Genes underlie the molecular basis of phenotypic variation between individuals. By identifying the underlying gene position via genetic mapping, it is possible to uncover the evolutionary principles that explain phenotypic variation. In this practical work, we associated ten single sequence length polymorphism (SSLP) markers with three phenotypes to identify any possible association between a marker and certain phenotypes in Arabidopsis. These three phenotypes were: whether the plant exhibited flowering, whether cell death was observed in the plant and finally the diameter of the rosette. The first two phenotypes were qualitative traits rated as yes or no, while the last was a quantitative phenotype with a continuous distribution and measured in centimeters. A chi-square test was performed 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 because we had to account for two variations depending on whether it flowered or displayed cell death. A result with a Chi-square value of 18.31 or greater would be interpreted as significant at a 5% confidence level. Therefore, this would mean that the marker was strongly associated with a particular trait. First, the flowering trait was noted because this trait was more evident than plant cell death. FRIGIDA (FRI) alleles have been shown to explain natural variation in flowering time in Arabidopsis. FRI exhibited linkage disequilibrium with the flowering trait, as they tend to be inherited together to the next generation. However, our empirical results contradicted the literature as the Chi-square value for this trait was 7.922 with a P value of approximately 0.75. This involved t...... middle of paper ...... So, simple and easy stroke scoring seemed to be the strength of our study. However, the small sample size was one of the drawbacks of our study which could have resulted in the insignificance of our results. Our experimental subject included only 12 Arabidopsis plants with a unique stock number, whereas Caporaso's study involved more than two thousand human subjects. A small sample size would certainly be unfavorable, as some outliers could bias the results of the statistical analysis.Works Cited1. Caproraso N, Gu F, Chatterjee N, Sheng-Chih J, Yu K et al. (2009) Genome-wide association study of genes and candidate genes on smoking behaviors. PLoS UN 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.