The intersection between deafness and culture in sub-Saharan African contexts such as Ghana has culminated in restricted access to sexual and reproductive health (SRH) services. While some attention has been given to the barriers faced by deaf persons in accessing SRH services, discussion of their needs and satisfaction with SRH services is at an embryonic stage. This lends support to the use of sequential mixed-method study design to assess the level of satisfaction and SRH needs of deaf persons.t-tests, analysis of variance, correlations, and multiple regression. In Phase II, a semi-structured interview guide was used to collect data from 60 participants who were drawn from the earlier pool. The interviews were subjected to thematic analysis.This study was guided by explanatory sequential mixed-method study design. Thus, a two-phase data collection approach was adopted. In Phase I, a 32-item questionnaire with 16 items each for satisfaction regarding SRH services and SRH needs, was used for data collection from 288 deaf persons recruited from 3 of the 16 regions in Ghana. The data were subjected to the following computations: means, , there was a convergence between both the qualitative and quantitative data as participants confirmed the lack of consideration given to the needs of deaf persons regarding SRH service provisions.The results showed of correlation and multiple analyses showed a small relationship and significant contribution of needs in the variance of satisfaction. AlsoDeaf persons who took part in this study were unsatisfied with SRH services due to barriers such as sign language interpreters and inaccessible information. Consequently, they expressed the need for preferred mode of communication and expedition of awareness creation on SRH. The study findings warrant the need for policymakers to inculcate the needs of deaf person in SRH services to improve access and thus, enhance satisfaction. For instance, recommendations such as the training of health professionals in the use of sign language could be considered in future SRH policy and other implications, are discussed. Sexual and Reproductive Health (SRH) refers to one’s state of physical, emotional, mental, and social well-being on matters relating to their reproductive system. Access to SRH services has been acknowledged widely as a human right –7. The IDeafness refers to partial or total hearing loss that interferes with the day-to-day living experience of an individual –16. AccoCurrently, as part of the effort regarding achieving a safe world for all, the United Nations, through Sustainable Development Goals , has urged countries to develop a robust system that would enable all persons to have access to essential services such as healthcare –35. In GIn low- or middle-income contexts, little attention has been given to the experiences of deaf persons , 26, 37 RQ1. What is the association between background variables, SRH needs, and satisfaction regarding SRH services among deaf persons in Ghana?RQ2. Will the SRH needs of deaf persons directly predict satisfaction with SRH services among deaf persons in Ghana?RQ3. How do deaf persons perceive their SRH needs and their level of satisfaction regarding SRH services provided to them?In this study, while needs were operationalized as lack of SRH services, which are essential to enabling deaf persons to enjoy appropriate reproductive health, satisfaction was conceptualized as meeting one’s needs. We hypothesized that once the SRH needs of deaf persons are met, satisfaction regarding SRH services will be high. The hypothesis is supported by Abraham Maslow’s hierarchy of needs, which states that humans are motivated by needs –52. WhenThe study was guide by a sequential explanatory mixed-methods design. Data were collected in two phases to enable an in-depth insight into a given problem or phenomena –55. ThusThe study was conducted in two phases. In phase one, data were collected from participants (deaf persons) who were recruited from various districts. In the second phase of the study, interviews were conducted with selected participants who took part in phase one. This was to enable participants to clarify and provide an in-depth explanation of the key trends that emerged in phase one. The sections below present participants’ information, data collection instruments, and procedures as well as data analysis techniques.Participants in this study were selected in collaboration with the Ghana National Association of the Deaf (GNAD), an association that seeks to promote the welfare of deaf persons in Ghana. Prior to the selection, a meeting was held with GNAD, who recommended the recruitment of six districts in three regions (two from each). GNAD believed that the regions suggested for the study represent three main categorizations in Ghana: north (Northern region), middle belt (Ahafo region), and southern sectors (Greater Accra region). The selection of these regions helps recruit participants which may reflect the national population and thus, provide insight into deaf persons in Ghana.The two districts from each region as well as the participants recruited were chosen at random. The list of the districts in the regions were placed before the study research team who random chose the first and last districts on the list. The inclusion criteria which guided the recruitment were as follows: a) participants are members of GNAD; b) lives in the designated areas; c) at least 18 years; and d) capacity to participate in this study. All members of GNAD who met the inclusion criteria were sent invitation and those who agreed to participant in this study visited the organization’s office on weekends to complete the questionnaire. This gave every member present a chance to be part of the study.Phase I: A two-part questionnaire was used for data collection. Part one collected participants’ background information, which includes gender, age, educational qualification, marital status, and religion. This background information was collected based on a review of existing literature e.g., , 40–49) –49 40–49The tool for data collection was made up of two sections. The first part was items on the needs of deaf persons. This section was made up of 16 items anchored on a binary scale . Some of the items on the scale were “I want easy access to education on sexual and reproductive health,” “Sign language interpreters at sexual and reproductive health centers/programs to interpreter sexual and reproductive health information for me (and other deaf people),” and “Sexual and reproductive health messages should be presented in simple and accessible formats such as dramas, videos, and pictures.” All the items were positively worded with a mean score of at most 1.5 interpreted as more needs. The 16-items on the scale were added to generate overall scores for needs .The second part was items on satisfaction regarding SRH services. The section also contained 16 items using a binary scale . The following are some examples of items: “How satisfied are you with access to sexual and reproductive health education?,” “How satisfied are you with the current form in which information on sexual and reproductive health is presented to you?,” and “How satisfied are you with the current respect you receive from health workers?” During analysis, the 16-items on the scale were added to generate overall scores for satisfactions .Delphi technique (which is a content review of the questionnaire by experts)  involvinThe questionnaire was then piloted among 10 participants from different regions. The piloting yielded the following reliability scores: SRH needs (.70) and satisfaction regarding SRH (.88). In this study, the reliability scores as computed using the Cronbach Alpha were as follows: SRH needs (.91) and satisfaction regarding SRH programs (.89).: Based on the emerging issues in phase one of the study  to come and train us in order for us to give more information and services and also to enable us to support other deaf people elsewhere .I do not trust 100% of the information and services on SRH issues I have because I do not fully understand the issues and, also, I think there are more things to learn about SRH issues. I do trust the source because the facilitators cannot share some of their experience because of communication barriers .Many participants said they distrust the information they got from the various sources: “Most of us do not trust them [service providers] because we do not understand what they say on most of the health-related issues” . Another female participant also said: “I do not trust them [services on SRH issues] because I think they may not explain things well for us to understand” . Participant in the focus groups similarly explained that they did not trust their sources of information.Some of us never went to school before and as such could not sign and write well. Therefore, it becomes a problem when we are inquiring for information and services on any of the SRH services from health workers because of lack of sign language interpreters .Other participants also recounted that their low satisfaction could be attributed to a limited level of education. In their view, most deaf women are uneducated and, as such, cannot read to understand the effects of self-medication or other accessible written information.There were mixed reactions from participants on the age group that is more likely to have more SRH needs. While most participants agreed that the young people would have more needs, some said that older young persons have more SRH needs. According to some participants, young deaf persons are more likely to be educated and more aware of their SRH needs. However, some participants said that deaf persons have the least education, and, in view of this, it is likely that young persons would not have much information of SRH. In terms of older persons, some participants said that they have experience that might have helped them develop an understanding of SRH. Overall, there was a consensus among participants that both young and older deaf persons are more likely to have their SRH needs unmet. Almost all participants indicated the need for policymakers to incorporate their needs in national SRH development and planning. Consequently, improved SRH services would enable deaf persons to enjoy their right to SRH. Indeed, most participants agreed that they would be more satisfied with SRH services once their needs are incorporated in policy reforms. Two main themes about needs emerged: using the preferred mode of disseminating information and awareness creation on SRH issues.Health workers and other reproductive health facilitators and teachers are the preferred sources of information for deaf people. This is because they are experienced [on SRH issues] and do share important issues with us, so we want them to provide information on SRH for us but they should use interpreters to facilitate understanding .Responses from the participants indicated that their preferred sources of SRH information were teachers, healthcare centers, and the media. But it appears hospitals would have been the preferred sources if they were deaf-friendly. The following quotes support this viewpoint.There is no organization that can provide information and services on SRH for the deaf people aside from hospitals. This is because hospitals are the only places where we know we can get good information and services on any of the health issues that we may want to know more about .Direct communication with health workers will be more useful because it will make deaf people more conformable. They should also try to train more interpreters and get more pictures with storylines on SRH issues with sign language symbols. Doctors and nurses should make the effort to learn the sign language so that they can communicate effectively with the deaf people on SRH issues. .On the preferred means of disseminating information from these sources, participants mentioned using sign language interpreters, videos, drama, storytelling, and pictures. In addition, health professionals should be encouraged to learn the sign so that they can communicate directly with deaf people. Using these modes of communication would improve access to quality services for deaf people. One participant recounted as follows:There should be education and materials on SRH issues, and also Ghana Health Service should visit church camps, churches, schools and communities to give information to deaf people on SRH issues. Deaf people should also be educated on their right to information and reproductive health issues. With education, I believe they will know their rights and be motivated to seek for information and services on SRH issues. .The provision of education on SRH issues was suggested by participants as the best way to increase knowledge on SRH issues. Participants were unanimous that education would enable deaf people to know more about their rights to health, which will, in turn, encourage them to ask more questions and hold professionals accountable. A focus group participant commented:Access can also be improved through the use of the appropriate formats: “When conducting education on sexual health, bright images, dramas, and banners should be used because it will make them interested to seek for more information on their SRH” . A female interview participant also suggested that “Captions for videos should be used and there should be continuous sensitization on matters concerning reproductive health” .In this study, attempts were made to develop in-depth insight into the satisfaction regarding SRH services and the SRH needs of deaf persons. The study findings support the hypothesized relationship between SRH needs and satisfaction of deaf persons regarding services. The results of the correlation, regression, and follow-up interviews showed the centrality of needs in achieving satisfaction with SRH services. In the conception of the theory of needs, Maslow reiterates the intricate relationship between needs and satisfaction , 51. TheThe quantitative and qualitative data showed convergence between participants on satisfaction regarding SRH services. In particular, satisfaction regarding SRH services was found to be low, claim participant confirmed in the second phase of the study. This finding is slightly consistent with other studies, which reported the inability of health systems to meet the needs of individuals with disabilities, including deaf persons , 39, 40.The results of this study showed participants’ expression of more SRH needs. It is apparent that the more needs of participants, the more current service provisions are inadequate to address the diverse needs of deaf persons. It is useful to state here that some studies have reported the lack of consideration given to the needs of deaf persons in the development or provision of essential services , 27, 40.The participants suggested needs to be included in future SRH policies. For instance, they indicated a preferred mode of communication and awareness creation on SRH as vital to meeting their needs. It is important to state here that a large body of literature has documented challenges to SRH service access to include illiteracy, inaccessible information, and lack of education on SRH , 61–64. One background variable that was found to impact satisfaction regarding SRH is age. As participants grow, they more likely would be unsatisfied with SRH services—a trend that is unexpected. Although previous study has reported the likelihood of aged persons with disability to utilize SRH services , this stIn spite of the contribution of this study to research on deaf persons, the findings should not be generalized to the whole population due to its limitation. First, all the participants in the study were members of GNAD; hence, non-members were not given the opportunity to express their views. Deaf persons who are not members of GNAD could have a contrary view to what has been reported in this study. However, it is worthy to state that the research team deemed it appropriate to collaborate with GNAD in conducting this study because it is a recognized body involved in advocacy for and promoting the well-being of deaf people. Additionally, the participants were from diverse backgrounds; therefore, their experiences could reflect other members of society. Second, the study could not ascertain whether participants were only deaf or had an additional disability. Since the research team did not have the capacity or resources to conduct a hearing assessment, it was prudent to depend on a recognized body such as GNAD to assist in identifying potential participants. Third, since GNAD is actively involved in a section of the study and recruitment of participants, there is a potential bias. It is possible a section of participants who could provide certain responses were invited or the executives did not follow the inclusion criteria in choosing participating districts. Nevertheless, inclusion criteria and selection of participants for the interviews were done solely by the research team. It is therefore recommended that future studies use quantitative design to understand background variables that may influence deaf persons’ perceptions regarding access to abortion services. Overall, a major strength of this study was recruiting male and female deaf persons to share their perspectives on this sensitive topic.This study was conducted using Maslow’s , 52 hierThe findings of the study have implication for policymaking and practice. For example, the communication needs of a deaf person in health service provisioning is vital, as it has consistently been identified as a gap , 25, 37.


