The tremendous progress made in unraveling the complexities of human immunodeficiency virus (HIV) replication has resulted in a library of drugs to target key aspects of the replication cycle of the virus. Yet, despite this accumulated wealth of knowledge, we still have much to learn about certain viral processes. One of these is virus assembly, where the viral genome and proteins come together to form infectious progeny. Here we review this topic from the perspective of how the route to production of an infectious virion is orchestrated by the viral genome, and we compare and contrast aspects of the assembly mechanisms employed by HIV-1 with those of other RNA viruses. Production of infectious viral progeny is the ultimate aim of the period of residence of a virus within a cell. Formation of viable virion particles during the later stages of the replication cycle is complex and requires coordination, by the virus, of a large number of cellular and viral factors many of which are proteins. Often overlooked in RNA viruses is the central controlling role of the one molecule that is present throughout this process—the viral genome. The packaged RNA is a key player in this highly organized sequence of events and they illustrate the protean capabilities of this molecule in directing cellular functions.cis acting elements , the unspliced RNA is also packaged into virions as the viral genomic RNA (gRNA). Dimerization of gRNA allows recognition and capture by the Gag protein. gRNA, however, is not a passive player in HIV-1 virus production; indeed, RNA-directed control of assembly is evident in other retroviruses, but also in more distantly related RNA viruses.Following the export of unspliced human immunodeficiency virus type 1 (HIV-1) mRNA from the nucleus into the cytoplasm, the 9 kb transcript plays a central role in the formation of new infectious virions . It servTranslation: In HIV-1 and feline immunodeficiency virus (FIV) gRNA control begins at the stage of translation to produce Gag and Gag-Pol. A conformational RNA switch in the 5’ untranslated region (UTR) of the RNA affects the balance between translation and packaging from the same template by altering exposure of the start codon and the elements required for genome dimerization and packaging [ackaging ,3,4,5,6.ackaging ,8.Genome capture: Viral RNA molecules act as scaffolds tethering adjacent Gag proteins through their nucleocapsid (NC) domains [ domains ,10 allow domains  before t domains ,13,14.Virion particle formation: Multimerization of Gag to form immature virus particles occurs at the plasma membrane; HIV-1 gRNA act as nucleation sites for the assembly of immature virions [φ6 [ virions ,16,17. Aions [φ6 ,19. DespRelease from the cell: HIV-1 Gag engages with the host endosomal sorting complexes required for transport (ESCRT) machinery to bud from the cell [cis-acting packaging elements [the cell ,21; subselements ,24,25,26elements  in additelements .This review traces the journey taken through the cell by RNA genomes, leading to viral assembly and release, highlighting the experimental data that demonstrates a role for the RNA in late stages of the virus replication cycle. Although focusing on HIV-1, we refer to other RNA viruses to illustrate themes common to different viral families. Critical steps leading to RNA encapsidation regulated by the genome can be briefly summarized thusly:cis- and trans-acting packaging determinants [cis-acting sequences involved in packaging include stem-loop 3 (SL3) [Packaging of the HIV-1 genome is a highly specific process. The major structural protein Gag packages dimers of full-length viral RNA with much greater specificity than spliced viral and cellular RNA species, due to the presence of highly conserved rminants ,30. The  3 (SL3)  and stem 3 (SL3)  in the 5 3 (SL3) ,33,34. S 3 (SL3)  in contr 3 (SL3)  and smal 3 (SL3) , in whic 3 (SL3) , thus pa 3 (SL3) . A domai 3 (SL3) . The zin 3 (SL3) .Unspliced gRNA acts as both a template for translation and as the genome to be packaged, implying a requirement for a control mechanism to regulate the balance between these mutually exclusive processes. There is long established evidence for the HIV-1 leader RNA adopting different conformations from studies using differences in electrophoretic mobility . AdvanceLys3, the host RNA used to prime HIV-1 reverse transcription, promotes formation of the dimerization-competent structure over the translation-competent structure [In vitro, the structural change in the 5’ UTR can be triggered by binding of NC protein . During tructure ,48.Although distinct from HIV-1 in overall structure, the packaging signal region of another lentivirus, FIV, also adopts two conformations that regulate the balance between translation, dimerization and packaging . The morIn recent years a clearer picture has emerged of the spatiotemporal dynamics of the HIV-1 Gag-gRNA interaction, thanks to elegant studies which enable visualization of the two molecules simultaneously in live cells ,52,53,54Recent studies using RNA constructs containing tags for binding of fluorescent fusion proteins suggested that gRNA moves through the cytoplasm in a random diffusive manner, both in the absence and presence of Gag , implyinIn summary, upon entering the cytoplasm following transcription and nuclear export, HIV-1 gRNA acts initially as a template for Gag translation, but following a structural switch in the 5’ UTR ,3,4,5 hi2 (a phospholipid found exclusively on the plasma membrane), enabling a stable anchor to form specifically at this site and avoiding unproductive anchoring to internal membranes [The matrix (MA) domain of HIV-1 Gag undergoes co-translational addition of myristic acid to its N-terminal glycine, ultimately enabling it to embed into the plasma membrane for early virion assembly . Initialembranes ,59.2, but not with control liposomes lacking this phospholipid [Apart from the NC region, the MA domain of HIV-1 Gag can also bind nucleic acid ,62,63,642, demonstrating that certain residues in MA are responsible for inhibiting promiscuous binding of the protein to internal cellular membranes [2 causes significantly more Gag to bind to the liposomes but, in the presence of the K25T/K26T mutations, this increase in binding is reduced.Mutation of lysine residues at MA positions 25 and 26 to threonine leads to enhanced binding to liposomes lacking PIPembranes . Since t2 [An RNA aptamer, identified by in vitro genetic selection , with a 2 , suggestThe domains of Gag are connected by flexible linkers and in solution MA appears able to fold back into close proximity to NC . AdditioDefects in Gag localization to the plasma membrane are linked to impaired export of HIV-1 gRNA from the nucleus ,14,73. AOnce at the plasma membrane, oligomers of Gag begin to assemble into higher-order structures mediated by contacts between adjacent MA, CA, and NC regions . This isHIV-1, like other retroviruses, packages two copies of its genome, detected as a stable non-covalently-linked dimer in virions. Whether Gag recognizes a dimer or two monomers that subsequently dimerize has been the subject of lengthy debate (reviewed in ) complicIn other RNA viruses, such as MS2 and satellite tobacco necrosis virus (STNV), multiple packaging signals are spaced in such a way as to allow cooperative binding of coat protein subunits ,83,84. Iφ6, a double-stranded RNA virus which packages exactly one of each of three genome segments into its capsid [In the above examples RNA acts as a nucleator for assembly of the viral capsid. An alternative, but less common, method by which viruses package their genomes is to produce the capsid and then for gRNA to be actively transported into the preformed structure, in a manner similar to some DNA viruses, such as the herpesviruses. A well-studied example of this mechanism in RNA viruses is the bacteriophage s capsid . The pacs capsid . To expls capsid . This mos capsid ,86. Altes capsid , consists capsid .φ6 thus illustrates an alternative to the ‘nucleation’ mechanism of assembly in HIV‑1 and other RNA viruses. However, the common theme is that gRNA actively influences packaging and infectious particle assembly.Packaging in HIV-1 hijacks the host ESCRT machinery to bud from the plasma membrane, recruiting TSG101 and ALIX through the PTAP and YPXnL motifs, respectively, both of which are found in the p6 domain of Gag ,21. ESCRThe PTAP motif in p6 recruits TSG101 (a member of ESCRT-I) which signals through ESCRT‑II —which alIn addition to the PTAP and YPXnL motifs in p6, in vitro pulldown experiments have shown that ALIX and TSG101 also interact with the NC domain of Gag ,27. ThisHIV-1 is remarkably efficient at packaging RNA into virions, with a recent study finding that >90% of virions contain gRNA . An attrDuring, and after, budding of virions from the plasma membrane, the Gag polyprotein undergoes a coordinated series of cleavages by the viral protease ,95,96. TMutations in the RNA packaging signals in both HIV-1 and HIV-2 result in Gag processing defects that affect particle morphology and, thus, infectivity ,23,24; sMutations in and around the packaging signal region of the HIV-1 genome drive evolution of compensatory mutations in long-term culture ,102,103.Although substituting the NC domain of Gag with a leucine zipper motif in the context of a full-length proviral clone does not completely block production of mature virions, the majority of particles display mildly or severely aberrant morphology . This fiGenome packaging in RNA viruses encompasses a multifaceted interplay between the viral genome and both cellular and viral factors. Constraints on genome size mean that RNA viruses have evolved many stratagems to enable them to use sequences, structures, and switches in gRNA to direct their assembly without requiring additional coding capacity. Increasing knowledge of the mechanisms used to coordinate this process will teach us more about basic molecular biology and provide new targets for treatment of RNA virus infections, particularly where the sequences involved are in highly-conserved regions of the genome, such as the 5’ UTR of HIV-1, which make the barriers to drug resistance high.


