature slightly below the primer Tm. This may reduce nonspecific binding.
Extension Time:
Unexpected bands could result from overly long extension times, causing nonspecific fragments. For 543 bp, 30 seconds at 72°C should suffice.
Additives:
PCR enhancers like DMSO (2–5%), betaine, or BSA can sometimes reduce off-target products. You mentioned trying additives—ensure you tested them individually.

Reaction Mix Checks
The mix can make or break PCR success.

MgCl₂ Concentration:
Too much magnesium increases nonspecific amplification. Start with 1.5 mM and adjust incrementally.
Primer Concentration:
Use equimolar primers at 0.2–0.5 µM. Too much primer can promote off-target amplification.

Technical Enhancements
When the basics fail, advanced tweaks might help.

Nested PCR:
Use a second set of internal primers to amplify a specific region within the initial product.
Touchdown PCR:
Gradually reduce the annealing temperature over the first 10–15 cycles to enhance specificity.

Band-Specific Checks
Your bands don’t include the expected 543 bp product.

Gel Issues:
Confirm your DNA ladder is correct, and ensure your gel resolves the range you’re amplifying. Misinterpretation of band sizes is more common than you'd think.
Unexpected Bands:

@1200 bp: Check for template contamination or nonspecific binding far from the target site.
@300 bp and 400 bp: These might be nonspecific primer-dimers or truncated products. Reducing primer concentration and adding DMSO could help.

Sequencing Validation
If none of these branches bear fruit, try sequencing the most prominent band to identify what is amplifying. This will give insight into the template or off-target regions involved.
For troubleshooting PCR issues like yours, the following resources provide insights and guidance:
Primer Design and PCR Optimization: Sigma-Aldrich details best practices for primer design and optimization, useful for minimizing off-target effects and enhancing PCR specificity.

thank you so much for taking out time to explain.

Primer Design- check specificity with both NCBI primer blast and UCSC genome browser. Very specific. I also tried genome tester for specificity.
Extension time was kept at 72 for 30 sec and 72 for 1 min. PCR additives (DMSO alone, BSA alone, DMSO+BSA) were used.
3.Wil adjust mgcl2 concentration and check
Will try touch down PCR and see the results
5.DNA was purified to remove the contamination variable
Planning to give the amplicon for sequence and see the results
Thanks again

Thanks @Bhavani "accepts" for a post are always more welcome than a note of thanks.

If you’re consistently observing multiple bands and no product at the expected size, it suggests that your PCR reaction may not be specific enough, or other factors could be interfering with amplification. I would suggest to begin troubleshooting with 1. Template quality; 2. re-design primers and check if the primer preparation or resuspension is in good condition; 3. perform gradient PCT and optimize conditions of PCR; 4. Adjust MgCl2 concentration; 5. Prefer to use hot-start Polymerase; 6. try two step PCR; 7. gel extract the faint band and use it for further amplification; 8. redesign primers with alternate sites

why was this answer downvoted? these are all reasonable suggestions.

@MaximilianPress User posted several answers in quick succession which were AI generated. This of two that are still up. (AI is getting better, even the medical answers, which used to be very easy to detect, are much more reasonable. )

I see, thank you.

Thank you. I used Hot start polymerase. I am planning to redesign primers.


text:
Anatomy of mature juice vesicles in hesperidium fruit?
What is the cellular structure of mature juice vesicles?
In a mature juice vesicle what cell types are present, how are they arranged and does this differ between species?

Can you provide any references describing what you mean? Why do you want to know? Editing your answer to add more information may make it easier to answer.

Sorry can’t find any references

I'd suggest taking a look at this paper linked through the wikipedia page. It has a variety of information about the structure and distribution of juice vesicles across different types of fruit e.g.:

The distribution of vesicles among segments
within the same fruit was similar (fig. 3). The un-
attached terminal ends of all vesicles exhibit a dis-
tinct orientation within the carpel; these terminals
point slightly toward the stylar end of the fruit. The
seeds within the segment are oriented so that the
chalazal end extends toward the stem end and the
micropylar end extends toward the stylar end of the
fruit.

Most citrus fruit possess roughly 130-400 ves-
icles per segment (table 1). Pummelo fruits contain
the most vesicles per fruit, followed in order of
decreasing vesicles per fruit by grapefruit, citron,
sweet orange, meyer lemon, papeda, lemon, sour
orange, mandarin, Satsuma mandarin, Citrus
miaray, trifoliate orange, Gabon cherty-orange, and
kumquat

etc. You should be able to answer most of your questions by reading that fully, but if there are follow up questions that come up, you should feel free to post another question.

What is the nature of the fluid filled cavity?                                            Is it a coenocyte? A schizogenous cavity? Perhaps a lysogenous cavity?

@Harrychink did you read the paper?

Indeed I did read the paper

If you are interested in the histology, I advise you to look on the first page at the section beginning with the sentence "To
summarize these past studies, juice vesicles are initiated just before or during anthesis as multicellular primordial bulges on the locular side of the endocarp surface usually on the radial wall." See also the cited references.

I am still unable to find the nature of the cavity

@Harrychink This is written quite clearly in there, I'm not sure what the issue is: The mature vesicles are elliptical multicellular sacs enclosed by a membrane, usually containing a minute oil gland in their center and connected to the segment wall by a multicellular stalk. What about that doesn't answer your question when you read the paper? There's a lot more information there about its development, but at some point you have to sit down and read closely for the details you're interested in, I'm going to reproduce them all here for you.

What types of cell compose the vesicle?

What is the nature of the central cavity

I still do not know what cells compose the vesicle or what the nature of the central cavity is.

@Harrychink I have given you a variety of paths to follow to answer your question, and I've put as much effort as I care to into this answer given that you have put very little effort into your own research. I know that you're dissatisfied that I'm not going and copying everything here to satisfy you, and you're free to exercise your various options to express that dissatisfaction.

Please provide a source explaining the nature of the central cavity and/or the types of cell present in the mature vesicle

I am having trouble accessing the articles


text:
When do growth curves "reach maximum"?
I have been reading about growth curves, specifically those with upper and lower asymptotes, which have been asked about here before. See also Tjørve & Tjørve (2017).
In these models, is there a generally accepted value for when the outcome reaches the maximum value? Since it approaches an asymptote, it will never reach it, so have biologists established a value at which they can talk about it "reaching maximum"? E.g. at 95%, 99% of the upper asymptote?

