Meier-Gorlin Syndrome (MGS) is a rare form of primordial dwarfism characterized by a short stature, small external ears, and absent kneecaps. Recently, mutations in the pre-replication complex (pre-RC) were linked to MGS. The pre-RC is composed of multiple proteins that must be present in order to initiate DNA replication. Although a genetic link has been made for MGS, it is unclear how these mutations cause the phenotypes observed in humans. To better understand the mutations’ phenotypes on a cellular and molecular level, our lab is utilizing the budding yeast, Saccharomyces cerevisiae. The MGS mutation in the Origin Recognition Complex (ORC) subunit six (ORC6) of the pre-RC occurs in a highly conserved region of the protein where there is a single amino acid substitution (Tyrosine to a Serine) in the C-terminal helix. Since the mutation is conserved from human to yeast, it is predicted that the function of the mutations is also conserved. I introduced the equivalent mutations into budding yeast (orc6^MGS), to investigate the consequences of harboring the MGS mutation on a molecular and cellular level and to elucidate complex genetic interactions these proteins may be involved in. The residues in ORC that recognize origins are unknown. Investigation into this mutation has the potential to illuminate the mechanism behind ORC in eukaryotic cells. The assays performed in this project have exciting implications for the model by which replication initiates and the consequences of a single mutated protein. This genetic approach will hopefully provide insight to how the conserved orc6^MGS mutation is functioning, which has the potential to be translated to the human condition.

Flowering plants exhibit diverse forms of floral symmetry that represent many independent changes throughout their evolutionary history. The selective and genetic basis to these changes has provided scientists with a complex puzzle that Darwin once referred to as an “abominable mystery.” Recent genetic studies began to uncover the genetic causes for this mystery, revealing the presence of certain genes that show correlations with this evolutionary trend. One such gene, the CYCLOIDEA (CYC) gene, has been identified as a major contributor to changes of floral symmetry. We have found this gene in the sequenced genome of Rhododendron williamsianum where it has experienced multiple duplications. The goal of my research is to identify the main duplications in one of the CYC copies (CYC2) in the Rhododendron genus. I accomplished this by using polymerase chain reactions to isolate any CYC2 copies present in two species from each of the subgenera of Rhododendron: Hymenanthes, Azaleastrum, Therorhodion, and Rhododendron. I then used cloning and sequencing to obtain the sequences of the CYC2 copies from each of the sampled species. I will conduct a phylogenetic analysis of these sequences in order to reconstruct a gene tree that will display a summary of the main CYC2 duplications that have occurred in the genus and when they emerged. Preliminary results from four species sampled thus far show that two independent duplications in CYC2 have arisen in both Hymenanthes and Rhododendron. My expanded analysis, sampling species from additional subgenera, will provide a more thorough history of this gene and its duplications throughout the genus. This will allow for more robust testing for correlation between symmetry and gene duplication in the future.

Understanding the genetic changes by which organisms adapt to novel and extreme environments is a central goal of evolutionary biology. One mechanism that may offer a rapid path to adaptation is hybridization: the union of two genetically distinct populations or species. Hybridization may transport beneficial genetic variation from a related species or may stimulate new variation to form within genomes, such as the mobilization of transposable elements (TEs). Transposable elements are large, repetitive sequences that can independently move around the genome, and thus mediate a cascade of large-scale changes in chromosome structure, gene expression, and gene content. I am interested in studying whether TE insertions occur more frequently in hybrid species vs. parental species and identifying the types of genomic changes TE insertions facilitate in hybrids. To do this, I am using a two-part approach in the model system of budding yeast, Saccharomyces cerevisiae. First, I am performing fluctuation assays to assess the rate of transposition in S. cerevisiae, its relative Saccharomyces uvarum, and an interspecific hybrid of the two. Second, I am using sequencing to identify novel TE insertions in hybrids evolved in nutrient-limited environments. If TEs do play a role in hybrid adaptation, I would expect to map transposition events with sequencing data and identify associated chromosome rearrangements and/or gene disruptions that may confer a fitness benefit. I also hypothesize finding higher transposition rates in the S. cerevisiae x S. uvarum hybrid clones compared to the non-hybrid parental clones. In doing so, I hope to gain a deeper understanding on the genetics of hybrid adaptation, which has yet to be studied in greater detail in the field of experimental evolution.

