Akriti Bhattarai
Year: 2018
Faculty Advisor: Michael Gore

“Transcriptome-Wide Association Study of Maize Leaf Cuticular Evaporation Rate


Project Summary:

Maize yields have increased greatly, but a limiting factor is drought sensitivity. The plant cuticle is a hydrophobic layer that plays a major role in preventing water loss and conferring protection against pathogens. By identifying genes associated with leaf cuticular evaporation (CE) rate, it could be possible to improve the efficiency at which drought-tolerant maize hybrids are developed. In that light, the CE rate of ~450 maize inbred lines constituting the Wisconsin diversity panel was measured in Maricopa, AZ, and San Diego, CA, in 2016 and 2017. To conduct a transcriptome-wide association study (TWAS), we used an existing gene expression data set for five different tissues from ~140 lines in the Goodman-Buckler maize diversity panel that overlap with the Wisconsin diversity panel. The best linear unbiased predictor (BLUP) for CE rate was calculated for each line across environments and probabilistic estimation of expression residuals (PEER) was implemented to extract hidden factors that may cause noise in the gene expression data. We performed the TWAS using a mixed linear model controlling for population structure and relatedness and PEER factors. Using a threshold of P-value < 10-5 for the correlation coefficient, we identified 21 candidate genes from the five tissues. One of the genes resided in the vicinity of a peak SNP identified in a genome-wide association study (GWAS) for CE rate. As preliminary research to a forthcoming large-scale RNA-seq study, our results show the potential of TWAS as a powerful tool in quantitative genetic studies.

My Experience:

My experience as a BTI intern has been incredibly fulfilling and rewarding. I was fortunate to have the opportunity to experience many aspects of plant science research, including field work and sample collection and statistical analysis. I had very little experience with programming or R coming into the program. With the support of my wonderful mentor, Meng Lin, I gained analytical skills and was able to expand my knowledge of both statistics and quantitative genetics. The skills I developed as an intern in the Gore lab will be invaluable for future undergraduate research experiences, graduate school, and my career goals. I learned to be patient and persistent, to tackle problems from different perspectives, and most importantly, to ask for help when I need it.