Investigation of RNA quality control pathways in RNP hypo-assembly
diseases
by
Siddharth Shukla
Integrated M.Sc., Indian Institute of Technology Bombay, 2011
A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirement for the degree of Doctor of Philosophy Department of Chemistry and Biochemistry 2016
i This thesis entitled: Investigation of RNA quality control pathways in RNP hypo-assembly diseases written by Siddharth Shukla has been approved for the Department of Chemistry and Biochemistry
______Roy Parker
______James Goodrich
Date ______
The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline.
ii Shukla, Siddharth (Ph.D., Biochemistry) Investigation of RNA quality control pathways in RNP hypo-assembly diseases
Thesis directed by Professor Roy Parker
A key aspect of cellular function is the proper assembly and utilization of ribonucleoproteins (RNPs). Defects in the formation of RNPs lead to "RNP hypo- assembly diseases", which can be caused by RNA degradation out-competing RNP assembly. Examples of such human diseases include Dyskeratosis Congenita (DC) and
Spinal Muscular Atrophy (SMA).
In order to test the hypothesis that specific RNA quality control pathways were responsible for degradation of RNAs in these diseases, I used yeast and mammalian cell lines as model systems to investigate two different diseases, SMA and DC. In SMA,
Sm-site mutations in yeast U1 snRNA led to their rapid degradation by two different
RNA decay pathways: 3’ to 5’ decay in the nucleus by Trf4/Rrp6, and 5’ to 3’ decay in the cytoplasm by Dcp2/Xrn1. Cytoplasmic degradation of snRNAs when the Sm site is mutated is conserved in human cells. The cytoplasmic decay pathway is also responsible for the degradation of snRNAs when SMN levels are reduced, as is the case in SMA. Importantly, inhibition of snRNA decapping through DCP2 knockdown rescued splicing defects observed for some mRNAs when SMN is limiting. These results suggest that inhibition of snRNA decay could rescue some phenotypes of SMA.
For the investigation of human telomerase RNA (hTR) quality control pathways in
DC, disease causing mutations were introduced in hTR, along with the depletion of dyskerin in human cells. These models established that hTR is degraded by
PAPD5/EXOSC10 in the nucleus, and DCP2/XRN1 in the cytoplasm. Inhibition of hTR decay rescued both the sub-cellular localization of hTR, as well as telomerase activity in
iii human cells. Additionally, PARN, which is a 3’ to 5’ exonuclease, stabilized hTR through deadenylation of its 3’ end. PARN mutations also lead to a severe form of DC. I have identified other possible substrates of PARN in human cells, which suggest that PARN deadenylates a number of stable non coding RNAs in human cells, but influences the stability of a select few. This potentially explains why PARN mutations cause a more severe form of DC than mutations in telomerase components.
iv Acknowledgements
Pursuing graduate school was not something I had anticipated till the third year of my undergraduate studies, so I feel a deep sense of gratitude towards a number of provocative mentors and supportive friends for invigorating this zeal for scientific research. I thank my thesis advisor, Roy, for leading by example on this pursuit of fundamental knowledge of our cells and their various minutiae. I have learned skills from Roy that will be useful not only in the lab, but also outside of it- asking the right questions, questioning conventional knowledge when necessary, and pushing yourself to be as efficient as you can be, to name a few. I also thank Roy for giving me a chance to spend a summer in his lab during my undergraduate studies, an opportunity that ultimately led to five years of graduate school culminating in this thesis.
I thank my Master’s thesis advisor, Dr. P.I. Pradeepkumar, for mentoring me during my undergraduate studies at IIT Bombay, and providing me with a sound exposure to biological research, which was otherwise impossible to get in a core chemistry department. I also thank the former members of his lab, Dr. Kiran Gore, Dr. V.
Dhamodharan and Dr. Jagdeesh Chandrashekhar, for teaching me the skills that were of great utility in graduate school.
For an international student 9,000 miles away from the comfort of the native culture, the lab becomes family. I am extremely grateful to have had the good fortune of being a part of a supportive lab with talented and caring people all around me. It is a testament to the people here that we function more as a unit and less as a group of individuals pursuing their own research. I will cherish all the random chats about
America and food, as well as the discussions and feedback over my research. I
v especially want to thank two former members, Dr. Ross Buchan and Dr. Saumya Jain, for life-long memories and friendship.
I thank the members of my thesis committee for being so supportive and helpful over the last two years, and providing me your valuable insight which has fostered new ideas and directions in my research. I especially want to thank Tom for his input and guidance during my study of human telomerase RNA quality control, which has now become a fruitful collaboration. I also thank the members of the Cech lab for their help during the course of this collaboration.
Last but not the least, I want to express my love and gratitude to friends and family back home. Thank you mummy and papa for supporting me in all of my pursuits, even those that did not pan out. Thank you for never letting anything get in the way of my studies and research, even when times were hard. I thank my younger brother,
Rishabh, for being the best sibling one could ask for. I am very proud of the person and the doctor he has become, and his hard work and dedication motivates me when things are not going smoothly. Finally, I thank my girlfriend Navneeta, for five wonderful years of companionship and love, which have been a source of comfort and inspiration. Life would not be what it is without you in it!
vi Table of Contents Chapter 1: Hypo-assembly diseases of RNA-protein complexes ...... 1
RNA quality control pathways compete with RNP assembly ...... 1
Introduction ...... 1
Diversity of RNA quality control pathways in eukaryotes ...... 4
Hypo-assembly diseases of RNPs ...... 11
Dyskeratosis Congenita and degradation of telomerase RNA ...... 11
Spinal Muscular Atrophy and snRNA degradation ...... 14
RNP hypo-assembly diseases include pathologies of ncRNAs ...... 18
Hypo-assembly diseases of mRNPs ...... 20
Discovery of possible treatments for RNP hypo-assembly diseases ...... 23
Conclusion ...... 24
Chapter 2: Quality control of snRNAs in Spinal Muscular Atrophy ...... 25
Summary ...... 25
SMA is a neurodegenerative disease caused by snRNP deficiency ...... 26
Results ...... 28
Mutations in the yeast U1 snRNA Sm site destabilize the snRNA ...... 28
Defective U1 snRNAs are degraded by both 3' to 5' exonuclease Rrp6 and
decapping and Xrn1-mediated decay ...... 30
Decapping of defective U1 snRNAs in yeast is catalyzed by the Dcp2 enzyme ..... 36
Decapping and 5' to 3' degradation of defective snRNAs is conserved in
mammalian cells...... 38
vii Reduction of snRNA levels by SMN knockdown can be rescued by inhibition of
decapping and XRN1-mediated decay ...... 42
Knockdown of DCP2 partially suppresses some SMN knockdown dependent
splicing defects ...... 45
Discussion ...... 49
Assembly-defective snRNAs are subject to quality control ...... 49
Defects in snRNP assembly in mammals leads to decapping and 5' to 3' decay ... 49
Prevention of snRNA decapping may lead to rescue of snRNP function ...... 51
RNP biogenesis generally competes with quality control ...... 52
Experimental methods ...... 53
Construction of U1 Sm-mutants in yeast and mammals ...... 53
Yeast strains and plasmids ...... 53
Northern blotting from yeast cultures and quantification ...... 53
Mammalian cell culture ...... 54
Plasmid transfection in mammalian cells ...... 54
RNA interference in mammalian cultures ...... 54
Western blotting from mammalian cells ...... 55
Northern blotting from mammalian cells and quantification ...... 55
RT-PCR and splicing assay from NIH-3T3 cells ...... 56
Chapter 3: Quality control of human telomerase RNA in Dyskeratosis Congenita
...... 57
Summary ...... 57
Results ...... 59
viii Loss of dyskerin binding leads to hTR degradation ...... 59
EXOSC10 competes with PARN for processing of mature hTR ...... 64
EXOSC10 & PARN compete for PAPD5-mediated 3’ end processing ...... 68
Rescue of telomerase activity in DKC1 or PARN depleted cells ...... 68
Rescue of hTR subcellular localization by decay inhibition ...... 71
Discussion ...... 79
Experimental methods ...... 83
Cell culture ...... 83
Plasmid transfection and siRNA knockdown ...... 83
Northern blot analysis of hTR ...... 84
Immunofluorescence and FISH in U2OS and HeLa cells ...... 84
Telomerase activity assay for HeLa and U2OS cells ...... 85
hTR 3’ end sequencing ...... 86
Chapter 4: Disease causing mutations in 3’ to 5’ exonucleases affect processing and stability of human non-coding RNAs ...... 88
Summary ...... 88
Misregulation of 3’ end formation of ncRNAs can cause human disease ...... 89
Results ...... 92
USB1 depletion reduces the steady state levels of U6 snRNA in human cells ...... 92
USB1 depletion does not affect the levels of human telomerase RNA ...... 92
USB1 knockdown leads to an increase in adenylated U6 mature and precursor
species ...... 94
ix Reduced U6 snRNA levels upon USB1 knockdown can be rescued by a co-
knockdown of PAPD5 or EXOSC10 ...... 96
PARN deadenylates a number of stable ncRNAs in human cells ...... 98
PARN and EXOSC10 both regulate the stability of human Y RNAs ...... 100
PARN and EXOSC10 regulate the maturation of Y RNAs in a PAPD5-dependent
manner ...... 104
DIS3L is involved in the degradation of Y RNAs ...... 107
Discussion ...... 110
USB1 deficiency leads to U6 destabilization and degradation by PAPD5/EXOSC10
...... 110
PARN’s possible role in regulating the stability of multiple ncRNAs ...... 111
Y RNAs are processed by PARN and EXOSC10 in human cells ...... 114
Y RNA deficiency could lead to the severe phenotype of DC observed in patients
with PARN mutations ...... 116
Experimental methods ...... 118
Cell culture ...... 118
RNA interference in HeLa cells ...... 118
Northern analysis of RNAs ...... 118
3’ end deep sequencing of RNAs ...... 119
Bibliography ...... 120
x List of Tables
Table 1.1 List of possible ncRNP hypo-assembly diseases...... 19
Table 1.2 List of possible mRNP hypo-assembly diseases...... 22
xi List of Figures
Figure 1.1 Mechanism of RNP hypo-assembly ...... 2
Figure 1.2 Eukaryotes mRNAs can be degraded in a 5’ to 3’ or 3’ to 5’ manner ...... 6
Figure 1.3 Diversity of ncRNA quality control pathways in eukaryotes ...... 10
Figure 1.4 Competition between hTR RNP assembly and quality control ... 12
Figure 1.5 snRNP biogenesis competes with programmed RNA quality control pathways ...... 16
Figure 2.1 Yeast U1 Sm-mut RNAs are unstable and rapidly degraded by quality control mechanisms ...... 29
Figure 2.2 Mutant U1 snRNA levels vary in various deletion strains specific to quality control in the nucleus and the cytoplasm ...... 31
Figure 2.3 Wild-type U1 steady state levels are unaffected in various yeast deletion strains ...... 32
Figure 2.4 Two independent yeast snRNA quality control mechanisms ..... 34
Figure 2.5 Precursor WT-U1 is stabilized in xrn1∆rrp6∆ strain ...... 35
Figure 2.6 Mammalian snRNAs with defects in Sm site are degraded by XRN1 ...... 40
Figure 2.7 NUDT16 modestly affects U1 Sm-mutant levels ...... 41
Figure 2.8 Reduced snRNA levels in SMN-limiting conditions are increased by XRN1 knockdown ...... 44
Figure 2.9 DCP2 KD leads to rescue of splicing defects observed upon SMN depletion ...... 46
Figure 2.10 Additional examples of pre-mRNA splicing defects rescued by DCP2 knockdown ...... 47
Figure 3.1 Lack of dyskerin binding reduces hTR levels by two different RNA decay mechanisms ...... 60
Figure 3.2 Quality-control pathways for A377G and C408G mutant hTR are conserved in U2OS cells ...... 63
xii Figure 3.3 PARN knockdown reduces hTR levels due to competing activity of EXOSC10 ...... 65
Figure 3.4 hTR 3’ mature end exhibits longer A tails after PARN knockdown ...... 67
Figure 3.5 Rescue of telomerase activity in dyskerin- or PARN-depleted HeLa cells by co-knockdown of competing nucleases ...... 70
Figure 3.6 Mislocalization of hTR in dyskerin or PARN knockdown HeLa cells can be corrected by knockdown of competing nuclease ...... 73
Figure 3.7 Mutant hTR localization to Cajal bodies can be rescued by knockdown of RNA decay pathways ...... 74
Figure 3.8 Mutant hTR localizes to cyTER bodies in U2OS cells ...... 75
Figure 3.9 FISH signal for WT and mutant hTR is specific and does not localize to P bodies or U bodies...... 77
Figure 3.10 Model for hTR biogenesis in mammalian cells ...... 80
Figure 4.1 USB1 knockdown leads to a decrease in U6 levels and affects 3’ end maturation...... 93
Figure 4.2 U6 snRNA levels can be rescued by a co-knockdown of PAPD5 or EXOSC10 in HeLa cells ...... 97
Figure 4.3 PARN depletion increases the proportion of oligoadenylated reads for U6 and RMRP in HeLa cells ...... 99
Figure 4.4 PARN or EXOSC10 knockdown reduces Y RNA levels in HeLa cells ...... 103
Figure 4.5 PARN and EXOSC10 process Y RNAs to a truncated 3’ end in PAPD5 dependent manner ...... 106
Figure 4.6 DIS3 and DIS3L exert contrasting effect on Y RNA levels in HeLa cells...... 109
Figure 4.7 Two modes of PARN-mediated 3’ end maturation of ncRNAs. . 113
xiii Chapter 1: Hypo-assembly diseases of RNA-protein complexes1
RNA quality control pathways compete with RNP assembly
Introduction
The proper interaction between RNA molecules and their protein partners is a ubiquitous event in the life cycle of every RNA. These interactions lead to the formation of ribonucleoprotein (RNP) particles that allow RNA function and control (G. Singh et al.,
2015).
The assembly of specific RNPs is generally in kinetic competition with RNA degradation (Figure 1.1). This competition both ensures that only fully assembled RNPs are produced, and it serves as a 'quality control' checkpoint for the fidelity of the RNP being formed. Given these competing RNA decay pathways, defects in RNP assembly can lead to degradation of key RNAs, and pathologies due to RNP loss in "RNP hypo- assembly diseases". Examples of these diseases include Spinal Muscular Atrophy
(SMA) and Dyskeratosis Congenita (DC) for non-coding RNAs, and Constant Spring � thalassemia for mRNAs.
1 Parts of this chapter have been modified from the publication: Shukla, S. & Parker, R., 2016. Hypo- and hyper-assembly diseases of RNA-protein complexes. Trends in Molecular Medicine, 22(7), pp.615-628.
1
Figure 1.1 Mechanism of RNP hypo-assembly. RNP hypo-assembly diseases are caused by RNA quality control pathways out-competing defective RNP assembly in the cell. Under normal physiological conditions, cellular RNAs interact with RNA binding proteins to form RNPs. In hypo-assembly diseases, RNP formation is reduced, leading to RNA degradation by competing RNA quality control mechanisms.
2 Individual RNPs also assemble into a variety of higher order structures, generally referred to as RNP granules (Müller-McNicoll and Neugebauer, 2013). For example, snRNPs, snoRNPs and telomerase RNPs traffic through a large RNP assembly in the nucleus referred to as the Cajal body. Similarly, non-translating mRNPs in the cytosol can assemble into P-bodies, which contain a number of proteins involved in mRNA degradation, or stress granules, which contain a diverse proteome, including RNA binding proteins and some translation factors. The formation of such mega-mRNPs is facilitated by protein-protein interactions of RNA binding proteins allowing multivalent interactions between individual RNPs, leading to the assembly of these structures
(Mitrea and Kriwacki, 2016). Hyper-assembly of such large RNP granules, either due to hyper-assembly of specific RNA binding proteins or to the expansion of nucleotide repeats in RNAs, can trigger several different pathologies, which we collectively refer to as "RNP hyper-assembly diseases". Examples of these diseases include Amyotrophic
Lateral Sclerosis (mutations in TDP-43 and FUS, or C9orf72 expansions of G4C2 repeats) (Renton et al., 2014), Multisystem proteinopathy (mutations in hnRNPA1 and hnRNPA2B1) (H. J. Kim et al., 2013), and CUG or CCUG expansions in Myotonic
Dystrophy Type 1 & 2 (Meola and Cardani, 2015).
Despite recent discoveries of causative mutations associated with RNP hypo- assembly diseases, there is a lack of clear understanding of disease etiology. Further, there are no treatments available for these diseases, which points to the urgency of finding druggable targets in these pathologies.
3 Diversity of RNA quality control pathways in eukaryotes
RNA quality control in eukaryotes is accomplished by diverse RNA decay machineries composed of ribonucleases and their protein partners. These proteins can enhance the ability of the ribonucleases to gain access to their substrates, as well as enhance the ability of the ribonucleases to degrade their substrate.
RNA decay mechanisms exhibit a remarkable amount of conservation between the baker’s yeast, Saccharomyces Cerevisiae, and higher eukaryotes like humans.
Therefore, most of our understanding of RNA quality control pathways stems from seminal work done using yeast as a model organism. An RNA molecule is vulnerable to degradation through three general modes: 5’ to 3’ decay, endonucleolytic cleavage and decay, and 3’ to 5’ decay. However, different RNA molecules are susceptible to different
RNA decay mechanisms because of differences in their features. For example, RNA pol
II transcribed RNAs, like mRNAs, snRNAs and human telomerase RNA, receive a m7Gpp cap structure at their 5’ ends, whereas RNA pol I transcribed rRNAs and RNA pol III transcribed tRNAs and other non-coding RNAs (ncRNAs) have a mono- or triphosphate group at their 5’ ends. The m7G cap structure on snRNAs and human telomerase RNA is modified to a trimethylated m2,2,7G structure during maturation.
Similarly, the 3’ end of RNAs can have long polyadenylated, or poly(A), tails, as is the case for mRNAs. On the other hand, most cellular RNAs, including a large majority of non-coding RNAs, lack a poly(A) tail. Different RNA decay mechanisms target some or all of these features to initiate RNA decay, and therefore have led to the evolution of diverse RNA quality control pathways in eukaryotes.
4 The RNA decay pathways that regulate mRNA levels and stability are the most well understood. Normally, mRNA decay is initiated through deadenylation, or shortening of the 3’ tail, and is predominantly carried out by the CCR4-CAF1-NOT complex in the cytoplasm (J. Chen et al., 2002; Daugeron et al., 2001; Tucker et al.,
2002; 2001) (Figure 1.2). Following deadenylation, mRNAs can be degraded in the cytoplasm either in a 5’ to 3’ manner, or in a 3’ to 5’ manner (Figure 1.2). The 5’ to 3’ degradation of mRNAs involved decapping, or removal of the m7Gpp cap, by the decapping enzyme DCP2 or NUDT16, followed by digestion of the mRNA by the exonuclease XRN1 (Beelman et al., 1996; Dunckley and Parker, 1999; Kenna et al.,
1993; Song et al., 2010; van Dijk et al., 2002; Z. Wang et al., 2002). The 3’ to 5’ degradation of mRNAs involves recruitment of the large exosome complex to the mRNA, in which DIS3 is the catalytic subunit and digests mRNAs in a 3’ to 5’ manner
(Lykke-Andersen et al., 2011; Schmid and Jensen, 2008; Wasmuth and C. D. Lima,
2012). The cap structure is then hydrolyzed and recycled by the decapping scavenger enzyme DCPS, completing the digestion of the mRNA (H. Liu et al., 2002; S.-W. Liu et al., 2004). While these enzymes define the minimum requirements for individual steps in mRNA degradation, a large number of proteins support these enzymes in carrying out their activity, and have been discussed in detail elsewhere (Doma and Parker, 2007;
Houseley and Tollervey, 2009; Parker, 2012).
5
Figure 1.2 Eukaryotes mRNAs can be degraded in a 5’ to 3’ or 3’ to 5’ manner. Deadenylation is generally the first step in the degradation of mRNAs in the cytoplasm. After deadenylation by the CCR4- CAF1 complex, mRNAs can be decapped by DCP2/NUDT16 and digested by XRN1 in the 5’ to 3’ decay pathway. Alternatively, mRNAs can be subjected to decay by the exosome in a 3’ to 5’ manner, with DCPS hydrolyzing the residual cap structure.
6 Recent investigations have begun to shed some light on RNA quality control pathways for ncRNAs. A general pathway for quality control of ncRNAs in the nucleus involves post-transcriptional oligoadenylation of the 3’ end by the TRAMP complex
(Kadaba et al., 2004; LaCava et al., 2005; Lubas et al., 2011; Vaňáčová et al., 2005;
Wyers et al., 2005). In humans, this addition of two to twenty adenosines to the 3’ end of the substrate is carried out by the non-canonical poly(A) polymerase PAPD5, which is the active component of the TRAMP complex comprising of the RNA helicase MTR4 and the Zinc finger RNA binding protein ZCCHC7 (Lubas et al., 2011; Rammelt et al.,
2011). How exactly the TRAMP complex identifies its substrate is still unclear; however, it has been shown to add oligo(A) tails to the 3’ ends of misprocessed and defective tRNAs and rRNAs in both yeast and mammals (Kadaba et al., 2004; Shcherbik et al.,
2010; Wolin et al., 2012). The oligoadenylated RNAs are then degraded by the nuclear exosome, predominantly by the 3’ to 5’ exonuclease EXOSC10 (RRP6 in yeast), which is a part of the larger exosome complex (Allmang et al., 1999b; Lubas et al., 2011)
(Figure 1.3 A).
