Novel Intronic Non-Coding RNAs Contribute to Maintenance of Phenotype in Saccharomyces Cerevisiae

The Saccharomyces cerevisiae genome has undergone extensive intron loss during its evolutionary history. It has been suggested that the few remaining introns (in only 5% of protein-coding genes) are retained because of their impact on function under stress conditions. Here, we explore the possibility that novel non-coding RNA structures (ncRNAs) are embedded within intronic sequences and are contributing to phenotype and intron retention in yeast. We employed de novo RNA structure prediction tools to screen intronic sequences in S. cerevisiae and 36 other fungi. We identified and validated 19 new intronic RNAs via RNAseq and RT-PCR. Contrary to common belief that excised introns are rapidly degraded, we found that, in six cases, the excised introns were maintained intact in the cells. In other two cases we showed that the ncRNAs were further processed from their introns. RNAseq analysis confirmed higher expression of introns in the ribosomial protein genes containing predicted RNA structures. We deleted the novel intronic RNA structure within the GLC7 intron and showed that this predicted ncRNA, rather than the intron itself, is responsible for the cell’s ability to respond to salt stress. We also showed a direct association between the presence of the intronic ncRNA and GLC7 expression. Overall, these data support the notion that some introns may have been maintained in the genome because they harbour functional ncRNAs.


INTRODUCTION
There are three main theories regarding the origin of introns: 'Introns Late', 'Introns Early' and 'Introns First' (JEFFARES et al. 2006). The 'Introns Late' and 'Introns Early' theories suggest that introns arose within the eukaryotic lineage, and before the Prokaryota-Eukaryota split, respectively, whereas 'Introns First' implies that these noncoding sequences appeared before protein-coding genes. Introns are maintained, lost or gained with different rates within different eukaryotic lineages. The recent evolution of the yeast genome has seen widespread intron loss, with the result that only 5% of Saccharomyces cerevisiae genes contain introns (DUJON 2006). It has been proposed that small organisms with a large effective population size, such as S.
cerevisiae, have seen deleterious introns gradually eliminated from the genome (LYNCH 2002). This raises the question of why some introns are maintained in the yeast genome and, furthermore, if they are functionally relevant.
Recent studies indicate that S. cerevisiae introns increase fitness under stress (PARENTEAU et al. 2008), aid ribosome assembly, and regulate expression of the paralogous copy of the gene (PARENTEAU et al. 2011). Introns may contain regulatory sequences and structures that affect splicing or expression of their host genes. In the HAC1 transcript, short RNA hairpins define the intron boundaries (SIDRAUSKI AND WALTER 1997). Splicing of the YRA1 mRNA regulates its export from the nucleus (PREKER et al. 2002;RODRIGUEZ-NAVARRO et al. 2002). Described RNA structures in pre-mRNA transcripts of RPL30 (LI et al. 1996) and RPS14B (FEWELL AND WOOLFORD 1999) regulate splicing of their host genes. Intronic hairpins in RPL18A and RPS22B pre-mRNAs are recognized by RNase III Rnt1p and promote mRNA degradation (DANIN-KREISELMAN et al. 2003). The RPS17B intron contains a RNAbased splicing enhancer that physically decreases the distance between the splice sites (ROGIC et al. 2008). RNA structures in the introns of RPS9A and RPS9B transcripts are vital components of an autoregulatory circuit (PLOCIK AND GUTHRIE 2012).
The cases described above are examples where introns function in cis; intronic sequences can also act in trans. In vertebrates, introns frequently harbor functional noncoding RNAs (ncRNAs). Tiling arrays and deep RNA sequencing have revealed the existence of many novel intronic transcripts, most of which have no known function (CHENG et al. 2005;MERCER et al. 2008). In addition, a recent study searching for RNAs bound by the chromatin-modifying polycomb complex raised the possibility that intronic ncRNAs can be used to guide chromatin modifications that influence gene expression in a manner analogous to some long intergenic ncRNAs (GUIL et al. 2012). In vertebrates, there are also well-characterized examples of intronic ncRNAs such as tRNAs, small nucleolar RNAs (snoRNAs), and microRNAs (KIM AND KIM 2007). However, in S. cerevisiae, well-known intronic ncRNAs classes are not prevalent: microRNAs are non-existent due to the loss of pre-miRNA processing enzymes (DRINNENBERG et al. 2009), intronic snoRNAs have been mostly 'de-intronized' (MITROVICH et al. 2010) and all tRNAs are present outside introns.
