Aim 1. We demonstrated previously that sleep can vary among flies having identical genotypes subjected to identical environmental conditions. We quantified this variability as the sensitivity to the environment. Sensitivity to the environment is strongly correlated with sleep duration; flies having short night sleep were far more sensitive to random environmental perturbations than longer-sleeping flies. As this sensitivity is heritable, we identified many polymorphisms putatively involved in its regulation. How these polymorphisms cause variable sleep phenotypes among flies having the same genotype and subjected to the same environmental conditions is not known, but one distinct possibility is that environmental sensitivity might alter gene expression. Therefore, our first goal is to determine whether transcripts are altered among flies with identical genotypes subjected to a common environment. If significant changes in gene expression among identical individuals exist, then it would indicate a possible mechanism by which different sleep phenotypes might arise in individuals of the same genotype. We examined the changes in endogenous gene expression in a sample of 16 lines randomly chosen from the Drosophila Genetic Reference Panel (DGRP). Each line was subjected to the standard environment of sucrose-cornmeal food, 25 deg. C, 60% humidity, and 12:12 hour light:dark cycle. Three biological replicates of the same environment were made. Individual virgin males and females were harvested, and total RNA was extracted. We constructed RNA sequence libraries and successfully sequenced RNA from 750 of the 768 individual flies that were frozen; 726 (730 mapped to the 6.0 Drosophila genome) samples passed genotype and sex quality control guidelines.
Aim 2. As there are no clear-cut strategies for the normalization and analysis of RNA-Seq data, we compared eight different popular normalization methods for raw count data, three data filtering methods, and two statistical analysis approaches. We found that one statistical analysis approach using either of two normalization methods was the most appropriate strategy for identifying differentially expressed genes. We summarized our findings in a manuscript entitled, Comparison of normalization and differential expression analyses using RNA-Seq data from 726 individual Drosophila melanogaster and have submitted this work for publication.
Aim 3. Using our preferred analysis methodology, we have identified genes that are significantly differentially expressed across environment, genotype, sex, and their interactions. We have identified genes with differential expression among identical genotypes reared in the same environment. We will summarize and report these findings.
| Wu, Katherine J; Kumar, Shailesh; Serrano Negron, Yazmin L et al. (2017) Genotype influences day-to-day variability in sleep in Drosophila melanogaster. Sleep : |
| Lee, Hangnoh; Cho, Dong-Yeon; Wojtowicz, Damian et al. (2017) Dosage-Dependent Expression Variation Suppressed on the Drosophila Male X Chromosome. G3 (Bethesda) : |
| Lin, Yanzhu; Golovnina, Kseniya; Chen, Zhen-Xia et al. (2016) Comparison of normalization and differential expression analyses using RNA-Seq data from 726 individual Drosophila melanogaster. BMC Genomics 17:28 |
| Lin, Yanzhu; Chen, Zhen-Xia; Oliver, Brian et al. (2016) Microenvironmental Gene Expression Plasticity Among Individual Drosophila melanogaster. G3 (Bethesda) 6:4197-4210 |
