Tau protein is subject to phosphorylation by multiple kinases at more than 80 different sites. Some of these sites are associated with tau pathology and neurodegeneration, but other sites are modified in normal tau as well as in pathological tau. Although phosphorylation of tau at residues in the microtubule-binding repeats is thought to reduce tau association with microtubules, the functional consequences of other sites are poorly understood. The AT8 antibody recognizes a complex phosphoepitope site on tau that is detectable in a healthy brain but significantly increased in Alzheimer’s disease (AD) and other tauopathies. Previous studies showed that phosphorylation of tau at the AT8 site leads to exposure of an N-terminal sequence that promotes activation of a protein phosphatase 1 (PP1)/glycogen synthase 3 (GSK3) signaling pathway, which inhibits kinesin-1-based anterograde fast axonal transport (FAT). This finding suggests that phosphorylation may control tau conformation and function. However, the AT8 includes three distinct phosphorylated amino acids that may be differentially phosphorylated in normal and disease conditions. To evaluate the effects of specific phosphorylation sites in the AT8 epitope, recombinant, pseudophosphorylated tau proteins were perfused into the isolated squid axoplasm preparation to determine their effects on axonal signaling pathways and FAT. Results from these studies suggest a mechanism where specific phosphorylation events differentially impact tau conformation, promoting activation of independent signaling pathways that differentially affect FAT. Implications of findings here to our understanding of tau function in health and disease conditions are discussed. Surprisingly, we found that pseudophosphorylation of selected residues sufficed for monomeric tau to inhibit either anterograde FAT or both anterograde and retrograde FAT. Additionally, we present evidence linking these effects to PAD exposure and activation of selected kinase pathways. Collectively, findings here are consistent with a mechanism linking residue-specific phosphorylation of tau, stabilization of unique conformations, and activation of selected phosphotransferase signaling pathways. Implications of these findings to disease and developmental-related roles of tau are discussed.The following antibodies were used for Western blots: KHC  was added to a final concentration of 0.4 mM to induce protein expression. After 3 h, bacteria pellets were collected by centrifugation at 8,000 g and resuspended in lysis buffer  with protease inhibitor cocktail (Sigma–Aldrich). Cells were sonicated on ice and tau was purified from cleared lysates with Talon Metal Affinity Resin as per the manufacturer’s instructions (Takara Bio). Eluted proteins were concentrated and buffer exchanged into 50 mM HEPES, 100 mM KCl using Amicon 30 kDa columns (Millipore).Recombinant tau proteins in Loligo pealii  as described  supplemented with 5 mM ATP and perfused into isolated squid axoplasm at final concentration of 2 μM. For TNT1 blocking experiments  in MOPS buffer and proteins were transferred to PVDF membrane (Bio-Rad) using Towbin buffer with 10% methanol. Membranes were dried for at least 1 h before being reactivated in methanol and blocked in 1% milk in TBS supplemented with 2 mM Sodium Orthovanadate and 10 mM Sodium Fluoride to block phosphatase activity present in milk. Primary antibodies were incubated overnight diluted in 1% BSA in TBS supplemented as before. Goat anti-mouse or goat anti-rabbit secondary antibodies (LiCor) were incubated for 1 h at RT and immunoblots visualized using a LiCor Odyssey Fc imaging system. LiCor ImageStudio Lite was used for quantitation of signal intensity.n values shown in Figures). For vesicle motility assays, the difference between the mean of velocity measurements obtained between 0–10 and 30–50 min after perfusion was calculated for both anterograde and retrograde FAT in each experiment. For biochemistry experiments, signal intensities of “sister” axoplasms were quantified as described in Section “Immunoblotting-Based Analysis of Kinase Activity in Squid”  to PAD exposure and activation of a downstream PP1-GSK3β signaling pathway. However, ample data exists showing that some tau phosphospecies are detectable in the normal and pathological brain including phosphorylation of some, but not all three S/T residues in the AT8 antibody epitope. For example, pS202 and pT205 tau are detected in cerebrospinal fluid of AD patients, with pT205 showing the highest correlation with disease progression  to glutamic acid, which mimics the negative charge effect associated with phosphorylation . FollowiNext, we set out to determine whether the effects elicited by hTau40-T205E and hTau40-S199E on FAT were impacted by phosphorylation of the adjacent S202 residue. As shown in Exposure of PAD in tau, an event associated with various pathological post-translational modifications, has been shown to trigger a PP1-GSK3β pathway that inhibits anterograde FAT  can be differentially phosphorylated either singly or in different combinations  led to a conformational change in tau that exposed a biologically active motif in the N-terminal of tau that is normally sequestered in dephosphorylated tau (Kanaan et al., Despite the proximity of the three phosphorylation sites analyzed here, we found that single phosphorylation at S199 or T205, but not at S202, produces monomeric tau that differentially affects FAT by activation of two distinct downstream signaling pathways. Specifically, hTau40-T205E inhibited anterograde FAT through a mechanism involving exposure of the N-terminal PAD and PP1/GSK3β activation, as seen with hTau40-AT8 in prior studies (Kanaan et al., In vitro, pseudophosphorylation of the AT8 epitope exposes the N-terminal whereas pseudophosphorylation at the C-terminal PHF1 epitope promotes exposure of the C-terminal (Jeganathan et al., Tau is generally classified as an intrinsically disordered protein. However, multiple studies have indicated that monomeric tau normally folds into a “paperclip” conformation with the N- and C-terminals near the central microtubule-binding domains (Jeganathan et al., Investigation of dually pseudophosphorylated hTau40 proteins indicated additional levels of complexity. Both hTau40-S199E/S202E and hTau40-S199E similarly inhibited both directions of FAT, implying that S202 pseudophosphorylation does not alter the specific hTau40 conformation elicited by S199 pseudophosphorylation significantly. In contrast, pseudophosphorylation of S202 significantly changed the effects of hTau40-T205E. Whereas hTau40-T205E affected only anterograde FAT and the effect was blocked by TNT1, hTau40-S202E/T205E inhibited retrograde FAT and exhibited a slow decline in anterograde FAT that did not reach significance in 50 min. Co-perfusion with TNT1 did not change the effects on either anterograde or retrograde FAT by hTau40-S202E/T205E. Tau is known to have a dynamic secondary structure, which can be stabilized by phosphorylation of selected residues (Jeganathan et al., Although most studies on tau function have focused on microtubule dynamics, there is evidence that tau can also affect neuronal signaling in other ways. For example, tau has also been suggested to potentiate NGF-ERK signal transduction in differentiating PC12 cells specifically through a mechanism involving phosphorylation at T231. Tau depleted cells were unable to initiate neurite extension and the effect could be rescued by exogenous expression of WT but not Tau-T231A (Leugers and Lee, While tau phosphorylation has commonly been studied in the context of disease, various lines of evidence indicate that it also has additional physiological functions, especially important during development. The relative levels of tau phosphorylation and the specific sits modified change during the development and maturation of the brain. When tau from the fetal brain is analyzed for the amount of phosphorylation, it has approximately six phosphates per molecule of tau whereas in tau from the adult human brain the ratio is 2–3 mol of phosphate per mol of protein (Kenessey and Yen, Further evidence of this is seen from the enrichment of AT8 immunoreactivity in gray matter, which is typically at low levels in adulthood, but at higher levels during development and in tauopathies (Brion et al., in vitro (Despres et al., It is important to note that a fourth phosphorylation site in tau, pS208, may also be recognized by the AT8 antibody (Malia et al., In vitro S199, S202, T205 all have the potential to be phosphorylated by at least seven kinases, including GSK3β and Cdk5 (Singh et al., in vivo, tau certainly has the potential to be a central point for multiple signaling pathways potentiating disparate downstream functions, depending on which site is modified. Equally important is switching off the signaling by dephosphorylation. The major phosphatase for tau is PP2A accounting for ~70% of the activity, but certain sites are preferentially dephosphorylated by either PP2B or PP1 (Liu et al., Phosphoprotein-species are maintained by an intricate balance of kinase and phosphatase activities, which are spatially and temporally regulated. Many questions remain about the role of tau in spatial and temporal regulation of signaling pathways, suggesting this is a rich area for further study. For example, an important feature of tau biology not addressed here relates to isoform-specific differences (Cox et al., The data presented in this study strongly supports our hypothesis that phosphorylation of tau at individual sites can modulate tau function as a signaling hub. Tau is well known to have a highly dynamic protein structure and several lines of research suggest that phosphorylation of tau at specific sites can stabilize distinct conformations. These conformations may allow activation of diverse signaling pathways through the exposure of multiple biologically active domains such as the N-terminal PAD and others yet to be defined (Ittner et al., The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the animal study because IACUC approval was not required for this study. All recommendations for humane use of squid set by the Marine Biological Laboratory were followed.SM and SB conceived and designed the study, plotted and analyzed the data. M-YT expressed and purified the recombinant proteins. KB, SA, SK, and SM collected the data with additional experimental assistance from GM and SB. SM, GM, and SB wrote and edited the manuscript. All authors contributed to the article and approved the submitted version.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.