Other examples of nuclear noncoding RNA quality control pathways involve the
5’ to 3’ exonuclease XRN2, which is a paralog of XRN1. XRN2 degrades misprocessed rRNA precursors and tRNAs, and also plays a role in degrading cryptic transcripts generated from promiscuous transcription (M. Kim et al., 2004; W. F. Lima et al., 2016;
M. Wang and Pestov, 2011; Wolin et al., 2012) (Figure 1.3 B). In yeast, this process is often aided by a nuclear decapping enzyme RAI1, which stimulates the activity of XRN2
(Fang et al., 2005). However, the role of the human ortholog of RAI1, DXO, in this
7 process is unclear. DXO by itself plays a role in the quality control of RNA pol II transcribed RNAs lacking the proper cap structure (Jiao et al., 2013). DXO can remove unmethylated caps from mRNAs, as well as degrade the resulting RNA molecule in a 5’ to 3’ manner through its intrinsic 5’ to 3’ exonucleolytic activity (Chang et al., 2012; Jiao et al., 2013) (Figure 1.3 C).
8
9 Figure 1.3 Diversity of ncRNA quality control pathways in eukaryotes. A) Non-coding RNAs can be degraded by PAPD5-mediated oligoadenylation of the 3’ end, followed by 3’ to 5’ degradation by EXOSC10 in the nucleus. B) XRN2 can degrade aberrant non-coding RNAs in the nucleus in the 5’ to 3’ direction. XRN2’s activity is stimulated by RAI1 in yeast, while the role of the human ortholog, DXO, is unclear. C) DXO recognizes and removes defective caps from RNA pol II transcribed RNAs. DXO removes the entire cap structure as well as the first nucleotide, and then degrades the RNA through its intrinsic 5’ to 3’ exonucleolytic activity.
10 Hypo-assembly diseases of RNPs
Dyskeratosis Congenita and degradation of telomerase RNA
Several mutations that cause Dyskeratosis Congenita (DC) do so by limiting assembly of the human telomerase RNP. DC is a telomere disorder belonging to a broader family of diseases characterized by shortening of telomeres and failure to renew stem cells (Armanios and Blackburn, 2012). The most common causes of DC are mutations in the RNA binding protein, dyskerin, or the human telomerase RNA (hTR), some of which disrupt the binding site for dyskerin in the 3' region of hTR (Mason and
Bessler, 2011). Mutations in dyskerin and some mutations in the 3' region of hTR lead to low levels of hTR in the cell, which is directly related to reduced telomerase activity observed in DC models (Wong and Collins, 2006).
As I discuss in chapter 3, when dyskerin binding is defective, the hTR RNA is degraded by two distinct RNA decay mechanisms. First, hTR can be degraded in the nucleus by PAPD5-mediated oligoadenylation, which then provides a 3' single stranded region that allows efficient recruitment of a 3' to 5' exonuclease, EXOSC10. EXOSC10 can in turn function either on its own, or as a subunit of the larger nuclear exosome
(Moon et al., 2015; Nguyen et al., 2015; Shukla et al., 2016; Tseng et al., 2015).
Alternatively, hTR can be degraded in the cytosol by DCP2-mediated decapping, which then exposes hTR to 5' to 3' degradation by the exonuclease XRN1 (Shukla et al.,
2016) (Figure 1.4).
11
Figure 1.4 Competition between hTR RNP assembly and quality control. Under normal conditions, hTR is bound by dyskerin and other H/ACA proteins to form the hTR RNP. In DC, unassembled hTR is degraded by EXOSC10 in the nucleus, and by DCP2/XRN1 in the cytoplasm. DCP2 removes the m7Gpp cap structure from the 5’ end of hTR, exposing the monophosphate to allow XRN1-mediated exonucleolytic digestion. Loss of PARN also leads to degradation of hTR by EXOSC10, which is aided by PAPD5-mediated oligoadenylation of hTR 3’ end, where it can destabilize both unbound and assembled hTR molecules.
12 Importantly, it has been shown that inhibition of either decapping and/or nuclear
EXOSC10-mediated degradation could rescue telomerase activity in dyskerin-depleted
HeLa cells. Inhibition of decapping and/or EXOSC10-mediated degradation also rescued localization of the telomerase RNP (presumably lacking dyskerin) to Cajal bodies in dykserin-depleted HeLa cells (Shukla et al., 2016). The rescue of activity and proper sub-cellular localization when RNA decay pathways are inhibited suggests that pharmaceutical approaches to block RNA nucleases might be a potential therapy for some alleles causing DC.
The evidence that hTR can be subjected to oligoadenylation, which triggers 3' to
5' degradation, has allowed an understanding of why loss-of-function (LoF) mutations in the Poly(A) ribonuclease (PARN) can cause DC and idiopathic pulmonary fibrosis
(Dhanraj et al., 2015; Stuart et al., 2015; Tummala et al., 2015). PARN removes the oligo(A) tails on the hTR 3' end which are added by PAPD5, thereby limiting its accessibility to EXOSC10 and/or the nuclear exosome (Figure 1.4) (Nguyen et al.,
2015; Shukla et al., 2016; Tseng et al., 2015). Further, analysis of hTR 3' ends, and sub-cellular localization and function suggests that PARN is not required for hTR maturation, since a co-knockdown of EXOSC10 and PARN rescues hTR levels and telomerase activity in PARN-deficient HeLa cells (Shukla et al., 2016). Overall, these studies propose a model where hTR levels in the cell are regulated by multiple pathways. While a tighter regulation of hTR levels might be necessary to prevent excessive telomerase activity, which could otherwise lead to uncontrolled proliferation of human cells leading to tumor formation, these pathways can also rapidly degrade RNA when hTR cannot be assembled into stable RNP molecules.
13
Spinal Muscular Atrophy and snRNA degradation
A second example of an RNP hypo-assembly disease is Spinal muscular atrophy
(SMA). SMA is an autosomal recessive disease caused by mutations in the SMN1 gene, which is the principal gene coding for the Survival Motor Neuron (SMN) protein in humans (Lefebvre et al., 1995). SMN is an assembly factor for the binding of the Sm complex to the conserved Sm site on snRNAs in humans, which is an important step in the maturation and trafficking of snRNAs in the cell (Pellizzoni et al., 1998). Humans also have a second copy of the SMN coding gene, SMN2, but a single point mutation in exon 7 leads to mis-splicing of the transcribed mRNA and production of an unstable truncated isoform of the SMN protein (Cho and Dreyfuss, 2010; Lorson et al., 1999).
SMA patients with LoF alleles in the SMN1 gene have reduced levels of SMN protein, and severity of the disease and survival are directly correlated to the number of copies of the compensatory SMN2 gene.
SMA mouse and Drosophila models and tissue culture experiments have shown that reduction in the SMN protein leads to a non-uniform decrease in the levels of snRNAs (Gabanella et al., 2007; Lotti et al., 2012; Shukla and Parker, 2014; Zhang et al., 2008). Moreover, several observations suggest that snRNAs are degraded rapidly when they are unable to assemble into snRNPs. Mutations in the Sm site of budding yeast snRNAs, which do not express a SMN ortholog but assemble the snRNAs into snRNPs, lead to reduced steady-state levels and an increase in snRNA rate of decay
(Shukla and Parker, 2014). Similarly, in human cells, knockdown of SMN or the SMN
14 complex components reduces the levels of snRNAs (Gabanella et al., 2007; Shukla and
Parker, 2014; Winkler et al., 2005).
As I discuss in chapter 2, examination of mammalian snRNAs that are defective in the Sm protein binding, either due to mutations in the Sm binding site or in models of
SMN knockdown, have revealed that these mutant snRNAs are degraded in the cytoplasm by DCP2 and XRN1 (Figure 1.5)(Shukla and Parker, 2014). These findings are consistent with the cytoplasmic assembly of snRNPs in mammalian cells, followed by cap hypermethylation and nuclear import (Fischer et al., 2011). Importantly, inhibition of snRNA decapping through siRNA-mediated DCP2 knockdown in SMN knockdown mouse cells, can rescue splicing defects observed for U12-dependent introns in some mRNAs (Lotti et al., 2012; Shukla and Parker, 2014). This is consistent with a model where if SMN is limiting, sufficient numbers of snRNAs are degraded by DCP2/XRN1 to alter splicing, and inhibition of decapping by Dcp2 knockdown can alter the kinetic competition to at least partially restore snRNP assembly.
15
Figure 1.5 snRNP biogenesis competes with programmed RNA quality control pathways. Under normal conditions, snRNAs are transcribed and exported to the cytoplasm, where the SMN protein as a part of the SMN complex promotes the binding of Sm complex to the Sm site on snRNAs. Following Sm complex binding, the 5’ cap of snRNAs is modified to m2,2,7Gpp, and snRNPs are re-imported to the nucleus for final maturation. When SMN levels are reduced, snRNAs are degraded in the cytoplasm by DCP2/XRN1 when Sm complex assembly is compromised, as observed in patients suffering from a severe form of SMA.
16 A recent study has suggested that quality control of snRNAs in the cytoplasm could also be triggered by bacterial infections such as Shigella sp., Listeria sp. and
Salmonella sp. in human cell lines, causing a decrease in the levels of snRNAs and sequestering snRNAs in cytoplasmic foci defined as U-bodies (Tsalikis et al., 2015).
Therefore, the snRNA quality control pathway in the cytoplasm seems to be a general tunable mechanism regulating snRNA availability in the cell in response to bacterial stress.
Two broader conclusions can be drawn from work on SMA and DC. First, in both diseases, specific RNA quality control pathways out-compete defective RNP assembly leading to RNA degradation, which could contribute to a pathological state when hTR
RNP assembly is decreased or when SMN levels are reduced in the cell. Second, inhibition of RNA decay pathways rescues RNA levels, and more importantly, the function of the RNP, at least in model systems. How effective these strategies will be in treating animal models or possibly humans, rather than in cultured cells, remains to be seen. This work raises the possibility that there are other RNP or mRNP hypo-assembly diseases where RNA quality control pathways are responsible for the disease pathology.
17 RNP hypo-assembly diseases include pathologies of ncRNAs
Examination of the literature suggests other examples where defects in assembly of an RNP lead to degradation of the RNA thereby leading to a pathological condition
(Table 1). For example, mutations in the RMRP gene, which encodes the RNA component of the MRP ribonuclease complex (thought to function in rRNA biogenesis)
(Chu et al., 1994; Lindahl et al., 2009; Lygerou et al., 1996), have been shown to lead to the human developmental disease Cartilage Hair Hypoplasia (CHH), which is characterized by sparse hair, skeletal abnormalities, immune deficiency and increased risk of cancer (Ridanpää et al., 2001). Interestingly, some of the RMRP mutations in the
RNA itself and not the promoter region, lead to reduced levels and stability of the MRP
RNA in cells derived from patients as well as in cell culture models, suggesting that defects in RNP assembly can lead to degradation of the MRP RNA by as yet unknown pathways (Hermanns et al., 2005; Nakashima et al., 2007). Consequently, insufficient levels of MRP affect its normal function in yeast, mouse model and patient leukocyte cells (Hermanns et al., 2005; Huang et al., 2015; Nakashima et al., 2007). Similarly, mutations in the U4atac snRNA coding gene have been shown to be the cause of the rare developmental disease Microcephalic Osteodysplastic Pulmonary Dwarfism Type 1
(MOPD 1) (Edery et al., 2011; He et al., 2011). One of the mutations adjacent to the Sm site has been shown to reduce the levels of the U4atac snRNA when expressed exogenously in a model rodent cell line, presumably due to a competing RNA decay mechanism, which could lead to defects in splicing dependent on the U12-spliceosome machinery, which the U4atac snRNP is a part of (Jafarifar et al., 2014).
18 Gene Disease association Effect on ncRNA
DKC1/TERC/PARN Dykseratosis Congenita (DC) Reduction in hTR levels
(Mitchell et al., 1999; Stuart
et al., 2015; Vulliamy et al.,
2001)
SMN1 Spinal Muscular Atrophy (SMA) Non-uniform reduction in
snRNA levels (Lefebvre et
al., 1995)
RMRP Cartilage hair Hypoplasia (CHH) Reduction in MRP RNA
levels (Nakashima et al.,
2007; Ridanpää et al., 2001)
RNU4atac Microcephalic Osteodysplastic Reduction in U4atac RNA
Primordial Dwarfism 1 (MOPD1) levels (Jafarifar et al., 2014)
Table 1.1 List of possible ncRNP hypo-assembly diseases.
19 Hypo-assembly diseases of mRNPs
mRNA destabilization due to a loss of RNP formation has similarly been implicated in human disease (Table 2). One example of this is Constant Spring � thalassemia, where a mutation in the stop codon substituting it for a Gln codon (UAA to
CAA) leads to the ribosome moving into the 3' UTR of the �-globin mRNA (Waggoner and Liebhaber, 2003). This leads to the removal of the �-globin mRNA stability complex from the 3' UTR of the mRNA, which normally stabilizes the mRNA during erythrocyte development (Weiss and Liebhaber, 1995). As a result, patients suffering from Constant
Spring a thalassemia exhibit reduced levels and stability of the a globin mRNA in red blood cells, resulting in hemoglobin deficiency and thalassemia. Similarly, a mutation in the SECIS element in the 3' UTR of SEPN1 mRNA, which codes for Selenoprotein N, leads to loss of SBP2 protein binding to the mRNA, and in the absence of this bound protein, SEPN1 mRNA is rapidly degraded, giving rise to a mild form of rigid spine muscular dystrophy (Allamand et al., 2006). Another example of disease caused by hypo-assembly of an mRNP is the retrotransposon insertion in the 3’ UTR of the FKTN mRNA, which codes for the Fukutin protein whose function is not well understood, in
Fukuyama congenital muscular dystrophy. The retrotransposon insertion leads to a strong reduction in the levels of the FKTN mRNA by an unknown mechanism
(Kobayashi et al., 1998). Similarly, a SNP in the 3’ UTR of the LRRK2 mRNA leads to a strong reduction in the levels of the LRRK2 mRNA in a specific region of the brain of patients suffering from Parkinson’s disease, and increases the risk of disease onset
(Cardo et al., 2014). One anticipates that a growing number of disease-related mutations in non-coding regions of mRNAs will lead to some form or other of disease
20 due to alterations in RNP assembly, which in some cases like Constant Spring a thalassemia, may even trigger competing RNA decay pathways. The effect of mutation(s) on mRNA or protein levels need not be large, as small reductions in the levels of a critical RNP component could be sufficient to reduce the rate of RNP formation and elevate RNA decay, also considering that RNP assembly in the cell is highly stochastic and varies for individual RNAs.
21 Gene Disease association mRNA mutation
HBA2 Constant Spring a thalassemia UAA-CAA mutation of the stop
codon (Waggoner and Liebhaber,
2003)
FKTN Fukuyama congenital muscular Retrotransposon insertion in 3’
dystrophy UTR of FKTN mRNA (Kobayashi
et al., 1998)
SEPN1 Rigid spine muscular dystrophy T-C or G-A mutation in the 3’ UTR
(Allamand et al., 2006;
Moghadaszadeh et al., 2001)
LRRK2 Parkinson’s disease SNP in 3’ UTR (Cardo et al.,
2014)
Table 1.2 List of possible mRNP hypo-assembly diseases.
22 Discovery of possible treatments for RNP hypo-assembly diseases
One possible way to treat RNP hypo-assembly diseases will be to inhibit the competing RNA decay pathways. Although many RNA decay enzymes are important for organismal viability, two reasons suggest this might be a viable option. First, RNA decay pathways are often redundant, and inhibiting one pathway may not impact general viability (Houseley and Tollervey, 2009). For example, hypomorphic mice where DCP2 protein levels have been reduced to ~10% of wild-type levels are still viable (Song et al.,
2010). This viability could be due to redundancy in decapping enzymes, since mammalian cells express multiple other enzymes with decapping activity, including the enzyme NUDT16 (Jiao et al., 2013; Li et al., 2011; Song et al., 2013a). Second, for many nucleases, there are specific co-factors for various substrates; thus targeting a key co-factor for a general nuclease may result in a more specific mode of RNA decay inhibition. Interestingly, the general splicing inhibitor, Isoginkgetin, has shown a similar effect as the knockdown of the exosome on hTR processing, leading to longer oligo(A) tails and more oligoadenylated hTR precursor species in HeLa cells, suggesting that it might also potentially block exosome-mediated degradation (Tseng et al., 2015).
Importantly, although warranting further investigation, the identification of compounds capable of targeting specific RNA decay mechanisms may provide useful therapeutic leads to treat some of these diseases.
One promising drug candidate for the treatment of DC and other related telomere pathologies is the synthetic androgenic sex hormone Danazol. In a large phase 1 clinical trial comprising of patients suffering from telomere disease arising from mutations in TERT, TERC (hTR) and DKC1, Danazol treatment led to an increase in
23 telomere length as well as an increase in the amount of red blood cells and neutrophils
(Townsley et al., 2016). It will be interesting to see if Danazol (or a derivative) could be improved further to advance to a phase 2 or 3 clinical trial, eventually leading to FDA approval for the treatment of telomere diseases.
Conclusion
Based on current evidence of misregulated RNP assembly in several human diseases, including SMA and DC, it will be important to understand not only the molecular mechanisms behind disease onset, but also the changes in the cellular function that occur during disease progression. This will facilitate the characterization of the most optimal therapeutic approaches targeting RNP assembly, as well as the temporal windows in which they might be used to treat some of the pathologies discussed here. An important step in this process will undoubtedly be the identification of appropriate model systems that best recapitulate/mimic the appearance and progression of given diseases in patients. Complementary in vitro, in vivo, and ex vivo
(e.g. patient cells) model systems constitute important components allowing a proper validation of experimental hypotheses regarding aberrant RNP assembly and disease.
As such, placing the most recent data on RNP assembly in this context will be most helpful in explaining the often conflicting results obtained from different studies on one given pathology, as in the case of SMA. Future research should also focus on translating small molecule treatments discovered in cell lines to clinical trials as quickly as possible, since there are little to no treatment options currently available for most of these devastating diseases.
24 Chapter 2: Quality control of snRNAs in Spinal Muscular Atrophy2
Summary
The accurate biogenesis of RNA-protein complexes is a key aspect of eukaryotic cells. Defects in Sm complex binding to snRNAs are known to reduce levels of snRNAs suggesting an unknown quality control system for snRNP assembly. snRNA quality control may also be relevant in Spinal Muscular Atrophy, which is caused by defects in the SMN1 gene, an assembly factor for loading the Sm complex on snRNAs, and when severely reduced, can lead to reduced levels of snRNAs and splicing defects. To determine how assembly defective snRNAs are degraded, we first demonstrate that yeast U1 Sm-mutant snRNAs are degraded either by Rrp6, or by Dcp2 dependent decapping/5’ to 3’ decay. Knockdown of the decapping enzyme DCP2 in mammalian cells also increases snRNA levels and suppresses some splicing defects seen in SMN- deficient cells. These results identify a conserved mechanism of snRNA quality control, and also suggest a general paradigm wherein the phenotype of a RNP hypo-assembly disease might be suppressed by inhibition of competing RNA quality control mechanism.
2 This chapter has been modified from the the publication: Shukla, S. & Parker, R., 2014. Quality control of assembly-defective U1 snRNAs by decapping and 5’-to’3’ exonucleolytic digestion. Proceeding of the National Academy of Sciences USA, 111(32), pp.E3277-3286.
25 SMA is a neurodegenerative disease caused by snRNP deficiency
Eukaryotic cells contain a growing diversity of functional noncoding RNA-protein complexes (RNPs). The biogenesis of a stable functional RNP requires multiple RNA processing reactions and assembly with specific RNA binding proteins. To prevent the formation of aberrant RNPs and to increase the specificity of RNP assembly, eukaryotic cells also contain a number of RNA quality control systems that recognize and degrade aberrant RNAs (Doma and Parker, 2007; Houseley and Tollervey, 2009). The full spectrum of RNA quality control mechanisms and their biological impacts remain to be determined.
snRNAs may be subject to quality control mechanisms since mutations in the binding site for the Sm protein complex reduce steady state snRNA levels, although whether this is directly due to specific RNA decay mechanisms has not been explored
(Jones and Guthrie, 1990; Seto et al., 1999). snRNA quality control may also be triggered by defects in assembly factors. For example, Spinal muscular atrophy (SMA) is a neurodegenerative disease caused by low levels of the Survival Motor Neuron
(SMN) protein due to mutations in the principal SMN-coding gene, SMN1 (Lefebvre et al., 1995; Lorson et al., 1999). One role of the SMN complex is to load the Sm protein complex onto the Sm site on snRNAs, which has a consensus sequence of PuAU4-
6GPu (Fischer et al., 2011; Neuenkirchen et al., 2008). Animal models of SMA, as well as in vitro analysis of SMN knockdown cell lines revealed that a severe decrease in
SMN levels leads to a non-uniform reduction in the levels of snRNAs and snRNPs, further leading to perturbations in splicing (Gabanella et al., 2007; Lotti et al., 2012; L.