In what context? in what application? Are you talking about partitioning growth phases in mathematical models, or growing a bucket of cells, checking the OD600, and saying "ok now it's ready"? Your citation describes work on mathematical growth models, but it does not seem to talk much about saturation. Most of the time we are not working in growing logistic curves into saturated systems (with some exceptions). Usually you harvest stuff mid-log-phase or you have a stably saturated system, so it's kind of a moot point.

@MaximilianPress I am not working on biological experiments, but rather learning about them for application in a different context and wanting to read about how biologists have treated this. I suppose my answer is closest to "saying 'ok now it's ready,'" but I don't know what an OD600 is, or what saturation is in this context.

OD600 is the standard experimental measurement of optical density of a microbial/cell culture, which is the main measurement that people use for growth in a laboratory context. Saturation of a culture is the same thing as your "maximum". But cultures at saturation are usually nasty to work with, so people generally use mid-log phase (which has standard OD600 values for different types of cells). However a stable natural ecosystem is usually "saturated" all the time (or cyclically varying around saturation). So it really does change depending on the context!


text:
Chimera generation rate between mouse and other animals
I have a question about the chimera generation rate of the mouse compared with other animals.
Before asking the question, I need to define the following terms:
ES cells: Embryonic stem cells
The procedure of generating chimera mice and other chimera animals should be similar, where I am supposed to do genetic modification, such as gene knockout, on the ES cells and implant them back into the animals' blastocysts. However, I found the following statement interesting:

The mice's chimera generation rate is higher than that of other animals.

and

Where chimera production with ESL cells has been attempted, both the rates and the levels of chimerism are typically much lower than found with murine ES cells."

From Gardner, RL (2014) Pluripotent Stem Cells from Vertebrate Embryos: Present Perspective and Future Challenges.
I am not sure why that is the case. Could anyone kindly give some directions? Thank you.

where did the statement come from? Did it provide a reference?

"Where chimera production with ESL cells has been attempted, both the rates and the levels of chimerism are typically much lower than found with murine ES cells." From Pluripotent Stem Cells from Vertebrate Embryos: Present Perspective and Future Challenges. ESL cells from other animals are very, very similar to murine stem cells. The only difference is the higher nuclear-cytoplasm ratio compared with the murine ES cells.

I am editing your question to include the relevant quotation and citation


text:
What is the difference between ‘classical’ and ‘non-classical’ pathogen resistance genes in plants?
I have stumbled across a mention of classical resistance genes against pests in plants, however the classification seems a bit vague.
What would be classified as classical resistance genes and what as non-classical in plants?
Edit:
Found it here:

'For example, the identification of classical plant resistant genes in
Arabidopsis and other model dicots facilitated the successful cloning
of multiple wheat rust resistant genes (Ellis et al., 2014; Wulff and
Moscou, 2014).'

Schwessinger, Benjamin, et al. "Focus issue on plant immunity: from
model systems to crop species." Frontiers in plant science 6 (2015):
195.

Where have you stumbled across the mention, and what was said about it?

@BryanKrause i originally encountered it at a conference but then also found it here:
Schwessinger, Benjamin, et al. "Focus issue on plant immunity: from model systems to crop species." Frontiers in plant science 6 (2015): 195.
'For example, the identification of classical plant resistant genes in Arabidopsis and other model dicots facilitated the successful cloning of multiple wheat rust resistant genes (Ellis et al., 2014; Wulff and Moscou, 2014). '

I edited to reflect that the reference is to classic genes rather than to classic immunity.
Note that this is not a formal definition but rather an informal way of talking about the state of the scientific literature: "classic" or "classical" is a way of referring to the first-described, standard, or most familiar example of a phenomenon.
The term "classic" has no biological salience, but rather has salience for the history of science and what is in textbooks (e.g. the necessarily subjective human perception of nature).
See e.g. this blog post discussing this loose way of writing.


text:
MSA cluster and MSA depth
I was reading the AlphaFold paper and had difficulty with a couple of terms introduced in the main text of the paper. I asked ChatGPT what these were but I'm not sure that it's accurate.
I had a hard time finding the definitions of an MSA (multiple sequence alignment) cluster and MSA depth. GPT-4 explains that an MSA cluster is a subset of sequences from an overall MSA that are closely related to each other, which seems to be simply the results from clustering analysis on MSA. GPT-4 also defines the MSA depth as the number of sequences in MSA. However, I want to make sure that these definitions are correct and are not just hallucinations from GPT-4.

Please finish reading the [Tour] and the Help on asking questions. Don't use non-standard abbreviations without definition. I have run MSA for years and never heard of GPT-4. Sure, I may be old and out of touch, but very few list members will have heard of it either. Say what it is and provide a link. If you can't find standard definitions for terms, say on Wikipedia, it is likely that there won't be any. Something like "cluster" and "depth" would seem so general that I doubt whether there can be any "correct" definition of them. What are you trying to do that you care?

Where did these terms come from? Are you just reading GPT-4 outputs, or did you find the terms and ask GPT-4 to explain them? If the former, I wouldn't trust the chatbot to understand differences between local/global alignment (see other answer), and thus it is probably mixing a lot of apples and oranges in a nonhelpful way. If the latter, it would be much more useful to see the original source, which we might be able to explain.

Hi @Maximilian Press, thanks for the reply and sorry for not providing more context. I was using AlphaFold and one of the parameters was for specifying the number of MSA clusters, I then asked GPT-4 for its definition. AlphaFold was introduced in this paper for protein structure prediction and is also where I saw the term "MSA depth": https://www.nature.com/articles/s41586-021-03819-2

@Jack: thanks for following up, I edited your question and provided an answer below.

I'd really recommend staying away from ChatGPT and similar for learning for now; these tools are really great at creating plausible text, but they can't cite sources so you can't follow up, and they have no concept of what is "correct" or not, they are just using a statistical model to predict which words should come next in a sequence. That means they can sometimes do a good job of summarizing content that is repeated over and over again in their training set, but also that sometimes it gets mixed up and confuses concepts, misses a negative, or confidently states something absolutely wrong.

