N6-methyladenosine (m6A) and 5-methylcytosine (m5C). We will introduce writers, readers, and erasers of these modifications, and we will present methods for their detection. Finally, we will provide insights into the distribution and function of these chemical modifications in selected, cancer-related lncRNAs.The broad application of next-generation sequencing technologies in conjunction with improved bioinformatics has helped to illuminate the complexity of the transcriptome, both in terms of quantity and variety. In humans, 70–90% of the genome is transcribed, but only ~2% carries the blueprint for proteins. Hence, there is a huge class of non-translated transcripts, called long non-coding RNAs (lncRNAs), which have received much attention in the past decade. Several studies have shown that lncRNAs are involved in a plethora of cellular signaling pathways and actively regulate gene expression via a broad selection of molecular mechanisms. Only recently, sequencing-based, transcriptome-wide studies have characterized different types of post-transcriptional chemical modifications of RNAs. These modifications have been shown to affect the fate of RNA and further expand the variety of the transcriptome. However, our understanding of their biological function, especially in the context of lncRNAs, is still in its infancy. In this review, we will focus on three epitranscriptomic marks, namely pseudouridine (Ψ),  Non-genomically encoded modifications of macromolecules, ranging further than simple changes in the sequence of the single building blocks, play important roles in nearly all cellular processes. The need to regulate activities and abundances of working components led to mechanisms involving several layers of control. For example, post-translational modifications of proteins, like phosphorylation, acetylation, ubiquitination, glycosylation and methylation are well-known modifications that control the fate of proteins .The first modified nucleotide in DNA was discovered in 1948 . In the In contrast to DNA and proteins, RNA was neglected for a long time and thought to be just an intermediary component on the way from the information stored inside the DNA double helix to the readily synthesized proteins that are to fulfill all important tasks inside the cell. This view changed in the 1980s, when catalytic functions of RNA molecules were brought to light . Only thNcRNAs are somewhat arbitrarily divided into two classes depending on their size: (1) small ncRNAs (<200 nucleotides (nt)); and (2) long ncRNAs (lncRNAs). Multiple types of small ncRNA (microRNAs (miRNAs), small interfering RNAs (siRNAs) and PIWI-interacting RNAs (piRNAs)) have been studied extensively, especially their role in development and carcinogenesis ,11,12,13The group of long ncRNAs is highly heterogeneous and its members have an extensive variability in their cellular effects as well as their molecular influences. They are characterized by the lack of a functional open reading frame, meaning they encompass less than 100 amino acids ,15,16,17In 1951, pseudouridine (Ψ), the first modification of a RNA base, was discovered , only shFor years, research on RNA modifications focused mainly on transfer RNAs (tRNAs) as a result of their relative abundance and their small size, with ribosomal RNA (rRNA) following after technological advances in sequencing methodology were made ,34,35,36N6-methyladenosine (m6A) and 5-methylcytosine (m5C) , ne (m5C) . After dPost-transcriptional modifications of RNA molecules have been known for nearly 70 years and about 150 epitranscriptomic marks have been described in the last decades. Chromatographic methods were used in early studies and they are still a very valuable tool for detection today. They remain the gold standard, especially for quantification of RNA modifications. However, reliable transcriptome-wide mapping of the most prevalent alterations with the help of next-generation sequencing technology is the ultimate goal today.N6-methyladenosine (m6A) and 5-methylcytosine (m5C), their interacting proteins and connections to disease states. Moreover, we will introduce current high-throughput detection methods of the aforementioned modifications and briefly discuss their benefits and limitations. In In this paragraph, we will briefly summarize our current knowledge about the three most widespread RNA modifications, namely, pseudouridine (Ψ), Overall, 5-ribosyluracil  is the most abundant RNA modification, first described in 1951 and found in several classes of RNA, i.e., tRNA, rRNA, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), mRNA and ncRNA . It is aIncorporated Ψ nucleosides enhance RNA’s ability for base stacking and make the sugar-phosphate backbone more rigid ,75. Ψ enIn humans, 13 proteins have been identified that contain a pseudouridine synthase domain. These so called pseudouridine synthases (PUS) fall into one of two categories: RNA-dependent or RNA-independent. PUS from the first category rely on other small RNAs that guide these enzymes to their respective target RNAs. In contrast, PUS from the latter category can fulfill their catalytic duty without these adaptor RNAs. Dyskerin, for example, associates with H/ACA snoRNAs, while PUS1 belongs to the snoRNA-independent group .Very recently, it was shown that TruB pseudouridine synthase family member 1 (TRUB1), which is also known as PUS4, and PUS7 combine for about 60% of all reproducibly detected Ψ sites in mRNA . MoreoveUntil today, specific reader or eraser proteins for Ψ have not been found. The reason for the absence of an eraser protein could be the fact that the formed C–C bond between the base and the sugar (Ψ) is significantly more inert than the C–N bond (uridine). The Ψ formation could, therefore, be irreversible . Hence, N-cyclohexyl-N′-(2-morpholinoethyl)carbodiimide metho-p-toluenesulfonate (CMCT) and the downstream application of next-generation sequencing [High-throughput and site-specific mapping of Ψ in RNA relies on the unique reaction of Ψ with quencing ,84. Pseuquencing ,85,86. EA related, yet more sensitive method, called CeU-Seq, was recently developed . Here, a6A detection section below.Next to these sequencing-based methods, alternative strategies have been introduced or are currently under development to map pseudouridine in RNA. For example, site-specific cleavage and radioactive-labeling followed by ligation-assisted extraction and thin-layer chromatography (SCARLET) is a low-throughput method to validate different RNA base modifications, e.g., Ψ, and to determine the stoichiometry at individual nucleotide positions ,88. SCARAnalyzing Ψ modifications in RNA by mass spectrometry is another, rather challenging approach, because there is no mass difference between uridine and Ψ . AccordiN6-methyladenosine (m6A) was first discovered in 1974 [6A occurs: RRACH [6A in mRNA is not random, but follows a certain pattern; it is often located near stop codons and in the 3′-untranslated region (UTR) suggesting a regulatory role in cellular processes [6A modifications have been shown to play important roles in RNA stability (mRNA and ncRNA) [6A in the UV-induced DNA damage response pathways was reported [6A in mRNA are highly dynamic and the modification is reversible. In fact, several m6A writer, reader, and eraser proteins have been identified [6A modifications serve important functions and might be involved in cell signaling networks. in 1974 ,92. It i in 1974 . There as: RRACH ,95 and Ds: RRACH   ,98, mRNAd ncRNA) ,99,100, d ncRNA) ,101,102,d ncRNA) ,103 as wd ncRNA) ,104. Verreported . Importaentified ,97,106. 6A formation is catalyzed inside the nucleus by the m6A writer complex, which consists of the enzymatically active methyltransferase-like 3 (METTL3) protein and several interacting proteins [6A methyltransferase associated (VIRMA); (d) RNA-binding motif protein 15 (RBM15), and; (e) RBM15B. METTL3 possesses a catalytically active methyltransferase domain and it is the principal m6A forming enzyme in polyadenylated mRNA, but it does not methylate rRNA [6A writer complex. Knockdown of METTL3 or METTL4 in glioblastoma stem-like cells (GSCs) dramatically increased their growth and self-renewal. In addition, this depletion substantially increased GSC-initiated tumor progression [The mproteins . Known iate rRNA . METTL14ate rRNA . It bindate rRNA ,109. Hengression .WTAP is a crucial component of the writer complex ,51. One 6A abundance in RNA [KIAA1429 is associated with the writer complex and its depletion led to a decrease in me in RNA . HoweverX-inactive specific transcript (XIST), for instance, is a target of RBM15/15B directed methylation [RBM15 and its paralog RBM15B are components of the methyltransferase complex and they interact with METTL3 in a WTAP-dependent manner ,54. RBM16A writer complex surrounding METTL3 [S-Adenosyl methionine (SAM) homeostasis by differentially methylating a hairpin structure inside the methionine adenosyltransferase 2A (MAT2A) mRNA thereby modulating alternative splicing [Recently, METTL16 was described as a methyltransferase fulfilling its functions independently of the mg METTL3 . It is asplicing .6A modifications in RNA transcripts are predominantly read by the eukaryotic initiation factor 3 (eIF3) or by proteins that contain a YTH (YT521-B homology) domain. There are additional RNA-binding proteins (RBPs) associating with m6A, which are not seen as classical m6A binders.The m6A reader proteins [DF1, DF2 and DF3 belong to the YT521-B homology domain family (YTHDF) and represent one group of cytoplasmic mproteins . DF1 is proteins ,99. Addiproteins .6A reader proteins are YTH domain-containing proteins (YTHDCs). YTHDC1 is a nuclear enriched protein that binds to protein-coding and non-coding transcripts. It is the major reader of nuclear m6A modifications [XIST and was characterized as a regulator of mRNA splicing events [6A sites in ncRNAs [A second group of mications . YTHDC1 g events ,103. YTHn ncRNAs . Tanabe n ncRNAs .6A binding protein is eIF3. In fact, adenosine methylation is a major mechanism by which eIF3 is recruited to mRNAs. After binding to m6A in the 5′-UTR, translation is initiated by eIF3 in a 5′-cap- and eukaryotic initiation factor 4E (eIF4E)-independent manner [6A modifications in 5′-UTRs of mRNAs when eIF4-dependent initiation is hindered by specific cell states.Another important mt manner . These f6A after changes in local and secondary structure of mRNA and lncRNA [6A-containing transcripts has been shown to affect alternative splicing as well as miRNA biogenesis [6A modifications, and loss of m6A methylation enhances HuR binding, which increases target RNA stability [Finally, heterogeneous nuclear ribonucleoprotein C (hnRNP C) and hnRNP A2/B1 belong to the group of proteins with reported binding to md lncRNA . Bindingogenesis ,61. Intetability . FurtherAlkbh5-deficient mice show defects in spermatogenesis, but are otherwise viable indicating that Alkbh5 demethylase activity is not strictly required during development [6A transcripts seems to be crucial in certain cancers. For example, Zhang et al. could show that ALKBH5 protein levels are elevated in GSCs and its