Kaposi’s sarcoma-associated herpesvirus (KSHV) induces life-long infections and has evolved many ways to exert extensive control over its host’s transcriptional and post-transcriptional machinery to gain better access to resources and dampened immune sensing. The hallmark of this takeover is how KSHV reshapes RNA fate both to control expression of its own gene but also that of its host. From the nucleus to the cytoplasm, control of RNA expression, localization, and decay is a process that is carefully tuned by a multitude of factors and that can adapt or react to rapid changes in the environment. Intriguingly, it appears that KSHV has found ways to co-opt each of these pathways for its own benefit. Here we provide a comprehensive review of recent work in this area and in particular recent advances on the post-transcriptional modifications front. Overall, this review highlights the myriad of ways KSHV uses to control RNA fate and gathers novel insights gained from the past decade of research at the interface of RNA biology and the field of KSHV research. Kaposi’s sarcoma-associated herpesvirus (KSHV), also known as human herpesvirus-8 (HHV-8) is a γ2-herpesvirus that is the causative agent of Kaposi’s sarcoma (KS), KSHV inflammatory cytokine syndrome (KICS), primary effusion lymphoma (PEL), and a plasmablastic form of multicentric Castleman’s disease (MCD) ,2,3. Alt6A) modification, can regulate viral RNA stability and function at a global scale while other more specific features, such as G4 quadruplex motifs, can enforce strict control over viral RNA translation. There are also several virally encoded non-coding RNAs (ncRNA) that indirectly influence viral mRNA fate through a variety of mechanisms that mimic or even outperform their cellular counterparts during infection. We will also examine the regulation of key trans-acting viral proteins like ORF57 that protect viral RNAs from nuclear decay and the KSHV endoribonuclease, SOX, which triggers a massive RNA degradation event during lytic reactivation. KSHV’s capacity to take advantage of cellular RNA regulatory networks with such precision gives researchers a window into the never-ending arms race between viruses and their host. Through the work reviewed here, we wish to reveal research that shines a light on the strategies KSHV uses to enhance its viral gene expression. The studies illustrated here undoubtedly open new avenues in which cellular RNA fate and KSHV exploitation of those systems can be explored in the future. To hijack the host, KSHV triggers an intricate takeover of cellular RNA fate ranging from widespread manipulation of RNA decay to influencing patterns of RNA expression. By seizing control of RNA surveillance pathways, the virus can fine-tune the global gene expression environment throughout both phases of infection. This newly forged pro-viral RNA landscape allows KSHV unprecedented control over viral gene expression, which requires extensive temporal regulation and the capacity to widely remodel gene expression pathways. Many mechanisms are at play to allow the cell to maintain tight control over mRNA fate through mechanisms often associated with physical RNA features such as pre-mRNA splice patterns, 5′ cap, 3′ poly-A tail, and sequences/modifications that recruit trans-acting factors that alter mRNA stability. Post-transcriptional modifications and RNA editing also appear to be particularly important for KSHV-mediated takeover of the host. This review will explore the strategies evolved by KSHV to co-opt or subvert cellular RNA regulatory pathways that influence different stages of mRNA development during viral infection . Many of6A). These chemical additions emerge as crucial for the regulation of many RNA processes, like splicing, translation, stability, and decay. Before RNAs can interact with nuclear export machinery, they must contend with mechanisms that regulate the amount of transcript that gets exported into the cytoplasm or nuclear decay pathways, like the CBCN-mediated RNA decay pathway, which protects the cell from aberrant transcripts. In this section, we will be reviewing how KSHV uses m6A to regulate splicing of its own transcripts, ORF57, to escape nuclear decay pathways and G-Quadruplexes on its mRNA to control nuclear export. Circular RNAs (circRNAs) will also be a new addition to the vast list of KSHV transcript regulator and will be discussed below.As the cell initiates RNA transcription, it also begins the process of regulating the fate of RNA very closely. As transcription occurs, RNA transcripts will undergo a series of maturation processes mainly consisting of co-transcriptional splicing, addition of a 5′ cap, and a 3′ poly-A tail. These processes are mediated by cellular factors that interact with one another and promote maturation of the RNA and ultimately determine their localization and function ,10. Anot6A. The m6A machinery consists of a complex set of proteins that coordinate the regulation of RNA: there is a writer complex that includes METTL3, METTL14, WTAP, METTL16, RBM15, and KIAA1429 [6A addition is a highly dynamic process that also includes a removal mechanism catalyzed by demethylases or erasers like FTO or ALKBH5 [6A modifications both on latent and lytic viral transcripts. Intriguingly, during KSHV lytic reactivation, they also observed a general decrease of m6A deposition on cellular mRNAs [6As possibly allows for enhanced 3′ UTR regulation, which has been known to affect localization, translation initiation, and the stability/decay rate of mRNAs [6A methylation. One of the hypotheses raised by the authors is that the enrichment of methylation in the 3′ UTR on cellular transcripts may help mediate targeting of miRNAs by KSHV own miRNAs that are known to be essential for KSHV-induced cellular transformation [6A modifications during infection and what occurs to the m6A landscape when KSHV switches from the latent to the lytic portion of its life cycle. Recent studies from Ye et al. in vivo and Hesser et al. in vitro have also reported that the amount of m6A-modified KSHV mRNA increases during lytic reactivation while decreasing on cellular mRNAs [6A deposition may be due to viral-induced widespread RNA decay leading to a decrease in available transcripts for m6A deposition and, therefore, an increase in viral transcript availability. Another possibility is KSHV influences m6A deposition directly by increasing viral RNA likelihood of being methylated or by affecting the m6A machinery itself. The counterpart of this shift in m6A deposition towards viral mRNA is that the reduced m6A deposition on cellular RNA could help dampen some host anti-viral processes by affecting host mRNA stability and/or translation. MKIAA1429 ,12,13,14r ALKBH5 ,18. Thesar mRNAs . In latear mRNAs . The disof mRNAs . In factormation . Howeverormation . All thiar mRNAs ,23. The 6A modifications are decoded by a collection of cellular factors that “read” this modification and enact the associated function. Depending on the localization of the modification on the mRNA, different reader proteins will be recruited and the resulting effect on the modified RNA will differ [6A readers that contain an aromatic cage that allows direct binding of the protein to the m6A modification [6A using 3-deazaadenosine (DAA)—an inhibitor of METTL3—a prominent m6A writer—prevented pre-mRNA splicing of the KSHV major lytic switch protein, RTA (ORF50), which resulted in a reduction of viral lytic replication [6A sites found in the RTA pre-mRNA, it was revealed that a single methylation site in exon 2 was responsible for enhancing splicing by using its m6A site to recruit YTHDC1 which in turn recruits SRF3 and SRS10 to aid in splicing. However, RTA pre-mRNA is known to encompass many different splice variants, so it is possible that the other m6A sites found by Ye et al. interact with other m6A nuclear reader proteins such as hnRNP-C1/2 and hnRNP-A2B1 to regulate differential splicing. More recently, a new class of readers from the “Royal” family, specifically Staphylococcal nuclease domain-containing protein 1 (SND1), was shown to bind directly to m6A modifications similarly to YTH domain proteins [6A in aiding the recruitment of splicing factors, uncovering more m6A readers on novel m6A sites will reveal a complex growing regulatory network of co-transcriptional regulators that will help us better understand cellular and KSHV RNA fate. ml differ ,24,25,26fication . One of fication ,29,30. Ylication . Althougproteins . It was proteins . Given tKSHV Circular RNA. Circular RNAs (circRNAs) are a class of 3′ to 5′ cyclized RNAs that are the product of a unique form of precursor RNA processing known as back-splicing ,33. The Recent large-scale screens have uncovered that virally encoded circRNAs are also expressed during latent and lytic KSHV infection. One of the first screens of the KSHV genome for circRNA expression was performed by Toptan et al. in 2018, uncovering several novel viral circRNAs, most abundantly derived from the vIRF4 and PAN/K7.3 gene loci. This same list also found several other low abundance circRNAs potentially derived from multiple lytic ORFs . In para6A methylation could in fact drive the translation of these transcripts [Many questions continue to surround the mechanisms that regulate the expression of KSHV-encoded circRNAs and their impact within the viral RNA pool. Several large-scale screens have already identified numerous small back-splice junctions throughout the KSHV genome, while curiously only a single major junction gives rise to one of the most abundant KSHV circRNAs, circ-vIRF4. For human circRNAs, cis factors such as inverted Alu elements within the nascent pre-RNA between the donor and acceptor sites have been shown to mediate their interaction leading to cyclization . While snscripts . This isnscripts ,45. Furtnscripts . To dateLike circ-PAN, circ-vIRF4 also represents a curious case in both its expression across various KSHV-infected cell types and the current air of ambiguity that surrounds its regulation between latency and lytic reactivation. Previous reports have shown that linear vIRF4 is expressed at low levels during latency and is highly expressed during lytic infection. Conversely, a recent report by Abere et al. found that circ-vIRF4 was expressed at lower levels than its cognate linear form during latency and strangely was only marginally enhanced or even reduced in most PEL cell lines following lytic reactivation . While tThe field of circRNA biology, having matured well over the past decade, has turned much of our understanding of post-transcriptional regulation and the contribution of splicing to control RNA fate on its head. The discovery of KSHV-encoded circRNAs especially calls into question many previously characterized pro- and anti-viral factors that may now have newly defined roles in circRNA biogenesis and regulation or even as circRNAs themselves. One example of this is the protein adenosine deaminase acting on RNA 1 (ADAR1), a recently identified pro-viral inhibitor of RLR-dependent immune signaling, is also inhibitory to circRNA biogenesis, which could in-turn impact KSHV fitness . FurtherG-Quadruplexes. Recently G-quadruplexes (G4s) have gained a lot of attention. These secondary DNA or RNA structures arise from nucleic acids that are rich in guanine residues and result in G-quartets forming from Hoogsteen hydrogen bonding stack upon one another. Multiple proteins