For example, if the training data includes phrases like "People think cats are dogs. They are wrong", ChatGPT learns that "cats are dogs" is a reasonable pattern and if you ask it to tell you about cats and dogs it may confidently spit out "Cats are dogs" from that training data.

AlphaFold defines these measures in the supplementary information of the paper, as referenced in the main text.
Generally speaking, a lot of information for these highly condensed papers goes into the supplementary information, and that's the first place to look for more explanation.
MSA depth
Figure S10 legend:

MSA depth is computed by counting the number of non-gap residues for each position in the MSA (using the Neff weighting scheme with a threshold of 80% identity measured on the region that is non-gap in either sequence) and taking the median across residues.

This is not a standard measure, just to be clear.
MSA clustering
There is a section "1.2.7 MSA clustering" in the paper supplement that describes the clustering procedure at some length.
MSA clustering is a fairly standard thing to do, but there are many possible algorithms for deriving clusters, and a large family of implementations of each algorithm. I suggest looking into the field of phylogenetic inference for other examples.


text:
Ecosystem naming discrepancies between LANDFIRE ESP and GAP/LANDFIRE National Terrestrial Ecosystems 2011 Datasets
first post here! I am working on a project using the LANDFIRE ESP (environmental site potential) categories, and saw that on NatureServe Explorer I could find broader classifications for the categories provided in the ESP data like this example for the rocky mountain subalpine mesic-wet spruce fir forest and woodland:

I found a table with all of these different levels of classification from the GAP/LANDFIRE National Terrestrial Ecosystems 2011 Dataset, but some of the ecosystem names from LANDFIRE ESP data do not match with any from the GAP dataset. for example, if you search for ecosystems with 'riparian' in the name you get pretty different results from both sets:
(GAP Dataset):
array(['northwestern great plains riparian',
       'western great plains riparian woodland and shrubland',
       'central appalachian riparian   forest modifier',
       'central interior and appalachian riparian systems',
       'ozark ouachita riparian',
       'south central interior small stream and riparian',
       'southeastern great plains riparian forest',
       'mississippi river floodplain and riparian forest',
       'mississippi river riparian forest',
       'southern piedmont small floodplain and riparian forest',
       'edwards plateau riparian',
       'columbia basin foothill riparian woodland and shrubland',
       'great basin foothill and lower montane riparian woodland and shrubland',
       'northern rocky mountain lower montane riparian woodland and shrubland',
       'rocky mountain lower montane riparian woodland and shrubland',
       'rocky mountain montane riparian systems',
       'rocky mountain subalpine montane riparian woodland',
       'north pacific lowland riparian forest and shrubland',
       'north pacific montane riparian woodland and shrubland',
       'california central valley riparian woodland and shrubland',
       'mediterranean california foothill and lower montane riparian woodland',
       'mediterranean california serpentine foothill and lower montane riparian woodland and seep',
       'north american warm desert lower montane riparian woodland and shrubland',
       'north american warm desert riparian systems',
       'north american warm desert riparian woodland and shrubland',
       'tamaulipan riparian systems',
       'rocky mountain subalpine montane riparian shrubland',
       'north american warm desert riparian mesquite bosque',
       'introduced riparian and wetland vegetation'], dtype=object)

(LANDFIRE dataset):
array(['inter mountain basins montane riparian systems',
       'north pacific lowland riparian forest and shrubland',
       'north pacific montane riparian woodland and shrubland',
       'rocky mountain montane riparian systems',
       'rocky mountain subalpine/upper montane riparian systems',
       'california montane riparian systems',
       'california central valley riparian woodland and shrubland',
       'north american warm desert riparian systems',
       'central interior and appalachian riparian systems',
       'gulf and atlantic coastal plain small stream riparian systems',
       'tamaulipan riparian systems', 'edwards plateau riparian'],
      dtype=object)

Any clues on this discrepancy or where I could find a lookup table that better matches the LANDFIRE ESP ecosystem categories? Thank you!!


text:
How do we formulate the mutational load for "junk DNA"?
Question(s)
Based on Joe Felsenstein's textbook, I was trying to formulate the mutational load for the majority of eukaryotic genomes that are junk DNA ($L_{most\_of\_genome}$). (See background section for more details and relevant quotes.)
Extrapolating from what Joe writes about non-junk loci and removing one simplifying assumption (Muller-Haldane), I believe that this should be equal to the allele frequency of each locus (simplifying here to the average across these loci, $q_e$) multiplied by whatever infinitesimal selection coefficient each locus has ($s$, on average), summed across all loci ($N_{positions}$):
$L_{most\_of\_genome} = N_{positions}q_{e}s$
(Ideally we would sum this across individual estimates of $q_e$ and $s$ for each locus, but that's obviously impractical here so we use the mean across loci.)
here are some closely related questions:
1) Is the above a reasonable formulation for $L_{most\_of\_genome}$? If not, what would be? (I can readily imagine that a lot of assumptions start breaking with hundreds of millions of positions etc.)
2) If it is a reasonable formulation, what are "reasonable" parameter ranges for $s$ and $q_{e}$ of "deleterious" nearly-neutral mutants for this majority of the genome? (For example, we might say that $s$ can take values less than the inverse of the population size.)
Note that I'm talking about junk DNA, not non-coding DNA. We know a fair amount about mutational load of (non-junk) non-coding DNA.
Possible problems with this
Let's plug in some values here, let's say across a billion loci with very small selection coefficients of $10^{-10}$ and $q_e$ equal to the mutation rate $u$ of $10^{-8}$ (e.g. all deleterious variants are new mutations), I can write:
$L_{most\_of\_genome} = N_{positions}q_{e}s = (10^9)(10^{-8})(10^{-10}) = 10^{-9}$
This is a subset of the overall mutational load. For these parameter values that seems plausible, but if we take seriously Joe's argument (see below) that many of these loci will fix deleterious variants, e.g. $q_e \approxeq 1.0$, then this value could get quite high.
For example, here's a different calculation assuming that $q_e \approxeq 0.1$:
$L_{most\_of\_genome} = N_{positions}q_{e}s = (10^9)(10^{-1})(10^{-10}) = 0.01$
That's a non-trivial load!
In fact, asymptotically we expect that every locus will fix slightly deleterious variants. In this case of universally fixed slightly deleterious variants, this load is closer to $10^{-1}$ for the above example. For conifers and axolotls with >10Gbp genomes, we would then expect the load just from junk DNA to be greater than 1 for these parameter values, e.g. dead. Joe has a section "Why aren't we all dead?" but it doesn't directly address this, and it uses principally verbal arguments.
Background
I am refreshing my knowledge of the mutational load by reading the section of Joe Felsenstein's book on the subject (pp. 152-158), and I am now remembering something I struggled with while taking the class he taught on the subject.
Joe writes in the section "Weak selection and mutational load":

