June 28, 2016

Like Tony Curtis and Jack Lemmon in “Some Like it Hot”, some transcription factors take on dual roles. Image from Wikimedia Commons.
According to an AFI poll, the best comedy of all time was the 1959 film “Some Like It Hot.” In this classic screwball comedy two men have to dress up as women to escape the mob and still make money as musicians. All sorts of hilarity ensues as one of them falls in love with a woman and a man falls in love with the other as a woman.
The key to this comedy is that the two actors, Tony Curtis and Jack Lemmon, have to play both the male and female parts. If they were played by separate actors and actresses, the movie would die at the box office. It would be a lethal mutation.
A new study by Solis and coworkers in Molecular Cell presents evidence that in yeast, the heat shock transcription factor Hsf1p is a bit like Tony Curtis and Jack Lemmon—it plays dual roles, both in maintaining basal levels of various heat shock proteins and in turning the appropriate genes up in response to a heat shock. This is different than in mammalian cells where HSF1 is only responsible for turning up heat shock genes in response to a spike in temperature. Something else maintains the levels of these proteins needed for survival.
So yeast is more like the comedy “Some Like it Hot,” or perhaps Tootsie, while mammalian cells are more conventional comedies where different actors play the male and female roles. Because Hsf1p plays a dual role in yeast, its deletion causes the cell to die. Mammalian cells can survive without HSF1 as long as it doesn’t encounter any temperature spikes.
Solis and coworkers started out by coming up with a way to dissociate the genes that Hsf1 regulates under normal conditions from those upregulated under heat shock conditions. For this they used the “Anchor-Away” approach to remove Hsf1p from the nucleus under normal conditions.
Basically, they co-expressed HSF1 fused to FRB, the FKBP rapamycin-binding domain, and a ribosomal protein L13A-FKBP12 fusion. When they add rapamycin to this strain, the two proteins heterodimerize and Hsf1p is dragged out of the nucleus. They confirmed that Hsf1p was gone from the nucleus within a few minutes.
Next, they used native elongating transcript sequencing (NET-seq) 15, 30, and 60 minutes after rapamycin addition to see which genes were affected when Hsf1p left the nucleus. They found that only 25 genes were repressed and five were induced at these time points. Using RNA-seq and ChIP of Hsf1p they showed that Hsf1p was probably responsible for the expression of 18 of the 25 repressed genes and none of the induced ones.
So yeast Hsf1p is involved in the basal expression of a number of chaperone genes. In a set of experiments that I don’t have time to go over here, they also showed that most of the heat shock response was independent of Hsf1p in yeast. Their data suggests that Msn2/4p may be the key player instead.
They next did a similar set of experiments in mammalian cells but with a couple of differences. First off, these cells can survive HSF1 deletion, meaning they didn’t need to do anything fancy—they just used CRISPR/Cas9 to delete the gene in mouse embryonic stem cells and mouse embryonic fibroblasts.
Under normal conditions they found that the deletion of this gene caused two genes to go up in expression and two to go down. This is what you might expect by chance suggesting that in mammalian cells, HSF1 isn’t involved in basal expression of any genes.
They next used RNA-seq to compare gene expression of these cells and their undeleted counterparts under normal and heat shock conditions. They found a set of nine genes that were induced in both wild type cells and repressed in the HSF1-deleted cells under heat shock conditions. Eight out of nine of these are involved in chaperone pathways and they overlap surprisingly well with the yeast genes that Hsf1p controls under basal conditions.
Taken together these experiments paint an interesting picture. In yeast, HSF1 is mostly responsible for the basal expression of chaperone genes, and in mouse cells it is a key player in the heat shock response of a similar set of genes. This suggests that deletion of HSF1 is lethal in yeast because the decreased expression of one or more of the genes it regulates under normal conditions.
In cancer cells, HSF1 takes on dual roles, like both Curtis and Lemmon in “Some Like it Hot”. Image from cinema-stache.com.
They tested this by expressing 15 of the 18 genes (three are redundant to some of the others) on four different plasmids and saw that a yeast strain that is deleted for HSF1 now survives. So one or more of these genes is responsible for yeast death in the absence of HSF1.
Through a process of elimination, Solis and coworkers found that the key genes were SSA2, a member of the HSP70 family, and HSC82, an HSP90 family member. The decrease in expression of these two genes cause by the deletion of HSF1 results in a dead yeast cell.
These experiments are so cool. In yeast, HSF1 makes sure there is enough of these chaperones around in good times to fold proteins properly and has a minor role in the heat shock response, while in mouse cells, the same gene plays no real role in basal levels of expression of chaperone genes and instead is critical for responding to heat shock. The protein regulates similar genes, just under different conditions.
These neat science experiments can tell us more about diseases, like cancer too. Turns out that some cancer cells may be more like yeast cells in that deletion of HSF1 stops them from growing and causes an increase in poisonous protein aggregates which may give us a new way to target HSF1-dependent cancers. For example, it may be that targeting Hsp70 or Hsp90 could be useful for treating HSF1-dependent cancers.
In cancer cells then, HSF1, like Dustin Hoffman in Tootsie, Milton Berle in the Milton Berle Show, or Bugs Bunny in many different cartoon shorts, takes on dual roles in the cell. And as we learned from yeast, this could be these cancers’ Achilles heel.
by Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
Categories: Research Spotlight, Yeast and Human Disease
June 22, 2016

