Genome-wide assessment of post-transcriptional control in the fly brain

Post-transcriptional control of gene expression has central importance during development and adulthood and in physiology in general. However, little is known about the extent of post-transcriptional control of gene expression in the brain. Most post-transcriptional regulatory effectors (e.g., miRNAs) destabilize target mRNAs by shortening their polyA tails. Hence, the fraction of a given mRNA that it is fully polyadenylated should correlate with its stability and serves as a good measure of post-transcriptional control. Here, we compared RNA-seq datasets from fly brains that were generated either from total (rRNA-depleted) or polyA-selected RNA. By doing this comparison we were able to compute a coefficient that measures the extent of post-transcriptional control for each brain-expressed mRNA. In agreement with current knowledge, we found that mRNAs encoding ribosomal proteins, metabolic enzymes, and housekeeping genes are among the transcripts with least post-transcriptional control, whereas mRNAs that are known to be highly unstable, like circadian mRNAs and mRNAs expressing synaptic proteins and proteins with neuronal functions, are under strong post-transcriptional control. Surprisingly, the latter group included many specific groups of genes relevant to brain function and behavior. In order to determine the importance of miRNAs in this regulation, we profiled miRNAs from fly brains using oligonucleotide microarrays. Surprisingly, we did not find a strong correlation between the expression levels of miRNAs in the brain and the stability of their target mRNAs; however, genes identified as highly regulated post-transcriptionally were strongly enriched for miRNA targets. This demonstrates a central role of miRNAs for modulating the levels and turnover of brain-specific mRNAs in the fly

Dynamic hyper-editing underlies temperature adaptation in <i>Drosophila</i>

<div><p>In <i>Drosophila</i>, A-to-I editing is prevalent in the brain, and mutations in the editing enzyme ADAR correlate with specific behavioral defects. Here we demonstrate a role for ADAR in behavioral temperature adaptation in <i>Drosophila</i>. Although there is a higher level of editing at lower temperatures, at 29°C more sites are edited. These sites are less evolutionarily conserved, more disperse, less likely to be involved in secondary structures, and more likely to be located in exons. Interestingly, hypomorph mutants for ADAR display a weaker transcriptional response to temperature changes than wild-type flies and a highly abnormal behavioral response upon temperature increase. In sum, our data shows that ADAR is essential for proper temperature adaptation, a key behavior trait that is essential for survival of flies in the wild. Moreover, our results suggest a more general role of ADAR in regulating RNA secondary structures <i>in vivo</i>.</p></div

EvoFold analysis of hyper-editing sites.

<p>EvoFold analysis of hyper-editing sites.</p

The degree and prevalence of A-to-I RNA editing are dynamically affected by temperature.

<p><b>(A)</b> Generation of editing list by combining the RADAR database (2,697 sites), Rennan's and Rosbash's datasets[<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006931#pgen.1006931.ref011" target="_blank">11</a>,<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006931#pgen.1006931.ref032" target="_blank">32</a>] (3,580 and 1,341 sites respectively) with novel hyper-editing sites detected by our method (30,190 sites). This resulted in a list of 32,974 unique sites, containing 11,097 editing sites in CDS. <b>(B)</b> Hyper-editing motif. The sequence near the hyper-editing sites is depleted of Gs upstream and enriched with Gs downstream as expected from ADAR targets. <b>(C)</b> Editing index, fraction of inosines among all expressed adenosines of all detected editing sites, show lower editing levels at 29°C. <b>(D)</b> Editing levels of significantly altered 55 editing sites in CDS. Each site is presented by a number which indicates its position in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006931#pgen.1006931.s006" target="_blank">S1 Table</a>. <b>(E)</b> The distribution of hyper-editing detected sites, shows higher number of sites found at elevated temperature. <b>(F)</b> Average hyper-editing events per detected sites. Statistical significance between 18°C and 29°C was assessed by Student-t test (p<10⁻⁴). <b>(G)</b> Editing cluster's difference between temperatures. Left panel presents the average cluster length for each temperature. Right panel presents the average unique number of detected editing-sites for each temperature.</p

Editing sites at lower temperatures are edited more frequently and are more commonly flanked by complementary sequences.

<p><b>(A)</b> Mean conservation (PhastCons) score of hyper-edited sites. Position 0 indicates the position of editing site. Blue line denotes conservation mean for editing sites supported by more than one event, red line denoted conservation mean for editing sites supported by only one event, and black line represents background conservation of chosen randomly adenosines. Left figure represents all genome wide hyper-editing sites, while the right figure represents hyper-editing sites in coding regions (CDS). The information from the non-hyper-edited reads was included. <b>(B)</b> RNA secondary structure prediction using BLAST[<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006931#pgen.1006931.ref050" target="_blank">50</a>] tool (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006931#sec009" target="_blank">Methods</a>). Blue bars donate for predicted dsRNA structure involving the hyper-editing site, as we succeeded to match the editing regions with their anti-sense sequence. Red bars denote for matches found in the sense sequence, representing the control. Green bars denote for predicted dsRNA structure involving the hyper-editing site after converting the adenosine (A) to its edited form, guanosine (G). Violet bars represents the control for the converted adenosines. <b>(C)</b> Genomic locations of detected hyper-editing sites show increase in the number of exonic sites at 29°C.</p

ADAR hypomorph flies display temperature dependent behavioral abnormalities.