Chromatin immunoprecipitation coupled with massively parallel DNA sequencing (ChIP-seq) is the gold standard for assaying the binding sites of chromatin-binding proteins and their modifications, such as histone tail modifications. One major limititation for this method is that it requires large amounts of starting material, therefore limiting applications in those cases where only a limited number of cells can be recovered, e.g. rare cell populations obtained directly from patients. In the last few years, great efforts have been made to develop new ChIP-seq protocols to overcome this limitation. In my lab, they have developed a method called carrier ChIP-seq (cChIP-seq). The method is based on the use of a DNA-free carrier to enhance recovery of DNA after IP. Using cChIP-seq they have been able to perform ChIP-seq on 10,000 cells for several histone tail modifications. I tested a series of modifications on the cChIP-seq protocol. The goal of my project was to develop a protocol that can be performed in one day. Currently the cChIP-seq protocol takes 3 days to be complete. This is mainly due to two overnight incubations. The first one is the immunoprecipitation, so I performed multiple trials to identity the minimum time sufficient for immunoprecitating the chromatin. The second overnight incubation is to reverse crosslink immuneprecipitated chromatin. I tested a version of the cChIP-seq protocol for native chromatin, meaning the DNA is not crosslinked. By optimizing and combining these two modifications I was able to shorten the cChIP-seq to a single day. Through my project I contributed to a larger project with the goal of scaling down the number of cells used for ChIP-seq.

Honeybees (Apis mellifera) use a caste system to organize individuals into different roles. The queen is the only bee in the hive to ingest royal jelly and the only fertile female. Many sterile workers perform different jobs in their short lives, moving from larvae-nurse to keeping the hive clean to foraging for food. At each stage the worker bees learn a new task. Such different phenotypes and behavior would indicate a difference in gene expression in the brain. In a population of organisms that are genetically similar, these changes in gene expression must be explained in chemical modifications of the genome, or the epigenome. Thus far, much attention has been given to DNA methylation as an epigenetic feature known to be associated with variation in gene expression. Royal jelly, however, contains butyrate, a histone deacetylase inhibitor, which suggests that histone tail modifications could be a major mechanism for regulating gene expression in queen bees. To further investigate the role of histone modification in determining honeybee caste division, we are performing chromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-seq) to profile key chromatin modifications: H3K27ac, and H3K27me3. H3K27ac and H3K27me3 are histone modifications that have opposing effects; where H3K27ac marks active regions of the genome, and H3K27me3 is indicative of repressive chromatin. We anticipate when using ChIP-seq to map chromatin modification in the brains of queen and worker bees, we will observe key differences in genome regulation and be able to identify genes important to honeybee behavior. As an initial step toward achieving our goal, we describe the chromatin state of brains from forager honeybees.

Global climate change causes weather patterns to be increasingly unpredictable, which has a major impact on plant productivity. Humans are dependent on the agricultural economy and loss of crop productivity would be devastating. Due to their sessile nature, plants are unable to escape environmental stresses and must be able to acclimate to rapidly changing conditions. Arabidopsis thaliana is an important plant model organism, which has around 30,000 genes (about as many as humans). Arabidopsis genes have been identified, but not fully characterized, which is why it is the optimal model organism to work with. There are also many genomic tools available in the reference organism Arabidopsis. One such tool is RNA interference. Using small RNAs, we knockdown an accumulation of gene products and screen to find which genes play important roles in that particular function – drought resistance, for example. In our Arabidopsis RNAi screen, we chose to use trans-acting small-interfering RNAs (tasiRNAs) for multiple reasons. TasiRNAs have a lower chance of off-target transcript silencing than other siRNAs. They are naturally occurring in plants and have a low chance of transgene silencing. Lastly, multiple tasiRNAs can be incorporated into the library at different positions at varying concentrations. Our RNAi screen includes tasiRNAs that target every gene in the Arabidopsis genome, which allows for easy identification of causative changes and the ability to screen for multiple phenotypes with one library. These screens allow us to identify essential genes and other complex interacting gene systems important to plants under various environmental stresses. In the future, this technology can be developed on a bigger scale with crops.