Even though many ncRNAs have been found in S. cerevisiae, such as stable unannotated transcripts (SUTs) and cryptic unstable transcripts (CUTs) , only 2% of the instances of these classes overlap with introns (XU et al. 2009).
It is commonly believed that splicing in higher eukaryotes increases protein diversity by providing multiple mRNAs from a single locus. However, alternative splicing in S. cerevisiae has been shown only for transcripts from the genes SRC1 (DAVIS et al. 2000;GRUND et al. 2008), PTC7 (JUNEAU et al. 2009) and MTR2 (DAVIS et al. 2000PREKER et al. 2002). Since alternative splicing in S. cerevisiae is rare and there has been a massive reduction in the number of typical intronic ncRNAs, we hypothesize that functional yeast introns may have been retained because they contain novel ncRNA genes or pre-mRNA RNA structures.
In order to discover potential functional RNA structures within introns in S. cerevisiae, we performed a computational screen for novel structures using intron orthologs from 36 fungal species and employing three de novo RNA structure prediction tools. The screen identified 19 introns containing potential RNA structures, 6 and we validated the expression and processing of a subset by RT-PCR. We showed that six introns tested are maintained in the cell after splicing and two contain novel ncRNAs. A novel ncRNA within the GLC7 intron, rather than the whole intron (JUNEAU et al. 2006;PARENTEAU et al. 2008), is responsible for cell's ability to respond to salt stress, by altering the gene expression.

RESULTS
Predictions of RNA structure within introns: Since a predicted secondary structure of a single sequence is not generally sufficient to distinguish between a functional RNA and random sequences (RIVAS AND EDDY 2000), most RNA prediction methods require multiple homologous sequences. Thus our first step in RNA prediction was to identify orthologs of S. cerevisiae introns in other fungi. We searched for orthologs of intron-containing host genes in fully sequenced genomes and then for corresponding introns in those genes. In 36 fungal genomes, we were able to identify at least 2 orthologs for 281 introns and at least one ortholog for 305 introns (see Fig 1A). Only the intron of YDR535C does not have an ortholog in any of the species searched, but annotation of this sequence as a gene is dubious. The vast majority of introns are conserved only in the Saccharomyces 'sensu stricto', and we identify fewer than 4 orthologs for each intron on average. In contrast, orthologs of yeast introns containing known intronic snoRNAs are found in a wider range of fungal genomes, having on average 9.6 orthologs (see Fig 1A).
Orthologous intronic sequences were used to predict novel RNA structures using three independent computational methods: CMfinder, RNAz and EvoFold. Each of these approaches yielded a very different number of predicted RNA structures in introns. RNAz, CMfinder and EvoFold identified putative conserved RNA structures in 17, 54 and 175 introns, respectively. We found 14 structures in the intersection of   all three approaches, within the only intron of each of GLC7, HAC1, IMD4, MPT5,   RPL18A, RPL18B, RPL22B, RPL28, RPS9A,  For further bioinformatical and experimental analysis, we decided to focus on the introns that had structures predicted by all three programs, together with their paralogs (i.e. introns in RPL22A, RPL7B), and 3 introns with high prediction scores in at least two out of three approaches (i.e. introns in NOG2, YRA1 and PSP2). We used the INFERNAL software (NAWROCKI et al. 2009) and the Rfam library of covariance models to search the intron sequences for known ncRNA classes (GARDNER et al. 2010). Besides the known snoRNAs, our other high-scoring RNA predictions do not resemble any previously known RNA families. We also used an iterative procedure combining covariance model searches using the INFERNAL package and manual inspection of multiple sequence alignments to identify additional homologs of our predicted structures in more distant species (Table I and Fig 1C). We find that the known snoRNAs are very well conserved among Fungi: snR191 orthologs were found in all Saccharomycotina, snR44 in Saccharomycotina and Pezizomycotina, while snR54 is present in some Metazoan genomes as well as Fungi. The previously known introns demonstrated that predicted structures within introns are well-conserved in Saccharomyces 'sensu stricto'. The high sequence conservation means that relatively 8 few compensatory mutations support these conserved predicted structures. Only in the case of the intron of RPS13 is there evidence for maintenance of the RNA structure through multiple compensatory mutations.