Nicotiana benthamiana 16C lines, to allow a comparison of relative RNA silencing suppressor strength. It is shown that NSs of all three tospoviruses are suppressors of local and systemic silencing. Unexpectedly, suppression of systemic RNA silencing by NSsTYRV was just as strong as those by NSsTSWV and NSsGRSV, even though NSsTYRV was expressed in lower amounts. Using the system established, a set of selected NSsTSWV gene constructs mutated in predicted RNA binding domains, as well as NSs from TSWV isolates 160 and 171 (resistance breakers of the Tsw resistance gene), were analyzed for their ability to suppress systemic GFP silencing. The results indicate another mode of RNA silencing suppression by NSs that acts further downstream the biogenesis of siRNAs and their sequestration. The findings are discussed in light of the affinity of NSs for small and long dsRNA, and recent mutant screen of NSsTSWV to map domains required for RSS activity and triggering of Tsw-governed resistance.RNA silencing is a sequence-specific gene regulation mechanism that in plants also acts antiviral. In order to counteract antiviral RNA silencing, viruses have evolved RNA silencing suppressors (RSS). In the case of tospoviruses, the non-structural NSs protein has been identified as the RSS. Although the tomato spotted wilt virus (TSWV) tospovirus NSs protein has been shown to exhibit affinity to long and small dsRNA molecules, its ability to suppress the non-cell autonomous part of RNA silencing has only been studied to a limited extent. Here, the NSs proteins of TSWV, groundnut ringspot virus (GRSV) and tomato yellow ring virus (TYRV), representatives for three distinct tospovirus species, have been studied on their ability and strength to suppress local and systemic silencing. A system has been developed to quantify suppression of GFP silencing in  In plants RNA silencing, besides playing a major role in host gene regulation, is also part of the innate immune system, targeting the nucleic acids of viruses and other molecular parasites, leading to their degradation or translational arrest , 2. In oSystemic silencing is the non-cell autonomous arm of RNA silencing and is also part of the plant innate immune response against viruses . During Bunyaviridae, a family that primarily consists of animal-infecting viruses. Like all members of this family, tospoviruses (type species: Tomato spotted wilt virus) contain three RNA genome segments of negative/ambisense polarity, denoted Large (L), Medium (M) and Small (S) according to their size. To counteract RNA silencing, TSWV encodes a nonstructural protein (NSs) that exhibits RSS activity [TSWV has also been briefly reported to suppress systemic silencing [TSWV is able to bind long and small (si- and micro- (mi)) dsRNA, indicating that NSsTSWV likely suppresses RNA silencing by sequestering long and small dsRNAs to respectively prevent cleavage by dicer-like proteins (DCLs) and uploading into RISC [Tospoviruses are the plant-pathogenic members of the activity , 16. Whiactivity , 18, resactivity . Besidesnto RISC . TSWV NSnto RISC . Althougnto RISC . For gronto RISC . Recentlnto RISC .GRSV) and tomato yellow ring virus , two distinct tospoviruses classified respectively in the American and Eurasian clades, have been shown to exhibit affinity for small and long dsRNA as well [GRSV also contains a WG/GW motif like NSsTSWV, but NSsTYRV does not, while on the other hand both NSsGRSV and NSsTYRV contain a Walker motif A indicative of putative NTPase/phosphatase activity. Although most tospovirus NSs proteins have not yet been studied on their ability to suppress RNA silencing to the extent of NSsTSWV and a generic mode of RNA silencing suppression is anticipated for all tospovirus NSs proteins, the presence or absence of motifs from certain NSs proteins raises the possibility of differences in their mode of action.The NSs from groundnut ringspot virus  of systemic GFP silencing. This system was additionally employed to functionally analyze NSs proteins from silencing-compromised TSWV isolates (160 and 171) and NSsTSWV gene constructs, mutated in predicted RNA binding domains, on their ability to suppress systemic GPF silencing.In the present study, a quantifiable system on systemic RNA silencing suppression was established, using transgenic sing GFP , 25, to TSWV [Due to the affinity of tospoviral NSs for small si- and miRNAs , NSs is TSWV  and exteN. benthamiana 16C (GFP transgenic) were co-agroinfiltrated with pBinGFP and pBinGUS (as a non-RSS). At 17 days post agroinfiltration (dpa)  systemic silencing was developed. To this end, individual leaves of ten on (dpa)  the six on (dpa) . Based oon (dpa) . Althougon (dpa) .°. The second (oldest) infiltrated leaf (L3) was located about 180° from leaf L4. Since systemic GFP silencing was always absent or very weak in leaves L5 and L6, these leaves were left out during the remainder of the analysis. In light of its angular position, leaf L9 was closest to the infiltrated leaf L4, followed by leaf L7, while leaves L8 and L10 were respectively the first and second closest ones to the (oldest) infiltrated leaf L3  agroinfiltrated leaves . To this leaf L3 . AccordiTSWV using the established VSSI and DSSI systems as described above. To this end, L4 leaves from N. benthamiana 16C plants were co-agroinfiltrated with a fixed amount of A. tumefaciens suspension containing pBinGFP and varying amounts of A. tumefaciens  0.25 and 0.5) containing binary constructs of NSsTSWV. Suppression of systemic GFP silencing was determined in leaves L9 by VSSI and DSSI. As positive and negative controls respectively P19 and GUS were included in the experiment. Since our experience during earlier experiments already indicated that transient NSsTSWV expression levels were always higher from the  binary vector pBin19 compared to pK2GW7 (Gateway vector), experiments to demonstrate a dose-dependent suppression of systemic GFP silencing by NSsTSWV were performed using both binary vectors. At 17 dpa GFP silencing was clearly visual in leaves L7 to L10  suspensions with higher OD were infiltrated , the additional use of different antisera for detection of NSs proteins, i.e. a polyclonal antiserum against TSWV NSs (anti-NSsTSWV) for detection of TSWV and GRSV NSs, and a monoclonal antibody against Asian tospovirus types of NSs for detection of TYRV NSs [Prior to a comparative analysis of TSWV, GRSV and TYRV NSs proteins on the suppression of systemic GFP silencing, NSsilencing . The GFPng -fusion constructs were made and used. An earlier study already showed that a N-terminal his-tag fusion to the NSsTSWV protein did not hamper its RNA silencing suppressor activity [N. benthamiana to analyze suppression of local GFP silencing. As positive and negative controls, respectively the untagged wild type NSs  and GUS constructs were included. In the presence of GUS, local GFP expression was almost fully silenced at five dpa, while in the presence of his-NSsTSWV, his-NSsGRSV and his-NSsTYRV high levels of GFP expression were discerned . However detection using anti-his antibody indicated relatively low levels of expression compared to those of TSWV and GRSV  determinant of the single dominant Tsw resistance (R) gene, and an extensive alanine mutant screen of NSs revealed the importance of the amino-terminus in both RSS and Avr functionality [TSWV mutants, containing mutations in predicted RNA binding domains or a putative AGO1 interaction domain (160 and NSs171) able to break Tsw resistance and hampered in their local RSS activity [N. benthamiana. In accordance to earlier data [TSWV. All other (mutant/variant) NSs constructs showed absent suppression of local GFP silencing (NSs160 and NSs-S48A/R51A) or only very low levels   .TSWV  NSs constructs, their expression was verified by western immunoblotting. Due to low expression levels of some NSs mutants, likely due to a loss of RSS activity, their detection was difficult and to solve this problem the NSs constructs therefore were co-expressed with P19 RSS. All NSs constructs were expressed but only weakly, with the exception of NSs-W17A/G18A and NSs-KKK452AAA/K457A that showed somewhat similar expression levels compared to wt NSsTSWV . The expstrength .in casu, TSWV. Here, it is shown that NSsGRSV and NSsTYRV, like NSsTSWV, are able to suppress local and systemic silencing, supporting the idea that this is a generic feature for the NSs protein from members of the Tospovirus genus. Furthermore, evidence is presented indicating that the NSsTSWV protein is able to suppress RNA silencing at another step further downstream siRNA sequestration. This is best demonstrated by the results obtained with NSs mutant W17A/G18A and NSs from the resistance breaking TSWV 171 isolate, both of which are clearly hampered in their local RNA silencing suppressor activity while they are still able to suppress systemic RNA silencing.So far, studies on the mode by which tospovirus NSs is able to suppress RNA silencing have mostly been limited to its representative, Tsw resistance gene). From this screen three NSs mutants  that mapped within two predicted RNA binding domains were further analyzed here using the established VSSI/DSSI systems. It was anticipated that in case essential RNA binding domains would be hit, those mutants would score negative on the ability to suppress systemic silencing. While mutants S48A and S48A/R51A partly or failed to suppress local RNA silencing, they showed respectively a mild and a weak suppression of systemic RNA silencing. In contrast, mutant KKK452AAA/K457A was still able to strongly suppress local and systemic RNA silencing. These data supported the idea that the first two mutants were likely affected by a genuine loss of RNA binding, while the third mutant was not, and