Toona ciliata is a traditional woody plant that can be used as a medicinal material in China. The extracts of its roots, stems, leaves, and flowers all have a wide range of bioactive compounds. However, T. ciliata has been facing an unresolved pest problem caused by Hypsipyla robusta Moore (HRM), which seriously affects its growth and development. In this study, the expression level of TcMYB3 gene reached the maximum (28-fold) at 12 h and transcriptome sequencing of young stems eaten by HRM for 0, 3, 12, and 21 h were performed. A large number of differentially expressed genes (DEGs) were identified including jointly up-regulated genes (263) and down-regulated genes (378). JA synthesis and signaling transduction, terpene biosynthesis, and MAPKs signaling pathway were analyzed in depth and found that TcOPR3, TcJAR1, TcJAZs, and TcTPS9 genes possessed anti-insect potential. Moreover, MYB and ERF transcription factor (TF) families were significantly strengthened to the point that they may participate in induced defense mechanisms in T. ciliata. These data not only provide insights into the molecular mechanisms in resistance of T. ciliata to HRM but also helps to explore the new biocontrol strategies against insects in eco-friendly woody plants. Toona ciliata is a wild and endangered plant under the national level II key protection, which belongs to Meliaceae family  adult worms prefer to lay eggs on the T. ciliata leaves, so the stems and apical buds are susceptible to damage from H. robusta larvae feeding on them. This damage will cause a lot of side branches to grow, eventually forming a “multi-headed tree”  is a key enzyme in the JA synthesis pathway. The 12-oxo-phytodienoic acid (OPDA) is transferred to peroxisome and reduced by OPR3. In tomatoes, OPR3 was silenced by RNA interference (RNAi), and it was found that OPR3-RNAi plants contained wild-type levels of OPDA but failed to accumulate JA or JA-Ile after wounding. Meanwhile, the loss of these JA/JA-Ile -dependent defense traits rendered them more attractive to the specialist herbivore AACT) gene, hydroxymethylglutaryl-CoA synthase (HMGS) gene, Hydroxymethyl glutaryl-CoA reductase (HMGR) gene, phosphomevalonate kinase (PMK) gene, mevalonate diphosphate decarboxylase (MDC) gene and mevalonate kinase (MK) gene  attacked rice, the JA and ET pathways was induced to coordinate and negatively regulate defenses  is a new generation of high-throughput sequencing technology developed in recent years  under Agrilus mali stress, different expressed genes were mainly involved in the signal transduction pathway of plant hormones and in the synthesis of compounds such as terpenes, quinones, flavonoids, and JA . T. ciliata young stems are endangered by the 1st and 2nd instar larvae of HRM, which are difficult to cultivate in the laboratory. Therefore, the HRM larvae used in the experiment was collected from the young tenders that had been eaten by the insects in Qilin North Experimental Base (SCAU) and no additional feeding of HRM was required. On the contrary, collected HRM were starved in a blank culture dish for 12 h. In addition, in order to make HRM consistent, the second instar larvae of HRM with a body length of 4–7 cm were selected. Sufficient numbers of HRM larvae were collected to ensure that each HRM only gnawed on one T. ciliata. Then HRM were placed on the young stem of T. cilata  and each T. ciliata was inoculated with one HRM. When the HRM began to bite T. ciliata, the time was counted. The young stems bitten by HRM for 0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, and 36 h were taken respectively, and each time point had three repetitions  not only confer resistance to the brown planthopper by regulating the phenylalanine ammonia lyase pathway in rice , then genomic DNA was eliminated through DNase I (TaKara). Total RNA quality was determined by a 2100 Bioanalyser and quantified using the ND-2000. Finally, the high-quality RNA sample  was used to construct the sequencing library . First, poly-A tail mRNA was enriched from 5 μg total RNA with oligo (DT) magnetic beads. Then the fragmentation buffer was added to randomly break the mRNA into small fragments of about 200 bp  were used to do de novo assembly with Trinity  and WoLF PSORT (https://wolfpsort.hgc.jp/) were combined to predict protein subcellular location.Plant hormone biosynthesis and signal transduction pathways play a vital role in the defense process induced by insect feeding. Three types of plant volatile compounds can be induced, including terpenes, fatty acid derivatives, and phenyl/phenylpropanes (derivatives of shikimic acid), which have important anti-insect functions. Therefore, this study combined the results of differential gene function annotation and the KEGG pathway to analyze the terpene synthesis and JA biosynthesis and signal transduction pathways. The synthetic transduction schematic diagrams of the two pathways are drawn through the reference, and the heat maps of related gene expression are drawn by TBtools  with 500 bootstraps. Meanwhile, the protein sequences of AtLOXs, AtJAZs, AtDXSs, CsDXSs, OsDXSs, PtrDXSs, and AtTPSs were downloaded from the Phytozome database.In the RNA-seq database, genes with more than 10-fold up-regulated gene expressions were regarded as key genes. The protein sequences of the key genes family were from RNA-seq library because there is no genome-wide database of http://planttfdb.cbi.pku.edu.cn/) to obtain the same homologous TFs information. Finally, the specific information of transcription factor analysis and transcription factor family were counted.By analyzing the domain information contained in the transcription product, the TF's prediction and family analysis of the transcript was carried out. Then the HMMER analysis method was used to compare with the database PlantTFDB , cDNA 2 μL, each primer 0.4 μL (10 μM), 7.2 μL ddH2O. Q-PCR reaction was performed in LightCycler480  with an optical 96-well plate. The reaction procedure is 95°C for 30 s; 95°C for 15 s, 60°C for 20 s, 72°C for 10 s, 40 cycles; performing melting curve analysis at 65–95°C, and then through the peak diagram of the melting curve to determine the specificity of primers. There are three biological replicates for each sample and three technical replicates for each biological replicate. According to the Ct value obtained in the experiment, the 2−ΔΔCt method was used to calculate the expression under different conditions. Meanwhile, Duncan's multiple test analysis of Q-PCR data by R software and linear regression analysis with GraphPad Prism 8.According to CDS sequence from RNA-seq database, Q-PCR primers were designed by NCBI-PrimerBlast , 3 h , 12 h , and 21 h  samples were selected for RNA-seq sequencing, to further explore the response pattern of T. ciliata against HRM.The response of plants to insect pests will change dynamically with time. Therefore, Q-PCR was used to quantify the expression of  feeding . The resT. ciliata fed on by HRM for 0, 3, 12, and 21 h were selected as RNA-seq sequencing materials , 10.60% shows strong homology  and the homology of the remaining unigenes is weak   . The num the HRM .T. ciliata in different time periods under HRM feeding. First, TC3, TC12, and TC21 were compared with TC0 to obtain DEGs (up regulated and down regulated) of TC0 vs. TC3, TC0 vs. TC12, and TC0 vs. TC21, respectively. Then, in order to distinguish the DEGs that were jointly up-regulated or jointly down-regulated, the up-regulation or down-regulation of TC0 vs. TC3, TC0 vs. TC12, and TC0 vs. TC21 were compared. The conditions for screening DEGs are |log2(foldchange)| > 1 and p-adjust <0.05. The results show that there are 263 and 378 genes that are jointly up-regulated and down-regulated, respectively  at 21 h  to dynamically adjust the content of IPP and DMAPP  catalyze the head-to-tail condensation of IPP and DMAPP to isoprene GPP, FPP, and GGPP . In addition, most members of the C2C2 TF family (5/7) are down-regulated, and TRINITY_DN14674_c1_g1, TRINITY_DN53864_c0_g1 are down-regulated by 44.52 and 33.92 times, respectively. Meanwhile, TRINITY_DN8705_c0_g1 is up-regulated by 21.73 times which may have potential to resist HRM. In addition, the bHLH (TRINITY_DN15909_c0_g1) is down-regulated by 24.77 times at 12 h. The genes mentioned above play a vital role in the process of T. ciliata resisting pests, and it is worthy of in-depth study in the later stage.In order to discover the potential TFs with anti-insect function, the classification and expression level of TFs in the RNA-seq database were analyzed in depth. A total of 1,120 TFs are divided into 35 families . The mosT. ciliata transcriptome data, 20 single genes related to JA and terpene biosynthesis were selected for Q-PCR analysis (R2 = 0.9498) at the level of P ≤ 0.001  at 3 h of HRM feeding, and remained at 500 ng/g at 12 and 21 h  and the second sampling time  were first determined. The determination of the third sampling time is based on the time rhythm. That is to say, the interval between the third sampling time and the second sampling time is the same as the interval between the second sampling time point and the first sampling time point, so as to minimize the influence of time rhythm on transcripts.In this study, the second instar larvae with a body length of 4–7 cm were selected for 12 h starvation culture which contributes to the smooth running of the gnawing experiment  signaling pathway involved in crosstalk with mitogen-activated protein kinases (MAPKs) also leads to the formation of JA  can induce the accumulation of terpenoids in its resin canal to effectively deal with the damage of beetles -α-bergamot emission than JA-Ile, suggesting that JA-Ile modulates specific aspects of herbivore resistance. This specificity may allow plants flexibility in the trade-off between herbivore resistance and growth and reproduction during ontogeny , accession number are SRR18680895, SRR18680894, SRR18680893, SRR18680892, SRR18680891, SRR18680890, SRR18680889, SRR18680888, SRR18680887, SRR18680886, SRR18680885, and SRR18680884.The data presented in the study are deposited in the SRA repository in submission SUB11223109 , Guangdong Basic and Applied Basic Research Foundation (Grant No. 2021A1515010534), Science and Technology Project of Guangzhou (Grant No. 202102080217), and Characteristic Innovation Projects of Department of Education of Guangdong Province (Grant No. 2019KTSCX017).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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Dear Editor:KMT2A::MLLT4 fusion in June 2018. First-line treatment was initiated according to the AIEOP-BFM ALL 2009 registry protocol and demonstrated a poor response to the prednisone prephase and high leukemic cell loads by measurable residual disease (MRD) during and after induction therapy  . , 2. KMT2Providing mechanistic support for our observation, a recent study demonstrated that the addition of venetoclax potently enhances the efficacy of therapeutic antibodies including daratumumab in CD38-positive malignancies, because of an increase in antibody-dependent cellular phagocytosis by macrophages . The une