expression is a negative prognostic factor for glioblastoma (GBM) patients [FOXM1 transcripts which results in enhanced FOXM1 expression. Interestingly, FOXM1-AS, a nuclear lncRNA, facilitates the interaction between ALKBH5 and nascent FOXM1 transcripts. Depletion of ALKBH5 and FOXM1-AS disrupted GSC tumorigenesis through the FOXM1 axis [The nuclear α-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5) protein was recently identified as a RNA demethylating enzyme . Alkbh5-elopment . Redundapatients . FurtherXM1 axis . In addiXM1 axis .6A modifications in RNA [N6, 2′-O-dimethyladenosine (m6Am) modification, which was co-detected with m6A in previous studies [6A is not the preferred target for FTO in vivo and they concluded that FTO is the eraser protein for m6Am.Very recent publications spawned conflicting data concerning the fat mass- and obesity-associated protein (FTO), a member of the AlkB-related dioxygenase family, which was originally described as an eraser of ms in RNA . Recentl studies . Their r6A levels in GSCs treated with the FTO inhibitor MA2, which suppressed GSC-initiated tumorigenesis and prolonged the lifespan of GSC-engrafted mice [6A demethylase, plays a critical oncogenic role in AML [6A levels in specific mRNA transcripts [In contrast, other reports showed a substantial increase in mRNA mted mice . Anothere in AML . FTO is nscripts .6A mapping strategies were based on the immunoprecipitation of modified RNA molecules using m6A-specific antibodies coupled to the subsequent application of NGS technologies , because peaks can be broad and identification of a single modified adenosine residue can be difficult. The same is true for m6A residues that lie in close proximity to each other. Therefore, true identification of specific m6A residues on a transcriptome-wide level is not possible with m6A-seq or MeRIP-Seq. Another drawback of these methods is the specificity of the available antibodies. These recognize m6A as well as N6,2′-O-dimethyladenosine (m6Am), which both contain the 6-methyladenine base. Therefore, it is not possible to distinguish between the prevalent m6A and m6Am, which is found close to the 5′-cap of mRNAs [First high-throughput m. Here, of mRNAs .6A-seq, m6A individual-nucleotide-resolution cross-linking and immunoprecipitation (miCLIP) was developed [6A residues and subsequent cross-linking by UV light, to identify precise positions of m6A-modified residues in RNA at single-nucleotide resolution. After next-generation sequencing and bioinformatical analysis of consensus motifs, identification of the modified residues is easier than in previously used methods.To circumvent some of the problems that arise with MeRIP-Seq and meveloped . This me6A sequencing (PA-m6A-seq), was recently introduced [6A-seq combines the incorporation of a photoactivatable ribonucleoside, 4-thiouridine (4-SU), into RNA and the immunoprecipitation with a m6A-specific antibody. By crosslinking the antibody to the introduced nucleotide and the subsequent transition of U/T to C during reverse transcription-polymerase chain reaction (RT-PCR), it is possible to narrow the resulting peaks after next generation sequencing to about 23 nt, which makes m6A position calling easier.Another very similar method, called photo-crosslinking-assisted mtroduced . PA-m6A-6A-level and isoform-characterization sequencing (m6A-LAIC-seq) uses a RNA immunoprecipitation protocol with m6A-specific antibodies and spike-in RNAs as internal standards coupled with whole-transcriptome sequencing to gain quantitative information about m6A modifications in poly(A)+ RNA fractions [6A levels per gene, but not the methylation stoichiometry of a single modified nucleotide.The mractions . Using s6A sites at single-nucleotide resolution is site-specific cleavage and radioactive-labeling followed by ligation-assisted extraction and thin-layer chromatography (SCARLET) [6A, but can be applied to detect other RNA modifications as well, e.g., m5C and Ψ [One laborious, low-throughput method to confirm mSCARLET) . Moreove5C and Ψ .5C) occurs in tRNA, rRNA, mRNA and lncRNA [5C sites are found about 100 nt downstream of the translation initiation site and in the UTRs [5C writers are known. The seven members of the NOP2/SUN RNA methyltransferase family member (NSUN) family, constituting the first group, methylate tRNA , rRNA , mRNA (NSUN2), ncRNA (NSUN2) as well as mt-rRNA (NSUN4) and mt-tRNA (NSUN3), respectively [Nsun7 gene lead to sperm motility defects, and therefore subfertility or complete infertility in male mice [NSUN2 gene are linked with autosomal-recessive intellectual disability [NSUN2 have been detected in human cancers [5-methylcytosine , which was previously thought to methylate DNA [The second writer protein group for mlate DNA . Howeverlate DNA ,127. DNMlate DNA . Indeed,late DNA . Additiolate DNA . However5C eraser is still to be identified. Also, the functions of m5C are not well understood yet, although a recent study suggests a role for m5C in RNA transport [5C binding (reader) protein, which promotes selective mRNA export from the nucleus [Importantly, a mransport . The Aly nucleus .5C modifications in transcripts and the proteins involved in this pathway are important to control the fate and function of RNAs. A dysregulation of this system might contribute to pathophysiological states. Hence, a more detailed mapping of m5C modifications, as well as the discovery and functional analysis of m5C interacting proteins could contribute to a better understanding of the underlying molecular disease mechanisms.Taken together, these findings suggest that m5C is the most extensively studied base modification in DNA. Owing to the different chemical characteristics of DNA and RNA, the standard method of bisulfite treatment followed by sequencing had to be adapted to be used for m5C detection in RNA [5C modifications could be detected by this method, called Bisulfite-seq, in tRNA, mRNA and ncRNA at single nucleotide resolution [5C residues. Aside from the structure-related issue, sites with alternative modifications of cytosine can be misidentified as m5C sites, because those modified bases are usually resistant to bisulfite treatment as well. This is especially true for the closely related hm5C modification, which cannot be distinguished from m5C through Bisulfite-seq [5C-specific antibody or a control antibody, followed by library preparation and NGS. This protocol was applied to the RNA of the archaeon Sulfolobus solfataricus, which verified the Bisulfite-seq results [mn in RNA . Bisulfisolution . Howeverfite-seq . Therefofite-seq . Fragmen results .5C mapping method, called 5-Azacytidine–mediated RNA immunoprecipitation, or Aza-IP, takes advantage of the random incorporation of 5-Azacytosine into RNA during RNA synthesis inside the cell [5C-RMTs due to the covalent link formed between the examined methyltransferase and its substrate RNA, which allows stringent washing steps. The Aza-IP is concluded by RNA fragmentation, cDNA library construction, and NGS. Comparison of resulting reads between the samples with a control or a specific antibody allows mapping of m5C sites. Additionally, the modified cytosine residue is read as a guanosine instead of cytosine during sequencing. This facilitates a precise calling of the candidate modified nucleotide. Identification of direct targets of DNMT2 and NSUN2 could be achieved with this method.Another, indirect mthe cell ,134. Ove5C detection method called methylation iCLIP (miCLIP) [5C mapping followed. A high cytosine appearance at position +1 in the cDNA libraries corresponds to the first nucleotide of the sequence reads, which means that reverse transcription terminated at the cross-link site of the cytosine with its modifying protein. New mRNA and ncRNA transcripts  were identified as methylation targets, aside from confirming already known tRNA targets of NSUN2. Thus, identification of direct targets of NSUN2 can be achieved with single-nucleotide resolution using this protocol.Indeed, NSUN2-specific methylation sites have been previously identified using yet another m(miCLIP) . This me(miCLIP) , and absIn summary, we are just at the beginning of a long journey to fully comprehend the breadth, dynamics and molecular functions of RNA modifications in mammalian cells. Recently developed high-throughput mapping approaches will enable us to characterize the epitranscriptome in diverse cellular contexts. Nevertheless, further technological improvements are needed to enhance the resolution and sensitivity of these methods. The discovery of additional writers, readers and erasers of the epitranscriptome, as well as a detailed analysis of already known ones, will spawn new research directions and might open the door for novel therapeutic strategies.Initial studies showed that RNA modifications have an impact on transcript localization, turnover and translation rates, thereby adding a new layer of gene expression control. However, most studies focused on mRNAs and much less is known about the functional relevance of RNA modifications in lncRNAs. Importantly, recent transcriptome-wide mapping studies revealed an overwhelming amount of RNA modifications in thousands of lncRNAs . Here, wMALAT1), also known as NEAT2 (nuclear-enriched abundant transcript 2), is a highly conserved and extremely abundant long non-coding RNA of ~8 kb in size that localizes to nuclear speckles [Transcribed from chromosome 11 through RNA Pol II the metastasis associated lung adenocarcinoma transcript 1  that either did or did not metastasize [MALAT1 as a master regulator of metastasis and a potential therapeutic target [MALAT1 has been found to control proliferation, migration and apoptosis in many different human cancers, e.g., pancreatic cancer, hepatoma and ovarian cancer [Originally, astasize . Follow-c target ,142. Furn cancer ,145,146.n cancer .MALAT1 is thought to fulfill its cellular functions by regulating gene expression levels as well as alternative splicing [MALAT1 undergoes a maturation process that yields a mature and stable transcript [MALAT1 is cleaved by RNase P at position A6690 that follows after an adenosine-rich tract. This produces two ncRNAs: a long, 5′-capped MALAT1 transcript with a short poly(A)-tail like moiety and a small, tRNA-like ncRNA, the so called MALAT1-associated small cytoplasmic RNA (mascRNA) [MALAT1 transcript remains in the nucleus, the mature 61-nt mascRNA is exported to the cytoplasm where it might act as an immune regulator [MALAT1 transcripts contain a 3′-triple-helical RNA stability element consisting of a U-rich internal loop that associates with a downstream A-rich tract to protect the MALAT1 transcript from degradation. This triple helix is recognized and bound by the m6A writer METTL16 [6A modification being present in this triple-helix. Alternatively, MALAT1 could serve a role as a regulator of RNA processing or modification events through guiding METTL16 onto its RNA targets.Mechanistically, splicing ,148,149.anscript . Here, tmascRNA) . While tegulator . Importa METTL16 . This raMALAT1 can carry m6A modifications [6A status of MALAT1 in different cell lines focusing on the largest