suggested that its mutated sequence (KKKK452/K457) does not play a major role in RNA binding domain. A closer look at mutants S48A and S48A/R51A also indicated that the combined mutations of S48 and R51 were more detrimental to the ability to suppress local and systemic silencing than mutation of only S48. To further confirm the ability—or loss—of RNA binding by any of these NSs mutants, electrophoretic mobility shift assays were performed earlier but these failed due to their relatively low expression levels [Short interfering RNA molecules play a major role in local and systemic silencing as in both cases they are needed to activate an antiviral RISC. Systemic silencing however requires that siRNAs prior to this have systemically moved as a mobile signal in order to activate RISC in systemic tissues . Viral Rn levels .The fourth NSs mutant analyzed was changed at residues W17/G18, a motif that is not part of a predicted RNA binding domain . GW/WG-mTsw resistance breaking TSWV isolates (NSs171 and NSs160) were analyzed on their ability to suppress systemic silencing. Earlier, it was shown that these proteins exhibited no (NSs160) or only a weak (NSs171) ability to suppress local RNA silencing [160 showed low levels of systemic silencing suppression, NSs171 exhibited similar levels as the ones from NSs-W17A/G18A. These observations are in agreement with data from the NSs mutant screen [Tsw resistance, thus not necessarily affect its additional ability to suppress  RNA silencing. In some cases it does affect only partially and/or locally, while leaving its ability to suppress systemic silencing unaltered, like in the case of the Tsw resistance breaker isolate NSs171 and mutant NSs-W17A/G18A. A further look at the amino acid sequences of NSs171 and NSs160 revealed a single nucleotide polymorphism (proline) in NSs160 at position S48, which is in a predicted RNA binding domain [171 (which does not harbor this S48P modification).Besides the four NSs mutants, two additional NSs variants collected from ilencing , but hert screen  that havg domain , that maTSWV was shown to be dose-dependent and in agreement with earlier indications on this [TSWV suppression of systemic silencing and stresses the importance of being more cautious when viral RSS proteins fail to suppress systemic silencing [The analyses of NSs mutants/variants on their ability to suppress systemic silencing has made use of two newly developed systemic silencing index (SSI) assays, one that relies on visual index (VSSI) and a second one on a digital index (DSSI). Both indexes provide a way to study and compare the suppression of systemic silencing by different viral RSS proteins in a fixed experimental setting that only requires the infiltration of one leaf L4) and a score based on a single systemic leaf (L9). Whereas the visual index (VSSI) allows a faster categorization and can be performed when having no access to ImageJ-like analysis tools, like all other quantification systems previously described , 26, it  on this . A dose- and a scilencing , 27 as tilencing . For TSWilencing .TSWV was somewhat more strongly expressed when fused with a his-tag at its N-terminus, and as a result led to a higher level of RNA silencing suppression. Another intriguing result was the observation that his-NSsTYRV was only expressed at relatively low levels compared to his-NSsTSWV and his-NSsGRSV but still exhibited a strong ability to suppress local and systemic silencing. The reason for this is unclear. Although TYRV belongs to the Eurasian clade of tospoviruses and is more distantly related from American clade tospoviruses (TSWV and GRSV) [N. benthamiana. However, when compared to results from his-NSsTSWV and his-NSsGRSV, the observation that his-NSsTYRV has lower expression but similar RNA silencing suppression strength implies it has a more efficient strategy or an alternative mode of action to suppress silencing, e.g. a stronger affinity to (short and long) dsRNA or the ability to target a step that is not efficiently targeted by TSWV and GRSV NSs. This, however, still remains to be further investigated.During the comparative analysis of tospoviral NSs proteins it was interesting to see that NSsnd GRSV) , 35, a dIn conclusion, here we have established a new and quantifiable systemic silencing system to investigate the suppression of systemic RNA silencing and demonstrated a dose-dependent suppression by viral RSS proteins. Combined with data from local silencing suppression assays this system will be very useful for initial characterization of RSS proteins and providing further support for the identification of predicted RNA binding domains. Based on data from a selected set of NSs mutants and variants we have also obtained further evidence that point towards the ability of TSWV NSs to interfere in the RNA silencing pathway further downstream siRNA biogenesis and sequestration and in which residues W17/G18 may play an important role.Nicotiana benthamiana and a GFP transgenic 16C line of N. benthamiana [Agrobacterium tumefaciens strain COR308 [thamiana , 25 weren COR308 , 37 was N. benthamiana. To this end, A. tumefaciens were transformed with the binary expression vectors and a single colony grown overnight  in LB3 medium  under proper antibiotics selection pressure (100 μg/ml kanamycin (pBin19) or 250 μg/ml spectinomycin (pK2GW7), and 2 μg/ml tetracycline). From the overnight culture, 600 μL were inoculated in 3ml of induction medium 2SO4, 0.5 g/L Sodium Citrate Dihydrate, 0.25 g/L MgSO4, 0.2% (w/v) glucose, 0.5% (v/v) glycerol, 50 mM acetosyringone and 10 mM MES pH5.6) and incubated overnight at 28°C, while shaking at 180 rpm. The next day, cells were pelleted at 4000 rpm for 15 min. and resuspended in Murashige-Skoog (MS) medium to an optical density at 600 nanometer (OD600) of 1.0 or 0.5. Agroinfiltrations were performed at the basal  side of leaves.Transient expression assays were performed by agroinfiltration of binary vector gene constructs in TSWV [TSWV, NSsGRSV, NSsTYRV [TSWV, 6xhisNSsGRSV, 6xhisNSsTYRV, GUS were generated by polymerase chain reaction (PCR) amplification using specific primers to introduce the 6xhis-tag sequence at the 5’end of the gene. The his-NSs coding sequences were cloned in GATEWAY vector pK2GW7 [TSWV gene from isolates BR01 (wild type), resistance breaker isolates 160 and 171 and mutants W17A/G18A, S48A, S48A/R51A, KKK452AAA/K457A were previously described [Binary vector pBin19 constructs with GFP, tombusviral P19 and tospoviral NSsTSWV , 38, as  NSsTYRV  were desr pK2GW7  using GAescribed , 28N. benthamiana 16C constitutively expressing GFP [For the induction of systemic GFP silencing, 3–4 weeks old seedlings of sing GFP  were agrN. benthamiana 16C were agroinfiltrated with pBinGFP for the induction of systemic GFP silencing in the absence or additional presence of a binary vector NSs (mutant/variant) gene construct (previous section). Determination of the Visual Systemic Silencing Index (VSSI) was as follows: systemic silencing in leaves was visually classified into six levels  were also analysed with the Systemic Silencing Indexes, as a background control.In each experiment, 10 plants x levels  and rangDetermination of the Digital Systemic Silencing Index (DSSI) was performed by digital analysis of pictures taken from the four most top leaves  . DigitalWestern immunoblot analysis was performed as previously described . DetectiS1 Fig(TIF)Click here for additional data file.S2 FigAngular leaf position (0–360 degrees) of leaves L7—L10 and the agroinfiltrated leaf L3 relative to agroinfiltrated leaf L4 (which was the reference and set at zero degrees).(TIF)Click here for additional data file.S3 FigDetection was performed using antiserum against TSWV NSs. Marker sizes are indicated at the left hand side.(TIF)Click here for additional data file.S4 FigN. benthamiana 16C plants were agroinfiltrated at leaf L4 with GFP and GUS or P19 or TSWV NSs (in vector pBin19 and pK2GW7) with different OD600 as indicated. Leaf L9 was visually scored 17 days after agroinfiltration. Error bars indicate the standard error of the mean (SEM) (n = 15).(TIF)Click here for additional data file.S5 FigAgroinfiltration was performed on leaf L4. Leaf L9 was visually scored 17 days after agroinfiltration. Error bars indicate the standard error of the mean (SEM) (n = 15).(TIF)Click here for additional data file.S6 FigAgroinfiltration was performed on leaf L4. Leaf L9 was visually and digitally scored 17 days after agroinfiltration. Error bars indicate the standard error of the mean (SEM). For each NSs construct, 15 plants were agroinfiltrated, and seven plants were agroinfiltrated with GUS.(TIF)Click here for additional data file.


It has been known for a number of years that only about 2% of this RNA encodes proteins. However, numerous studies employing both tiling arrays and high-throughput sequencing found that the genome is pervasively transcribed, with most DNA copied, at least at some point in time, into RNA. Indeed, Birney et al.  estimateWhile much remains to be learned, we are truly at the frontier of important discoveries in the lncRNA field. The articles in this special issue continue this exciting trend connecting lncRNAs and cellular function, focusing particularly on their roles in development, metabolism, and association with the disease.Several papers address the connection between lncRNAs and metabolism. Kameswaran and Kaestner  discuss Aplysia californica, which is a natural antisense RNA from the sensorin gene and it plays an important role in neuronal function and aging.The role of lncRNAs in the nervous system are also addressed. Clark and Blackshaw  and Vuciin vivo functions.Finally, there is an opinion article Kohtz,  by KohtzThe 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.