are required to help form or unwind these structures . G4s havORF57 and nuclear RNAi-defective 2 (NRDE2). RNA quality control (QC) pathways play a crucial role in the regulation of gene expression and RNA fate. Nuclear RNA QC pathways monitor the presence of improperly matured RNA and prevent their export to the cytoplasm. Among these QC pathways, two play a significant role in controlling the longevity of nuclear transcripts. These pathways are the PABPN1 and PAPα/γ-mediated RNA decay (PPD) pathway and the cap-binding complex (CBC) in association with the nuclear exosome targeting (NEXT) complex, known together as the CBCN-mediated RNA decay pathway. These pathways act on the decay of polyadenylated, short, and intronless transcripts, such as improperly spliced pre-mRNA that do not meet the requirements to become fully processed mature mRNA. These pathways also oversee the regulation of promoter upstream transcripts (PROMPTs),  short inTo answer this question, Ruiz and colleagues explored the involvement of ORF57 and ALYREF in connection to the CBCN and PPD nuclear decay pathways. The authors knocked down various components of these host RNA QC pathways and observed the effects on mutant of PAN that lacks the cis-acting nuclear retention element (PAN∆ENE) and lytic transcript ORF59 ,55. In tDespite the observation that ORF57 is capable of protecting viral transcripts form nuclear RNA QC decay pathways, it was observed that a small subset of transcripts still underwent PPD and CBCN modulated decay even in the presence of ORF57 ,55. UsinThrough these mechanisms, KSHV can hijack and manipulate host nuclear RNA regulatory pathways to promote infection. Both systems exploit host RNA QC pathways primarily through the manipulation of the mRNA export adaptor ALYREF. While the NRDE2 pathway does not directly require ORF57, interactions surrounding this event may also include ORF57, as it is vital for the recruitment of ALYREF to specific transcripts and plays a major role in splicing within KSHV replication compartments merged with nuclear speckles where it colocalizes with splicing factors . One aspDuring KSHV infection, as mRNAs enter the cytoplasm they are subjected to an even greater repertoire of cellular and viral factors that dictate whether they are translated, stored, or degraded. KSHV co-evolution with its human host has resulted in a wide breadth of viral intrusion into cytoplasmic RNA surveillance and mimicking of RNA features such as RNA interference or RNA structural elements. These processes emerge as crucial to suppress unwanted mRNA translation in favor of both latency maintenance and lytic viral replication .G-quadruplexes. As we previously discussed, G4s within LANA transcript are important to regulate LANA export from the nucleus, but it was also suggested that these G4s also play a role in the cytoplasmic regulation of LANA. It was discovered that when LANA G-quadruplex is stabilized, LANA translation was inhibited and, therefore, protein expression was reduced, despite normal mRNA synthesis. Furthermore, when LANA mRNA was mutated to disrupt the G4 formation, it was revealed that LANA translation was increased, further supporting G4s as a translation regulator of LANA. LANA has been shown to modulate antigen presentation by interacting with components of the antigen presentation ,67. G4s 6A. As previously mentioned, m6A modifications influence many aspects of an mRNA life. In the cytoplasm, m6A readers have been shown to affect the stability, localization, and translation of mRNAs. One such reader that has come up as an important regulator of the cytoplasmic viral mRNA pool is YTHDF2. This reader binds directly to m6A-modified mRNA and promotes their degradation by localizing them to RNA granules known as processing bodies (P-bodies) [6A in promoting lytic reactivation [6A reader [6A in this case would have an antiviral role [6A deposition and/or m6A-mediated functions are highly dynamic. One possibility is that m6A regulation is dependent on temporal factors and that fine-tuning of viral mRNA stability could be a requirement for proper progression of the viral life cycle. Furthermore, mapping of m6A sites within viral mRNA revealed that despite some differences, many of the m6A peaks are consistent across multiple cell types: the same transcripts overall are methylated but the position of this methylation along the transcript can vary. This suggests that the viral mRNAs are not necessarily interfacing with host m6A methyltransferase machinery differently between cell types but instead the contradictory results further enforce the idea that m6A deposition is dynamic and does not always occur on every possible m6A motif. Localization of the m6A mark can be tied to the rate of RNA Pol II elongation where a slow elongation leads to enhanced m6A modification and eventually decrease of translation efficiency [6A deposition and thus be highly context-dependent, possibly explaining this variability. Understanding where and what m6A depositions mean on an mRNA may help in understanding their effects on KSHV replication. M-bodies) ,69. Hesstivation . In starA reader . On the ral role . It is sficiency ,16. It iKSHV miRNA. Having passed an extensive panel of nuclear checkpoints, cytoplasmic mRNAs fall under an equally vast network of regulatory oversight evolved to control the terminal stages of their fate from translation to decay. One form of cytoplasmic RNA surveillance are small non-coding RNAs known as microRNAs (miRNA). miRNAs are short (19–23 nt), single-stranded RNAs that coordinate with cellular RNA silencing factors to dictate the rate of translation and longevity of target transcripts. Mechanistically, miRNAs often target complementary sites within the 3′ UTR or occasionally the coding region of their cognate mRNA. Binding specificity of miRNAs to these sites typically relies on a minimum seed sequence match (2–7 nt), but this requirement has been challenged by several recent reports . Once boStringent control over the switch between the latent and lytic stages of KSHV infection is critical for a successful persistent infection and timely coordination of viral replication. Most KSHV-encoded miRNAs are predominantly expressed during the latent phase of infection except for those derived from the Kaposin locus, which is highly expressed during the lytic phase. These expression patterns are evident across most KS/MCD derived tissues and cell lines albeit with inconsistency between expression levels of the miRNAs themselves . TherefoWhile RTA represents the most direct example of how KSHV-encoded miRNAs regulate the viral life cycle, only a handful of groups have identified other miRNA targets of viral origin. Aside from RTA, these earlier studies identified a few viral gene targets including ORF56, ORF57, and viral interleukin-6 (vIL-6) ,80,83. FWhile miRNA regulation of KSHV genes is typically discussed from the perspective of trans-regulation, pre-miRNAs that give rise to mature viral miRNA can also regulate viral gene expression in cis. In canonical miRNA biogenesis, primary-miRNAs (pri-miRNA) hairpins are transcribed and processed by the nuclear microprocessor complex comprised of DiGeorge Syndrome Critical Region 8 (DGCR8) and the ribonuclease III enzyme, Drosha into long duplex RNA fragments known as pre-miRNAs. These RNA duplexes are then exported into the cytoplasm where they give rise to mature miRNAs. Two pre-miRNAs, miR-K12 and miR-K10, located apart from the remaining 23, are encoded by 3′UTR of the coding gene Kaposin B (KapB). Many KSHV genes are divided into either latency or lytic gene families based on their expression patterns throughout viral infection. However, several KSHV transcripts, including KapB, are constitutively expressed at low levels during latency and highly expressed following lytic reactivation . A curreThis binary fate of the KapB mRNA highlights the interconnectedness between post-transcriptional regulation of viral mRNA and viral miRNA biogenesis. It would be exciting to see if pre-miRNAs of other unrelated DNA tumor viruses, especially those encoded in the 3′ UTRs or exons of coding transcripts, have also been evolved to serve as cis-regulatory factors in the regulation of viral gene expression. Along the same vein, adaptation of the microprocessor machinery by KSHV opens a number of avenues of investigation including studies of viral manipulation of miRNA processing beyond Drosha, the regulation of Drosha in respect to cellular miRNA biogenesis during infection, and the host mRNAs they regulate therein. Much work is still necessary to fully uncover the depth to which miRNAs influence the fate of viral RNAs and the physiological consequences of this activity. Several studies have reported functions for miRNAs far beyond this scope, especially with reports describing their incorporation into extracellular vesicles and even KSHV virions for signaling in a paracrine like manner ,95. WithSOX. Similarly to ORF57 that regulates RNA decay in the cytoplasm, KSHV also has a major RNA decay regulator in the cytoplasm, SOX (ORF37). This protein is expressed as a delayed early gene during lytic reactivation and is responsible for the host shutoff event, which results in decreased host gene expression ,100. Dur6A in the context of KSHV have been elucidated, however, there are conflicting roles depending on cell type and the reason for this remains to be discovered. Similarly, new research has been done into KSHV miRNAs now leaves questions regarding how the host monitors these miRNAs and how the dynamics of P-bodies affect their function as well. KSHV’s use of the G4 structural element is fascinating and makes one wonder if there are more transcripts that use G4s or other structural elements to regulate their translation efficiency. Finally, although a lot of research is done into viral endonucleases like KSHV SOX, there are still mysteries surrounding the mechanisms of targeting and escape of transcripts. Answering these outstanding questions will reveal new avenues of KSHV cytoplasmic regulation of RNA in the cell. The continued research into KSHV’s pervasive use of cellular regulatory pathways has revealed new insights into how KSHV enhances its infection as well as new aspects of cellular RNA fate. Although this research as given more insights into KSHV regulation, more questions remain. New roles for m6A on KSHV biology. The extent of factors that can interact with these structural and chemical modifications is by no means a complete list. Finding and characterizing these factors will greatly expand our knowledge of RNA fate as well as increase our understanding of KSHV host takeover. There are also still over a hundred different RNA modifications and post-transcriptional RNA editing that have been documented like inosine (I), pseudouridine (Y), and 2′-O-methyladenosine (Am). Although m6A has been studied in the context of KSHV, these other RNA editing strategies may be used by the virus in order to regulate cellular and viral RNAs [6A modification could also contribute to the host side of the viral-host battle. By understanding these processes further, we continue to better appreciate how the tenuous and important the balance of RNA fate is.The past two decades have uncovered exciting new ways by which KSHV extensively regulates both its own and its host’s RNA during infection. This emphasizes KSHV large investment in the everlasting battle with its host over the gene expression cascade. Viruses have historically been good models to gain a deeper understanding of basic cellular mechanisms, and by studying how KSHV manipulates RNA fate, we continue to discover novel aspects of the gene expression regulation. It also underlines the critical role of the RNA fate equilibrium and how disrupting that balance can have far-reaching consequences. Currently, there is still much to study and understand about what governs these mechanisms. In particular, we are only starting to appreciate the contribution of G-Quadraplexes or mral RNAs . Given t