m6A/MeRIP-Seq peak previously identified [6A-consensus motifs (RRACH), and four of these consistently carried methylated residues across the four different cell-types tested. However, the modification rate varied: two positions (A2515 and A2577) displayed the highest  modification rate, followed by A2611 (13–49%) and A2720 (7–14%). Only a small fraction of MALAT1 molecules (2–3%) carried the m6A modification at the other predicted sites (A2674/2684/2698) in two out of four cell lines. Importantly, secondary structure prediction and mapping experiments demonstrated that the two residues with the highest m6A rate  are located in hairpin stems. Subsequent structural mapping assays using methylated and unmethylated synthetic RNA oligonucleotides in conjunction with a set of structure-sensitive nucleases revealed that the presence of m6A in the hairpin stem increases the opening of the stem, i.e., reduces duplex stability [MALAT1 hairpin is maintained upon m6A modification, but the nucleobases of the hairpin stem are more flexible and solvent accessible [6A regulates protein binding through its influence on RNA structure (“m6A switch”) [MALAT1 hairpin stem is the first example of such an m6A-switch, changes induced by m6A modifications might apply to a much larger family of m6A-regulated RNA structures. Of note, modification of MALAT1 with m6A is highly dynamic and can be modulated by heat shock, UV and growth factor treatments in HepG2 cells [It has recently been shown that ications . The autentified ,97. Thiscessible . These r6A, MALAT1 also contains several pseudouridine residues at positions U5160, U5590 and U3374 [MALAT1 structure, protein interaction or molecular function are not known.Next to mnd U3374 ,87. Howe5C sites within MALAT1 through RNA bisulfite conversion combined with NGS [5C modification of MALAT1 are unknown, but DNMT2 and NSUN2 could potentially be excluded, since MALAT1 was only slightly enriched after respective Aza-IPs in HeLa cells [5C writers should be tested in the future.Additionally, Squires et al. identified several putative mwith NGS . HoweverLa cells . Hence, HOTAIR) is a long, intergenic ncRNA of ~2.2 kb that is transcribed from the antisense strand of the developmental HOXC gene cluster on chromosome 12 [HOTAIR, which promotes metastasis in several cancer types, is often found in human cancers, e.g., melanoma, breast, hepatocellular, gastric, colorectal or pancreatic carcinoma, and its expression is correlated with poor prognosis, e.g., in colorectal cancers [HOTAIR can serve as a plasma-derived biomarker for the diagnosis and monitoring of NSCLC [The Hox transcript antisense intergenic RNA  resulting in inhibition of gene expression across 40 kb of the HOXD gene locus [HOTAIR and is required for the interaction with the histone demethylase complex lysine specific demethylase 1 (LSD1)/co-repressor of RE1-silencing transcription factor (CoREST)/RE1 silencing transcription factor (REST) [HOTAIR to tether these two distinct chromatin-modifying complexes enables coupled histone H3K27 methylation and lysine 4 demethylation (H3K4) to induce epigenetic gene silencing.Mechanistically, omplexes . One intne locus ,162. TheHOTAIR at position C1683 occurring with complete penetrance  and present in all five cell lines tested [HOTAIR suggesting that other methyltransferases might be responsible for this modification [HOTAIR and LSD1 with downstream effects on histone H3 lysine 4 methylation changes has yet to be shown.Interestingly, a previous study identified a specific cytosine methylation in s tested . Howeverfication . ImportaHOTAIR have not been analyzed in more detail so far, Meyer et al. identified a single m6A peak region (126 nt) in the first half of HOTAIR, not overlapping with m5C, in HEK293T cells using MeRIP-Seq [6A signal in HOTAIR using HepG2 cells or human brain tissue despite the presence of several DRACH consensus motifs [While additional chemical modification in eRIP-Seq . In conts motifs .HOTAIR as a target for pseudouridylation [HOTAIR.Studies form Carlile et al. using Pseudo-Seq in HeLa cells, and Li et al. applying CeU-Seq in HEK293T cells, could not establish dylation ,87. HoweXIST is a ~17 kb lncRNA that is expressed from a region called X inactivation center (XIC). XIST is essential for the initiation and spread of X-inactivation by coating the chromosome in cis [XIST RNA-protein interactome thereby providing further insights into the molecular mechanisms of XIST-mediated heterochromatinization [The process of X inactivation, i.e., the transcriptional silencing of one of the pair of X chromosomes, is initiated early in female mammalian development to provide dosage equivalence between males and females. e in cis ,166,167.nization ,170,171.nization . However6A formation and recognition that is required for XIST-mediated transcriptional repression [6A modification rate (78 m6A residues) of XIST is dependent on RBM15 and its paralogue RBM15B, two RNA-binding proteins that link the m6A methylation complex to XIST through interaction with WTAP that in turn binds to the methyltransferase METTL3. Finally, m6A residues in XIST are recognized by YTHDC1 which leads to gene silencing. How exactly YTHDC1 binding to XIST leads to gene silencing remains unclear, but might involve additional molecular interactions between YTHDC1 and other proteins with well-established roles in the initiation of transcriptional silencing [In line with this, a recent study revealed a RBM15/METTL3/YTHDC1 pathway of mpression . In detailencing .6A, XIST was also shown to contain methylated cytosine residues [XIST, termed repeat A-region, consists of 8.5 repeats with 26 nt per full repeat and is required for the association with PRC2 [XIST revealed five methylated cytosines within repeat 8: C701, C702, C703, C711 and C712. The methylation rate of individual cytosine residues was between 19–24%, and a simultaneous modification of all five residues was detected in 19% of the sequences analyzed. Interestingly, non-methylated, but not methylated RNA oligonucleotides spanning the R8 tetra-loop and part of the inter-repeat helix of XIST were bound by PRC2 indicating that m5C, in contrast to m6A, can prevent XIST-protein interactions. However, no m5C modification was detected at the corresponding cytosines C668, 669, 670 and 678 in the A-region of mouse Xist, arguing against a conserved mechanism [In addition to mresidues . A 5’-reith PRC2 . Charactechanism .XIST, a pseudouridine residue at position U11249, was recently discovered [Finally, a third chemical modification in scovered . HoweverXist in the blood compartment of mice led to the development of a highly aggressive myeloproliferative neoplasm and myelodysplastic syndrome (mixed MPN/MDS) with 100% penetrance establishing a tumor-suppressive role of Xist [XIST deletions and X chromosome duplications have been found in MPN, MDS, and myeloid cancers [XIST gene copy number amplifications and increased expression levels have been detected in other cancers, e.g., microsatellite-unstable colorectal carcinoma (CRC) [XIST was recently associated with poor survival in CRC patients, and knockdown of XIST inhibited proliferation, invasion, epithelial-mesenchymal transition (EMT) and CRC stem cell formation in vitro, as well as tumor growth and metastasis in vivo [Interestingly, X chromosome aneuploidies have long been associated with human cancers, but causality has not been established. A recent study in mice made a step forward. Here, deletion of  of Xist . Intrigu cancers ,177,178. cancers ,179,180.ma (CRC) . Elevate in vivo .XIST might have context-dependent pro- or antitumor functions in human cancers and it would be interesting to know, if chemical modifications in XIST can shift the balance in one or the other direction.Hence, SRA) is an example of a bifunctional gene that is active as a lncRNA (SRA1), yet also encoding a conserved protein (SRAP) [SRA1 has a large number of isoforms, some of which display tissue-specific expression [SRA have been described to be involved in the regulation of the transcriptional activity of different hormone receptors  in a cell-specific manner indicating potential anti-cancer targets [SRA1 in carcinogenesis is not fully understood yet. For example, transgenic overexpression of SRA1 in mice caused hyperplasia and morphological abnormalities in steroid hormone responsive tissues, but did not induce tumors and was accompanied by higher apoptosis rates. SRA1 also antagonized Ras-induced tumor formation [The steroid receptor RNA activator (n (SRAP) . SRA1 hapression ,185. Whipression ,186,187. targets . Howeverormation .SRA1, which is required for its role as a coactivator. In a subsequent study, the same authors identified a specific uridine residue in SRA1 (U206) whose modification by Pus1 (or Pus3) might induce a functional switch to allow SRA1 to act as coactivator or corepressor [SRA1.Interestingly, the pseudouridine synthase Pus1 was previously identified as an interaction partner and coactivator of retinoic acid receptors (RARs), as well as other class I and II nuclear receptors in mouse cells . Furtherepressor . This coSRA1 have not been described or functionally analyzed so far. However, a close examination of transcriptome-wide m6A datasets warrants further investigations to clarify a putative link between the epitranscriptome and SRA1-dependent nuclear receptor signaling events [Other chemical modifications of g events ,97.6A to well-known lncRNAs, e.g., PVT1 and NEAT1 as well as uncharacterized lncRNA transcripts [5C sites in lncRNAs, Squires et al. identified several putative target sites, e.g., in SNHG12, GAS5, TERC, RPPH1 and ANRIL [6A in the lncRNA taurine up-regulated 1 (TUG1) (A1114) [LRRC75A antisense RNA 1  and small nucleolar RNA Host Gene 1  [RN7SK and Hussain et al. could identify RN7SK as a target for the m5C-introducing enzyme NSUN2 in HEK293T cells [ST7-AS1 (U1138), ZFAS1 (U569), SNHG7 (U292), DICER1-AS1 (U463), including also many inducible sites, e.g., DLEU2L , APTR , or MAGI2-AS3  [TERC) [Mining published datasets for lncRNAs reveals a broad selection of chemically modified transcripts . For exanscripts . Having nd ANRIL . However (A1114) . The sam; U1766) . Individ3T cells ,120. Kcn3T cells . In addiducible) . The tra) [TERC) .Nevertheless, the relevance of these epitranscriptomic changes in lncRNAs are largely unknown and require additional validation, as well as functional follow-up studies.The research field of epitranscriptomics has made huge strides in the last few years. High-throughput sequencing techniques enabled nearly transcriptome-wide modification detection and generated enormous amounts of data . ValidatMALAT1 was shown to be important for cell proliferation, apoptosis or motility by regulating alternative splicing and gene expression in one cell system, but affecting the expression of different genes in other cell lines [MALAT1 and other lncRNAs.Furthermore, investigating the distribution and function of chemical modifications in lncRNAs, as well as their association with the relevant proteins in more detail, will contribute towards an integrative understanding of the multilayered gene expression control mechanisms active in mammalian cells . Intrigull lines . Hence, Moreover, recent large-scale ribosome footprinting studies have made the surprising and controversial observation that lncRNAs interact with ribosomes and suggest that lncRNAs are capable of translating short peptides ,199,200.In summary, we are only starting to unravel the full breadth of the transcriptome, which comes in many  flavors. To date, more than 150 modifications have been identified in RNA, but only a handful can be currently mapped with high-throughput methods. This offers plenty of opportunities to discover novel regulatory principles. Moreover, proteins involved in the epitranscriptomic cascade might represent interesting therapeutic targets. However, our current knowledge about the epitranscriptomic changes that might occur during carcinogenesis, as well as their functional relevance on single molecule level, especially in lncRNAs, is still very limited. Hence, further molecular and mechanistic investigations are needed. These studies might pave the way for the development of novel therapeutics and might help to identify biomarkers for early cancer detection and therapy response.