Triticum aestivum L.) by Wheat streak mosaic virus  and Triticum mosaic virus  of the family Potyviridae causes synergistic interaction. In this study, the effects of the synergistic interaction between WSMV and TriMV on endogenous and virus-derived small interfering RNAs (vsiRNAs) were examined in susceptible (‘Arapahoe’) and temperature-sensitive resistant (‘Mace’) wheat cultivars at 18°C and 27°C. Single and double infections in wheat caused a shift in the profile of endogenous small RNAs from 24 nt being the most predominant in healthy plants to 21 nt in infected wheat. Massive amounts of 21 and 22 nt vsiRNAs accumulated in singly and doubly infected Arapahoe at both temperatures and in Mace at 27°C but not 18°C. The plus- and minus-sense vsiRNAs were distributed throughout the genomic RNAs in Arapahoe at both temperature regimens and in Mace at 27°C, although some regions served as hot-spots, spawning an excessive number of vsiRNAs. The vsiRNA peaks were conserved among cultivars, suggesting that the Dicer-like enzymes in susceptible and resistant cultivars similarly accessed the genomic RNAs of WSMV or TriMV. Accumulation of large amounts of vsiRNAs in doubly infected plants suggests that the silencing suppressor proteins encoded by TriMV and WSMV do not prevent the formation of vsiRNAs; thus, the synergistic effect observed is independent from RNA-silencing mediated vsiRNA biogenesis. The high-resolution map of endogenous and vsiRNAs from WSMV- and/or TriMV-infected wheat cultivars may form a foundation for understanding the virus-host interactions, the effect of synergistic interactions on host defense, and virus resistance mechanisms in wheat.Co-infection of wheat ( Co-infection of plants with two or more viruses is common in nature because plants are susceptible to multiple viruses. Additionally, many hemipteran vectors transmit more than one virus, thus causing mixed infections by related or unrelated viruses Plant viruses are considered to be strong inducers as well as targets of host RNA silencing. RNA silencing is one of the most important antiviral defense mechanisms used by plants against viral infections Arabidopsis thaliana (L.) Heynh, 4 DCLs, 10 AGOs, and 6 RDRs have been identified Oryza sativa L.). So far, in rice, 8 DCLs, 19 AGOs and 5 RDRs have been identified A. thaliana suggests that different RNA silencing pathways might be utilized by these two angiosperms. The mechanisms of RNA silencing were extensively studied in A. thaliana using mutant plants that defined the roles of DCLs, AGOs and RDRs in RNA silencing A. thaliana have been implicated in the formation of vsiRNAs Both monocotyledonous and dicotyledonous plants contain DCL ribonucleases, AGOs and RDRs, the core components of host RNA silencing Triticum aestivum L.) is the world’s most widely grown crop, covering 200 million hectares with an annual production of 681 million tons in 2011, slightly behind maize (Zea mays L.) and rice, providing the primary source of carbohydrates, proteins, vitamins, and minerals for the world’s population Wheat streak mosaic virus (WSMV) is the most economically important virus causing significant yield losses Triticum mosaic virus (TriMV), a new virus, was reported from several Great Plains states Tritimovirus and Poacevirus genera, respectively, in the family PotyviridaeAceria tosichella Keifer, the wheat curl mite Wsm-1 gene, which is also found to provide similar levels of resistance to TriMV Wsm-1 was introduced to wheat from the related perennial grass Thinopyrum intermedium (Host) Barkworth & D.R. Dewey Wheat  seedlings at the single leaf stage g for 15 min at 4°C. Total RNA was precipitated from the 3 ml aqueous phase by adding an equal volume of isopropanol and incubated at room temperature for 10 min. The RNA was pelleted at 12,000×g for 10 min at 4°C, and the pellet was washed with 5 ml of 70% ethanol. The air-dried RNA pellet was suspended in 500 µl of sterile water and stored frozen at –70°C. The amount of total RNA was quantified using a NanoPhotometer .One gram of fully expanded upper leaves of wheat infected with WSMV, TriMV, WSMV plus TriMV, or healthy plants was ground in liquid nitrogen into a fine powder, followed by the addition of 5 ml of TriPure isolation reagent . The tissue was ground thoroughly and the extract was transferred to an Oak ridge tube. The mortar was washed with an additional 2 ml of TriPure isolation reagent. The extract was vortexed for 30 s, followed by the addition of 1.4 ml of chloroform and vortexed for 30 s. This mixture was incubated at room temperature for 10 min, followed by clarification at 12,000×Two µg of total RNA was separated on 15% polyacrylamide-urea gels , followed by electro-transfer to Nylon membranes (Roche). Nylon membranes were probed with DIG-labeled minus-strand RNA riboprobes specific to nt 6303 to 9384 of WSMV or nt 6401 to 10,245 of TriMV. These probes were further hydrolyzed into ∼50 nt long RNA pieces by treatment with sodium carbonate as described in Dalmay et al. Thirty µg of total RNA was denatured in the presence of 47.5% formamide, 0.1X TBE buffer plus 0.015% of each bromophenol blue and xylene cyanol FF at 95°C for 4 min, followed by incubation on ice for 5 min. Denatured total RNA was separated on a 15% polyacrylamide-urea-TBE gel (Bio-Rad) at 120 V until the bromophenol blue reached the bottom of the gel. Gel slices from just below the center of the xylene cyanol band and extending to three-quarters of the way toward the bromophenol blue band were collected into a 30 ml corex tube containing 5 ml of 0.3 M sodium chloride. The gel slices were crushed into small pieces with a 10 ml syringe piston and incubated in a shaker at 4°C overnight. The supernatant was collected after centrifugation at 10,000 g for 15 min at 4°C. Two ml of 0.3 M sodium chloride was added to acrylamide pieces and incubated in a shaker for 1 h at room temperature. The small RNAs were precipitated from the pooled supernatants by addition of 3 volumes of ice-cold ethanol in the presence of 0.3 M sodium acetate, pH 5.2 and 2 µl of glycogen (Roche), and incubated at −70°C for 1.5 h. The small RNAs were suspended in 350 µl of 0.3 M sodium chloride and loaded onto a spin-x-cellulose acetate filter . The spin column was centrifuged at 10,000 g for 2 min at room temperature. The small RNAs were precipitated from the elutant by adding 3 volumes of ethanol in the presence of 0.3 M sodium acetate and 1 µl glycogen for 30 min at −70°C, followed by centrifugation at 12,000 g for 15 min at 4°C. The RNA pellet was washed with 70% ethanol, and the air dried small RNA pellet was suspended in 10 µl sterile water and stored at −70°C.Small RNA libraries were prepared from gel-eluted small RNA fractions of total RNA using Illumina TruSeq small RNA Sample Prep Kit , essentially as described in the manufacturer’s instructions at the University of Nebraska-Lincoln Genomics Core Research Facility. Illumina TruSeq SR Cluster Generation Kit v5 was used to generate the cluster at one sample per lane. Amplified library was sequenced on Illumina Genome Analyzer IIx using a 36-cycle sequencing kit to read 36 nts of sequence from a single end of each insert by standard v8 protocol. The raw sequence reads for all 16 samples were deposited in the GEO Omnibus under accession GSE54026.cut-adapt tool  was removed; for both the healthy and virus-infected samples, small RNAs were size-selected between 18 to 26 nucleotides (inclusive) and reads containing alignment mismatches, or that do not map uniquely, were removed. For the samples with the double virus infection, any RNAs that cross match between the two viruses were removed as well.MATLAB  was used to generate coverage graphs of the small RNAs on the virus genomes.Chi-square analysis was used to determine whether the treatments induced statistically significant changes in the distribution or composition of small RNAs. For each cultivar and temperature treatment, the observed distribution (as percent) of sRNA from 20 to 25 nt in healthy tissue was used as the “expected” class in chi-square calculations.The effect of the synergistic interaction between WSMV and TriMV on the accumulation of vsiRNAs in wheat cultivars Arapahoe and Mace at 18°C and 27°C was examined by Northern blot hybridization of total RNA using strand-specific digoxigenin (DIG)-labeled riboprobes. The riboprobes hybridized neither with total RNA from healthy wheat cultivars nor another co-infecting virus, suggesting that these riboprobes are highly specific to their respective viruses . In singTo obtain insight into the mechanisms of synergistic interactions among unrelated viruses and the effects of these interactions on host defense mechanisms, the profile of endogenous small RNAs and vsiRNAs was examined from singly (WSMV or TriMV) and doubly (WSMV plus TriMV) infected wheat cultivars Arapahoe (susceptible) and Mace (temperature sensitive-resistant) at 18°C and 27°C.Composition of small RNAs obtained through Illumina Solexa high-throughput sequencing was examined by computational alignment of sequences identical or complementary to the genomes of WSMV and TriMV. Similarly, small RNAs not corresponding to the viral genomes from doubly infected wheat cv. Arapahoe at 27°C were also BLAST searched for sequences identical to the wheat genome and most of the sRNAs were aligned with the wheat genome. Since there are few gaps in the wheat genome sequence A total of 29.8 to 37.6 million reads were obtained from WSMV- and/or TriMV-infected Arapahoe and Mace at 18°C and 27°C, and 34.2 to 39.2 million reads were obtained from healthy samples . In infeIn healthy wheat cultivars Arapahoe and Mace at 18°C and 27°C, 24 nt endogenous sRNAs were the most predominant (33 to 41%), followed by 21 nt (22 to 24%), 22 nt (13 to 15%), 23 nt (9 to 10%), and 20 nt (7 to 10%) . Among eSimilarly, the shift in the profile of endogenous sRNAs was significantly different from healthy in double infections of Arapahoe at both temperature treatments and in Mace at 27°C, with 21 nt sRNAs as the most abundant (37 to 41%), followed by 22 nt (20 to 22%) and 24 nt (13 to 17%) sRNAs . Co-infeIn contrast, the profile of endogenous sRNAs in singly and doubly infected Mace at 18°C did not differ significantly from healthy ; Fig. 2,The most prevalent vsiRNAs from WSMV- and/or TriMV-infected Arapahoe at both temperatures and Mace at 27°C were 21 nt , followed by 22 nt  ; Fig. 2.In singly and doubly infected Mace at 18°C, vsiRNAs accumulated to lower levels than in Arapahoe and Mace at 27°C ; Table 3Accumulation of vsiRNAs and endogenous sRNAs was compared within a sample, but not between the samples because high-throughput sequencing of small RNAs may not reflect accurate quantitative differences between the samples due to variation in the quality and quantity of starting small RNA preparations. Hence, the pool of small RNA reads of deep sequencing most accurately represents differences within a sample but not between the samples.The effect of the synergistic interaction between WSMV and TriMV on vsiRNA biogenesis was examined by comparing vsiRNAs from singly and doubly infected wheat with those of endogenous sRNAs in Arapahoe and Mace. Accumulation of 20 to 25 nt endogenous sRNAs and vsiRNAs in singly and doubly infected Arapahoe and Mace is presented in The polarity of the most abundant 21 and 22 nt redundant vsiRNAs was analyzed and presented in Analysis of strand polarity of nonredundant vsiRNAs revealed a different picture from those of redundant vsiRNAs . NonreduThe most abundant 21 and 22 nt redundant and nonredundant vsiRNAs of WSMV and TriMV were grouped by their 5′-terminal nucleotide  as presented in We also analyzed nonredundant vsiRNAs for the 5′-terminal nucleotide from all the samples. In WSMV- and/or TriMV-infected samples, the predominant 5′-terminal nucleotide of nonredundant 21 and 22 nt vsiRNAs was A (30 to 33%), followed by G (23 to 27%), U (20 to 28%), and C (18 to 22%) . These dBecause a large number of WSMV- and TriMV-derived redundant vsiRNAs accumulated in infected wheat, the distribution of 21 to 24 nt vsiRNAs along the corresponding genomic RNAs of WSMV or TriMV was examined to reveal any hot- and cold-spot regions for vsiRNAs. A region of 5 nt or more without any 21 to 24 nt vsiRNA reads was considered to be a ‘cold-spot’, and a peak with more than 50,000 reads was considered to be a hot-spot for vsiRNAs.The genomes of WSMV and TriMV were covered completely with both plus and minus-sense polarity vsiRNAs of 21 to 24 nt in all the samples, except in Mace at 18°C. In Mace at 18°C, fewer vsiRNAs accumulated, especially in single infections with a few cold-spots without vsiRNAs in the genomes of WSMV and TriMV. WSMV-derived vsiRNAs in Mace at 18°C covered most of the genomic RNA except nt 2719, 3503 to 3505, 3843 to 3844, and 5475 to 5478. However, in doubly infected Mace at 18°C, WSMV-derived vsiRNAs covered the entire genomic RNA . In singEven though more TriMV-specific vsiRNAs accumulated in singly infected Mace at 18°C compared with those of WSMV , six colNonredundant vsiRNAs of WSMV and TriMV covered the entire respective genomic RNAs in all the samples, except in singly infected Mace at 18°C . SimilarIn WSMV and/or TriMV-infected Arapahoe at 18°C and 27°C and Mace at 27°C, 6.3 to 16.2 million reads of 20 to 25 nt plus- and minus-sense vsiRNAs accumulated in each virus infected sample . SeveralA clear difference in size and composition of vsiRNA peaks was observed between WSMV-infected Arapahoe 18°C and 27°C samples . In singSeveral vsiRNA hot-spots in the TriMV genome were also found in singly and doubly infected Arapahoe at 18°C and 27°C and Mace at 27°C . The hotIn singly and doubly infected Mace at 18°C, fewer WSMV- and TriMV-derived vsiRNAs accumulated due to its temperature sensitive-resistance, and peaks with fewer vsiRNAs were found at the same position as in Mace at 27°C .Synergistic interactions among unrelated viruses in plants have been well-documented PotyviridaeEven though WSMV and TriMV are distantly related type members of two distinct genera in the family A. thaliana and rice encode four and eight DCL proteins, respectively A. thaliana DCL proteins in the biogenesis of 21 to 24 nt vsiRNAs have been thoroughly characterized Plants have evolved to tolerate biotic and abiotic stress by reprogramming gene expression via the biogenesis of endogenous small RNAs In RNA silencing, 21 and 22 nt vsiRNAs play a crucial role in combating viral infections Turnip mosaic virusPotato virus X Citrus tristeza virusRice stripe virus are host dependent Polarity analysis of redundant vsiRNAs of WSMV and TriMV from singly and doubly infected plants revealed that the plus-sense vsiRNAs were predominant than the minus-sense, suggesting that the majority of vsiRNAs were generated from plus-sense genomic RNAs. In contrast, the plus- and minus-sense nonredundant vsiRNAs exhibited stark differences between WSMV and TriMV infection with symmetrical and asymmetrical accumulation, respectively. The polarity of nonredundant vsiRNAs might give some cues on the vsiRNA biogenesis: WSMV nonredundant vsiRNAs originate from viral dsRNAs and subsequent biogenesis of redundant vsiRNAs might be a combination of primary vsiRNAs from dsRNAs and secondary vsiRNAs by host RDRs. It is possible that TriMV-specific vsiRNAs were generated using the latter method. Several studies indicate that cloned vsiRNAs are predominantly plus-sense polarity in nature compared to those of minus-sense polarity as exemplified in The 5′-terminal nucleotides of vsiRNAs determine the vsiRNA loading preference into specific AGO complexes: vsiRNAs with a 5′-terminal U nucleotide preferentially load into the AGO1 complex, nucleotide A into AGO2 and AGO4, and C into AGO5 invivo nature of these secondary structures needs to be verified by probing with nuclease treatment.vsiRNAs were generated from most of the genomic RNAs of WSMV and TriMV in wheat cultivars, suggesting that DCL enzymes target most of genomic RNAs. However, some regions of the WSMV and TriMV genomes were found to be hot-spots for preferential excessive vsiRNA accumulation of more than 50,000 reads. More hot-spot regions in the genomes of TriMV and WSMV were found in singly and doubly infected wheat at 18°C than 27°C, suggesting that DCL enzymes at 18°C preferentially cleave more regions than at 27°C. In addition to hot-spot regions, we also found several cold-spot regions of 5 to 21 nt long in the genomic RNA of TriMV with no vsiRNA reads. In the WSMV genome, though no cold-spot regions were found, some regions had fewer reads than others. The genomic regions with hot- and cold-spots for vsiRNAs might depend on the accessibility of RNA to DCL enzymes, or the visRNAs may preferentially accumulate by associating with AGOs or with the silencing suppressor. The hot-spot regions of genomic RNA might have extensive secondary structures that are favorable for easy access to DCL enzymes. The WSMV and TriMV genomic regions with hot-spot regions were folded into stem-and-loop structures in the mFOLD program (data not shown). However, the Figure S1Distribution of nonredundant vsiRNAs throughout the genomes of WSMV and TriMV in wheat cv. Arapahoe (a) and Mace (b) at 18°C and 27°C.(PPTX)Click here for additional data file.Table S1Total number of small RNA (host and virus-derived) reads and bases obtained by deep sequencing from healthy and WSMV and/or TriMV-infected wheat cultivars.(DOCX)Click here for additional data file.Table S2Normalization of small RNAs reads (host and virus) accumulated in healthy and WSMV and/or TriMV-infected wheat cultivars Arapahoe and Mace at 18°C and 27°C against total small RNA reads accumulated in Arapahoe at 18°C.(DOCX)Click here for additional data file.