Wan et al., 2005; Workman et al., 2009; Zhang et al., 2008; 2013). There are
26 contrasting views as to whether the snRNP assembly function of SMN is causative of
SMA (Burghes and Beattie, 2009). Transcriptome analysis in some SMN mutant animal models reveals few splicing defects early in the disease progression, and at least in
Drosophila, raises the possibility that toxicity could be due to SMN deficiency triggering a stress response (Bäumer et al., 2009; Garcia et al., 2013; Praveen et al., 2012). At the same time, expression of mature snRNPs can rescue motor function deficit in another
SMA model (Winkler et al., 2005), and splicing defects have been identified in genes that are important for proper development and function of motor neurons from other disease models (Lotti et al., 2012; See et al., 2014; Zhang et al., 2013). One way to address the role of snRNA degradation in SMA is to identify the mechanisms by which assembly defective snRNAs are degraded, and then examine how disruption of such snRNA decay mechanisms affect SMN mutant phenotypes.
Herein, we utilize yeast and mammalian cells to identify snRNA quality control systems that degrade snRNAs when Sm complex assembly is limiting. In yeast, snRNAs defective in Sm complex assembly are subject to quality control both by 3' to 5' decay in the nucleus and by decapping and 5' to 3' cytoplasmic decay. Strikingly, decapping and 5' to 3' degradation is conserved for mammalian snRNAs defective in
Sm complex assembly, either due to mutations in the Sm site, or due to reduced levels of the SMN complex. Moreover, splicing defects seen in SMN deficient cells can be partially suppressed by knockdown of the DCP2 decapping enzyme. These results identify specific snRNA quality control mechanisms in eukaryotic cells. This work also raises the possibility of a general paradigm wherein the effect of mutations that cause disease by limiting RNP assembly, referred to as RNP hypo-assembly diseases, might,
27 at least in some cases, be ameliorated by inhibition of the competing RNA quality control mechanism.
Results
Mutations in the yeast U1 snRNA Sm site destabilize the snRNA
To identify quality control mechanisms for snRNAs, we first analyzed the decay of yeast U1 snRNAs defective in binding the Sm complex. We expressed exogenous U1 snRNA from a galactose-regulated promoter, which allows repression of transcription with glucose to measure RNA decay rates. To specifically detect the exogenous U1 snRNA, it included the HVII-m2 mutations, which are neutral base-changes in helical loop VII (Liao et al., 1990). To mimic defects in loading of the Sm complex caused by reduced levels of the SMN protein in SMA, we created two different mutations in the yeast U1 Sm site (AUUUUUG; Figure 2.1 A). The first Sm mutant, hereafter referred to as U1-C2, has the mutated sequence AUUCCUG, while the second Sm mutant, hereafter referred to as U1-C4, has the mutated sequence AUCCCCG.
Expression of the U1-C2 and U1-C4 mutants in a wild-type background in yeast revealed that both mutations reduced the levels of U1 snRNAs to <1% of the comparable wild-type U1 snRNA (Figure 2.1 B). We also observed that the residual U1-
C2 and U1-C4 snRNAs detected were longer than the mature wild-type U1 (Figure 2.1
B). This is consistent with earlier results that mutations in the Sm site of the U1 snRNA alter its 3' processing, leading to species that are ~75nt longer than the WT 3’ end of the
U1 snRNA (Seipelt et al., 1999).
28 A WT-U1: 550 AUAAUUUUUGAU 561 U1-C2: 550 AUAAUUCCUGAU 561 U1-C4: 550 AUAAUCCCCGAU 561
B Vec WT-U1 U1-C2 U1-C4
EP Pre-U1
U1
SCR1(control)
100% 0.8% 0.7% +/-0.2% +/-0.2%
Figure 2.1 Yeast U1 Sm-mut RNAs are unstable and rapidly degraded by quality control mechanisms. A) The 3’ end sequence starting from base 550 for the 568 bases long S.cerevisiae U1 snRNA. The wild-type Sm sequence is underlined (mutations in red). B) Representative steady state northern depicting the levels of the wild-type and Sm-mut U1 snRNA in a yRP840 strain. The probe is an oligonucleotide specific for the GAL expressed exogenous U1 RNA. ‘EP’ indicates extended precursor species. Quantification of 4 independent experiments with averages and standard deviation is shown below each lane.
29 This reduction of U1-C2 and U1-C4 snRNA levels could be due to decreased transcription or increased decay. However, by blocking transcription with glucose and following snRNA levels over time, we observed that the low steady state level of the U1-
C2 and U1-C4 snRNAs is due to their rapid degradation (Figure 2.2 A). In comparison, the WT-U1 snRNA is highly stable after inhibition of transcription. These observations indicate that defects in the Sm binding site of U1 snRNAs lead to their rapid degradation.
Defective U1 snRNAs are degraded by both 3' to 5' exonuclease Rrp6 and decapping and Xrn1-mediated decay
To identify the nucleolytic pathways that degrade the U1-C2 and U1-C4 mutant snRNAs, we introduced their expression plasmids into a number of yeast strains lacking components of different nuclear and cytoplasmic RNA degradation pathways (Parker,
2012), and examined their steady state levels in log phase of growth.
An important observation was that U1-C2 and U1-C4 mutant snRNA levels were significantly higher in rrp6Δ, trf4Δ, xrn1Δ, and dcp1Δ strains as compared to wild-type
(Figure 2.2 B & C). In contrast, the U1-C2 and U1-C4 snRNA levels did not significantly increase in the rai1∆, ski7∆ and edc3∆ strains.
30 C2 A D WT-U1 C4 WT-U1 C2 C4 0 5 15 30 0 5 15 30 0 5 15 30
Vec0 5 15 30 60 0 5 15 30 60 0 5 15 30 60 p ep xrn1∆ m ep WT(yRP840) p m SCR1 (control) SCR1(control)
ep rrp6∆ p m U1-C2 B SCR1 (control)
WT dcp1Δ edc3Δ rai1Δ rrp6Δ ski2Δ ski7Δ trf4Δ xrn1Δ ep p trf4∆ m Gal-U1
SCR1 (control) SCR1(control) ep dcp1∆ p ** m
SCR1 (control)
* * **
U1-C2 Levels ep ski2∆ p m
SCR1 (control)
U1-C4U1-C4 C E U1-C2 Δ Δ 3 Δ 6Δ 2Δ 7Δ Δ c3 p6 i2 i7 f44 WT dcp1Δ edc3Δ rai1Δ rrp6Δ ski2Δ ski7Δ trf4Δ xrnxrn1Δ
Gal-U1
SCR1(control)
*** U1-C4 *
*
U1-C4 Levels *** % U1 Remaining % U1 Remaining
Figure 2.2 Mutant U1 snRNA levels vary in various deletion strains specific to quality control in the nucleus and the cytoplasm. A) Representative northern image for a time-course experiment for wt- U1 and Sm-mut RNA in a wild-type strain. ‘p’ & ‘m’ indicate precursor and mature WT-U1 species respectively. ‘ep’ indicates extended precursor species. Representative northern image depicting B) steady state U1-C2 RNA levels & C) steady state U1-C4 RNA levels in various deletion strains. Histogram
31 depicting averages and standard deviation, along with significant differences (p<0.05(*), p<0.01(**), p<0.001(***)) between the snRNA levels in various deletion strains compared to the WT strain for at least 3 independent replicates, is also depicted. P-values were calculated using one-tailed unpaired Student’s T-test. D) Representative northern images depicting the time-course experiment for WT-U1 and U1-C2 and U1-C4 snRNAs in various deletion strains. ‘p’ & ‘m’ indicate precursor and mature WT-U1 species respectively. ‘ep’ indicates extended precursor species. E) Quantification of 3 independent time course experiments in various deletions strains as labeled. The semi-logarithmic plot depicts the average RNA levels (+standard deviation) as a percentage of 0' on the y-axis.
These effects were specific to the U1-C2 and U1-C4 RNAs since the steady state
level of the wild-type U1 snRNA was not altered in any of the RNA decay mutants
(Figure 2.3). The effect of Rrp6, which is a nuclear 3' to 5' exonuclease (Schmid and
Jensen, 2008), and Trf4, which is a nuclear poly(A) polymerase that adenylates RNAs
to promote their 3' to 5' degradation (Kadaba et al., 2004; LaCava et al., 2005;
Vaňáčová et al., 2005; Wyers et al., 2005), suggest that the U1-C2 and U1-C4 snRNAs
can be degraded by a 3' to 5' nuclear decay mechanism. In addition, the effect of
dcp1∆ and xrn1∆ on the levels of the U1-C2 and U1-C4 RNAs suggests that these
mutant snRNAs can also be degraded by decapping and 5' to 3' digestion.
A Mature WT-U1 Levels Mature WT-U1
BFigure 2.3 Wild-type U1 steady state levels are unaffected in various yeast deletion strains. Quantification of WT-U1 snRNA levels in various yeast strains. Histogram depicts average (+/- standard
deviation) for three replicates.
remainaing %Precursor WT-U1 %Precursor 32 To determine if the increase in the mutant snRNA steady-state levels seen in these mutant strains was due to an effect on their rate of degradation, we measured the decay rates of the U1-C2 and U1-C4 snRNAs in trf4∆, rrp6∆, dcp1∆ and xrn1∆ strains.
We observed that the xrn1∆, rrp6∆, trf4∆ and dcp1∆ all increased the stability of both the U1-C2 and U1-C4 snRNAs (Figure 2.2 D & E). In contrast, the decay rates of the
U1-C2 and U1-C4 snRNAs are not affected by inhibition of cytoplasmic 3' to 5' degradation dependent on the Ski complex (Figure 2.2 D). We interpret the altered decay rates in the xrn1∆, dcp1∆, trf4∆ and rrp6∆ strains to indicate that the U1-C2 and
U1-C4 snRNAs can be degraded by adenylation and 3' to 5' decay in the nucleus, as well as by a second pathway consisting of decapping and 5' to 3' decay, which is most likely cytoplasmic.
In the simplest model, the 3' to 5' and decapping/5' to 3' decay pathways for the mutant U1 snRNAs would be independent and function redundantly to limit the production of aberrant snRNAs. This model predicts that strains defective in both pathways should show an additive or synergistic increase in the levels and stability of the mutant snRNAs. To test this prediction, we examined the steady state levels of the wild-type and mutant snRNAs in an xrn1∆ rrp6∆ double mutant. Strikingly, we observed that by inhibiting both decay pathways, the levels and stability of the mutant snRNAs were restored almost to wild-type U1 snRNA levels (compare mutant snRNA levels between wild-type (~1% of WT-U1) and xrn1∆ rrp6∆ strain) (Figure 2.4 A & B). These observations demonstrate that the U1-C2 and U1-C4 snRNAs are degraded by two independent and redundant decay mechanisms, and inactivation of both pathways strongly increases the levels and stability of the mutant snRNAs (Figure 2.4 C).
33 U1-C2 U1-C4 U1-C2 U1-C4 A D
xrn1Δ xrn1Δ WT rrp6Δ xrn1Δ rrp6Δ WT rrp6Δ xrn1Δ rrp6Δ WT dcp2Δ dcs1Δ WT dcp2Δ dcs1Δ (yRP2856) (yRP2856)(
Gal-U1 Gal-U1
SCR1(control) SCR1(control)
1.00 12.10 4.39 82.28 1.00 13.08 4.54 89.11 1.00 0.63 1.15 1.00 0.70 1.30 +/- 3.54 2.85 32.43 +/- 2.18 1.99 43.31 +/- 0.15 0.11 +/- 0.38 0.16
C2 B xrn1∆ rrp6∆ E WT-U1 C4 0 5 15 30 0 5 15 30 0 5 15 30 WT-U1 C2 C4 dcp2-7 rrp6∆ p ep 0 5 15 30 0 5 15 30 0 5 15 30 (1hr at 37℃) m
SCR1(control) Gal-U1 p ep m p ep dcs1∆ rrp6∆ m
SCR1 (control) SCR1(control)
U1-C2 U1-C2 C F % U1 Remaining
U1-C4 U1-C4 % U1 Remaining % U1 Remaining % U1 Remaining
Figure 2.4 Two independent yeast snRNA quality control mechanisms. A) Representative northern image depicting the steady state levels of U1-C2 and U1-C4 snRNA levels in indicated deletion strains. Quantification of 4 independent experiments with averages and standard deviation is shown below each lane. B) Representative northern image of the time-course experiment for WT-U1, U1-C2 and U1-C4 snRNAs in xrn1Δ rrp6Δ strain. ‘p’ & ‘m’ indicate precursor and mature WT-U1 species respectively. ‘ep’ indicates extended precursor species. C) Quantification of 3 independent RNA decay rate experiments in
34 xrn1Δ rrp6Δ strain as a percentage of 0’ (+/- standard deviation). D) Representative northern image depicting steady state RNA levels along with quantification of 4 independent replicates (Average +/- Standard deviation) below each lane for various decapping mutants. E) Representative northern images for the time-course experiment for WT-U1, U1-C2 and U1-C4 snRNAs in dcp2-7 rrp6Δ and dcs1Δ rrp6Δ strains respectively. ‘p’ & ‘m’ indicate precursor and mature WT-U1 species respectively. ‘ep’ indicates extended precursor species. F) Quantification of three independent time course experiments in various strains as indicated. The semi-logarithmic plot depicts RNA levels as a percentage of 0’ on the y-axis (+/- standard deviation). A
∆∆of the wild-type mature U1 snRNA is not affected by the xrn1∆ rrp6∆, the pre-
U1 snRNA is stabilized (Figure 2.5). This indicates that quality control mechanisms for snRNAs may not only play a role in degrading snRNAs defective in assembly reactions, but Levels Mature WT-U1 they can also function to maintain the proper level of snRNA relative to its snRNP protein components.
B
remainaing %Precursor WT-U1 %Precursor
Figure 2.5 Precursor WT-U1 is stabilized in xrn1∆rrp6∆ strain. Quantification of 3 independent time course experiments in each strain as indicated. The semi-logarithmic plot depicts the average remaining precursor WT-U1 RNA levels (+/- standard deviation) as a percentage of 0' on the y-axis.
35 Decapping of defective U1 snRNAs in yeast is catalyzed by the Dcp2 enzyme
In principle, the smaller effects of the dcp1∆ on the decay rate of the U1-C2 and
U1-C4 snRNAs could be due to the involvement of multiple decapping enzymes in their degradation. Specifically, work has identified the Dcs1, Rai1 and Dxo1 proteins as additional yeast decapping enzymes (Chang et al., 2012; Jiao et al., 2010; H. Liu et al.,
2002). In our initial screen of yeast mutations affecting RNA decay, we did not see any effect of the rai1∆ on the U1-C2 or U1-C4 snRNAs (Figure 2.2 B & C). To test if another decapping enzyme could be involved in U1-C2 and U1-C4 snRNA decay, we examined the steady state levels in a mutant strain lacking Dcs1, which is a cytoplasmic scavenger decapping enzyme which can remove the m7G cap, or a strain lacking Dcp2, which is the catalytic subunit of the major mRNA decapping enzyme complex that works with Dcp1. We also examined the U1-C2 and U1-C4 snRNA levels in a dxo1Δ strain, which lacks the Dxo1 enzyme believed to specifically remove unmethlyated defective mRNA caps (Chang et al., 2012).
We observed that dcs1∆ or dcp2Δ did not significantly increase the U1-C2 or U1-
C4 snRNA levels (Figure 2.4 D). We also did not see any measurable difference in the snRNA levels between WT and dxo1Δ strains, consistent with its specificity for unmethylated caps (Chang et al., 2012). Surprisingly, we observed a small, but consistent decrease in the steady state levels of these snRNAs in the dcp2∆ strain, which may be explained by a decrease in global transcription in dcp2∆ strains
(Haimovich et al., 2013). This complicating effect of dcp2∆ mutants on transcription suggested that we needed to directly measure snRNA decay rate in strains defective in
36 Dcp2’s activity in order to establish whether Dcp2 is involved in the decapping of snRNAs before their 5’ to 3’ digestion by Xrn1.
To do this experiment, we took advantage of the synergistic effect of the xrn1∆ with the rrp6∆ on U1-C2 and U1-C4 degradation, which suggested that we could also examine the effect of decapping defects on U1-C2 and U1-C4 snRNA decay by making double mutants with rrp6∆. This experiment has the advantage of testing the effect of decapping mutations when the alternative 3' to 5' degradation pathway is inhibited, and therefore any effect will have a larger consequence on snRNA decay. Thus, we created dcs1∆ rrp6∆ and dcp2-7 rrp6∆ strains and used these strains to directly measure the effects of dcp2-7 and dcs1∆ mutations on snRNA decay. The dcp2-7 is a temperature sensitive allele of Dcp2 (Dunckley and Parker, 2001), which we used because a dcp2∆ rrp6∆ strain was synthetically lethal (data not shown).
We observed that dcp2-7 rrp6∆ strain showed a slow decay rate of the defective snRNAs after a shift to restrictive temperature (Figure 2.4 E) suggesting that the
Dcp1/Dcp2 enzyme is responsible for snRNA decapping. In contrast, the dcs1∆ rrp6∆ strains behaved similar to rrp6∆ (Figure 2.4 F). We interpret these observations to indicate that the major decapping enzyme for defective snRNAs is the Dcp1/Dcp2 holoenzyme, which is consistent with the increase in mutant snRNA levels in the dcp1∆ strain.
Taken together, these results argue that yeast snRNAs defective in Sm complex assembly are degraded independently by 3' to 5' and decapping/5' to 3' decay mechanisms. Since Sm complex association with snRNAs in yeast has been proposed to occur in the nucleus (Jones and Guthrie, 1990), we suggest that Sm assembly on
37 yeast snRNAs first competes with nuclear 3' to 5' degradation by Rrp6. However, given that yeast snRNAs can enter the cytosol (Olson and Siliciano, 2003) and Dcp2/Xrn1 activity are primarily cytoplasmic (Decker and Parker, 2012), we speculate that nuclear
3' to 5' decay also competes with snRNA export to the cytosol, and that exported snRNAs are subject to subsequent decapping by Dcp1/Dcp2 and 5' to 3' degradation by
Xrn1.
Decapping and 5' to 3' degradation of defective snRNAs is conserved in mammalian cells
To determine if these snRNA quality-control pathways are conserved in humans, we first created human U1 snRNA plasmids that contain analogous C2 and C4 mutations in their Sm site. These U1 gene plasmids also have additional mutations in the stem-loop III region, which do not disrupt the function of the U1 snRNA, but allows for specific detection of the exogenous U1 RNA (Beckley et al., 2001).
We measured the levels of the U1-C2 (human) and U1-C4 (human) snRNAs in
HeLa cells after transient transfection of the respective plasmids for 24 hours. We found that the U1-C2 and U1-C4 RNA levels are approximately 15% and 10% of the WT-U1
RNA in the cell, respectively (Figure 2.6 A). We interpret the reduced levels of the U1-
C2 and U1-C4 snRNAs to indicate that these defective snRNAs are degraded more rapidly than wild-type U1 snRNA.
To determine if the role of Rrp6 and Xrn1 was conserved in human snRNA quality control, we used siRNA knockdown of these components (Figure 2.6 B) and examined the levels of the U1-C4 (human) snRNA after transient transfection. We found
38 that the knockdown of the XRN1 enzyme increased the levels of the U1-C4 snRNA, while knockdown of EXOSC10 (mammalian ortholog of Rrp6) did not have an effect on the U1-C4 snRNA levels (Figure 2.6 C & D). This suggests that the decapping and 5' to
3' decay of snRNAs is conserved in mammalian cells, while the role for Rrp6 in snRNA quality control is not. Although we cannot rule out the formal possibility that EXOSC10 is involved, the RNAi knockdown was not sufficient to reveal a phenotype. The greater importance of cytoplasmic decay mechanisms in mammalian cells could be because snRNAs are exported from the nucleus and assembled with the Sm complex in the cytosol in mammals (Fischer et al., 2011), and therefore defects in Sm assembly would be expected to primarily expose the snRNAs to cytoplasmic decay mechanisms.