As the mutational load is said to be a function of the mutation rate, but not the selection coefficient, it is natural to wonder how a very weak selection could impose a load. Surely the Haldane-Muller principle cannot hold all the way to $s = 0$. Of course, it does not. In the haploid case, the mutational equilibrium gene frequency $q_{e} = \frac{u}{s}$ is only correct if $u < s$, otherwise the only equilibrium of the system (III-21) is $q_{e} = 1$. If $u \geq s$, so that $q_{e} = 1$, the load is $L = q_{e}s = s$, so that as we consider cases with progressively smaller values of $s$, the load will remain $u$ until $s = u$, then below that point the load will smoothly decline to zero as s declines.

(Where $s$ is the selection coefficient for a mutant allele, $q_{e}$ is the mutant allele frequency, and $u$ is the mutation rate at that locus.)
Joe then talks about some other stuff and concludes:

The load will be a simple function of $u$ unless $s$ is so small that it is not substantially greater than $u$. Below that point the load will decline to zero as $s$ does.

This last sentence (my emphasis) is not obvious to me based on what I've read.
I am having trouble following this logic. Here is what I understand of it:
1) Muller-Haldane asserts that $s$ has very little impact on $L$, such that to a close approximation $L \approxeq u$ (for a haploid; shown on p.153 and elsewhere), in other words the load is mostly unrelated to $s$ because $s$ only has an effect if $q_{e}$ is not close to zero, which is rarely true for new mutants.
2) At very low $s$ there is a higher chance that the mutant will go to fixation (e.g. reach the $q_{e} = 1$ equilibrium) due to the lesser action of selection.
3) From (2), I think that this means that $s$ is then part of the load formulation again at low $s$.
4) So as $s$ goes to zero the contribution of such variants still goes to zero.
5) Joe also uses the C value paradox/junk DNA/onion principle to argue that the mutational load isn't affected by most of the genome for large genomes e.g. human. But that argument seems to say that we just shouldn't worry about these regions of the genome because their selection coefficients are in the region of negligibility close to zero.
But these are not formally worked out here in the book. Can anyone formulate an expression or approximation for exactly how we can treat the load associated with very small selection coefficients that are found in most of a large eukaryotic genome?

I ended up writing directly to Joe after not getting an outside answer here. I won't directly quote him without his permission, but to sum up, he wrote the following:

This paper (among others) gives an numerical treatment of different selection coefficients in small populations, which effectively means loci that are not under selection but still have coefficients (which I am defining as junk DNA in my question). It shows a smooth decline (Figure 1) with decreasing $s$ and population size, indicating that my instinct was correct that there exists a load for such "junk" DNA.

Figure 1 from Kimura, Maruyama, and Crow 1963

Joe was rather skeptical that such loads were actually significant for evolution, except in the case of very small populations. I think that this also agrees with my intuition, but as an important practical note it's important to not get too excited about junk DNA from a biological standpoint (see e.g. Graur et al. 2013).


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

As far as I know, many vespids have very good orientation, which is used to find food. If they find something with sugar like ripe fallen apples, they will start by scouting and mapping the area, and then they can fly back to base and to the food area again. so, they recognize their home and food places very well. to disorient them, I 'd figure you can test it out... mark him and take him a mile away, i think it would be enough, 10 would more probably be ok.

There is strong evidence that wasps can recognize color patterns of other wasps. Whether that extends to humans I don't think is known but given some remarkable work on bee learning, I would not be surprised. https://www.youtube.com/watch?v=rx7lEBE-wJE

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

The aforementioned studies should be linked in the answer.

@G.Shepherd, do you have articles on this? I tried to google it but without success :(


text:
Evolution of umbilical cord and reason of its elongation
To answer a question myself, recently I've read that

Years and years ago, a long umbilical cord enabled a woman to grasp her baby after birth and run away from predators"

Update:
$Question:$ How umbilical cord is evolved and what's the reason behind it's elongation?

There is at least one position that supports this claim:

So why 61 cm? Umbilical cords of whales, porpoises, goats and other
  mammals are rela- tively shorter than the human cord. Walker and Rye
  of Cambridge surmised in the British Medical Journal in 1960 that
  prehistoric humans evolved length for protection. Nature's purpose was
  to allow the mother to pick up the newborn without disturbing the
  placenta. The event of breast feeding would then separate the placenta
  - an event which could attract predators. Having the fetus in tow would allow escape for mother and child.

(title: Silent Risk, auth.:Jason H. Collins). Well, right now I feel confused a bit...

Of course.. thats a folk tale.. Anyways, you do know what umbilical cord is really for, don't you?

Ok, maybe I should ask another question - why is this so long?

+1 for the sense of humor; I haven't seen any question of such comical kind here recently.

:)... is it malice-exchange or science-exchange? :( could you, guys, please help me in either improving my answer or explaining why it's stupid?

Sorry, but this is bullshit. Anyone who has been at a birth (or given) will know that women will do a lot of things afterwards, but running is usually none of them.

@Lili: Better Now?

:-) better (even more than simple "better") - thank you!

I do believe that this is not a HW question and has scope to be answered

The woman running bit is obviously a myth but that is genius.. Other than that the length of the umbilical cord has been found to be highly variable depending on each individual. Characterizing it as just long would therefore not be right. According to Wikipedia,

The umbilical cord in a full term neonate is usually about 50
  centimeters (20 in) long and about 2 centimeters (0.75 in) in diameter
  (reference).