In this work we used colocalization single-molecule spectroscopy (CoSMoS) to elucidate the pathway of 5' SS selection by purified yeast U1 snRNP. We determined that U1 reversibly selects 5' SS in a sequence-dependent, two-step mechanism. A kinetic selection scheme enforces pairing at particular positions rather than overall duplex stability to achieve long-lived U1 binding. Our results provide a kinetic basis for how U1 may rapidly surveil nascent transcripts for 5' SS and preferentially accumulate at these sequences rather than on close cognates.In eukaryotes, splice sites define the introns of pre-mRNAs and must be recognized and excised with nucleotide precision by the spliceosome to make the correct mRNA product. In one of the earliest steps of spliceosome assembly, the U1 small nuclear ribonucleoprotein (snRNP) recognizes the 5' splice site (5' SS) through a combination of base pairing, protein-RNA contacts, and interactions with other splicing factors. Previous studies investigating the mechanisms of 5' SS recognition have largely been done in vivo or in cellular extracts where the U1/5' SS interaction is difficult to deconvolute from the effects of  In eukaryotes, the introns of precursor messenger RNA (pre-mRNA) must be identified and removed with nucleotide precision by the spliceosome to produce mRNA . The junU1 small nuclear ribonucleoprotein complex (snRNP) is responsible for 5ʹ SS selection during the earliest steps of spliceosome assembly . The 5ʹ Saccharomyces cerevisiae (yeast) and human U1 snRNP has revealed how snRNP proteins could play key roles in 5ʹ SS recognition in addition to base pairing with the SSRS. In crystal structures of human U1 snRNP bound to a 5ʹ SS-containing RNA oligonucleotide (oligo), the conserved U1-C protein (Yhc1 in yeast) contacts the SSRS/5ʹ SS duplex in the minor groove at the pairing site between the nearly invariant 5ʹ SS G(+1) and U(+2) nucleotides with the snRNA  or the branch site bridging protein (BBP)/Mud2 complex, that together with U1 form the yeast E complex spliceosome or commitment complex  has previously been used to study the kinetics of both yeast and human U1/RNA interactions in cell extracts . In all  complex . Our res complex . Yet, neIn this study, we use CoSMoS to directly observe how individual yeast U1 snRNP molecules interact with short RNA oligos. The short- and long-lived interactions observed in cell extracts with large pre-mRNA substrates are also observed when purified U1 snRNP binds cognate RNAs providing direct evidence for these kinetic features being inherent to 5ʹ SS recognition. By using RNA oligos with varying base-pairing strength to the snRNA as well as with different locations and types of mismatches, we show that 5ʹ SS recognition leading to long-lived complexes occurs subsequent to binding. RNAs with limited pairing to the SSRS are released quickly after association while those with extended complementarity and pairing at certain positions are more likely to be retained and form long-lived complexes. Significantly, formation of long-lived U1/RNA complexes does not always correlate with the predicted thermodynamic stabilities of the SSRS/5ʹ SS RNA duplexes, which likely reflects the importance of snRNP proteins in the process. We propose that U1 uses a multi-step kinetic pathway to discriminate between RNAs and that formation of long-lived complexes is dependent on multiple factors that together favor U1 accumulation on introns competent for splicing.trans-acting factors, we first developed a protocol for purifying fluorophore-labeled U1 snRNP from yeast extract. We genetically encoded a tandem affinity purification (TAP) tag on the U1 protein Snu71 and a SNAP-tag on the U1 protein Snp1 in a protease-deficient, haploid yeast strain -long RNA oligonucleotides with varying degrees of complementarity to U1 . The RNAWe immobilized the purified U1 snRNP with streptavidin on a passivated and biotinylated glass slide  and readS) was ~13 s with an amplitude of 0.89 (where amplitude reflects the proportion of this time constant across the entire distribution), while the long-lived kinetic parameter (τL) was much larger (~177 s) but with a smaller amplitude (0.11). When we increased the frame rate fivefold, we observed a similar distribution of signals that yielded similar fit parameters  also resulted in multi-exponential dwell time distributions . The exptrans-acting factors present in a WCE or folding/unfolding of large RNA substrates. We do not exactly know how these factors influence U1 binding in complex environments, but they may be the origins of differences we observed between experiments carried out with purified U1 and with U1 present in WCE.Together, our data indicate that short- and long-lived interactions with RNA substrates are an inherent property of U1. Since we purified and immobilized U1 and studied its interactions with small RNAs, the diversity of binding events cannot solely originate from the influence of We next systematically studied how the base-pairing potential of the RNA oligo influenced binding by U1 snRNP. We carried out single-molecule binding assays with RNAs capable of forming between 4 and 10 contiguous base pairs with the snRNA . All theWhen the number of binding interactions to immobilized U1 and the apparent association rates were measured, the RNA oligos exhibited two observable and distinct classes of behavior. In the first class, RNA oligos capable of forming <6 contiguous base pairs showed very few colocalized binding events with U1 . While tassociation) to U1 under these conditions  and a mixture of short and long dwell times for RNAs capable of forming increasing numbers of base pairs (RNA-8a and RNA-10). When the individual dwell times from each experiment were combined and fit to single- or double-exponential functions, resulting probability density plots and kinetic parameters confirmed these observations (S ≈ 12 s), consistent with short-lived binding. RNA-8a can make up to eight base pairs with U1 and its dwell times were best fit using an equation with two kinetic parameters describing short- (τS≈ 43 s) and long-lived binding events (τL ≈ 137 s). RNA-10 also require two exponential parameters to describe the data, yielding longer ‘short-lived’ events (τS ≈ 120 s) as well as increased dwell times for the longer-lived events (τL ≈ 355 s).We next studied the dwell times with U1 for the same series of RNA oligos. By visually inspecting the individual fluorescence time trajectories, we were immediately struck by apparent differences in binding behaviors. We frequently observed very short dwell times with RNAs capable of only forming a small number of base pairs (rvations . RNA-6a S < 120 s) with a small fraction of long-lived (τL > 120 s) binding events and correspondingly small amplitude for the long-lived kinetic parameter (L. It is unlikely that these results arose from presence of two subpopulations of U1 snRNPs in our experiments (one capable of only making short-lived interactions and one capable of only making long-lived interactions) since we would not expect these subpopulations to change in abundance between experiments carried out with the same preparations of U1. Furthermore, hidden Markov modeling of RNA-4+2 (which considers the relationship between consecutive binding and unbinding events) favored a sequential scheme involving RNA binding followed by a transition to long-lived state  can form the short-lived complex. RNAs with a limited number of base pairs  rarely progress through the second step to form the long-lived complex and most often dissociate from the intermediate state. On the other hand, RNAs with many base pairs (RNAs-7–10) are more probable to transition to the long-lived complex.Instead, these data are most consistent with a mechanism in which U1 association with RNAs involves multiple steps. All RNAs that we can observe interacting with U1  also varied (S) ranged from 12 to 120 s for RNA oligos capable of forming 6–10 contiguous, potential base pairs. The long-lived dwell time parameter (τL) ranged from 137 to 388 s for RNA oligos capable of forming 7–10 base pairs. For both parameters, RNAs capable of forming more base pairs also tended to have longer dwell times. With the exception of τS for RNA-10, τS and τL parameters only varied within a range of two- to fourfold. This was surprising since a previous single-molecule fluorescence study of RNA oligo hybridization reported a 10-fold decrease in off-rate due to presence of one additional base pair  and only one (a cryptic 5' SS in RPL18A) may contain more than seven contiguous base pairs . Most 5'We observed long-lived complexes for RNA-7a, which has a 7 bp predicted duplex length, and only short-lived complexes for RNA-6a and -6b, which have only 6 bp predicted duplex lengths . Whethero –4.4 to –2.7 kcal/mol). Yet, the amplitude of the long-lived parameter for RNA-5+1 is ~×14 greater than that for RNA-2+7 (A+1). These results show that long-lived complex formation between U1 and the RNA oligos is intolerant of mismatches at the +1 position. Failure of U1 to accumulate on RNAs with mismatches at the +1 site is not due to lack of association. Rather, recognition of a mismatch at +1 involves a discrimination step occurring after association and mismatched RNAs are rapidly released.We next tested if a single mismatch could eliminate long-lived binding even if all other positions within the 5' SS oligo could potentially pair with SSRS. We incorporated single mismatches at the +1 position of RNA-10 . This reBy studying single molecules of yeast U1 snRNPs interacting with a diverse range of RNA oligos, our experiments have revealed the dynamics associated with the earliest step of 5' SS recognition. U1 can form both short- and long-lived, sequence-dependent complexes with RNAs  and 3. Rtrans-acting factors or confounding effects due to RNA secondary structures. We have not yet identified what specific event or conformational change is associated with long-lived complex formation; however, comparison of cryo-EM densities for free yeast U1 and the U1/U2-containing yeast pre-spliceosome (in which U1 is bound to a 5' SS) reveals that Yhc1 and Luc7 are more ordered in the latter  of the 5' SS. This particular position of the 5' SS is important since it also pairs with the ‘ACAGA’ sequence of the U6 snRNA (base-pairing position underlined) to promote splicing catalysis , Hfq  and Argonaute  RNPs are involved in very different