Experimental detection of the predicted intronic ncRNA: In order to determine if the predicted intronic RNAs are expressed and maintained in the cell, we performed RT-PCR on total and low molecular weight cDNA from haploid BY4741 wild type S. cerevisiae strain. We designed three sets of specific primers to amplify the fragment of intron with the predicted structure or snoRNA, the entire intron, and part of the exons flanking the intron. As a positive control for the PCR, we used the genomic DNA to amplify products with the primer pairs described above in the snR44, snR191 and snR54 snoRNA genes. Negative controls for all PCR experiments were performed with no template added to the reactions.
If a bona fide ncRNA product is processed from an intron, we expected to obtain bands corresponding to the spliced mRNA of the host gene, and also for the region of the predicted structure, but not the larger product from the complete intron. This pattern was observed for the RPS22B intron harboring the known snoRNA snR44 and for two other introns with predicted structures, namely the intron of GLC7 and the first intron of RPL7B, thus confirming these sequences as novel ncRNAs (Fig 2A, Fig   S1). A similar pattern was also observed for MPT5 although its expression was very low (Fig 2A, Fig S1C). The RT-PCR corresponding to snR191 in NOG2 displayed a pattern indicative of complete splicing of the host mRNA, but also showed the maintenance of the complete intron and of the predicted ncRNA. We refer to these sequences as 'introns maintained' after splicing as opposed to 'introns retained' in the pre-mRNA. We observed a similar pattern of correct splicing with intact intron and ncRNA maintenance for our predicted structures in the introns of RPS13, RPS9B, RPL7A, RPL22A and in the 5' UTR intron of RPS22B (Fig 2B and Fig S2-S3). These data show that a mixed population of mature ncRNAs and spliced but unprocessed introns are present in the cell. We also found that the mRNA transcripts of IMD4 (containing snR54 in its intron), PSP2, RPS9A, RPL28, RPL22B, RPL18A, RPL18B and YRA1 were present in both spliced and unspliced forms, supporting the existing evidence that intron retention is the most common case of alternative splicing in yeast (PLASS et al. 2012) (Fig 2C, Fig S4-S5). We found no evidence of splicing of HAC1 under the specific experimental conditions we tested (see Fig S6A). As negative controls, we conducted the same RT-PCR analysis on six intron-containing genes that had no predicted RNA structures. None of the six displayed patterns consistent with ncRNAs processed from the introns. The genes YBR219C and BMH2 did not appear to be expressed and the four ribosomal protein genes RPL27A, RPS27B, RPS16A and RPS19B showed the intron-maintained pattern (Fig S6B-G). RNAseq data show higher expression of introns in ribosomal protein genes that contain predicted RNA structures.
We also validated the presence of expressed intronic sequences in the cell by deep sequencing of total RNA extracted from S. cerevisiae BY4741. We counted all reads overlapping introns and normalized by the intron length and the total number of reads mapped to obtain values of reads per kB per million mapped (RPKM). Median intron expression was 15.3 RPKM. We observed that 17 of 19 introns with predicted structures have evidence of expression (more than 150 reads or 20 RPKM), seven of which fell within the 90th percentile of intron expression.
Since a third of all introns are found in highly expressed ribosomal protein (RP) genes, we next measured the relative expression levels of maintained introns in RP that contain or do not contain predicted structures. Since the mRNA levels of the genes hosting predicted intronic structures appeared to be greater than the average mRNA amount for the entire set of intron-containing genes, we also normalized the intron expression levels by the level of their host gene transcript. Interestingly, expression of RP introns with predictions was significantly higher compared with all RP introns before and after normalizing for host gene expression (median RPKM 65.5 compared to 33.0, Mann-Whitney U test p-value: 0.006 and median normalized expression 0.11 compared to 0.03, Mann-Whitney U test p-value: 0.014, Fig 3A).