Some complications during birth are

A number of abnormalities can affect the umbilical cord. The cord may
  be too long or too short. It may connect improperly to the placenta or
  become knotted or compressed (reference).

Why does it become too long has been associated with these factors.

Long umbilical cords, defined as total length over 70 cm, have been
  significantly associated with:
Maternal factors:
Systemic diseases. Delivery complications. Increased maternal age.
Fetal factors:
Non-reassuring fetal status during labor. Respiratory distress. Vertex
  presentation Cord entanglement. Fetal anomalies. Male sex. Increased
  birth weight.
Placental features:
Increased placental weight. Right-twisted cords. Hyper-coiled cords.
  True knots (reference).

In conclusion, length of the umbilical cord has an average as mentioned before and being too long or short can lead to complications during birth. Regarding evolution of the cord, you could read this discussion.


text:
Marine invertebrate San Juan Islands, WA, USA
I noticed a green-colored marine arthropod in harbor in the US San Juan Islands (early July 2022, around noon), specifically Haro Strait, and took several pictures from the dock.
The bug was approximately 1 centimeter in length. I am guessing that it is algivorous (or algivore-vorous) based on the green color. It was in constant motion in sunlight, possibly hunting though it wasn't clear what it was going after (though the area was very algae-rich).
Apologies for the low quality images, some of these are stills from a movie (I had issues focusing because it was underwater and it was swimming around quite quickly).
Google image search was not very helpful, and neither was iNaturalist.
Update 2024
I have continued observing these inverts in the same location. I saw one in mid-September (two months later), and it was notably larger, perhaps 2cm. That suggests significant annual growth.
While I did not get a picture, I also clarified something observable in one of my pictures: the invert appears to habitually swim with its ventral side up (belly up). That explains something about the arrangement of the legs and the complex-looking carapace.

Looks very strongly Isopoda to me. I have no idea on species though. Looks like most of the species (~5000ish I think) on Wikipedia are stubs or non-existent pages.

Thanks to the tip from @bob1 that it looks like an isopod, I was able to google "Puget Sound isopod" which found me this Reddit post, where an expert randomly chimed in identifying this as probably either a kelp isopod or an eelgrass isopod (possibly both are present there). I am leaning towards eelgrass isopod

kelp isopod

eelgrass isopod
A more complete species description of eelgrass isopod is present here at the Invertebrates of the Salish Sea site (Haro Strait is in the Salish Sea).


text:
Compute a melting temperature in viennaRNA?
Posting here to get views, but may be more appropriate for bioinformatics or chemistry SE.
There are a variety of utilities such as biopython or primer3 that compute melting temperatures.
However, tools for performing thermodynamic calculations on oligonucleotides should in theory be able to do this. ViennaRNA is one such popular tool, which although it has famously difficult documentation, I can't find anything there about melting temps.
Frankly, I would trust Vienna more than some of the other tools, and I'd like to compute all my oligo stuff in one place.
It seems like I should be able to back-calculate a melting temperature from a delta G along with a series of parameters about concentrations etc. I found some equations that solve for Tm in terms of enthalpy and entropy, but I'm not sure how to get those values from Vienna either, which prefers to just give you the overall deltaG.
Can anyone clarify how to compute from ViennaRNA:

Enthalpy of folding
Entropy of folding
Tm

For context, I am mostly interested in using ViennaRNA's RNAlib via the Python API.

Have you seen this table of programs in ViennaRNA? I don't know exactly which one should be used, but there seems to be several that calculate interaction energy between two RNAs. For melting temperature, you can use $T_\mathrm{M} = \Delta H^\circ/(\Delta S^\circ + R \ln C_T)$. However, I am slightly worried if that is the best approach as you cannot change the sodium concentration in ViennaRNA, which

significantly affects the melting temperature.

thanks @Domen, I clarified in the ticket now that I am using the RNAlib API rather than vienna programs. I would accept using one of those binaries if needed (though it's clunkier than I'd like), but I'll return again to the fact that I'm not sure how to compute either $\Delta H$ (enthalpy) or $\Delta S$ (entropy). None of those programs seem to do that, and searching the API docs or the viennarna docs leaves me empty-handed.

Just FYI, biopython is now at version 1.81. The docs you linked to were from 1.76 (I'm not sure if this API has changed since 2019 or not). You can always find the latest version of that page here, and it'll show you the specific version in the lower left.


text:
Antibody structural determinants of epitope size
I am curious whether there are structural correlates in antibodies that relate not to epitope sequence but to epitope size. Specifically, I imagine that the antibody-epitope interface size is constrained to some extent by the structure of the variable regions that confer specificity, which likely do not have any direct interaction with the epitope.
Put another way, taking this illustration below from this educational site, it seems to me that the $V_{H}$ and $V_{L}$ portions (including hypervariable regions) that are not necessarily part of the orange "hand" interacting with the antigen, but rather lead to the gross shape of this "hand", can significantly affect the size of the epitope independently of the epitope linear sequence (assuming a linear epitope).

I'm aware that epitope prediction is an extremely difficult computational task, so presumably there is not a straightforward structural encoding of epitope size. Nonetheless, I'm curious if anything is known.
I found this question pointing to a paper that indicates substantial variation in the size of the epitope, leading me to believe that such an epitope size-antibody conformation relationship might be possible. This possibly suspect company page indicates some very small possible epitope of 5 amino acids or less, which would suggest a high degree of constraint in the interface if true.

Slightly OT, but why do you think that page is "possibly suspect"?

@MattDMo It's a marketing page without supporting data, i.e. "trust us". I don't personally doubt that it's more or less true, but I've noticed that SE Biology tends to be pretty critical of such sources.

I agree. I used to work at an antibody company, and we had tons of internal data that we'd never release, because it's proprietary and gave us a business advantage. No so good for an open-access site like this, but good for the customers who believed the marketing (which was for the most part rather accurate, I must say).


text:
Why do some bad traits evolve, and good ones don't?
If a trait would be advantageous to an organism then why hasn't it evolved yet?
Conversely, if a trait is not advantageous or mildly disadvantageous, why does it exist?
In other words why does evolution not make the organism more "perfect"?