biological processes than RNA splicing, single-molecule studies of each of these RNPs reveal striking similarities with yeast U1 . All theS. cerevisiae strain BJ2168 and selection for growth in the absence of uracil (TAP) or in the presence of hygromycin (fSNAP)  .A total of 10 L U1-SNAP-TAP yeast cultures were grown in 1 L batches of rich media (YPD) in a shaking incubator  to late log stage. The cells were pelleted, washed, and resuspended in 3.5 mL (per 1 L culture) Lysis Buffer . The resuspended cells were flash frozen in a drop-wise fashion in liquid nitrogen and stored at –80°C until lysed. The frozen pellets were lysed in batches using a Retsch Mixer Mill MM 400 . The frozen lysate powder was stored at –80°C.2, 5 mM imidazole, 0.1% v/v NP40, no reducing agent) to incubate at 4°C with rotation for 2 hr.The total cell lysate from 10 L was thawed at 4°C. Lysis Buffer (10 mL) was used to dissolve one EDTA-free Protease Inhibitor Tablet (Pierce), and this solution was combined with the cell lysate. Insoluble material was removed by centrifugation . The supernatant was then cleared in an ultracentrifuge at 36,000 rpm, 4°C, for 75 min. The resulting middle layer was carefully removed and added to 300 μL GE Healthcare IgG Sepharose 6 Fast Flow resin that had been equilibrated with IgG150 Buffer  containing one dissolved Protease Inhibitor Tablet (Pierce) per 50 mL buffer. The flow was stopped by capping the columns with 1.0 mL of resin plus solution remaining. TEV protease (40 U) and the SNAP-tag dye (2 μM) were then added. The columns were sealed with caps, and the resin was incubated for 45 min at room temperature in the dark with mixing. Subsequent steps were carried out with as little exposure to light as possible.2, 5 mM imidazole, 2 mM CaCl2, 0.1% v/v NP40, no reducing agent, 4°C). The IgG resin was washed with an additional 200–300 μL IgG150 Buffer (plus 1 mM DTT) to ensure all sample was transferred to the calmodulin resin. To this slurry, three equivalent volumes (with respect to the volume of the TEV eluate) of Calmodulin Binding Buffer containing 10 mM β-mercaptoethanol were added. The slurry was then incubated at 4°C with rotation for 60 min.The labeled, TEV-cleaved eluent was added directly to calmodulin affinity resin (400 µL) that had been equilibrated with Calmodulin Binding Buffer . Immediately afterward, labeled U1 snRNP was eluted in 4×150 µL fractions using incubation times of 0, 2.5, 5, and 10 min with the elution buffer.The resin slurry was divided between two 0.8×4 cm Poly-Prep Chromatography Columns. After the flow through was eluted, each column was washed with 3×5 mL Calmodulin Binding Buffer containing 10 mM β-mercaptoethanol. Before elution, the columns were capped at the bottom to control the timing of subsequent steps. Buffer exchange was performed by washing the resin with 100 μL (approximate resin bed volume) Calmodulin Elution Buffer  overnight at 4°C. In the morning, the cassette was moved to fresh Dialysis Buffer (1 L) for 4 hr. The dialyzed sample was concentrated in an Amicon Ultra 100 kDa MWCO centrifugal filter unit . The sample was mixed by pipetting up and down between spins and by addition of more dialyzed sample. The final sample volume (~100 μL) was divided into 5 μL aliquots, flash frozen, and stored at –80°C.Fractions were then analyzed by SDS-PAGE, and fractions E1-E3 typically had the highest concentrations of U1. These fractions were pooled and dialyzed in a 10 kDa MWCO Slide-A-Lyzer dialysis cassette in 1 L Dialysis Buffer  connected to an electrospray ionization (ESI) Orbitrap mass spectrometer . HPLC separation employed a 100×365 mm fused silica capillary micro-column packed with 20 cm of 1.7-µm-diameter, 130 Å pore size, C18 beads (Waters BEH), with an emitter tip pulled to approximately 1 µm using a laser puller (Sutter Instruments). Peptides were loaded on-column at a flow rate of 400 nL/min for 30 min and then eluted over 120 min at a flow rate of 300 nL/min with a gradient of 2–30% acetonitrile in 0.1% formic acid. Full-mass profile scans were performed in the orbitrap between 300 and 1500 m/z at a resolution of 60,000, followed by 10 MS/MS HCD scans of the 10 highest intensity parent ions at 42% relative collision energy and 7500 resolution, with a mass range starting at 100 m/z. Dynamic exclusion was enabled with a repeat count of two over the duration of 30 s and an exclusion window of 120 s.S. cerevisiae as previously described  so that RnaseH would digest the 5ʹ end of endogenous U1 snRNA in the yWCE (Splicing extracts (yWCE) were prepared from a BJ2168-derived strain of escribed . Aliquotrotocols . Splicinthe yWCE . After 3the yWCE . The pro32P]-labeled primer complementary to nucleotides 27–44 of U1 snRNA (5ʹ- TCAGTAGGACTTCTTGAT) in Annealing Buffer  and the reaction was incubated at 90°C for 3 min, snap cooled on ice for 3 min, then pre-heated to 45°C for 5 min. A reverse transcriptase (×2 RT) master mix was prepared containing 1 U/μL AMV Reverse Transcriptase in 25 mM Tris pH 8.0, 8 μM DTT, and 0.4 mM dNTPs.RNA from purified U1 snRNP or 40 μL U1-SNAP-TAP yWCE was isolated by phenol-chloroform extraction and ethanol precipitation. All of the RNA isolated from labeled, purified U1 snRNP was used for reverse transcription while only 10% of the isolated RNA from yWCE was necessary. The isolated RNA was combined with 1 pmol  Events in each time series were detected using the DISC algorithm  and visually inspected to ensure only specific binding events were included in the analysis.”We do note however that in these data sets, we are able to observe the short-lived (~40s) binding events with RNA-10. We have revisited our data collected at 0.2 Hz (1 frame every 5 seconds) and indeed find evidence of a short- and long-lived state. As such, we have updated Figure 3, the corresponding supplemental tables, and the discussion of data with RNA-10 accordingly.7) The authors have chosen to extrapolate rates via exponential fitting to dwell time distributions. This is a reductive approach that ignores the relationship between consecutive events. It is strongly recommended that the authors consider using a hidden Markov modeling (HMM) approach instead. HMMs have long become the gold standard in single molecule biophysics. Even better, a Bayesian approach could help analyze entire datasets at the same time. In this reviewer's opinion, the ebFRET software package from the Gonzalez lab at Columbia University could, for example, work well here.We disagree with this statement. While HMMs are powerful, we do not believe they are the “gold standard” for all single molecule measurements in biophysics. Alternative approaches including change-point detection, auto/cross correlation analysis, image recognition, and others are commonly used in biophysics, particularity for “model-free” analysis. For certain cases, ebFRET is indeed a powerful tool; however, this software was designed specifically for intramolecular smFRET data, and it is unclear which priors are appropriate for intermolecular CoSMoS data without further investigations that are beyond the scope of this work.unbound and bound events is unlikely to change between our method and a standard HMM given the high signal to background of our data . An example of this is clearly provided in Figure 3 of Greenfield et al., PLOS One, 2012 where thresholding and HMMs provided similar results at high signal to noise ratios in simulated smFRET data. In fact, our association rates reported in Figure 2-Source Data 1 are free of contamination from photobleaching (a feature often not corrected for in HMM modeling) as we only analyzed the time to the first association event. Therefore, our analysis in the main text is appropriate.Herein, events were discretized via thresholding and further inspected by examining the raw camera data at each AOI to discern specific and non-specific binding, a well described and robust approach for CoSMoS analysis  The exact classification of For our new, faster framerate data at 0.2 Hz, the signal to noise ratio is lower, as this set up uses sCMOS detectors. Therefore, these data were analyzed by the DISC algorithm , which has exhibited higher accuracy for intermolecular CoSMoS data than vbFRET (the predecessor of ebFRET). DISC is like the segmental k-means algorithm (SKM) and uses unsupervised learning to approximate an HMM. The final output of DISC (and SKM) is the Viterbi path of state transitions . Importantly, our new analysis of RNA-10 and RNA-4+2 provided dwell time distributions with similar parameters from MLE fitting, suggesting both analysis methods are providing consistent results (see reviewer Comment #6).To the first point of the reviewer, we agree more information can indeed be obtained by considering the time between successive events rather than dwell time analysis alone. We have now performed HMM analysis for RNA-4+2 which represents a very common 5’SS observed in vivo to compare three specific models (see response to Comment #5). For our survey of >20 other RNAs, we have chosen to only compare maximum likelihood estimates (MLE) of dwell time distributions as we are not confident a parsimonious model can be selected for each dataset. Thus, to avoid over interpreting our data, our manuscript focuses on a discussion of parameters from MLE fitting, a long standing a reliable approach in the single-molecule community.8) The authors should say more about the particular requirement for basepairing at position 6, especially in the context of the experiments in Figure 5. This is particularly striking as this position is not well conserved in natural 5'ss, at least compared to position 5.Position +6 (G/GUAUGU) is frequently conserved as a “U” in both yeast  and in humans . In fact, of 245 “GUAUG” introns in yeast, 227 (93%) of them also contain a U at +6 (GUAUGU). Presumably, this site is conserved since it permits pairing with the U6 snRNA “ACAGA” sequence during the catalytic steps in splicing. We have expanded on this idea in the discussion and this text is included on page 21.“An additional consequence of this length requirement and the duplexes described in Figure 7C is that they also favor base pairing interactions between the 5' end of the U1 SSRS and the 3' end of the splice site. For example, each of the RNAs in our study capable of forming long-lived interactions also could pair at the +6 position (G/GUAUGU) of the 5' SS. This particular position of the 5' SS is important since it also pairs with the “ACAGA” sequence of the U6 snRNA (base-pairing position underlined) to promote splicing catalysis  As mentioned above for recognition of G+1, the kinetic properties of U1 are, in part, optimized to facilitate interactions between the 5' SS and the splicing machinery that are important for catalysis even after U1 is released.”