39 A Mock WT-U1 U1-C2 U1-C4 C
U1 Mock XRN1 KDEXOSC10 KDMock XRN1 KDDCPS KDMock DCP2 KD
U1-C4 7SL 7SL 1.00 0.15 0.10 +/-0.05 +/- 0.03
B Western: D siRNA ** siRNA *
Mock DCPS Mock NUDT16 DCPS 41 ** NUDT16 21 * GAPDH 38 GAPDH (control) (control) U1-C4 Levels MockXRN1 Mock EXOSC10 XRN1 195 EXOSC10 110 GAPDH (control) GAPDH (control) Mock DCP2
DCP2 52
GAPDH (control)
Figure 2.6 Mammalian snRNAs with defects in Sm site are degraded by XRN1. A) Representative northern image depicting WT-U1 or Sm-mut snRNA levels in HeLa cells. Quantification of 3 independent experiments with averages and standard deviation is depicted below each lane. B) Representative western blot images for knockdowns of various targets during the U1 plasmid co-transfection experiment. GAPDH was used as a loading control. Predicted molecular weight corresponding to each band is also indicated. C) Representative northern images for the U1-C4 RNA in various knockdown conditions compared to mock knockdown. 7SL RNA was used as a loading control. D) Histogram depicting the average steady state U1-C4 RNA levels along with standard deviation in various knockdown conditions as indicated. Significant differences (p<0.05(*), p<0.01(**)) from the mock transfection group for at least three independent replicates are shown. P-values were calculated for each group using one-tailed unpaired Student’s T-test.
40 Mammalian cells contain a greater diversity of decapping enzymes than yeast (Li et al., 2011; Song et al., 2010). To determine if one or more decapping enzyme was involved in snRNA quality control, we examined siRNA knockdowns of human DCP2,
DCPS (the human ortholog of Dcs1), and NUDT16, a decapping enzyme that can work on snoRNAs and some mRNAs (H. Liu et al., 2002; Scarsdale et al., 2006), along with transient transfection of the U1-C4 snRNA in HeLa cells. We observed that knockdown of DCPS led to a 2.5-fold increase in the U1-C4 (human) RNA levels in the cell, DCP2 knockdown gave a two-fold increase, while NUDT16 had only a ~1.3 fold increase
(Figure 2.6 D & 2.7). This suggests that DCPS and DCP2 can affect snRNA quality control in humans (see discussion).
Mock XRN1 KD NUDT16 KD
U1-C4
7SL
Figure 2.7 NUDT16 modestly affects U1 Sm-mutant levels. Representative northern image for co- transfection of the U1-C4 human plasmid (300ng) and Xrn1- or Nudt16-targeting siRNA (25nM) in HeLa cells. Nudt16 KD shows an ~1.3 fold average increase in the U1-C4 snRNA levels for three replicates. 7SL RNA was used as a loading control.
41 Reduction of snRNA levels by SMN knockdown can be rescued by inhibition of decapping and XRN1-mediated decay
In spinal muscular atrophy, the levels of snRNAs are reduced due to mutations limiting the levels of the SMN protein, which is an assembly factor for the loading of Sm complex on snRNAs (Pellizzoni, 2002; Pellizzoni et al., 1999; L. Wan et al., 2005).
Since limiting Sm complex loading on the snRNA by defects in the SMN complex is analogous to limiting it by mutations in the Sm site, we predicted that the reductions in snRNA levels when SMN is defective should be rescued by inhibition of cytoplasmic decapping and 5' to 3' degradation pathway. To test this prediction, we examined the levels of various snRNAs in response to SMN knockdown, with or without knockdowns of decapping enzymes or XRN1.
Consistent with earlier results (Gabanella et al., 2007; Lotti et al., 2012; Praveen et al., 2012; Zhang et al., 2008), we observed that SMN knockdown reduced levels of the U1, U5, U11, U12, and U4atac snRNAs (Figure 2.8 A & B). We did not examine the
U2 and U4 snRNAs since they were previously shown to be the least susceptible to
SMN KD in cell culture experiments (Lotti et al., 2012; Zhang et al., 2008).
We observed that knockdown of XRN1 in addition to SMN knockdown restored the levels of these snRNAs to their native levels (Figure 2.8 C & D). In contrast, we saw no significant effect on snRNA levels in an SMN and EXOSC10 double knockdown experiment. This is consistent with our results for the U1-C4 (human) mutant snRNA and argues that inefficient Sm assembly leads to cytoplasmic 5' to 3' decay.
Examination of the various mammalian decapping enzymes suggests that knockdowns of DCP2 and/or DCPS can partially restore the levels of U1, U5, U11, U12
42 and U4atac that are reduced due to the SMN knockdown (Figure 2.8 D), suggesting these enzymes play a role in the degradation of snRNAs in mammalian cells (see discussion). These results argue that decapping and XRN1-mediated degradation compete with SMN-mediated assembly of the Sm complex on snRNAs, and when SMN levels are reduced, the degradation of snRNAs outcompetes assembly with the Sm complex.
43 B A C Mock SMN KDscr SMNS KDSSMN+XRN1SSMN+DCPS KD KD
U1 U1
U5 U5
U11 U11 D * U12 U12 * * * * ** * * * ** * * * ** * * * U4atac U4atac Relative Levels Relative Levels
7SL 5S rRNA
Figure 2.8 Reduced snRNA levels in SMN-limiting conditions are increased by XRN1 knockdown. A) Representative northern blot for snRNA levels in HeLa cells under various transfection conditions. 7SL RNA was used as a loading control B) Quantification of four independent replicates for snRNA levels in SMN KD cells compared to control transfected cells (Average + standard deviation) C) Representative northern blot showing snRNA levels in HeLa cells under various transfection conditions. Cells were transfected with 25nM of SMN siRNA on day 1, followed by transfection with the second siRNA (25nM) targeting a gene of interest on day 2. Co-knockdown of XRN1 and SMN restores snRNA levels to their native levels, while DcpS knockdown has a lesser effect. 5S rRNA was used as a loading control. D) Histogram depicting average snRNA levels with standard deviation under various transfection conditions. Significant differences were calculated using one-way ANOVA for all groups, and subsequently P-values were calculated for each group individually using one-tailed unpaired Student’s T-test. (*) above red bar: p<0.05 for SMN KD alone compared to control. (*) above other bars: p<0.05 for double knockdowns compared to SMN KD alone.
44 Knockdown of DCP2 partially suppresses some SMN knockdown dependent splicing defects
We next investigated if the rescue of snRNA levels by knockdown of the components of the cytoplasmic 5’ to 3’ decay pathway is functionally relevant in rescuing the splicing defects previously observed in SMN mutant models (Lotti et al.,
2012; Zhang et al., 2008). In order to address this question, we employed the NIH-3T3 mouse fibroblast cell line wherein splicing defects due to SMN knockdown in U12- dependent introns have been identified (Lotti et al., 2012). We first reproduced earlier results wherein SMN knockdown results in altered splicing as assessed by the accumulation of precursor at the expense of mature mRNA for the C19orf54, Vps16 and
Parp1 mRNAs (Figure 2.9 A & 2.10 A). We then examined if this defect in splicing due to SMN knockdown could be affected by additional knockdowns of DCP2 or XRN1.
An important result was that DCP2 knockdown, but not XRN1 knockdown, partially suppressed the splicing defect observed in the SMN knockdown cells, as seen by an increase in the (mature/precursor) ratio for the C19orf54 and Vps16 transcripts.
(Figure 2.9 A). We also saw a small but reproducible effect of Dcp2 knockdown on the
Parp1 mRNA splicing defect in SMN knockdown cells (Figure 2.10A). Importantly, for each mRNA, DCP2 knockdown alone in the absence of SMN knockdown does not significantly affect the ratio of mature/precursor transcript for either of the tested mRNAs, indicating that the effect of DCP2 knockdown is only seen when SMN is limiting (compare Scr and DCP2 KD lanes in figures 2.9A and 2.10A). We also observed a significant but small effect of DcpS knockdown on the splicing of the
C19orf54 mRNA in SMN knockdown cells (p=0.03) (Figure 2.10 B). This suggests that
45 the DCPS enzyme has a secondary role in snRNA quality control compared to the
DCP2 enzyme (see discussion).
A B Scr SMN KD SMN+SMN+DCP2SMN+XRN1SMN+ KD DCP2 KD KD Mock SMN KD Scr Scr SMN KDSMN+DCP2SMN+XRN1 KD KD
p U11 C19orf54 302 m E4-6 213
U12
** 5S rRNA C19orf54 Mature/Precursor ratio
262 p C Vps16 E13-14 135 m * ** * * *
** Vps16 Mature/Precursor ratio
Gapdh 240 E3-5
Figure 2.9 DCP2 KD leads to rescue of splicing defects observed upon SMN depletion. A) Upper panel depicts a representative image for the PCR amplification of the indicated region of the C19orf54 mRNA or Vps16 mRNA under different transfection conditions. ‘p’ and ‘m’ indicate mature and precursor transcript product respectively. GAPDH mRNA was used as an internal loading control. Lower panel depicts quantification of at least 4 independent replicates (Average + standard deviation) for each mRNA. Significant differences in the double knockdown from SMN KD alone were calculated using one-tailed unpaired Student’s T-test, and are indicated (p<0.01(**)). B) Representative northern images depicting U11 and U12 snRNA levels under various knockdown conditions. 5S rRNA was used as a loading control. C) Quantification of three independent replicates (Average + standard deviation) for snRNA levels in NIH-3T3 cells. Significant differences were calculated using one-way ANOVA, followed by subsequent one-tailed unpaired Student’s T-test to identify individual p-values. The SMN KD is compared to scrambled control, while the double knockdowns are individually compared to SMN KD alone.
46 A
Scr SMN KDSMN+DCP2SMN+XRN1 KDDCP2 KD KD
p 504 Parp1 m E21-23 265
Gapdh 240 E3-5
* Mature/Precursor ratio Mature/Precursor
B
** * Mature/Precursor ratio
C19orf54 E4-6 Figure 2.10 Additional examples of pre-mRNA splicing defects rescued by DCP2 knockdown. A) Representative image of the splicing assay for the Parp1 mRNA under various transfection conditions. Gapdh mRNA was used as an internal loading control. ‘p’ and ‘m’ indicate mature and precursor transcript product respectively. (*), (**) as in Figure 2.9. B) Quantification of three independent replicates for the splicing assay for the C19orf54 mRNA (Average +/- Standard deviation) under SMN and DCPS double knockdown condition. DCP2 and XRN1 co-knockdowns with SMN are shown for reference. Significant differences in the double knockdown from SMN KD alone were calculated using one-tailed unpaired Student’s T-test, and are indicated (p<0.05(*), p<0.01(**)).
47 We next investigated if the effect of DCP2 or XRN1 knockdown on splicing defects in SMN KD NIH-3T3 cells correlates with changes in the levels of U11 and U12 snRNAs under these transfection conditions. Similar to our results with HeLa cells, we observed that SMN knockdown gave a ~35% decrease in the levels of the U11 and U12 snRNAs, which could be partially restored by DCP2 or XRN1 knockdown (Figure 2.9 B
& C). We interpret these results to suggest that prevention of decapping by DCP2 knockdown leads to a slight increase in snRNA levels, and this increase is sufficient to partially rescue the splicing defects observed for the C19orf54 mRNA. We suggest that the failure of XRN1 knockdown to suppress the splicing defect, despite having a similar effect on snRNA levels, is because inhibition of XRN1 would be expected to lead to the accumulation of uncapped snRNAs, which presumably would be non-functional.
48 Discussion
Assembly-defective snRNAs are subject to quality control
We present several lines of evidence that defects in snRNP assembly causes snRNAs to be cleared from the cells by specific RNA quality control mechanisms. First, yeast U1 snRNAs with mutations in the Sm binding site show reduced steady state levels and faster RNA decay rates (Figure 2.1). Second, similar mutations in the Sm site of the human U1 snRNA reduce its steady state level (Figure 2.6). Third, knockdown of the Sm complex assembly factor SMN led to reduced snRNA levels in human cells
(Figure 2.8 & 2.9), which is consistent with earlier work (Gabanella et al., 2007; Lotti et al., 2012; L. Wan et al., 2005; Workman et al., 2009; Zhang et al., 2008). Finally, mutations in specific RNA nucleases increase the stability and/or steady state levels of the defective snRNAs. These observations demonstrate that assembly defective snRNAs are subject to accelerated RNA degradation.
Defects in snRNP assembly in mammals leads to decapping and 5' to 3' decay
Several lines of evidence indicate that mammalian snRNAs with defects in snRNP assembly are unstable and are subject to accelerated decapping followed by decay in 5’ to 3’ direction by XRN1. First, the reduction in human U1 snRNA levels due to mutations in the Sm site can be at least partially restored by knockdown of decapping enzymes or Xrn1 (Figure 2.6). Second, the reduction in snRNA levels seen when SMN is limiting can also at least partially be restored by knockdown of XRN1 or decapping enzymes (Figure 2.8 & 2.9). A role for decapping in mammalian snRNA decay is consistent with truncated U1 snRNAs accumulating in P-bodies (Ishikawa et al., 2014), where the decapping machinery is concentrated (Sheth and Parker, 2003). In contrast,
49 despite efficient knockdowns of EXOSC10, we did not observe any effect on the levels of human mutant U1 snRNAs (Figure 2.6), which argues that EXOSC10-mediated decay of mammalian snRNAs in response to defects in Sm loading is minimal. A predominant role for cytoplasmic decapping and 5' to 3' decay for mammalian snRNP quality control is appropriate since loading of the Sm complex on snRNAs is cytoplasmic followed by re-import of the snRNP to the nucleus (Fischer et al., 2011).
Our results suggest that multiple decapping enzymes can affect mammalian snRNA quality control. First, knockdown of DCPS and DCP2 increased the levels of the
U1 Sm-mut RNA (Figure 2.6). Second, snRNA levels in SMN knockdown cells can be restored to some extent by DCPS or DCP2 knockdowns (Figure 2.8 & 2.9 C). The effect of multiple decapping enzymes on snRNAs could be explained by direct effects of redundant decapping enzymes in mammals (Song et al., 2013b). Alternatively, the effects of some decapping enzymes could be indirect, in that knockdown of one decapping enzyme could titrate the other enzyme away from its normal RNA target, leading to stabilization of those transcripts that would otherwise be decapped specifically by these enzymes. Finally, it is possible that DCP2 is the primary enzyme for decapping of snRNA substrates in mammals, while the main role of DCPS, and hence its effect on snRNA levels, is through its ability to directly stimulate XRN1’s activity (Meziane et al., 2015). This latter possibility is supported by the observations that DCPS can affect XRN1-mediated miRNA decay through its interaction with XRN1 and independent of its decapping activity (Bossé et al., 2013; Sinturel et al., 2012).
Consistent with DCPS affecting snRNAs through XRN1 stimulation, DCPS and XRN1 knockdowns both give increased snRNAs levels with none or limited effects on the
50 splicing defects in the SMN knockdown, which is in contrast to DCP2 knockdown, which both increases snRNA levels and partially rescues some splicing defects.
Prevention of snRNA decapping may lead to rescue of snRNP function
There is ample evidence in literature to suggest that the minor spliceosome is affected under conditions of low SMN (Lotti et al., 2012; Zhang et al., 2013; 2008).
Consistent with previous results, we observe that SMN KD leads to reduced levels of the U1, U5, U11, U12 and U4atac snRNAs (Figure 2.8 A). A reduction in the U11, U12 and U4atac snRNA levels also leads to splicing defects in transcripts that contain introns spliced via the U12-dependent splicing (Figure 2.9 A & 2.10 A). Further, knockdown of the decapping enzyme DCP2, but not the 5’ to 3’ exonuclease XRN1, leads to partial rescue of the splicing defects observed upon SMN KD (Figure 2.9 A &
2.10 A). The competition between snRNP assembly and degradation suggests that limiting snRNA degradation pathways might be a possible therapeutic route to restoring the reduced snRNA levels seen in SMA models. Further altering this competition could be functionally relevant in rescuing the function of snRNPs in splicing.
These results indicate that while XRN1 KD could stabilize snRNA levels (Figure
2.9 C), some (or all) of these snRNAs might be missing the 5’ cap structure, which leads to a non-functional pool of snRNAs unable to participate in splicing. On the other hand, knockdown of DCP2 protects the cap structure of some snRNAs, making them inaccessible to XRN1-dependent digestion and able to participate in splicing. The cap structure is especially important because after Sm complex assembly, the m7G cap on the snRNA is modified to the m2,2,7G trimethylated structure, which serves as a nuclear localization signal for further snRNP maturation and participation in splicing (Fischer et
51 al., 2011; Mattaj, 1986). Therefore, prevention of snRNA decapping could be a relevant strategy to ameliorate snRNA reductions due to SMN defects, although it is still unresolved if snRNA level reductions underlie the pathology of SMA.
Interestingly, one of the current drug candidates in clinical trial for SMA is a quinazoline derivative that inhibits DCPS and resembles a general m7G cap structure
(J. Singh et al., 2008). While it was earlier believed that the DCPS inhibitor increases the levels of the SMN2 transcript in the cell (J. Singh et al., 2008), in at least one mouse model, treatment with the inhibitor has no effect on SMN protein levels in the organism
(Van Meerbeke et al., 2013). We suggest that this drug’s efficacy in SMA mouse models may be due to its repression of the competing snRNA degradation pathway, thereby giving more time for snRNP assembly with limited SMN.
RNP biogenesis generally competes with quality control
These results highlight a general principle wherein competition between RNP assembly pathways and degradation mechanisms has two consequences. First, such degradation systems function as a quality control mechanism to reduce the levels of defective RNAs. Moreover, such degradation systems serve to amplify minor kinetic defects in RNP assembly, for example the reduction in snRNA levels under low levels of
SMN, and potentially create a pathogenic condition. Thus for mutations whose consequence is on RNP assembly per se, and not RNP function, we suggest that such
RNP assembly mutations would be suppressed and pathogenesis avoided in the absence of competing RNA degradation systems. Note that such mutations could be either in RNAs, RNP components, or assembly machines.
52 Experimental methods
Construction of U1 Sm-mutants in yeast and mammals
Yeast Gal-U1 plasmid was a kind gift from Dr. Michael Rosbash at Brandeis
University. Human U1 plasmid was a kind gift from Dr. Sam Gunderson at Rutgers
University. The mutations were created by QuikChange II mutagenesis kit (Agilent
Technologies, Santa Clara, CA) using primers specific to the mutated U1 gene, and the mutated plasmid was verified by Sanger sequencing.
Yeast strains and plasmids
The following yeast strains were used for this study: WT-yRP840 or yRP2856, edc3Δ-yRP1745, dcp1Δ-yRP1200, xrn1Δ-yRP1199, rrp6Δ-yRP1377, rai1Δ-yRP2921, ski2Δ-yRP1192, ski7Δ-yRP1533, trf4Δ-yRP2922, xrn1Δ rrp6Δ-yRP2923, dcp2-7 rrp6Δ- yRP2924, dcp2Δ-yRP2859, dcs1Δ-yRP2876, dcs1Δ rrp6Δ-yRP2929.
Northern blotting from yeast cultures and quantification
The cultures were grown in 2% Gal 1% Suc medium to OD~0.5 and pelleted for steady state experiments. For decay rate measurements, the culture was grown to
OD~0.5 in 2% Gal 1% Suc medium, pelleted, and re-suspended in 2% Dex medium.
Time points were taken from the culture at desired duration. RNA extraction was carried out using Phenol:Chloroform extraction protocol. The RNA was separated on a 6%
Polyacrylamide denaturing gel at 300V for 9 hours, transferred to a Nytran membrane
(GE Healthcare Biosciences, Pittsburgh, PA), and probed with a radioactive oligo complementary to the Hel VII mutation on the RNA (oRP1710:5’-
GGCACCGGAAACAAAGGGC-3’). The blot was then exposed to a phosphoimager
53 screen, and the signal was visualized on a Typhoon 9410 phosphoimager (GE
Healthcare). The bands were quantified using ImageQuant 5.2 software.
All quantification includes average +/- standard deviation for the indicated number of replicates. Significant differences were calculated using one-tailed unpaired
Student’s t-test, with P-values less than 0.05 denoted by an asterisk.
Mammalian cell culture
HeLa and NIH-3T3 cell lines purchased from ATCC were used for mammalian cell culture experiments. The cells were grown in appropriate volume of 10% FBS in
DMEM media, supplemented with non-essential amino acids (Life technologies, Grand
Island, NY), L-glutamax, 1% Penicillin/Streptomycin and Sodium Pyruvate. All cultures were grown in a 37°C incubator, 5% CO2 under normal humidity.
Plasmid transfection in mammalian cells
12x104 cells were plated on a six well plate in 10% FBS DMEM media lacking antibiotic. 300ng of appropriate plasmid was transfected per well using Dharmafect I
(Thermo Scientific, Pittsburgh, PA), as per manufacturer’s specifications. Cells were grown in Opti-Mem I reduced serum medium (Life technologies) for 6 hours, and then shifted to complete growth medium. Analysis was carried out 24 hours post-transfection.
For knockdown experiments, the cells were co-transfected with 300ng of the U1-C4 plasmid along with 25nM of siRNA of choice, and analysis was performed after 24 hours.
