Three distinct TRAMP complexes are detected in vivo

The TRAMP complexes potentially comprise four different combinations of Trf4/5 and Air1/2, together with Mtr4. We assessed the actual combinations formed in vivo, by tandem-affinity purification and MS. Air1, Air2, Trf4, and Trf5 were each tagged with His6-TEV-protein A (HTP). Purifications were initially performed under high salt conditions (1 M NaCl) to recover only stable interactions. Associated proteins were identified by MS and subjected to label-free quantification. iBaq scores28,29 were calculated for each protein recovered (Supplementary Data 2). These indicated that Air1 interacts with both Trf4 and Trf5, while Air2 interacts almost exclusively with Trf4 (Fig. 1c). Previous analyses reported that Mtr4 is not efficiently retained in TRAMP above 125 mM NaCl4. Consistent with this, Mtr4 was weakly recovered in the 1 M NaCl preparations. These data demonstrate that three distinct TRAMP complexes co-exist in vivo, containing Trf4 + Air1 (TRAMP4-1), Trf4 + Air2 (TRAMP4-2), and Trf5 + Air1 (TRAMP5-1) (Fig. 1d). Each presumably also associated with Mtr4.

Trf5 and Air2 were not detected in association with either reciprocal precipitation, but it was unclear whether this reflected an inability to interact, or simply a higher affinity for Trf5–Air1 binding. To test this, AIR1 was deleted in the strain expressing Trf5-HTP. In the air1∆ strain, Air2 was well recovered with Trf5-HTP, indicating competition for Trf5 association and redundancy between Air1 and Air2 (Fig. 1c).

To further characterize factors binding to Trf4 and Trf5, these purifications were repeated at 150 mM NaCl, with and without the inclusion of RNase treatment (Supplementary Data 3 and Fig. 1e; colored boxes indicate fold enrichment in the precipitation indicated relative to the non-tagged control; <2-fold enrichment is gray). In this lower stringency purification, Mtr4 was well recovered with both Trf4 and Trf5, independent of RNA. However, in the air1∆ strain, recovery of Mtr4 with Trf5 was RNase sensitive (Trf5 air1∆). This suggests that the Trf5–Air1 complex binds jointly to Mtr4, and that this interaction is not fully recapitulated by Trf5–Air2, making the complex less stable.

Nab3 and Nrd1, subunits of the Nrd1–Nab3–Sen1 complex, were recovered with Trf4 but not Trf5, consistent with the reported presence of a Nrd1-interacting motif in Trf4 but not Trf525. Both Nab3 and Nrd1 are implicated in RNA surveillance on RNAPII and RNAPIII transcripts, but are not known to participate in pre-rRNA degradation. The 5′ exonuclease Xrn1 showed RNase-sensitive recovery with Trf4 and was also identified with Air1 and Air2. Xrn1 is predominately cytoplasmic, but several studies have reported nuclear roles30,31,32,33, consistent with this finding. Several early binding, pre-mRNA packaging factors were also recovered with Trf4 and Trf5, likely reflecting the role of TRAMP in promoting rapid degradation of non-coding RNAs (ncRNAs)6,34, and these interactions were largely RNase sensitive.

Multiple proteins associated with both the box C/D and box H/ACA classes of small nucleolar RNAs (snoRNAs) were strongly recovered with Trf4, Air1, and Air2, consistent with the reported involvement of Trf4 in snoRNA maturation35,36. Curiously, recovery of the small nucleolar ribonucleoprotein (snoRNP) proteins with Trf5 was enhanced in the air1∆ strain, which has increased Trf5–Air2 association, possibly indicating that Air2 contributes to snoRNP binding. A subset of ribosome synthesis factors was recovered, showing greater interaction with Trf5 than Trf4 and, particularly, with Air1 relative to Air2, for which none showed >2-fold enrichment (Fig. 1e). This suggests a preferential role for TRAMP5-1 in pre-rRNA degradation.