Four types of A‐related RNA modification regulators interact with each other and even the crosstalk between the regulators could characterize the tumor immune microenvironment infiltration patterns, chemosensitivity, and cancer prognosis in patients with pan‐cancer. Dear Editor,RNA modifications, mediated by “writers,” “readers,” and “erasers”, actively participate in tumorigenesis and cancer development, as well as immune dysregulation.To address this issue, we curated a catalog of 6, 20, 12, and 3 genes that function as m1A, m6A, APA, and A‐I regulators, respectively Figure  were colBased on weighted gene coexpression network analysis, we identified the hub genes of 33 cancer types from 41 A‐related RNA modification regulators Figure . MoreoveTo evaluate the prognostic value of the crosstalk among four types of A‐related RNA modification regulators in various cancers, a total of 18 hub regulators  were first excavated for constructing the A‐related RNA modification subtypes Table . Based oIn summary, this study is the first to comprehensively analyze the role of the crosstalk among the four types of A‐related RNA modification regulators across 33 cancers. We demonstrated that these regulators could interact with each other and even the crosstalk between the regulators could characterize the tumor immune microenvironment infiltration patterns, chemosensitivity, and cancer prognosis in patients with pan‐cancer. This study provides new insights into epigenetic tumor regulation and effective therapeutic target development.The authors have no conflict of interest.The National Natural Science Foundation of China , the Science and Technology Foundation of Guizhou Province , and the Science and Technology foundation of Guizhou Health Committee (gzwjkj2019‐1‐037).Appendix S1Click here for additional data file.


N6-methyladenosine (m6A) is the most abundant internal modification on eukaryotic mRNAs. There is increasing evidence that m6A plays a key role in tumor progression, so it is important to analyze m6A modifications within the transcriptome-wide in lung adenocarcinoma (LUAD). Three pairs of LUAD samples and tumor-adjacent normal tissues were obtained from the South University of Science and Technology Hospital. And then methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RNA sequencing (RNA-seq) were used to identify differential m6A modifications between tumor and tumor-adjacent normal tissues. We identified 4041 aberrant m6A peaks, of which 1192 m6A peaks were upregulated and 2849 m6A peaks downregulated. It was found that genes with the dysregulated m6A peaks were enriched in the pathways in cancer, Rap1 signaling pathway, and insulin resistance. Additionally, 612 genes with abnormal regulation of m6A peaks and RNA expression were identified by combining MeRIP-seq and RNA-seq data. Through KEGG analysis, the 612 genes were enriched in cancer-related signaling pathways, such as the cGMP-PKG signaling pathway, and the Rap1 signaling pathway. What’s more, GSEA enrichment analysis showed these genes were enriched in cell cycle phase transition, cell division, cellular response to DNA damage stimulus, and chromosome organization. To further explore the relationship between differential m6A modified genes and clinical parameters of LUAD patients, we searched The Cancer Genome Atlas (TCGA) and identified 2 genes (FCRL5 and GPRIN1) that were associated with the prognosis and diagnosis of LUAD patients. Furthermore, we found a positive correlation between GPRIN1 and m6A reader YTHDF1 in the GEPIA2 database. It was verified that YTHDF1 binds to GPRIN1 mRNA and regulates its expression. Our study results suggest that m6A modification plays important role in the progression and prognosis of LUAD and maybe a potential new therapeutic target for LUAD patients in the future. RNA methylation mostly regulates gene expression at the posttranscriptional level, which is considered to be another layer of epigenetic regulation similar to DNA methylation and histone modification. Recently, a variety of molecular modifications of RNA  have been discovered . The wayvia promoting the attenuation of AXIN1 mRNA to activate the Wnt/β-catenin signaling pathway, which may be a potential therapeutic target for LUAD. In addition, miR-600 induces degradation of METTL3 mRNA by targeting the 3’UTR of METTL3 mRNA and leads to inactivation of the PI3K/AKT pathway related to cell growth and survival  following the instructions of the manufacturer. Total RNA was chemically broken into 200nt fragments. The product was added to anti-N6-Methyladenosine (m6A) antibody , protein A-magnetic beads , protein G-magnetic beads , which was then mixed and incubated overnight. RNA was extracted by phenol-chloroform lysate to afford the purified product. A portion of the initial fragmented RNA was used as the input RNA-seq library for MeRIP-seq. Ribosomal RNA was removed from the products. The first-strand cDNA was synthesized by the SMART principle, and enriched library fragments were amplified by PCR. Ultrafine RNA methylation m6A detection library fragments were obtained by DNA purification of magnetic bead library fragments. Bioptic Qsep100 Analyzer was used to perform a quality inspection on the library and detect whether the size distribution of the library is consistent with the theoretical size. NovaSeq high-throughput sequencing platform and PE150 sequencing mode were used.Lung adenocarcinoma cell line A549 cells were cultivated in 1640 medium containing 10% fetal bovine serum (FBS)  and 100 U/mL penicillin-streptomycin mixture . The cells were maintained at 37°C in a humidified atmosphere of 95% air and 5% CO2. YTHDF1 siRNA was designed and constructed by Genechem Bio . In transfection, siRNAs were transfected by LipoRNAiMAX Transfection Reagent (Invitrogen) according to product instructions. Briefly, siRNAs were diluted in the 100 μL Opti-MEM (Gibco) at 10 nmol/L and mixed with 2.5 μL Lipofectamine RNAi Max. After incubation at room temperature for 18 min, the mixture was added to the cell culture medium, and the cells were collected after 48 h. The sequences of the targets were as follows: YTHDF1-Homo-370 sense 5’- GGAUACAGUUCAUGACAAUTT-3’, antisense 5’-AUUGUCAUGAACUGUAUCCTT-3’; YTHDF1-Homo-1076 sense 5’-CCUCCACCCAUAAAGCAUATT-3’, antisense UAUGCUUUAUGGGUGGAGGTT-3’; YTHDF1-Homo-1503 sense 5’-GCUCCAUUAAGUACUCCAUTT-3’, antisense 5’-AUGGAGUACUUAAUGGAGCTT-3’.Total RNA was extracted from A549 cells using Trizol  according to the manufacturer’s instructions. For RT-qPCR, RNA was reverse transcribed to cDNA by using a reverse transcription kit . The levels of RNA transcripts were analyzed by the Jena qTOWER3 RT-qPCR system . The sequences of the primers were as follows: GAPDH forward primer, 5’-CTCCTCCTGTTCGACAGTCAGC-3’, reverse primer 5’-CCCAATACGACCAAATCCGTT-3’; YTHDF1 forward primer, 5’-GCACACAACCTCCATCTTCG-3’, reverse primer 5’-AACTGGTTCGCCCTCATTGT-3’; GPRIN1 forward primer 5’-AAAGCAGGCCGATTCCACTTC-3’, reverse primer 5’-TCCTTCCTCGGTGACACTGTA-3’.The collected cell precipitates were coprecipitated by EZ-Magna RIP™ RNA-Binding Protein Immunoprecipitation Kit (Millipore 17-701) following the manufacturer’s procedure. Cells were lysed in a moderate volume RIP lysis buffer on ice for 5 min, and then the lysates were moved to -80°C overnight. Lysates were centrifuged at 4°C, and 12,000 rpm for 30 min to obtain the supernatant. 5μg YTHDF1 antibody or rabbit IgG was conjugated to protein A/G magnetic beads on a shaker for 30 min at room temperature. Magnetic beads containing antibodies were added to the supernatant, followed by rotating overnight at 4°C. TRIzol LS reagent (Invitrogen) was used to extract the RNA according to the manufacturer’s instructions. RT-qPCR follows the above method.https://david.ncifc rf.gov/) was used in Gene Oncology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. 594 LUAD patients’ RNA-seq data were downloaded from The Cancer Genome Atlas (TCGA) database . The expression levels of genes were analyzed using the R package DESeq2 [version 1.26.0]. Then, 526 LUAD patients including primary tumor, lymph node metastasis, distant metastasis, and clinical stage were selected for the further study. A univariate Cox regression model was adopted to calculate the hazard ratios (HRs) of the genes’ overall survival. Kaplan-Meier analysis was used to construct survival curves, and the Cox regression model was utilized to estimate the significance of the differences. ROC curves were constructed to estimate the accuracy of genes in predicting outcomes. YTHDF1-RIP-seq data was downloaded from the NCBI Gene Expression Omnibus (GEO) database under the accession number GSE136433.The Database for Annotation, Visualization and Integrated Discovery (DAVID) database , cellular components (CC), and molecular functions (MF) were taken into consideration. The transcriptome profiles of tumor tissues versus normal tissues from three LUAD patients were detected using RNA-seq (MeRIP-seq input library). Compared to normal tissues, tumor tissues had 1726 up-regulated genes and 2011 down-regulated genes   were identified as most correlated with the development of LUAD using TCGA databases. Overexpression of GPRIN1 served as a factor for poor prognosis, while FCRL5 favors prognosis. Besides, high expression of GPRIN1 is highly involved in the lymph node metastasis, and FCRL5 with not only lymph node metastasis but also distant metastasis and the clinical stage of LUAD patients. Further analysis revealed that the region with a gain of m6A in LUAD is the same that gains enrichment of YTHDF1 in A549 cells. What’s more, YTHDF1 binds GPRIN1 mRNA by YTHDF1-RIP-qPCR assay, in which the fold enrichment of the YTHDF1-IP group was significantly higher than that of the IgG-IP group.However, our research still has some shortcomings. Firstly, LUAD is a kind of highly heterogeneous cancer, and the tissue samples of clinical patients vary greatly. Although the three pairs of clinical samples met the statistical requirements, they were too small a sample size to reflect the differential m6A modification and gene expression between LUAD and adjacent tissue in the LUAD population, and the number of cases still must be further increased. Secondly, although we have performed some experiments to verify that YTHDF1 regulates GPRIN1 expression, more experiments are needed to strengthen the credibility, which is also the direction of our future in-depth research.In summary, the different m6A methylome in LUAD relative to the corresponding normal controls was analyzed, which demonstrated a strong association between m6A modifcation and LUAD progression. 