This is a general question that would be applicable for any kind of trait. Please keep the answers precise and scientific.
Read this meta post for more information: Questions asking for evolutionary reasons

A classical article on the subject: The spandrels of san marco and the panglossian paradigm

Technically, i found that to be a very muddled, vague question, 1/ with no examples to illustrate an example trait. 2/ deducting that evolution follows a retrograde course by encourageing negative traits. 3/ why is it making an animal NOT more perfect... is too vague a concept to talk about and it caps off the previous vague statements with a nonsensical culmination which would have greatly benifited from trait examples, more perfect/less perfect examples, and statements which generalize trait selection which is not generally true.

there are no bad traits that are not related to another good one. please give some examples.

The answers to this question are very good and I think it useful as a portmanteau reference for closing questions related to it. But I have always been put off by the title. Most questions are from people playing God, asking why such and such a thing they think advantageous has not evolved. The evolution of bad traits (sickle cell anaemia etc.) is a quite separate question that can have a much clearer and more objective answer. Could we do something about this?

During the process of selection, individuals having disadvantageous traits are weeded out. If the selection pressure isn't strong enough then mildly disadvantageous traits will continue to persist in the population.
So the reasons for why a trait is not evolved even though it may be advantageous to the organism, are:

There is no strong pressure against the individuals not having that trait. In other words lack of the trait is not strongly disadvantageous.
The trait might have a tradeoff which essentially makes no change to the overall fitness.
Not enough time has elapsed for an advantageous mutation to get fixed. This doesn't mean that the mutation had not happened yet. It means that the situation that rendered the mutation advantageous had arisen quite recently. Consider the example of a mutation that confers resistance against a disease. The mutation wouldn't be advantageous if there was no disease. When a population encounters the disease for the first time, then the mutation would gain advantage but it will take some time to establish itself in the population.
The rate for that specific mutation is low and therefore it has not yet happened. Mutation rates are not uniform across the genome and certain regions acquire mutations faster than the others. Irrespective of that, if the overall mutation rate is low then it would take a lot of time for a mutation to arise and until then its effects cannot be seen.
The specific trait is too genetically distant: it cannot be the result of a mutation in a single generation. It might, conceivably, develop after successive generations, each mutating farther, but if the intervening mutations are at too much of a disadvantage, they will not survive to reproduce and allow a new generation to mutate further away from the original population.
The disadvantage from not having the trait normally arises only after the reproductive stage of the individual's lifecycle is mostly over.  This is a special case of "no strong pressure", because evolution selects genes, not the organism. In other words the beneficial mutation does not alter the reproductive fitness.
Koinophillia resulted in the trait being unattractive to females. Since most mutations are detrimental females don't want to mate with anyone with an obvious mutation, since there is a high chance it will be harmful to their child.  Thus females instinctually find any obvious physical difference unattractive, even if it would have been beneficial.  This tends to limit the rate or ability for physical differences to appear in a large & stable mating community.

Evolution is not a directed process and it does not actively try to look for an optimum. The fitness of an individual does not have any meaning in the absence of the selection pressure.

If you have a relevant addition then please feel free to edit this answer.

Here it is implyed that NOT having the trait is a drawback ie that there is a selection pressure against not having the trait.
So I think the true answer is that keeping diversity or even traits that are drawbacks is an advantage : if there is a pandemy of malaria, having drepanocytose will be an advantage. Moreover having the whole population stuck in the same local fitness maxima is not good for exploration of potential greater maxima

@agemO It is implied here that there is no strong selection pressure against not having a trait. Therefore the trait does not establish itself. The case of malarial resistance that you mention would be an example of tradeoff: sickle cell disease being a tradeoff for malarial resistance.

Ok I think I underestimated the "strong" part in what you wrote.
For the tradeoff part, I think even without an already existing tradeoff, keeping diversity is usefull for parameters exploration or to adapt to a future environemental change

I think it's important to point out that in order for many useful adaptations to evolve, they need to start evolving in a way that is either not important to the species survival or differently important to it's survival.  This relates to the 'genetic distance' you mentioned.  For example, it's not like one animal sprouted some wings and then because it could fly, had lots of offspring.  Evolution of low-impact features is not a strange phenomenon but rather it is a crucial part the process.

How beneficial a trait is is also strongly affected by its environment and environments change constantly. Since it has no foresight natural selection is always playing catch up with the environment.

There's always the most obvious: Evolution is chance.
Some traits allow an individual to have a higher chance to produce offspring. That doesn't mean individuals with that trait have more offspring, not even on average unless the law of large numbers applies. A randomly mutated perfect squirrel could appear, and since it's only one, it gets run over by a car before it can reproduce and all perfect traits are lost.
Then there is a chance that a trait is beneficial for the individual, but doesn't have a significant effect on its chance of having offspring. For example, take human eyesight. People with really poor eyesight have a disadvantage. But most people have good enough eyesight until they are too old to have kids, so it doesn't matter to evolution if they fall off a cliff afterwards. It may even be advantageous if kids don't have to spend resources to care for their parents.
And a very nice effect is a swarm effect where you look at entire swarms, for example of fish. Take a swarm or community that reproduces primarily within itself, where for some reason only traits that are beneficial for the individual can get inherited. As soon as the swarm gets into competition with a superior swarm - where traits that benefited the swarm got inherited - the entirety of the former swarm may die.
There's also the effect of society. If during one decade a society thinks people with green hair are not attractive partners - even though it's better for camouflage - it sucks to have green hair during that decade. This doesn't only apply to humans. I remember reading that among some bird species the singing evolves and which songs are "hip"/attractive depends on social factors as well as genes. Just imagine what would have happened if a small number of humans would have started to grow bat wings that made them fully capable of flight, during the time of the Spanish Inquisition - rather than spreading the new gene they would have burned on a stake.
Let's not forget about the really cool effect of frequency dependent selection where a trait is only beneficial if not too many other individuals have it. These traits can be beneficial for an individual, or a species, or both, but only if not too many individuals carry the trait. A community of humans can benefit from super smart people who have limited control of their bodies and emotions, but if all humans in the community are like that the community has a problem.
Last but not least, there's the change in external conditions. If conditions change, many species will simply go extinct (e.g. Ice Age). Imagine all viruses disappear. If there are no viruses, a trait that makes the immune system more efficient against bacteria and cancer at the expense of having no defense against viruses, is clearly a beneficial trade. Then viruses come back and every species that adapted the "no defense against viruses" trait goes extinct from a viral infection. This can make it beneficial to not adapt new traits too quickly.
In summary: By accepting that evolution is a random process where individuals with more advantageous traits are simply somewhat more likely to have more offspring, and where entire communities or subspecies are slightly more likely to go extinct if the traits are less beneficial for the community, you get all of the above effects and many more. Keep in mind that individuals with advantageous traits are in no way guaranteed to have more offspring, and communities can be wiped out or flourish due to all kinds of incidents that completely ignore how advantageous or disadvantageous their traits are.