RNA interference in mammalian cultures
For HeLa cells, 12x104 cells were plated in a 6-well plate in 10% FBS DMEM media without antibiotic. For NIH-3T3 fibroblasts, 20x104 cells were plated in a 6-well
54 plate in 10% FBS media without antibiotic. Transfection was carried out using
Dharmafect I (Thermo Scientific) and Opti-Mem I reduced serum medium (Life
Technologies), as per manufacturer’s specifications. siRNAs targeting genes of interest were purchased (Qiagen, Germantown, MD) and 25nM of siRNA was used per well per knockdown. Cells were grown in Opti-Mem I, and then shifted to normal growth media after 24 hours. For double knockdowns, selected wells were transfected with the second siRNA (25nM) 24 hours after transfection with the SMN siRNA (25nM for HeLa cells,
30nM for 3T3 cells), while the other wells were mock transfected. Knockdown was allowed to go on for 3 days total before analysis was performed.
Western blotting from mammalian cells
Post-transfection, the cells were washed with 1x DPBS (Life Technologies) twice, and harvested using PLB buffer. Approx. 10μg of total protein was separated on 4-12%
Bis-Tris pre-cast gels purchased from Life technologies. The protein was transferred to a Protran membrane (Thermo Scientific), and blotted with appropriate antibodies in 5% milk powder solution in 1xTBST. The antibodies used were as follows: Mouse anti-SMN
(BD Biosciences), Rabbit anti-DCP2 (Bethyl), Rabbit anti-XRN1 (Bethyl), Rabbit anti-
EXOSC10 (Pierce), Rabbit anti-DCPS (Pierce), Rabbit anti-GAPDH (Cell signaling),
Rabbit anti-NUDT16 (Proteintech), Rabbit anti-α tubulin (Cell signaling). The signal was visualized using Super Signal west Dura extended duration substrate (Pierce).
Northern blotting from mammalian cells and quantification
Post-transfection, the cells were washed twice with 1x DPBS, and harvested using Trizol (Life Technologies). RNA was extracted using Trizol extraction protocol as per manufacturer’s specifications, and separated on a 6% Polyacrylamide denaturing
55 gel at 300V for 4.5 hours. The RNA was transferred to a nylon membrane, and probed with radioactive oligonucleotides specific to the transfected U1 plasmid (oRP1711:
CCAAGCTTTGGGGAAATCGC), or to endogenous snRNAs. The signal was visualized on a Typhoon 9410 imager.
All quantification includes average +/- standard deviation for the indicated number of replicates. Significant differences were calculated using One-way ANOVA analysis for comparison of all groups, and subsequently one-tailed unpaired Student’s t- test to calculate the significant differences (p<0.05(*)).
RT-PCR and splicing assay from NIH-3T3 cells
RNA was extracted as described above, and treated with Turbo DNAse
(Invitrogen) to remove contamination. 1μg of total RNA was used for cDNA synthesis using RNA-to-cDNA ecodry premix kit (Clontech). 2.5% of product was used for semi- quantitative PCR amplification using primers described previously (Lotti et al., 2012).
The PCR product was then resolved on a 1.5% agarose gel, and visualized using Gel
Red staining on Fluorchem HD2 (ProteinSimple).
The mature/precursor transcript ratio was calculated by quantifying the intensity of the respective bands using ImageJ software. Averages and standard deviation are shown for the indicated number of replicates.
56 Chapter 3: Quality control of human telomerase RNA in Dyskeratosis
Congenita3
Summary
Telomere elongation by telomerase is required for continuous proliferation of human stem cells (Blackburn and Collins, 2011). Insufficient telomerase levels are responsible for the inherited disorder dyskeratosis congenita and contribute to more common diseases such as aplastic anemia and idiopathic pulmonary fibrosis (Armanios and Blackburn, 2012). Telomerase is a ribonucleoprotein (RNP) enzyme, and disease- causing mutations have been identified in its RNA component (hTR), its catalytic protein subunit (hTERT), and the small nucleolar ribonucleoprotein dyskerin, which stabilizes hTR in the nucleus even in the absence of hTERT (Heiss et al., 1998; Mitchell et al.,
1999; Vulliamy et al., 2001; Vulliamy and Dokal, 2008). Dyskerin is a pseudouridine synthase and an RNA binding protein, which also associates with the H/ACA box small nucleolar RNAs (snoRNAs) in eukaryotes, and is important for the snoRNA-directed pseudouridylation of target RNAs in the nucleus (Kiss et al., 2010). However, an RNA target of hTR-directed pseudouridylation has yet to be discovered, and it is thought that dyskerin binding to hTR stabilizes it in the nucleus (MacNeil et al., 2016).
More recently, mutations in the poly(A) ribonuclease (PARN) have been identified in patients suffering from a severe form of dyskeratosis congenita, as well as idiopathic pulmonary fibrosis (Dhanraj et al., 2015; Stuart et al., 2015; Tummala et al.,
3 This chapter has been modified from the publication: Shukla, S., Schmidt, J.C., Goldfarb, K.C., Cech, T.R. & Parker, R., 2016. Inhibition of telomerase RNA decay rescues telomerase deficiency caused by dsykerin or PARN defects. Nature Structural and Molecular Biology, 23(4), pp.286-292.
57 2015). PARN is a 3’ to 5’ exonuclease that deadenylates its substrates, which usually leads to the degradation of the RNA (C.-Y. A. Chen and Shyu, 2010; Katoh et al., 2015).
An unaddressed issue is how hTR is degraded and the interplay between those RNA degradation systems and mutations in PARN and dyskerin. Our goal was to investigate the quality control pathways of hTR when dyskerin or PARN is depleted from cells, and whether inhibition of RNA quality control pathways can rescue hTR levels and function under these conditions.
We demonstrate that defects in dyskerin binding lead to hTR degradation by
PAPD5-mediated oligoadenylation promoting 3’ to 5’ degradation by EXOSC10, as well as decapping and 5’ to 3’ decay by the cytoplasmic DCP2 and XRN1 enzymes. PARN increases hTR levels by deadenylating hTR, thereby limiting its degradation by
EXOSC10. Telomerase activity and proper hTR localization in dyskerin- or PARN- deficient cells can be rescued by knockdown of DCP2 and/or EXOSC10. Prevention of hTR RNA decay also leads to a rescue of localization of DC-associated hTR mutants.
These results suggest that inhibition of RNA decay pathways might be a useful therapy for some telomere pathologies.
58 Results
Loss of dyskerin binding leads to hTR degradation
To determine how hTR is degraded when dyskerin levels are reduced, we examined how knockdowns of RNA decay enzymes affected endogenous hTR levels when dyskerin was depleted in HeLa cells. We observed that knockdown of dyskerin reduced hTR to 17% of wild-type levels (Figure 3.1 A), but could be partially rescued by knockdown of DCP2 (~2.5X, from 17% to 41% of control) or of XRN1 (~1.6X, from
~17% to 28% of control) (Figure 3.1 B). DCP2 and XRN1 are components of a cytoplasmic decapping and 5’ to 3’ decay pathway. We also observed that hTR levels upon DKC1 knockdown can be rescued by knockdown of the nuclear 3’ to 5’ exonuclease EXOSC10 (~2.6X from 17% to 45% of control) (Figure 3.1 B & C).
Moreover, double knockdown of EXOSC10 and DCP2 or XRN1 restored hTR levels in the dyskerin-depleted cells to ~70% of the wild-type levels.
59 DKC1+ A D DKC1+ DKC1+ DCP2+ Scr DKC1 KD DCP2 KD EXOSC10 KD EXOSC10 KD
Scr DKC1 KD Time (hr) 0 4 7 0 4 7 0 4 7 0 4 7 0 4 7 siRNA Scr DKC1 (0.5DKC1 nM) (1nM) hTR hTR Anti-DKC1 7SL Anti-GAPDH 7SL 1.0 0.17 +/- 0.03
E 100
DKC1 KD + B C 75 D + EXOSC10 KD XRN1 KD 1 K Scr DKC DKC1 50 Scr DCP2 KDXRN1 KDEXOSC10EXOSC10 + DCP2 KD+ hTR hTR 25
7SL levels (%) Relative RNA 7SL 1.0 0.17 0.45 1.0 0.17 0.41 0.28 0.71 0.68 +/- 0.03 0.03 0 +/- 0.03 0.04 0.02 0.06 0.04 047 Time (hr) Scr DKC1 KD DKC1 + DCP2 KD DKC1 + EXOSC10 KD DKC1 + DCP2 + EXOSC10 KD
F GHhTERT + C408G ∆ G 8G In vitro Mock WT A377 C40 378-415
Scr DKC1 KD DKC1 + PAPD5 KD In vitro WT hTR scr DCP2 KDDOM3Z EXOSC10KD XRN1 KD KDXRN2 KD hTR hTR hTR
7SL 7SL 1.0 0.17 0.40 7SL +/- 0.03 0.04
1.0 0.18 0.15 <0.05 1.0 3.12 1.06 3.96 3.84 1.17 +/- 0.03 0.02 +/- 0.15 0.09 0.21 0.14 0.08
Figure 3.1 Lack of dyskerin binding reduces hTR levels by two different RNA decay mechanisms. A) Western blot for DKC1 knockdown and northern blot for hTR in HeLa cells (mean +/-s.d., n=5 independent experiments). Scr, scrambled negative control siRNA. B,C) Representative northern blot for hTR upon DKC1 knockdown and rescue in HeLa cells (mean+/-s.d., n=4 independent experiments. D,E) Representative northern blot for hTR upon Actinomycin D shutoff in dyskerin knockdown and rescue in HeLa cells. Measurement of hTR decay rate in dyskerin knockdown HeLa cells. Error bars, s.d. (n=3 independent experiments). F) Northern blot showing hTR upon DKC1 knockdown with or without PAPD5 knockdown (mean+/-s.d., n=3 independent experiments). G) Northern blot for wild type (WT) disease- causing hTR mutants in U2OS cells (mean+/-s.d., n=3 independent experiments). H) Northern blot for C408G hTR RNA upon DCP2, EXOSC10 or XRN1 knockdown (mean+/-s.d., n=4 independent experiments).
60 To determine if these differences in RNA levels were due to changes in hTR stability, we measured the decay of hTR following inhibition of transcription with actinomycin D. As expected, we observed that in dyskerin knockdown cells, hTR was degraded faster than in control cells (Figure 3.1 D). More importantly, knockdown of
DCP2, EXOSC10, or both led to a decrease in hTR decay in the dyskerin knockdown cells (Figure 3.1 D & E). These results indicate that in the absence of dyskerin, hTR can be degraded by DCP2-mediated decapping leading to 5’ to 3’ degradation by
XRN1, as well as by nuclear 3’ to 5’ degradation by EXOSC10.
The exonucleolytic activity of EXOSC10 is enhanced by the poly(A) polymerase
PAPD5, which adds 3’ oligo(A) tails to promote substrate recognition by EXOSC10
(Kadaba et al., 2004; LaCava et al., 2005; Vaňáčová et al., 2005; Wyers et al., 2005).
To determine if PAPD5 affected hTR degradation, we examined if PAPD5 knockdown could rescue the reduced hTR levels in dyskerin-deficient cells. We observed that
PAPD5 knockdown increased hTR levels 2.4X (from 17% to 40% of control) in the dyskerin knockdown (Figure 3.1 F). Consistent with PAPD5 adding oligo(A) tails to hTR, a subset of endogenous hTR population exists in an oligoadenylated state (Goldfarb and Cech, 2013).
Pathogenic point mutations in hTR that disrupt either the dyskerin binding site
(A377G, 378-415∆) or the BIO box (C408G) also reduce hTR levels (Fu and Collins,
2003; Ueda et al., 2014; Vulliamy and Dokal, 2008). To determine if these reduced levels could also be rescued by inhibition of RNA decay enzymes, we transfected wild- type or mutant hTR along with hTERT into U2OS cells, which do not express detectable endogenous hTR by northern blotting, and examined hTR levels by northern blots with
61 or without knockdown of nucleases (Figure 3.2 A). Compared to the wild-type hTR, the
A377G, C408G, and 378-415∆ mutants have <20% steady-state hTR levels in U2OS cells (Figure 3.1 G). The reduced levels of the A377G and C408G hTR RNAs could be partially rescued by knockdown of DCP2 (3x), XRN1 (4X), EXOSC10 (4X) or PAPD5
(2X) (Figure 3.1 H and Figure 3.2 B, C & D). Knockdowns of several other RNA decay enzymes did not rescue hTR levels (Figure 3.1 H and Figure 3.2 E). Thus, when either dyskerin is deficient or its binding site in hTR is mutated, hTR molecules are degraded by PAPD5-mediated adenylation coupled to EXOSC10-mediated 3' to 5' degradation, as well as degradation by DCP2 and XRN1.
62
Figure 3.2 Quality-control pathways for A377G and C408G mutant hTR are conserved in U2OS cells. A) Western blot for knockdown of various nucleases in U2OS cells. B) Northern blot for A377G hTR levels upon knockdown of DCP2, EXOSC10 or XRN1 (mean+/-s.d., n=4 independent experiments). C) Northern blot for C408G hTR levels upon PAPD5 knockdown with or without a co-knockdown of DCP2 or XRN1 (mean+/-s.d., n=3 independent experiments). D) Northern blot for C408G hTR upon co- knockdown of EXOSC10 and PAPD5 (mean+/-s.d., n=4 independent experiments). E) Northern blot for hTR upon knockdown of various decapping enzymes in U2OS cells (mean+/-s.d., n=4 independent experiments).
63 EXOSC10 competes with PARN for processing of mature hTR
The degradation of hTR by PAPD5-promoted EXOSC10 nucleolytic activity led us to hypothesize that PARN would contribute to hTR stability by removing oligo(A) tails added by PAPD5, thereby limiting the ability of EXOSC10 to degrade hTR (Figure 3.3
A). Consistent with this model, PARN knockdown in HeLa cells led to reduced levels of hTR, and those were partially restored by knockdown of PAPD5 or EXOSC10 (Figure
3.3 B). Moreover, measurement of hTR stability following inhibition of transcription with actinomycin D showed that PARN knockdown leads to reduction in the stability of hTR in HeLa cells, which could be partially rescued by knockdown of EXOSC10 (Figure 3.3
C & D). We interpret this observation to argue that PARN and EXOSC10 are competing for hTR 3’ end processing (Figure 3.3 A).
To examine how 3’ adenylation of hTR was modulated by these enzymes, we sequenced the 3’ end of hTR in control cells and in cells with knockdowns of PARN,
EXOSC10, PAPD5, or a double knockdown of PARN and EXOSC10. We observed a fraction of hTR with oligo(A) tails, consistent with earlier results, and this oligoadenylated fraction decreased upon PAPD5 knockdown and increased upon
PARN, EXOSC10, or PARN & EXOSC10 knockdowns (Figure 3.3 E).
64 A D 100
75
PAPD5 50
25 PARN Relative RNA levels (%) Relative RNA
DKC 0 AAAAAAA 0 4 7 Time (hr) Scr PARN KD PARN + EXOSC10 KD EXOSC10
E 6 ***
*** B 5 *** 4 Scr PARN KDEXOSC10PAPD5 KDPARN KD +PARN EXOSC10 + PAPD5 KD KD
3 hTR ***
2 7SL 1 Oligo(A) tails at mature 3’ end (%) Oligo(A) tails at mature 3’ 1.0 0.36 1.83 1.08 0.68 0.74 +/- 0.03 0.08 0.05 0.03 0.04 0 Scr PAPD5 KD PARN KD EXOSC10 KD PARN+ EXOSC10 KD PARN + C Scr PARN KD EXOSC10 KD Time (hr) 0 4 7 0 4 7 0 4 7
hTR
7SL
Figure 3.3 PARN knockdown reduces hTR levels due to competing activity of EXOSC10. A) Model for competition between PARN and EXOSC10 for access to adenylated hTR 3’ end mediated by PAPD5. B) Northern blot for hTR upon PARN knockdown and rescue by EXOSC10 or PAPD5 co-knockdown (mean+/-s.d., n=6 independent experiments). C,D) Representative northern blot for Actinomycin D shutoff in PARN knockdown and rescue in HeLa cells. Measurement of hTR decay rate in PARN knockdown HeLa cells. Error bars, s.d. (n=4 independent experiments). E) Relative abundance of oligoadenylated reads at the mature hTR 3’ end with different components knocked down. Reads were normalized to the total number of mature end-containing reads under each condition. P<0.001 by two tailed Student’s t test for total number of reads in each condition.
65 The approximately fivefold reduction in the percentage of adenylated hTR molecules in the PAPD5 knockdown argues that PAPD5 adenylates hTR. Moreover, the increase in adenylated hTR molecules in PARN, EXOSC10, or the PARN and
EXOSC10 knockdowns provides evidence that PARN and EXOSC10 can deadenylate and/or degrade adenylated hTR molecules (Figure 3.3 A). We also observed that the length distribution of residual oligo(A) tail lengths on the mature 3’ end of hTR slightly decreases with PAPD5 knockdown and increases in PARN or PARN and EXOSC10 knockdowns (Figure 3.4). Oligo(A) tails at the mature 3’ end were slightly shorter in the
EXOSC10 knockdown, which is consistent with increased PARN activity in the absence of EXOSC10-mediated degradation (Figure 3.4). Thus, PARN competes with PAPD5 to limit the length of oligo(A) tails on hTR and thereby prevent EXOSC10-mediated degradation of hTR.
66 PARN KD vs Scr Mean: 6.41 vs 4.45 (P < 0.001)
PARN + EXOSC10 KD vs Scr Mean: 5.97 vs 4.45 (P < 0.001)
PAPD5 KD vs Scr Mean: 4.11 vs 4.45 (P < 0.001)
% of oligo(A) reads relative to total EXOSC10 KD vs Scr Mean: 3.99 vs 4.45 (P < 0.001)
No. of A’s at the mature 3’ end
Figure 3.4 hTR 3’ mature end exhibits longer A tails after PARN knockdown. Length distribution of oligo(A) tails at the mature 3’ end of hTR under different transfection conditions. Relative amount of each two or more A-containing reads was calculated to the total number of two or more A’s containing hTR reads under each transfection condition (P<0.05 by one tail unpaired Student’s t test).
67 EXOSC10 & PARN compete for PAPD5-mediated 3’ end processing
The sequencing of the 3' ends of hTR and their adenylation status also provides several observations arguing that PAPD5, PARN and EXOSC10 also affect 3’ end processing and/or the degradation of 3’ extended hTR precursors. Compared to the mature hTR 3' end, where 2.3% of the total reads were oligoadenylated, those hTR molecules extended up to 10 nucleotides past the mature 3’ end had a much greater proportion of oligoadenylation (74.5% of total reads). The percentage of these adenylated 3’ extended molecules decreased upon PAPD5 knockdown (down to 60%,), and increased upon knockdown of PARN (up to 90.1%) or EXOSC10 (87.4%).
We also observed that PARN knockdown led to an increase in the total amount of 3' extended hTR molecules detected, from 7.2% in the control to 15.7 % upon PARN knockdown. We interpret this result to suggest that PARN promotes the efficient 3' end processing of at least a subset of hTR molecules, which could occur if 3' end maturation requires deadenylation prior to trimming to the mature end.
Rescue of telomerase activity in DKC1 or PARN depleted cells
Our results indicate that knocking down RNA decay enzymes restores hTR levels in dyskerin- or PARN-deficient cells. To determine if the stabilized hTR molecules were functional, we examined the endogenous telomerase activity in dyskerin- or PARN-deficient HeLa cells, with or without rescue of hTR levels by knockdown of various nucleases. Immunoprecipitation with an anti-TERT antibody allowed a direct assay of the low endogenous telomerase activity (Cohen and Reddel,
2008).
68
We observed that knockdown of dyskerin in HeLa cells reduced telomerase activity (Figure 3.5 A), but activity could be partially restored by knockdowns of DCP2 or
EXOSC10 (Figure 3.5 A & B). A co-knockdown of EXOSC10 and DCP2 restored telomerase activity to essentially wild-type levels, in correlation with an increase in hTR levels to ~70% of WT levels under this condition (Figure 3.5 B and Figure 3.1 B).
Similarly, PARN-deficient cells showed reduced telomerase activity, and this decrease was rescued by a co-knockdown of EXOSC10 or PAPD5, similar to what was observed for the hTR levels in the cells under this condition (compare Figure 3.5 C & D with
Figure 3.3 B). These results indicate that the defect in telomerase activity in dyskerin- or
PARN-deficient cells is due to the reduced levels of hTR, and restoration of the RNA by inhibiting its decay is sufficient to restore telomerase activity.
69 A C
Scr DKC1 DKC1KD DKC1+ DCP2 +DKC1 EXOSC10KD + DCP2 KD + EXOSC10 KD Scr PARN KDPARN + EXOSC10PARN + PAPD5 KD KD
7
6 6 5
5 4
4 3 3
2 2
+4 +4 LC1 LC1 LC2 LC2
BD** 150 ** 150
** ** ** * ** 100 100
50 50 Relative telomerase activity (%) Relative telomerase activity (%) 0 0 Scr DKC1 KD DKC1+ DKC1+ DKC1+ Scr PARN KD PARN+ PARN+ DCP2 KD EXOSC10 KD DCP2+ EXOSC10 KD PAPD5 KD EXOSC10 KD
Figure 3.5 Rescue of telomerase activity in dyskerin- or PARN-depleted HeLa cells by co- knockdown of competing nucleases. A) Autoradiograph for telomerase activity assay in HeLa DKC1 knockdown and rescue cells. LC1 and LC2, oligonucleotide loading controls.1-6, telomeric repeats added to the telomeric primer. B) Telomerase activity relative to the Scr control sample. Error bars, s.d. (n=5 independent experiments). ** P<0.01 by one-tailed unpaired Student’s t test. C,D) Autoradiograph for telomerase activity assay in HeLa PARN knockdown and rescue cells. Labeling of blot as in A). Error bars, s.d. (n=5 independent experiments), * P<0.05, ** P<0.01 by one-tailed unpaired Student’s t test.