From blood vessels to the small intestine to the spinal cord, tubes are an essential part of nearly all living organisms. The study of the formation of biological tubes, called tubulogenesis, is therefore indispensible in the understanding of the developmental pathways that, when impaired, cause many of the birth defects that afflict infants today. Our lab uses the fruit fly Drosophila melanogaster as a model organism to study these complex pathways. Recently, we discovered that a family of genes known as Imaginal Disc Growth Factors (IDGFs) are linked to tubulogenesis in fruit flies. However, the mechanisms by which these genes act, and their involvement in the tubulogenesis pathway, remain unclear. My project investigates the function of a specific IDGF, the gene CG5210, using a powerful new method for deleting genes known as the CRISPR/Cas9 system. With this technique, I created flies lacking the CG5210 gene by first designing highly specific plasmid vectors, which encoded RNAs that bound to the target DNA. When injected into fly embryos, these RNAs directed the Cas9 protein to cleave the DNA on either side of CG5210. Cas9 then replaced the gene with DNA that encodes a red fluorescent protein expressed in the eyes of the fly. The fluorescent red eyes served as a marker for a successful deletion in my later experiments. If my initial hypothesis is correct, I expect to see unusual phenotypes in these mutant flies that correlate with tube formation or growth pathways. From there, the next phase of my research will include further exploration of this genetic pathway, including determining what other genes and pathways interact with CG5210 to cause similar mutant phenotypes. This information will be an important contribution to our understanding of tubulogenesis and provide new insight into disease pathways that cause defects such as spina bifida in newborns.

Cellular growth and tissue elongation are critical features of development, but the mechanisms that regulate these processes remain poorly understood. Our lab, however, uses the fruit fly, Drosophila melanogaster, as a model organism to study these complex pathways and we recently discovered that a novel family of six growth factors may play a role in the development of the adult fly. IDGFs were first discovered by Dr. Peter Bryant in 1998 while attempting to culture individual cells taken from the wing imaginal disc. He found that the wing-disc cells secreted factors that would help cultured cells grow, but further experiments were not conducted to test their function in the wing disc. To begin to test whether these genes play a role in vivo, I am using in situ hybridization to localize the mRNA sequences. I found that IDGF 1, 2, 3, and 4 transcripts are present in the wing blade and hinge regions, and I am currently characterizing IDGF 5 and 6 expression. My long-term goal is to determine the function of the IDGFs; I will use a yeast transcription factor, Gal4, to drive expression of IDGFs from Upstream Activating Sequences (UAS) and examine whether over- or mis-expression alters the growth of the wing. I will also use Gal4/UAS to express RNA that interferes with RNAi in the same wing disc. Subsequently, I will measure potential abnormalities by examining outward defects and quantifying wing size relative to body size. These studies will contribute to our understanding of the mechanisms that regulate tissue growth during development. 