Image from http://biology.uiowa.edu/.
Model Organisms such as yeast, worm, fly, fish, and mouse are key drivers of biological research, providing experimental systems that yield insights into human biology and health. Model Organism Databases (MODs) enable researchers all over the world to uncover basic, conserved biological mechanisms relevant to new medical therapies. These discoveries have been recognized by many Nobel Prizes over the last decades.
NHGRI/NIH has recently advanced a plan in which the MODs will be integrated into a single combined database, along with a 30% reduction in funding for each MOD (see also these Nature and Science news stories). While integration presents advantages, the funding cut will cripple core functions such as high quality literature curation and genome annotation, degrading the utility of the MODs.
Leaders of several Model Organism communities, working with the Genetics Society of America (GSA), have come together to write a Statement of Support for the MODs, and to urge the NIH to revise its proposal. We ask all scientists who value the community-specific nature of the MODs to sign this ‘open letter’. The letter, along with all signatures, will be presented to NIH Director Francis Collins at a GSA-organized meeting on July 14, 2016 during The Allied Genetics Conference in Orlando. We urge you to add your name, and to spread the word to all researchers who value the MODs.
In other words, sign this letter!
Categories: Announcements, News and Views, Yeast and Human Disease
June 09, 2016

It is worth a pause before leaping into action. This is true at the edge of a cliff, making a life or death situation, and before DNA repair. Cliff jumping image from Evan Bench on flickr, emergency technician image from Wikimedia Commons
Sometimes in an emergency, it can be useful to take a pause before trying to fix a problem. If the ambulance is on the way you may not want to start removing someone’s appendix right then and there. Yes you may save them, but the ambulance and EMTs will do less damage to the patient once they get there.
The same sort of logic applies to cells too. For example, a double stranded break is a deadly emergency that can wreak havoc with a cell’s genome.
The cell can deal with this in a few ways; the big two being non-homologous end joining (NHEJ) and homologous recombination (HR). NHEJ is the simplest in that the broken ends are simply stuck back together. However, it often results in a bit of DNA damage as a few bases are added or lost at the ligation point.
The other option, homologous recombination (HR), involves using a homologous DNA region as a template to essentially resynthesize the broken area. There are two possible ways this can happen in a cell: gene conversion and break induced replication (BIR).
If both ends are available without too much of a gap and in the right orientation, the cell opts for gene conversion, the safer of the two options. Only a small section of DNA is resynthesized, keeping most of the original DNA intact.
It is a different story for BIR, the second approach. Here, a large swath of DNA gets resynthesized, meaning a big loss of heterozygosity (LOH)—two sections of DNA are now identical over a large region. BIR only happens when there is only one end available or when there is a big gap of missing DNA.
Of the two HR possibilities, gene conversion is preferable over BIR. This is why the cell wisely waits to make sure there is no other option before starting down this path. This pause goes by the name of recombination execution checkpoint (REC).
A new study by Jain and coworkers out in GENETICS has identified two of the key players involved in this checkpoint—SGS1 and MPH1. Both are highly conserved 3’ to 5’ helicases.
These researchers found that when both are deleted, the REC disappears. And that isn’t all. In situations where the wild type cell would choose to repair its DNA by BIR, the double deletion strain no longer does. Instead, it now uses a process that is more similar to gene conversion.
Jain and coworkers found this using a reporter that contained an HO endonuclease site in the middle of the LEU2 gene. Once the HO endonuclease is activated, it makes a double strand DNA break, cutting the LEU2 gene in half.
The cell was provided with a variety of templates to be used in HR. One of these only provides the part of the LEU2 gene to the right of the HO endonuclease site. As only one of the ends has homology to the cleaved LEU2 gene, with this template, the cell can only use BIR to repair the break.
The researchers saw a huge increase in how fast the DNA was repaired using the BIR-only template in the strain deleted for both sgs1 and mph1 compared to the wild type strain. The double mutant repaired the DNA using BIR nearly as quickly as a wild type cell could using gene conversion. The pause before repair was essentially lost in the double mutant.
The double deletion strain wasn’t just faster with the BIR-specific template either. It repaired DNA via this pathway about 4 times better than the wild type strain did.
There are at least a couple of different reasons why the double mutant could be so much better at repairing DNA in BIR situations. In the first, the cell is just better at BIR—it can initiate the BIR pathway much more quickly than wild type. The second possibility is that this double mutant isn’t using the BIR pathway anymore and is using something closer to gene conversion.
Jain and coworkers found that the second option is the more likely of the two. The way they figured this out was to make a mutation in the POL30 gene, a gene required for DNA repair by BIR but not gene conversion. So, they tested what happens when POL30 is mutated in the wild type and the sgs1 mph1 double deletion strains.
They found that while a dominant negative mutant of pol30 had the predicted effect of severely compromising repair in wild type cells using their BIR-specific reporter, it had no effect in the double deletion mutant. Since Pol30p is needed for the BIR pathway, the strain deleted for sgs1 and mph1 must be using a different pathway to fix the DNA damage. So the pause is eliminated because the cell isn’t really using the BIR pathway anymore.