70 Rescue of hTR subcellular localization by decay inhibition
Normally, hTR is predominantly localized to Cajal bodies and to telomeres
(depending on the cell cycle stage) in telomerase-positive human cells (Tomlinson et al., 2006; Venteicher et al., 2009; Zhu et al., 2004). Since knockdown of nucleases increased hTR levels in cells that were deficient in dyskerin or PARN, we determined if these hTR RNPs could localize to Cajal bodies by FISH.
Similar to previous results (Venteicher et al., 2009; Zhu et al., 2004), we observed that endogenous hTR was localized to Cajal bodies in essentially all HeLa cells (Figure 3.6 A). However, in cells with knockdown of dyskerin or PARN, we observed a reduction in FISH signal, consistent with the reduced hTR levels; only 8% or
14% of the cells maintained hTR in Cajal bodies upon DKC1 or PARN knockdown, respectively (Figure 3.6 A & B). Surprisingly, in a fraction of the dyskerin (23%) or
PARN (13%) knockdown cells, we observed the residual FISH signal for hTR in cytoplasmic puncta that have not been previously described (Figure 3.6 A, white arrowheads). We refer to these puncta as cytoplasmic TER (cyTER) -bodies.
71 DAPI Coilin hTR Merge A 100
Scr
8+/-3.1
DKC1 KD
29+/-6.2
DKC1 + DCP2 KD
45+/-6.7
DKC1 + EXOSC10 KD
84+/-13.4
DKC1 + DCP2 + EXOSC10 KD
B DAPI Coilin hTR Merge 100
Scr
14+/-4.6
PARN KD
100
EXOSC10 KD
85+/-11.8
PARN + EXOSC10 KD
72 Figure 3.6 Mislocalization of hTR in dyskerin or PARN knockdown HeLa cells can be corrected by knockdown of competing nuclease. A) Subcellular localization of hTR by FISH in HeLa cells upon dyskerin knockdown (white arrowheads), and the localization to Cajal bodies upon rescue by DCP2 or DCP2 and EXOSC10 co-knockdown (light brown arrowheads) (Scale bar 5 μm). White numbers in Merge, % of cells showing hTR localization to CBs (mean+/-s.d., n=3 independent experiments). B) Subcellular localization of hTR by FISH to the cytoplasm or to CBs upon PARN knockdown and rescue, respectively (light brown arrowheads) (Scale bar 5 μm). White numbers in Merge, % of cells showing hTR localization to CBs (mean+/-s.d., n=4 independent experiments).
Similar aberrant localization of hTR was observed when we analyzed hTR point mutations. In U2OS cells transfected with hTERT and wild-type hTR, we observed that hTR localized to telomeres along with Cajal bodies, which have been defined as neo-
Cajal bodies (Figure 3.7 A) (Zhong et al., 2012). In contrast, cells expressing hTERT and the A377G or C408G mutant hTR showed reduced FISH signal for hTR and loss of hTR association with Cajal bodies, and only 21% and 18% of cells respectively still showed hTR in Cajal bodies (Figure 3.8). The residual hTR signal was observed in cyTER-bodies (82% of cells for C408G hTR) (Figure 3.8, white arrowheads).
73 A TRF2 Coilin hTR Merge
Mock (negative control)
100
WT hTR
B A377G + hTERT Lamin A/C Coilin hTR Merge 21+/-4
Scr
40+/-6
DCP2 KD
53+/-5
EXOSC10 KD
57+/-5
DCP2+ EXOSC10 KD
Figure 3.7 Mutant hTR localization to Cajal bodies can be rescued by knockdown of RNA decay pathways. A) WT hTR localization to neo-Cajal bodies at telomeres (labeled with TRF2) by FISH in cells overexpressing hTERT (Scale bar 5μm). White numbers in Merge, % of cells showing hTR localization to CBs (mean+/-s.d., n=4 independent experiments). B) Nuclear localization of A377G mutant hTR to Cajal bodies by FISH (light brown arrowheads) in hTERT co-transfected U2OS cells upon knockdown of nucleases (Scale bar 5μm). White numbers in Merge, % of cells showing hTR localization to CBs (mean+/-s.d., n=3 independent experiments).
74 Lamin A/C Coilin hTR Merge
Mock (negative control)
100
WT hTR
21+/-4
A377G hTR
18+/-7
C408G hTR
Figure 3.8 Mutant hTR localizes to cyTER bodies in U2OS cells. Mutant A377G or C408G hTR is mislocalized to the cytoplasm in cyTER bodies in U2OS cells. Cytoplasmic localization of A377G or C408G RNA (white arrowheads) by FISH in U2OS cells. The nucleus is labeled with an antibody that recognizes either of the nuclear envelope components lamin A or lamin C (Scale bar 5 μm). White numbers in Merge, % of cells showing hTR localization to Cajal bodies (mean+/-s.d., n=4 independent experiments).
75 To test if cyTER-bodies might represent sites of promiscuous hybridization of the hTR probes, we performed a FISH experiment with a combination of differently labeled hTR probes. The two different probes clearly co-localize in Cajal bodies for wild-type hTR. For the C408G mutant, the probes co-localize in cyTER-bodies but not with Cajal bodies (Figure 3.9 A, white arrowheads). cyTER-bodies also do not co-localize with
DCP1 or SMN, indicating these assemblies are not P-bodies, U-bodies or GEMS, respectively (Figure 3.9 B). Thus, defects in PARN or dyskerin binding reduce hTR levels, disrupt proper hTR localization to Cajal bodies and telomeres, and lead to the identification of a novel cytoplasmic pool of hTR.
76 A hTR probe schematic Alexa 488 Alexa 647 Probe 1 A 1 Probe 2 B 2 Probe 3 C 3
Coilin hTR hTR Merge
A+B+3
A+C+2 WT hTR
B+C+1
A+B+3 C408G hTR
B DCP1 SMN hTR Merge
C408G hTR
Figure 3.9 FISH signal for WT and mutant hTR is specific and does not localize to P bodies or U bodies. cyTER bodies are novel sites of hTR storage. A) Subcellular localization of WT or C408G hTR (white arrowhead) by FISH using different combinations of Alexa Fluor labeled probes (Scale bar 5 μm). B) Subcellular localization of C408G RNA puncta (white arrowhead) in U2OS cells. Other foci stained were U-bodies or Gems (SMN) or P-bodies (DCP1) (Scale bar 10μm).
77 An important result was that knockdown of DCP2 and/or EXOSC10 could restore hTR levels and proper localization of defective hTR RNPs by FISH in three cases. First, in dyskerin knockdown cells, EXOSC10, DCP2 or a double DCP2 and EXOSC10 knockdown led to restoration of hTR localization to Cajal bodies (29%, 45% and 84% of cells respectively) (Figure 3.6 A, light brown arrowheads). For EXOSC10 knockdown, the RNA sometimes localized to sites other than Cajal bodies in the nucleus (yellow arrowheads), which could possibly be telomeres. Second, we observed that knockdown of EXOSC10 in PARN-deficient cells restored localization of hTR to Cajal bodies (85% of cells) (Figure 3.6 B, light brown arrowheads). Finally, we observed that knockdowns of DCP2, EXOSC10, or DCP2/ EXOSC10 could restore the localization of A377G hTR to Cajal bodies (Figure 3.7 B). Thus, stabilization of hTR in either dyskerin or PARN- deficient cells can restore both telomerase activity (Figure 3.5) and localization to Cajal bodies (Figure 3.6).
78 Discussion
The absence of dyskerin protein or mutations in hTR that alter RNP assembly lead to decreased hTR levels, insufficient telomerase, and failure to maintain human stem cells. Here we identify decapping followed by XRN1-mediated 5’ to 3’ degradation and 3’ to 5’ degradation by the nuclear exosome as two independent quality control pathways for hTR in response to defects in dyskerin protein or mutations in hTR.
Importantly, we show that these reduced levels of hTR and of telomerase activity can be rescued by knockdown of DCP2, XRN1, or EXOSC10 (Figure 3.1 and Figure 3.2).
Evidence that decapping/XRN1 and the nuclear exosome comprise independent pathways is that double knockdowns of DCP2 or XRN1 with EXOSC10 have an additive effect on hTR levels (Figure 3.1). Additional evidence that the nuclear exosome affects hTR degradation comes from the observation that knockdowns of the nuclear exosome lead to the accumulation of 3’ extended hTR molecules, as well as an increase in the levels of mature hTR (Nguyen et al., 2015; Tseng et al., 2015).
These observations support a model for hTR biogenesis that involves competition between dyskerin binding and hTR decay in the cell (Figure 3.10). Under normal conditions, dyskerin binding allows hTR accumulation, either through co- transcriptional association or through cytoplasmic binding followed by nuclear re-import.
When dyskerin binding to hTR is compromised, hTR can be degraded in the nucleus by
EXOSC10 as well as exported to the cytoplasm and degraded by DCP2–XRN1.
79 Nucleus Cytosol
DKC RNP Assembly
DKC Possible reimport
m7Gppp m7Gppp
Functional nuclear teomerase RNP PAPD5 PARN DKC Export
m7Gppp Possible cytoplasmic RNP assembly
AAAAAAA
m7Gppp DKC
m7Gppp
Concentrate in foci Decapping and 5’ 3’ decay
DCP2 m 7 Gppp
m7Gppp A A A
hTR cytoplasmic foci Xrn1 p
Figure 3.10 Model for hTR biogenesis in mammalian cells. hTR biogenesis involves competition between hTR assembly with H/ACA snoRNP proteins, 3’ end processing by PAPD5 and PARN and degradation by EXOSC10, and cytoplasmic export and degradation by DCP2 and XRN1.
80 Several observations provide a molecular explanation for the requirement of
PARN for hTR stability, wherein it specifically removes oligo(A) tails on hTR added by
PAPD5, which would otherwise recruit EXOSC10 (the nuclear exosome) to degrade hTR. First, knockdown of PARN leads to reduced levels of hTR due to faster hTR degradation (Figure 3.3) (Moon et al., 2015), which can be rescued by knockdown of
EXOSC10 or PAPD5 (Figure 3.3). Second, we observe that the oligo(A) tails on hTR are reduced when PAPD5 is depleted, and increase upon PARN or EXOSC10 depletion
(Figure 3.3). Since PARN is specific for adenosine residues, deadenylation by PARN would limit the recruitment of EXOSC10 to hTR, thereby increasing it stability.
Our observations suggest that PARN is not primarily required for hTR biogenesis, since when PARN is limiting, knockdowns of EXOSC10 or PAPD5 can restore hTR levels (Figure 3.3), telomerase activity (Figure 3.5) and localization of hTR to Cajal bodies (Figure 3.6). Instead, we suggest that PARN continually functions to remove oligo(A) tails added to hTR by PAPD5. This is likely to be a general phenomenon wherein stable non-coding nuclear RNAs with accessible 3’ ends will be constant substrates for PAPD5, and therefore their equilibrium concentrations would be maintained by PARN removing such oligo(A) tails to limit their degradation by the nuclear exosome.
There are two important implications of our observation that defects in hTR levels, telomerase activity, and proper subcellular location of hTR in cells deficient in
PARN or dyskerin could all be rescued by knockdowns of EXOSC10, PAPD5 and/or
DCP2. First, this demonstrates that neither PARN nor dyskerin is required for the biogenesis, activity, or in certain cases, localization of hTR. Second, this restoration of
81 function suggests that inhibition of hTR degradation could be a viable therapeutic strategy for telomere pathologies. As such, dyskeratosis congenita is now seen to fall in the broader category of a ‘RNP hypo-assembly disease’, where a competing RNA quality control pathway degrades the RNA and limits RNP assembly due to reduced binding by the RNA’s protein partner(s) (Shukla and Parker, 2016).
A surprising observation was that in cells deficient in PARN or dyskerin, or those expressing mutant hTR molecules, hTR accumulated in discrete cytoplasmic foci, in a fraction of cells, referred to as cyTER-bodies. This provides evidence that hTR can be exported from the nucleus, as described previously for the budding yeast telomerase
RNA (Gallardo et al., 2008; Teixeira et al., 2002), and reveals a completely new aspect of human telomerase RNA cell biology. These foci do not co-localize with markers of P- bodies or GEMs, and thus are of unknown composition. Future work should reveal if these puncta are sites of hTR storage, or play a role in normal hTR biogenesis, possibly licensing the hTR RNP for nuclear import.
82 Experimental methods
Cell culture
HeLa cells were purchased from ATCC, and the U2OS cells were a kind gift from
Dr. Sabrina Spencer (University of Colorado Boulder), and were tested for mycoplasma contamination. All cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% Fetal Bovine Serum (FBS), L-Glutamax (Thermo Fisher),
Penicillin/Streptomycin (Thermo Fisher) and Normocin (Invivogen), at 37°C and 5%
CO2.
Plasmid transfection and siRNA knockdown
The 3xFLAG-hTERT and WT U1-hTR plasmid were gifts of Joachim Lingner
(ISREC, Lausanne, CH). The disease-causing mutations were introduced in the WT hTR plasmid using site-directed mutagenesis, and the mutations were verified using
Sanger sequencing. Plasmid transfection was performed on U2OS cells using JetPrime
(Polyplus transfection) according to manufacturer’s protocol. Total plasmid concentration was limited to 2 μg for 6-well plates and 10 μg for 10 cm dishes. Plasmid transfection was allowed to take place between 24 and 48 hours before harvesting cells. siRNAs were purchased from Qiagen (Scr, DKC1, EXOSC10 and DCPS) and
Dharmacon (PARN, XRN1, DCP2, XRN2, DOM3Z, PAPD5 and NUDT16). siRNA transfection was performed using Interferin (Polyplus transfection) according to manufacturer’s protocol, and final siRNA concentration was limited to 5 nM except for
DKC1 siRNA, where final concentration of the siRNA was kept at 0.5 nM. Knockdown was allowed to take place for at least 48 hours and was verified using western blot analysis using antibodies against XRN1 (Bethyl #A300-443A) , EXOSC10 (Thermo
83 #PA5-28672), DCP2 (Bethyl #A302-597A), DPCS (PA5-30532) and NUDT16 (LSbio
#LC-C117055) described previously (Shukla and Parker, 2014), while the other antibodies are as follows: anti-Dyskerin (Bethyl #A302-591A), anti-XRN2 (Cell Signaling
#13760S), anti-DOM3Z (Pierce #PA5-29505), anti-PARN (Abcam #ab27778) and anti-
PAPD5 (Atlas #HPA042968). Anti-GAPDH (Cell Signaling #2118S) was used as loading control. Antibody validation is provided on the manufacturer’s website.
Northern blot analysis of hTR
RNA extraction was carried out using Quick RNA miniprep kit (Zymo Research).
RNA was separated on a 5% polyacrylamide 7M urea gel at 20W, and transferred to a
Nylon membrane (Whatman). hTR and 7SL northern probes have been previously described (Xi and Cech, 2014). In vitro transcribed hTR was used as a marker and has been previously described (Xi and Cech, 2014). For hTR decay rate measurement, cells were treated with Actinomycin D (Sigma) to final concentration of 5 µg/ml and harvested at 0, 4 and 7 hours post-treatment. All blots were imaged on a Typhoon phosphorimager, and hTR levels were quantified using Image Quant 5.2 and normalized to the 7SL levels under each condition.
Immunofluorescence and FISH in U2OS and HeLa cells
For imaging, HeLa or U2OS cells were grown directly on coverslips in six well plates, and siRNA knockdown/plasmid transfection was performed on these cells before fixing them with 4% formaldehyde. Immunofluorescence was performed with Mouse anti-TRF2 (Novus Biologicals # NB100-56506), Rabbit anti-coilin (Santa Cruz #sc-
32860), Mouse anti-lamin A/C (Cell Signaling #4777S), Rabbit anti-DCP1B (Cell
Signaling #13233S), Rabbit anti-pan cadherin (Abcam #ab16505). Secondary
84 antibodies used were Anti-rabbit Alexa Fluor 405 (Life Technologies #A-31556), Anti- mouse Alexa Fluor 405 (Life Technologies #A-31553), Anti-rabbit Alexa Fluor 594 (Life
Technologies #A-11037), Anti-mouse Alexa Fluor 594 (Life Technologies #A-11005) and Anti-mouse Alexa Fluor 647 (Abcam #ab150119). Antibody validation is provided on the manufacturer’s website. After IF protocol, the antibodies were again fixed using
4% formaldehyde, and FISH for hTR was performed using Alexa 488 or Alexa 647 5’- labeled DNA oligos as described previously (Abreu et al., 2011)2. The coverslips were sealed using ProLong Diamond Antifade Mountant (Thermo) with or without DAPI
(Thermo Fisher). For FISH combination experiments in U2OS cells, transfected cells grown on coverslips were hybridized by equal amounts of each individual probe such that the total amount of hTR probe used was the same as that for single probe FISH experiment. In all U2OS imaging experiment, hTERT was co-transfected along with the indicated hTR RNA. Cells were imaged on a Deltavision deconvolution microscope using either a 60x or a 100x zoom, and all images were deconvolved and quick projected using the SoftWoRx software. All images taken for a particular experiment were normalized to the same threshold. Representative images are shown under each condition. For quantification, at least 50 cells were quantified for three biological replicates. Cells showing hTR localization to at least one Cajal body were scored and depicted as a percentage of total cells counted.
Telomerase activity assay for HeLa and U2OS cells
For direct assays of endogenous telomerase activity, a similar number of HeLa cells for each experiment was trypsinized, pelleted and lysed using lysis buffer described previously (Cohen and Reddel, 2008). hTERT IP was performed using an
85 anti-hTERT antibody (generous gift from Dr. Scott B. Cohen, Children’s Medical
Research Inst., Sydney AU). The activity assay conditions (Cohen and Reddel, 2008;
Schmidt et al., 2014) and the primer (Schmidt et al., 2014) used have been described previously. Reactions were quenched using a stop buffer containing 3.6 M ammonium acetate, 20mg/ml glycogen and two 32P-labeled telomeric template oligos used as loading controls. The reaction products were separated on a 10% polyacrylamide 7 M urea sequencing gel at 90W, and imaged on a Typhoon phosphorimager. Intensity of the bands was quantified using Image Quant 5.2 software and normalized to one of the two loading controls (labeled LC1 and 2). hTR 3’ end sequencing
hTR sequencing was performed from total RNA isolated under various knockdown conditions. The RNA was DNase-treated, followed by RiboZero (Illumina) treatment as per manufacturer’s protocol. The resultant RNA was treated with rAPid
Alkaline phosphatase (Sigma Aldrich) as per manufacturer’s protocol. ~125 ng of the resultant RNA was used for library preparation as previously described, except that a different hTR barcoded forward primer downstream of the original primer was used for
3’ RACE (Goldfarb and Cech, 2013). The amplified libraries were quantified on
Bioanalyzer and Qubit, and 3 pM pooled libraries containing 30% phiX control were sequenced on the Illumina MiSeq as per manufacturer’s instructions. Data analysis was performed as previously described (Goldfarb and Cech, 2013). More than 160,000 reads containing both the RNA appendix and the hTR search primer were generated for each condition. For analysis of oligo(A) distribution at the mature 3’ end, total number of reads containing the mature 3’ end (UGC-451), whether adenylated or non-adenylated,
86 was calculated, and reads that contained the first A (UGCA-452) were assumed to be non-adenylated, since the mechanism of generating those reads (whether genomically encoded or adenylation of the mature end) is ambiguous. Reads that contained two or more A’s were identified as oligoadenylated, and these were pooled to calculate the relative percentage of oligoadenylated mature 3’ ends under each transfection condition. To calculate the frequency distribution of the A tails, the relative percentage of each tail length was calculated relative to the total number of reads containing two or more A’s. For PAPD5 knockdown, the total number of mature oligoadenylated reads vs non-adenylated reads was very small (2388 reads against 529628 reads), and the hTR oligo(A) tail length distribution at the mature end shown in Figure 3.4 overestimates the abundance of such reads under this condition.
87 Chapter 4: Disease causing mutations in 3’ to 5’ exonucleases affect
processing and stability of human non-coding RNAs
Summary
Loss-of-function mutations in some 3’-5’ exoribonucleases have been implicated in hereditary human diseases. For example, PARN mutations have been implicated in a severe form of Dyskeratosis Congenita (DC) and familial pulmonary fibrosis, and USB1 mutations in Poikiloderma with Neutropenia (PN) as well as DC. Here, we show that
PARN depletion also affects the stability of abundant human Y RNAs, which could explain the severe phenotype of DC observed in patients carrying PARN mutations.
