Genetic Basis of Transcriptome Diversity in Drosophila melanogaster

This preprint from Trudy Mackay‘s group at NC State uses a recombinant inbred series of flies known as the Drosophila Genome Reference Panel (DGRP) to evaluate how genetic variation affects transcription.  To do this they extracted RNA from whole flies, pooled from males and females of each of the 192 recombinant inbred fly lines.  They fit the transcriptome data for each gene to a linear mixed effects model that included gender as the dependent variable and the RI line as a random effect.  They then calculated broad (based on the random effects term) and narrow sense (by incorporating a genetic covariance matrix) heritability for each transcript.

They found several interesting things.  First, with respect to sex they found that of the 18,140 transcripts tested, 7626 of these genes showed significant variability across the panel.  The broad sense heritability of genes ranged from 0.034-0.946 across the panel.

They then incorporated additive genetic variance into their model to compare narrow sense and broad sense heritability, and surprisingly found that this simple additive model explained most of the broad sense heritability (for a good explanation of the difference between the two see here, here and here).  What this suggests is that in their model, additive genetic effects explains most of the phenotypic variance of the transcripts.  They also modelled the within-transcript variance in expression, and found that unlike mean expression, the variance in expression was often modified by trans-eQTLs.  Supporting this, they found that nearly 50% of genes had a nearby cis-eQTL, mostly clustered around the 5′ transcriptional start site.  This is consistent with the idea that genetic drivers of transcriptional variation are near the upstream transcriptional regulatory modules of a gene.  The most surprising thing they saw (to me at least) was that most genetic expression variance was sex-specific, with only 185 eQTLs affecting expression in both sexes, out of 941 (male) and 1139 (female) cis-eQTL’s identified.  This is much higher than the rates identified by others in humans (12-17% in this paper).  Certainly this suggests that incorporating sex as a factor in GWA studies is extremely important.

In sum, this paper along with the previous work by Leonid Kruglyak’s group showing most heritability can be explained by additive genetic effects (see here in yeast) adds an important element to our understanding of how genetic variation can affect heritability.

Hat tip to Haldane’s Sieve who mentioned the paper here

Wen Huang, Mary Anna Carbone, Michael Magwire, Jason Peiffer, Richard Lyman, Eric Stone, Robert Anholt, & Trudy Mackay (2015). Genetic Basis of Transcriptome Diversity in Drosophila melanogaster bioRxiv : 10.1101/018325


The association between sleep duration and obesity amongst Canadians aged 12 and over

In this paper, published on PeerJ Preprints, the authors describe the relationship between sleep, obesity and hormones in adolescent Canadians.  The authors used data from the 2012 Canadian Community Health Survey (CCHS) to evaluate sleep duration and body mass index .  The authors looked both at adolescents (12-17) and adults (18+).  In both cases, obese and overweight participants slept less, with a negative correlation between sleep and obesity with correlation co-efficients of -0.031 and -0.056 for adolescents and adults respectively.  This is consistent with other studies that have also shown that sleep deficits either lead to, or correlated with increased obesity risk.

  • I am curious if the lack of sleep corresponded to changes in activity level or food intake, if that data is in the survey, or whether sleep deprivation is an independent predictor of obesity.
  • A plot showing the correlation would be helpful.  The analysis presumes a linear relationship between sleep and obesity, but if it is a nonlinear relationship, a more powerful model could be used.
  • Was the relationship similar between males and females?
  • The p-values are missing in Table 3
  • It would be helpful if the introduction and discussion had some more details of some of the other proposed causes of obesity, in addition to sleep disruption.

As a side note, this project came out of a undergraduate research project, so congratulations are due to both Maha Temkit and her advisor, Dr. Sanni Yaya for publishing an interesting UROP project!

Temkit, Maha, & Yaya, Sanni (2015). The association between sleep duration and obesity amongst Canadians aged 12 and over PeerJ Preprints : 10.7287/peerj.preprints.962v1