Image from The Petrick on vimeo
We don’t have time to go into it here, but there is a lot more research in this paper that looks at why the REC might be lost and that probes the differences in how MPH1 and SGS1 influence the BIR pathway that I encourage you to read. For example, deleting SGS1 is not identical to deleting MPH1 in terms of the BIR DNA repair pathway. And each single mutant still uses the BIR DNA pathway as the pol30 mutation severely compromises the ability of each to repair the BIR-specific reporter.
There is a lot more fascinating stuff like this in the study. The bottom line, though, is that MPH1 and SGS1 are the level-headed people urging folks not to panic and to wait for the EMTs to get to the accident scene to help. When MPH1 and SGS1 are gone, the cell dives right in and starts repairing breaks without waiting for the safest option—gene conversion. Who knows what havoc is wreaked in their absence!
by Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
Categories: Research Spotlight
June 06, 2016
We’ve added 1,400 high-throughput (HTP) cellular component GO annotations from a new paper published by Maya Schuldiner’s lab. In this paper, Yofe et al., 2016 devised and implemented a methodology, called SWAT (short for SWAp-Tag), creating a parental library containing 1,800 strains, all known or predicted to localize to the yeast endomembrane system. Once created, this novel acceptor library serves as a template that can be ’swapped’ into other libraries, thus facilitating the rapid interconversion to new libraries by simply replacing the acceptor module with a new tag or sequence of choice. As proof of principle, this paper describes the parental library (N’ SWAT-GFP), and its utility as a gateway to the construction of two additional libraries (N’ mCherry and N’ seamless GFP). A high-content screening platform was used to generate images that were then manually reviewed and used to assign subcellular locations for proteins in these collections. Based on these results, SGD has incorporated GO annotations for proteins when at least two of three tags gave the same cellular localization. In addition, Locus Summary page descriptions for genes within this collection that did not have a known cellular location prior to this study have been updated. Finally, this study also provides access to a list of proteins predicted to contain signal peptides using three different algorithms. We would like to thank Maya Schuldiner and members of her lab for help with the integration of this information into SGD.
Categories: New Data
June 01, 2016

Image courtesy of The Internet Speculative Fiction Database.
In the Foundation series by Isaac Asimov, Hari Seldon invented a field of study called psychohistory which was able to “make general predictions” about human history. It only worked because the population of the Galactic Empire was in the quadrillions. You need huge numbers to get useful predictions.
Sometimes real life biologists need lots of individuals to see what they are looking for too. In the case of a recent paper in PNAS by Lee and Stevens, they needed to sift through half a trillion yeast to find what they were looking for. And boy was it worth it!
They saw an intron jump from one gene to another. Twice. In 500 billion tries.
This is the first example where we have caught an intron in the act of moving from one place to another. This has important implications for the study of evolution where over time introns spread or recede. It might even help us better understand cancer where intron loss can play a role.
Seeing something as rare as this means making a very specific, complicated reporter. You don’t want to manually sort those 500 billion colonies…or at least I wouldn’t want to.
Here is a “simplified” schematic of the reporter they came up with:

It is as complicated as it looks but it got the job done! Let me walk you through what everything is and how it works.
The GU and AG sequences are splice site junctions. Sequences between a GU and an AG can be spliced out.
The red gene is the S. pombe his5+ gene that has a promoter driving its expression shown with the red arrow. It is in the reverse orientation compared to the eGFP gene which is under the control of the promoter represented by the blue arrow.
The S. pombe his5+ gene works fine in S. cerevisiae his3 mutants to make up for histidine auxotrophy. But it won’t work from this construct.
See, the his5+ gene has an intron that keeps it from being translated correctly unless the intron is spliced out. But this intron can’t be spliced out when the gene is transcribed using the red promoter because the splice junctions GU2 and AG1 are in the wrong orientation. Any transcripts from the red promoter will not work because the intron cannot be spliced out.
You also can’t get His5 from the blue promoter. Even with splicing (which will work in that orientation), the gene can’t be translated because it is in the wrong orientation.
To get any his5+ transcript, the yeast needs to take the spliced RNA from between GU1 and AG2 and get it into DNA. It also needs to get rid of the intron in the middle of his5+ gene before it happens.
So what they are looking for are yeast that glow green and can survive in the absence of histidine. There are a couple of ways this can happen.
The more common way results in the his5+ gene recombining back into the plasmid such that the intron is missing from its middle. Basically the RNA between GU2 and AG1 is spliced out and the resulting RNA is reverse transcribed into DNA. This DNA then undergoes homologous recombination with the plasmid DNA resulting in a working his5+ gene. They got over 10,000 of these in their experiment.
The much less common way involves the intron being inserted into a gene within the genome. This way uses some of the same steps with one extra one—a reverse splicing event.
As I said, they got two of these with one ending up in the RPL8B gene and the other in the ADH2 gene.
Here’s how they think this happened…
The spliced out RNA from the plasmid was left for a brief time in the spliceosome (or what remained of it after the splicing reaction). During this time, a second mRNA arrived for splicing while the intron from the reporter was still there.
Then something called reverse splicing happened which basically replaced the native intron of the RPL8B or the ADH2 gene with the spliced out intron from the reporter. Next this was turned into DNA with reverse transcriptases and then this construct ended up in the genome through homologous recombination.

Only with yeast can we sift through 500,000,000 cells to find the two introns that have moved to new genes. Image from Needle in a Haystack, on Tumblr.
No wonder this was so rare! Reverse splicing is thought to be really uncommon in vivo as is reverse transcription of DNA. Add in a loitering intron on the remnants of a spliceosome and you can see why this was a 1 in 250 billion shot.
So there you have it, one way a transposon can hop. It is no transposon, but occasionally an intron can move to a new gene.
And of course we turned to the awesome power of yeast genetics to help us figure this out. Only with yeast can we sift through half a trillion cells to find the two that show us how intronogenesis, the introduction of an intron to a new site, might happen. #APOYG!
by Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
Categories: Research Spotlight
Tags: mobile intron, reverse splicing
May 26, 2016

If you’re not already using JBrowse to view all your favorite S. cerevisiae genes…you should be! SGD’s JBrowse is a quick and easy way to browse through the information-rich yeast genome. Using JBrowse, you can visualize spatial relationships between genes, locate SGD annotations throughout the yeast genome, and align chromosomal features to hundreds of experimental data sets.
Our upcoming webinar on June 1st will provide a short 15-minute tutorial on the basics of JBrowse. We will demonstrate how to navigate the genome with JBrowse, locate your favorite genes or chromosomal features, and visualize experimental data with data tracks. Whether you’re an experienced GBrowse user looking to try JBrowse for the first time, or someone new to genome browsing as a whole, this webinar is sure to help you get started.
If you are interested in attending this event, please register using this online form: http://bit.ly/SGDwebinar3
This is the third episode of the SGD Webinar Series. For more information on the SGD Webinar Series, please visit our wiki page: SGD Webinar Series.
Categories: Announcements, Tutorial
May 18, 2016