Additionally, there are other stable non-coding RNAs (ncRNAs) which are substrates for
PARN-mediated deadenylation without an effect on their abundance. We also show that
USB1 depletion affects the steady state levels and processing of the U6 snRNA. In both cases, depletion of PAPD5 rescues the effect of PARN or USB1 depletion on their respective RNAs, implicating oligoadenylation followed by 3’ to 5’ exonucleolytic degradation as the mechanism responsible for degradation of ncRNAs in these diseases. Therefore, inhibitors of PAPD5’s activity could be a viable therapeutic target for the treatment of a variety of human diseases.
88 Misregulation of 3’ end formation of ncRNAs can cause human disease
Proper 3’ end formation of RNAs plays an important role in regulating their function in the cell. Correct 3’ end formation is also important for the recruitment of protective protein(s), which serve to stabilize the RNA. For a number of stable non- coding RNAs in the cell, like snRNAs, snoRNAs and human telomerase RNA, the 3’ end formation is regulated by coordinated activity of exonucleases that trim the precursor
RNA to the mature form (Allmang et al., 1999a; Fu and Collins, 2003; van Hoof et al.,
2000; Yong et al., 2010). These exonucleases compete with RNA binding proteins to regulate the levels and stability of the RNA, and perturbations in this equilibrium can lead to a disease state (Shukla and Parker, 2016).
Mutations in 3’ to 5’ exonucleases have been shown to cause a number of different human diseases. Mutations in PARN lead to familial pulmonary fibrosis, as well as a severe form of DC characterized by congenital defects and abnormally short telomere lengths (Dhanraj et al., 2015; Stuart et al., 2015). We along with others have recently shown that PARN deadenylates hTR 3’ ends, and PARN depletion leads to oligoadenylation of hTR 3’ end by PAPD5, leading to its degradation by EXOSC10
(Nguyen et al., 2015; Shukla et al., 2016; Tseng et al., 2015). Whether PARN regulates the stability of other non-coding RNAs in a similar manner remains to be investigated.
Loss-of-function mutations in the C16orf57 gene, hereafter referred to as USB1, lead to poikiloderma with neutropenia (PN), as well as DC (Kilic and Cekic, 2016;
Tanaka et al., 2010; Volpi et al., 2010; Walne et al., 2010). Subsequent studies have shown that USB1 is a 3’-5’ exonuclease that removes terminal U’s from the U6 snRNA
89 precursor, and catalyzes the 2’-3’ cyclic phosphate bond formation at the mature end
(Hilcenko et al., 2013; Mroczek et al., 2012; Shchepachev et al., 2012). Analysis of U6 snRNA from PN patient cells and yeast strains lacking the human USB1 ortholog have shown that USB1 deficiency leads to the accumulation of extended forms of U6, which contain post-transcriptionally added oligo (A) nucleotides (Hilcenko et al., 2013;
Shchepachev et al., 2012). However, the mechanism by which U6 snRNA is oligoadenylated in absence of USB1, and more importantly, how that affects the stability and function of U6, is not well understood.
Apart from PARN and USB1, mutations in various exosome components have been shown to cause human disease. Mutations in EXOSC3 lead to pontocerebellar hypoplasia (J. Wan et al., 2012). Mutations in EXOSC8 have been shown to cause a form of spinal muscular atrophy (Boczonadi et al., 2014). Finally, mutations in EXOSC2 have recently been shown to cause pleiotropic effects that include vision, hearing and intellectual defects (Di Donato et al., 2016). How these specific mutations in a single complex lead to different human diseases remains unresolved.
PARN-mediated deadenylation of hTR suggests that post-transcriptional processing of stable non-coding RNAs could be a general phenomenon that regulates the stability of a number of different RNAs. Further, it is still unclear why mutations in
PARN lead to a much more severe form of DC compared to mutations in telomerase enzyme components. One possibility is that PARN deficiency is compounded by defects in the processing of other RNAs, which could be important for maintenance of telomeres.
90 Here, we investigated how the exonucleases USB1 and PARN regulate the processing and stability of different abundant ncRNAs, which reveals previously unknown quality control pathways for U6, RMRP and human Y RNAs. We show that in the absence of USB1, U6 snRNA is oligoadenylated by PAPD5 at its 3’ end, and is degraded by EXOSC10. A co-knockdown of USB1 with PAPD5 or EXOSC10 rescues
U6 snRNA levels comparable to control. Sequencing analysis of U6 snRNA reveals information about the position of 3’ ends susceptible to degradation by EXOSC10.
We also show that PARN deadenylates both U6 snRNA and RMRP under normal conditions, but has no significant effect on the steady state levels of either of these RNAs. This suggests that many ncRNAs are substrates for PARN-mediated deadenylation, without getting destabilized in its absence like hTR does. We found that
PARN does destabilize human Y RNAs, which are abundant small RNA pol III transcribed RNAs that are posited to play a role in RNA quality control, initiation of DNA replication, and histone mRNA processing (Christov et al., 2006; Hendrick et al., 1981;
Köhn et al., 2015; Wolin and Steitz, 1983). Low levels of Y RNAs could potentially exacerbate the effect of PARN depletion on telomere maintenance, leading to the severe phenotype of DC observed in patients carrying PARN mutations.
91 Results
USB1 depletion reduces the steady state levels of U6 snRNA in human cells
Previous studies have shown contradictory effects of USB1 depletion on U6 snRNA levels and stability in cell culture models (Hilcenko et al., 2013; Mroczek et al.,
2012; Shchepachev et al., 2012). In order to study the effect of USB1 depletion on U6 snRNA processing, we first investigated whether USB1 knockdown in HeLa cells affects the steady state levels of U6 snRNA. We found that USB1 knockdown leads to a ~35% reduction in the levels of U6 snRNA in HeLa cells (Figure 4.1 A & B). This suggests that efficient knockdown of USB1 does reduce U6 snRNA levels in mammalian cells, supporting a role for USB1 in U6 snRNA stability.
USB1 depletion does not affect the levels of human telomerase RNA
Since USB1 mutations have also been shown to lead to DC, we investigated whether USB1 knockdown also affects the steady state levels of the human telomerase
RNA (hTR). In contrast to the U6 snRNA, USB1 knockdown does not significantly affect the steady state levels of hTR in human cells (Figure 4.1 C). This supports the prevailing hypothesis in the field that USB1 mutations lead to DC by a currently unknown mechanism independent of telomere maintenance, since patients carrying
USB1 mutations have normal telomere lengths comparable to healthy controls (Walne et al., 2010).
92
Figure 4.1 USB1 knockdown leads to a decrease in U6 levels and affects 3’ end maturation. A) Representative western blot for USB1 KD in HeLa cells. B) Representative northern blot for U6 snRNA in HeLa cells. Probe against 5s rRNA was used as a loading control. Numbers represent normalized U6 levels (Average +/- S.D.) for four biological replicates. C) Representative northern blot for hTR levels in HeLa cells. Numbers represent normalized hTR levels (Average +/- S.D.) for four biological replicates. D) Percentage of total reads terminating at mature or extended ends of U6 snRNA in HeLa cells. E) Percentage of oligoadenylated reads at different 3’ ends for U6 snRNA. Fraction of oligoadenylated reads was calculated from total number of reads at each individual end. F) Percentage of oligoadenylated reads and percentage of total reads at extended U6 ends in HeLa cells. Fractions were calculated as in D) and E).
93 USB1 knockdown leads to an increase in adenylated U6 mature and precursor species
A previous study in PN patient cells found that U6 snRNA exists in an oligoadenylated state in these cells in contrast to healthy controls (Hilcenko et al.,
2013). However, no difference was seen on the steady state levels of the U6 snRNA in the patient cells in this study. Since we observed that U6 levels decrease upon USB1 knockdown, we then investigated whether the post-transcriptional processing of U6 snRNA is affected under these conditions.
We deep-sequenced the 3’ ends of U6 snRNA under control or USB1 knockdown conditions. We discovered that there is significant heterogeneity in the formation of the
3’ end of U6 snRNA. A significant fraction of total reads terminated at ends within the
Lsm 2-8 complex binding site (AUUUU) at the -1 and 0 position, where the 0 position is the last U in the Lsm 2-8 binding site, and at precursors up to the +4 position beyond the Lsm 2-8 binding site. In control cells, ~9 % and 11% of total reads terminated at the
-1 U and 0 U, which are a part of the Lsm site, and ~18% of total reads terminated at the +1 U, which is the most abundant 3’ end for U6 in HeLa cells. Further, ~12 %, 10% and 5% of total reads terminated at +2 U, +3 U and +4 U respectively. These precursor ends are unlikely to be genomically encoded, since RNA Pol III transcription terminates at poly(T) stretches 5-6 nucleotides in length. Together with the proportion of reads that terminate at ends in the Lsm site, this suggests that U6 snRNA 3’ end formation in human cells is dynamically regulated by the competition between terminal uridylases and 3’ to 5’ exonucleases, along with the association and dissociation of the Lsm 2-8 complex.
94 Comparison of U6 snRNA 3’ ends between control and USB1 knockdown cells led to three observations regarding the processing and post-transcriptionally modified fate of the U6 snRNA. First, knockdown of USB1 led to a reduction in the percentage of reads terminating at the canonical 3’ end of the U6 snRNA (Figure 4.1 D). Interestingly, the strongest decrease was observed for reads terminating at the +1 U, which is the next nucleotide after the Lsm 2-8 site (Achsel et al., 1999). This suggests that steady state levels of U6 snRNA observed upon USB1 knockdown are likely to reflect the pool of U6 snRNA that is bound to, and therefore, stabilized by the Lsm2-8 complex.
Second, knockdown of USB1 led to significant increase in the percentage of oligoadenylated U6 snRNA species at the +1 U and +2 U positions (Figure 4.1 E). This increase was not observed at the 0 U position, which suggests that this nucleotide is either structurally protected from the activity of the TRAMP complex, or is rapidly deadenylated upon USB1knockdown. This further supports the argument that the pool of U6 snRNA observed upon USB1 knockdown reflects the assembled U6 snRNP.
Third, we observed an increase in oligoadenylation, as well as the percentage of total reads, for U6 snRNA precursors that were detected in our sequencing (+3 to +5 U)
(Figure 4.1 F). This data supports previously observed oligoadenylation of U6 snRNA precursors in PN patient cells (Hilcenko et al., 2013). This also suggests that in the absence of USB1’s exonucleolytic activity, U6 snRNA precursors accumulate in an oligoadenylated state, making the RNA a substrate for exosome mediated degradation.
Based on the steady state levels of the U6 snRNA and the nature of the 3’ end upon
USB1 knockdown, we conclude that the competition between USB1, TRAMP complex and the exosome likely occurs post-transcriptionally when the U6 snRNA is undergoing
95 assembly with the Lsm complex. However, co-transcriptional competition between La binding to the nascent 3’ oligo U tail and USB1 cannot be completely ruled out.
Reduced U6 snRNA levels upon USB1 knockdown can be rescued by a co- knockdown of PAPD5 or EXOSC10
The accumulation of oligoadenylated U6 snRNA species in USB1 knockdown cells suggested that U6 snRNA is most likely a substrate for the TRAMP complex in this condition. Therefore, we performed a co-knockdown of USB1 and PAPD5, which is the poly (A) polymerase component of the TRAMP complex, in HeLa cells to ask whether prevention of oligoadenylation can rescue the levels of U6 snRNA. We observed that a knockdown of USB1 reduced U6 snRNA levels, and a co-knockdown of USB1 and
PAPD5 increased the levels of the U6 snRNA to control (Figure 4.2 A). We also performed a co-knockdown of the exosome component EXOSC10, which is a nuclear 3’ to 5’ exonuclease, to verify that U6 snRNA is degraded by the exosome in the absence of USB1. Similar to PAPD5 knockdown, a co-knockdown of USB1 and EXOSC10 rescued U6 snRNA to control levels (Figure 4.2 A). This supports the hypothesis that in the absence of USB1, PAPD5 adenylates U6 snRNA, which leads to its degradation by
EXOSC10.
As mentioned earlier, our deep sequencing analysis of U6 snRNA 3’ end suggests that the population of U6 snRNA that remains after USB1 knockdown is stabilized by the Lsm 2-8 complex. To test this prediction, we performed a co- knockdown of Lsm8 and USB1. This led to highly reduced levels of U6 snRNA (23% of control), that were lower than U6 snRNA levels upon Lsm8 knockdown alone (42% of control) (Figure 4.2 B). Interestingly, we observed a smear above the U6 snRNA band
96 in Lsm8 knockdown, which became stronger upon Lsm8 and USB1 co-knockdown
(Figure 4.2 B). This smear could represent post-transcriptionally added nucleotides to the 3’ end, suggesting that Lsm 2-8 complex’s association with U6 snRNA plays a role in preventing oligoadenylation of U6 snRNA by PAPD5.
We then investigated if EXOSC10 knockdown could rescue U6 snRNA levels when USB1 and Lsm8 have been depleted. A co-knockdown of EXOSC10 with Lsm8 and USB1 rescued U6 snRNA levels to control (124% of control) (Figure 4.2 C). This suggests that U6 snRNA is degraded by the exosome upon destabilization of its 3’ end, either due to loss of snRNP formation upon Lsm8 deficiency, or due to the prevention of
3’ end maturation and 2’-3’ cyclic phosphate formation upon USB1 depletion.
Figure 4.2 U6 snRNA levels can be rescued by a co-knockdown of PAPD5 or EXOSC10 in HeLa cells. A) Representative northern blot for U6 levels in USB1 KD alone or a co-knockdown of USB1 with PAPD5/EXOSC10 in HeLa cells. Average +/-S.D. of steady state levels is shown below each lane for four biological replicates. B) Representative northern blot for U6 levels in HeLa cells depleted of Lsm8 at different siRNA concentrations. Arrow shows smear representing post-transcriptionally added nucleotides to the 3’ end. Average +/-S.D. of steady state levels is shown below each lane for three biological replicates. C) Representative northern blot for rescue of U6 levels in Lsm8 and USB1 knockdown HeLa cells. Average +/-S.D. of steady state levels is shown below each lane for three biological replicates.
97 PARN deadenylates a number of stable ncRNAs in human cells
In order to identify novel substrates for PARN-mediated 3’ end deadenylation and processing in human cells, we chose a number of different stable ncRNAs, some of which have been reported to possess post-transcriptionally added oligo(A) tails at the 3’ end. We sequenced the 3’ ends of U6 snRNA in PARN depleted cells, since U6 snRNA is a substrate for PAPD5-mediated oligoadenylation. We also sequenced the RMRP
RNA, which is the catalytic component of the mitochondrial RNase P-like enzyme complex, and was shown to contain post-transcriptionally added oligo (A) tails (Goldfarb and Cech, 2013). We sequenced the RNA component of the RNase P enzyme, H1
RNA, as a negative control, since this RNA was shown to not contain a significant number of post-transcriptionally added adenosines in the same study (Goldfarb and
Cech, 2013).
We found that (similar to what we had previously shown for hTR (Shukla et al.,
2016)) knockdown of PARN led to an increase in the fraction of oligoadenylated reads at the mature end for U6 snRNA, and an increase at the precursor ends for RMRP
(Figure 4.3 A). In the case of RMRP, while the increase in oligoadenylated reads at the mature end was marginal, we did observe longer oligo (A) tails in PARN knockdown cells compared to the control cells at the 0 U position (mean number of A’s at mature end; 2.6 for control and 3.0 for PARN knockdown) (Figure 4.3 B). These results suggest that PARN does act on RMRP and U6 snRNA, and removes oligo(A) tails from the 3’ ends of these RNAs post-transcriptionally. However, we did not observe a decrease in the total percentage of reads terminating at the mature end for either RNA, in contrast to the effect of USB1 knockdown on U6 snRNA (Figure 4.3 C). Finally, we did not observe
98 any effect of PARN knockdown on the processing of the H1 RNA (<0.05% A-containing reads in both control and PARN knockdown), validating previous data on the lack of post-transcriptional oligo(A) addition on the H1 RNA.
Figure 4.3 PARN depletion increases the proportion of oligoadenylated reads for U6 and RMRP in HeLa cells. A) Percentage of oligoadenylated reads at different 3’ ends of U6 or RMRP in HeLa cells. Fraction of oligoadenylated reads at each end was calculated from the total number of reads at each end. B) Frequency distribution of oligo(A) tail length at the canonical 3’ end for RMRP. Percentage of reads for each oligo(A) tail was calculated from the total oligoadenylated reads at the canonical 3’ end. Average oligo(A) tail lengths were calculated from the weighted mean of each distribution. C) Percentage of total reads terminating at mature or extended ends for U6 or RMRP in HeLa cells. D) Representative northern blots for RMRP or U6 levels in PARN knockdown HeLa cells. Numbers represent normalized U6 or RMRP levels (Average +/- S.D.) for three biological replicates.
99 We then tested whether the lack of any effect of PARN knockdown on the percentage of reads terminating at the mature end for RMRP and U6 snRNA correlates with the steady state levels of these RNAs. As expected, PARN knockdown had no effect on the steady state levels of U6snRNA, and only a slight effect on the steady state levels of RMRP (~11% decrease compared to control) (Figure 4.3 D).
Together with the increase in the fraction of oligoadenylated reads for these
RNAs upon PARN depletion, two possible conclusions can be reached. First, PARN acts to promote the stability of only a subpopulation of these RNAs, and therefore, the effect on steady state levels is not significant. This could be mediated by different subcellular localization of fractions of these ncRNAs during their biogenesis or trafficking. Second, PARN deadenylates the majority of these RNA populations, but the lack of PARN depletion is not sufficient to trigger the decay of these RNAs in a 3’-5’ manner. This could possibly be due to the presence of protective protein complexes, like the Lsm 2-8 complex for U6 snRNA, or the Rpp20-Rpp25 complex for RMRP, which associate stably with these ncRNAs and mask the 3’ end from targeted degradation
(Achsel et al., 1999; Mattijssen et al., 2010).
PARN and EXOSC10 both regulate the stability of human Y RNAs
Since PARN is involved in the deadenylation of U6 and MRP RNAs, we asked whether other abundant Pol III transcribed RNAs in the cell are also targets for PARN’s activity. We chose the human Y RNAs (also referred to as hY RNAs), Y1, Y3, Y4 and
Y5 (in decreasing order of length), which are small Pol III transcribed RNAs 83-112 nt in length (Hendrick et al., 1981). The exact function of these abundant RNAs in the cell in unclear; however, they have been suggested to play a role in quality control of
100 structured RNAs, initiation of DNA replication, and maturation of histone mRNAs
(Christov et al., 2006; Gardiner et al., 2009; Köhn et al., 2015; Wolin et al., 2014). Even less is known about the quality control mechanism for Y RNAs.
We found that in PARN depleted HeLa cells, Y RNA levels decreased non- uniformly (Figure 4.4 A). Y1 and Y3 were the most affected, and their levels decreased by ~60% and ~42% respectively. Y5 levels decreased by ~36%, while Y4 was the least affected, with ~21% decrease in its levels. Differential effect of PARN knockdown on Y
RNAs could be due to differences in cellular localization, as well as the differences in ribonucleoproteins formed by the different Y RNAs (Hogg and Collins, 2007).
Interestingly, we found that Y RNA levels also decreased in EXOSC10 knockdown cells, which is in contrast to what we previously saw for hTR, where hTR steady state levels increased upon EXOSC10 depletion (Shukla et al., 2016) (Figure 4.4
A). This suggests that EXOSC10 plays a protective role in Y RNA biogenesis, in contrast to what was observed for hTR.
A co-knockdown of PARN and EXOSC10 led to slightly lower levels of some Y
RNAs compared to PARN knockdown alone (Figure 4.4 A). This suggests that PARN and EXOSC10 are involved in the same pathway of Y RNA maturation. Further, this also suggests that PARN and EXOSC10 have overlapping functions in this pathway, potentially removing post-transcriptionally added nucleotides from the 3’ ends of Y
RNAs.
Since PARN deadenylates 3’ ends of ncRNAs, and EXOSC10 can also recognize its substrates through oligo(A) tails on their 3’ ends, absence of either or both of these enzymes could lead to oligoadenylated species that are substrates for
101 degradation by an unknown exonuclease. Therefore, we investigated whether prevention of Y RNA oligoadenylation by a knockdown of PAPD5 could rescue Y RNA levels upon PARN or EXOSC10 knockdown. We found that PAPD5 co-knockdown with
PARN rescued all Y RNA levels essentially to wild type levels compared to PARN knockdown alone (Figure 4.4 B). PARN and EXOSC10 co-knockdown only showed a modest increase in Y1 and Y3 RNA levels compared to PARN knockdown alone (Figure
4.4 C). However, Y4 (which is the least affected by EXOSC10 knockdown) and Y5 RNA levels were rescued to control levels compared to EXOSC10 knockdown alone (Figure
4.4 C). This suggests that Y RNAs are adenylated by PAPD5 and are substrates for degradation by a 3’ to 5’ exonuclease.
102
Figure 4.4 PARN or EXOSC10 knockdown reduces Y RNA levels in HeLa cells. A) Representative northern blot for Y RNA levels in PARN, EXOSC10 or PARN & EXOSC10 co-knockdown in HeLa cells. Histogram represents quantification of normalized Y RNA levels in individual knockdown conditions (Average+/-S.D.) for four biological replicates. B and C) Representative northern blot for Y RNA levels in
103 PARN and PAPD5 or EXOSC10 and PAPD5 co-knockdown in HeLa cells. Numbers represent quantification of normalized Y RNA levels (Average+/-S.D.) for four biological replicates.