The assay measures expression of 12 cancer-related genes representing four biological pathways and 5 reference genes which are algorithmically combined to calculate the Genomic Prostate Score (GPS). This biopsy-based assay has been analytically and subsequently clinically validated as a predictor of aggressive prostate cancer. The aim of this study was to validate the analytical performance of the Oncotype DX Prostate Cancer Assay using predefined acceptance criteria.The Onco2 of the RNA input per PCR assay well. Gene assays were shown to accurately measure expression over a wide range of inputs (from as low as 0.005 ng to 320 ng). Analytical accuracy was excellent with average biases at qPCR inputs representative of patient samples <9.7% across all assays while amplification efficiencies were within ±6% of the median. Assessments of reproducibility and precision were performed by testing 10 prostate cancer RNA samples over multiple instruments, reagent lots, operators, days (precision), and RNA input levels (reproducibility) using appropriately parameterized linear mixed models. The standard deviations for analytical precision and reproducibility were 1.86 and 2.11 GPS units  respectively.The lowest quartile of RNA yields from prostate needle biopsies (six 5 μm sections) was between 19 and 34 ng. Analytical validation of the process requiring as little as 5 ng of RNA met all pre-defined acceptance criteria. Amplification efficiencies, analytical sensitivity, and accuracy of gene assays were measured by serially diluting an RNA sample and analyzing features of the linear regression between RNA expression measured by the crossing point (Cp) versus the logtype DX Prostate Cancer Assay, a clinical RT-PCR assay specifically designed for use with prostate needle biopsies, has been analytically validated using very limited RNA inputs. The assay requirements and analytical performance will provide physicians with test results from a robust and reliable assay which will enable improved treatment decisions for men diagnosed with early-stage prostate cancer.The Onco Prostate cancer is one of the most common malignancies in men with an estimated 250,000 new cases being diagnosed in the US in 2012, mostly as a consequence of PSA screening . Althougtype DX® Assays) which identify underlying biology in an individual patient’s tumor to help guide treatment decisions in invasive node negative and node positive breast cancer [in situ[type DX Breast Cancer Assay has become widely used in standard clinical practice, and is incorporated into the major oncology practice guidelines, including NCCN and ASCO [There is a growing recognition that molecular biomarkers can complement conventional clinical and pathologic parameters to personalize the care of cancer patients. However, incorporation of biomarkers into standard clinical practice requires a level of validation which is not often achieved. In order for a biomarker to enter wide clinical practice it needs to demonstrate evidence of strong analytical validity, clinical validity, and clinical utility . Indeed,t cancer -11, brea [in situ and stag [in situ-15. Sincand ASCO ,17.type DX Prostate Cancer Assay was specifically designed for analysis of fixed, paraffin-embedded (FPE) prostate needle biopsy tissue. Some of the key challenges in developing this biopsy-based assay for prostate cancer include the heterogeneous and multifocal nature of the disease, and the very small amounts of tumor tissue available from diagnostic prostate needle biopsies. Most newly diagnosed prostate cancer patients harbor low-volume disease that may be diagnosed from a single biopsy core [type DX Prostate Cancer Assay platform and enable processing of small volume tissue from prostate biopsies. Some of the most notable changes include addition of a multiplexed preamplification step after reverse transcription and combining the genomic DNA detection step with the quantitative PCR step. Considering that the RNA yields of many samples cannot be reliably measured with current methods, the sample quality is determined primarily by the expression of reference genes rather than mass as a measure of the amplifiable RNA. The analytical portion of the Oncotype DX Prostate Cancer Assay was designed to target 20 ng as the nominal input, however the assay accommodates samples with lower concentration through variable RNA inputs, thus enabling the assay to perform well with RNA inputs which are 110–180 fold lower than required by the Oncotype DX Colon and Breast Cancer Assays [type DX Prostate Cancer Assay includes 5 reference genes and 12 cancer genes representing distinct biological pathways with a known role in prostate tumorigenesis: the androgen pathway , cellular organization , proliferation (TPX2), and stromal response . Reference gene normalization is used to control for sources of pre-analytical and analytical variability as well as allow for variable RNA inputs. Reference normalized expression of the 12 cancer-related genes are used to calculate the Genomic Prostate Score (GPS), which has been shown to predict adverse prostate cancer pathology beyond conventional clinical/pathologic factors in a recently completed clinical validation study [In order to impact clinical decision-making at the time of diagnosis, the Oncopsy core . A serier Assays ,7. The Oon study .type DX Prostate Cancer Assay is well-controlled and produces reliable assessment of RNA from individual FPE prostate tumor tissue. These studies demonstrated analytical validity of the gene assays comprising the Oncotype DX Prostate Cancer Assay with respect to analytical sensitivity, bias, amplification efficiency, precision and reproducibility, and also validated the precision and reproducibility of the resulting GPS.Prior to initiation of the clinical validation study, analytical validation studies, with pre-specified endpoints and acceptance criteria, were conducted to ensure that the analytical component of the OncoFPE needle biopsies were provided by the Cleveland Clinic Pathology and Laboratory Medicine Institute and Glickman Urological and Kidney Institute  and were centrally reviewed by two pathologists (C.M-G and S.M.F). The use of the samples has been approved by the Cleveland Clinic Institutional Review Board. All biopsies were sectioned into eight 5 μm sections. The top and the bottom slides were hematoxylin and eosin (H&E) stained and the presence of tumor was confirmed by a board-certified pathologist. The tumor area was marked in the top H&E slide and the markings were transferred to the subsequent 6 unstained slides. The tumor was manually dissected from each unstained slide using a scalpel blade and transferred into a microcentrifuge tube. FPE prostate cancer samples from radical prostatectomies were purchased from ProteoGenex . The needle biopsy tumors were microdissected to exclude normal-appearing tissue. The selected radical prostatectomy blocks spanned a wide range of gene expression and range of GPS. Gleason score was assigned using the 2005 International Society of Urological Pathology Consensus guidelines [Paraffin from FPE samples was solubilized by Shandon Xylene Substitute  and removed. Tissue was lysed and protein was digested with Proteinase K . Nucleic acids were bound to paramagnetic beads using the Agencourt® FormaPure Kit  and manipulated using Tecan® liquid handling robots  with an integrated KingFisher® Flex magnetic particle processor . DNA was digested with 200 units of DNaseI . Purified RNA was released from the paramagnetic beads and suspended in water.RNA was quantified using the RiboGreen® fluorescence method  according to the manufacturer’s instructions. The limit of quantitation for the assay was 0.5 ng/μL.RNA (up to 20 ng) was converted to complementary DNA (cDNA) by combining the Omniscript® RT kit  and a specific reverse primer for each gene assay using Tecan liquid handling robots. All primers  were purchased from Integrated DNA Technologies . The RT reaction (30 μL) was incubated at 37°C for 60 minutes and then inactivated at 93°C for 5 minutes.The cDNA was preamplified using custom TaqMan® PreAmp Master Mix  and custom forward and reverse primers  for each target gene, including the control assay for genomic DNA (gDNA) detection. The reactions were assembled using Tecan liquid handling robots, placed in a thermocycler  and incubated under the following conditions: 95°C for 10 min followed by 8 cycles of 95°C for 15 sec and 60°C for 4 min.ARF1_promoter, designed to amplify a promoter region of ARF1) using Tecan liquid handling robots. QuantiTect® Primer Assay master mix  was used, and the 5 μL reaction was amplified for 45 cycles in a LightCycler® 480  under the following conditions: enzyme activation , amplification , cooling . The level of expression was calculated with the crossing point (Cp) method implemented by the Roche LightCycler 480 software version 1.5. All gene assays were measured in triplicate and required at least 2 valid wells. Oligonucleotide and amplicon sequences can be found in the Additional file The amplified product was mixed with the forward and reverse primers and probes  for each of the gene assays and for the gDNA detection assay  were selected in an independent study for their low inter-patient variability, lack of relationship to clinical outcome and robust analytical performance (data not shown). Reference gene normalization was used to adjust for potential sources of pre-analytical variability, such as fixation, RNA fragmentation and tissue quality, analytical variation including assay plate  and instrumentation (liquid handler or LC480), and varying RNA inputs (with 20 ng as the target input). Gene expression was normalized by subtracting the aggregated expression of the reference genes from the weighted mean Cp for each of the 12 informative genes and centering by adding 10 units to the result. The formula used to calculate the GPS is shown in Figure The five reference genes (TPX2 and SRD5A2), and the lower starting concentration was used for all other genes. For each starting concentration, three independent series of two-fold serial dilutions were prepared using a Tecan liquid handling robot. The serially diluted RNA was converted to cDNA, preamplified for 8 cycles of PCR and taken through 45 cycles of qPCR. The linearity of signal response between the measured gene expression (Cp) and the log base 2 of RNA concentration was evaluated for each of the individual gene assays. In total, for each gene and RNA concentration, 9-replicate PCR measurements were recorded and analyzed.Linearity was assessed by serially diluting RNA and analyzing gene expression as a function of 14 input concentrations of RNA extracted from FPE prostate tumor tissue. Two different starting RNA concentrations were used  where the higher starting concentration was used for the genes with the lowest expression levels  log base 2 RNA concentration described above.The analytical accuracy of predicted RNA concentrations relative to the (known) input RNA concentrations was estimated for each of the 17 genes separately. Specifically, for every evaluable Cp measurement, an inverse prediction of RNA concentration was derived from the final linear model:k (k = 1…14); namely, byAn estimate of the accuracy of the assay was given by the mean percent bias in prediction at each known RNA concentration Xk is the (known) input RNA concentration for the kth level and th plate , jth well  and kth RNA concentration level, mi was the number of valid wells on the ith plate, and m was the total number of valid wells across all plates. Analyses were performed using restricted maximum likelihood estimation (REML) in the PROC MIXED procedure of SAS version 9.2.where min or at the minimum concentration fulfilling the linear range criteria if the inverse prediction of ymin was less than the lower linear range limit . Analyses were performed using an iterative estimation scheme involving the PROC MIXED and the PROC NLMIXED procedure in SAS version 9.2.The analytical sensitivity of each of the gene assays was evaluated separately. Specifically, for each gene a nonlinear mixed effects model with log-linear variance function or unstructured covariance was used to model the expected heteroscedasticity in intra-assay response as a function