DDIG and the Government Shutdown

I'm currently writing my DDIG (Doctoral Dissertation Improvement Grant) which will be submitted to NSF. It's going pretty slowly, but hopefully I'll have something worthwhile here shortly. Fortunately for me, the House Republicans were kind enough to shut the government down and give me a couple extra days to write. Thanks John Boehner! Thanks Ted Cruz! You guys are the best!

New Hamsters!

We just received a new strain of Siberian dwarf hamsters. They are an inbred line from Bruce Goldman at UMASS Amherst. They are reported to change color reliably and, as they are a different collection from the stocks that we've been using so far, they should be genetically distinct from ours to some degree.

I'm hoping to use them to assay imprinting within P. sungorus if they are different enough. Of the projects that I've done so far, the main shortcoming is that I do not know which genes are imprinted in hamsters and which are not. I have to guess based on the genes that are imprinted in house mice, deer mice, and humans. This is a problem because we know that different species imprint different genes. For example, deer mice do not imprint Mash2 while house mice do. Of the genes I surveyed in our original strains of dwarf hamster, there were three that appeared to not be imprinted, but that may instead be due to imprinting breaking down in both reciprocal hybrids. Using this new strain of P. sungorus I should be able to determine which genes are actually imprinted within that species.

This will of course depend on whether there are an appreciable number of nucleotide differences between the two strains. In order to determine whether an allele is imprinted, I have to find at least one diagnostic SNP within the expressed region. If these two strains are very closely related, they may not have such diagnostic SNPs. However, I think that they likely will as between P. campbelli and P. sungorus there are 3-6 diagnostic sites per kilobase and those two are relatively recently diverged. The standing polymorphism within one species should be less, but likely still high enough for there to be at least 1 SNP in each exon. I am assuming that these two independent collections will have sampled different subsets of the standing species-level polymorphism and so will have enough differences to answer my question.

candidate imprinted gene sequencing experiment

I have a paper that I'm working on in which I have sequenced the cDNA from 8 candidate imprinted genes in both species and the hybrids. I did this in order to determine whether imprinting is breaking down at these loci. I found that there is no signature of imprinting breakdown in 7 of these genes (the eighth had no diagnostic differences) in 6 hybrids (3 P. campbelli x P. sungorus and 3 P. sungorus x P. campbelli). However, we have since realized that there may be sex-specific issues and as the original 6 ended up being 4 males and 2 females (we had no way to sex-type the offspring at the time) we have decided to repeat this experiment with 3 males and 3 females.

Fortunately I have all the RNA extracted for the next-gen project and so all I had to do was synthesize cDNA and amplify then sequence the genes of interest. I'll update with results.

So far 6 of the 7 candidates that have diagnostic fixed differences have been sequenced. The results remain the same as before: no breakdown of imprinting in one hybrid: there are some genes where breakdown occurs in both hybrids and some where imprinting is correctly maintained. Furthermore, there are no differences between the two sexes in the pattern of expression.

The 7th gene, Peg3, is not amplifying and so I can't sequence it. It is an important gene to assay because it is one of the main partners in the deer mice that cause parent-of-origin growth (Vrana et al, 2000). It is frustrating that it won't amplify reliably as samples I ran a year ago were great. The primers do not include an intron and so the first thing I will do is to try the primers on gDNA instead of cDNA - maybe the gene is not expressed highly in the placenta of hamsters and that is why the PCR won't work.

update 7-15-13: The PCR with gDNA worked fine, not a brilliantly blazing as the first time I did it, but not bad. This leaves me with the question of whether the original PCRs had gDNA contamination with the RNA. I think that this is not the case as Peg3 showed imprinted expression in those samples. If gDNA was a contaminate, the sequences would have been heterozygous and shown what I would have interpreted as biallelic expression. The only way imprinted expression could be found is if the gene is truly imprinted and there was no gDNA contamination.

Now the problem remains of how to get the Peg3 primers to work on cDNA like they did before. I have increased the extension time by 20 seconds in case the full 1000bps weren't being copied and I increased the cycle number from 35 to 40. Although I'm a little skeptical of amping anything 40 cycles, if there are faint bands there, 40 cycles should make them show up.

update 7-16-13: All the cDNA bands are really faint if they're there at all. I'm pretty sure the positive is present, but it's kinda shitty all the way around.  E~ suggested that I should do a comparison between the gDNA of the original sequences and the gDNA of the one's I'm struggling with now to tell if there has been a problem with the primers (all gDNA's fail) or perhaps a SNP in the priming site (new gDNAs fail, old ones work). Although this is going against the Prime Directive (Science's General Order no. 1: only change one variable at a time) I am using new Taq too. This is partly because we are out of the old, and partly because I think the old may not be working. Here is my  predictions/interpretation table:

IF:                                               Then:
Both old and new gDNA fail     primers are bad, reorder primers
Old gDNA works, new fails      SNP in the priming site, redesign primers
Old gDNA fails, new works      WTF, I have no idea what this would mean, I hope it doesn't happen...
Both old and new gDNA work  old Taq was bad, the new is good, re-try with cDNA

update 7-30-13: here is the gel:

Land 1 is the ladder, lanes 2-7 are the samples, the first three are the old gDNA, the second three are the new gDNA, lanes 8 and 9 are the positive and negative control, lane 10 is another ladder. 

All the gDNAs worked, so I will assume that the issue was bad Taq and tomorrow I will run out the cDNA with the good Taq.

update 8-1-13: Didn't work. The old cDNA still doesn't amplify. Try making new cDNA

update 8-14-13: I figured it out! I had cleaned the cDNA in the previous trials and since I had started with so little, I lost most of it. This time I did not clean the cDNA and have beautiful bands. Now for sequencing!