IntroductionAs total hip arthroplasty (THA) and total knee arthroplasty (TKA) transition to outpatient settings, appropriate pain management remains a challenge. Nonsteroidal anti-inflammatory drugs (NSAIDs) may subvert the need for postoperative opioids. This study evaluated: 1) total opioid consumption; 2) postoperative pain intensity; 3) discharge destination; 4) length of stay (LOS); and 5) THA and TKA patients’ satisfaction in receiving adjunctive intravenous (IV) diclofenac or ketorolac.MethodsIn this retrospective cohort study, patients scheduled to undergo primary THA or TKA by a single surgeon between March 2017 and April 2018 were identified. Patients were stratified based on the receipt of IV diclofenac  or IV ketorolac  in addition to the standard pain management regimen. Student’s t-testing and Chi-square were used to analyze continuous and categorical variables, respectively.ResultsTKA diclofenac patients had lower opioid consumption 12 hours postoperatively (p: 0.037). TKA patients in the diclofenac cohort were discharged to home less often (p: 0.025). Both diclofenac cohorts had greater patient satisfaction than the ketorolac cohorts (p: <0.05). There was no significant difference between groups in postoperative pain intensity at 24 or 48 hours or in the length of stay .ConclusionThis study demonstrated that both TKA and THA patients treated with IV diclofenac had no difference in postoperative pain intensity while THA patients had no difference in opioid consumption relative to those treated with IV ketorolac. Further comparison of IV NSAIDs with other IV pain medications may provide broader insight into the ideal management for postoperative pain for this widening patient population. Total joint arthroplasty (TJA) poses a significant economic burden to the healthcare system, with combined inpatient costs for Medicare total hip and knee arthroplasties exceeding USD 7 billion in 2014 . As a reAlthough opioids have classically been a mainstay in the management of postsurgical pain, cognizance of their unfavorable side-effect profile and potential to prolong hospital stays has spurred initiatives to identify alternative pain-control avenues -14. A nuAlthough several studies have evaluated the efficacy of IV ketorolac and diclofenac on postoperative outcomes and pain control, there is a paucity of literature comparing the two in the setting of primary TJA. As such, this study evaluated: 1) total opioid consumption; 2) postoperative pain intensity; 3) discharge disposition; 4) length of hospital stay; and 5) satisfaction with adjunctive IV diclofenac or ketorolac pain control in primary THA and TKA patients, at a single institution between 2017 and 2018.Patient selectionInstitutional Review Board approval was obtained for all aspects of this retrospective cohort study. All patients that underwent TJA with a single surgeon between March 1, 2017 and April 31, 2018 were identified and screened for study inclusion. Patients were included if they had undergone a primary TKA or THA and received adjunctive diclofenac or ketorolac as a part of their postoperative pain management regimen. Patients were excluded from the review if they were on methadone therapy, had a history of chronic opioid use, had a low calculated creatinine clearance (less than 30 mL/min2), had undergone epidural anesthesia during their procedure, had a poor cardiac function, had an allergy to any NSAIDs, narcotics, or local anesthetics used in the study, or if they had undergone revision or conversion THA or TKA.We identified a total of 136 eligible TJA patients who had received IV diclofenac or IV ketorolac that were blinded to their perioperative pain regimen. The final patient cohorts comprised 25 THA patients and 51 TKA patients who had received postoperative IV diclofenac, and 28 THA patients and 32 TKA patients who had received postoperative IV ketorolac.Pain regimenThe standard pain regimen included: celecoxib 400 mg per oral (PO) preoperatively, then celecoxib 200 mg twice per day, starting on the evening of postoperative day one POD1) . The ketorolac group similarly received 30 mg of IV ketorolac every six hours for four doses upon arrival to the PACU. Oxycodone immediate-release (5 or 10 mg PO) was made available postoperatively to all patients in both groups to ease breakthrough pain if necessary.Study variablesDemographic information including gender, race, age, and body mass index (BMI) was collected for all patients. Opioid consumption [converted to morphine milligram equivalents [MME]), length of stay (LOS), visual analog scale (VAS) pain scores at eight-hour intervals, discharge destination, and post-admission satisfaction scores were collected to evaluate patient outcomes. Patient satisfaction with postoperative pain control was assessed via three questions selected from the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey Table  25]..25].Pain intensity, expressed as area under the curve (AUC), was calculated utilizing VAS pain scores at eight-hour intervals through the 48-hour postoperative period.The THA patients in the IV diclofenac and IV ketorolac cohorts differed in race  and gender ; however, there were no differences in other demographic characteristics, including age  and BMI  .Statistical analysisChi-square analysis/Fisher’s exact test and Student’s t-test were utilized to analyze categorical and continuous variables, respectively. A p-value of less than 0.05 was designated as statistically significant. All statistical analysis was performed using IBM SPSS Statistics version 24 .For THA recipients, there was no significant difference between the IV diclofenac and ketorolac groups in mean total morphine milliequivalents (MME) opioid consumption at 12  or 24 hours  postoperatively  or POD2 , LOS , or discharge destination  ; “During this hospital stay, how often was your pain well-controlled?” ; and “During this hospital stay, how often did the hospital staff do everything they could to help you with your pain?” .For TKA recipients, patients in the IV diclofenac cohort had lower opioid consumption than patients in the IV ketorolac cohort during the first twelve hours postoperatively  , pain intensity on POD1  or POD2 , or mean LOS . The diclofenac group was less likely than the ketorolac group to be discharged home  (Table There was no difference in mean postoperative Knee Society Score (KSS) between the groups . Patients receiving diclofenac were significantly more satisfied with their pain control experience than those who received ketorolac Table .Specifically, IV diclofenac recipients answered “Always” more often than IV ketorolac patients in response to the questions “During this hospital stay, how well was your pain controlled?” ; “During this hospital stay, how often was your pain well-controlled?” ; and “During this hospital stay, how often did the hospital staff do everything they could to help you with your pain?” .Optimizing pain control regimens following TJA is an important aspect to help these procedures transition to the outpatient setting, as improved pain management can improve clinical outcomes and curtail costs . Due to There are some limitations to this study. As we only included procedures performed by a single surgeon at a single institution, the sample sizes are small. However, this was meant to be a preliminary study, reporting the early outcomes of IV NSAIDs in TJA. Additionally, data input and collection may have been susceptible to human error. To minimize this risk, data collection was limited to one investigator and the same nursing floor. Finally, satisfaction was significantly higher for the diclofenac group, despite similar outcomes. This could be due to the small sample sizes, as patients were blinded, and pain intensity was similar in all groups. Nevertheless, the present study is a great starting point for the investigation of TJA outcomes in patients receiving adjunctive IV diclofenac and IV ketorolac.Although TKA patients receiving IV diclofenac had lower opioid consumption at 12 hours, our findings revealed no difference in 24-hour opioid consumption for TKA and THA patients in the IV diclofenac and IV ketorolac groups. Other studies have reported on the comparative decrease in opioid consumption with both IV diclofenac and IV ketorolac. A double-blind, randomized control trial by Alexander et al. compared morphine consumption, as well as pain scores and opioid side effects, in 102 TKA and THA patients who were given IV diclofenac, IV ketorolac, or placebo preoperatively . They reThe present study demonstrated no differences in postoperative pain intensity or LOS between the IV diclofenac and IV ketorolac THA and TKA cohorts. Although prior studies have found decreased postoperative pain with the use of ketorolac and diclofenac in TJA, no study has demonstrated a significant difference between the two drugs. Etches et al. performed a multicenter, double-blinded, randomized controlled trial (RCT) comparing postoperative pain control between TKA and THA patients who received general anesthesia with placebo (n = 88) or with continuous infusion ketorolac (n = 86) . CompareAlthough patients in both THA and TKA diclofenac cohorts had increased satisfaction with IV diclofenac over IV ketorolac, outcomes were similar between the cohorts. Similar postoperative pain intensities and opioid consumption demonstrate the effectiveness of both drugs in managing postoperative pain. However, there are no studies comparing the cost of IV diclofenac to IV ketorolac for orthopedic surgery. In our institution, there is a vast pricing difference between IV diclofenac and IV ketorolac. The cost of four doses of IV diclofenac is USD 48.00, while the cost of four doses of IV ketorolac is USD 3.12. When extrapolated for 1,000 patients, the cost savings between these two drugs becomes apparent . This supports the utilization of IV ketorolac in postoperative pain management to yield the greatest cost savings. Nonetheless, the utilization of IV NSAIDs for pain management after TJA appears beneficial in reducing opioid consumption and may be well suited to supporting outpatient surgery in the future.Optimizing postoperative pain management is essential to improving clinical outcomes and reducing costs, especially as TJA moves out of the hospital. The addition of NSAIDs to the postoperative pain regimen is a promising way of decreasing opioid consumption and reducing postoperative pain. This study demonstrated that both TKA and THA patients treated with IV diclofenac had no difference in postoperative pain intensity while THA patients had no difference in opioid consumption relative to those treated with IV ketorolac. Further comparison of IV NSAIDs with other IV pain medications may provide broader insight into the ideal management of postoperative pain for this widening patient population.


