AcknowledgementsWe would like to thank the PSU Research Advisory Council and Student Research Advisory Council for funding support. Research reported in this poster was also supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM103506. We would like to thank the UNH Hubbard Center for Genome Studies and Dartmouth College Molecular Biology Shared Resources Lab for sequencing. We would also like to thank Jon Bairam, Kevin Chesmore, Joel Dufour, Evyn Grimes, Ethan Johnson, Kathryn Kahrhoff, Lauren Oakes, Stacy Peterson, Ellen Rounds, Harlie Shaul, Kate-Lyn Skribiski, Amed Torres, Zoe White, and Alycia Wiggins for their contributions.

Conclusions

Department of Biological Sciences at Plymouth State University, Plymouth NH

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Further sequencing to identify SNPs within CTGF in a more diverse population

Insertion of additional variants into the CTGF vector

Investigate CTGF variants in a cell culture model of wounding to determine whether they impact fibrosis-related phenotypes

SNPs published in Ensembl are not fully representative of the larger human population

2 newly discovered SNPs may impact CTGF structure and function because they are nonsynonymous

Nonsynonymous SNPs in exon 2 do not appear to be associated with cardiovascular disease risk factors

The nonsynonymous SNP in exon 3 may be protective against cardiovascular disease, but a larger sample size is needed to make a definitive conclusion

Determination of CTGF SNP Frequencies and Vector Design by Site-Directed Mutagenesis

KM Jesseman, LL Smith, HA Gentile, ZM Stevens, AE Kennedy, and HE Doherty, PhD

Future Directions

Connective Tissue Growth Factor

Figure 2: Chromatograms from Sanger fluorescent sequencing generated by PolyPhred demonstrate the contrast between A) homozygous and B) heterozygous SNPs. Homozygous locations produce a single peak. Heterozygous alignments exhibit a primary peak and a secondary peak underneath, representing the two different nucleotide bases at the locus. Secondary peaks must reach at least 50% the height of primary peaks after subtraction of background fluorescence to be considered a true heterozygote.

Figure 1: Sequences obtained from the CTGF gene include the 5 exons, as well as a portion of the 5’ and 3’ untranslated regions. Each box represents an exon. Blue arrows indicate the amplicons used for sequencing and the direction in which they are sequenced. Each exon was amplified separately, except exons 1 and 2, which were amplified together.

PolyPhred Used to Identify SNPs

Cardiovascular disease is the leading cause of death in the United States. Following a heart attack, myocardial tissue becomes damaged which can lead to scarring of the heart known as fibrosis. Connective Tissue Growth Factor (CTGF), a gene involved in tissue repair, is upregulated and expressed in fibroblast cells when tissue damage occurs. Fibrosis develops due to continued remodeling of myocardial tissue after a heart attack. As a result, the heart’s ability to contract is compromised, reducing its elasticity which can lead to sudden cardiac death. Previous studies conducted in animal models suggest that increased expression of CTGF can lead to increased severity of fibrosis. Research in our lab focuses on identifying single nucleotide polymorphisms (SNPs) within CTGF that may alter its structure, function, and may potentially impact fibrotic phenotypes. In order to identify these SNPs, cheek swabs were collected from volunteers at PSU. DNA was extracted from the cheek cells, amplified via PCR, purified, and sent for sequencing at the Dartmouth or UNH sequencing facilities. Sequences were analyzed for homozygous and heterozygous SNPs using PolyPhred (University of Washington). Familial background information from volunteers was also gathered to see if SNPs correlated with a family history of obesity, cardiovascular disease, diabetes, high blood pressure, heart attack, stroke or a combination of these factors. Mutant CTGF alleles of interest were inserted into a CTGF vector via site directed mutagenesis. Future research includes testing CTGF vectors containing SNPs in a cell tissue culture model of wounding to determine whether they impact fibrosis-related phenotypes. By identifying SNPs that impact fibrosis risk, individualized treatment plans can be implemented for patients following a heart attack.