PARN and EXOSC10 regulate the maturation of Y RNAs in a PAPD5-dependent manner
PARN and EXOSC10 could play a role in the maturation of Y RNAs, or they could be involved in the removal of post-transcriptional modifications from its 3’ ends. In order to differentiate between these two possibilities, we deep sequenced the 3’ ends of these RNAs in HeLa cells. This analysis revealed several interesting insights into the processing of Y RNAs. First, the most abundant 3’ end of Y RNAs in these cells is actually five bases upstream (-5 A) of the canonical 3’ end described previously (31% and 38% of total reads for Y1 and Y3 RNAs respectively) (Figure 4.5 A, B) (Wolin and
Steitz, 1983). The next most abundant end is the -4 G end, whereas the canonical end
(0 U) represents ~2% of total reads (Figure 4.5 B). While previous studies identified the sequence of Y RNAs based on biochemical purification and hybridization to genomic
DNA, our deep sequencing of 3’ ends identified the precise location and relative abundance of each 3’ end in HeLa cells. We conclude that mature Y RNAs in human cells exist as trimmed species at their 3’ ends.
The stem in Y RNA secondary structure is formed through the base pairing of its
5’ and 3’ ends (Figure 4.5 A). Since the 3’ end is trimmed to an upstream end, it is possible that the 5’ end is also trimmed to a corresponding position in order to preserve the stem structure. However, our analysis is insufficient to answer this question.
Second, we observed that while PARN and EXOSC10 knockdown alone or together led to a decrease in the fraction of reads terminating at the abundant -5 A and -
104 4 G positions. However, the reduction was modest upon PARN and EXOSC10 co- knockdown (38% to 35% at -5 A and 20% to 16% at -4 G for Y3 RNA), suggesting that other enzymes might be involved in the trimming of Y RNAs to the abundant end. At the same time, knockdown of PARN and EXSOC10 led to an increase in the fraction of reads terminating from -3 position onwards for both Y1 and Y3, and led to an ~1.5-2x increase in the abundance of reads terminating at the canonical 3’ end at the 0 U position (Figure 4.5 C, D). We also observed an increase in the fraction of reads terminating at the +1 U and +2 U position upon PARN and EXOSC10 knockdown
(Figure 4.5 C, D). Together, this trend suggests that both PARN and EXOSC10 are involved in the trimming Y RNAs to the abundant -5 A end (Figure 4.4 A). However, we cannot rule out the role of other 3’ to 5’ exonucleases in this process.
105
Figure 4.5 PARN and EXOSC10 process Y RNAs to a truncated 3’ end in PAPD5 dependent manner. A) Representative secondary structures for Y1 and Y3 RNA in human cells. ‘-5’ and ‘0’ depicts abundant and canonical 3’ end respectively. B) Percentage of total reads at each position for Y1 and Y3 RNAs in HeLa cells. >30% of total reads end at the ‘-5’ position for both Y1 and Y3 RNAs. C and D) Percentage of total reads at canonical and precursor ends increase upon PARN or EXOSC10 knockdown. E) Percentage of total reads decrease at the ‘-5’ end for Y1 and Y3 RNAs upon PAPD5 knockdown along with PARN or EXOSC10 knockdown. F) Percentage of total reads increase at the canonical ‘0’ end upon PAPD5 co-knockdown along with PARN or EXOSC10.
106 Third, we observed that PAPD5 co-knockdown along with PARN or EXOSC10 led to a strong decrease in the levels of reads terminating at the abundant -5 A end, and a strong increase (>2x) in the levels of the reads terminating at the canonical 0 U end
(Figure 4.5 E, F). Together with the rescue of Y RNA levels upon PAPD5 and PARN or
PAPD5 and EXOSC10 co-knockdown, this suggests that at least for a subpopulation of
Y RNAs, PAPD5-mediated adenylation is required to make the 3’ end of the RNA accessible to 3’ to 5’ exonucleases that can trim the RNA to the abundant end at -5 position. One possibility is that PARN and EXOSC10 work as a complex to trim Y RNAs to the -5 A position, with PARN removing genomic encoded adenosines and EXOSC10 removing all other nucleotides. -5 position would be a boundary defined by the presence of a protein, most likely the Ro protein, preventing further cleavage of the RNA. In the absence of PARN or EXOSC10, other 3’ to 5’ nucleases recognize the post- transcriptionally added A’s, and degrade the RNA resulting in lower steady state levels.
Together, these data suggest that PARN and EXOSC10 regulate the levels of Y
RNAs in HeLa cells by processing it to a shorter form in conjunction with 3’ end oligoadenylation by PAPD5.
DIS3L is involved in the degradation of Y RNAs
In order to identify the 3’ to 5’ exonuclease responsible for degradation of Y
RNAs upon PARN or EXOSC10 knockdown, we performed a knockdown of various 3’ to 5’ exonucleases in HeLa cells. We specifically knocked down DIS3, which is the catalytic component of the exosome possessing both 3’ to 5’ exo- and endonucleolytic activities (Schmid and Jensen, 2008). We also knocked down DIS3L, which is a DIS3- like exonuclease believed to interact with the exosome and degrades RNAs carrying
107 oligoadenylated 3’ ends (Staals et al., 2010; Tomecki et al., 2010), and DIS3L2, which is a second cytoplasmic 3’ to 5’ exonuclease that preferentially degrades oligouridylated
RNAs independent of the exosome (Faehnle et al., 2014; Lubas et al., 2013; Malecki et al., 2013).
We found that DIS3L knockdown led to an approximate two-fold increase in the levels of Y1 and Y3 RNAs in HeLa cells (Figure 4.6 A). In contrast, DIS3 knockdown led to a decrease in Y RNAs levels (~30% for Y1 and ~20% for Y3), and DIS3L2 knockdown had no significant effect on Y RNA levels. This is in contrast to recent reports that suggest that DIS3L2 targets 3’ uridylated Y RNAs for degradation (Pirouz et al., 2016; Łabno et al., 2016). Our deep sequencing of Y1 and Y3 3’ ends suggests that the proportion of uridylated reads is very small in HeLa cells, so we cannot rule out a cell line-specific effect of DIS3L2 on Y RNAs. This suggests that DIS3L is the primary enzyme responsible for the degradation of Y RNAs in human cells, possibly through its recognition of oligo(A) tails at the 3’ end. Further, the effect of DIS3 knockdown on Y
RNA levels suggests that DIS3 and EXOSC10 could have a redundant role in the stabilization of Y RNAs in the nucleus (Figure 4.6 B).
108
Figure 4.6 DIS3 and DIS3L exert contrasting effect on Y RNA levels in HeLa cells. A) Representative northern blot for Y1 and Y3 RNA in HeLa cells depleted of DIS3, DIS3L or DIS3L2. Numbers represent normalized Y1 and Y3 RNA levels (Average+/-S.D.) for three biological replicates. B) Model for the regulation of Y RNA processing and stability by various 3’ to 5’ exonucleases. Full length Y RNAs are adenylated by PAPD5, and the oligoadenylated species can undergo trimming by PARN, EXSOC10, and possibly DIS3, or can be degraded by DIS3. The trimmed Y RNAs can also get adenylated by PAPD5, and the oligoadenylated species can be stabilized by PARN/EXOSC10/DIS3, or can get degraded by DIS3L. We suggest that PARN, DIS3 and EXOSC10 might all have specific roles in this pathway, since a deficiency of either of these RNAs can reduce Y RNA levels in human cells.
109 Discussion
USB1 deficiency leads to U6 destabilization and degradation by PAPD5/EXOSC10
How USB1 mutations lead to PN and DC, and moreover, which RNA substrates are affected by USB1 deficiency, is not well understood. A previous study from PN patient cells suggests that U6 snRNA is oligoadenylated at its 3’ end in these cells
(Hilcenko et al., 2013). We show that U6 snRNA is destabilized upon USB1 knockdown in HeLa cells (Figure 4.1). An analysis of U6 snRNA ends upon USB1 knockdown suggests that the population of U6 snRNA that remains upon USB1 knockdown is stabilized by the Lsm2-8 complex. In support of this argument, a co-knockdown of Lsm8 and USB1 leads to a much stronger reduction in the levels of U6 snRNA, even stronger than Lsm8 knockdown alone (Figure 4.2).
Post-transcriptional modifications to the 3’ end of U6 snRNA in the absence of
Lsm 2-8 complex or USB1 could lead to its degradation. We show that the decrease in
U6 snRNA levels is due to oligoadenylation of its 3’ end by PAPD5, followed by degradation by EXOSC10 (Figure 4.2). PAPD5 knockdown rescues U6 snRNA levels upon USB1 co-knockdown. Finally, EXOSC10 knockdown rescues U6 snRNA levels to wild type upon USB1 knockdown alone, or in conjunction with Lsm8 knockdown (Figure
4.2). Together, these results argue that USB1 and EXOSC10 compete for U6 snRNP assembly with the Lsm 2-8 complex, and prevention of U6 snRNA oligoadenylation could be a potential therapeutic strategy for PN.
Interestingly, some forms of cancers are caused by an overexpression of the
Lsm1 protein (Fraser et al., 2005; Little et al., 2016; Schweinfest et al., 1997). The Lsm1 protein is part of the Lsm 1-7 complex, and plays an important role in the regulation of
110 mRNA decapping and degradation in eukaryotic cells (Bouveret et al., 2000; Tharun et al., 2000; Tharun and Parker, 2001). A yeast model of Lsm1 overexpression suggests that Lsm1 overexpression titrates Lsm 2-7 proteins away from the Lsm 2-8 complex, resulting in a destabilization of U6 snRNA and leads to splicing aberrations (Luhtala and
Parker, 2009). It is possible that Lsm1 overexpression exerts its oncogenic effect through downregulation of the U6 snRNA in these forms of cancer. Further studies are warranted to establish if this is the case, and whether rescue of U6 snRNA levels can rescue the cancer phenotype, providing a route to therapy.
PARN’s possible role in regulating the stability of multiple ncRNAs
PARN is mutated in a severe form of DC and familial pulmonary fibrosis (Dhanraj et al., 2015; Stuart et al., 2015). We along with others have shown that PARN stabilizes hTR by removing oligo(A) tails from its 3’ end. However, it is possible that the severe phenotype of DC observed in patients with PARN mutations is due to the misregulation of other RNAs. We investigated a few stable non-coding RNAs to test this hypothesis, and found that PARN knockdown leads to an increase in oligoadenylated ends for a number of ncRNAs, such as U6 snRNA and RMRP (Figure 4.3). However, PARN knockdown does not affect the steady state levels of either of these RNAs in HeLa cells
(Figure 4.3).
PARN can affect the processing of ncRNAs by two different mechanisms (Figure
4.7). For some ncRNAs, PARN competes with PAPD5 to limit the addition of oligo(A) tails on the 3’ end. When PARN is limiting, oligo(A) tails are recognized by a 3’ to 5’ exonuclease, for example, EXOSC10 in the case of hTR, which leads to the degradation of the RNA (Figure 4.7 A). For other ncRNAs, PARN competes with PAPD5
111 to limit the addition of oligo(A) tails on the 3’ end, but the 3’ end is well protected by a protein complex, which prevents RNA degradation even in the case of low PARN levels
(Figure 4.7 B). This would hold true for RMRP and U6 snRNA, as well as H/ACA snoRNAs described previously (Berndt et al., 2012). One aspect of this process is that
RNA turnover would simply require dissociation of the protective protein complex from the 3’ end, and therefore, could be used by the cell to regulate the levels of ncRNAs in a
PARN dependent manner (see below).
112
Figure 4.7 Two modes of PARN-mediated 3’ end maturation of ncRNAs. A) PARN competes with PAPD5 to limit the addition of oligo(A) tails to the 3’ end of the RNA, and conditions where PARN is limiting leads to the degradation of the RNA through recognition of the oligo(A) tails, as is the case for hTR degradation by EXOSC10. B) PARN removes oligo(A) tails from the 3’ end of the RNA, but the pre- assembled RNP is stabilized through the presence of protein partners at the end that block exonucleolytic degradation.
113 One interesting possibility is that PARN acts a general regulator of ncRNA stability in mammalian cells. PARN could exert its effect through two general mechanisms. First, programmed cellular pathways could downregulate or upregulate the expression of PARN in cells, depending on response to stimuli at the cellular level, or to cell stages during growth and development. Second, the proteins at the 3’ end of ncRNAs, which presumably protect them from destabilization by PARN knockdown (as is the case for U6 or RMRP), could themselves be downregulated by the cell, which would sensitize them to the activity of PARN. PARN-mediated RNA decay (PMD) could therefore be a widespread cellular phenomenon to establish homeostasis in cellular ncRNA (and mRNA) levels, and further research is warranted to test this hypothesis.
Y RNAs are processed by PARN and EXOSC10 in human cells
Y RNAs are abundant RNA pol III transcribed ncRNAs in human cells, and are overexpressed in certain types of cancers (Kowalski and Krude, 2015; Köhn et al.,
2013). Therefore, an understanding of the mechanisms that regulate Y RNA stability in human cells could have potential therapeutic benefits. We found that Y RNA stability is regulated by a complicated process comprised of multiple 3’ to 5’ exonucleases. Y RNA levels decrease upon both PARN and EXOSC10 knockdown in HeLa cells (Figure 4.4
A). Further, Y RNA levels could be rescued partially or completely in each condition upon PAPD5 knockdown, providing a direct evidence for 3’ end oligoadenylation being a destabilizing mechanism for Y RNAs (Figure 4.4 B, C). Interestingly, DIS3 knockdown also affects Y RNA levels in HeLa cells, albeit the effect is not as strong as EXOSC10 knockdown for Y1 and Y3 RNAs (Figure 6A). DIS3 associates with the exosome in both the nucleus and the cytoplasm (Staals et al., 2010; Tomecki et al., 2010), which
114 suggests that EXOSC10 and DIS3 could have overlapping functions in the trimming of
Y RNAs to the abundant -5 end in conjunction with PARN. Analysis of Y RNA levels in
HeLa cells depleted of two other 3’ to 5’ exonucleases, DIS3L and DIS3L2, suggests that DIS3L might be responsible for degrading Y RNAs normally, or when PARN or
EXOSC10/DIS3 enzymes are limiting in the cell.
How do these different nucleases co-regulate the maturation and stability of Y
RNAs in the cell? Differential subcellular localization of Y RNAs, as well as of
EXOSC10, DIS3, DIS3L and PARN in human cells provides some clues to this question. Human Y RNAs localize to both the nucleus and the cytoplasm, and the nuclear localization is observed at discrete puncta called perinucleolar compartments
(PNCs) (Farris et al., 1997; Kowalski and Krude, 2015; Matera et al., 1995). DIS3 and
PARN both shuttle between the nucleus and the cytoplasm, whereas as EXOSC10 is predominantly localized to the nucleus in the cell (Gao et al., 2000; Körner and Wahle,
1997; Staals et al., 2010; Tomecki et al., 2010). DIS3L and DIS3L2 are both predominantly cytoplasmic enzymes, although DIS3L is also found at discrete sites in the nucleus (Lubas et al., 2013; Malecki et al., 2013; Staals et al., 2010; Tomecki et al.,
2010). Therefore, Y RNAs can be susceptible to the activity of these nucleases at different stages of its life cycle, based on its localization and interaction with different protein partners. For example, Y RNAs could be trimmed to the abundant -5 end by
PARN and EXOSC10 post-transcription in the nucleus, aided by oligoadenylation by
PAPD5 (Fouraux et al., 2002; Gendron et al., 2001; Sim et al., 2009). If PARN or
EXOSC10/DIS3 are absent, the RNA could be acted upon by DIS3L, which could recognize the oligo(A) tails at its 3’ ends for degradation (Figure 4.6 B). Y RNAs could
115 also be degraded in the cytoplasm by DIS3L post-nuclear export, which could be a part of the normal recycling of the Y RNAs in human cells.
An important point here is that PARN, EXOSC10 and DIS3 potentially have specific roles in the process of Y RNA maturation, since a knockdown of any one of these enzymes leads to a reduction in Y RNA levels, which would not be expected if these enzymes had redundant roles in this process.
Y RNA deficiency could lead to the severe phenotype of DC observed in patients with PARN mutations
The severe phenotype of DC observed due to PARN mutations is intriguing, not the least because of severely short telomere lengths and earlier onset compared to mutations in the telomerase components like DKC1 and TERC (Mason and Bessler,
2011; Stuart et al., 2015; Tummala et al., 2015). Two previously published reports suggest that defects in Y RNA maturation could contribute to this severe phenotype.
First, PARN patient cells have a defective response to UV irradiation stress compared to controls (Tummala et al., 2015). Y RNAs, in complex with the Ro protein, relocate to the nucleus upon UV stress as a part of the cell’s DNA damage response mechanism, which is important in adaptation to UV stress (X. Chen et al., 2000; 2003).
Therefore, PARN deficiency could negatively impact the cell’s DNA damage response mechanism.
Second, PARN patient cells arrest in the G0/G1 cell cycle phase (Dhanraj et al.,
2015). Y RNAs have been shown to be important for the initiation of DNA replication in mammalian cells, and Y RNA knockdown arrests cells in late G1 phase (Christov et al.,
2006; Gardiner et al., 2009; Krude et al., 2009; I. Wang et al., 2014). Interestingly, this
116 function of Y RNAs is independent of its binding to the Ro protein, which suggests that newly transcribed Y RNAs in the nucleus could be important for this process (Gardiner et al., 2009). Therefore, lack of proper 3’ end processing of Y RNAs could impact their function upstream of interaction with Ro protein, which would be a likely scenario in
PARN or EXOSC10 deficient cells. Analysis of Y RNA levels and maturation in PARN patient cells would be important in establishing the causality between Y RNA function and the DC phenotype.
117 Experimental methods
Cell culture
HeLa cells purchased from ATCC were cultured in Dulbecco’s Modified Eagle’s
Medium (DMEM), supplemented with 10% Fetal Bovine Serum (FBS), 1x Glutamax,
Penicillin/Streptomycin and Normocin. Cells were regularly checked for mycoplasma contamination.
RNA interference in HeLa cells
siRNAs targeting USB1, PAPD5, PARN, DIS3, DIS3L and DIS3L2were purchased from Dharmacon (On-target plus Smart pool formulation). siRNAs targeting
EXOSC10 were purchased from Qiagen (pool of four siRNAs). Allstars negative control siRNA from Qiagen was used as negative control. Approximately 150,000 cells were seeded per well in a six-well plate for transfections. Transfections were carried out 24 hours after seeding with Interferin reagent as per manufacturer’s instructions. siRNA concentrations were limited to 5nM for each siRNA, except for Lsm8, where 0.5nM final concentration was used. Cells were harvested 48 to 60 hours post-transfection.
Northern analysis of RNAs
RNA extraction was carried out using the Quick RNA miniprep kit from Zymo
Research. Approximately 5 µg of total RNA was separated on a 8% Polyacrylamide gel, and transferred to a nylon membrane (Nytran). Blots were probed with 32P-labeled probes, and imaged on a Typhoon FLA 9500 phosphoimager. Probes used for specific
RNAs are as follows: U6- ATATGGAACGCTTCACGAATTTGC; RMRP-
AGCCGCGCTGAGAATGAGCCCCGTGT; Y1-
GAACAAGGAGTTCGATCTGTAACTGACTG; Y3- CACCACTGCACTCGGACCAGCC;
118 Y4- GATAACCCACTACCATCGGACCAGCC; Y5- GGGGAGACAATGTTAAATCAAC.
Probes for hTR and 5s rRNA have been described previously (Shukla et al., 2016).
Northern blots were quantified on Image Quant 5.2, and intensities were normalized to the loading control.
3’ end deep sequencing of RNAs
Libraries for individual RNAs were prepared as previously described (Goldfarb and Cech, 2013; Shukla et al., 2016). Briefly, 5 µg of total RNA was Ribozero treated to deplete ribosomal RNAs. RNA was then dephosphorylated using rAPid alkaline phosphatase (Roche), and ligated to two different 3’ appendices. cDNA was prepared from the ligated RNA using Superscript III RT, and selected cDNA was amplified using barcoded forward primers through 3’ RACE. RACE products corresponding to 100-500 nt in length were purified on a 1% agarose gel, and libraries were amplified using universal Illumina primers. The libraries were analyzed on bioanalyzer and quantified on
Qubit, and were sequenced on an Illumina Miseq desktop sequencer as previously described (Goldfarb and Cech, 2013).
An excess of 500,000 reads was obtained from each library. Reads of interest were selected using barcodes in the forward primer of 3’ RACE and the appendix, and analyzed for information regarding the nature of the 3’ end and the number of reads under each condition. For determination of canonical ends, sequences were mapped to the reference RNA sequence deposited in the NCBI database.
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