Notable omissions were Utp18 and Nop53, which were reported to bind Mtr4 directly in the context of pre-ribosomes and promote TRAMP-independent, pre-RNA processing16. The exosome was also very poorly recovered (Supplementary Data 3), consistent with the failure of the original exosome purifications to recover TRAMP components and vice versa4,5,37. TRAMP–exosome interactions may be too transient in vivo to be readily recovered.

The TRAMP complexes exhibit distinct substrate preferences

RNA targets of the different TRAMP subunits were identified by in vivo UV-cross-linking followed by protein purification and sequence analysis of cDNAs (CRAC). We compared strains in which the endogenous gene was HTP tagged for Air1, Air2, Trf4, Trf5, and Mtr4, as well as the exosome exonucleases Rrp44 and Rrp6. The Mtr4 arch domain is implicated in substrate recruitment13,14,38,39, so we also constructed and analyzed a tagged Mtr4 mutant lacking this region (Mtr4∆arch) (Supplementary Fig. 1A). The Mtr4∆arch construct was expressed from PMTR4 in a strain in which wild-type (WT) Mtr4 was under PGAL control, allowing its depletion on glucose medium (Supplementary Fig. 1B).

Comparison of RNA target classes recovered with each protein showed clear differences (Fig. 2a). Notably, pre-rRNA spacer regions (external transcribed spacer (ETS) and internal transcribed spacer (ITS)) were substantially more targeted by Air1 than Air2, whereas Trf4 and Trf5 exhibited similar recovery. They were also less recovered with Mtr4∆arch relative to Mtr4, consistent with pre-rRNA maturation defects reported for strains carrying arch mutations (Supplementary Fig. 1C)13,14,38,39. In contrast, the major ncRNA classes, CUTs, SUTs, and XUTs, were strongly recovered with Air2 and Trf4, relative to Air1 plus Trf5. Notably, protein-coding genes appeared to be major targets of Trf5, which showed the strongest recovery compared to the other factors.

Fig. 2: RNA interactions by TRAMP components.

a, b Distribution of all (a) and non-encoded A-tailed (b) reads mapped to different RNA substrate classes recovered in CRAC datasets. Two biological replicates were averaged for each protein. c Correlation matrix displayed as a heat map showing correlation between binding sites recovered with different factors. Note: Above the diagonal, the matrix shows the extent to which the factors target the same RNA species as “co-targeting of RNAs.” Below the diagonal, the matrix shows the extent to which the factors target the closely positioned RNA sites (≥50 nt) as “co-localization of sites.” See Supplementary Data 4 for values for individual CRAC dataset.

TRAMP targets are expected to be subject to oligoadenylation, so we specifically analyzed cDNAs that carry additional, 3′-terminal non-templated A residues (Fig. 2b). These are very likely to represent the authentic 3′ ends of RNAs that have been recognized by one of the TRAMP complexes and targeted for degradation by oligo(A) addition. In these datasets, the preference for Air1 over Air2 in pre-rRNA binding was even more marked. Similarly, the preference for Air2 and Trf4 in recovery of ncRNAs was more striking in the oligo(A) population. This was seen for CUTs, SUTs, and XUTs, as well as antisense and intergenic regions and RNAPIII transcripts (“other ncRNAs” in Fig. 2b).

Similarities and differences between TRAMP components were assessed by the degree of correlation between the recovered targets for RNAPII transcripts (Fig. 2c and Supplementary Fig. 2, Supplementary Data 4) As expected, target RNA species (“co-targeting”) were more similar than the co-localization of the precise binding sites for different factors (“co-localization”). Consistent with the proteomic analyses and target RNA classes, Air1 binding was similar to Trf4 and Trf5, while Trf4 showed similarity to both Air1 and Air2. In contrast, Trf5 binding was more similar to Air1 than to Air2, while Air2 more resembled Trf4 that Trf5. Notably, targets for Mtr4∆arch were substantially less well correlated with all other TRAMP components than intact Mtr4 (Fig. 2c). This might not have been anticipated, since the arch domain was implicated in targeting Mtr4 to degrade specific pre-rRNA spacer regions that are independent of TRAMP15,16. Higher correlations between different TRAMP components were observed for oligo(A) RNAs than considering all reads (Fig. 2c and Supplementary Fig. 2), confirming that filtering for adenylated species more reliably identifies bona fide surveillance targets.