Lane 1 is the ladder, 2-18 are Peg3 from cDNA, 19 is the positive control and 20 is the negative control.

Such a ton of work for so simple a problem. I'm just glad it's working.

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Vrana, P. B., J. A. Fossella, P. Matteson, T. del Rio, M. J. O'Neill, and S. M. Tilghman. 2000. Genetic and epigenetic incompatibilities underlie hybrid dysgenesis in Peromyscus. Nat Genet 25:120–124.

RNAseq Libraries sent!

I finished pooling my samples (lesson learned: don't use small volumes it evaporates as you pipette) a couple weeks ago and they've been sitting in the fridge ready to ship off just waiting for the finances to come through with the University of Utah. All the paperwork was finalized yesterday and we just missed the shipping time (dropped the package off at 4:05 for a 4pm pickup). We had to pick it back up and hold onto it until today. We'll add some more dry ice and send it off this afternoon.

It has been a ton of work to get that 30ul ready for shipping. Now we cross our fingers and hope that it comes out all right. In the mean time, I think I'll have a beer.

Evolution Conference 2013 - Tuesday

Many more talks today, here's some notes on the ones that stood out:

Jennifer Kovacs told us about a cool ability of the endosymbionts of aphids and how they defend against ladybugs. When a female ladybug eats the infected aphids, she suffers no immediate consequences, but her offspring show a reduced ability to successfully pupate. Those that do pupate are on average larger than normal which may be due to a “filter” effect where the smaller, weaker ones were weeded out by the bacteria. As aphids reproduce clonally, the relatedness between two aphids on the same leaf is 1. This means there is strong selection to stop the adult ladybug’s offspring from consuming other aphid clones. The only hole in the story so far is that no one has been able to show that the aphid’s bacteria survives the adult ladybug’s stomach and gets into her ovaries. Somehow it must get into her eggs, but they haven’t been able to show that yet. Still a really cool story of host defense. 

Taichi’s talk was fun too. He’s looking at Bergman’s Rule (body size increases with latitude) and how it correlates with the gut microbiome. He’s showed that especially in the east coast there is a strong correlation between composition of microbes and latitude that also correlates with average body size in house mice. There is less of a pattern on the west coast, but that is likely because the colonization was much more recent and there has been subsequent gene flow from Mus spretus that may be confounding the pattern. 

Jamie Zuniga-Vega talked about superfetation in live-bearing fish. Superfetation is where one female carries many broods at different developmental timepoints concurrently. There are three main hypotheses for superfetation which are: (1)  it lowers the peak cost of reproduction - at any given time, female must invest less per unit time. (2) It results from morphological constraint - many offspring take up a lot of space forcing the female to not be hydrodynamic anymore, if the offspring are at different stages, they take up less space. And (3) it compensates for high adult mortality. If there is a high probablility of adult mortality, high fecundity may be able to comensate. Thus superfetation may increase rate of offspring production rate. They found that hypothesis 2 is best model for two species where fast water causes higher rates of superfetation, but the third species doesn't have anything that shows preference of one hypothesis over another.

Keenan Morrison then talked about anamniotic eggs and how they may predispose species for the evolution of matrotrophy.  Amniotic eggs are impermeable and cannot absorb nutrients, but anamniotic eggs can assimilate resources across the “shell.” As these eggs already can accept nutrients from the environment, it is easy to make the next step to accepting nutrients from the mother’s uterus.

David Reznick followed the previous two talks and discussed how placental or matrotrophic fish should have greater male-female conflict. Furthermore he argued that placentas should correlate with long gonopodium (penises), small body size, lack of courtship, and sneaker mating strategies, non-placentals on the other hand should show strong sexual dimorphism, elaborate mating rituals etc. I was unclear on his logic as to why this is true (can’t placentals have pre-mating sexual selection as well as post-mating conflict?) and am looking forward to reading a paper he will hopefully publish ont eh topic (I felt better about my confusion as Doug was also unsure of his logic here). Surprisingly, he has found that there is an elevated speciation rate in non-placentas compared to placental fish. This is opposite of what I would have expected given the opportunity for maternal-offspring conflict in placental species. The species that do not have placentas instead show elaborate mating rituals and are characterized by strong premating sexual selection. This may then go hand-in-hand with the observation that birds, where strong premating sexual selection/sexual dimorphism is common, speciate twice as fast as mammals, where developmental conflict is more pervasive. Reznick also found that there is no support for “adaptive hypotheses” of the origin of placentas, but I’ll need to see his paper to remember/understand why he thinks so. Hopefully the paper with come out soon. 

I was lost with Turelli’s talk. He went fast and had a ton of words on his slides. It sounded impressive, but I couldn’t follow anything he was saying. 

Rob Unckless’ talk was a great conclusion for the day. He talked about the drive system in Drosophila affinis. He and I had spent many hours talking about this system back in the Jaenike lab and creating recursion equations to model it. the equations we made then were comparatively quite simple - one driver, one suppressor. What he talked about today was how this system may maintain polymorphism of the Y chromosome given many drivers and many suppressors. Apparently he had to make a perl script to generate the recursion equations as they got so complicated. I am going to invite him out for a talk in the spring if I can manage it. 

The last talk of the evening was Jack Sullivan’s SSB presidential address. It was really fun and he showed great pictures of bacula and was quite entertaining. Much of his talk was work done by J~ either as his masters student or recently in collaboration. He ended with the statement that you should always treat your students well so that you can exploit them years into the future. 

I got to hang out with Rob and Yaniv, Erica, Mike Shapiro, Yasir, Daniel Matute and a bunch of others in the evening which was a blast.  All in all it was a superb conference.  