Methods

Introduction

Following a heart attack, myocardial tissue becomes damaged and invokes a robust healing response. However, excess healing of cardiac tissue can cause scarring of the heart known as fibrosis. The dense fibrotic tissue to build up reduces the heart’s ability to contract efficiently and the resulting dysfunction can lead to sudden cardiac death. Connective Tissue Growth Factor (CTGF) is a gene involved in tissue repair and remodeling. Research in our lab focuses on identifying Single Nucleotide Polymorphisms (SNPs) that may potentially alter the structure and/or function of CTGF. To do so, cheek cell swabs were collected from volunteers at PSU, amplified via PCR, purified, and sent for sequencing at Dartmouth Molecular Biology Core sequencing facility. Once sequences were returned, they were analyzed for SNPs using PolyPhred software (University of Washington). To date, 9 SNPs have been detected; 4 novel and 5 previously identified. Of the 9 variants, 4 are nonsynonymous mutations. Family history of cardiovascular disease and risk factors were recorded by survey at the time of cheek cell collection. A Kendall’s Tau-b test was used to detect any significant associations between family history and SNPs in exon 2 and 3, but none were detected. Variants of interest were inserted in a vector via site-directed mutagenesis. CTGF variants will be further examined in a model of wounding to determine if they impact fibrosis-related phenotypes. By doing so, individualized treatment plans could be developed for patients after suffering a heart attack.

Abstract No Correlation Between SNPs and Family History Scores

Figure 3: A) Diagram of pUC19 vector containing WT CTGF, the BamHI and XbaI cut sites used to insert it, an ampicillin resistance gene, and the location of the T482C base change. B) Chromatograms showing alignment of WT vector and vector following mutagenesis with a base change of T to C.

Results: Site Directed Mutagenesis generated a successful base change from T to C at cDNA location 482 in the CTGF gene. The base change will result in a V94A amino acid change in the protein. Efforts continue for C57Y, H83D, and V174M mutagenesis.

Successful Insertion of SNP into Vector

Table 2: Kendall’s Tau-b values were calculated for each risk factor and a combined risk of all factors. Values for b range from -1 to 1 with values < 0 suggesting a negative correlation, values > 1 suggesting positive correlation, and values close to 0 suggesting no correlation. p < 0.05 was considered statistically significant. Risk factors were tested for association to two nonsynonymous SNPs in exon 2 and one in exon 3. Exon 2 samples with variants contained both G371A and T482C (n=5) and the WT sample size was n=39. The exon 3 variant tested was G721A (n=1) and the WT sample size was n=73.

Results: No correlation was observed between individuals with the exon 2 variants (G371A and T482C) and family history score, suggesting this subset of variants does not impact cardiovascular disease risk factors. No statistically significant correlation was observed between the G721A variant in exon 3 and family history score for individual risk factors. Combined risk showed a Tau-b value of -0.127 and a p-value of 0.108, suggesting there may be a negative correlation between the SNP and combined risk. In order to determine if the exon 3 SNP results in protection against cardiovascular disease risk, a larger sample size needs to be collected.

DNA Preparation• Cheek cell samples were obtained from Plymouth State University student volunteers. • DNA was extracted from the cells.• Exons 1 and 2 of CTGF were PCR amplified together using Phusion polymerase (Thermo-Fisher).• Exons 3 through 5 of CTGF were PCR amplified separately for each sample using Dream Taq

polymerase (Thermo-Fisher). • Gel electrophoresis was used to confirm PCR amplification.• Successfully amplified samples were purified and sent out for fluorescent Sanger sequencing at

UNH Hubbard Center for Genome Sciences or Dartmouth College Molecular Biology Core Facility.SNP Detection• PolyPhred (v 6.18) software assigns a quality score to each fluorescent peak based on peak height

and location while filtering out background fluorescence. Base changes are then identified through alignment to the published human sequence (Ensembl.org Build 38, Release 85).