Trf5–Air1 recruits Mtr4 to the A2–A3 region of the pre-rRNA

Mtr4 and the exosome are required for degradation of the excised 5′ ETS and the ITS2 region present in the 7S pre-rRNA. These are “default” activities, in that they are required during maturation of all pre-rRNAs, and neither is known to involve the TRAMP complexes. In both cases, Mtr4 is directly recruited to the pre-ribosome by binding to AIM-containing proteins, Utp18 and Nop53, respectively16. In contrast, the 23S RNA, an aberrant intermediate that extends from the transcription start to site A3 in ITS1, is also a characterized Mtr4 and exosome substrate, but is an subject to RNA oligoadenylation and surveillance27. To assess the roles of other TRAMP components in Mtr4 recruitment, we tested strains lacking Air1, Air2, Trf4, or Trf5. Notably, loss of the other TRAMP components did not affect Mtr4 abundance (Supplementary Fig. 1D).

Analysis of protein binding in ITS1 (Fig. 3 and Supplementary Fig. 3) using oligo(A) reads (Fig. 3) showed high binding of Air1, Trf5, and Mtr4 at positions 5′ to site A3 (the 3′ end of 23S) relatively to total reads (Supplementary Fig. 3A, D, E), whereas little association was seen for Air2 or Trf4 (Fig. 3b, c and Supplementary Fig. 3B, C). Mtr4 binding across ITS1 was also tested in strains deleted for TRAMP component (Fig. 3f–i and Supplementary Fig. 3F–I). Loss of Trf5 or Air1 strongly reduced Mtr4 association (~5.8- and ~3.7-fold, respectively) (Fig. 3f, i, m). The effects of air1∆ were more modest, probably due to its replacement by Air2 (see Fig. 1c). Strains lacking Air2 also showed a reduction in Mtr4 association with ITS1 (~3.2-fold decrease), while loss of Trf4 had a milder effect on Mtr4 binding at this site (~2.0-fold).

Fig. 3: TRAMP interaction sites on the pre-rRNA ITS1 region.

ak Distribution of non-encoded oligo(A)-tailed reads, normalized to millions of total mapped reads, across the ITS1 region of the pre-rRNA. The graph shows the distribution of reads recovered with the indicated TRAMP components (ae), Mtr4 in strains lacking the indicated TRAMP components (fI), Mtr4 lacking the arch domain (j), and Rrp44 (k). Scale is linear. A diagram of the pre-rRNA region is also shown. Two independent replicates are shown in panels as light and dark colored lines. m, n Hits per millions oligo(A)-tailed reads (m) and total reads (n) encompassing the A2–A3 region of ITS1 extended by 10 nt from each side were summed and are exhibited as a bar diagram. Two individual replicates were averaged, with standard deviation shown as error bars (except for Mtr4 (trf4∆) for which only one experiment was performed). o Northern blot analysis with probe for the A2–A3 fragment (probe for 5S rRNA was used as a loading control). p Model for surveillance within ITS1. Trf5 and Air1 are recruited co-transcriptionally to the A2–A3 region. Following A2 cleavage, ribosome synthesis factors are released, freeing site A3. Mtr4 is recruited, probably via protein–protein interactions involving Trf5 and an Mtr4 arch interaction. Following A3 cleavage, Trf5 oligo-adenylates the free 3′ end prior to degradation by the exosome.

These observations probably reflect both alterations in the balance of the remaining TRAMP complexes, when one component is absent, and the significant redundancy between Air1/Air2 and Trf4/Trf5 proteins. In the absence of Air2, increased levels of free Trf4 are expected to compete with Trf5 for Air1 binding, leading to increased formation of TRAMP4-1 and correspondingly reduced TRAMP5-1. This will partially mimic effects of air1∆, consistent with ITS1 binding specificity arising from Trf5.