Introns with predicted RNA structures are more likely to be targeted by the exosome: We hypothesize that introns with RNA structures either contain novel noncoding RNAs or are involved in the regulation of pre-mRNA splicing; in both cases, the host transcript would be expected to associate with the exosome complex.
We analyzed the data of Schneider et al. (SCHNEIDER et al. 2012), who used in vivo RNA crosslinking (CRAC) of exosome components to show that noncoding RNAs, snoRNAs, pre-tRNAs and pre-mRNAs are the most prominent exosome targets. The Schneider et al. dataset (GEO accession GSE40046) contains deep sequencing reads from sixteen separate in vivo crosslinking experiments to the tagged protein components of the exosome. When we normalized the number of reads of each introncontaining gene from GSE40046 by the average number of reads for this introncontaining gene from our sequencing, we observed that the set of genes with both known snoRNA host genes and our novel RNA predictions appears to be targeted by the exosome machinery more than expected (our predictions, Mann-Whitney U test, p = 2.44x10 -4 ; snoRNAs, p = 0.005; Fig 3B). This suggests that the introns of interest are either retained in pre-mRNAs or contain noncoding RNAs. Taken in conjunction with our RT-PCR data, the CRAC data indicated that the transcripts of PSP2, RPS9A, RPL18A and RPL18B retain introns, and as a result their pre-mRNAs are targeted for exosome-mediated degradation. In contrast, the presence of novel ncRNA was indicated for the MTP5 intron.
Function of the GCL7 intronic ncRNA: The intronic sequence in GLC7 was recently shown to play a role in the cellular response to osmotic pressure (PARENTEAU et al. 2008). We therefore investigated further the putative ncRNA derived from this intron. Firstly, we used Northern hybridization to confirm the RT-PCR analysis of expression of the ncRNA; and secondly we employed primer walking to define the 5' and 3' ends of the ncRNA. We were able to specifically define GLC7 ncRNA boundaries, which are different to those of the previously annotated CUT568 residing on the opposite strand (Fig 4).
To study the phenotype of the ncRNA we used two approaches: deletion and alteration of the ncRNA structure. We deleted two regions in the intron of GLC7 via PCR-mediated gene deletion and the cre-loxP system: an intronic region overlapping with CUT568 but not with the ncRNA (negative control deletion mutant) and the intronic region corresponding to the ncRNA (GLC7 ncRNA deletion mutant). For the alteration, we inserted 139 bp in the middle of the predicted ncRNA to modify its structure (GLC7 ncRNA insertion mutant, see Methods). Previously it was shown that replacing the GLC7 gene with its cDNA decreases the cell viability in NaCl stress (JUNEAU et al. 2006;PARENTEAU et al. 2008). In order to determine if this defect was due to the ncRNA structure rather than the intron in itself or the CUT568, we tested all engineered strains with the mutated GLC7 intron in F1 medium and in F1 medium containing 0.9 M NaCl (Fig 5A). In F1 supplemented with 0.9 M NaCl, we observed a significant difference in growth, as estimated by the area under the growth curve (NORRIS et al. 2013), for both GLC7 ncRNA deletion and insertion mutants (Student's t-test, p = 1.4 x 10 -9 and p = 1.88 x 10 -7 , respectively) compared with the wild type or the negative control deletion (p = 2.44 x 10 -9 and p = 9.67 x 10 -9 respectively, Fig 5B).
Specifically, we found that in the F1 + 0.9 M NaCl media the lag phase (λ) is longer in the GLC7 ncRNA deletion and insertion mutants. Moreover, their maximum growth rate (µ) and the final biomass after 48 hours (A) are decreased, whereas for the negative control deletion mutant those parameters are the same as the wild type ( Fig S7).