Cooking time varied from 19 to 271 minutes with the genotypes Cebo Cela and Ervilha consistently cooking fastest in 24 and 27 minutes respectively. Comparatively, the local checks  took 35 to 45 minutes to cook. Cooking time was largely controlled by genotype (40.6% of TSS). A GGE biplot analysis uncovered the presence of two mega-environments for yield and one mega-environment for cooking time. Identification of mega-environments for these traits will help expedite common bean breeding, evaluation, and variety selection through reduction of number of test environments needed for phenotype evaluations. The high yielding and fast cooking genotypes from this study can be targeted as parental materials to improve existing common bean germplasm for these important traits.Common bean variety choice by farmers in Uganda is driven by seed yield plus end-use quality traits like market class and cooking time. Limited genotype by environment information is available for traits valued by consumers. This research evaluated yield, seed size, hydration properties, and cooking time of 15 common bean genotypes within market classes recognized by consumers along with three farmers’ checks at nine on-farm locations in Uganda for two seasons. Yield ranged from 71 to 3,216 kg ha Common bean (Phaseolus vulgaris L.) is a widely grown and consumed staple crop in many parts of Latin America and Africa including Uganda3. In Eastern Africa, Uganda is the second largest producer of common bean and consumption provides 25% of the calories and 45% of the daily protein requirement4. In Uganda, on-farm yields are often very low compared to those reported on research farms5. Reasons for the low on-farm yields include: (1) Use of poor-quality farmer saved seed; (2) Use of unimproved landrace genotypes that are susceptible to diseases and insect pests; (3) The poor soil fertility conditions and variable weather patterns in the production areas6. In Uganda and throughout Eastern Africa, farmers often place a greater value on end-use characteristics like seed color, seed size, flavor, and cooking time when compared to actual seed yield7.The world population is projected to reach 10 billion by the year 2050 and crop varieties that are resilient, productive, and nutritious under changing biotic and abiotic threats are urgently needed to meet the food security needs of the expanding population8. Seed yield performance is often measured through collaboration at University research sites, International Center for Tropical Agriculture and the National Agricultural Research System. However, there is limited information on studies conducted on farms owned and managed by the common bean growers8. On-farm participatory evaluation of genotype and genotype by environment interactions can identify novel germplasm suited for specific agro-ecological conditions, as previously demonstrated for rice in India9, sweet potatoes in Uganda and South Africa11, and cassava in Tanzania12. Genotypic yield performance is influenced by multiple genes interacting with biotic and abiotic stress factors over the course of the crop’s growing season13. Additionally, evaluation of germplasm on farmers’ fields enables plant breeders to determine crop genotype performance amidst natural disease and pest pressures in the target locations14.Determining the degree of genotype by environment interactions for yield performance in common bean has been a major focus for plant breeders16. Therefore, new common bean varieties for Uganda must have improvements for both seed yield and end-use quality traits. One important end-use quality trait in common bean is cooking time because the crop often requires large amounts of heat energy to cook before consumption17. A large proportion of the population in Eastern Africa use either fuelwood or charcoal as the primary source of energy for cooking18. The process of gathering (and purchasing) wood fuel for cooking is a labor-intensive and time-consuming activity for families especially those living in the rural communities19. Genetic variability for cooking time exists in common bean and there is potential to improve this trait in new varieties belonging to the market classes recognized by the consumers21.Recent studies in Uganda have revealed that common bean farmers attach equal value to both agronomic performance and end-use quality traits23. On-farm trials that include cooking time evaluation offer numerous advantages, including direct feedback about the harvested materials from the end users. Additionally, the approach allows for measurement of genotype performances at the actual environments where the future common bean varieties will be released for adoption, production, consumption, and marketing24.Cooking time has been shown to be highly heritable with limited effects of genotype by environment interactionsGiven common bean’s wide range adaptation and importance as a food and nutrition security crop, our study evaluated the magnitude of genotype plus genotype by environment responses for seed yield, seed size, water uptake, and cooking time traits in 15 common bean test genotypes across nine on-farm locations spanning three agro-ecological zones in Uganda. The test genotypes were evaluated along with the farmers’ local check varieties. Local check varieties were included to serve as benchmarks for each measured trait and determine the overall potential value of the test genotypes as parental materials to improve common bean for the aforementioned traits.Results of the analysis of variance (ANOVA) for all traits are presented in Table 2) estimates for all traits ranged from 46.8 to 96.5%. Seed yield had a moderate heritability estimate of 69.7% while seed weight had a high broad-sense heritability estimate of 96.5%.The most important source of variation for seed yield was location  and the interaction component between location and season (48.6% of TSS)  and bean common mosaic virus (a member of the Potyvirus).Differences in environmental mean performance were large for yield with values ranging from 336 to 1,057 kg haSeed weight varied from 19–63 g per 100 seeds  and G8 (Chijar) denote higher yielding and genotypes trending towards the opposite direction represent the poor performing lines like G4 (Cebo Cela) and G12 (Uyole 96) Fig. . GenotypGenotypes in the direction of G2 (Ervilha) and G13 (Charlevoix) absorbed more water while genotypes in the direction of G9 (Vazon 7) and G5 (Amarelo Cela) had lower water uptake values Fig. . Most geP value < 0.0001). Seed weight was positively correlated to water uptake  but negatively correlated to cooking time   implying that soaked beans that absorbed the most water cooked faster . The two top yielding varieties were both indeterminate Middle American small-seeded genotypes. While these genotypes were all landraces with limited potential for direct release, their on-farm yield performance was similar to previous reports that showed indeterminate Middle American germplasm to produce higher yields and can thus be used as parents in breeding crosses to improve the determinate common bean types.30. There were also large differences in mean performance for yield across locations due to variability in disease pressure and soil characteristics with non-tropical varieties from North American being the most susceptible. Location TW in Kamuli district had insufficient soil NO3-N and lowest yield performance of 336 kg ha−1 demonstrating that soil fertility is a major challenge to common bean farmers in this region  cutting through the sides of the polygon divide groups of genotypes and environments into sectors32. This study revealed presence of two mega environments for yield . In common bean, seed size is strongly tied to gene pool structure. Andean genotypes are usually larger when compared to genotypes from the Middle America gene pool35. Hardshell is induced under semi-arid environmental conditions during seed fill and maturation and dry storage conditions36. Some genotypes are more susceptible to hardshell than others37. Hardshell is one reason for long cooking times, but it can often be reversed by storing harvested common bean seeds at ~68% relative humidity before cooking38. Genotypes G5 (Amarelo Cela), G8 (Chijar), and G9 (Vazon 7) that all belong to the Middle American gene pool were the most susceptible to the hardshell condition in this study. Genotypes grown at locations TW and GE in Kamuli district exhibited more hardshell defect as they imbibed the least amount of water.Hydration properties as measured by water uptake after 12-hour soaking, is an important parameter to evaluate seed quality in common bean. Typically, seeds will take up water at least 90% of their weight during a 12-hour soaking period. Hardshell is a phenomenon used to describe beans that take up insufficient water during soaking39 reported that genotype Amarelo Cela also accumulated the highest concentration of seed calcium. Presence of free calcium ions in the seed has been reported to form crosslinks with cell wall polysaccharides resulting in reduced cell separation and longer cooking times41.Genotypes G5 (Amarelo Cela), G8 (Chijar), and G9 (Vazon 7) were also among the longest cooking accessions, showing that water uptake may be a useful predictor of long cooking time, although not always since G10 (PR0737-1) also had the second longest cooking time but still absorbed 110.7% water following a 12-hour soak. Therefore, genotype G10 (PR0737-1) likely has a different mechanism for long cooking time that is not related to the seed coat but could be related to its cotyledon structure. The longest cooking genotype G5 (Amarelo Cela) was a yellow grain colored landrace from Angola (Table The three fastest cooking genotypes G1 (Blanco Fanesquero), G2 (Ervilha), and G4 (Cebo Cela) cooked at least 10 minutes faster than the farmers’ local checks, indicating a potential valuable germplasm source that can be deployed to breed for fast cooking common bean for Uganda. The strong influence of genotype and the lack of large genotype by environment interactions for this cooking time suggest that breeding and evaluation for this trait can be carried out in fewer environments. In addition, the GGE biplot result showed presence of one mega-environment for cooking time Fig.  which fu42. Using this methodology, stability of genotypes is measured by the length of their projection from the AEC horizontal axis  view (genotype mean performance