To directly assess redundancy of the Air proteins and the altered balance of TRAMP complexes in strains deleted for TRAMP components, we performed CRAC on Air1 in an air2∆ strain, and on Air2 in air1∆ (Supplementary Fig. 4). In the air2∆ background, Air1 was less recovered (~2.5-fold decrease) across ITS1 relative to the AIR2 strain (Supplementary Fig. 4A, C, E, G, I, J). We conclude that the absence of Air2 leads to its partial replacement by Air1, with increased TRAMP4-1 formation and correspondingly less TRAMP5-1 than in WT. This depletes binding across transcripts specifically targeted by Trf5. In contrast, binding of Air2 across ITS1 was minimally affected by loss of Air1 (Supplementary Fig. 4B, D, F, H–J), probably indicating that a Trf5–Mtr4–Air2 complex is not efficiently recruited to Trf5-specific targets. Similarly, in the absence of Trf4, TRAMP5-1 is expected to partially occupy previous TRAMP4-1 and 4-2 binding sites, reducing recovery at sites specifically occupied by Trf5 in the WT background.

Deletion of the arch domain from Mtr4 (Fig. 3j, m) also strongly reduced its association upstream of site A3. Similar profiles were observed for total, unfiltered reads (Fig. 3n and Supplementary Fig. 3E, J), confirming that the loss of Mtr4 binding in trf5∆ was due to a recruitment defect and not to reduced oligoadenylation. Neither Rrp44 nor Rrp6 showed clear binding across the A2–A3 region. We re-analyzed published data for exonuclease-deficient Rrp44 (Rrp44 exo), which is stabilized in binding to many exosome substrates, but this also did not show clearly elevated binding to A2–A3. Northern blot analysis showed strong accumulation of cleaved A2–A3 fragment in trf5∆ compared to WT, confirming the role of Trf5 in degradation of this RNA (Fig. 3o). No comparable effect was observed for trf4∆.

We conclude that recruitment of Mtr4 to the A3-cleaved pre-rRNA requires both Trf5 and the arch domain (see Fig. 3p for a cartoon). The finding that the loss of Mtr4 was modest in the absence of Air1 indicated that this is largely redundant with Air2. This was unexpected, since it had long been envisaged that RNA-binding specificity would largely be determined by Air1 and Air2, which are Zn-knuckle RNA-binding proteins4,5,26,40.

In an attempt to identify regions of Trf4 or Trf5 responsible for target specificity, we generated Trf5 constructs with non-conserved domains deleted or exchanged with Trf4. Unfortunately, neither deletion nor exchange of the N-terminal domain resulted in stable protein accumulation. Stable fusion constructs were expressed in which the C-terminal domain was deleted (Trf5∆CTD) or replaced by Trf4 C-terminal domain (Trf5-CTD4), or in which a 5-aa, AIM-like sequence was replaced by 5 Ala (Trf5-5xA). In CRAC analyses, these constructs all showed inefficient cross-linking, resulting in poor signal-to-noise ratios and variable results (Supplementary Fig. 6C–G and Fig. 8). However, the Trf5 C-terminal domain appeared to be important for recruitment of Trf5 to pre-rRNA (Supplementary Fig. 6C), particularly across the A2–A3 region of ITS1 (Supplementary Fig. 6E, F), whereas the AIM-like domain appeared dispensable for recruitment (Supplementary Fig. 6G).

Trf4 and Trf5 are enriched on different regions of pre-mRNAs

The distribution of TRAMP components on protein-coding genes was initially assessed in metagene analyses of mRNAs aligned by the transcription start sites (TSS) or pA sites (Fig. 4a–m; all protein-coding genes >500 nt in length were included in metagene plots).

Fig. 4: Metagene analyses of TRAMP components across protein-coding genes.