Virtually every step of HIV-1 replication and numerous cellular antiviral defense mechanisms are regulated by the binding of a viral or cellular RNA-binding protein (RBP) to distinct sequence or structural elements on HIV-1 RNAs. Until recently, these protein–RNA interactions were studied largely by in vitro binding assays complemented with genetics approaches. However, these methods are highly limited in the identification of the relevant targets of RBPs in physiologically relevant settings. Development of crosslinking-immunoprecipitation sequencing (CLIP) methodology has revolutionized the analysis of protein–nucleic acid complexes. CLIP combines immunoprecipitation of covalently crosslinked protein–RNA complexes with high-throughput sequencing, providing a global account of RNA sequences bound by a RBP of interest in cells (or virions) at near-nucleotide resolution. Numerous variants of the CLIP protocol have recently been developed, some with major improvements over the original. Herein, we briefly review these methodologies and give examples of how CLIP has been successfully applied to retrovirology research. Following the integration of proviral DNA into the host cell chromosome, genesis of new HIV-1 particles is initiated by the host RNA Polymerase II-mediated synthesis of a single poly-cistronic viral RNA species . Like ceIn simple terms, CLIP is a powerful methodology with which one can identify the RNA targets of RNA-binding proteins in physiological settings, ranging from live cells to virus particles and even animal tissues. The inception of the original CLIP protocol , 8 and iHistorically, protein–RNA interactions were studied largely using in vitro binding assays with pure proteins and RNAs. Alternatively, GST-pulldown and immunoprecipitation-based assays were conducted on cell lysates followed by downstream quantitative analysis of RNA by Q-RT-PCR or microarrays. A major drawback of these cell lysate-based approaches was their limited ability to identify direct interactions between a RBP and its target RNA molecules. Their limited power was due at least in part to the presence of contaminating protein and RNA molecules in the isolated RBP-RNA complexes. Development of the original CLIP protocol , 8, in wC. elegans which can be grown in 4SU containing media and efficiently UV-crosslinked due to its transparency [A major advantage of PAR-CLIP  over HITsparency ). Althousparency , we and sparency , 14, Argsparency –18, as wsparency –24. A posparency . Thus, osparency , which mIdentification of the precise crosslinking site in the HITS-CLIP and PAR-CLIP approaches relies respectively on deletions and substitutions introduced by RT during cDNA synthesis. However, read-through at crosslinking sites appears to be a relatively rare event as compared to truncations that occur as a result of RT stalling at these sites , 28. ThuThe eCLIP protocol  proposesSimilar to eCLIP, irCLIP has been developed to overcome some of the shortcomings of previous CLIP methodologies by simplifying the library generation steps, increasing the yield and complexity of the CLIP library, and allowing faster processing times. One of the major differences of this approach is the utilization of a 3′ adapter conjugated to an infrared fluorescent dye , which pThe major shortcomings of all of the above CLIP approaches include technically challenging and labor-intensive protocols, and loss of the starting material at several inefficient steps in the procedure. This problem is further exacerbated if the initial protein–RNA complexes are not abundant due to low levels of expression in cells (virions), low crosslinking or immunoprecipitation efficiencies. These problems can often lead to a final library with insufficient complexity and enrichment of environmental contaminating sequences. When we adapted the CLIP protocol to study HIV-1 Gag-RNA interactions , we took3–10), which allow multiplexing and differentiating between independent ligation versus PCR overamplification events, respectively. In these circumstances, a typical pipeline will involve removing low quality reads, collapsing of raw reads into unique reads, demultiplexing samples, discarding short reads  and trimming the adaptors prior to mapping. One of the most commonly used tools is the FASTX_toolkit (http://hannonlab.cshl.edu/fastx_toolkit/), which provides a number of functions to accomplish all of these steps. Other alternatives, with more limited functions include Cutadapt [Pre-processing of sequencing reads: The resulting CLIP libraries in all of the above protocols will contain some form of 3′ and 5′ adaptors. In the majority of cases, these adaptors contain barcodes and degenerate sequences , RMAP [254 nm crosslinking in HITS-CLIP and related methods. For example while the original Bowtie algorithm did not allow gaps during alignment, Bowtie2 was developed to enable alignments with indels. Similarly, if mapping is done on transcriptomes, alignment algorithms such as STAR, which allow higher accuracy and speed for mapping spliced transcripts should be preferred. However, mapping to the transcriptome will clearly lead to the exclusion of reads derived from introns, which may constitute the primary binding sites for various splicing regulatory proteins. Thus, a general strategy whereby CLIP reads are mapped first to the transcriptome and the remaining reads are mapped to the genome may work the best for proteins for which there is no information on the types of targeted RNA molecules.Mapping to reference genomes: The reads that pass the above filtering steps are mapped onto reference genomes or transcriptomes. The most commonly used mapping algorithms used for this task include Bowtie , Bowtie2/), RMAP , TopHat /), RMAP , GSnap [/), RMAP , SOAP [5/), RMAP  and BWA /), RMAP , some wipeak calling. In simple terms, peak calling is the process by which clusters of reads that map to distinct locations are separated from background reads that may stem from unspecific binding events or contaminants during the CLIP procedure. Peaks are typically defined based on a number of variables such as read depth relative to surrounding regions, presence of expected and absence of unwanted mutations (as in the case of PAR-CLIP-based approaches) and peak shape. While peak calling can be based solely on CLIP data, additional controls such as data derived from replicates and negative controls (i.e. immunoprecipitations done with isotype controls and/or conducted in lysates lacking the RBP of interest) can further increase specificity of peak calling. Comparison of the CLIP peaks with transcript abundance derived from matching RNA-seq experiments allows the discrimination of whether a binding event is merely a result of transcript abundance or a more specific interaction between the RBP and its target RNA. Several peak calling programs have been developed and include Piranha [Peak calling: The next essential step in CLIP analysis is identification of the true binding sites by what is often referred to as  Piranha , CLIPper Piranha , PIPE-CL Piranha , Pyicos  Piranha  that wor Piranha  and wavC Piranha , 42.Post-processing analyses: Following the identification of peaks, further analyses are typically conducted to identify the specific rules that may determine protein binding. For example, many studies generally assess what classes of RNAs and where within those transcripts binding sites are located and whether there are distinct motifs within the binding sites. While the former analyses are done usually by custom scripts, programs such as MEME , HOMER  and cERMCLIP data analyses can be summarized in four major steps: (1) pre-processing of sequencing reads. (2) mapping of reads to reference genomes, (3) subjecting mapped reads to cluster finding algorithms to define binding sites, (4) analysis of binding sites for enrichment of certain features including where within a gene body the binding site is located, presence of distinct motifs or nucleotide composition. Recently a few pipelines that can perform the majority of these steps have been developed and include the PARCLIPsuite , CLIPZ , CIMS 3 and CLIPAll major steps of HIV-1 particle assembly are orchestrated by the major structural protein, Gag . Gag undcis-acting packaging element, psi (Ψ), within the 5′ leader of the viral genome, composed of sequences in the unique 5′ region (U5) and between the tRNA primer binding site (PBS) and the 5′ portion of the Gag open reading frame (ORF). However, disruption of Ψ only modestly decreases HIV-1 RNA encapsidation [The mechanism by which HIV-1 selectively packages a dimeric unspliced viral genome is based largely on prior observations with simple retroviruses, as well as genetic studies and limited in vitro data. Selective packaging of the HIV-1 genome is governed in part by binding of the nucleocapsid (NC) domain of Gag to a highly structured sidation –68, and sidation –73. In asidation , 75. ThuApplication of the CLIP methodology to the study of Gag-RNA interactions during different stages of particle assembly in cells revealed previously unanticipated rules of selective genome packaging . First, Pro can inhibit Gag binding to negatively charged lipid membranes lacking PIP2 [Lys, which was one of the most frequently bound to tRNAs by MA in cells [In addition to the NC domain, the matrix (MA) domain of Gag had long been suspected to bind RNA, based largely on in vitro assays –87. The P2 . Interesin cells , did notin cells . As thisLys, tRNAGlu and tRNAVal were found to be amongst the most frequently bound by MA, suggesting the possibility of MA enhancing the translation of Gag and Pol by sequestering these specific set of tRNAs. Alternatively, it is conceivable that by sequestering tRNAs, MA could inhibit translation of host mRNAs whose products may block viral replication. Indeed, one report has suggested that interaction of MA with host translation elongation factors via a tRNA bridge could inhibit in vitro translation [In