I didn't expect that analogy.

@armani Nobody expects the Spanish Inquisition!

"There's always the most obvious: Evolution is chance."
Not necessarily so.
Predictable Evolution Trumps Randomness of Mutations
http://www.scientificamerican.com/article/predictable-evolution-trumps-randomness-of-mutations/

@MakotoKato Evolution is a (flawed) optimization algorithm based on chance. Es an effect, in some cases the predictability of some changes happening can be very high, especially with bacteria in a controlled environment, where you have a massive number of individuals combined with a massive number of generations. It's why we can predict more bacteria will become resistant to more antibiotics over time.

Because evolution is an effect, not a cause.  That is, there's no "God of Evolution" out there deciding that this or that trait would be beneficial to a species, and deciding to add it.  Evolution just works* on whatever random variations happen to come along.
*And as others have pointed out, it works statistically, not deterministically.

@WYSIWYG: I think this post does add something that has been missed, which is a succinct reason why traits aren't evolved on demand.  The other answers, while correct, are long-winded enough to IMHO lose some people.

I actually like this answer. This kind of question makes the most sense in a mental model which silently assumes intelligent design of organisms, even if the asker believes in evolution and is unaware of the inconsistency of his knowledge structure. All the other answers explain the points in which evolution behaves unlike intelligent design, but this one also notes which core assumption is responsible for the misunderstanding.

Below are the reasons I can think of. The list is not exhaustive and there are some conceptual overlaps.

The trait seems advantageous but it is not, maybe due to its effect on another component of fitness (trade-off). It sounds to me to be the most likely explanation whenever you are wondering why a given species does not carry a given trait. In other words, the fitness landscape matter.
The trait is not that easy to build it requires a series of mutations that are either neutral, quasi-neutral or deleterious.
The mutation just hasn't happened yet (lag load).
the mutant variant had appeared several times but got extinct because of genetic drift even though it was beneficial (assuming no fitness valley to cross).
Putting the two previous points together, if only one mutation (one SNP) is needed to build this trait and if the trait is beneficial but quasi-neutral, then the expected time before fixation to occur is around $10^9$ generations. Here is why. Let $N$ be the population size and $\mu$ be the mutation rate. In a diploid population (but the end result is the same for the haploids), there are $2n\mu$ appearing at this locus each generation. As the mutation is quasi-neutral, its probability of fixation (calculated from Wright-Fisher equations or Moran birth-death process, or from Kimura's diffusion equation) is $\frac{1}{2}N$. Therefore the rate at which fixation occur is $2N\mu \frac{1}{2N} = \mu$. $\mu$ for an SNP in a species that has a large genome is around  $10^{-9}$. The probability that fixation occurs in $t$ generations is given by the exponential distribution with parameter $\mu$ ad the expected value of this exponential distribution is $\frac{1}{10^{-9}} = 10^9$ generations. If there is one generation per year, that takes a lot of time! Of course, those calculations are a good approximation when the trait of interest is quasi-neutral. If the positive selection is very very strong on this trait to the point that we can completely neglect drift, then the expected time for the mutant to occur is $\frac{1}{2N\mu}$, which is $10^5$ for a population size of $N = 10000$ which is still quite a lot. In the meantime, the environment or the genetic background may change so that the trait is not advantageous anymore. The above calculations assumed that the trait appeared with only one mutation and that only one SNP can cause the trait to exist. One can be more general by summing exponential distribution (for multiple mutation scenarios) and increasing the mutation rate (for mutations at different loci can make the trait exist).
the mutant variant had appeared several times but got extinct because of drift because the Ne in the genomic region is very low due to the act that there are many loci under selection in the surroundings (background selection).
the trait is beneficial and occur sometime but either stay at low frequency or even regularly disappear due to a migration of individuals coming from an environment where this trait is strongly deleterious (dispersal load).
Be careful to understand what evolution does and therefore to understand what advantageous mean. Taking kin selection/group selection/lineage selection apart to make things easier, an advantageous allele is the one who increases the fitness of its carrier. The effect of a given allele depends on the environment and on the genetic background in which it exists. A beneficial allele does not necessarily increase survival or increase the probability of the population to not get extinct. Think about sexual selection typically.

Evolution occurs by a change in gene frequencies, with gene frequencies potentially affected by four mechanisms (mutation, migration, drift, and selection).

The answer to the question Why does the seemingly advantageous trait X not evolve? could be:

The mutations for a trait have never occurred within a population, or such genes have never migrated into the population
The mutation(s) to cause such a trait may have once been present in a population but migration and/or drift and/or selection has since removed them from the population
Selection has removed the mutations causing the seemingly advantageous trait because the same (or tightly linked) genes have other deleterious effects by pleiotropy

Similarly, the answer to the question Why does the seemingly disadvantageous trait X evolve? could be any of the following:

Alternative genes have never been introduced to the population by mutation or migration
Mutation, drift, and migration have allowed the gene to fix over other more advantageous genes
Selection has spread the mutations causing the seemingly disadvantageous trait because the same (or tightly linked) genes have other beneficial effects by pleiotropy

Note also that the trait may seem (dis)advantageous in the current adaptive landscape, but selection exhibits temporal variation
Read here on why and how genetic variation is required for evolution/adaptation to occur
Read here for more about the process of adaptation
Read here for more on genetic variation
Read here for more on rapid evolution
Read here for more on the relationship between multivariate selection and adaptation
A detrimental phenotypic character may have no genetic variance, so it may be impossible for selection to stop such occurring; many diseases have considerable environmental inducers (e.g. selection can't work against emphysema developed as a result of smoking, but it can work against genes that increase the tendency of developing emphysema).