DNA replication is essential for cells to divide and is initiated at specific areas along chromosomes called origins. To better understand how perturbing the process of origin initiation affects cells, our lab created a mutant of the Pre Replication Complex in the model organism Saccharomyces cerevisiae. We observe interesting phenotypes in this mutant, including an altered replication pattern and a shortened Chr XII, due to a loss of ribosomal DNA repeats. The rDNA locus contains around 150 copies of a 9.1 kb repeated sequence which encodes the template needed for ribosome synthesis and also an origin of replication, called rARS. We find the activity of rARS is reduced in the mutant and believe the highly repetitive nature of this region and lack of origin initiation make this locus particularly sensitive to replication stress during S-phase. Interestingly, we have found in a different genetic background of yeast, cells harboring this same mutation in the Pre-RC can maintain a relatively large rDNA locus. My research specifically studies this phenomenon and attempts to explore the mechanisms by which this mutant can overcome replication stress in the rDNA region without reducing rDNA copy number. I am currently investigating several possibilities including using gene replacement to determine the role of a notable mutation in a DNA damage repair protein present in this background. This mutation could confer some stress relief to the cells, which would allow them to retain their large rDNA. I will use the genetic tools available in yeast to study this mutation and its effect on rDNA size variation by Pulsed Field Gel Electrophoresis. DNA replication is vital for cell growth and we hope these inquiries will better elucidate the mechanisms and factors involved in replication in order to better our overall understanding of cell biology.

Phenotypes of mutant alleles in a given environment can be used to determine which processes depend on the normal function of a gene. Although genes involved in specific biosynthesis pathways are well characterized in the model organism Saccharomyces cerevisiae, there are genes involved in these processes that still have uncharacterized function. The interaction between gene function and the environmental condition is complex, and requires a comparative approach across yeast species to identify the function of uncharacterized genes in a variety of conditions. We have used a Tn7 transposon insertion mutagenesis system in Saccharomyces uvarum to randomly mutate genes across the genome and pooled all resulting insertional mutants together. We used deep sequencing to identify the insertion sites, and previously predicted 809 genes to be essential for growth in standard laboratory conditions in S. uvarum. Using these same methods, we will apply different selective pressures to libraries of mutant yeast, and aim to understand which genes are critical for growth under specific conditions, such as glucose, phosphate, and sulfate limiting media. We expect that it will be more common to find genes that were non-essential in normal growth media to be essential in more limiting conditions, whereas most genes that were essential in normal growth media should also be essential in limiting conditions. Studying yeast in conditions where they are naturally found (such as grape-must) can provide insight into new, critical genes. This information can be used to make commercial processes such as fermentation more efficient by optimizing metabolic pathways. Additionally, this data can be used to improve gene annotations and increase our knowledge of the biochemical pathways that underlie these essential processes. Thus, acquiring phenotypic information of mutant genes across species and conditions can even help discover genes involved in previously well-studied pathways.

 Protein aggregation is implicated in many human diseases. For example, Alzheimer’s disease is characterized by the misfolding of the amyloid beta (abeta) protein that disrupts cellular function by accumulating into fibrils with a characteristic cross-beta sheet structure. A wide variety of computational, sequence based tools are available to predict amyloidogenic “hot spots”; the regions in proteins that cause the formation of these toxic aggregates. Recently we have performed a comprehensive mutational analysis of abeta using a high throughput method termed Deep Mutational Scanning (DMS). Four hundred and fifty abeta variants were simultaneously assayed for solubility. An aggregation score that reflects the effect on the aggregation propensity of abeta was calculated for each variant. Using these data as a gold standard, we benchmarked aggregation prediction tools and assessed the ability of each algorithm to accurately predict aggregation. In particular, we were interested in identifying methodological weaknesses in these tools and then determining how to improve aggregation propensity prediction. I measured the correlation between several tools’ aggregation predictions for abeta single mutants with the measured aggregation scores. My initial analysis revealed that these tools are often insensitive and over-predict amyloidogenic regions, indicating an opportunity to improve these methods. Having comprehensively measured the relationship between abeta sequence and aggregation propensity, we are now in a position to assess and improve current aggregation prediction tools. Improving our ability to predict this critical process will enhance our understanding of diseases of protein aggregation.