2 genes (FCRL5 and GPRIN1) with differential methylated m6A peaks and synchronously differential expression were associated with the prognosis and diagnosis of LUAD patients. Further one step research, GPRIN1 was found to act as an downstream target of YTHDF1. Targeting the YTHDF1-m6A-GPRIN1 axes may offer a promising therapeutic approach in curing LUAD.The data presented in the study are deposited in the GEO repository, accession number GSE198288.The studies involving human participants were reviewed and approved by the Ethics Committee of the South University of Science and Technology Hospital. The patients/participants provided their written informed consent to participate in this study.WM was a major contributor to all of the experimental work, data analysis, and manuscript writing. KW, YZ, and WL were involved in the experimental work. QY, QM, NW, and GZ were involved in the data analysis. YW acquired funding and assisted with the manuscript development. The final manuscript was reviewed and approved by all of the authors.This work was supported by the Stability Support Plan for Higher Education Institutions in Shenzhen (20200809124551001).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Nucleocapsid protein (N-protein) is required for multiple steps in betacoronaviruses replication. SARS-CoV-2-N-protein condenses with specific viral RNAs at particular temperatures making it a powerful model for deciphering RNA sequence specificity in condensates. We identify two separate and distinct double-stranded, RNA motifs (dsRNA stickers) that promote N-protein condensation. These dsRNA stickers are separately recognized by N-protein's two RNA binding domains (RBDs). RBD1 prefers structured RNA with sequences like the transcription-regulatory sequence (TRS). RBD2 prefers long stretches of dsRNA, independent of sequence. Thus, the two N-protein RBDs interact with distinct dsRNA stickers, and these interactions impart specific droplet physical properties that could support varied viral functions. Specifically, we find that addition of dsRNA lowers the condensation temperature dependent on RBD2 interactions and tunes translational repression. In contrast RBD1 sites are sequences critical for sub-genomic (sg) RNA generation and promote gRNA compression. The density of RBD1 binding motifs in proximity to TRS-L/B sequences is associated with levels of sub-genomic RNA generation. The switch to packaging is likely mediated by RBD1 interactions which generate particles that recapitulate the packaging unit of the virion. Thus, SARS-CoV-2 can achieve biochemical complexity, performing multiple functions in the same cytoplasm, with minimal protein components based on utilizing multiple distinct RNA motifs that control N-protein interactions. Phase separation has long been described in polymer physics but only relatively recently is an appreciated mode of macromolecular self-assembly in cells that results in the formation of micron-scale droplets contributing to numerous cellular functions . While mViruses present an opportunity to dissect interactions between proteins and nucleic acids that lead to liquid-like condensates because of their limited proteome that must engage with specific viral nucleic acids . Indeed, proteins and nucleic acids from many different viruses have now been shown to undergo condensation in physiological conditions and form droplets in cells . ImportaAlthough, the global COVID-19 pandemic motivated many studies of N-protein condensates, the specific role(s) of such assemblies in the viral replication cycle is still an open problem. The nucleocapsid protein (N-protein) is required for multiple viral functions . N-proteN-protein phase separation shows remarkable specificity for RNA sequence but the mechanism for N-protein's recognition of RNA is unknown. We previously showed that the first 1000 nucleotides of the SARS-CoV-2 genome (termed 5′end RNA) drive N-protein droplet assembly. In contrast, another RNA sequence of identical length surrounding the frameshifting element (FS) promoted solubilization of N-protein . A clue We show that the two RNA-binding domains in N-protein interact with distinct RNA-sequence and structure elements. This indicates N-protein has at least two distinct types of protein-RNA interaction ‘stickers’ that could provide multivalency for phase separation. RBD1 recognizes transcription-regulating sequence (TRS) and similar sequences in an RNA structure dependent manner. RBD2 specifically interacts with dsRNA, independent of sequence. The patterning and quality of these stickers can lead to emergent material properties of condensates. N-protein ‘RNA stickers’ can specify condensation temperature, RNA translation efficiency, sgmRNA generation, and genome condensation. Our work provides the first evidence of dsRNA/RBD interactions in specifying temperature-sensitive behavior in any phase separating system. Importantly, we identify how combinations of the two dsRNA stickers can pattern protein-RNA interactions to regulate condensation with important implications for betacoronavirus replication.Escherichia coli (New England Biolabs). All steps of the purification after growth of bacteria were performed at 4°C. Cells were lysed in lysis buffer  and via sonication. The lysate was then clarified via centrifugation  and the supernatant was incubated and passed over a HisPurTM Cobalt Resin (ThermoFisher Scientific 89965) in gravity columns. The resin was then washed with 4 × 10 CV wash buffer  and protein was eluted with 4 CV elution buffer . The eluate was then dialyzed into fresh storage buffer  and aliquots of protein were flash frozen and stored at –80°C. Protein was checked for purity by running an SDS-PAGE gel followed by Coomassie staining as well as checking the level of RNA contamination via Nanodrop and through running of a native agarose RNA gel. All experiments were performed with His-tagged N-protein. Whi3 was purified according to our established protocols  were expressed in BL21 rotocols ,39.N-protein was dyed by adding (3:1) Atto 488 NHS ester (Millipore Sigma 41698) to purified protein and incubating mix at 4°C for 1 h with rocking. Unbound dye was removed by overnight dialysis into protein storage buffer. For phase separation assays percent of dyed protein was adjusted to 10% of total by dilution with undyed protein.http://rna.tbi.univie.ac.at). Sequences were generated via site directed mutagenesis using overlapping oligos (IDT). DNA sequences of tested RNA fragments are in the supplement.Template predicted structure was designed using Vienna fold . Orf1ab templates were synthesized (IDT) and cloned into pJet (ThermoFisher Scientific K1231) using blunt end cloning. Directionality and sequence were confirmed using Sanger sequencing (GENEWIZ). Plasmid were linearized using PCR (iProof Bio-Rad 1725310). 5 μl of PCR product was loaded onto an agarose gel to determine size and purity. If the PCR product was pure then the sample was PCR purified (QIAGEN 28106) if the band was impure, it was gel purified (QIAGEN 28706) . 100 ng of gel or PCR purified DNA was used as a template for in vitro transcription (NEB E2040S) carried out according to the manufacturer's instructions with the addition of 0.1 μl of Cy3 (Sigma PA53026) or Cy5 (Sigma PA55026) labeled UTP to each reaction. Following incubation at 37°C for 18 h, in vitro transcription reactions were treated with DNAseI (NEB M0303L) according to the manufacturer's instructions. Following DNAse treatment, reactions were purified with 2.5 M LiCl precipitation. Purified RNA amounts were quantified using nanodrop and verified for purity and size using a denaturing agarose gel and Riboruler RNA ladder (Thermo Scientific SM183). Of note in an earlier version of this manuscript RNA molarity was calculated with a molecular weight of 499.5 (nucleotide triphosphate) rather than 321.5 (nucleotide monophosphate) meaning original reported values were inaccurate by a factor of ∼1.6.RNA production was carried out according to our established protocols  was mixed with cy3 or cy5 labeled desired RNA and DEPC treated H20  and 5 μl protein in storage buffer was added at desired concentration. The mix was incubated in 384-well plates (Cellvis P384-1.5H-N) for 1–20 h at 37°C unless indicated otherwise. Droplets formed after short incubations of 20 min or less, however, they were initially smaller and matured into larger droplets during the overnight incubation step. Time to maturation varied based on the ratio of RNA to protein, concentration of RNA and protein and RNA sequence. Multiple conditions per mutant were tested with the most optimal conditions for differences selected for comparison. Imaging of droplets was done on a spinning disc confocal microscope (Nikon CSU-W1) with VC Plan Apo 100×/1.49 NA oil (Cargille Lab 16241) immersion objective and an sCMOS 85% QE 95B camera (Photometrics). Data shown are representative of three or more independent replicates, across two or more RNA preparations. Whenever possible multiple mutations were designed to disrupt the same class of feature in multiple sequence contexts.A280 was recorded. Error bars indicate the A280 measurement from the three technical replicates.  N = 3 technical replicates.The mix was incubated in 384-well plates (Cellvis P384-1.5H-N) at 25, 30 or 37°C. Following imaging. 2 μl of dilute phase solution (taken from the top of the well) was nanodropped and absorbance HEK293T cells were originally obtained from ATCC. All cell lines were maintained in DMEM (Corning 10-013-CV) supplemented with 10% fetal bovine serum (Gibco). No antibiotics were used.N = 3 biological replicates.Twenty four hours prior to transfection, confluent cells were split 1:5. Two hours prior to transfection, 500 μl of fresh media was added to 24-well plates. 