All the previous answers are very good. However, I feel a point was missed (or maybe I didn't read deeply enough).
I will highlight the concept of fitness landscapes. This is how it looks:

The peaks represent the fitness of the species for a particular allele frequency. In the multipeak scenario, there are valleys which represent, obviously, reduced fitness. The concept of evolution being a chance event translates to "local peaks are favored over the global peak". As a result, a species may reach a high fitness level even though a higher peak exists (assume the highest peak is the perfect organism you speak of). Once it has climbed a peak, to change to the other peak it has to go through a valley i.e reduced fitness to improve. If nature was a benevolent entity then it could have been a grand transition. However, less fitness makes species susceptible to die off and hence they mostly don't make the transition making the perfect organism statistically less likely.
I also attach a link a .gif to show species heading to a certain peak. Notice the fact that no one likes to stay in the valley and rapidly swarms to the peak.

Richard Dawkins devoted an entire chapter of The Extended Phenotype to this question, Constraints on Perfection (the third chapter in the edition I have to hand); he listed six (not including those he critiqued as perhaps not being such strong constraints as others have suggested). The whole thing is worth a read, but for brevity, I'll state the six he had in mind here:

Time lags (a given adaptation may arrive in the future)
Historical constraints (the new system has to modify the old rather than starting from scratch)
Available genetic variation (for example, this may explain why many non-functional body parts shrink instead of disappearing)
Constraints of costs and materials (big brains, for example, are so expensive we're very unusual in having a net use for them)
Imperfections at one level due to selection at another level (Dawkins had previously spent a whole book, The Selfish Gene, arguing - among other things - that what's good for the gene may not be good for the individual)
Mistakes due to environmental unpredictability or 'malevolence' (an organism is built to be well-suited to average and dangerous conditions in their environment, and cannot quickly update its structure for every possible contingency)

Let's break this down to cover your two questions individually
Question 1 If a trait would be advantageous to an organism then why hasn't it evolved yet?
This one is really easy, natural selection, as well as other forms of selection, can only work with the variation that arises through mutation. Mutation is a random process evolution has no control about what variation will arise it can only select from those that do. Successful mutations tend to be small changes (small changes are less likely to disrupt a complex process like an organism) because of this organisms can get stuck with disadvantageous setups because evolution cannot go back to drawing board, it cannot go through a disadvantageous change to get an advantageous one.
My classic example is human back problems, a spine is a horrible thing to use to support weight upright but a spine was all evolution had to work with, it was the best option of what was available and being upright was a bigger advantage than the problems with a spine were a disadvantage. Designing a whole new system would be better but the chances of the hundreds of thousands of mutations need to "start over from scratch"  are so astronomically unlikely we will never see it. Evolution can only select for the best out of what is available and mutation can only make small changes to what is available.
Another example is the Laryngeal nerve in giraffes which is a 14ft nerve that literally only goes a few inches, but since the nerve evolved when a straight line from the brain to the tongue left the heart in front of it (fish), as terrestrial vertebrates developed necks and moved the heart into the chest the nerve is stuck running down around the heart before returning to the head, a ~14ft detour. having the nerve is a bigger advantage than the detour is a disadvantage, and a mutation redirecting the nerve would be a large complex mutation thus is unlikely to ever occur. A historical legacy like this is responsible for a lot of bad adaptations that stick around, changing them is just too difficult to happen by random mutation.
Question 2 Conversely, if a trait is not advantageous or mildly disadvantageous, why does it exist?
there are a few components to this no trait is advantageous in an of itself, it is advantageous in a particular organism and environment. Sharks beautifully adapted masters of the ocean, drop one in the Sahara and it is doomed. what is good in one environment is often a disadvantage in another. Combine this with the fact that organisms move(or spread) and the fact that environments change and it is easy to see how organisms can end with a mildly disadvantageous adaptation. Adaptations for hunting from the ice was an advantage for polar bears when ice was plentiful now that the ice is disappearing it is not so advantageous. but the ice is disappearing faster than evolution can change the polar bears.
Often the changes in environment are changes in the other organisms around them, being extremely fast is actually a horrible adaptation for gazelle in many ways, it makes them fragile, it makes them small and weaker than other ungulates, it spends calories to grow muscles that could be used to produce larger offspring or taller bodies, etc, but in an environment with cheetah not being fast is a worse disadvantage. In this way, evolution is often about taking the least bad out of a set of bad "choices". And of course, the faster the gazelle get the faster the cheetah get until they are too specialized to live any other way. This push to specialization is very common however specialized organisms are the least able to handle change, they are too specialized to do anything different. So if say a new predator shows up that can force fragile cheetah away from their kills (humans) the cheetah are screwed, they could suffer a huge die off (Africa) or go extinct (North America). Evolution cannot make you good in every direction, you cannot be both a good swimmer and a good climber and a good digger.
Another aspect is cost vs benefit, a trait does not occur in isolation, a body is a complex thing, the same mutation that makes some humans  resistant to cholera also makes them more susceptible to cystic fibrosis, this will be an net advantage when cholera is a big threat and a net disadvantage when cholera is rare. they key term here is net there is no condition when it is purely an advantage or disadvantage. Basically, all traits fall into this cost-benefit comparison. No trait is an advantage in every situation, every change has a cost, even if it is just calories that could be spent elsewhere.  We know of no traits that are purely a disadvantage that persists but there are many many (if not all of them) such tradeoff traits, a disadvantage for an advantage.
Another example is sexual selection, some traits help you to find or attract mates but are detrimental to your survival, but reproduction is a bigger advantage in evolution than survival. Evolution simply cannot favour genes if they never make it into the next generation consistently. So you end with peacock tails that get the males killed but are the only way to find mates. A male without the huge tail will not mate and the male offspring of a female without the desire for big tails will suffer the same problem (because the female keeps ending up with unattractive male offspring) so it is basically impossible for peacocks males to stop growing huge tails and it is unlikely peacock females will stop preferring bigger and bigger tails. Thus even though it is very detrimental to peacock survival the trait sticks around because it is an advantage in reproduction.