Evolution Conference 2013 - Monday

Lynda Delph talked about how she found Haldane’s rule in a species of plant that has sex chromosomes. I got a little lost with all of her logic so I should probably read her paper, but I think she was arguing that the dominance theory does not explain male rarity while both dominance theory and the faster male theory serve to explain pollen sterility. I’ll have to look up her paper though to see the actual data again before I make too many claims about what she said.

Yaniv’s talk went well too, he described some ngs data he has on M. nasutus and M. gutattus and some patterns of introgression that he found.

The highlight of my day was a talk by Matt Brandley who was looking at placentation in squamates, specifically skinks. He was trying to figure out how the evolution of viviparity occurs and used a species of skink that shows polymorphism for viviparity to compare uterine gene expression. He found that there was not much different at all between the two reproductive modes but thought that due to pretty stringent penalties against high variance and a large sample size that had high variance in expression levels that he may have missed a bunch of true differences. He said that he had just gotten the data back and hadn’t had time to really play with it much yet. In a previous paper he’s described some differences in uterine gene expression in another skink and compared it to mammals and found that many of the same genes are used to facilitate live birth. For example both systems must repress the mother’s immune system to keep her from rejecting the offspring. 

Lila’s talk was fun too, it was good to hear about Margaret’s old project looking at thermal adaptation in mimulus in Yellowstone park. 

There were no talks in the afternoon and I headed up the tram with Taichi and Katya to hike down the mountain, ended up meeting Rob up there and eventually Kris. We spotted a marmot and a mountain goat which was pretty fun. Below are photos of the view from the top and a golden manteled ground squirrel who was interested in some peanuts.

My poster session was in the evening and I was pretty worried that no-one would show up after the afternoon’s break, but it was packed. I had about 10 minutes in the beginning free and after that it was one person after another. Turelli came and chated as did Kristi Montooth and Nitin as well as a number of other folks. Had a couple really good chats about imprinting and ligers and how the dominance theory may explain growth disorders involving imprinting. Afterwards Kris and I went and hung out with Doug and Matt and Paulo in the bar at the hotel and ended up heading home early as we were pretty exhausted after 3 hours on the mountain and 2 hours of hard poster-sessioning.

Evolution Conference 2013 - Sunday

I saw a long-tailed weasel near the main tent later in the day which was pretty exciting and Matt saw a moose in the parking lot that Kris and I ran down to try and find but couldn’t.

Talks-

Amy Dapper just presented some theory that the pattern of evolution of male reproductive genes is more consistent with a null of relaxed constraint rather than positive selection. It was quite interesting and based on a couple observations such as that sex-specific gene expression causes the selection coefficient to be reduced by half and that genes that select for highly competitive sperm are only actually beneficial when the female mates multiply (and with males who have different alleles at those loci). This causes the strength of selection to be scaled down even further by the harmonic mean of the number of mates. Her main result was to show that recently published dN/dS ratios that seem so high in male reproductive genes fall exactly on the null expectation of dN/dS that she calculated. It was interesting and she said that it should be published by the end of the summer. It may make a fun lab meeting paper to discuss once it's out.

David Gokhman presented new data on the epigenome (methylome specifically) of the neandertal and denisovan. He used the natural degradation of C->U and Cmeth->T to determine which bases in ancient dna was methylated. found that of the regions differentially methylated between humans and neandertals (Hox8,9,10) all control bone growth and expression correlates with patterns of neandertal morphology and known human pathology. Really cool.

Went to Zach Gompert’s talk - way over my head. I followed the selection equation parts and then once he actually got into the model I lost it.

Also attended Joan Roughgarden’s talk. Was not impressed. 

Matt Hahn discussed genomic islands of speciation and described how the divergence in these islands - when measured in an absolute manner, is incredibly low. The point is that while there is likely something - selection possibly -  driving the patterns of Fst that we identify as “islands” it does not mean that there is speciation with gene flow occurring. 

Dolph Schulter’s ASN presidential talk was interesting. He talked about the latitude-speciation correlation and if it exists or not, decided that ecological opportunity (which we can’t really measure) is really what drives everything. Talked about how the stickleback fish species are the result of repeated fixation of standing variation and how that doesn’t align with the standard thoughts about DMI’s - he has wide-scale additivity across many genes that seems to isolate species. Claimed that it was much different than the classic DMI model.

Evolution Conference 2013 - Saturday

Kris and I arrived late Friday night. It’s good that we had Siri to navigate for us as we would have been completely lost otherwise. Turns out that Brice got one hell of an awesome mansion for us to live in for the next couple days.  

Driving in in the morning, we saw a coyote - great way to start a biology conference. 

We got a bit lost on the way in - it was not immediately obvious where the conference actually was, but we finally found it and got registered.

Here’s some talks that I went to that really stood out:

Daniel Matute - great, talked fast and I am not 100% familiar with all the molecular techniques that you can use in drosophila, so I got a little lost in the end. He is using deficiency mapping technique to find the genes that isolate melanogaster/yakuba (I think it was yakuba, but now that I write it I’m not really sure). Inviability depends on x-x interactions as well as a 3rd locus somewhere else. Should have typed this yesterday directly after the talk as I can’t remember the specific details. I talked with him later and it turns out that he’ll be starting as a professor soon and is looking for grad students.