500 ng of plasmid DNA for each Nucleocapsid GFP Spark  and the MSCV blast 1–1000 fragments was co-transfected using FUGENE HD. Transfections were then incubated for 24–48 h prior to imaging. N = 3 biological replicates.Cells were imaged using a 40× air objective on a spinning disk confocal microscope . Images were taken with a ANDOR camera. Representative cells are taken from Cells with puncta were cropped using FIJI. Experimenters were then blinded to conditions, and puncta were counted for each cell. Whole cell N:GFP signal was quantified using ImageTank .YRRRY motifs were counted throughout the NC_045512.2 reference genome (with overlapping motifs counted separately) and the motif counts in each 1000 bp window were plotted as a histogram. The density of double-stranded RNA was plotted using a kernel density estimation plot with smoothing parameter set to 100.2, 0.1 mg/ml BSA, 2.5 μg yeast TRNA, 10 U RNAse inhibitor and loading dye. Samples were then loaded onto an 8% TBE gel and run at 100 V for 1 h at 4°C. Gels were then stained with SYBRgold (S11494) and imaged. Unbound RNA was quantified using ImageJ. N = 3 technical replicates.65 ng/μl of the indicated RNA sequence was incubated with 0, 0.75, 1.5 or 2.2 μM Y109A mutant N-protein at 25 or 37°C for 1 h in the following buffer 10 mM HEPES pH 7.5, 50 μM EDTA, 10% glycerol, 1 mM DTT, 5 mM MgClN = 1 technical replicate.The LCST behaviors of different phase separation systems were investigated on a Cary 300 temperature-dependent ultraviolet-visible spectroscopy equipped with a multicell thermoelectric temperature controller. The samples (4 μM of N-protein with 24 nM of RNAs) were mixed and prepared in a droplet buffer  at 4°C. Before the initiation of the heating process of the turbidity test, for the experiments shown in Figure http://www.unafold.org/results2/twostate-fold/220509/163346/ Parameters for RNA at 37°C [Na+] = .15 M, [Mg++] = 0 M.Melting temperatures were calculated using DINAMelt webserver. The following SARS-CoV-2 amino acid sequence was input into PhyreTKKSAAEASKKPRQKRTATKAYNVTQAFGRRGPEQTQGNFGDQELIRQGTDYKHWPQIAQFAPSASAFFGMSRIGMEVTPSGTWLTYTGAIKLDDKDPNFKDQVILLNKHIDAYKTFP.This sequence best matched with the crystal structure of the RBD2-dimerization domain of SARS-CoV-1 . The resN-protein amino acid sequences from MHV, OC43, MERS-CoV, SARS-CoV-1, and SARS-CoV-2 were taken from Uniprot and aligned using Clustal Omega.Patient mutations from GSAID were downloaded on 7/14/2021  for the following sequence.TKKSAAEASKKPRQKRTATKAYNVTQAFGRRGPEQTQGNFGDQELIRQGTDYKHWPQIAQFAPSASAFFGMSRIGMEVTPSGTWLTYTGAIKLDDKDPNFKDQVILLNKHIDAYKTFP.Fraction of samples with mutations for each amino acid was calculated by combining detected substitutions or indels and dividing by the total number of sequences. For highly mutated amino acids the most common mutation(s) were noted.Mass photometry was performed according to established protocols . 10 μl oet al. (in vitro translation product was then mixed with 25 μl of nano luciferase assay reagents (Promega N205A). Light production was measured on a luminometer. Data depicted represents N = 3 replicates. Of note, similar translational repression was observed when we incubated RNA under droplet permissive conditions in plates  however this was much less reproducible likely due to the difference in RNA partitioning in the well post incubation with N-protein.Protocol was adapted from the method described by Tsang et al.  Briefly,For negative stained TEM images used to quantify the assemblies of RNP size distribution, 5 μl of 20 μM protein in 250 mM NaCl, 20mM phosphate buffer pH 7.5 and 5 μl of 80 nM RNA (FS RNA or 1000) in water were mixed in 15 μl of reaction buffer . The final protein and RNA concentrations in the solution were 4 μM and 16 nM, respectively. For control measurements, protein without RNA and RNA without protein solutions were prepared. All mixture solutions were incubated at room temperature for overnight to measure negative stained TEM images.Negatively stained samples were prepared on carbon film-coated grids supported by lacey carbon on 300 copper mesh (Electron microscopy Sciences). Grids were glow-discharged immediately before use. 8 μl aliquot of protein and RNA mixture solution was applied to the grid. After 2 min absorption to the carbon film, the solution was blotted and washed with 8 μl of water for 10 s, blotted, stained with 8 μl of 2% uranyl acetate for 10 s, blotted, and dried. Negative stained TEM images were obtained on a FEI Morgagni microscope.http://imagej.nih.gov/ij). Since the shape of the small RNP is not a sphere, two major and minor diameters of the elliptical shape of the RNP were measured, and the averaged values from two diameters were reported. Gaussian fitting of averaged diameter histogram was performed with Igor Pro 8.0.4.2 (WaveMetrics).Images were analyzed with ImageJ software  and incubated at 37°C for 10 min, heated to 95°C for 5 min, cooled on ice for 2 min, and warmed to 37°C for 2 min. Proteinase K was then added to 0.5 mg/ml and incubated for 1 h at 37°C, followed by 1 h at 55°C. RNA was purified with 1.8′ Mag-Bind TotalPure NGS SPRI beads (Omega Bio-tek), purified again , and eluted with 14 μl of nuclease-free water.N-Protein and RNA mixtures were prepared as described in the ‘Phase Separation Assay’ section above and incubated for 1.5 h at 37°C. N-protein or N-protein Y109A–FS RNA mixtures were prepared in 80 nM RNA, 1μM protein  RNA-only samples were also prepared as a control. After confirmation of phase separation by imaging mixtures were immediately subjected to RNP-MaP treatment as described , with moet al., 2019). Briefly, 7 μl of purified modified RNA was mixed with 200 ng of random 9-mer primers and 20 nmol of dNTPs and incubated at 65°C for 10 min followed by 4°C for 2 min. 9 μl 2.2 2′-MaP buffer  was added and the combined solution was incubated at 23°C for 2 min. 1 μl Superscript II Reverse Transcriptase  was added and the reverse transcription (RT) reaction was performed according to the following temperature program: 25°C for 10 min, 42°C for 90 min, 10′ , 72°C for 10 min. RT cDNA products were then purified .After SHAPE and RNP-MaP RNA modification and purification, MaP cDNA synthesis was performed using a revised protocol as described (Mustoe Double-stranded DNA (dsDNA) libraries for sequencing were prepared using the randomer Nextera workflow . BrieflyShapeMapper 2 software  sample. Nucleotides whose reactivities exceed reactivity thresholds are defined as ‘RNP-MaP sites’. RNP-MaP site densities were calculated over centered sliding 15-nt windows to identify RNA regions bound by N-protein. An RNP-MaP site density threshold of five sites per 15-nt window was used to identify ‘N-protein binding sites’ with boundaries defined by the RNP-MaP site nucleotides.A custom RNP-MaP analysis script  was usedN = 10 acquisitions were taken, and the results presented represent the mean Rh of the sample.Dynamic light scattering (DLS) measurements were performed at 25°C using a Wyatt DynaPro temperature-controlled Plate Reader . Samples for the DLS system were prepared in the droplet buffer and filtered through 0.02 mm Whatman Anotop sterile syringe filters  into a 96-well plate . Samples were incubated for 20 min at 25°C before testing. YYAAAY motifs were counted throughout the NC_045512.2 reference genome (with overlapping motifs counted separately) and the motif counts in each 1000 bp window were plotted as a histogram. The density of double-stranded RNA was plotted using a kernel density estimation plot with smoothing parameter set to 100. Viral genome RNA structure data was taken from .We first sought to determine which RNA features promote N-protein condensation using an in vitro phase separation assay which we perform at physiological salt, protein and RNA concentrations in the absence of any artificial crowding agents. Previously, we identified two regions within the first 1000 nucleotides (nt) or 5′end of SARS-CoV-2 which preferentially crosslinked with recombinant N-protein at protein concentrations below those required for phase separation . These principal sites are in single stranded sequences between two strongly structured Figure  and consin vitro? To this end, we tested 1–1000 nt, 1–267 nt (the 5′UTR), 1–500 nt and 500–1000 nt fragments at either 24, 40 or 80 nM RNA and 3.6 μM protein. All tested fragments could drive N-protein condensation however some fragments drove condensation more readily (1–500 or 1–1000)  Figure . Given t) Figure . We seleWe predicted if N-protein recognizes ssRNA, altering the ssRNA content between stem-loops (increasing or decreasing) should alter N-protein binding to principal sites and in turn condensation. Alternatively, if adjacent dsRNA mediates N-protein recognition of principal sites, we predict that changing the length of stem-loops will alter N-protein binding and condensation. Thus, we designed a series of mutations to independently disrupt single stranded and double-stranded RNA in or adjacent to the principal sites.We disrupted principal site 1 in 1–500 nt Figure , principWe next sought to address the role of the conserved structured RNA Figure  located To examine if dsRNA addition could be additive, we also tested individually +dsRNAb and +dsRNAc on a single principal site (either 1 or 2) in the context of 1–1000 nt. We observed that mutations which affect principal site 2 were better able to enhance condensation compared to those which effect principal site 1 . This isSo far, all tested mutations which enhanced structure also destroyed the single stranded principal site by converting it to dsRNA. Therefore, we next asked whether addition of 10 paired nucleotides (20 nt per stem-loop) of dsRNA at the base of the principal site flanking stem-loops would also promote condensation (+dsRNAd). This mutant would preserve the ssRNA of the principal site while creating additional structure. We observed that these extended stem-loops indeed also enhanced condensation relative to wildtype in all three sequence contexts Figure –F. A cavWe sought to disentangle the effects of length addition to the dsRNA constructs by expanding the single stranded region by inserting exogenous sequence (+ssRNAa) (27 nt coding for Hemagglutinin (HA)) in the center of the single stranded principal sites. Two different ssRNA sequences were independently inserted into principal site 2 . We obseNext, we