Summer Students
Summer Intern Program
The Jackson Laboratory has been conducting a summer student intern program for undergraduates since 1924 when C.C. Little had six students for a summer biology field study. The Summer Student program became an official part of the laboratory in 1931. Starting in 1949 high school interns started to become a regular part of the intern program. Students in this program have performed research in the Center since 2006.
Understanding the Nature of Research
The program focuses on the methods of science and communication. The students work closely with a faculty mentor and begin the summer with a written proposal for their planned work. The students participate in active research groups and conduct their work in a highly interactive and team oriented atmosphere under the guidance of their mentor. At the end of the summer the students present their work at a Symposium and prepare a written research report.
Students - 2009
Alan Bohn
North Carolina School of Science & Math, Durham, NC
Sponsors: Rachael Hageman and Gary Churchill
NSAIDs such as ibuprofen are commonly used to control inflammation byinhibiting COX-2. However, the side effects of COX-2 inhibition not fully understood. Transcriptional effects of COX-2 inhibition were explored by comparing the liver and adipose tissues of genetically altered COX-1 > COX-2 exchange mice (B6.129(FVB)-Ptgs2tm2.1(Ptgs1)Fun/J) to C57BL/6NJ controls. ANOVA models were used to identify differentially expressed genes between strains for each tissue. Significantly enriched pathways were determined using Gene Set Enrichment information. GenMapp was used to visualize enriched pathways and patterns of differentially expressed genes. Results show no significant difference in the Ptgs1 or the Ptgs2 locus between the COX-1 > COX-2 mice and the controls, nor are there downstream consequences in prostaglandin synthesis. Results indicate up-regulation in the cholesterol biosynthesis pathway in both liver and adipose tissues. Liver tissue has up-regulated bile acid metabolism and down-regulated gluconeogenesis. In the Reverse Cholesterol Transport pathway, Scarb (SR-B1) and Cel are significantly up-regulated. This suggests an increase in selective uptake of cholesterol esters from HDL. In adipose tissue, there is up-regulation in fatty acid metabolism, ketone degradation, and glycolysis. Therefore, several pathways that produce Acetyl-CoenzymeA are up-regulated, yet Cholesterol Biosynthesis is the only enriched pathway that uses Acetyl-CoenzymeA as a substrate.
Sarah Benjamin
Maine School of Science & Math, Limestone, ME
Sponsors: Peter Vedell and Gary Churchill
Type II diabetes is a disease that affects over 17.9 million people in the United States alone. The goal of this study is to develop a gene expression model that shows the relationships between specific genes in the liver, and how they affect the phenotypes insulin and glucose. The first part of my project involved analyzing all the transcript data for liver tissue that I was given. I used R, a statistical software, to identify quantitative trait loci, or regions of the genome that have a strong relationship with the clinical trait in question, and correlated the transcripts with insulin and glucose. This produced a gene list that I was then able to use to produce a graphical model showing how these genes interact with each other. I identified chromosomes 1,17, and 6 as chromosomes of interest using QTL analysis of insulin and glucose. I also identified approximately forty genes of interest. The next step in this project is to map these genes to the insulin signaling pathway to determine their effect on insulin resistance, and identify strong candidates that can be linked to the direct cause of insulin resistance and type II diabetes.
Minna Chen
Wayzata High School, Plymouth, MN
Sponsors: Joel Graber and Nicole Leahy
We demonstrated that there are significant differences between genes and biological processes associated with conserved and non-conserved gene deserts. Using a novel means of determining gene deserts based on local protein-coding gene density, we tested the hypothesis that genes and biological processes associated with conserved gene deserts are different from those associated with non-conserved gene deserts. We separated our deserts into conserved and non-conserved groups based upon the level of overlap between our deserts and syntenic blocks, which are regions of the genome that contain the same genes and gene order in evolutionarily diverged organisms. We investigated two different classes of conservation: deep conservation, represented by conservation between mouse and zebrafish genomes, and mammalian conservation, represented by conservation between mouse and human genomes. We used the gene ontology to analyze and compare genes located in both types of deserts to identify the overrepresented biological processes. Initial evaluations indicated an over-representation of genes involved in the regulation of transcription and gene regulation in deeply conserved deserts. Analysis of mammalian conservation revealed that non-conserved deserts have an over-representation of genes involved in cell-cell communication and nervous system development.
Justin Huang
North Carolina School of Science & Math, Durham, NC
Sponsors: Ricardo Verdugo and Gary Churchill
Many cases of obesity are caused by sedentary lifestyle, but research has also shown that there is a significant genetic factor in the onset of obesity. The goal of this study was to use a Systems Biology approach to identify candidate genes causing obesity in mice that can be tested as drug targets of the treatment of obesity. Quantitative Trait Loci (QTL) analysis was complemented with genome-wide gene expression profiling to discover networks of gene co-expression that are associated to the Fat Percentage (FP) phenotype in an F2 cross between the C57BL/6J and C3H/HeJ mouse strains. An over-representation test was performed to identify biochemical pathways that are over-represented with genes with high correlation to FP and that share one or more QTL with this phenotype. Co-expression networks were then enriched with positional candidates genes that were members of the most significant pathways. Networks were also enriched with genes with LOD score profile highly similar to FP. As a result, I propose Crla2 and Icos as best candidates for the FP QTL on chromosome 1 and the topology of the co-expression networks suggest Rab27b and Sult1e1 as best candidates for drug manipulation for the treatment of obesity.