CRISPR can now be used like a ‘find in genome’ function.
A long time ago, through the mists of time, finding a phrase or a passage in a document was hard. If you didn’t have the foresight to highlight it, you were stuck.
You could reread the whole document but that might take way too much time. Or you could narrow down where to look by remembering the chapter it was in and rereading just that.
Nowadays of course, finding that phrase or passage is trivial in a Google or Word doc. You just use the find function!
Finding the genetic variant responsible for a given trait is still, in many ways, in the age of the typewriter. A genetic association study can find a part of the DNA responsible for that trait but homing in on the exact variant is terribly time consuming and labor-intensive.
Enter that wonder of a gene editing tool, CRISPR.
In a new study in Science, Sadhu and coworkers have essentially turned CRISPR into a find function for genetic association studies. They use CRISPR’s double stranded DNA cutting ability and mitotic recombination in a heterozygote yeast strain to blanket a region of DNA with crossover events.
Sifting through the results let them find the actual amino acid change responsible for manganese sensitivity with much less effort than would have been required with the old method. They only needed to use 358 lines instead of the 7,500 or so they predict they would have had to go through without good old CRISPR.
And think how much time might be saved with a more complicated beast! Given its short generation time and relatively small genome, yeast is like a magazine article. A human is more like War and Peace. This new system might make linking human traits/diseases to the causative SNP much simpler.
The usual way to link a trait to the DNA that causes it is to see what known traits tend to get passed down with it. If you know trait A is at position X on chromosome Y and the trait you are interested in, trait B, is usually passed down with A, then trait A and trait B are close to each other (this is called linkage mapping). This is the easy part.
The hard part is getting from A to B. To get finer mapping, you need to rely on the recombination that happens during meiosis. This is the step where this new study can help.
Instead of relying on the slow, natural process of meiotic recombination, these authors use the CRISPR-Cas9 system to jump start mitotic recombination.
They start off with a heterozygote in which one of the parent strains has a trait and the second does not. They chose the lab strain, BY, and the vineyard strain, RM, as the parents.
Next they designed 95 guide RNAs that would direct Cas9 to 95 different spots along the left arm of chromosome 7. Sadhu and coworkers targeted sites that were heterozygous in the two strains.
Once Cas9 cuts the DNA, the cell uses homologous recombination to repair the cut using the DNA on the other chromosome in the pair as the template. This results in a loss of heterozygosity (LOH) which can reveal recessive traits.
They picked 384 lines, approximately 4 from each cutting event and found that 95% of these had undergone LOH with hardly any off-target effects.
They next measured the growth of these strains in 12 different conditions and found that one trait, growth on 10 mM manganese sulfate could work for their purposes. Using the more traditional approach with 768 segregants obtained through meiotic recombination, they were able to narrow it down to an overlapping piece of DNA of 3,900 bases. However, using CRISPR-Cas9, they were able to narrow down the location of the variant to a 2,900 base pair stretch of DNA. Score one for the new method!
Next they did finer mapping by targeting the 2,900 bases they had identified with CRISPR-Cas9. Even though they only used three guide RNAs that targeted three locations, they were able to look at many more places on the DNA than this because the length of DNA repaired around the cut varies a bit between strains.

Targeting recombination events to regions of interest allows rapid, systematic identification of causal variants underlying trait differences. Image from SQUARESPACE.
They isolated 358 lines of which 46 or 13.1% had a recombination event in the 2,900 bases they were interested in. Only 0.7% of segregants obtained the old way were in the right place. Score another one for the new method!
After measuring how well these 46 lines grew in manganese sulfate, the researchers were able to narrow the search to a single polymorphism that resulted in an amino acid change in the PMR1 gene. A perfectly reasonable result, given that Pmr1p is a manganese transporter. They then showed that this variant, pmr1-F548L, did indeed make a strain sensitive to manganese all on its own.
By targeting recombination events to regions of interest, these authors have provided proof of principle for a technique that should make connecting traits (phenotype) with DNA variants (genotype) much easier than it is currently. Behold yet again the awesome power of yeast genetics (#APOYG)!
by Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
Categories: Research Spotlight
Tags: CRISPR/Cas9, genotype, mapping, phenotype
May 10, 2016
SGD’s new JBrowse genome browser allows quick and easy browsing of the information-rich yeast genome.
Take a look at our newest video tutorial to learn how to download or upload JBrowse data tracks. Let us know if you have any questions or suggestions.
For more SGD Help Videos, visit our YouTube channel, and be sure to subscribe so you don’t miss anything!
Categories: Tutorial
May 04, 2016

