Comparison of normalization and differential expression analyses using RNA-Seq data from 726 individual Drosophila melanogaster

Comparison of normalization methods across conditions. Boxplots show the differences in the coefficient of variation across flies in each genotype/sex/environment condition. (PDF 245 kb

Nonlinear expression patterns and multiple shifts in gene network interactions underlie robust phenotypic change in Drosophila melanogaster selected for night sleep duration.

All but the simplest phenotypes are believed to result from interactions between two or more genes forming complex networks of gene regulation. Sleep is a complex trait known to depend on the system of feedback loops of the circadian clock, and on many other genes; however, the main components regulating the phenotype and how they interact remain an unsolved puzzle. Genomic and transcriptomic data may well provide part of the answer, but a full account requires a suitable quantitative framework. Here we conducted an artificial selection experiment for sleep duration with RNA-seq data acquired each generation. The phenotypic results are robust across replicates and previous experiments, and the transcription data provides a high-resolution, time-course data set for the evolution of sleep-related gene expression. In addition to a Hierarchical Generalized Linear Model analysis of differential expression that accounts for experimental replicates we develop a flexible Gaussian Process model that estimates interactions between genes. 145 gene pairs are found to have interactions that are different from controls. Our method appears to be not only more specific than standard correlation metrics but also more sensitive, finding correlations not significant by other methods. Statistical predictions were compared to experimental data from public databases on gene interactions. Mutations of candidate genes implicated by our results affected night sleep, and gene expression profiles largely met predicted gene-gene interactions

The Sleep Inbred Panel, a Collection of Inbred Drosophila melanogaster with Extreme Long and Short Sleep Duration

Understanding how genomic variation causes differences in observable phenotypes remains a major challenge in biology. It is difficult to trace the sequence of events originating from genomic variants to changes in transcriptional responses or protein modifications. Ideally, one would conduct experiments with individuals that are at either extreme of the trait of interest, but such resources are often not available. Further, advances in genome editing will enable testing of candidate polymorphisms individually and in combination. Here we have created a resource for the study of sleep with 39 inbred lines of Drosophila—the Sleep Inbred Panel (SIP). SIP lines have stable long- and short-sleeping phenotypes developed from naturally occurring polymorphisms. These lines are fully sequenced, enabling more accurate targeting for genome editing and transgenic constructs. This panel facilitates the study of intermediate transcriptional and proteomic correlates of sleep, and supports genome editing studies to verify polymorphisms associated with sleep duration

Short-Term Memory Deficits in the SLEEP Inbred Panel

Although sleep is heritable and conserved across species, sleep duration varies from individual to individual. A shared genetic architecture between sleep duration and other evolutionarily important traits could explain this variability. Learning and memory are critical traits sharing a genetic architecture with sleep. We wanted to know whether learning and memory would be altered in extreme long or short sleepers. We therefore assessed the short-term learning and memory ability of flies from the Sleep Inbred Panel (SIP), a collection of 39 extreme long- and short-sleeping inbred lines of Drosophila. Neither long nor short sleepers had appreciable learning, in contrast to a moderate-sleeping control. We also examined the response of long and short sleepers to enriched social conditions, a paradigm previously shown to induce morphological changes in the brain. While moderate-sleeping control flies had increased daytime sleep and quantifiable increases in brain structures under enriched social conditions, flies of the Sleep Inbred Panel did not display these changes. The SIP thus emerges as an important model for the relationship between sleep and learning and memory

Supplemental Material for Serrano Negron, Hansen, and Harbison, 2018

Figure S1. Plot of sequence coverage in SIP lines. Figure S2. Plot of LoFreq score distributions for known and novel variants. Figure S3. Day sleep in The Sleep Inbred Panel. Figure S4. Comparison of SIP night sleep and 24-hour sleep with the longest- and shortest-sleeping lines of the DGRP. Table S1. Analysis of variance of sleep traits. Table S2. Comparison of variant calls between BWA and novoalign alignments. Table S3. Mean sleep parameters for each line.Table S4. Comparison of SIP line sleep phenotypes to progenitor populations by progenitor selection scheme and replicate population. Table S5. Mean sleep <i>CV</i>_Eparameters for each line. Table S6. ANOVA of sleep <i>CV</i>_E traits by progenitor selection scheme and replicate population. Table S7. Standard deviation across days for each sleep parameter of each line. Table S8. ANOVA of sleep <i>σ</i> traits by progenitor selection scheme and replicate population. Table S9. Sequence variant categories. Table S10. Comparison of actual versus predicted homozygosity on each chromosome arm of the SIP. File S1. Plot of predicted DGRP founder haplotypes from Hidden Markov Model for Chromosomes <i>X</i>, <i>2L</i>, <i>3L</i>, and <i>3R</i>. File S2. Sleep Inbred Panel list of variants and confidence intervals using BWA alignment. File S3. Sleep Inbred Panel list of variants and confidence intervals using Novoalign alignment. File S4. Sleep Inbred Panel annotated variant call file using BWA alignment. File S5. Sleep Inbred Panel annotated variant call file using Novoalign alignment

Deficiencies tested in the chromosome <i>2R</i> candidate region.