addition to regulation of Gag membrane binding, MA-tRNA interactions could have other functions. An obvious possibility is regulation of viral and/or host translation. As a result of the unusually A-rich nature of the HIV-1 genome –97, Ile,nslation . It remaThe morphological changes that occur during HIV-1 particle maturation are often thought to be dependent only on proteolytic cleavage of Gag. The cleaved CA domain of Gag forms the conical lattice within which the viral genome condenses, along with the cleaved NC domain of Gag as well as viral enzymes integrase (IN) and reverse transcriptase (RT), cleavage products of the Pol polyprotein. However, more than two decades ago, mutational studies of the HIV-1 IN indicated that it may also play an active role in proper particle maturation –110. In The recent development of allosteric integrase inhibitors (ALLINIs) reignited research in this area. While ALLINIs were initially developed to target IN binding to the cellular cofactor LEDGF, it was later shown that these compounds primarily act during particle maturation and lead to morphological aberrations in particles similar to those induced by the aforementioned Class II IN mutations –119. BioWhile viral RNAs contain sequence and structural elements that regulate key steps in HIV-1 replication, they can also be recognized by host defense mechanisms. Infiltration of the host APOBEC3 (A3) proteins into virus particles by binding viral RNAs is a prime example of this process. A3 proteins are a family of cytidine deaminases that inhibit the replication of a broad range of viruses and retroelements . AThree recent studies employing CLIP have provided insight into the RNA-binding properties of several A3 proteins in infected cells and in virions , 147. ThZAP gene, but could replicate with wild-type kinetics in cells rendered ZAP-deficient by CRISPR-Cas9 editing [The genomes of vertebrates are marked with a paucity of CG dinucleotides , a featu editing .While previous studies had shown that ZAP had antiviral activity against a number of RNA viruses, several conventional techniques could not identify a common sequence motif or RNA feature that could explain how ZAP was able to specifically target viral RNA sequences , 155. RN6A) is the most prevalent of these and has been proposed to regulate several aspects of RNA metabolism, including splicing, nuclear export, localization, stability and translation [6A modification is catalyzed by a nuclear “writer” protein complex, composed of two methyltransferase-like enzymes, METTL3 and MTTL4, and their cofactor Wilms tumor 1-associated protein (WTAP). This modification can be reversed by two RNA demethylases, or ‘‘erasers’’, ALKBH5 (a-ketoglutamarate-dependent dioxygenase homolog 5) and FTO (fat mass and obesity associated). m6A-modifications on mRNAs can be bound by three related cytosolic ‘‘reader’’ proteins called YTH-domain containing family 1 (YTHDF1), YTHDF2, and YTHDF3. Exactly how binding of these proteins on modified nucleotides regulate mRNA metabolism is currently unknown. Nonetheless, m6A modifications can be found on mRNAs of diverse viruses that replicate in the nucleus, including SV40 [6A modifications and how this affected virus replication was not known.Like proteins and DNA, RNA can undergo a number of chemical modifications that subsequently affect its metabolism, function and localization. While tRNAs and rRNAs are subjected to the most diverse set of modifications, recent transcriptome-wide studies revealed the presence of numerous mRNAs modifications –162. Metnslation . m6A moding SV40 , adenoviing SV40 , 166, ining SV40  as well ing SV40  and Rousing SV40 , 170. Un6A-specific antibody followed by high throughput sequencing of the immunoprecipitated mRNAs [6A sites identified in these independent studies. This lack of consistency can in part be explained by the different approaches taken. The first published study that has utilized a RIP-seq approach, in which m6A-modified RNAs were immunoprecipitated from cell lysates and sequenced, found m6A modifications throughout the viral genome [6A-modified RNAs, found that the m6A modifications were exclusively localized within the viral 3′ UTRs [6A-specific immunoprecipitations [6A-seq [6A sites on HIV-1 RNAs, cross-validation of reagents  and methods  will be necessary to reach to a consensus in future studies.Three recent studies have addressed this question by immunoprecipitating methylated HIV-1 RNAs from infected cells using a med mRNAs –173. Strl genome . In cont 3′ UTRs . Importaitations . A thirdApplication of the CLIP methods to questions in retrovirology will undoubtedly continue to increase, given the large number of RBPs that are known and continuing to emerge as key regulators of retroviral replication. Several poorly explored areas in retrovirology will benefit from these approaches. One of the immediate applications of this methodology will be in determining how the alternative splicing of HIV-1 transcripts is regulated by cellular hnRNP and SR splicing-regulatory proteins. Although the families of hnRNP and SR proteins constitute more than 50 proteins, only a few have been shown to play roles in HIV-1 RNA splicing. In addition, none of the studies performed to date determined where on viral RNAs these proteins bind. Instead, in vitro splicing reporters and genetic assays were used, which are prone to artefacts. Another exciting area of research where CLIP and related methodologies may make a major impact is the sensing of viral nucleic acids in infected cells. HIV-1 infection induces high levels of interferon and other cytokines during the acute phase of infection, suggesting that viral nucleic acids are sensed in infected cells. While a few isolated studies indicated that viral reverse transcription products or RNA elements can be sensed in certain settings, it remains to be determined what features of viral nucleic acids are sensed and whether viral RNA or DNA elicits an inflammatory response. While A3 proteins provide a good example of how viral RNAs can be targeted by antiviral host proteins, it is plausible that many other cellular proteins that can recognize and target viral RNAs. CLIP will be a key tool in unveiling novel cellular proteins that participate at the HIV-1-host interface. Finally, although CLIP has so far only been applied to HIV-1 biology, it will certainly find broad applications in retrovirology and virology more generally as the methods and next-generation sequencing becomes more accessible.


Hepacivirus in the family Flaviviridae and has a single-stranded RNA genome of positive orientation. The HCV RNA genome is translated and replicated in the cytoplasm. Translation is controlled by the Internal Ribosome Entry Site (IRES) in the 5′ untranslated region (5′ UTR), while also downstream elements like the cis-replication element (CRE) in the coding region and the 3′ UTR are involved in translation regulation. The cis-elements controlling replication of the viral RNA genome are located mainly in the 5′- and 3′-UTRs at the genome ends but also in the protein coding region, and in part these signals overlap with the signals controlling RNA translation. Many long-range RNA–RNA interactions (LRIs) are predicted between different regions of the HCV RNA genome, and several such LRIs are actually involved in HCV translation and replication regulation. A number of RNA cis-elements recruit cellular RNA-binding proteins that are involved in the regulation of HCV translation and replication. In addition, the liver-specific microRNA-122 (miR-122) binds to two target sites at the 5′ end of the viral RNA genome as well as to at least three additional target sites in the coding region and the 3′ UTR. It is involved in the regulation of HCV RNA stability, translation and replication, thereby largely contributing to the hepatotropism of HCV. However, we are still far from completely understanding all interactions that regulate HCV RNA genome translation, stability, replication and encapsidation. In particular, many conclusions on the function of cis-elements in HCV replication have been obtained using full-length HCV genomes or near-full-length replicon systems. These include both genome ends, making it difficult to decide if a cis-element in question acts on HCV replication when physically present in the plus strand genome or in the minus strand antigenome. Therefore, it may be required to use reduced systems that selectively focus on the analysis of HCV minus strand initiation and/or plus strand initiation.Hepatitis C virus (HCV) preferentially replicates in the human liver and frequently causes chronic infection, often leading to cirrhosis and liver cancer. HCV is an enveloped virus classified in the genus  Hepatitis C virus (HCV) preferentially infects human liver hepatocytes, likely leading to chronic liver infection and often proceeding to liver cirrhosis and hepatocellular carcinoma (HCC) . Worldwicosts and emergence of resistance remain serious problems of disease control .Figure 1) is directly translated and replicated in the cytoplasm . The RNA secondary structures and sequences at the genome ends are highly conserved .Hepatitis C virus comes as a lipoviral particle that contains viral proteins as well as cellular lipids and proteins, covering the viral positive-sense single-stranded RNA genome . After Hytoplasm . The IREytoplasm  and therl genome  . From this minus strand, progeny plus strands are then produced in 10- to 100-fold excess over the minus strand antigenome template  and build a so-called membranous web  with vestemplate . Then, ftemplate , and fintemplate .cis-elements in the viral plus strand genome and minus strand antigenome and focus on particular aspects concerning the regulation of RNA translation and RNA synthesis.Comprehensive and detailed overviews on the HCV life cycle have been previously reviewed . Also thFigure 2A) contains highly conserved RNA secondary structures and sequences and bears cis-elements that control viral RNA genome translation as well as RNA replication and stability. These signals mainly reside in the 5′ UTR but also reach into the coding region of the core protein. Thereby, some of these functional signals overlap.The 5′ end of the plus strand  characterized in the above studies are concluded to be actually involved in the control of HCV RNA replication. However, strictly speaking this statement does not distinguish between elements in the annotated HCV sequence that are functional at the 5′ end of the plus strand, or as reverse complementary sequence at the 3′ end of the minus strand .Despite this prominent role of SL II in translation, the most 5′ region of the HCV 5′ UTR including the SL I, SL II and the region between them have been reported to be involved in HCV overall RNA replication , with a Figure 2A). Single-stranded miR-122 guide strand can induce a conformational change in HCV 5′ UTR structure by displacing this inhibitory hybridization in vitro  is conserved among HCV isolates, and it is as thermodynamically stable as the “canonical” IRES structure . However, all experimental data obtained so far . Thus, if the predicted alternative