Sometimes when there should be two ways to get someplace, there is only one. What is true for mapping apps can also be true for mutations that increase fitness. Image from flickr.
As HBO’s Silicon Valley scathingly relates, the mapping app from Apple was truly terrible when it was first launched. There are all kinds of funny (scary?) stories in which people following the directions ended up in the wrong place. (Click here for a few more of the epic fails.)
And sometimes it would show impossible ways to get from one location to the other. For example, to get to a certain place, my iPhone would recommend two different routes. After choosing the seemingly easiest route I quickly realized that it would take me through a building. Sometimes, even though it seems there are a couple of different ways to get somewhere, there is actually only one.
It turns out that this can be true in gene expression too. While you might increase expression by either mutating the promoter or duplicating the whole gene, sometimes only duplication is enough. There is just one route from here to there.
This point is driven home in a new study out in GENETICS by Rich and coworkers. Here they show that, under sulfate-limiting conditions, the only way that yeast can boost the expression of the SUL1 high affinity sulfate transporter enough to thrive is by duplicating it.
In many previous experiments, whenever yeast is starved for sulfate, after 100 generations or so the population almost always ends up selecting for a SUL1 duplication rather than increasing expression with a promoter mutation. This duplication results in a fitness advantage of 35% or more, which makes sense – when there isn’t much sulfate available, those cells that can get more of what’s there will outcompete their neighbors.
There are a couple of possible reasons things go down like this. It could be that the duplication is simply the most likely way to increase expression enough to survive, meaning that promoter mutations are possible but rare. Alternatively there may be no way to mutate the promoter enough to adequately increase the activity in such a short window of time. You simply can’t get to enough increased fitness by this route.
The first step in figuring out how to get somewhere is to map the roads in the area. This is also what Rich and coworkers needed to do – they needed to figure out how SUL1 is regulated. They did this in the standard way by nibbling away bits of the sequences upstream of the gene until there was a significant impact of gene expression. This is how they identified the 493 base pairs upstream of SUL1 as its promoter.
In the meantime, they also managed to develop a broadly applicable methodology for investigating any promoter – saturation mutagenesis, chemostat selection, and DNA sequencing to track variants.
The next step was to generate a library of mostly single point mutations in this promoter using error-prone PCR. As might be expected, most of the mutants had no effect or decreased gene expression but a few did increase activity. However, none of these last set increased expression as much as duplicating the gene.
They found 8 mutants that gave a 5% or better increase in fitness with the best being a 9.4% increase. Even when they combined these point mutations they could not increase the fitness much beyond 11%, not even half of the increase in fitness that an extra SUL1 gene gives. It seems that to get the most bang for its buck, yeast needs to duplicate SUL1. At least in the time frame of the experiment, that is.

Point mutations just can’t hold a candle to simply duplicating the SUL1 gene. Image from flickr.
Using what is essentially the scanning mutagenesis of this promoter, they were able to identify three sites that were important for SUL1 regulation. One site at -465 to -448 corresponded to a Cbf1-Met28-Met4 regulatory site, the second site at around -407 was most similar to either a Met31 or Met32 site and the third site at around -350 matched a Met32 site.
Mutations that resulted in increased activity tended to bring one of these three sites closer to the consensus transcription factor binding site. For example, the strongest point mutation, -353T>G, did this with the Met32 site at -350.
Even with these stronger consensus sequences for sulfate-regulatory transcription factors, none of these point mutations could get the yeast to where it needed to be in the fitness landscape in order to be able to thrive under sulfur limitation. Point mutations just can’t hold a candle to simply duplicating the SUL1 gene. Sometimes there really is just one way to get from point A to point B.
by Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
Categories: Research Spotlight
Tags: adaptation, chemostat selection, fitness, gene duplication, saturation mutagenesis
April 26, 2016

If you’re not already using YeastMine to answer all your questions about S. cerevisiae genes and gene products…you should be! SGD’s YeastMine is a powerful search tool that can retrieve, compare, and analyze data on thousands of genes at a time, greatly reducing the time needed to answer real, practical research questions. Through YeastMine, questions such as “What proportion of plasma membrane proteins are essential?” or “How many different gene products physically interact with the mitochondrial ribosome?” can be answered within minutes.
Next week on May 4th, 2016 at 9:30 AM PDT, we will provide a brief webinar tutorial on how to run queries and create gene lists in SGD’s YeastMine. As a practical demonstration of YeastMine, we will also showcase a research scenario in which yeast-human homology data is used to predict potential chemotherapy targets for human cancers.
Space for this webinar is limited. To reserve your spot, please register for the event using this online form: http://bit.ly/registerFor2ndSGDwebinar
This is the second episode of the SGD Webinar Series. If you missed the first one, or if you’d like to find out more about upcoming webinars, please visit our wiki page: SGD Webinar Series.
Categories: Announcements, Yeast and Human Disease