Robin Hopkins discussed reinforcement among flowers in texas: blue in most of the range but red in the area of overlap. She had me pretty convinced that it was reinforcement: hybrids show really low fitness, but are common when flower color is the same between the two species.  Also got into the mechanism of reinforcement: the butterfly pollinators have a preference for flowers of the same color - some like red, some like blue, but the ones that like red always go to red and the ones that like blue always go to blue. The one thing that I was confused about is that the preferences I just described operate in the area of sympatry, but not in the area of allopatry where pollinators have a distinct preference for blue. I’m not sure why it would be different as it’s the same species of butterfly that does the all pollinating. She also got into the genetics of flower color change from light blue to dark red, it’s a 2-locus, each with complete dominance (the standard 9:3:3:1 ratio). One loci controls brightness, one does red/blue. Yaniv asked afterward it it may be collapse rather than reinforcement though, but I had to run to the next talk and didn’t hear what she said. I’ll try to talk to Yaniv about it.

Matt Jones’ talk was great, it will be fantastic to have him in the lab.

Amanda Moehring claimed to have found the first speciation gene for a behavioral trait in melanogaster but she didn't actually present any data, only asserted that it had an effect. I found it really frustrating  as she showed images of her deletion mapping, but not any actual data about what the region she found actually does. Many of the speciation people were there (Matute, Noor, Yasir) just shaking their heads at her the whole time. It was one of these  extraordinary  claims that have no evidence supporting it. I talked to both Daniel Matute and Yasir about it later and neither were impressed. I’ll be looking up the papers and possibly writing more about it later.

I realized that I printed the wrong version of my poster and had to skip the poster session to re-print it, but I ended up getting together with Yasir and Erica and Ryan and Matt for some beers later.

Great first day.

Diluting and pooling - last step

I have now prepared and amplified all my samples. I used 12 cycles and 8ul of product so that I wouldn't blow through the entire 20ul of library if something went wrong. Most of these had plenty of product, the couple that didn't I re-amplified for 14 cycles. For the dilution, I used the values from the nanodrop rather than the bioanalyzer as Sara has had some issues with pooling based on bioanalyzer values.

Here are the bioanalyzer traces of the completed pools:

The final concentration is a little low, but as the sequencing facility only needs ~10ul of 10nmol/L it should be fine. I actually ended up making 4 pools as the first two didn't stack up well on the qPCR. I think this was because I was pipetting such small volumes that the liquid was evaporating and changing my concentration. For the second set (Pools 3 and 4, seen above) I made sure that my sample volumes were never less than ~10ul. It seemed to work much better. Here's the qPCR trace of 5 of my samples. They should all be right on top of each other (except for the light blue one which is the no-template-control:

There is only about 1 cycle spread from the first one to the last, whereas the pools 1 and 2 had at least a 4 cycle spread. 

S~ is now setting up the account at Utah and I'll be sending the samples as soon as all the paperwork goes through. (We've had some issues with sequencing at Berkeley and so we're gonna try a new facility.)

Epigenetics and a new direction

I have been keeping an eye on a couple other science blogs - homologus and Judge Starling among them, and I have decided that I should include among my descriptions of experiments an occasional review of some bit of literature that I find interesting. And so:

PNAS recently published two papers: Epigenetics, a "Core Concepts" piece by Sarah Williams (2013) and Epigenetics: Core Misconcept by Mark Ptashne (2013) where he argues that Williams is perpetuating some of the main misconceptions about epigenetics. In order to analyze this little spat, I will first define epigenetics and then analyze what each of the authors say and whether Williams is indeed perpetuating misconceptions. This disagreement boils down to another fundamental argument over whether DNA methylation and/or histone placement should be considered "epigenetic mechanisms" and I will conclude by pitching in my two cents in this debate.

Here are a couple of current definitions of epigenetics from the literature:

From Bird (2007): "... epigenetic events... [are] the structural adaptation of chromosomal regions so as to register, signal or perpetuate altered activity states."

From Eccleston et al (2007): "Epigenetics is typically defined as the study of heritable changes in gene expression that are not due to changes in DNA sequence."

From Sasaki et al (2008): "Epigenetics refers to a collection of mechanisms and phenomena that define the phenotype of a cell without affecting the genotype"

From Bonasio et al (2010): "Epigenetic signals are responsible for the establishment, maintenance, and reversal of metastable transcriptional states that are fundamental for the cell’s ability to “remember” past events, such as changes in the external environment or developmental cues."

These definitions all agree that epigenetics does not include changes to the base sequence of DNA, but rather changes in the expression level of different genes. Said another way, epigenetic changes must be reversible: coding changes are not reversible (a back mutation is quite rare) while expression changes are (it's relatively easy to turn genes on and off). These definitions also all agree that these expression changes must be heritable from one generation to the next (it should be noted that this is most often cell generations i.e.: heritable through mitosis, rather than organism generations, though both are applicable).

One other condition is also commonly found in the literature and is necessary for an epigenetic system: it must be self-perpetuating (Riddihough and Zahn 2010; Bonasio et al 2010). Self-perpetuating means that there is a positive feedback loop somewhere such that once it is initiated and even in the absence of the initial signal, the new expression level will persist.

In summary: there are three characteristics that are necessary for a system to be labeled "epigenetic:"
1.) It must be reversible by dealing with changes in expression level not sequence identity.
2.) It must be heritable, at least through mitosis, possibly through meiosis and fertilization.
3.) It must be self-perpetuating in the absence of the initial signal.

The predominate biological process that this refers to is development where a single cell divides and differentiates into a large number of distinct tissue types. At the end of the process, each cell in every tissue has the complete genome of the organism, but each cell type has it's own specific set of genes that is expressed. This is one of the most incredible - but rarely-recognized - cases of plasticity: a single set of genes gives rise to a vast number of different cell types and functions. Epigenetics is concerned with how, for example, a liver cells divides into two new liver cells. Certain genes are on in each liver cell that, when present in the daughter cells, cue those to also express the suite of "liver genes." Thus, this aspect of development complies with the heritable and self-perpetuating requirements of epigenetics. It is also reversible as no coding changes have occurred - only expression levels change, not the DNA sequence. We know this is true because the entire genome is present in every cell - it is certainly NOT the case the all of the "non-liver genes" are destroyed or excluded from future liver cells. This is depicted in the following diagram (from Ptashne 2013):

The blue circle protein (a transcription factor) activates the gene for the red oval protein (also a transcription factor) by binding to a cis-regulatory element (blue box). The red protein activates itself by binding to the red cis-regulatory element and also activates a suite of other green genes by binding to their cis-regulatory elements (red boxes). 