We further verified the phenotypic difference of the mutant using one-to-one competition experiments. The wild type BY4742 strain and the GLC7 deletion mutant were grown together in F1 medium supplemented with 0.9 M NaCl and the composition of the population was analyzed after 37 generations. A significant drop in relative amount of the mutant strains was detected with just over 25 % of total cells being GLC7 deletion mutant, instead of the expected 50 % (Student's t-test, p = 7.30x10 -5 ). Taken together, these data further indicate that the deletion of the putative ncRNA in the GLC7 intron is responsible for the observed impairment of cell growth rate and competitive fitness during salt stress, whereas deletion of the upstream intronic region overlapping the CUT568 expressed from the opposite strand has no impact on the phenotype in salt stress.
We then looked at the expression of GLC7 via real time PCR in both wild-type and GLC7 ncRNA deletion mutant. The data shows that the deletion of the ncRNA in GLC7 intron does not impair splicing and that the GLC7 mRNA level appears to be slightly elevated in F1 media compared to that of wild type (1.21 ± 0.07). However, in salt stress the GLC7 mRNA level of the GLC7 ncRNA deletion mutant is reduced to 0.60 ± 0.12 of that of the wild type ( Fig 5C). We suggest that the phenotypic effect of the ncRNA knockout under salt stress may be due to the decreased expression of GLC7 in the GLC7 ncRNA deletion mutant.

DISCUSSION
Using multiple computational methods, we predicted stable and conserved RNA structures in 19 introns, 12 of which are present in ribosomal protein genes. By RT-PCR, we validated the presence of the predicted ncRNAs and, in several cases, of the whole introns. Our predicted RNA structures include in the 5' UTR intron of RPS22B HAC1 and YRA1 introns contain structures that regulate their own splicing and IMD4 and NOG2 contain snoRNAs that guide chemical modification of other RNAs, whereas GLC7 and MPT5 introns appear to be required for stress tolerance (PARENTEAU et al. 2008). Our data raise the possibility that, at least in some cases, a processed ncRNA is responsible for the biological function, rather than the intron itself.
Our experimental characterization and follow-up analysis has allowed us to generate hypotheses regarding the mechanism of function of specific sequences. For example, the GLC7 intron was previously shown to mediate the response to salt stress (PARENTEAU et al. 2008) and we now demonstrate that the factor responsible for the biological function is an intronic ncRNA sequence with a discreet RNA structure (see Fig 5). Furthermore, characterization of the stable ncRNA by RT-PCR suggests that the predicted structure functions in trans after removal from an intron lariat to enhance the expression of the GLC7 gene. Similarly, a recent study in human cancer cells showed that the SMYD3 intron may negatively regulate the expression of the We and others observe that many of the introns examined are retained in the pre-mRNA or maintained in the cell after splicing. This is consistent with the observations of Coleclough and Wood (1984) who were the first to described discrete intron products processed from the mouse immunoglobin pre-mRNA. Immunoglobulin mRNAs are expressed at high levels, like the ribosomal genes tested in our study. We therefore speculate that post-splicing intron stability might be a prevalent phenomenon for highly expressed genes and that intron products may be regulators of these highly expressed gene products.

CONCLUSIONS
We undertook a systematic approach using the well-studied Saccharomyces cerevisiae genome in order to identify introns with undiscovered function. Comparing intron sequences of related yeast species, we found at least 19 introns contain putative conserved RNA structures. By RNAseq and RT-PCR, we show that several of the intronic sequences containing secondary structures are not degraded after removal from pre-mRNAs. Furthermore, we show that ncRNAs embedded in introns can be directly responsible for regulating gene expression and maintaining phenotype in the intron-poor yeast. For example, a small portion of the GLC7 intronic sequence, representing a novel ncRNA, plays an important role in the cellular response to salt stress. More generally, the cellular abundance of intron sequences from ribosomal protein genes with predicted intronic ncRNAs are significantly more highly expressed than those lacking such predictions. Overall, our data support the possibility that the presence of functional RNA structures in introns has contributed to selective intron retention in the Saccharomycetes.

