SUMMARY The nuclear RNA exosome is essential for RNA processing and degradation. Here, we show that the exosome nuclear-specific subunit Rrp6p promotes cell survival during heat stress through the cell wall integrity (CWI) pathway, independently of its catalytic activity or association with the core exosome. Rrp6p exhibits negative genetic interactions with the Slt2/Mpk1p or Paf1p elongation factors required for expression of CWI genes during stress. Overexpression of Rrp6p or of its catalytically inactive or exosome-independent mutants can partially rescue the growth defect of the mpk1Δ mutant and stimulates expression of the Mpk1 p target gene FKS2 . The rrp6Δ and mpk1Δ mutants show similarities in deficient expression of CWI genes during heat shock, and overexpression of the CWI gene HSP150 can rescue the stress-induced lethality of the mpk1Δrp6Δ mutant. These results demonstrate that Rrp6p moonlights independently from the exosome to ensure proper expression of CWI genes and to promote cell survival during stress.

Many small nucleolar RNAs (snoRNA)s are processed from introns of host genes, but the importance of splicing for proper biogenesis and the fate of the snoRNAs is not well understood. Here, we show that inactivation of splicing factors or mutation of splicing signals leads to the accumulation of partially processed hybrid messenger RNA–snoRNA (hmsnoRNA) transcripts. hmsnoRNAs are processed to the mature 3′ ends of the snoRNAs by the nuclear exosome and bound by small nucleolar ribonucleoproteins. hmsnoRNAs are unaffected by translation-coupled RNA quality-control pathways, but they are degraded by the major cytoplasmic exonuclease Xrn1p, due to their messenger RNA (mRNA)-like 5′ extensions. These results show that completion of splicing is required to promote complete and accurate processing of intron-encoded snoRNAs and that splicing defects lead to degradation of hybrid mRNA-snoRNA species by cytoplasmic decay, underscoring the importance of splicing for the biogenesis of intron-encoded snoRNAs.

Aneuploidy, the state in which an organism's genome contains one or more missing or additional chromosomes, often causes widespread genotypic and phenotypic effects. Most often, aneuploidies are deleterious; the most common examples in humans being Down's syndrome (Trisomy 21) and Turner's syndrome (monosomy X). However, aneuploidy is surprisingly common in wild yeast populations. In recent years, there has been debate as to whether yeast contain an innate dosage compensation response that operates at the gene, chromosome, or the whole-genome level, or if natural isolates are robust to aneuploidy without such a mechanism. In this study, we tested for differential gene expression in 20 aneuploid and 16 euploid lines of yeast from two previous mutation accumulation experiments, where selection was minimized and therefore aneuploidies arose spontaneously. We found no evidence for whole-chromosome dosage compensation in aneuploid yeast but did find some evidence for attenuation of expression on a gene-by-gene basis. We additionally found that aneuploidy has no effect on the expression of the rest of the genome (i.e. 'trans' genes), and that very few mutually exclusive aneuploid lines shared differentially expressed genes. However, we found there was a small set of genes that exhibited a shared expression response in the euploid lines, suggesting an effect of mutation accumulation on gene expression. Our findings contribute to our understanding of aneuploidy in yeast and support the hypothesis that there is no innate dosage compensation mechanism at the whole-chromosome level.

RT-PCR and northern blots have long been used to study RNA isoforms usage for single genes. Recently, advancements in long read sequencing have yielded unprecedented information about the usage and abundance of these RNA isoforms. However, visualization of long-read sequencing data remains challenging due to the high information density. To alleviate these issues we have developed NanoBlot, an open-source, R-package, which generates northern blot and RT-PCR-like images from long-read sequencing data. NanoBlot requires aligned, positionally sorted and indexed BAM files. Plotting is based around ggplot2 and is easily customizable. Advantages of nanoblots include: a robust system for designing probes to visualize isoforms including excluding reads based on the presence or absence of a specified region, an elegant solution to representing isoforms with continuous variations in length, and the ability to overlay multiple genes in the same plot using different colors. We present examples of nanoblots compared to actual northern blot data. In addition to traditional gel-like images, the NanoBlot package can also output other visualizations such as violin plots and 3′-RACE-like plots focused on 3′-ends isoforms visualization. The use of the NanoBlot package should provide a simple answer to some of the challenges of visualizing long-read RNA sequencing data.

RT-PCR and Northern blots have long been used to study RNA isoforms usage for single genes. Recently, advancements in long read sequencing have yielded unprecedented information about the usage and abundance of these RNA isoforms. However, visualization of long-read sequencing data remains challenging due to the high information density. To alleviate these issues we have developed NanoBlot, a simple, open-source, command line tool, which generates Northern blot and RT-PCR-like images from third generation sequencing data. NanoBlot accepts processed bam files. Plotting is based around ggplot2 and is easily customizable. Advantages of NanoBlots include: designing probes to visualize isoforms which would be impossible with traditional RT-PCR or Northern blots, excluding reads from the Nanoblots based on the presence or absence of a specified region and, multiplexing plots with multiple colors. We present examples of NanoBlots compared to actual northern blot data. In addition to traditional gel-like images, NanoBlot also outputs other visualizations such as violin plots. The use of Nanoblot should provide a simple answer to the challenge of visualization of long-read RNA sequencing data.