So what are some concrete examples of epigenetics? The prime example is a transcription factor that activates the expression of itself (self-perpetuating) and also activates the expression (reversible) of a suite of other genes as in the above figure. When this transcription factor is in the cytoplasm of a cell undergoing the cytokinesis phase of mitosis, it will be allocated into the two daughter cells (heritable) and will thus cause them to express a similar suite of genes as the parent cell. Another common example is prions. Prions are poteins with a specific tertiary conformation (reversible) that cause other proteins (self-perpetuating) to assume the same confirmation (heritable). Though prions seem to me to be in a slightly different class of epigenetics than transcription factors as prions don't involve DNA at all. This is not to say that prions are not epigenetic - they most certainly are - but rather that the term epigenetic is quite broad. I will from here on concentrate on the subset of epigenetics that deals directly with gene expression.

Moving on to Williams' (2013) Core Concept article, I found it to be a bit brief but not horribly off the mark. Williams focused on only two types of epigenetic inheritance: DNA methylation and histone placement and she did not go into detail about the mechanism by which these epigenetic changes occur. Her argument mainly concerned the reversible aspect of epigenetics: the fact that differential methylation (or differential histone placement) results in differential gene expression. She also asserted that these 'flags' on a bit of DNA are copied along with the rest of the genome during the S phase of the cell cycle and are therefore heritable. She did not directly address whether methylation or histone modifications are self-perpetuating, though the argument is that due to the action of methyltransferases the methylated sites are indeed perpetuated, and hence the expression profile of that site is maintained.  Specifically, De Novo Methyltrasnferase 1 (DNMT1) finds DNA where a methyl group is on one strand but not the other (as woud occur durring DNA synthesis) and it methylates the second strand. This results in two daughter cells each with accurately-reproduced methylation patterns and hence similar expression profiles as the parent cell.

Ptashne (2013) takes issue however with Williams' (2013) description of epigenetics. In doing so he puts forth two criteria which together are both necessary and sufficient to call something "epigenetic": these are memory and specificity. Ptashne's "memory" is a combination of the earlier "self-perpetuating" and "heritable" - a distinction that often becomes blurred (for instance: see the preceding paragraph - my argument for heritable and self-perpetuating are actually the same). As such I agree with Ptashne (2013) that the more general term of "memory" is useful. Technically, memory is the continuation of a specific expression profile of a given gene. Under this criterion DNA methylation is an epigenetic mechanism as DNMT1 faithfully transmits the signal to new molecules. On the other hand, histone placements are not known to be heritable or self-perpetuate, even though they do seem to correlate with gene expression, and so should not be considered "epigenetic" according to Ptashne (2007, 2013).

Both DNA methylation and histone placement also fails Ptashne's (2013) second test of specificity. Specificity has to do with which genes a give transcription factor acts upon: for instance in the earlier figure, the red circle only acts on the blue oval's regulatory region, NOT on any of the geen genes' regulatory regions. The opposite of something being specific is for it to be general in which case it acts ubiquitously across the genome. This is the sense in which DNMT1 fails the test: any time it finds a bit of hemi-methylated DNA, it methylates the unmethlyated strand regardless of location. Histone placement also fails this test, as according to Ptashne (2007) we have no evidence that histones are placed specifically. Ptashne states: "... it is said [that] chemical modifications to DNA... drive gene regulation. This obviously cannot be true because the enzymes that impose such modifications lack the essential specificity: All nucleosomes, for example, “look alike,” and so these enzymes would have no way, on their own, of specifying which genes to regulate under any given set of conditions." (Ptashne 2013). Clearly Ptashne takes issue with Williams' claim that DNA methylation and histone modifications are epigenetic mechanisms.

I disagree with Ptashne, and think that histone modifications and DNA methylation should be considered epigenetic. I will discuss each of these in turn, first DNA methylation. To be fair, Ptashne (2013) does opt-out of making a call on the methylation side of things, citing that its role in development remains unclear because it doesn't occur in the flies or worms - which he seems to consider the two "real" models for development. I can only conclude that Ptashne is slightly ignorant of the current findings in mammal models (yes mammal models for development do exist, even if Ptashne doesn't consider them "real").  Sasaki et al published an entire review in Nature Reviews Genetics five years ago (Sasaki 2008) that describes most of how trans-generational epigenetic events are established in the germ-line. One of the main things that happens during germ cell development is the erasure and reestablishment of the parental imprint. Imprinting is regulated by DNA methylation in the imprinting control region and fits both of Ptashne's requirements: memory because the methylation established at this point in development regulates gene expression throughout life, and specificity because there are only a subset of genes that are imprinted - it's not a ubiquitous genome-wide process. So contrary to what Ptashne (2013) claims, we do know plenty about DNA methylation in mammalian development and furthermore it does fit both of his requirements. That being said, we still do not have a solid understanding of exactly how the specificity is achieved - there is not a DNMT specific for each region that needs to be methylated (indeed there are only 3 DNMTs that actively methylate DNA). Presumably there is some type of factor that is specific to certain regions and recruits the DNMTs to specific areas. DNMT3L may fill this role as it does not actually methylate DNA, but instead complexes with DNMT3a and facilitates proper methylation (Sasaki 2008). This DNMT3a-DNMT3L complex also relies upon a specific histone (H3K4 allows methylation while H3K4me does not)(Sasaki 2008), and so specificity may be achieved due to an interaction between local histone type and the DNMT complex. In short DNA methylation certainly counts as an epigenetic mechanism of transcription control.