vs. stability) allows for the comparison of genotypes based on estimates of genotype performance and stability across environments within a mega-environment43. This study showed that yield was correlated to seed size. Previous studies have showed that increasing seed size results in a yield penalty and this has been one of the major limitations to yield improvements among genotypes in the Andean versus those in the Middle American gene pool33. No correlations were found between seed yield and water uptake or cooking time, suggesting that fast cooking varieties will not suffer a reduction in seed yield.From a plant breeding perspective, correlation analysis can help identify positive or negative relationships among traits, identify novel parental combinations for variety development and detect trait measurement redundancyCommon bean genotypes with higher yields than the local checks were identified, although these had smaller seed size and longer cooking times than the farmers’ selected local checks. Fast cooking genotypes were also identified, including landraces G2 (Ervilha) and G4 (Cebo Cela), and the Ecuadorian white kidney variety G1 (Blanco Fanesquero) but none of the fastest cooking genotypes had higher yield than the preferred NABE-15 local check. There is a need to pyramid fast cooking and high yielding traits into a single genetic background and to evaluate preference of fast cooking genotypes among farmers and consumers. The moderate broad-sense heritability for on-farm seed yield and cooking time suggests phenotypic selection for these traits can allow for improvements in trait performances. With a single mega-environment for cooking time it is feasible that common bean germplasm evaluation and selection for this trait can be conducted in one or few test locations thus maximizing the value of resources available to the in-country breeding programs. On-farm varietal selection with farmers participation may be a well-suited strategy to identify fast cooking genotypes that appeal to growers and consumers.27.The study was conducted at nine on-farm locations representing three agro-ecological zones across Hoima, Kamuli, Rakai, and Masaka districts in Uganda Table . Hoima a44. Kamuli district receives an annual rainfall ranging from 800 to 1,300 mm with temperatures ranging from 16 to 31 °C44. Both Masaka and Rakai districts are located near Lake Victoria in Central Uganda and these districts receive an annual rainfall ranging from 850 to 2,125 mm. The annual temperature varies from 15 to 27 °C45. Across each of the on-farm locations variable amounts of rainfall, fluctuating number of rain days, and increasing changes in temperatures of 0.5 to 0.9 °C have been recently reported by Mubiru44.All study locations receive bimodal rainfall with the first rains falling from March to May while the second rainy season is from mid-September to early December. Hoima district receives rainfall ranging from 800 to 1,400 mm per year with temperature ranges of 15 to 30 °Chttp://www.spnl.msu.edu) for evaluation of nutrient composition. Soil fertility analysis was conducted to measure pH, organic matter (OM), nitrate-nitrogen (NO3-N), Bray-1 extractable phosphorus (P), potassium (K), and calcium (Ca) based on previously published protocols46.Before planting, soil samples were collected from a soil layer depth of 0-to-30 cm at each of the nine on-farm sites for field seasons 2015 and 2016. The composite soil cores from each site were mixed and allowed to air-dry separately in Uganda, then shipped to the Soil and Plant Nutrient Laboratory at Michigan State University  and BA (2015) had soil P levels below the optimum value of 36 µg g−1 required for good crop productivity on agricultural soils , AG (2015), and KV (2016) had organic matter greater or equal to 3% (Supplementary Table http://arsftfbean.uprm.edu/bean/) germplasm of over 200 lines previously field-grown in Montcalm, Michigan, USA in 2012 and 2013. The panel has been characterized for cooking time, seed mineral concentration, and iron bioavailability47. Genotypes targeted for inclusion in the 15-germplasm set had variable cooking times (from fast to slow cooking), iron (Fe) concentrations greater than 70 µg g−1 and zinc (Zn) concentrations greater than 30 µg g−1 on a dry weight basis47. Three of the genotypes were dark red kidney, four were yellow, five were red mottled, and there was one genotype from each of the white, small red, and light red kidney seed market classes. Most of the yellow and white colored genotypes were faster cooking and had higher Fe bioavailability when compared to the dark red kidney and red mottled accessions. The red mottled genotypes were particularly slower cooking but had higher concentrations of Fe and Zn47.The genotypes were chosen from a large Andean Diversity Panel  was grown in AG and was also released by NaCRRI in 1999. NABE-4 is a large red mottled variety described as fast cooking, drought tolerant, and high yielding49. Eleven genotypes and all local checks had type I determinate growth habit while the other five genotypes were indeterminate  is a cream mottled common bean variety that is popular with farmers in Uganda and was grown at six locations  for field seasons 2015 and 2016. NABE-15 was released in 2010 by National Crops Resources Research Institute (NaCRRI) of Uganda with the attributes of high yield, fast cooking, and anthracnose resistance−1 to all sites in both field seasons. During each growing season the research plots were kept weed-free by two cycles of hand-weeding at 30- and 45-days post-planting. The trial plots were harvested and threshed by hand and all harvesting was completed by the first week of December in 2015 and third week of June in 2016.The experiment was conducted as a randomized complete block design with two field replications for all genotypes at the nine on-farm locations. Each genotype plot was comprised of five rows that were 3.5 m long with 0.5 m between row length. The entire five-row genotype plot was planted with 220 seeds. The study was conducted for two field seasons during the long rainy season of 2015 (September - through early December) and the shorter 2016 rainy season (March to May). Planting was initiated at the onset of rains (first week of September in 2015) and (first week of March in 2016). At planting, a light application of starter fertilizer containing nitrogen, phosphorus, and potassium (NPK: 17-17-17) was applied at a rate of 125 kg ha2 and converted to kg ha−1. Seed weight was collected by counting 100 seeds and measuring their weight in grams.Seed yield was collected on all harvested genotypes from a research plot area of 7 mPrior to soaking and cooking, a total of 150 seeds for each genotype in both field seasons was placed in paper envelopes and kept at 4 °C (relative humidity of 75%) to ensure that seeds maintained a moisture content of 10–12%. Before conducting the water uptake and cooking time experiments, the seed moisture content of each genotype was measured using a Moisture Check Plus meter . To measure the hydration properties (water uptake) of the common bean genotypes, 30 moisture equilibrated seeds were weighed and then soaked in distilled water (1:8 raw seed weight/water weight) for 12 hours at room temperature. The seeds were then drained, bloated dry, and reweighed to compute water uptake based on the following equation:50.To quantify cooking time, a total of 25 soaked seeds from each genotype were cooked using a pin-drop Mattson cooking device . The Mattson cooker utilizes 2 mm stainless steel rods (each weighing 70 g) positioned above the center of each common bean seed during the cooking process. The Mattson cooker is then lowered into a four-liter stainless steel beaker containing 1.8 liters of boiling distilled water heated over a Waring SB30 portable burner. Cooking time was recorded as the number of minutes for taken for 80% of the pin-rods (i.e. 20 out of 25) to puncture through seeds under a steady boil at 100 °C51. Pearson correlation coefficients among traits across locations and years were determined using the PROC CORR statement also in SAS. The variance components for estimating broad sense heritability (H2) for all traits were computed using the PROC VARCOMP statement in SAS v9.4 using the restricted maximum likelihood estimation method51. The statistical model used for the ANOVA and computing variance components in SAS v9.4 is shown below:ijkm is the response variable like yield or cooking time of the ith common bean genotype in the mth replication of the jth location in the kth season; µ is the grand mean; Gi, Lj, Sk, GLij, GSik, LSjk, GLSijk are effects of the ith genotype, jth location, kth season and their respective interactions; rep(LS)jkm denotes the effect of the mth replication nested within the interaction term of the jth location and kth season; εijkm is the error term assumed to be normally distributed with mean = 0. For the ANOVA in SAS, the effects of Gi, Lj, and GLij were treated as fixed. The remaining effects were treated as random to estimate Fisher’s protected least significant difference (LSD) and to compare means among the common bean genotypes, as well as the locations for each phenotype. To generate the variance components for computing broad-sense heritability estimates (H2) all effects in the statistical model above were treated as random. Broad sense heritability (H2) was computed using the equation below:The analysis of variance (ANOVA) for all sources of variation was conducted using PROC MIXED statement using the statistical analysis software, SAS v9.452, a GGE biplot analysis was conducted using the GGEBiplotGUI package53 in RStudio. To generate two-way data required for GGE biplot analysis, all location by season combinations for each trait were defined as environments32 and the data files were inputted into RStudio to visualize the GGE patterns. All data were tester centered (G + GE) and non-scaled as described in Yan and Tinker32. Biplots intended to evaluate test environments and genotypes such as “which-won-where” polygons were drawn with column metric preserving singular value partitioning (SVP). Biplots for evaluating genotype and genotype by environment main effects, such as mean performance vs. stability and genotype rankings were drawn with row metric preserving SVP54.To visually assess the presence of mega-environments, trait stability, and genotype rankingsSupplementary information S1.