MATERIALS AND METHODS
Intron alignments: Sequences of intron-containing genes were extracted from the Saccharomyces Genome Database (SGD, http://www.yeastgenome.org/). Genes orthologous to intron-containing genes from S. cerevisiae were identified in 36 fungal genome sequences (Table S1) using TBLASTX with the coding gene sequence as the query, and with following settings: -E e-6 -qframe 1 -hspsepsmax 1000 -topcomboN 1. We collected the sequences of putative orthologs with at least 65% query coverage, to which 1000 bp and 300 bp of flanking sequence were added to the 5' and 3' ends of each hit. The putative ortholog gene sequences were then searched for the presence of the orthologous intron using BLASTN with options: -E 0.1 -W 3 -hspsepsmax 1000.
The best hit (with the lowest e-value and confirmed by manual inspection) was retained for each intron in each species. RNA structure predictions: Three structure prediction programs were used: CMfinder (v 0.2) RNAz (v 2.0) and Evofold (v 7b). Sequences of orthologous introns were used for predictions with CMfinder as described in Torarinsson et al. (2008).

Strains and media:
Intron sequence replacement strains were engineered from the BY4743 (MATa/α,his3Δ1/his3Δ1,leu2Δ0/leu2Δ0,lys2Δ0/ LYS2,MET15/met15Δ0,ura3Δ0/ura3Δ0;4741/4742),BY4742 (MATα,his3Δ1,leu2Δ0,lys2Δ0,ura3Δ0) and BY4741 (MATa,his3Δ1,leu2Δ0,met15Δ0,ura3Δ0) parental strains and maintained in YPD medium containing 2% (w/v) yeast extract, 1% (w/v) peptone and 2% (w/v) glucose. The transformants were plated on solid YPD medium with 300 mg/ml geneticin (GibcoBRL, UK) for kanMX selection and on 10 mg/ml phleomycin (Invitrogen) for pCre-ble selection. Mineral salt F1 media was prepared as described previously (BAGANZ et al. 1998) and the synthetic minimal SD medium (0.67% Bacto yeast nitrogen base without amino acids, 2% glucose) was supplemented with required amino acids appropriate for the parental strain. RNA concentration and quality was evaluated by measuring absorbance at 260 nm on a NanoDrop spectrometer ND-1000 (Thermo Scientific). The low molecular weight enriched RNA sample was obtained from total RNA as described in Catalanotto et al. (2002). Total RNA was used for RNAseq and both total and low molecular weight enriched RNA was used for RT-PCR. The number of reads mapping to introns and their host genes is presented in Supporting Information 3.

Analysis of exosome target data:
The CRAC data presented by Schneider et al. (2013) were filtered for genes that contain introns. From the RNAseq data presented here, we calculated the number of reads in RPKM corresponding only to the ORFs for the same set of genes. For each individual CRAC experiment, the number of reads for each gene was normalized by the number of ORF reads for this gene from our RNAseq data. The percentile rank of normalized values was calculated for each gene in each CRAC experiment, and then averaged across the sixteen CRAC experiments (Supporting Information 3). We considered genes with an average percentile rank with the top 10% to be preferentially bound by the exosome protein components.
Deletion of predicted intronic RNA: In order to generate deletions of intron fragments or insertions into introns, the Cre-loxP system was used with a kanMX cassette flanked by loxP sites (GULDENER et al. 1996). Deletion cassettes were amplified as described previously (DELNERI et al. 2003). The S. cerevisiae BY4743 strain was transformed with 1 µg of each PCR product according to Gietz and Schiestl (2007). Selection of mutants and PCR confirmation were performed as described by Carter and Delneri (2010). The strains with the loxP-kanMX-loxP cassette were then transformed with the plasmid containing Cre-recombinase to excise the sequence between two loxP sites. Cre-recombinase was induced by culturing the cells overnight in the YP-raffinose medium and then for 2-3 h in YP-galactose medium. Growth rate assay: Growth properties of the BY4742 strain and the intron mutants were assessed by time course growth profiles obtained using a FLUOstar optima microplate reader. Cells were cultured to stationary phase in YPD or F1 medium. The OD was measured at 595 nm and the cultures were diluted to an OD at 595 nm of 0.1 with pre-warmed YPD media, F1 media or F1 media containing 0.9 M NaCl. Each of the 96 plate wells was filled with 240 µl of diluted culture or media control.