Binding by RNA surveillance and degradation factors is strongly enriched close to the TSS on protein-coding genes. an Distribution of individual components indicated, across all mRNAs longer than 500 nt. Each panel shows the hit density, normalized to millions reads mapped to mRNAs. The two lines in each panel represent results from independent CRAC experiments. Reads were aligned with transcription start sites (TSS) and polyadenylation sites (pA). op Distribution of Rrp44 in strains expressing Mtr4 or Mtr4∆arch across the 200 mRNAs showing the greatest dependence on the arch for Mtr4 recruitment. Each panel shows the hit density, normalized to millions of reads mapped to mRNA, for all genes longer than 500 nt. The two lines in each panel represent results from independent CRAC experiments. Reads were aligned with transcription start sites (TSS) and polyadenylation sites (pA). q Model representing proposed recruitment pathways. Close to the TSS, Nrd1–Nab3–Sen1-mediated early transcription generate TSS-proximal ncRNAs and recruits TRAMP4-2 through Trf4 and interactions involving the arch domain. Following Trf4-mediated oligoadenylation, RNAs are targeted to both Rrp44 and Rrp6 nucleases activity of the exosome. A distinct surveillance mechanism occurs at some pA sites involving specifically TRAMP5-1 and Rrp6, which can also be directly recruited by Nab363.

Strong, promoter-proximal enrichment of the exosome has previously been reported41,42, reflecting degradation of ncRNAs generated by early RNAPII termination (shown for the exosome catalytic subunits Rrp6 and Rrp44 in Fig. 4f, l). Similar 5′ enrichment was seen for Mtr4 (Fig. 4a), Air2 (Fig. 4c), and Trf4 (Fig. 4d), as well as the exosome-associated nucleases Rrp6 and Rrp44 (Fig. 4l–n). In marked contrast, pA site-proximal peaks were seen for Trf5, Rrp6, and to a lesser extent for Air1, but not for Trf4, Air2, or Rrp44. In addition, a modest pA-proximal peak was seen for Mtr4.

Analysis of mRNA binding by Air1 in air2∆ and Air2 in air1∆ strains (Supplementary Fig. 4K–N) revealed profiles that are much more similar than in the WT background. In the absence of Air2, recovery of Air1 was elevated on mRNAs, particularly in the TSS-proximal region where Air2 is normally bound. In the absence of Air1, recovery of Air2 was elevated at the pA site, where a peak of Air1 is otherwise observed. These observations strongly support the model that the specificity of binding by TRAMP complexes is largely conferred by Trf4 and Trf5.

All TRAMP components showed substantial numbers of hits within pre-mRNA introns (Supplementary Fig. 5), with TRAMP4-1 apparently most strongly targeting introns. Notably, the arch domain appears to be dispensable for Mtr4 recruitment to introns.

The 5′ peak for Mtr4 was reduced by either deletion of the arch (Fig. 4g) or the absence of Trf4 (Fig. 4j), but was not clearly altered by loss of Trf5, Air1, or Air2. Recruitment of Trf4 to the TSS was not clearly affected by Mtr4∆arch (Fig. 4f and Supplementary Fig. 1E). These results are consistent with arch-dependent recruitment of Mtr4, with specificity dependent on Trf4. Surprisingly, recruitment of Rrp44 was unaffected in Mtr4∆arch (Fig. 4m, n). The same analysis was performed considering only the mRNAs for which Mtr4 binding was most dependent on the arch domain; that is, the 200 mRNAs that showed the greatest reduction in recovery with Mtr4∆arch compared to Mtr4 (Fig. 4o, p). On these mRNA, the TSS-proximal peak of Rrp44 was substantially decreased, indicating that the Mtr4 arch domain plays a role in TSS-proximal recruitment of the exosome on specific targets (see model in Fig. 4q).

Distribution of TRAMP components on individual mRNAs

The metagene plots indicated differential recruitment of Trf4 and Trf5, so we next assessed whether this reflected preferential association with different mRNA subsets. The top 1000 mRNAs in the CRAC datasets for each TRAMP component were combined (2005 mRNAs in total). All mRNAs were divided into five bins of equal length and the distribution of each factor was determined for every bin. These data were used to cluster genes with related patterns of factor distribution (Fig. 5a and Supplementary Fig. 7, Supplementary Data 5). This analysis identified groups of mRNAs with distinctly different TRAMP occupancy.