of RNA concentration. This information was used to estimate the Limit of Detection (LOD) and LOQ of the assay on the Cp scale. For each of the 17 gene assays, the LOD was estimated by a lower 95% confidence bound on the mean expression at zero concentration . Similarly, the LOQ on the Cp scale was estimated by the upper one-sided 95% confidence interval of the fitted (linear) model at the inverse prediction of yData for the precision and reproducibility were generated from 10 different FPE prostate cancer samples that were run 9 times each: 3 replicates at each of 3 different RNA inputs . Both precision and reproducibility were generated using multiple lots of RT-PCR reagents, multiple PCR instruments and multiple Tecan liquid-handling robots. The precision component for each of the 12 informative genes as well as the GPS was defined as the within RNA input standard deviation captured in the residual variation term from the linear mixed model described below:ijk was the outcome measurement , μ was the overall mean effect, αi was the random effect of the ith sample , distributed N, λj was the fixed effect of the jth RNA Input , ϵijk was the residual error ~ N where k indexes replicate , assumed independent of αi.Where YThe reproducibility component for each of the 12 informative genes as well as the GPS was defined as the within and between RNA input standard deviation, captured in the residual variation term from the linear mixed model described below:ijk was the outcome measurement , μ was the overall mean effect, αi was the random effect of the ith sample , distributed N, ϵijk was the residual error ~ N where k indexes replicate , assumed independent of αi.Where Ytype DX Prostate Cancer Assay RT and preamplification assay plate has 5 wells containing processing controls: RNA extracted from prostate cancer FPE , human genomic DNA , and 3 wells containing nuclease-free water (a negative control for contamination). In addition, all qPCR plates have 12 wells of positive (gDNA) and 12 wells of negative (nuclease-free water) controls.Each Onco3 of tumor volume (1 mm tumor length × 0.75 mm biopsy core width × 0.030 mm tumor depth (based on availability of six 5 μm sections)) and sought to investigate distribution of RNA yields in such samples. In two separate studies [We estimated that the smallest diagnostic biopsies would contain 0.0225 mm studies , RNA wasAZGP1) to 100% (TPM2). Amplification efficiencies of individual assays, including 95% confidence intervals are shown in Table In order for normalization and multianalyte GPS result calculation to be accurate, amplification efficiencies of individual gene assays were required to be similar , definedKLK2 assay. Considering that this value was established at its final dilution point, it is possible that the true LOQ is higher. However, even with this estimated LOQ, the discriminative capability of the KLK2 assay is appropriate for the expected population distribution (median population expression level has been estimated to be approximately Cp=20). Table For a multianalyte assay to be clinically useful, it must also be able to distinguish between signal and background non-specific signal. All gene assays had LODs that surpassed the pre-specified Cp criteria of 35. Moreover, to make accurate expression measurements, LOQs need to be in a range of Cp values that are higher than the estimates for gene expression within the intended specimen type. Acceptance criteria were pre-specified for each gene assay separately, and all were met. Most of the assays had estimated LOQs between Cp=33 and Cp=35 effectively indicating that most individual assays can accurately quantitate several copies of RNA. The lowest estimated LOQ of 29.4 was for the FLNC, GSTM2) to the full 14 log units  RNA concentrations studied . The smallest amounts that could be accurately quantified ranged from 0.025 ng to 1.6 ng RNA per PCR well. These results demonstrate the performance of these gene assays to quantify cDNA over a wide range of input concentrations that can be encountered in small prostate needle biopsies.FPE RNA was serially diluted two-fold and performance of the individual gene assays was assessed over a linear range of 14 RNA concentrations. Table ATP5E assay (9.7%) and all other assays displayed a bias smaller than 5% in absolute value. Both the amplification efficiency and the accuracy at the individual concentrations are measures of the assay’s ability to detect the doubling in the amount of RNA for individual genes in 1 Cp increments. The combination of low measures of biases and amplification efficiencies approaching 100% demonstrated robust analytical performance at RNA inputs expected to be found in prostate biopsies.For all 17 GPS gene-specific assays, the absolute value of the average percent accuracy at the nominal, one-half and the one-quarter qPCR input was required to be less than 25% in order to meet pre-specified criteria. All assays met these criteria and the results for accuracy are listed in Table 3 tumors. A total of 10 blocks were chosen to span a wide range of GPS results. Each RNA extract was processed three separate times at three different input levels  by several operators over a two week period. Multiple lots of oligonucleotides, preamplification master mixes, and qPCR master mixes were used and processed on different Tecan liquid-handling robots and LightCycler 480 instruments. The standard deviation for precision was 0.21 Cp or smaller for individual gene assays. For GPS, standard deviation was 1.86 units on the 100-unit scale. The standard deviation for reproducibility was also 0.21 Cp or smaller for all assays. Reproducibility variation for the GPS was 2.11 units on the 100-unit scale. Tables Precision was evaluated by examining variation within the same RNA input, and reproducibility incorporated both within and between RNA input variation. Pre-specified acceptance criteria were set for the average within RNA input standard deviation pooled between 20 ng, 10 ng and 5 ng RNA input (precision) and the within and between RNA input  standard deviation (reproducibility). The lowest input of 5 ng was chosen to mirror the lowest 2.5 percentile of the 0.0225 mmThe box plots presented in Figure type DX Prostate Cancer Assay can accurately and reproducibly quantitate gene expression at RNA input levels 110–180 fold less [type DX assays.Prostate cancer is one of the most common malignancies in adult males and is typically diagnosed using small needle core biopsies. While many men with newly diagnosed prostate cancer harbor indolent disease, most are treated with immediate surgery or radiation. A molecular assay capable of obtaining reliable, clinically relevant genomic information from small amounts of tumor tissue available in diagnostic core biopsies could help more accurately identify men with low risk of clinical progression who could be managed by active surveillance. In this manuscript we demonstrate that the Oncoold less ,7 than ttype DX Prostate Cancer Assay is a multi-gene RT-PCR assay specifically designed to analyze underlying tumor biology in tumor tissue from diagnostic FPE core needle biopsies. In order for a biomarker to enter wide clinical practice, evidence of strong analytical validity needs to be demonstrated [type DX Prostate Cancer Assay. All pre-specified analytical criteria  were met, and the analytical assay has been demonstrated to be reliable for clinical use even for patients from whom only limiting amounts of biopsy material are available.The Onconstrated . Prior anstrated  and a sitype DX platform used for Breast and Colon cancer were required. More specifically, the multiplexed preamplification step was introduced to create multiple copies of the starting RNA prior to quantitative assessment of gene expression. Given the very low yields and the resulting limitations to accurate measurement of extracted RNA for many samples, acceptance criteria for the assay include a specification of the average of the reference genes rather than on mass of RNA input as the primary specification for sample quality. This, in turn, allows for the processing of variable RNA inputs, and samples containing as little as 5 ng of RNA have generated reproducible results as demonstrated by the reproducibility of the individual genes and the GPS  of the total variation. In a separate study , within-block reproducibility of the GPS was assessed in biopsies from 46 patients (up to 4 separate samples per biopsy-containing block). The within block standard deviation for GPS in that study was 2.8 GPS units  indicating excellent reproducibility even when histological variability is introduced.The estimates of analytical precision and reproducibility were obtained by analyzing 10 prostate tumor RNA samples on multiple instruments, using multiple reagent lots, by various operators over a period of 2 weeks. Standard deviation for precision for the analytical process was at or below 0.21 Cp for all gene assays and 1.86 GPS units on a 100 unit scale. Reproducibility of the analytical process, in addition to the previously mentioned sources of analytical variability, incorporated variation in RNA input levels . Reproducibility standard deviation for the analytical process of the individual gene assays was at or below 0.21 Cp, and for the overall score was 2.11 GPS units. Given that the estimated total standard deviation in the GPS  is approximately 11.4, the analytical assay variability is estimated to account for only 3.4%  and low bias (under 9.7%) demonstrate that the assay is able to measure accurately gene expression on a wide population range using a very limited amount of RNA.Average amplification efficiency of the 17 gene assays in the Oncotype DX Prostate Cancer Assay has been clinically validated [The Oncoalidated , demonstalidated .type DX platform has enabled the development and analytical validation of the Oncotype DX Prostate Cancer Assay for use with prostate biopsy specimens. This RT-PCR assay has been clinically validated to predict the risk of high grade and/or non-organ confined disease at radical prostatectomy using biopsy samples containing as little as 1 mm of tumor tissue. The Oncotype DX Prostate Cancer Assay complements traditional clinical and pathologic diagnostic features and will assist clinicians to discriminate patients with indolent prostate cancer from aggressive prostate cancer to help make the most appropriate treatment decisions.Optimization of the OncoDK, ADG, NN, DBC, KCL, JS, DW and CQ are employees and stock holders of Genomic Health Inc. EAK, CMG and SMF have received research funding from Genomic Health Inc. Patents relating to the content of this manuscript have been applied for by Genomic Health Inc. Genomic Health Inc. funded this project.DK led the study and drafted the manuscript. DBC was responsible for assay designs and discussion; JS, DK, KCL, AG and CQ were responsible for study design; CQ and DW were responsible for statistical analysis. NN coordinated and performed laboratory procedures. CM-G, SMF and EAK were responsible for selection and preparation of diagnostic biopsies and data review. All authors read and approved the final manuscript.Oligonucleotide Sequences for each primer and probe.Click here for fileAmplicon Sequences for 17 genes in the Oncotype DX GPS.Click here for file