Ptashne (2007, 2013) also claims that we have no evidence that the pattern of histones is heritable and so should not be considered epigenetic. On the contrary, it is true that allele-specific histone patterns are conserved within tissues and so must be heritable. For example, histones (not DNA methylation in this case) are the primary drivers of imprinted expression of the Kcnq1 region of Chromosome 7 in mice (Umlauf et al 2004; Lewis et al 2004). This shows that histones do fit the specificity criterion - they are allele specific, as well as the memory criterion - imprinting is tissue-specific (and *naturally* allele-specific). As far as I can tell, we do not know how this specificity is achieved, but just because we don't  know how it's achieved, doesn't mean that it is not indeed specific.

In conclusion, I consider both differential DNA methylation and differential histone placement to be true epigenetic mechanisms of gene regulation as both of these processes are heritable, reversible, self-perpetuating, and specific.

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Bird, A. 2007. Perceptions of epigenetics. Nature 447:396–398.

Bonasio, R., S. Tu, and D. Reinberg. 2010. Molecular Signals of Epigenetic States. Science 330:612–616.

Eccleston, A., N. DeWitt, C. Gunter, B. Marte, and D. Nath. 2007. Epigenetics. Nature 447:395.

Lewis, A., K. Mitsuya, D. Umlauf, P. Smith, W. Dean, J. Walter, M. Higgins, R. Feil, and W. Reik. 2004. Imprinting on distal chromosome 7 in the placenta involves repressive histone methylation independent of DNA methylation. Nature Genetics 36:1291–1295.

Ptashne, M. 2007. On the use of the word “epigenetic.” Current Biology 17:R233–R236.

Ptashne, M. 2013. Epigenetics: Core misconcept. Proceedings of the National Academy of Sciences 110:7101–7103.

Riddihough, G., and L. M. Zahn. 2010. What is epigenetics? Science 330:611.

Sasaki, H., and Y. Matsui. 2008. Epigenetic events in mammalian germ-cell development: reprogramming and beyond. Nature Reviews Genetics 2008:129–140.

Umlauf, D., Y. Goto, R. Cao, F. Cerqueira, A. Wagschal, Y. Zhang, and R. Feil. 2004. Imprinting along the Kcnq1 domain on mouse chromosome 7 involves repressive histone methylation and recruitment of Polycomb group complexes. Nature Genetics 36:1296–1300.

Williams, S. 2013. Epigenetics. Proceedings of the National Academy of Sciences 110:3209.

Placental Histology

Another experiment that I'm pursuing in collaboration with L~ (an undergraduate here at UM) is to analyze placental histology of hybrid hamsters. She found that there seems to be some striking abnormalities in the layering of the hybrids' placentas. Placentas are very complex and formed from three main embryonic tissue layers (labyrinthine trophoblast, spongiotrophoblast, and trophoblast giant cells) as well as a maternal layer (decidua).

***This figure is taken from Wagschal and Feil (2006) - a great paper on imprinting and the placenta***

So far L~ has found that there seems to be a sex-specific placental abnormalities in the hybrids - only the female hybrids show major disruptions of the boundaries between the layers, especially between the labyrinthine trophoblast and spongiotrophoblast. This is quite exciting as I can find nowhere in the published literature that reports sex-specific hybrid phenotypes. It also complicates the over/under-growth story because overgrowth assorts by cross type, not sex while undergrowth is only found in males, not females. If we assume that abnormal layering of the placenta results in abnormal nutrient transfer, then L~'s defects do not explain the patterns of over/under-growth.

However, the issue we have is that the sample size is quite low - 7 males and 2 females total from both hybrid types. We are now curious if the pattern that both females show abnormal morphology is true or only an artifact of small sample size. To address this, I have just set up 10 more crosses (expectation is ~50 offspring/placentas) that L~ and I will be dissecting and doing histology to next week.

I hope to be able to present the findings at the Evolution Conference in Salt Lake in a couple months.

6-4-13 update: So far I have dissected 5 Sun x Cam (overgrown) crosses and 1 Cam x Sun (undergrown) cross resulting in 10 placentas (7 Sun x Cam and 3 Cam x Sun). I fixed these in 4%PFA overnight and used the histology lab's tissue processer to embed them in parafin. Yesterday I sectioned them and put them on slides. Now I need to stain them and then measure them.  I had forgotten how difficult and touchy sectioning is. Major props to L~ for all the sectioning she did on the earlier samples.

6-18-13 update: I have dissected everything, embedded them, sectioned them, stained them, and imaged them. I'm going to present the results at Evolution this weekend and I'll type up a post afterwards.

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Wagschal, A. and R. Feil. 2006. Genomic imprinting in the placenta. Cytogenetic Genome Research 113:90–98.

PCR amplification and the number of cycles

I had earlier decided that amplifying 8ul for 9 cycles would be good for my libraries. It turned out that 9 cycles was much to few and I increased the cycle number to 12 as per J~'s suggestion. I have now amplified all 40 samples at 12 cycles (still 8ul) and have just finished bioanalyzing the results. It seems that 12 has worked great for many of my samples, but has under-amplified a few (see below).

Of these samples, the first 4 are under-amplified, the middle 4 are fine, and the last 4 are perfect. None are over-amplified which is great. 