• Homozygous SNPs were detected by the presence of primary peaks only. • Heterozygous SNPs were identified by detecting secondary peaks at the same locus which are at

least 50% the height of the corresponding primary peak. • Population frequencies were calculated for each SNP and, for those previously detected, compared

to published frequencies in Ensembl.Site Directed Mutagenesis• The four nonsynonymous SNPs observed in the PSU population were introduced into a previously

designed CTGF vector with a pUC19 base and the Wild Type (WT) human CTGF gene.• The WT allele was determined for our population by CTGF resequencing and includes three

SNPs not present in the Ensembl published sequence.• Synonymous SNPs at cDNA positions A420C and A441C• Nonsynonymous SNP at cDNA position C448G, causing an H83D amino acid change

• Q5 Site Directed Mutagenesis Kit (NEB) was used to insert G371A, G448C, T482C, or G721A• Samples were sent for sequencing at the Dartmouth Molecular Biology Core Facility to determine if

the desired mutation had occurred.Family History Association • A survey of family history for cardiovascular disease was collected along with cheek cell samples. • For each incidence of disease in the individual or 1st degree relative, a value of 1 was assigned. For

2nd degree relatives, incidence of disease was assigned a value of 0.5. To determine combined disease risk all factors were summed (similar to Milne et al 2008).

• Variant scores were assigned as 0 for no copies, 1 for one copy, and 2 for two copies. • A custom program in Python using a statistical package from SciPy was used to calculate p-values

and Kendall’s Tau-b values (Van Rossum, 2007) (Jones et al., 2001)• Analysis was run for nonsynonymous SNPs in exons 2 and 3

9 SNPs Detected in PSU Sample

Table 1: Summary of SNPs identified in CTGF including exon, Ensembl location (Build 38, Release 85), published frequency, PSU sample frequency, nucleotide change, amino acid change, and sample size (chromosomes). Individuals studied are primarily of European descent.

Results: Overall, 9 SNPs were detected. 4 SNPs were novel and 5 were previously identified. SNP frequencies in our population are similar to frequencies previously published in Ensembl. 2 common variants in exon 2 were found that are not currently published. The remaining 2 novel SNPs were uncommon with a frequency of 3%, occurring in the exon 5 and the 3’ UTR of CTGF. G371A and T482C SNPs in exon 2 were always observed together, as well as C1224T and C1362T in exon 5 and the 3’ untranslated region. Of the 9 detected SNPs, 4 were nonsynonymous and, therefore, could potentially impact the structure and function of CTGF.

Exon Ensembl Location

cDNA Location

Published Frequency

PSU Sample Frequency

Nucleotide Change

Amino Acid Change

Sample Size

2 6:131950889 371 Novel 0.06 G/A C57Y

91

2 6:131950840 420 >0.99 0.99 A/C Syn

2 6:131950819 441 >0.99 0.99 A/C Syn

2 6:131950812 448 >0.99 0.99 C/G H83D

2 6:131950778 482 Novel 0.06 T/C V94A

3 6:131950313 721 <0.01 <0.01 G/A V174M 159

5 6:131949291 1224 Novel 0.03 C/T Syn221

5 6:131949279 1236 <0.01 <0.01 C/T Syn

3’ UTR 6:131949153 1362 Novel 0.03 C/T UTR 221

Risk FactorExon 2 Tau-b

Exon 2 p-value

Exon 3 Tau-b

Exon 3 p-value

Obesity -0.046 0.663 -0.078 0.325

Cardiovascular Disease -0.052 0.618 -0.078 0.325

Diabetes 0.087 0.404 -0.063 0.426

High Blood Pressure -0.039 0.705 -0.104 0.188

Heart Attack/Stroke <65 -0.088 0.402 -0.062 0.437

Heart Attack/Stroke >65 0.053 0.611 -0.067 0.396

Combined Risk -0.017 0.870 -0.127 0.108

AmprA

CTGF

pUC19 with CTGF insert

6934 bpXbaI

1

2000

6000

4000

BamHI

T482C

WT Vector

T482C Vector

B

A B