Four patients attained disease stability with no increase in circulating blasts for ≥4 weeks. Median (range) survival was 106 days (60–502). Target serum lithium concentration was achieved in all patients and correlated with GSK3 inhibition in leukemic cells. Immunophenotypic changes associated with myeloid differentiation were observed in five patients. The combination treatment led to a reduction in the CD34+ CD38– AML stem cell population both in vivo and in vitro. The combination of lithium and tretinoin is well-tolerated, induces differentiation of leukemic cells, and may target AML stem cells, but has limited clinical activity in the absence of other antileukemic agents. The results of this clinical trial suggest GSK3 inhibition can result in AML cell differentiation and may be a novel therapeutic strategy in this disease, particularly in combination with other antileukemic agents. Lithium is a weak GSK3 inhibitor and future strategies in AML treatment will probably require more potent agents targeting this pathway or combinations with other antileukemic agents. This trial is registered at ClinicalTrials.gov NCT01820624.Glycogen synthase kinase-3 (GSK3) inhibitors induce differentiation and growth inhibition of acute myeloid leukemia (AML) cells. Our pre-clinical studies showed GSK3 inhibition leads to sensitization of AML cells to tretinoin-mediated differentiation. We conducted a phase I trial of lithium, a GSK3 inhibitor, plus tretinoin for relapsed, refractory non-promyelocytic AML. Nine patients with median (range) age 65 (42–82) years were enrolled. All subjects had relapsed leukemia after prior therapy, with a median (range) of 3 (1–3) prior therapies. Oral lithium carbonate 300 mg was given 2–3 times daily and adjusted to meet target serum concentration (0.6 to 1.0 mmol/L); tretinoin 22.5 or 45 mg/m Safe and effective treatments for this patient population are greatly needed. AML is defined by maturation arrest as well as rapid proliferation of leukemic cells. Currently available cytotoxic therapies primarily target the latter but not the maturation arrest. Inducing differentiation of leukemia cells is a potentially useful therapeutic approach that can force malignant cells to exit the cell cycle and decrease cell proliferation without overt toxicity. Such differentiation therapy has proven successful in the treatment of acute promyelocytic leukemia  but not l models –7.in vitro testing, at present, lithium is the only clinically available drug that inhibits GSK3  performance status 0–2 was required. Prior treatment for pre-existing hematologic conditions was allowed, including hematopoietic cell transplantation. Concurrent use of hydroxyurea to control circulating blast counts was allowed during the study period. A minimum of 4 weeks was required from the administration of other prior conventional or investigational agents and patients with unresolved grade >1 treatment-related non-hematologic toxicities were excluded. All toxicities were graded according to the National Cancer Institute Common Toxicity Criteria (version 4.0), i.e., NCI CTCAE v 4.0. Patients were required to have adequate hepatic and renal function . Hematologic parameters were not a basis for exclusion. Exclusion criteria included central nervous system involvement by AML. Cerebrospinal fluid (CSF) analysis was not required and was only performed based on clinical suspicion by the treating physician.2/day (dose level 1) or 45 mg/m2/day (dose level 2) in two divided doses, from days 1 to 7 and from days 15 to 21 of a 28-day cycle. Further tretinoin dose escalation to 60 mg/m2/day (dose level 3) and 90 mg/m2/day (dose level 4) was outlined in the protocol if significant clinical activity of the combination was observed in the first two cohorts.Lithium carbonate (lithium) 300 mg was administered orally three times a day (or two times daily for patients age ≥65 years) starting on day - 3 prior to cycle 1 and on day 1 of all subsequent cycles consisting of 28 days . The “leToxicity was graded for severity according to the NCI CTCAE v 4.0. The definition of dose limiting toxicities (DLT) included grade 3 or 4 non-hematologic toxicities attributed to lithium or tretinoin, with the exception of toxicities occurring in the context of tretinoin-induced differentiation syndrome  and toxiDisease response was not a primary endpoint in this study, but evaluated based on previously published response criteria , 18. Subt-test assuming equal variances. Univariate repeated measures analysis of variance (ANOVA) was used to compare group means of continuous variables over the time course of the study. One-way ANOVA was used to compare means across treatment groups for the in vitro correlative analysis.Survival was calculated using the Kaplan-Meier estimate. Patients not known to have died at last follow-up were censored on the last date they were known to be alive. For correlative studies, comparison of means between two groups or time points was performed using two-sample Blood samples were collected at baseline, days 1, 8, and 30 and at the end of the study period. Specimens were processed only if ≥5% leukemic cells were present in the blood as assessed using morphologic criteria. Using this criterion, seven patients had blood samples evaluated for laboratory correlative studies. Bone marrow was collected at baseline and end of study. Immunophenotyping was performed by multi-parameter flow cytometry using fluorochrome-labeled antibodies to CD11b, CD14, and CD15 as markers for monocytic and/or granulocytic differentiation –22. The in vitro studies. All patients previously gave written informed consent to the respective institutions at time of E1900 or E3999 study enrollment for participation of therapy and blood sample collection. Cryopreserved cells were thawed and cultured in RPMI 1640 media (Hyclone) containing 10% fetal bovine serum  and 1% final concentration penicillin and streptomycin. Amphotericin B (0.5 μg/ml) and ciprofloxacin (10 μg/ml) were added to help eliminate fungal and mycoplasma contamination in the cell culture. Cells were treated with SB415285 (10 μM) obtained from Tocris , a laboratory-grade GSK3 inhibitor which competitively binds to the ATP binding site of GSK3  tumor repository of newly diagnosed and untreated AML patients  to conduct  of GSK3 , and treBetween May 2013 and August 2015, 12 patients (nine men and three women) were enrolled. Three patients enrolled in dose level 1 were considered not evaluable for DLT as they did not complete a full cycle of therapy. One subject discontinued study participation due to personal choice after 10 days, without observed toxicity. The second patient had rapidly progressive disease with high circulating blast counts and came off study at 12 days. The third patient had mast cell leukemia, a rare variant of AML, and was enrolled in the study after intolerance to initial therapy with imatinib. He had biopsy-proven gastrointestinal infiltration with mast cells, and had progressive disease characterized by gastrointestinal hemorrhage secondary to histamine release  after receiving only 9 days of study treatment. These patients were replaced with 3 additional patients. Median age of the remaining nine evaluable patients was 65 (range 42–82) years. Baseline patient characteristics are summarized in Patients who received at least one dose of protocol therapy were evaluable for toxicity. One patient enrolled in dose level 1 presented with delirium and confusion during his third week of treatment. His confusion required hospitalization (CTCAE grade 3) and was attributed possibly to lithium toxicity, although the patient had underlying dementia and recent exposure to psychotropic medications including benzodiazepine, diphenhydramine, and steroids. The serum lithium concentration at admission was below the reference range for toxicity (0.28 mmol/L). The patient's mental status improved within 48 h after withholding all potential offending medications, including lithium. This neurologic event was considered a DLT. Dose level 1 was subsequently expanded to a total of six patients; no additional central nervous system toxicity or DLTs were observed. Three patients were enrolled at dose level 2 with no DLT observed. Adverse events are summarized in n = 2) did not have an effect in disease response or survival.The median duration on treatment protocol for the nine patients was 55 (range 31–112) days. The median number of cycles of therapy was 2 (range 1–4). Response to treatment was assessed after 2 cycles or at the time of removal from study. No patient achieved hematologic improvement using standard AML response criteria. Disease progression occurred in all nine patients. Four patients had a period of disease stability defined by absence of increase in circulating blasts for ≥4 weeks. Of these four patients, none had sustained improvement in other blood count parameters or significant improvement in transfusion requirement. Median survival was 106 (range 60–502) days for the nine evaluable patients. Treatment with hydroxyurea  induction of myeloid differentiation of leukemia blasts; and (3) the effect of GSK3 inhibition on the AML stem cell population.Correlative laboratory studies were performed to investigate the following: (1) in vivo to significantly inhibit GSK3 (The laboratory-defined target serum lithium concentration (0.6–1.0 mmol/L) was achieved at least once in all nine patients ; howeverbit GSK3 . The inhbit GSK3 . Baselinbit GSK3 .We next evaluated for differentiation by measuring the increase in the percentage of cells expressing surface antigens associated with myeloid differentiation . This was measured as a fraction of all peripheral blood mononuclear cells (PBMCs) as well as specifically within the CD34 and/or CD117-positive blast population. Analysis of both of these compartments allowed for assessment of the total population of cells, including leukemia blasts that may have lost CD34 and/or CD117 expression with differentiation.Seven subjects had samples evaluable for analysis (based on pre-defined criteria of ≥5% circulating blasts). Overall, changes in expression of the surface antigens associated with myeloid differentiation was variable throughout the study period . NonetheLastly, we investigated the potential for our therapeutic approach to target the AML stem cell population as these cells are poorly targeted by current AML therapies and play a key role in disease relapse , 26. We in vitro studies to assess whether this effect was due to tretinoin-mediated GSK3 inhibition, or the combination. These studies were performed using cryopreserved blood samples from newly diagnosed, untreated AML patients that were obtained independently of this trial. After thawing, these cells were cultured and treated for 6 days with a laboratory-grade GSK3 inhibitor SB415285, tretinoin, or the combination. SB415285, a more potent GSK3 inhibitor than lithium, was chosen to study the specific effect of GSK3 inhibition on AML stem cells. The combined in vitro treatment with SB415285 and tretinoin resulted in a greater decrease in the CD34+ CD38– AML cell population compared to either agent alone in three of nine samples tested  exhibited disease stability while on the study regimen, defined by the absence of increase in the circulating blast count for ≥4 weeks. While all patients eventually had progressive disease, the disease stability observed in a proportion of the study population serve as a basis for further investigation of GSK3 inhibition as a therapeutic approach for AML. Furthermore, this therapeutic approach may be more effective in patients with minimal residual disease following conventional chemotherapy and warrants further study in this setting.One DLT was observed in our phase I study: a case of delirium in an elderly patient with underlying dementia. Although the serum lithium levels were low, the event was considered as possibly related to lithium, as central nervous system abnormalities can occur even with sub-therapeutic lithium serum concentrations, especially in elderly subjects. Hematologic adverse events were common, although these toxicities were most likely secondary to persistent and progressive AML. No other severe adverse events were attributable to the combination of lithium and tretinoin, with all other reported serious adverse events considered secondary to progressive disease. The two deaths that occurred within the first 60 days of treatment were secondary to disease progression. While the combination of tretinoin and lithium appeared safe, further dose escalation beyond 45 mg/min vivo  with high specificity (in vitro are under pre-clinical development (Although this study demonstrated the ability to inhibit GSK3 in leukemic blasts and induce AML cell differentiation, it is possible that higher levels of GSK3 inhibition are necessary for greater clinical efficacy. As lithium concentrations cannot be increased significantly without incurring drug toxicity, future studies using more potent GSK3 inhibitors in AML are needed to further investigate this strategy. Several GSK3 inhibitors have been investigated in early-phase clinical trials for malignant –31 and ncificity  that hascificity , 30. In in vivo and in vitro reduction of the AML stem cell population, an unmet need in the field of AML therapeutics. Differentiation therapy in patients with minimal residual disease or low leukemia burden following conventional chemotherapy warrants further investigation. More potent GSK3 inhibitors are likely necessary for greater clinical efficacy and combinations of GSK3 inhibition with cytotoxic therapies may achieve greater clinical activity.In conclusion, our phase I study showed that the combination of lithium and tretinoin is safe and well tolerated and induces leukemic cell differentiation in an older, heavily-pretreated cohort of AML patients with relapsed, refractory disease. Lithium, at clinically attainable serum concentrations, achieved modest GSK3 inhibition. The combination treatment results in All datasets generated for this study are included in the article/The studies involving human participants were reviewed and approved by University Hospitals Cleveland Medical Center Institutional Review Board for Human Investigation. The patients/participants provided their written informed consent to participate in this study.MU wrote the manuscript. MU, TS, and DW performed correlative studies. LS, JI-H, BT, RC, BC, HL, ML, DW, and PC critically revised the manuscript. PC designed and conducted the clinical trial.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.