Fig. 5: Heat maps for distribution of TRAMP components on each mRNA.

a Heat map showing binding across individual mRNAs of different factors. The top 1000 protein-coding genes recovered in CRAC with each TRAMP component were selected and combined (2005 mRNAs in total). Each transcript was divided into five bins of equal length from TSS to pA site. Binding across each bin was calculated as a fraction of total binding across individual gene (set to 1). The number of reads was averaged between two biological replicates. Only the coverage of Air1, Air2, Trf4, Trf5, and Mtr4 along each transcript was used for Euclidean distance-based clustering. Other datasets shown were not included in the clustering analysis but are sorted according to the clustered list. The data are displayed as heat maps. The RPM for each transcript recovered by each protein was calculated and represented as independent heat maps. See Supplementary Data 5 for cluster composition. b Enriched GO terms43 and features for clusters of mRNA defined in a.

The largest group of mRNAs was cluster 3 (Fig. 5a and Supplementary Fig. 7C, I), which showed high TSS-proximal occupancy of Trf4, Air2, and Mtr4, with somewhat lower binding for Air1 and Trf5. This is consistent with the metagene profiles in Fig. 4. In contrast, cluster 2 showed high poly(A) proximal occupancy of Trf5, Air1, and Mtr4, with lower total binding of Air2 and Trf4 (Fig. 5a and Supplementary Fig. 7B, H). These features are also seen in metagene plots (Fig. 4). Other clusters showed distinct features: in cluster 1 (Fig. 5a and Supplementary Fig. 7A, G), Trf5 showed substantial 3′ occupancy, along with a mild enrichment for Air1 (Supplementary Fig. 8). Cluster 1 mRNAs are very likely targeted by two distinct pathways: a minor one in which TRAMP4-1 plus TRAMP4-2 bind proximal to the TSS and the major pathway in which Trf5 targets the 3′ end, probably partly with Air1. In consequence, Air1 hits within the mRNA are split between TSS and the pA site. Since the data are normalized across each mRNAs, this results in a reduced 3′ peak for Air1 relative to Trf5 (Supplementary Fig. 8). Rrp6 and Rrp44 are not clearly 3′ enriched on these mRNAs, suggesting that their interaction with Trf5 may not be linked to surveillance. In cluster 4, Trf4, Trf5, Air1, Air2, Rrp6, and Rrp44 all show moderate TSS-proximal binding, but Mtr4 is largely absent. Surprisingly, TSS-proximal binding was relatively increased for Mtr4 in trf4∆ or trf5∆ strains and for Mtr4∆arch (Fig. 5a and Supplementary Fig. 7D). However, total association for Mtr4 was reduced in the absence of Trf4 (Supplementary Fig. 7J).

The identified clusters in the heat map were analyzed for GO term enrichment of the protein products, as an indication of functional classes43 (Fig. 5b). Each cluster showed highly significant enrichment for mRNAs encoding specific, functional subsets of proteins. This provides strong evidence that the TRAMP-binding patterns observed have functional consequences for the regulation of protein production.

Correlations in pre-mRNA-binding sites

Trf4 and Trf5 appear to recruit Mtr4 to at least some nuclear pre-mRNA sites, but the origin of their binding specificity was unclear. As an initial attempt to address this, we compared the distribution of TRAMP components to other nuclear RNA-binding proteins that have been similarly mapped using CRAC (Fig. 6 and Supplementary Fig. 2, Supplementary Data 4 and 6). For this we compared both the total relative recovery over each RNA species or the extent of binding at closely positioned RNA sites (closer than 50 nt) (designated as “co-targeting of RNAs” and “co-localization of sites,” respectively, in Fig. 6a and Supplementary Fig. 2). These analyses were performed either genome wide across all annotated genes (Supplementary Fig. 2, Supplementary Data 4) or over all annotated RNAPII transcribed genes (Fig. 6a and Supplementary Data 6).