Absorbance measurements were taken every 5 minutes immediately after 1 minute shaking. Growth curves were plotted and analyzed using R according to a modified version of the method specified previously (NORRIS et al. 2013). In brief, the area under each growth curve (AUC) was calculated by the pracma package from normalized absorbance data. Additionally, we fitted growth curves from data points taken every 30 minutes using grofit R package with default settings (KAHM et al. 2010). Maximum growth rate, lag-phase and maximum growth were calculated from the fitted curves.
Competitive growth test: Competitive growth assays were performed in 8 ml media by adding equal number of cells (2 × 10 5 cells/ml) of a mutant strain and the BY4742 reference strain, which had the HO gene replaced with kanMX as a marker to facilitate selection between strains. The GLC7/reference competition was performed in F1 media containing 0.9 M NaCl. The cultures were grown at 30 °C and maintained in log-phase by diluting each culture to 2 × 10 5 cells/ml in fresh media every 12-24 h until generation number 37 ± 1 or 50 ± 2 was attained for F1 + 0.9 M NaCl or YPD media, respectively. The number of generations was calculated as described by Parenteau et al. (2008). When the appropriate generation number had been reached, approximately 200 cells were plated on YPD media and after 2 days replicated onto YPD + geneticin. Cells were counted to obtain the ratio of mutant versus reference strains.    • A Schematic representation of intron mutants used for phenotype studies.
• B The GLC7 ncRNA deletion and GLC7 ncRNA insertion mutants disrupting the structure sequence of GLC7 intron were compared with the wild type strain and the intronic negative control in F1 medium containing 0.9 M NaCl.
Values in the box plots present the means of the area under the growth curve (AUC) as determined by R pracma package. Significant p-values obtained from Student's t-tests are indicated (***: p < 10 -6 ).
• C Expression levels (average expression with standard error bars) of GLC7 mRNA in the WT and in the GLC7 ncRNA deletion mutant grown in F1 and F1 + 0.9M NaCl media, assessed by real time PCR.  Figure S1. RT-PCR confirmation of ncRNA expressed from introns. Products for:

SUPPLEMENTARY INFORMATION
Lane designations for DNA templates: G, Genomic DNA; T, total cDNA; L, low molecular weight enriched cDNA; (-), no template negative control. Except GLC7 ncRNA, which was run on a separate gel, for each gene brightness and contrast applied equally across the entire gel image. Figure S2. RT-PCR confirmation of intron expression accompanied by complete mRNA splicing. Products for: Lane designations for DNA templates: G, genomic DNA; T, total cDNA; L, low molecular weight enriched cDNA; (-), no template negative control. Brightness and contrast were applied equally across each gel image.  • Lane designations for DNA templates: G, Genomic DNA; T, total cDNA; L, low molecular weight enriched cDNA; (-), no template negative control. Except YRA1 ncRNA, which was run on a separate gel, for each gene brightness and contrast applied equally across the Figure S6. Control RT-PCRs confirming mRNA splicing status and intron expression. PCR products for genes: • G RPS19A/B. Lane designations for DNA templates: G, Genomic DNA; T, total cDNA; L, low molecular weight enriched cDNA; (-), no template negative control. Brightness and contrast was applied equally across each gel image. For RPS16A and RPS19B designed mRNA primers also hybridize with the paralogous genes RPS16B and RPS19A giving two products from genomic DNA template. Figure S7. Growth of GLC7 mutants in F1 and F1 + NaCl media.
• A Growth curves made by plotting average OD measurements for each mutant taken every 60 minutes with bars representing standard deviation. • B Maximum slope of a growth curve for each mutant.
• C Lag-phase time estimated from growth curves.
• D Maximal growth for each mutant. Mutants are labelled as displayed on the legend in the bottom right corner. Data presented in (B)-(D) was obtained by growth curve fitting with R package grofit.