Sheetal Rajagopal
Univ. of Pennsylvania, Philadelphia, PA
Sponsors: Matt Hibbs
Given the recent production of massive amounts of data, we can utilize computational methods to accurately predict genes associated with phenotypes or diseases. Machine learning methods can make novel inferences of relationships between genes and phenotypes by training on existing data. We trained a Bayesian network (BN) based on a compendium of microarray data and a “gold standard” constructed from all experimentally proven gene-phenotype associations in mice. We used this BN to infer the probabilities that gene pairs are phenotypically related. We then constructed a phenotypic relationship network (PRN), in which the probability of phenotypic relationship is the weight that connects each gene to every other gene. We mined our PRN to make novel predictions of genes associated with the phenotype “abnormal DNA repair.” Also, we created a second PRN focused on the key phenotypes of ovarian cancer. This second BN was trained on an ovarian cancer specific gold standard, and the resulting PRN was mined to determine which genes are most associated with ovarian cancer’s key phenotypes. Initial evaluations indicate that our predictions are promising candidates for further experimental research and could potentially be used to research the causes and treatment of ovarian cancer and abnormal DNA repair.
Students - 2008
Marion Elizabeth Deerhanke
The North Carolina School of Science and Mathematics, Durham, NC
Sponsors: Gary Churchill and Randy Von Smith
Elizabeth investigated hypertension as a complex phenotype and searched for the genetic basis of this widespread disease using quantitative trait loci analysis. In her study she conducted a QTL analysis of systolic blood pressure in F2 males from eight intercrosses comprising fourteen inbred mouse strains. The use of multiple crosses allows for greater precision in narrowing QTL regions through identification of concordant peaks. The search for individual and interacting pairs of loci affecting systolic blood pressure indicated fourteen significant QTL, three epistatic interactions, and linked QTL on Chr 3. Through multiple regression analysis, she developed multiple QTL models for each of the eight intercrosses accounting for as much as 35% of phenotypic variance. These novel loci affecting blood pressure contributed to our understanding of the complex genetic basis of hypertension.
Alex Ellison
Connecticut College
Sponsor: Joel Graber
Alex Ellison identified genes within the deserts identified by Cheryl Zapata (Summer Student in 2007) and tested these for over-representation of biological processes and molecular functions within in the deserts. The research identified genes involved in cell-cell adhesion and neurogenesis occurring more frequently than expected under a random model.
Ryan Keating
The Maine School of Science and Mathematics, Limeston, ME
Sponsors: Gary Churchill and Randy Von Smith
Ryan investigated chronic kidney disease (CKD). CKD, a complex trait, is affected by developmental, environmental, and genetic factors. In his study, eight intercrosses from fourteen inbred mouse strains were analyzed for genetic factors that influence CKD. He performed quantitative trait loci (QTL) analysis of kidney weight with a covariate of body weight to identify regions of the mouse genome that affect CKD. From these eight crosses, he identified twenty significant (P <.05) QTL and eight interactive QTL pairs and accounted for variance in kidney weight, ranging from 51.7 to 73.0 percent. Identification of candidate genes from the significant QTL could then be used to locate orthologous regions in humans.
Students - 2007
Arielle TorresBrandeis University Arielle created an interface in Perl that allowed her to input gene lists and interaction thresholds. It then searched a pre-existing data set detailing patterns of correlated inheritance (represented by linkage disequibrium of pairs of single nucleotide polymorphisms or SNPs) and extracted interacting pairs. Such interaction webs can later be integrated with gene expression profiles and other data sets, enabling a broad network and profile analysis. |
David WitmerThe Maine School of Science and Mathematics, Limestone, ME
David investigated gene expression patterns in multi-factorial DNA microarray data. The core of his study was the utilization of ANOVA-based statistical tests to test general and focused research hypotheses through overall F-tests and specific contrasts. Groups of co-expressed genes were resolved through hierarchical and k-means clustering analysis. Important biological processes associated with key factors were determined by statistical tests for association with gene ontology (GO) terms. Finally, he investigated relationships between gene expression levels and phenotypic response patterns. |
Cheryl ZapataNorth Carolina State University
Cheryl Zapata constructed maps of gene deserts under the definition of gene sparsity. Five definitions of “gene” were used: complete transcript, transcription start sites, exons, coding exons, and exons plus introns. She found that different definitions were either similar to coding exons or exons plus introns. Next, it was demonstrated that deserts are not significantly more or less conserved than the rest of the genome, but some individual chromosomes had greater than expected conservation. |
Students - 2006 |
Arielle TorresBrandeis University
Arielle developed a web-based browser for viewing networks. This tool was developed in the context of the linkage disequilibrium data generated in the Center, but will be generalized to be independent of the underlying data type. This web-based tool allows a user to submit one or more “seed” regions or genes and returns tabular and graphical representations of the sub-network surrounding the seeds. Work is being performed to cast this analysis into a form that can be viewed with existing interfaces such as Cytoscape and N-browse. |
Luis Zapata North Carolina School of Science and Math
Luis worked on analyzing, quantifying, and assessing the gene expression in 12 inbred mouse strains of each sex raised on high fat or chow diets using Genechip arrays. Luis assessed probe level quality, normalized probe intensity, adjusted background, and performed graphical diagnostics on microarray images. He then assessed the influence and interactions of strain, sex, and diet on the overall intensity value of each gene on the array. He finally generated lists of genes that will be studied for functional associations using available genomic annotation software tools. |