Next I need to pool all of these samples into two lanes as per my earlier plans. The pooling will be done so that there are equal molar ratios of each sample in the final mix. The issue I am having is that J~ and I had talked earlier and said that I should amplify each sample the same number of cycles (12) but at this point, 12 cycles has under-amplified some of them and not others. One option is to amplify the low samples a couple times more to bring them up to par with the rest. I am unsure of whether treating some samples differently will cause any catastrophic failures of my experiment. It seems like it will not as the expression analysis will be standardized by the relative expression of a number of housekeeping genes. I would guess that this should remove any effects of cycle number, but I'm not sure. I'll talk to J~ and report back.

Below is a plot of all the samples spread along the X-axis and the final concentration (ng/ul) that the bioanalyzer reported on the Y. The different colors represent different batches of library prep (batch size = 8) and the different shapes represent the different RNA extraction batches (batch size = 4). The horizontal line is at 5ng/ul.

It looks like there are no batch effects for the most part. The one main exception is in the red batch where the squares (males) are lower than the circles (females). Earlier, I had started with unequal amounts of RNA for that batch and I ended up re-doing the males. It seems that something went wrong with the 2nd prep of those, and I need to re-prep them again. As long as I am at it I will also re-prep some of the others that are below 5ng/ul. 

Cycle number in the TruSeq protocol

The qPCR results showed that 13-14 cycles would be excellent for my libraries (see this post). However, the amount of library that I started with was 1 40th of the total library (i.e. 0.5uL). If 0.5ul achieves the exponential phase in 13 cycles, then 8uL should achieve exponential phase in 9 cycles:
starting      cycles to
   ul         exponential
0.5              13
1                 12
2                 11
4                 10
8                  9
16                8

Thus I used 8uL of my libraries and amplified them for 9 cycles. This resulted in some libraries that were perfectly amplified and some that were not amplified enough. The top sample is great, a small even peak (and no secondary hump under the 1500 marker). The second sample does have a peak in the right area, but hasn't been amplified enough - there is not enough library there to sequence.

Fortunately, I only used 8uL of my pre-amplification library, not the entire 20uL just in case this issue arose. So now, instead of going back and re-preparing the entire library, I can just take and amplify the remaining parts. 

I'll need to talk to J~, as there are some serious batch effects (the first 8 all look like the top image, while the second 8 all look like the bottom image) but it looks like 8ul at 11 or 12 cycles will work fine for most everything without over-amplifying the library. As I will be comparing transcript levels, it is important that all the libraries are amplified the same number of cycles. 

Over-amplification is also bad because at that point in the PCR, the DNA molecules are being heated and cooled without being replicated. Thus they will fall apart and re-anneal repeatedly. They will often re-anneal with a DNA of a different sequence. This happens because the adapters have the same sequence, while the center sequences vary, two different molecules can meet eachother and the adapters on the ends will anneal while the middle region will for a big loop. This will mess up the sequencing machine and you'll get bad results. You know if you've over-amplified a library because there will be a low hump that around the 1500 marker. This is the weird hybridized molecules which travel slowly through a gel and so look quite large. In fact they are not any larger than the rest of the library and so can't be selectively removed via their size. The only thing that remains at that point is to re-amplify the library.

In short, I need my samples amplified more, but not too much more, so a cycle or two should be fine. J~ will be able to help me out with that. 

qPCR and strand-specific TruSeq protocol

The qPCR results of my ssTruSeq prep (Sultan, 2012) showed up a little weird:

The group of 4 that amplified first was the females (prepared on 12-15 with []'s of 512, 367, 553, and 455ng/ul from the bioanalyzer) while the second group of 4, amplifying around 14 cycles is the males (prepared on 12-7 with []'s of 3086, 5631, 1783, 2363ng/ul from the bioanalyzer).  The initial concentrations shouldn't matter much because I dilute them down to have 2ng of RNA entering the ssTruseq protocol. In this case though, it seems that I over-diluted the males causing them to amplify later. There is something really odd going on here because when I looked back through my lab book, the concentration of those samples from the nanodrop was much less: 1351, 1559, 1027, and 1276ng/ul. In fact these concentrations are ~4x less (i.e.: two pcr cycles different...). As they amplify on average 2 cycles later, I took a look back at the bioanalyzer results and found that the concentrations were slightly outside the optimal range and therefore likely a little spurious.

In the future I will dilute my samples down and then nano-drop them before I start the ssTruSeq protocol in order to avoid starting with different concentrations of RNA.

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Sultan, M., S. Dökel, V. Amstislavskiy, D. Wuttig, H. Sültmann, H. Lehrach and M.-L. Yaspo. 2012. A simple strand-specific RNA-Seq library preparation protocol combining the Illumina TruSeq RNA and the dUTP methods. Biochemical and Biophysical Research Communications 422:643–646. Elsevier Inc.

strand specific RNAseq: TruSeq Protocol + Sultan (2012)

I have begun preparing libraries for the sequencing. The Sultan (2012) protocol is nice and clear, but there are two buffers that it incorporates which are quite expensive. These buffers are parts of a second strand synthesis kit and it costs upwards of 1000$ for the kit - but the cost of the kit is due to the enzyme (which I don't use for Sultan's protocol) not the buffer. Instead of buying the entire kit, I ended up making the buffer myself (all the components cost less than 200$ total). Other than this issue with the buffer, I am quite pleased with the protocol in general.

the recipes I used are here:

5x second strand synthesis buffer  invitrogen cat #11917-010
formula: 100 mM Tris-HCl (pH 6.9), 450 mM KCl, 23 mM MgCl2, 0.75 mM beta-NAD+, 50 mM (NH4)2SO4
for 10ml:
-1ml Tris HCl pH6.9
-0.3355g  KCl
-0.23ml 23mM MgCl2
-0.0050g beta NAD+
-0.0661g (NH4)2SO4
bring to 10ml with DEPC H20


10x Reverse transcription buffer  invitrogen cat #18080051
formula: 200 mM Tris-HCl, pH 8.4, 500 mM KCl
for 10ml:
-2ml 200mM Tris HCl pH 8.4
-0.3728g KCl
bring up to 10ml with DEPC H2O


As for the TruSeq protocol, the final step is a PCR enrichment of the adapter-ligated fragments. The protocol calls for 15 cycles to enrich the product, but that will likely place the reaction in the plateau phase (really bad because it results in "PCR duplicates" and reduces the overall complexity of the library). To optimize the number of cycles that I'll end up using I am running a qPCR. This will give me an understanding of how efficiently the library amplifies and therefore how many cycles to run so that my library is in the exponential phase and not plateau.