IRES structure forms at all in nature, it may be very short-lived and therefore yet escaped detection. Since the high degree of conservation suggests a function, we can only speculate if this alternative IRES structure may decrease the affinity of the IRES to the 40S subunit and by that may support the escape of the ribosome from the translation initiation site to proceed with translation elongation.Finally, a rather hypothetical consideration applies to the structure of the HCV 5′ UTR. In a bioinformatic evaluation of conserved RNA structures in the HCV RNA genome and antigenome ends , an alteFigure 3) initially focused on the 3′ UTR, although now it becomes more and more clear that several signals in the upstream coding region  are also involved in the control of HCV overall replication . In an alternative conformation  largely the SLs 2 and 3 rearrange to form one larger RNA secondary structure, while the SL 1 undergoes only a slight change at its base leading to the extrusion of two single-stranded 3′ terminal nucleotides from the double-stranded stem.The investigation of signals in the 3′ region of the plus strand RNA genome  . This CRE is important for HCV replication   and a bulge (position 9365). This RNA element was characterized as a lication , likely lication . Howeverlication  is not clication . The buligure 3) . This upigure 3) . Mutatioigure 3) .Figure 3), a LRI can form between the apical loop of the 3′ X SL 2 (GCUGUGA) and the apical loop of the upstream 5BSL3.2 CRE structure (UCACAGC). This “kissing-loop” interaction is required for overall HCV replication, and even covariant point mutations that retain the long-range interaction between both partners slightly reduce viral replication efficiency, pointing to the importance not only of the structure but also of the involved primary sequences  (in vitro (in vitro dimerization of the DLS RNA is stimulated by the HCV core protein (in vivo – like it has been demonstrated for human immunodeficiency virus (HIV) (The large RNA secondary structure formed by the combined SLs 2 and 3 (lower structure in igure 3)  exposes in vitro . The in  protein , and the protein  and was  protein . This shus (HIV)  – has noContradictory results have been published regarding a possible role of the CRE in the regulation of translation. One study  shows thFigure 3, “SL8647”). This SL8647 element is named JFH-SL8647 in Moreover, another important RNA secondary structure is located in the NS5B coding sequence upstream of the CRE ; it was shown to be involved in RNA replication  and also is involved in RNA replication  is located even more downstream; it has an effect on early genome replication but virtually no effect on final virus particle production . Since the GGG sequence in the SL IIId loop is a main determinant in the isolated IRES RNA that is required for 40S ribosome binding  can interact with the loop of the small SL IIId (UCCCU) in the large IRES SL III domain , 2017  is important for translation stimulation .In addition to the  subunit . Therefo subunit . The bin subunit . Consistmulation , the polmulation . SupportFigure 4), and some have been functionally linked to HCV replication. These are insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1 or IMP1), heterogeneous nuclear ribonucleoprotein L (hnRNP L), a complex containing the nuclear factors (NF) 90 and NF45, and poly-C binding protein 2 (PCBP2). Moreover, functional circularization of the HCV genome by binding to the ribosomal 40S subunit may also be supported by the oligomerization of Argonaute (Ago) protein which associates with miR-122 at the 5′ end and the 3′ end of the HCV RNA (see below); it can be assumed that Ago protein routinely associates with ribosomes since it was initially purified from ribosomes  and stimulates HCV translation , and its binding has been correlated with IRES activity    . Therebyigure 4) . Consistigure 4) . NF90 anigure 4) . This coFigure 4)  . In the igure 4) , likely igure 4) . The secigure 4) . In the igure 4) . Since Pigure 4)  and bindigure 4) , PCBP2 digure 4) .Figure 4), indicating that they may act in concert to functionally circularize the HCV genome. These interactions suggest that there may be a regulated balance between genome translation and replication. After sufficient amounts of replication proteins have been synthesized, a switch may be required in order to reduce translation and proceed with minus strand synthesis. The above mentioned proteins may, in addition to RNA–RNA long-range interactions, be involved in the regulation of such a switch.The above described interactions of proteins with the HCV RNA genome are largely non-overlapping but appear to complement each other  usually do not represent exact mirror images of the structures formed by the plus strand (due to different G:U base pairs). At the 5′ end of the minus strand, the structure of the SLα is well conserved, whereas the SLβ can assume three different structures , three variant structures have been proposed  in common, whereas the determination of the structure of the SL III cdef′ varies among the studies. The design of local mutations for functional analyses of these sequences at the 3′ end of the minus strand was always guided by these structures. However, up to now experimental analyses were performed only in the reverse complement of the plus strand 5′ UTR but not further upstream in the minus strand. Our predictions (data not shown) of the conserved structure upstream of the SL IV′ in the minus strand using the LocARNA program , while having some structure changes due to different G:U base pairs.For the 3′ end of the minus strand .In a genetic approach, genotype-specific chimera were generated with the HCV 5′ UTR, the 3′ UTR and the NS5B replicase either from genotype 1b (the Con1 isolate) or from genotype 2a (the JFH-1 isolate). The results showed that the genotype-specific NS5B replicase proteins appear to have preferences for their own  templates at both genome ends . In a moin vitro approaches were used to completely uncouple the initiation of plus strand RNA synthesis at the 3′ end of the minus strand from the functions of the mirror sequences in the opposing plus strand , since it was found that its deletion resulted in enhanced RdRP activity  or as a reverse complement in the minus strand .In contrast, for the more upstream sequences at the 3′ end of the minus strand, these biochemical approaches returned results that are somewhat different from those obtained in the replicon studies discussed above . In the activity . Moreoveactivity , while tactivity . In contin vitro . Thus, sin vitro  are actiFigure 1), depending on genotype . One site (5B.1) that is not conserved and two sites (5B.2 and 5B.3) that are highly conserved among HCV isolates are located in the NS5B coding region, and one conserved site (S3) is located in the otherwise variable region of the 3′ UTR . miR-122 is required for efficient overall HCV genome replication, but low-level HCV replication can occur independently of miR-122  with higher affinity than to the first binding site (S1)  protein, a key component of microRNA–protein (miRISC) complexes . In miRNA/Ago2 complexes, the seed sequence of the miRNA is primarily exposed by the Ago protein, and miRNA binding to the target RNA is initiated in this region. Therefore, this region is more important for binding target than the following 3′ nucleotides of the miRNA (The two binding sites in the 5′ UTR have a rather fixed distance . In vitrite (S1) . In vivoomplexes , confersomplexes . Then, bhe miRNA . Continuhe miRNA , likely he miRNA . The seehe miRNA . This coThe effector functions of miR-122 binding to the 5′ UTR appear to be complex and are still controversially discussed. The first studies described a strong effect of miR-122 on overall HCV replication . HoweverThe second downstream effector function of the two miR-122/Ago2 complexes binding to the HCV 5′ UTR is to protect the 5′ end of the genomic RNA against degradation by 5′–3′-exonucleases . The exoThe third effector function of the miR-122/Ago complexes binding to the HCV 5′ UTR is assumed in RNA replication. According to effects of miR-122 not explained by the functions actually analyzed, one study proposed a function in replication . This suHowever, all above studies focused on the 5′ UTR miR-122 binding sites. In contrast, only few reports focused on the NS5B and 3′ UTR binding sites so far. Ago2 crosslink-immunoprecipitation (CLIP) experiments have shown that Ago2 binds mainly to the HCV 5′ UTR miR-122 target sites but also to the NS5B and 3′ UTR target sites . miR-122Other putative functions of miR-122 in the HCV replication cycle have not yet been resolved. It has been speculated that miR-122 affects the switch from translation to replication, the displacement of the plus strand RNA from its minus strand template following replication, the modulation of binding of RNA binding proteins and the recruitment of the HCV RNA to replication complexes .trans-acting factors are involved in the initiation of minus strand synthesis? (2) Do plus strand 5′ region sequences regulate minus strand initiation at the genome’s 3′ end? (3) Does translation at the genome 5′ end interfere with minus strand initiation or vice versa? (4) What are the molecular details of the initiation of plus strand synthesis? (5) Do the complete HCV genomes actually dimerize in vivo? (6) Which determinants of the HCV RNA genome are involved in packaging of progeny genomes? (7) How is the stimulation of translation by miR-122 conferred? (8) Are there additional roles of the 5′ UTR miR-122 binding sites in replication? (9) What are the roles of the NS5B and 3′ UTR miR-122 binding sites? These and other questions need to be answered in future studies.Even though much progress has been achieved in the analysis of the molecular biology of the HCV life cycle, there are still several open questions: (1) Which signals and MN: writing the original draft. MN, LS, GG, and OR: reviewing and editing the manuscript. MN and OR: funding acquisition.