<p><b>(A)</b> ADAR hypomorph flies (red) are less active than control flies (blue) both at 18°C and 29°C. Total activity per day obtained by adding the average activity during the light and dark periods (8 days). N = 32 and 29 for hypomorph flies at 18°C and 29°C respectively and N = 27 for control flies at both temperatures. Statistical significance was assessed by Student-t test. Error bars represents SEM. <b>(B)</b> Although less active than their controls, at 18°C, the pattern of day-night activity of ADAR hypomorph and control flies is similar, with higher activity during the day. We calculated and ploted the average activity during the light (9 days) or dark periods (8 nights). Statistical significance was assessed by Student-t test. Error bars represents SEM. <b>(C)</b> At 29°C, control flies increase their night activity whereas the ADAR hypomorph flies remaine active mostly during the day. Statistical significance was assessed by Student-t test. Error bars represents SEM. <b>(D)</b> Behavioral activity assay for control (left) and ADAR hypomorph flies (right) that were exposed to 12:12h light:dark (L:D) cycles at 29°C for 4 days and then transferred to 18°C (L:D cycles) for 5 days. N = 29 for control and N = 32 for Adar hypomorph flies. An arrow marks the transition time point. Error bars represent SEM. <b>(E)</b> same as in (D), with the opposite temperature transfer, from 18 to 29°C. N = 30 for control and N = 31 for ADAR hypomorph flies. An arrow marks the transition time point.</p

Functional analysis of hyper-edited genes.

<p>Functional analysis of hyper-edited genes.</p

Marked Differences in C9orf72 Methylation Status and Isoform Expression between C9/ALS Human Embryonic and Induced Pluripotent Stem Cells

We established two human embryonic stem cell (hESC) lines with a GGGGCC expansion in the C9orf72 gene (C9), and compared them with haploidentical and unrelated C9 induced pluripotent stem cells (iPSCs). We found a marked difference in C9 methylation between the cells. hESCs and parental fibroblasts are entirely unmethylated while the iPSCs are hypermethylated. In addition, we show that the expansion alters promoter usage and interferes with the proper splicing of intron 1, eventually leading to the accumulation of repeat-containing mRNA following neural differentiation. These changes are attenuated in C9 iPSCs, presumably owing to hypermethylation. Altogether, this study highlights the importance of neural differentiation in the pathogenesis of disease and points to the potential role of hypermethylation as a neuroprotective mechanism against pathogenic mRNAs, envisaging a milder phenotype in C9 iPSCs

Circular RNAs in the Mammalian Brain Are Highly Abundant, Conserved, and Dynamically Expressed

Circular RNAs (circRNAs) are an endogenous class of animal RNAs. Despite their abundance, their function and expression in the nervous system are unknown. Therefore, we sequenced RNA from different brain regions, primary neurons, isolated synapses, as well as during neuronal differentiation. Using these and other available data, we discovered and analyzed thousands of neuronal human and mouse circRNAs. circRNAs were extraordinarily enriched in the mammalian brain, well conserved in sequence, often expressed as circRNAs in both human and mouse, and sometimes even detected in Drosophila brains. circRNAs were overall upregulated during neuronal differentiation, highly enriched in synapses, and often differentially expressed compared to their mRNA isoforms. circRNA expression correlated negatively with expression of the RNA-editing enzyme ADAR1. Knockdown of ADAR1 induced elevated circRNA expression. Together, we provide a circRNA brain expression atlas and evidence for important circRNA functions and values as biomarkers.Fil: Rybak Wolf, Agnieszka. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Stottmeister, Christin. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Glažar, Petar. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Jens, Marvin. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Pino, Natalia. Max Planck Institute of Psychiatry; AlemaniaFil: Giusti, Sebastian. Max Planck Institute of Psychiatry; AlemaniaFil: Hanan, Mor. The Hebrew University of Jerusalem; IsraelFil: Behm, Mikaela. Stockholms Universitet; SueciaFil: Bartok, Osnat. The Hebrew University of Jerusalem; IsraelFil: Ashwal Fluss, Reut. The Hebrew University of Jerusalem; IsraelFil: Herzog, Margareta. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Schreyer, Luisa. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Papavasileiou, Panagiotis. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Ivanov, Andranik. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Öhman, Marie. Stockholms Universitet; SueciaFil: Refojo, Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Max Planck Institute of Psychiatry; AlemaniaFil: Kadener, Sebastian. The Hebrew University of Jerusalem; IsraelFil: Rajewsky, Nikolaus. Max-Delbrück Center for Molecular Medicine; Alemani