The model yeast, Saccharomyces cerevisiae, can evolve the ability to clump, a trait called flocculation that protects the yeast cells from stress factors including antimicrobial treatments. Understanding the genetics behind this trait could give us insight into treatment options for biofilm-related complications in hospitals as well as targets for microbe engineering in the case of industrial production. In this project, we are interested in identifying the mutations that occur when yeast evolve flocculation. We evolved S. cerevisiae from a non-flocculent ancestor strain for 300 generations in miniature chemostats, multiplexed culture devices that maintain a constant environment. Strains that flocculate have a selective advantage in these devices, and 35% of our final populations evolved this trait. In backcrossing these flocculent strains with their ancestor and dissecting the tetrads into four spores, 20 out of 22 strains segregated the flocculation trait with a 2:2 ratio, indicative of a mutation in a single gene causing the trait. We identified causal alleles using bulk segregant analysis, a pooling and sequencing approach, including a causal transposable element insertion in the promoter of FLO1, a gene known to control flocculation. We hypothesize that this mutation is responsible for changing how FLO1 is expressed and have now identified this mutation in 13 of the clones, some of which exhibit varying phenotypes. We believe that additional mutations may be responsible for this phenotypic variation and are using microscopy to target our sequencing for the gene(s) of interest. We also used these findings to engineer a new strain with FLO1 deleted, which we hypothesized would take longer to flocculate. We report the results of a new evolution experiment comparing flocculation time between the deletion strain and the wild-type strain and demonstrate that our engineering effectively decreases flocculation ability. This is a promising result for both medical and industrial applications.

Many genetic diseases are currently explained by monogenic mutations; however, a number of human disorders and conditions are genetically complex and cannot be attributed to a single mutation. One of the main research goals at the Waterston Lab is to identify genetic interactions that may give rise to disease, such as synergistic, alleviating, or epistatic interactions that could affect important pathways. By using the small nematode worm, Caenorhabditis elegans, as a model, we have developed a high-throughput approach to look for interactions. Forty different transcription factor (TF) genes were separately knocked down using RNAi bacteria on pooled populations composed of 38 mutated and fully sequenced strains of C. elegans. After growth for several generations in the presence of the RNAi, the abundance of strains in each population was compared by targeting strain-specific single nucleotide variants (SNVs) with Molecular Inversion Probes (MIPS) and sequencing on an Illumina MiSeq system. After growth for over 12 generations and screening for ~115,000 possible genetic interactions, two negative and two positive interactions were detected. Strains that quickly fell out of the population on a given RNAi indicate possible negative interactions. We observed this negative interaction between the strain VC20123 and RNAi for the gene K11D2.4, as well as VC20128 and F22D6.2. Strains that did significantly better than other strains on a given RNAi indicates possible positive genetic interactions. We observed these interactions between VC20424 and B0261.1 as well as VC20514 and let-607. To confirm these candidate interactions, we are growing the specific strains against a control strain. To identify the interactions at the gene level, we are using genetic mapping. Broadly, studying the nature of genetic interactions and potential roles of transcription factors may contribute to the elucidation of human development and complex diseases.

Eukaryotic cells are constantly locked in genetic conflict with selfish elements. These elements, such as transposons, are detrimental to the host, but rely on the host for their own replication and passage to host progeny. This results in selective pressure on the host to evolve mechanisms to restrict these genetic parasites, and selective pressure on the parasite to evade those mechanisms to survive. I hypothesize that these elements could be a driving factor in the evolution of the host and parasite. One example of the host and selfish element relationship is in yeast and its 2 micron plasmid. The 2-micron plasmid confers a 1-3% growth rate defect to the yeast while utilizing host machinery, making it a selfish element and a source of genetic conflict. The plasmid is naturally occurring in most yeast strains, making this model a currently occurring and natural model of study, as well as having a wide array of genetic tools already developed for this organism. In order to understand how the plasmid is shaping evolution in different yeast strains, we need to first fully understand how it is utilizing host machinery. This allows us to identify genetic changes due to pressure from the plasmid versus other factors. We have screened a yeast deletion collection where non-essential yeast genes were knocked out one by one. DNA was extracted from each strain and checked strains for decrease in plasmid copy number using southern dot blots and/or PCR. In future work, we will then check each candidate gene using bioinformatics tools to look for evidence of positive selection as evidence of an evolutionary arms race between the yeast host and plasmid. This will allow us to form secondary hypotheses about the effects of the plasmid on yeast genome evolution.