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Triple negative breast cancer (TNBC) is a heterogeneous disease that lacks unifying molecular alterations that can guide therapy decisions. We previously identified distinct molecular subtypes of TNBC (TNBCtype) using gene expression data generated on a microarray platform using frozen tumor specimens. Tumors and cell lines representing the identified subtypes have distinct enrichment in biologically relevant transcripts with differing sensitivity to standard chemotherapies and targeted agents. Since our initial discoveries, RNA-sequencing (RNA-seq) has evolved as a sensitive and quantitative tool to measure transcript abundance.To demonstrate that TNBC subtypes were similar between platforms, we compared gene expression from matched specimens profiled by both microarray and RNA-seq from The Cancer Genome Atlas (TCGA). In the clinical care of patients with TNBC, tumor specimens collected for diagnostic purposes are processed by formalin fixation and paraffin-embedding (FFPE). Thus, for TNBCtype to eventually have broad and practical clinical utility we performed RNA-seq gene expression and molecular classification comparison between fresh-frozen (FF) and FFPE tumor specimens.Analysis of TCGA showed consistent subtype calls between 91% of evaluable samples demonstrating conservation of TNBC subtypes across microarray and RNA-seq platforms. We compared RNA-seq performed on 21-paired FF and FFPE TNBC specimens and evaluated genome alignment, transcript coverage, differential transcript enrichment and concordance of TNBC molecular subtype calls. We demonstrate that subtype accuracy between matched FF and FFPE samples increases with sequencing depth and correlation strength to an individual TNBC subtype.TNBC subtypes were reliably identified from FFPE samples, with highest accuracy if the samples were less than 4 years old and reproducible subtyping increased with sequencing depth. To reproducibly subtype tumors using gene expression, it is critical to select genes that do not vary due to platform type, tissue processing or RNA isolation method. The majority of differentially expressed transcripts between matched FF and FFPE samples could be attributed to transcripts selected for by RNA enrichment method. While differentially expressed transcripts did not impact TNBC subtyping, they will provide guidance on determining which transcripts to avoid when implementing a gene set size reduction strategy.NCT0093093007/01/2009.The online version of this article (doi:10.1186/s12885-017-3237-1) contains supplementary material, which is available to authorized users. Multi-gene prognostic and predictive gene signatures are now routinely performed in pathology laboratories to guide treatment decisions in breast , lung 22 and colOriginally, TNBC molecular subtypes were identified by correlating gene expression to six centroids comprising 2188 genes representing each subtype . RecentlTranscriptional profiling by RNA sequencing (RNA-seq) provides unprecedented sensitivity and quantitative measurement of a diverse range of RNA species . HoweverIn order to determine if RNA-seq would produce high quality data and permit proper molecular classification of TNBC, we compared the gene expression and TNBC subtype concordance with RNA obtained from 98 matched FF and FFPE tumors processed on microarray or RNA-seq platforms, respectively. The feasibility of performing molecular subtyping on RNA isolated from TNBC specimens was further determined by comparing RNA-seq data from 21 matched FF and FFPE samples sequenced on either Illumina HiSeq or MiSeq platforms. Our analyses show that the majority of differential transcripts identified between matched FF and FFPE samples could be attributed to RNA isolation methods.Tumor tissues were acquired from an active clinical trial and the Vanderbilt Cooperative Human Tissue Network (CHTN). All patients provided written informed consent prior to enrollment and were approved by an Independent Ethics Committee at Vanderbilt University. Tissues from the CHTN have been obtained from de-identified female patients. Vanderbilt University Institutional Review Board (exempt form IRB#090026) was reviewed and determined that the study does not qualify as “human subject” research per §46.102(f) (2). Tissue was obtained from the pathology lab before being discarded. No identifiers were included and there was no contact with donor.FF tissue sections were processed using the RNeasy Mini Kit (QIAGEN cat. # 74104). Briefly, the samples were disrupted in 350 μL Buffer RLT with dithiothreitol (DTT), and 0.5 mm glass beads (BioSpec cat # 11079105) on a Mini-Beadbeater (Bio-Spec cat # 3110BX). The tissue lysate was then purified via RNAeasy column and eluted in 50 μL nuclease-free water. RNA quantity was measured via Qubit RNA assay (Life Technologies cat # Q32855) and quality via Agilent 2200 TapeStation R6K ScreenTape assay (cat # 5067–5367).FF samples were enriched for messenger RNA (mRNA) by treating the total RNA (tRNA) extracted from tissue sections with NEBNext Magnetic Oligo d (T)25 Beads (New England Biolabs cat. # E7490S) that bind to the poly-A tail of mRNA molecules. After repeated washes and re-suspension in binding buffer, the NEBNext beads were combined with tRNA and incubated at 65 °C for 5 min on a thermal cycler before bring the temperature down to 4 °C in order to denature the RNA and facilitate binding of the poly-A tailed RNA to the beads. When the samples reached 4 °C they were removed from the thermal cycler and allowed to incubate at room temperature for 5 min before being placed on a magnetic rack for 2 min to separate the poly-A RNA bound to the beads from the solution. After removal of the supernatant, the samples were washed twice to remove unbound RNA. The samples were then placed back on the magnet and the supernatant was removed after a 2 min incubation at room temperature. The beads were then re-suspended in the Tris buffer and mixed thoroughly by pipette before being placed on a thermal cycler and incubated at 80 °C for 2 min and then cooled 25 °C to elute the poly-A RNA from the beads. Tubes were removed from the thermal cycler when the temperature reached 25 °C. Binding buffer was added to each sample to facilitate the RNA’s binding to the beads and they were incubated at room temperature for 5 min before being placed on the magnetic stand. After 2 min on the magnet the supernatant was removed and discarded. The beads were then rinsed twice with Wash Buffer while off the magnet. The mRNA was then eluted off the beads by adding 17 μl of the Tris Buffer and incubating the sample at 80 °C for 2 min before immediately returning the samples to the magnet. After 2 min on the magnet the purified mRNA was collected by transferring the supernatant to a clean nuclease-free PCR tube and placing on ice.FFPE tissue sections were deparaffinized using deparaffinization solution (QIAGEN cat # 19093) processed with the RNeasy FFPE kit (QIAGEN cat # 73504). FFPE RNA was eluted in 25 μL nuclease-free water. RNA quantity was measured via Qubit RNA assay and quality via Agilent 2200 TapeStation R6K ScreenTape assay  - Low input (Epicentre cat # LIG1224) kit. This was only performed on FFPE samples where an adequate amount of RNA was extracted from the tissue (0.2–1.0 μg of RNA). Samples with less than 0.2 μg of RNA were not rRNA depleted but treated with the TotalScript library preparation protocol described below rather than the ScriptSeq protocol used on all other samples. Prior to beginning rRNA depletion, the Ribo-Zero beads were removed from the storage solution and washed twice with RNase-Free water (before being resuspended in Magnetic Bead Resuspension Solution and combined with RiboGuard RNase Inhibitor) and stored at room temperature until needed. Next, the total RNA samples were combined with Ribo-Zero Reaction Buffer and Ribo-Zero rRNA Removal Solution and incubated at 68 °C for 10 min before a 5 min incubation at room temperature. This sample mixture was then combined with the washed magnetic beads that were prepared first and mixed thoroughly. After a 5 min incubation at room temperature, the samples were vortexed at level 5 for 10 s and placed at 50 °C for 5 min. The samples were then placed on the magnetic stand for 1 min before the supernatant  was removed and transferred to a labeled RNase-Free microcentrifuge tube and purified using RNAClean XP (Beckman Coulter Cat. No. A63987).For FF samples, the mRNA isolated using the NEBNext PolyA Module was incubated at 85 °C for 5 min with random-hexamer primers linked to capture tags in fragmentation solution and then immediately placed on ice to simultaneously fragment the RNA anneal tagged cDNA synthesis primers. FFPE samples were not fragmented but were instead annealed to the cDNA synthesis primers by incubating the ribosomal RNA-depleted samples with tagged random hexamers at 65 °C for 5 min before placing them immediately on ice. For FFPE samples, the fragmentation solution was then added along with a cDNA synthesis master-mix and DTT. For FF samples, only the cDNA synthesis master-mix and DTT were added. cDNA synthesis was then performed on both sample types by incubating at 25 °C for 5 min followed by 42 °C for 20 min and then the temperature was raised to 37 °C and a Finishing Solution was added. The samples were then incubated at 37 °C for 10 min followed by 95 °C for 3 min before the temperature was reduced to 25 °C and random hexamers linked to a terminal tag and a DNA polymerase were added to apply a capture tag to the 3' end of the cDNA molecules. The samples were then incubated at 25 °C for 15 min and then 95 °C for 3 min before being placed immediately on ice. FFPE samples were then purified using the MinElute PCR Purification Kit from Qiagen. FF samples were purified using the Agencourt AMPure XP system from BeckmanCoulter at a bead to sample volume ratio of 0.9. All samples were then amplified by PCR using primers that anneal to the capture tags at the 3′ and 5′ ends of the cDNA. These sequencing primers also contained Illumina adapter sequences and sample identifier indexes, enabling the PCR to simultaneously amplify the cDNA library while also applying sequencing adaptors and indexes. After PCR, all samples were purified using the Agencourt AMPure XP system from BeckmanCoulter at a bead to sample volume ratio of 0.9 and quality was assessed using the Agilent 2200 TapeStation D1000 ScreenTape assay. The libraries were then quantified using the Library Quantification Kit from Kapa and diluted to a concentration of 4 nM. Samples analyzed on the same sequencer run were pooled equally and denatured by incubating in 0.2 N NaOH for five min before being diluted to 15 pM and sequenced on an illumina MiSeq instrument using version 3150 cycle kit. All sequences generated are deposited in the Sequence Read Archive under SRP101418.Homo sapiens reference using star [Raw fastq files were obtained for each sample and aligned to the ing star . The aliing star .p-value <0.5, absolute fold change >2 and average read count >4) were identified using DESeq2 [Differential genes between FF and FFPE (FDR g DESeq2 . Differeg DESeq2 ).http://gdac.broadinstitute.org/). Gene level 3 RSEM mRNA (stddata__2016_01_28 run) and lowess normalized Agilent microarray expression (stddata__2016_01_28 run) were downloaded and overlapping TNBC samples were identified by common participant barcode (TCGA-XX-XXX). RNA-seq and microarray data were subtyped independently as previously described [RNA-seq and Agilent microarray gene expression data for TCGA breast cancer (BRCA) study were obtained from the Broad GDAC Firehose (http://cbc.mc.vanderbilt.edu/tnbc/) as previously described [TNBC subtyping was performed on FPKM normalized RNA-seq counts from paired FF and FFPE samples uploaded in separate batches to TNBCtype website , demonstrating conservation of gene expression across RNA-seq and microarray platforms and suggesting that subtype discordance were likely due to other factors . We identified 98 samples with gene expression data generated on both microarray and Illumina RNA-seq platforms. We performed TNBC subtyping and achieved a similar distribution of samples in TNBC subtypes as previously reported , 17 with2 = 