Genes underpin the molecular basis of phenotypic variation among individuals. By identifying the location of the underlying gene through genetic mapping, it is possible to uncover the evolutionary principles that explain phenotypic variations. In this practice, we associated ten simple sequence length polymorphism (SSLP) markers with three phenotypes to identify any possible association between a marker and a certain phenotype in Arabidopsis. These three phenotypes were: the plant showed flowering, cell death was observed in the plant, and finally the rosette diameter. The first two phenotypes were qualitative traits assessed with yes or no response, while the second was a quantitative phenotype with continuous distribution and measured in centimeters. The Chi-square test was conducted to account for the association between SSLP markers and qualitative phenotypes that had a discrete distribution. Since our sample size was 12, there were 10 degrees of freedom as we would have to account for two variations depending on whether it flowered or showed cell death. A result with a Chi-square value of 18.31 or greater would be interpreted as significant at a 5% confidence level. Thus, it would mean that the marker was highly associated with a particular trait. First, the flowering characteristic was evaluated because this characteristic was more evident than the cell death score of the plant. FRIGIDA (FRI) alleles have been shown to explain natural variation in flowering time in Arabidopsis. FRI showed a linkage disequilibrium with the flowering trait as they tend to be inherited together with the next generation. However, our empirical result contradicted the literature as the Chi square value for this trait was 7.922 with a P value of approximately 0.75. This implied t...... middle of paper...... Therefore, scoring a simple and easy trait seemed to be the strength of our study. However, the small sample size was one of the demerits of our study that could have resulted in the insignificance of our findings. Our experimental subject included only 12 Arabidopsis plants with a unique accession stock number, while Caporaso's study involved over two thousand human subjects. A small sample size would certainly be unfavorable as some outliers could influence the result of the statistical analysis. Works Cited1. Caproraso N, Gu F, Chatterjee N, Sheng-Chih J, Yu K, et al.(2009) Candidate gene and genome-wide association study on cigarette smoking behaviors. PLoS UNO 4(2): e4653.2. Johnson U, West J, Lister C, Michaels S, Amasino R, et al.(2000) Molecular analysis of FRIGIDA, a major determinant of natural variation in flowering time in Arabidopsis. Science 290:344-347.