<p>The figure depicts genes implicated in this study and a previous genome-wide association study of sleep, plotted along the chromosome, along with tested deficiency lines. Not all genes in the region are plotted, and the plot is not to scale. Polymorphisms are indicated at the bottom as triangles. Lavender triangles, night sleep <i>CV</i>_E; Purple triangles, night sleep from the GWAS; black triangles, both night sleep <i>CV</i>_E and night sleep; blue triangles, night sleep from the artificial selection study. Deficiency mapping implicated at least two quantitative trait loci (QTL) in the region. Blue bars denote genes within the first QTL; orange bars denote the second QTL.</p

Selection for long and short sleep duration in <i>Drosophila melanogaster</i> reveals the complex genetic network underlying natural variation in sleep

<div><p>Why do some individuals need more sleep than others? Forward mutagenesis screens in flies using engineered mutations have established a clear genetic component to sleep duration, revealing mutants that convey very long or short sleep. Whether such extreme long or short sleep could exist in natural populations was unknown. We applied artificial selection for high and low night sleep duration to an outbred population of <i>Drosophila melanogaster</i> for 13 generations. At the end of the selection procedure, night sleep duration diverged by 9.97 hours in the long and short sleeper populations, and 24-hour sleep was reduced to 3.3 hours in the short sleepers. Neither long nor short sleeper lifespan differed appreciably from controls, suggesting little physiological consequences to being an extreme long or short sleeper. Whole genome sequence data from seven generations of selection revealed several hundred thousand changes in allele frequencies at polymorphic loci across the genome. Combining the data from long and short sleeper populations across generations in a logistic regression implicated 126 polymorphisms in 80 candidate genes, and we confirmed three of these genes and a larger genomic region with mutant and chromosomal deficiency tests, respectively. Many of these genes could be connected in a single network based on previously known physical and genetic interactions. Candidate genes have known roles in several classic, highly conserved developmental and signaling pathways—EGFR, Wnt, Hippo, and MAPK. The involvement of highly pleiotropic pathway genes suggests that sleep duration in natural populations can be influenced by a wide variety of biological processes, which may be why the purpose of sleep has been so elusive.</p></div

Change in distance between polymorphisms in LD over generation.

<p>The average distance between a given variant and a variant in high LD (<i>r</i>² > 0.8) is shown for each generation. Dark blue triangles indicate averages over populations selected for long sleep; dark red squares indicate averages over populations selected for short sleep; and black circles indicate averages over control populations. (A) Chromosome <i>2L</i>. (B) Chromosome <i>2R</i>. (C) Chromosome <i>3L</i>. (D) Chromosome <i>3R</i>. (E) <i>X</i> chromosome.</p

Examples of allele frequency trajectories observed across generations.

<p>Each plot shows the minor allele frequency for the long- and short-sleep selection schemes plotted against generation. Minor allele frequency was defined using the combined allele frequencies for all populations prior to selection (i.e., generation 0). (A), divergent trajectory at position 14,976,564 on chromosome <i>3L</i>; (B) similar trajectory at position 6,300,126 on chromosome <i>X</i>. Dark blue triangles indicate the average minor allele frequencies for long sleep Replicate 1 and Replicate 2 populations; Dark red squares indicate average minor allele frequencies for short sleep Replicate 1 and Replicate 2 populations. (C) box plots for all of the polymorphisms significant for the logistic regression versus generation. Blue, long sleep; red, short sleep.</p

Sleep traits with a significant correlated response to artificial selection for long or short night sleep duration.

<p>(A, C, E, G), the combined-sex mean sleep trait ± SE is plotted for each generation of selection; (A), day sleep duration; (C), night average bout length; (E), day bout number, and (G) sleep latency. (B, D, F, H), the combined-sex sleep trait coefficient of environmental variation (<i>CV</i>_E) is plotted for each generation of selection; (B), day sleep <i>CV</i>_E; (D), night average bout length <i>CV</i>_E; (F), day bout number <i>CV</i>_E; (H), sleep latency <i>CV</i>_E. Colors and symbols are the same as <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007098#pgen.1007098.g001" target="_blank">Fig 1</a>.</p