0.763) and discordant subtype calls were typically of low confidence  for FF tissues or ribosomal depleted RNA for FFPE, and sequenced 10 matched pairs of RNA using the Illumina MiSeq platform and 11 matched pairs of RNA using the Illumina HiSeq platforms  or HiSeq  platforms, but the HiSeq had on average 6.2 times more aligned reads    with Ensembl (v75) annotation and read alignment was evaluated between platforms and tissue processing. The total number of aligned reads was similar between matched FF and FFPE samples on the MiSeq , and 3′ RNA degradation is common in FFPE samples, poly-A transcript selection is not appropriate and ribosomal depletion provides a more accurate transcript estimation for FFPE samples. To determine the efficiency of ribosomal depletion, we calculated the ratio of rRNA to total coding RNA transcripts. The fraction of rRNA was less than 0.0011% and 0.0014% for poly-A selected transcripts from FF tissue processed on the MiSeq and HiSeq platforms, respectively. This fraction was similar to those obtained by ribosomal depleted RNA from FFPE on the MiSeq and HiSeq platforms , demonstrating effective reduction of rRNA species.p < 0.0001) and HiSeq  platforms   and MiSeq  platforms. The latter could be mitigated by increased coverage as the percentage of intergenic reads was decreased on the HiSeq platform.To determine the accuracy of transcript coverage, we evaluated the on- and off- target reads in each of the paired FFPE and FF samples. There were no significant differences between on-target, intergenic and intronic aligned reads on the MiSeq compared to the HiSeq platform Fig. . Howeverrms Fig. . The vas01) Fig.  and b. Ip < 0.0001) better on the HiSeq platform compared to the MiSeq platform, for all transcripts, protein-coding transcripts and those belonging to the TNBC centroid used to define TNBC subtypes, suggesting that MiSeq platform may not be sufficient for accurate transcript abundance estimation  , demonstrating a high degree of similarity between gene expression profiles of matched FF and FFPE samples, regardless of platform  samples compared to MiSeq (0.83 +/− 0.08) pairs. However, the MiSeq correlations were significantly affected by sample age, as four tissue samples were >10 years from collection. Correlations between FF and FFPE were significantly better in paired samples collected more recently (< 4 years) versus older pairs (> 10 years)  of transcripts were differentially expressed on the HiSeq platform and 28%  of transcripts differentially expressed on the MiSeq platform , but not the MiSeq platform   and most were in non-coding genes that included antisense, long non-coding RNA (lincRNA), small nuclear RNA (snRNA), small nucleolar RNAs (snoRNA), microRNA (miRNA), rRNA, 3′ noncoding (ncRNA) and pseudogene transcripts (Table p < 2.2e-16)  versus FFPE (48%). To better understand the differences in mRNA species isolated from matched FF and FFPE samples, we performed gene ontology (GO) and pathway analysis on differential protein coding transcripts that were enriched in FF or FFPE. Pathway analysis showed a typical distribution of proteins across cellular compartments (GO C5) in FF samples Table  and an u% versus 16) Fig.  and b. T16) Fig.  and d.TaTo determine if TNBC subtyping can be extended to FFPE samples profiled by RNA-seq, we performed subtyping on gene expression data derived from RNA prepared from 21 matched FF and FFPE pairs and sequenced on a HiSeq or MiSeq. Using the TNBCtype algorithm on samples sequenced on the HiSeq, we obtained subtype calls for 10 FF and 9 FFPE samples .p = 0.048) than the HiSeq and weaker correlations to each of the subtypes, demonstrating increased sequencing depth can increase prediction confidence and reproducible subtyping  between FF and FFPE sample sequenced on the HiSeq Fig. . Evaluating Fig. . Correlaing Fig. .Fig. 6AcTo determine if differential transcripts identified between FF and FFPE preparation of tissue affect TNBC subtype calls, we performed subtyping using only genes with similar expression between both methods, resulting in 1685 genes instead of full 2188 genes for centroid correlation. There were no differences in subtype calls between the non-differential genes (1685) and the full centroid, demonstrating the robustness of subtype prediction  and only those high confidence samples resulted in identical calls. There are several variables that can decrease prediction confidence including intratumoral and tissue heterogeneity  in addition to biopsy sampling location. Further, we show that the accuracy of TNBC subtype prediction is substantially impacted by the age of FFPE samples, as FFPE blocks from patients isolated from older (>10 y) samples had a much lower accuracy than newer samples (<4 y). However, this time-dependent decrease in accuracy was not observed in FF samples, suggesting that age and storage of FFPE samples can alter transcript levels Therefore, researchers should remain cautious when performing retrospective TNBC molecular subtype analysis on FFPE tissues until further more in depth studies are performed on aged specimens.Using two different sequencing platforms, we demonstrate that sequencing depth greatly improves prediction confidence and that the Illumina MiSeq platform does not provide sufficient depth for accurate prediction when evaluating the entire transcriptome. However, the MiSeq platform may be amenable to smaller hybrid based capture of the TNBC subtype signature composed solely of 2188 gene centroid or reduced subset of the signature. Using paired FF and FFPE TNBC samples we demonstrated significant differences in transcript type abundance. These were largely attributed to RNA isolation methods. While Poly-A of FF samples yields a higher degree of on-target reads compared, poly-A selection has inherent 3′ selection bias, resulting in an underrepresentation of longer protein coding transcripts compared to ribosomal depleted FFPE samples. Since poly-A selection is not possible for heavily degraded FFPE tissues, RNA isolation by ribosomal depletion must be performed and in a higher degree of off-target reads that map to intergenic or intronic regions from nascent unprocessed transcripts. In addition, ribosomal depletion needed for FFPE sample processing results in the retention of a significant amount of non-poly (A) transcripts such as miRNA, lnRNAs, snoRNAs and snRNAs. Therefore, investigators should be cautious in reducing large gene signatures to smaller clinically feasible assays and applying these tests between FF and FFPE tissues. In general, large transcripts and non-poly A RNA species should be avoided to yield similar results between tissue preparations. We anticipate these differences would be diminished when FF samples are isolated with similar methods.Interestingly, while nearly 23% of the TNBC subtype genes were differentially expressed between matched FF and FFPE due to differing RNA enrichment methods, overall subtype calls were not affected. Since large gene signatures are not practical for clinical assay development, the TNBC subtype predictor will require gene set size reduction as to accommodate easier development of clinical diagnostic tools. This comparative study of matched FF and FFPE samples defines differentially expressed genes that should be avoided when performing future gene set reduction to smaller, clinically achievable signatures.In this study, we determined that TNBC subtype transcript classifications were reproducible between microarray and RNA-seq platforms. Further, using matched FF and FFPE samples, we demonstrated that TNBC subtypes could reliably be identified from FFPE samples with greater prediction confidence in samples less than <4 y old and samples sequenced at higher depth. TNBC subtype calls between FF and FFPE samples were identical when evaluating high-confidence samples. While there were consistent differentially expressed genes between FF and FFPE, the majority of these transcripts were the result of different RNA isolation methods. However, the knowledge of differential gene transcript representation due to RNA isolation methods can identify transcripts that should be excluded f when applying gene set size reduction strategies required for clinical implementation.Additional file 1:Table S1. TCGA microarray and RNA-seq comparison. TCGA analysis of TNBC subtype using gene expression obtained from matched fresh-frozen specimens profiled by microarray and RNA-seq. (XLSX 106 kb)Additional file 2:Figure S1. TNBC subtype correlation between RNA-seq and microarray. Correlations to TNBC subtypes do not differ with data sets generated from microarray or RNA-seq platforms. Correlations to TNBC subtypes do not differ with data sets generated from microarray or RNA-seq platforms. Scatterplots show the gene expression correlation values to TNBC subtypes (A) BL1 (B) BL2 (C) M and (D) LAR for paired samples processed by microarray and RNA-seq platforms. (TIFF 1568 kb)Additional file 3:Table S2. Samples sequenced. Sample type, processing and sequencing. (XLSX 51 kb)Additional file 4:Figure S2. Comparison of read alignment for FF- and FFPE-derived RNA samples sequenced on MiSeq and HiSeq. Comparison of read alignment for FF- and FFPE-derived RNA samples sequenced on MiSeq and HiSeq. Distribution of unmapped, on-target and off-target (intronic and intergenic) reads for individual FF and FFPE paired samples sequenced on the (A) HiSeq or (C) MiSeq. Boxplots shows the number of mapped reads from FF an FFPE samples sequenced on the (B) HiSeq or (D) MiSeq. (E) Boxplot show distribution of unmapped reads (%) from FF and FFPE samples obtained from new (<4 y) or old (>10 y) samples. (TIFF 833 kb)Additional file 5:Figure S3. Specimen age correlation. Tumor specimen age decreases transcript correlation of sequenced FF- and FFPE-derived RNA samples. Tumor specimen age decreases transcript correlation of sequenced FF- and FFPE-derived RNA samples. Boxplots show correlation (Spearman) for (A) all transcripts or (B) non-differential transcripts between matched FF and FFPE specimens by sequencing method and age of sample . (TIFF 606 kb)Additional file 6:Figure S4. Differential expression of paired samples using MiSeq. Comparison of gene expression from paired FF- and FFPE-derived RNA samples before and after differential transcript removal. Comparison of gene expression from paired FF- and FFPE-derived RNA samples before and after differential transcript removal. Heatmap displays (A) unsupervised hierarchical clustering, (B) sample-wise correlation coefficients and (C) principal component analysis (PCA) for all transcripts  or (D) hierarchical clustering (E) sample-wise correlation coefficients and (F) PCA for transcripts remaining after removal of differentially expressed genes between FF and FFPE . (TIFF 3206 kb)Additional file 7:Table S3. Differential gene expression. Differentially expressed genes between 21 paired FF- and FFPE-derived RNA samples from TNBC tumors. (XLSX 2255 kb)Additional file 8:Table S4. TNBC subtype comparisons after removal of differentially expressed genes. TNBC subtype comparison between FF and FFPE samples after differential gene removal. (XLSX 21 kb)