Fig. 6: Correlations between protein interaction sites on RNAPII transcripts.

a Correlation matrix displayed as a heat map, showing correlations between binding sites recovered with different factors across RNA polymerase II transcripts. Note: Above the diagonal, the matrix shows the extent to which the factors target the same RNA species as “co-targeting of RNAs.” Below the diagonal, the matrix shows the extent to which the factors bind closely positioned RNA sites (≥50 nt) as “co-localization of sites.” bm Binding of the indicated proteins relative to Air1. CRAC peaks for Air1 across the genome were selected and used as a reference to align peaks for other proteins. Data are shown for the combined top 100 RNAPII transcripts bound by Npl3 and Air1 (bg, 127 genes in total) or top 100 mRNAs (hm, 147 genes in total). Two independent replicates were combined in each panel.

Some expected results were obtained; the nuclear poly(A) binding factors Pab1 and Nab2 were closely correlated and distinct from most other factors. However, Nab2, which has been implicated in RNA surveillance41, showed closer correlation with other surveillance factors (Fig. 6a). Similarly, the snoRNP proteins Nop1, Nop56, and Nop58 were closely correlated over RNAPII transcripts (Fig. 6a) or all genes (Supplementary Fig. 2). Ribosome synthesis factors (Utp proteins) were closely correlated on all genes, and showed correlations with surveillance factors, reflecting their interactions on pre-rRNAs.

For TRAMP components, Trf5 was better correlated with Air1 than with Trf4 or Air2, while Trf4 and Air2 were most highly correlated, consistent with the analyses of individual genes. The TRAMP components were also correlated with the exosome, as expected, although it was notable that Rrp6 was more correlated with Trf5, while Rrp44 correlated better with Trf4. Nab3 showed higher correlation with Air2 and Trf4 than Air1 and Trf5, consistent with Trf4 being recruited by Nrd1–Nab3 on some targets, including TSS-proximal ncRNA transcripts.

Hrp1, which was implicated in RNA surveillance41, also showed correlations with TRAMP factors. A number of other proteins, showed notably close correlations, including the pre-mRNA-binding protein Npl3 with Air1. It may be relevant that Air1 was initially identified through an interaction with Npl39. To follow-up this observation, Air1 CRAC peaks across the genome were selected using a peak-calling algorithm and used as a reference point to align reads from pre-mRNA-binding proteins and TRAMP components (Fig. 6b–m and Supplementary Fig. 10). Binding sites were compared across the top 100 bound RNAPII transcripts, which includes the abundant snoRNA species (Fig. 6b–g), or considering only mRNAs (Fig. 6h–m). Close co-localization was seen for Air1 and Air2 (Fig. 6e, k), supporting the conclusion that they are functionally redundant on many substrates. Consistent with the data in Fig. 6a, the peak of Air1 binding sites closely correlated with a peak of Npl3 binding over the top RNAPII transcripts (Fig. 6b; these include many snoRNAs) or mRNAs (Fig. 6f). Co-localization with Air1 was also seen for the surveillance factor Hrp1 (Fig. 6f, l).

Similar analysis were performed on Trf5∆CTD, Trf5-CTD4, and Trf5-5xA (Supplementary Fig. 9). As for the pre-rRNA analyses (Supplementary Fig. 6), these constructs gave poor cross-linking on mRNAs. However, mutation or deletion of the CTD increased Trf5 association with the TSS region (Supplementary Fig. 9A). Notably, deletion of the CTD apparently lead to more delocalized binding across almost all mRNAs (Supplementary Fig. 9C), presumably reflecting a loss of specificity.