I started with 0.5ul of ligated product in the qPCR and the concentration was well below what the Nanodrop can read (not surprising as I haven't enriched it yet, but normally a bad sign). The qPCR results show that my library plateaued in 20 cycles, so I will be shooting for 14 cycles which should be mid-exponential phase. The next trick is that when I do the actual enrichment PCR I will have a much higher amount of starting DNA (~10ul instead of 0.5ul) and so plateau will be achieved much sooner. As I will be starting with 20x more DNA, I will need 4-5 fewer cycles (2^4 < 20 < 2^5). Assuming that the amplification will procede with the same efficiency (and that the efficiency is ~2, though often slightly lower, 1.8ish), this means that in my enrichment PCR I should use 10 cycles.

I will actually run two qPCRs to test the difference between 10 and 13 cycles. This should help me hone in on the exact number of cycles to use. I can afford to do this with this library as it is a "test." I won't be doing different cycles on the future libraries that I plan to sequence.

I will need to do this same qPCR experiment on each of my library samples and determine an "average" number of cycles to use. I could enrich each sample independently, but that is a bad idea since this is transcriptome work and the relative expression levels will depend on the number of cycles. I will probably do qPCR on the first 8 to get  a good average, and then use that as the standard number of cycles for the entire experiment.

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Sultan, M., S. Dökel, V. Amstislavskiy, D. Wuttig, H. Sültmann, H. Lehrach and M.-L. Yaspo. 2012. A simple strand-specific RNA-Seq library preparation protocol combining the Illumina TruSeq RNA and the dUTP methods. Biochemical and Biophysical Research Communications 422:643–646. Elsevier Inc.

Indexing Samples

Here is my earlier plan for multiplexing the samples:

Lane 1:                      Lane 2:

BBM1+2+3              BBM3+4+5

BBF1+2+3               BBF3+4+5

BSM1+2+3              BSM3+4+5

BSF1+2+3               BSF3+4+5

SBM1+2+3              SBM3+4+5

SBF1+2+3               SBF3+4+5

SSM1+2+3              SSM3+4+5

SSF1+2+3               SSF3+4+5

Each of these numbers will have it's own unique barcode. But as I only have 24 barcodes, some will have to be repeated between the lanes. For example, BBM3 must go in both lanes and will have the same barcode. This will force BBM1 and BBM4 to share a barcode, same with BBM2 and BBM5. It will end up with barcodes 1-16 in each lane but on different samples, and barcodes 17-24 in each lane and on the same sample.

Here is a schematic of my plan:

	Sample ID	Illumina Barcode Number	Reference Number (above)	Lane
1	BB.BB15.3M	1	BBM1	1
2	BB.SS70.3M	2	BSM1	1
3	SS.BB20.2M	3	SBM1	1
4	SS.SS82.1M	4	SSM1	1
5	BB.BB15.4F	5	BBF1	1
6	BB.SS70.2F	6	BSF1	1
7	SS.BB20.6F	7	SBF1	1
8	SS.SS82.2F	8	SSF1	1
9	BB.BB77.2M	9	BBM2	1
10	BB.SS70.5M	10	BSM2	1
11	SS.BB25.5M	11	SBM2	1
12	SS.SS87.1M	12	SSM2	1
13	BB.BB77.1F	13	BBF2	1
14	BB.SS70.4F	14	BSF2	1
15	SS.BB25.3F	15	SBF2	1
16	SS.SS87.3F	16	SSF2	1
17	BB.BB86.2M	17	BBM3	both
18	BB.SS72.2M	18	BSM3	both
19	SS.BB25.3M	19	SBM3	both
20	SS.SS88.1M	20	SSM3	both
21	BB.BB86.1F	21	BBF3	both
22	BB.SS72.1F	22	BSF3	both
23	SS.BB29.1F	23	SBF3	both
24	SS.SS88.3F	24	SSF3	both
25	BB.BB87.6M	1	BBM4	2
26	BB.SS73.3M	2	BSM4	2
27	SS.BB20.8M	3	SBM4	2
28	SS.SS89.2M	4	SSM4	2
29	BB.BB87.1F	5	BBF4	2
30	BB.SS73.1F	6	BSF4	2
31	SS.BB24.2F	7	SBF4	2
32	SS.SS89.1F	8	SSF4	2
33	BB.BB77.3M	9	BBM5	2
34	BB.SS71.3M	10	BSM5	2
35	SS.BB22.4M	11	SBM5	2
36	SS.SS91.1M	12	SSM5	2
37	BB.BB90.1F	13	BBF5	2
38	BB.SS73.2F	14	BSF5	2
39	SS.BB24.3F	15	SBF5	2
40	SS.SS91.4F	16	SSF5	2

Furthermore, I will need to prepare these in even batches to avoid any weird batch effects. I will therefore do them in 5 batches of 8. Each batch will have one male and one female from each cross type.

I'll start the first batch (numbers 1-8) tomorrow.