The retina is a stratified layer of sensory neurons lining the posterior portion of the eye. In humans, fine detail and color vision are enabled by the macula, a central region of the retina dense in cone photoreceptors (PRs). Achromatic low light and peripheral vision are facilitated by rod PRs found with increasing density outside the macula in the peripheral retina. The outer retina is nourished by choroidal blood flow regulated by a single layer of intervening retinal pigment epithelial (RPE) cells. Existing human retinal transcriptome projects have been critical for studying aspects of retinal development and disease however, there are currently no publicly available data sets accurately describing the aging human central retina, peripheral retina, and supporting RPE/choroid. Here we used Illumina RNA sequencing (RNA-seq) analysis to characterize the mRNA transcriptome of rod and cone PR-enriched human retina as well as supporting macular RPE/choroid tissue. These data will be valuable to the vision research community for characterizing global changes in gene expression in clinically relevant ocular tissues. Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12464540 Once made publicly available, genome-wide experiments provide the research community with valuable data that can be subsequently mined to further scientific knowledge. Beyond submission to public repositories, detailed curation of these datasets is critical for accurate interpretation and repurposing of NGS data. NGS technology has allowed for extensive eukaryotic transcriptome analysis using a wide range of tissues and single cells harvested from a variety of species3. These RNA-seq analyses have become the gold standard for in depth characterization of global differences in transcript expression as well as the accumulation of novel tissue and cell-specific transcript isoforms.Since the emergence of commercial Next Generation Sequencing (NGS) technology ~13 years ago, genomics data represents one of the most proliferative Big Data domains with unprecedented growth projected by the year 20255. Non-mammalian models such as zebrafish and chickens have been successfully employed to characterize global changes in chromatin organization8 and associated transcriptional networks11 during vertebrate retinal development. Mammalian models, particularly the mouse, have been more extensively used to integrate retinal transcriptome and chromatin organization NGS data sets15. Collectively, these data have been critical for the determination of chromatin states required for cell-type specific transcription in vertebrate retinal neurons as well as for modeling rare retinal degenerative diseases. Ultimately though, detailed aspects of human retinal development as well as genetically complex human retinal diseases such as age-related macular degeneration (AMD) have proven difficult to model in non-human animals.The vision research community has greatly benefited over the past decade from a deluge of RNA-seq and associated NGS data describing the neural retina and its supporting tissues16. Rod and cone PR neurons orchestrate cell-specific transcriptional networks critical for differentiation and proper function17. Farkis and colleagues completed the first comprehensive RNA-seq analysis of whole retina tissue collected from three adult human donors18. This analysis provided initial insight into the complexity of the whole human retinal transcriptome including novel exons and novel transcripts expressed in whole retinal tissue. A subsequent study sampling central and peripheral regions of eight adult human retinas hinted at transcriptional networks controlling rod and cone-specific PR function19. However, a 8 mm region of the central retina was collected in this study extending to an area 1.5X beyond the anatomical macular circumference and thereby resulting in rods representing the majority PR cell type in both sample groups. Additionally, Li and colleagues report limited read quality and sampling metrics in their study.The experiment described here is part of a larger ongoing project within the James Madison University’s Center for Genome & Metagenome Studies (CGEMS) investigating transcriptional regulation in the developing, mature, aging, and diseased vertebrate retina. Within the human retina, fine detail and color vision required for reading, facial recognition, and many other day-to-day activities are enabled by the macula, a 5.5 mm central region dense in cone photoreceptors (PRs). Achromatic low light and peripheral vision are facilitated by rod PRs found with sharply increasing density outside of the macula moving toward the peripheral regions of the retina20. Together, the macular retina and adjacent RPE are the primary sites of pathology associated with the complex retinal disorder AMD. RNAs extracted from these tissues were subjected to a rigorous workflow for robust and accurate analysis of mRNA transcriptional networks in clinically relevant ocular cell and tissue types that will be valuable to our research group’s future studies as well as the vision research community . Informed consent from the donor next-of-kin was collected prior to tissue collection. Left and right pairs of whole globe human donor eyes were curated from the National Disease Research Interchange  with an on column DNaseI treatment step per the manufacturer’s instructions Table . IsolateTotal RNA samples were submitted to the Genewiz commercial sequencing facility  for Bioanalyzer quality control analysis  and Illumina Next Generation Sequencing. All submitted samples had an RNA integrity number (RIN) > 8. Stranded TruSeq cDNA libraries with poly dT enrichment were prepared from total RNA from each sample according to the manufacture’s protocol. Libraries for the 37 cDNA samples were sequenced using the Illumina HiSeq sequencing platform yielding 23–34.3 million 150 bp paired end (PE) sequence reads per sample Table .21 (see Code availability 1). Figure 22 (see Code availability 2), including per base . The percentage of aligned reads ranged from 73.9 to 91.1% (Table 24 (see Code availability 4).Between 23–34.3 million PE sequence reads per sample were delivered from Genewiz Table . Trimmomase Fig.  and per ase Fig.  analysis1% Table . Aggrega25 for determination of differential transcript expression between samples (see Code availability 5). Sleuth is available as an R package and was used to generate a principal component analysis (PCA) plot demonstrating the variance between distinct sample groups as well as similarity within sample replicates for all 37 samples , and have been assigned the SRA study accession SRP222833 Table 27. AdditQuality of total RNA fractions was assessed using an Agilent Bioanalyzer to calculate a RNA Integrity Number (RIN). The RIN algorithm determines the RNA quality of the samples with the highest quality having a score of 10. Conventional to NGS analysis, only RNA samples with a RIN > 8 were used for sequencing analysis.Trimmomatic was used to filter and trim minority low quality sequencing reads and bases from downstream analysis Fig. . FastQC 23, with the specific interest in expression quantification of previously characterized mRNA isoforms. An alignment-free pipeline significantly reduces the time of analysis as well as required computing power and file storage, which may be beneficial for some users. Other very fast alignment-free programs such as Sailfish29 and Salmon30 can be used to achieve similar expression quantification analysis with these data. Alignment-free programs however, are not suitable for novel isoform analysis. More traditional alignment-based RNA-seq pipelines such as the ‘new tuxedo’ suite can be used to analyze these data for novel isoforms31. Here our differential gene expression analysis was carried out using the Sleuth software25, however other publicly available packages such as edgeR32 or StringTie31 may also be used for similar analysis. Importantly, QC data presented in Fig. The bioinformatics pipeline applied to our data set outlined in Fig. 33. A recent transcriptome study integrating AMD GWAS data with RNA-seq data from 453 postmortem human retina samples identified three novel candidate AMD-associated genes34. Notably, Ratnapriya and colleagues collected their RNA-seq data from whole retina. In contrast, the study presented here focuses more specifically on primary sites of AMD pathology thereby providing a unique data set to the vision research community.Our data set will be useful for a variety of studies investigating cell type and tissue-specific patterns of gene expression in the human retina, RPE/choroid, and cornea as well as diseases that affect these tissues. In particular, this work will build on existing genomic data sets investigating the human retina and AMD in particular. Fritsche and colleague’s landmark GWAS identified 52 SNPs at 32 loci constituting the majority of AMD heritabilityOPN1SW, OPN1MW, GNAT2, ARR3, PDE6H) were not differentially expressed in our study. Second, cDNA libraries were prepared using a poly dT primer, thus the data set is representative of only polyadenylated transcripts and does not represent many non-coding RNA or other non-polyadenylated cellular transcripts. Additionally, usage of poly dT priming introduces a bias towards overrepresentation of the 3′ end of transcripts, particularly in the case of relatively large transcripts. Finally, the quantity of sequenced and mapped reads per sample in this study (Table 35. Taking these considerations into account, these data will be a useful resource for the vision research community for robust and accurate analysis of polyadenylated transcriptional networks in clinically relevant ocular cell and tissue types.Several considerations must be taken into account when using these data for downstream analysis. First, RNAs were extracted from retinal tissue enriched in rod and cone photoreceptors, RPE/choroid, and whole cornea without any further enrichment for cell type. Therefore, resulting downstream analysis will be representative of heterogeneous mixtures of differing cell types within these tissues. In particular, 3 mm biopsies of the central retina sample a subsection of the 5.5 mm diameter macula encompassing the fovea, parafovea and portions of the perifovea. Though this cone-rich region contains some rod PRs, our data demonstrates that rod-specific transcripts are present at much lower counts compared to adjacent peripheral retina Fig. . These ddy Table  is suffi