Loss of Trf5 alters Mtr4 association and target mRNA abundance

Previous functional and structural analyses of TRAMP have largely focused on Trf4 and Air221,22,23,24,25. However, the heat maps (Fig. 5) indicated that subsets of nuclear mRNAs show preferential enrichment for binding to Trf5 (clusters 1 and 2). We therefore determined whether Trf5 has a functional impact on Mtr4 recruitment and mRNA stability.

mRNAs were stratified by ranking in Trf5 association, based on reads per kilobase per million mapped reads (RPKMs) across the genome. Bins of 200 mRNAs were compared between TRF5 and trf5∆ backgrounds for changes in Mtr4 association by CRAC (Fig. 7a) or RNA abundance by RNA-sequencing (RNAseq) (Fig. 7b and Supplementary Fig. 11). Strikingly, mRNAs that were most strongly bound by Trf5 showed greatest reduction in Mtr4 binding when Trf5 is absent. Note that these are normalized data, so total recovery of Mtr4 across all genes is constant. The effects were quite substantial, with nearly 4-fold reduced Mtr4 association over the genes that were most strongly bound by Trf5. Conversely, mRNAs with the strongest Trf5 binding were modestly increased in the absence of Trf5, again using normalized sequencing data. These data suggest that loss of Trf5 reduces Mtr4 recruitment with a consequent increase in pre-mRNA or mRNA stability. Changes in abundance shown in the RNAseq data were confirmed by real-time quantitative PCR on selected mRNAs (Supplementary Fig. 11A, Supplementary Table 7) relative to the ncRNA SCR1. The trend for increased mRNA abundance in trf5∆ was conserved between RNAseq and quantitative PCR (qPCR). However, greater increases were measured in qPCR, probably reflecting differences in normalization, which is complicated in surveillance mutants that potentially affect all RNA species.

Fig. 7: Alterations in mRNA abundance in strains lacking Trf5.

a Changes in Mtr4 binding by CRAC in strains lacking Trf5, relative to the wild type. b Changes in mRNA abundance by RNAseq in strains lacking Trf5, relative to the wild type. Genes are ordered by ranking in frequency of Trf5 binding (RPKM) and bars show fold change (log 2) in strains lacking Trf5 relative to the wild type. Note that these are normalized data, so the total recovery of Mtr4 across all genes is constant. c, d RNAseq distribution across mRNAs, normalized to the total binding value across the mRNA subset, in wild-type (four independent replicates averaged) and trf5∆ (three independent replicates averaged). Reads were aligned with the polyadenylation sites (pA). c shows genes grouped according to clusters identified in Fig. 5a, plus all mRNAs. In d, the 2005 genes analyzed in Fig. 5 are grouped by Trf5 binding in the 3′ region (bin 5 in Fig. 5a and Supplementary Fig. 7).

A notable finding from the heat maps was the identification of group of mRNAs showing strong 3′ association with Trf5 and Air2 = 1 in the absence of Mtr4 or the exosome (cluster 1 in Fig. 5 and Supplementary Fig. 8) suggesting a distinct function for TRAMP5-1 here. To assess potential roles of Trf5, we assessed the distribution of RNAseq reads across mRNAs in WT and trf5∆ strains (Fig. 7c, d). For cluster 1, comparison of the WT and trf5∆ strains showed a clear deficit in reads close to the poly(A) site in the absence of Trf5 (Fig. 7c). Strikingly, comparable effects were not seen for any other cluster. This is presented for cluster 2, which also showed a 3′ peak of Trf5, but accompanied by Trf4, Mtr4, and Rrp6, and cluster 3, which showed only a 5′ peak of Trf5 and other TRAMP components (Fig. 7c). When mRNAs were ranked by Trf5 binding in bin 5 (the 3′ end), the same trend was seen (Fig. 7d). However, even for the most highly bound group, the 3′ depletion in mRNAs reads was less marked than for cluster 1.

We conclude that mRNAs bound by Trf5 are selectively affected by its absence. Notably, the clustering in Fig. 5 was entirely orthogonal to the mRNA sequence data in Fig. 7, indicating that the specific 3′ binding by Trf5 identified in cluster 1 is robustly correlated with stabilization of this region of the transcripts.

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