Using a set of experimental data obtained from a lab under dim light, adjustments can be made to calculate the required parameters for an equation without the offset term. This study uses mathematical simulations and lab tests to support our thesis and crosslink test results generated from different ambient light conditions. This paper defines the offset ratio as the ratio of the offset value, I0, versus the initial light intensity in an equation. This ratio can be used to evaluate possible effects on the calculated parameters of an equation in an associated numerical simulation. The most reliable parameters will have consistent results from the use of multiple single exponential equations, with and without the offset term, in simulations to obtain them in an equation to model a set of data.This study examines the effect of the offset term in a multiple single exponential equation that fits into experimental afterglow decay curve data for material applications. For afterglow materials applied and attached to structures, the inclusion of this offset term may reduce the values of the calculated decay times,  I0) as follows:I is the light intensity at any time, t, after switching off the excitation illumination, I0 is the offset term that represents residual light, and Ai is a time-invariant constant. The term τi is a decay constant (or decay time) for the exponential components. A choice can be made from among n = 1 as single, n = 2 as double, and n = 3 as triple exponential equations.Many researchers commonly use empirical multiple single exponential equations to fit experimental curve data . If a laI0 was identified as background by Pedroza-Montero et al. and as background intensity by Chen et al. [I0 term can be computed independently and subtracted from the I equation [I0 should not exist in good experimental data, and its influence on modeling must be investigated.n et al. , 3. In oequation . By quotequation . Using lequation . In otheI0 should be zero in  in (I0) versus the initial light intensity :R is the offset ratio in this paper, Iinitial is the initial light intensity in a test, and I0 is the offset value of an equation.Several lab tests were executed to study the effect of ambient light on the afterglow decay curve simulation. R) in  is definR), the processed curve (with I0) will greatly diverge from a perfect one (without I0). I0. The calculated parameters for these cases are tabulated on the lower side of the figure. They were calculated using triple exponential equations. Examination of the first three curves reveals that the largest is τ3 in curve 1 (no A0) calculated using ..2). ThenUsing some predefined parameters for a specific curve description in this study, we generated a set of data points that represent the curve before the separate application of  and 2)  2) to coThis study used data points that extend up to 120 min in the decay process and collected the calculated parameters in Tables I0 term. It seems that 120 min is fine for the comparison with an opponent as without I0 case . The mismatch of 4.623 versus 23.19 for the two slow-decay times, τ3, in this example indicates that either the R value used is too large or  are approximately 2 times the original values.In examples 2–4 from Figures R values as high as 10.44%. τ2) in the table is 6 times greater. This shows that the experimental environment for afterglow luminescence measurements should be taken seriously.Example 5 shows an extreme situation with τ2 or τ3) from the use of (It is common to retain dim light in afterglow experimental tests for different reasons, including easy operation, operator friendliness or ease of use, and physical chemistry applications of afterglow decay curve data. However, if such experimental data is directly used for numerical simulations, the consequence of having an offset term in the equation may cause confusion. The offset ratio is used to evaluate the possible effect of the offset term. This study points out that increasing the offset ratio may decrease the calculated slow-decay time (e use of  in inter


Puccinia striiformis f. sp. tritici (Pst), is one of the most important diseases of wheat worldwide. Understanding the survival of Pst during the overwintering period is critical for predicting Pst epidemics in the spring. Real-time quantitative PCR (qPCR) methods quantifying Pst DNA and RNA (cDNA) were developed and compared for the ability to quantify viable Pst in leaf tissues. Both qPCR of DNA and RNA can provide reliable measurement of viable Pst in plant tissues prior to the late sporulation stage for which qPCR of DNA gave a much higher estimate of fungal biomass than qPCR of RNA. The percentage of Pst biomass that was viable in detached and attached leaves under low temperatures decreased over time. Pst survived longer on attached leaves than on detached leaves. The survival of Pst in cultivars with strong winter-hardiness at 0°C and -5°C was greater than those with weak winter-hardiness. However, such differences in Pst survival among cultivars were negligible at -10, -15 and -20°C. Results indicated that Pst mycelia inside green leaves can also be killed by low temperatures rather than through death of green leaves under low temperatures. The relationship of Pst survival in attached leaves with temperature and winter-hardiness was well described by logistic models. Further field evaluation is necessary to assess whether inclusion of other factors such as moisture and snow cover could improve the model performance in predicting Pst overwintering potential, and hence the epidemic in spring.Wheat stripe rust, caused by  Puccinia striiformis Westend. f. sp. tritici Erikss. (Pst), is one of the most important diseases of wheat worldwide . However, both methods could not differentiate dead, fresh and dormant urediniospores except for a much lower amount of quantified Pst by qPCR of RNA for dead urediniospores at the ambient temperature  . The amoperature .P < 0.05) than RNA from day 7 onwards. The greater increase in DNA from day 7 to day 10, relative to RNA, led to significant (P < 0.01) interactions between DNA-RNA differences and time (0–11 days). On day 20 and 30, RNA concentration decreased to nearly zero, in contrast to the sharp increase in DNA concentration (P < 0.01) and also the interaction between DNA-RNA difference and time (P < 0.001) when all data were analyzed together. On day 20, more than 50% leaf area senesced  over time at all test temperatures  between attached and detached leaves. A greater (P < 0.001) percentage of Pst survived in attached leaves than in detached leaves after prolonged incubation: at 0°C during 42–54 h, at -5°C during 42–48 h, at -10°C during 36–42 h and at -15°C and -20°C after 18 h. This difference was most pronounced at 0°C  and time to 50% mortality (m). This model explained more than 99% of the total variability in average viable Pst over time for all 30 datasets (five temperatures × six cultivars). Both r and m were related to temperature though the relationship of m with temperature  are the respective minimum and maximum of m . This model accounted for 97.7% of the total variability in m.For all six cultivars, Pst in wheat leaves using qPCR of RNA. RNA is usually more easily degraded than DNA. Quantified DNA concentration based on qPCR may remain stable for longer than the corresponding estimated RNA. However, whether qPCR quantification of RNA is better than the corresponding qPCR of DNA as an indicator of viable fungal structure depends on the type of fungal structure. For urediniospores, both qPCR of RNA and DNA cannot distinguish dormant from dead spores. In contrast, qPCR of RNA, but not DNA, can determine whether hyphae inside leaves are viable. Two possible reasons may explain why qPCR of RNA cannot distinguish dead urediniospores from viable ones. First, RNA is closely linked to protein synthesis (hence concentration), which varies considerably according to the organism’s metabolic needs [This is the first published study that quantifies viable ic needs . In the ic needs –36. In nPst in inoculated wheat leaves from 0 to 11 days after inoculation. However, qPCR of DNA resulted in a much greater estimate of Pst than qPCR of RNA post sporulation (12 to 30 days). Usually, DNA can remain intact for a longer time after cell death than RNA; therefore, qPCR of DNA may overestimate the amount of Pst because of dead urediniospores or mycelia. Thus, both qPCR of RNA and DNA can be used to estimate Pst amount during the initial latent period but only qPCR of RNA should be used post sporulation to estimate viable Pst.There were no significant differences between the two qPCR methods (RNA and DNA) in the amount of quantified Pst that is viable in detached and attached leaves decreased over time under low temperatures. Low temperature is believed to reduce pathogen survival in infected leaves [Pst survival is greatly reduced when temperature is below -10°C. However, some reports claimed that Pst can survive as long as the infected foliage remains green during winter [Pst in attached green leaves did not survive at -20°C after 30 h, however the plants were still alive at this condition. Saulescu and Braun [Pst mycelia inside green leaves can be killed by low temperature and that the decrease in viable Pst is not all due to death of leaf tissues. It should be noted that seedlings were transferred to low temperatures without adequate acclimatization time in the present study. Wheat plants that have grown to the tillering stage and been slowly acclimated to low temperatures may survive better, which may also influence Pst survival. Thus, it would be interesting to study whether wheat plant age and acclimatization time could affect Pst survival.The percentage of d leaves . As expeg winter –4. The pnd Braun  also repPst overwintering [Pst was greater on cultivars with strong winter-hardiness than those with weak winter-hardiness mainly at 0°C and -5°C. Under the conditions of this study, both temperature and cultivar winter-hardiness affect Pst survival in winter, but temperature has more impact on determining the Pst survival.Winter-hardiness of wheat cultivars may affect intering ,21. The Pst mortality to temperature and cultivar winter-hardiness. These models predict the shortest and longest Pst survival on cultivars of low and high winter-hardiness, respectively, at a particular temperature. It should be noted that we assumed that there is no mortality when temperature > 0°C which was shown previously [Many models have been developed to describe the relationship between winter temperature and stripe rust epidemics based on field observations ,7,11,38 eviously .Pst biomass in leaf tissues. This qPCR-RNA method can be used in detecting and quantifying the pathogen prior to symptoms, which may be used as an input for disease prediction. A mathematical model was derived to relate Pst survival to temperature and cultivar winter-hardiness, which can be used predict Pst survival under fluctuating conditions. However, further data on field Pst survival are needed to assess whether inclusion of other factors (e.g. moisture and snow cover) could improve model predictions of Pst survival over the winter. For this purpose, we are sampling wheat leaves in early spring from plants showing symptoms in the autumn at many locations to quantify viable Pst biomass. These data will be used to evaluate and, if necessary, improve this temperature-only model. Availability of such a predictive model will be valuable to assist growers in timing fungicide applications in given geographical regions.In summary, we have developed a method based on qPCR of RNA to quantify viable S1 Fig(TIFF)Click here for additional data file.S2 FigEF1 distinguished Pst from other pathogens. Lane M, DNA ladder MD 101 ; lane 1, negative control using sterile distilled water; lane 2, negative control using cDNA of healthy wheat leaves; lane 3 to 7, cDNA from Pst, P. triticina, P. graminis f. sp. tritici, Fusarium graminearum, and Blumeria graminis f. sp. tritici, respectively. B: cDNA (159 bp) and DNA (248 bp) band amplified using EF1 primer from cDNA and DNA of Pst, respectively. Lane M, DNA ladder MD 101 ; lane 1, negative control using sterile distilled water; lane 2 to 3, cDNA and DNA of Pst urediniospores, respectively. C: Melting curve of real-time quantitative PCR amplification using primer pair EF1 of Pst.A: the primer pair (TIFF)Click here for additional data file.S3 Fig(A) fresh urediniospores; (B) fresh urediniospores spread onto 2.5% water agar surface and incubated at 12°C in dark with relative humidity 85% for 12 h; (C) fresh urediniospore heated in a water bath at 60°C for 1 h; (D) fresh urediniospore heated in a water bath at 60°C for 1 h and spread onto 2.5% water agar surface and incubated at 12°C in the dark with relative humidity 85% for 12 h.(TIFF)Click here for additional data file.S4 Fig(TIFF)Click here for additional data file.S5 Fig(TIFF)Click here for additional data file.S6 FigLM) and temperature (T) of Mingxian 169 and Xiaoyan 22, 01–314 and Xinong 979 and Lantian 15 and Jingnong 411 were well described by the following logistic models:P = 0.05.The relationship between wheat leaf mortality ((TIFF)Click here for additional data file.