sought to determine whether the sequence and/or structure of the stem–loops flanking the principal sites were important. Therefore, we unpaired the principal site flanking stem-loops by making mutations (–dsRNA) on the 5′ side. We observed that in all three contexts -dsRNA resulted in a reduction (1–500) or loss  of condensation relative to wildtype Figure –F. To reA280)  . In all A280) . Thus, dWe next determined which RNA binding domain of N-protein mediates the dsRNA-based condensation enhancement. N-protein has two distinct RNA-binding domains; located in the N-terminal domain (NTD) RBD1 is structured  and in tWe sought to test whether the condensation-promoting mutations in the RNA sequences were specific to N-protein or generalizable to any RNA-driven phase separating system. To this end, we tested all mutations in the 1–1000 context with recombinant Whi3 protein. Whi3 has previously been shown to undergo sequence-specific RNA-dependent phase separation ,39. We oNext, we sought to confirm our observations regarding RNA sequence/structure-mediated N-protein droplet formation in cells to see if the sequences behave similarly in the more complex and crowded cellular environment. To this end, we first needed to control for the reported translational repressive effects ,53 of noTo determine if dsRNA addition altered condensates in cells, we imaged cells co-transfected with specific RNAs and protein. We observed that at early timepoints (24 hours) +dsRNAa resulted in a significant increase in the number of puncta (4–5 per cell) per square micron in cells compared to Wildtype or Start Mutant control (2–3 per cell) . HoweverThe apparent acceleration in droplet formation time prompted us to examine differences in timing with the in vitro system for mutants in all 3 sequence contexts (shorter incubation time (2 hours) than shown in Figure We next asked if the addition of dsRNA alters the material properties of the resulting droplets. In our previous work, we found that different RNA sequences could lead to N-protein droplets with distinct physical properties. This feature may be relevant for generating immiscible droplet populations . In thesN-protein will condense in the absence of RNA at high temperatures, but addition of RNA lowers the temperature at which droplets emerge. Thus N-protein displays lower critical solution temperature (LCST) behavior and RNA tunes this property . NotablyTo determine how LCST behavior is encoded by RNA sequence and structure we first confirmed N-protein condensation temperature changed as a result of the co-condensing RNA (three different RNA sequences). To this end, we used a temperature-dependent ultraviolet-visible spectroscopy assay to map the saturation temperature, read out as turbidity to test if this assay could be used as a proxy for phase separation. We examined the following conditions: N-protein alone, N-protein + an RNA which does not drive condensation (Frameshifting region RNA (FS)(26), N-protein + 5′end RNA (1–1000nt) which drove condensation, or N-protein + Nucleocapsid RNA (drives condensation but is a longer sequence then 5′end).Consistent with previous results,  we obserWe wanted to identify the RNA and protein features which were responsible for conferring N-protein LCST independent of RNA length (Nucleocapsid RNA is longer then 5′end). To disentangle the effects of RNA length and RNA sequence we tested the 1–1000nt mutant RNAs  lowered the LCST of N-protein with all other mutations having comparable temperature to wildtype Figure  and C. WWe next evaluated contributions of RBD1 and/or RBD2 of N-protein in promoting temperature-dependent condensation. We hypothesized that RBD2 would likely be critical based on the ability of dsRNA to tune the LCST behavior. Additionally, N-protein interactions with the 5′UTR increase modestly at higher temperatures in RBD1 mutants (Y109A) as assessed via EMSA . This su2O control Figure A280 signal) were detected following the phase separation assay for all tested temperatures consistent for altered LCST behavior compared to wildtype  Figure  which wawildtype . Reducinwildtype . These dHow do N-protein RBD2 dsRNA interactions lower phase separation temperature? We were surprised to see that RBD2 deletion leads to overall enhanced formation of condensates rather than reduction, which is associated with loss of RBD1 activity . Based oCollectively, these data suggest that while RBD1 is required for 5′end RNA to phase separate, RBD2 is required for LCST behavior at physiologically-relevant temperature and salt, and RBD2 encodes LCST behavior through preferentially binding to dsRNA. These data reveal exquisite specificity of N-protein for different RNA sequences, raising the question what role this specificity plays in the biology of the virus.Given the +dsRNA mutants promoted droplet formation Figure  and the cis.To address if N-protein mediated protein translational regulation could be encoded by dsRNA, we first needed to design a translation reporter with differential dsRNA content but identical coding sequences (to control for translation). We reasoned that reporter RNAs with different untranslated regions, but identical coding sequences would fulfill our requirements. Thus, we sought to replicate our dsRNA/ssRNA addition experiments Figure  in the cA280 absorbance in the dilute phase suggestive of more protein recruitment to droplets  to nano luciferase. To determine if 5′UTR structure affects condensation for the fusions, we mixed 3.2 μM N-protein with 40, 24 or 8 nM RNA. At the highest tested RNA concentration, 40 nM, only the more structured mutant UTR resulted in condensation Figure . Similars Figure . Thus, cAshbya gossypii  impact translation? To this end, we performed an in vitro translation assay ±3.2 μM N-protein. We observed that addition of 3.2 μM N-protein almost completely blocked the translation of both tested RNAs Figure  Collectii Figure . NotablyWe hypothesize that N-protein binding to the genome (particularly the 5′UTR) may act to halt Orf1ab protein translation and promote packaging in later stages on infection Figure . In suppThe data thus far show that a primary driver of phase separation is dsRNA/RBD2 interactions but there are several lines of evidence that suggest additional interactions are mediated by RBD1. First, Y109A mutant N-protein does not undergo condensation with wildtype 5′end sequence. Second, the Y109A + dsRNA droplets have altered morphology suggesting some interaction between N-protein and RNA has been altered in the absence of RBD1 activity. Thus, we sought to identify what RNA sequence features are favored by RBD1.Given the transcriptional regulatory sequence (TRS in SL3) is the reported binding site of RBD1 in MHV , and theTo test if the presence of the TRS was required for phase separation, we deleted the entire TRS stem-loop (TRS-del) or added an additional TRS motifs to the 3′ end (Add TRS-3′) in the context of the 1–1000nt RNA sequence Figure . TRS-delWe next wondered if N-protein could also bind sequences which were similar to the TRS-loop. This is because N-protein can drive condensation with other genomic RNA sequences ,29,32,33The complete block of condensation by a single point mutant in the A68U RNA was striking and could be due to the primary sequence change or a larger-scale structural rearrangement. To assess a potential structure rearrangement, we performed SHAPE on a subset of the tested RNAs. We observed that compared to wildtype control, there was only a minor change associated with an A68U mutation in the probability to form the wild-type structure in the SL3/TRS  and all We next asked if the identity of the A nucleotide is critical for condensation. To test this possibility, we converted A’s in the TRS-Loop sequence to G’s as G is chemically more similar to A then U. We observed that regardless of whether a single A was replaced  or all 3 A’s of the loop were replaced  there was no obvious effect on phase separation Figure . These dIn examining the genome for YRRRY motifs we noticed that this would include the TRS leader (TRS-L) and TRS body (TRS-B) sequence utilized by SARS-CoV-2 (ACGAAC) Figure . TherefoWe were intrigued by the observation that 2 motifs were in such close proximity in the TRS-L Figure . Thus, wU test. To this end, we divided the genome into 46 nucleotide bins, removing any bins that overlapped with a TRS-B motif or 20 bp flanking the TRS-B. We observed that the TRS-B containing bins were significantly enriched (P < 1.3e–5) in YRRRY motifs comparing to the rest of the genome and similar enrichment was found in the SARS-CoV-1, MERS, and MHV genomes. For SARS-CoV-2, enrichment was preserved even when the TRS-B sequence was not included in the calculation (P < 0.014).We wondered if local enrichment of N-protein condensation promoting RNA features might instead explain how TRS-B’s are chosen for sgmRNA generation. To this end, we examined the highly structured  TRS-B foP < 2.5e–7 for TRS-B inclusive and P < 0.0011 for YRRRY without TRS-B sequence. Collectively, these results suggest that TRS-B contains densely packed high-quality N-protein binding sites which have both YRRRY (RBD1 motif) in secondary structure (RBD2 motif) compared to the rest of the genome.We also noticed that the YRRRY motifs tended to be 5′ to the TRS-B sequence. When limiting the enrichment calculation to just the 20 nucleotides proceeding the TRS-B or 26 nucleotide long genome bins the enrichment improved with We hypothesized that the number of N-protein binding motifs controls the relative abundance of sgmRNAs. Given Nucleocapsid (N) sgmRNA is more abundant than Spike (S) sgmRNA and TRS-B N contains more motifs than TRS-B S, we reasoned that N-protein may preferentially condense with TRS-N and this bias could control the ratio of sgmRNAs present thereby ensuring the proper stoichiometry for virion assembly Figure . In thisOperating under the assumption that preferential generation of N sub-genomic RNA may provide a selective advantage to the virus, we next asked if mutations present in highly infectious variants of concern, such as Delta or Omicron, may create additional YRRRY motifs near any TRS-B (particularly that of N). We observed that in position 20871nt, Delta and Omicron independently acquired 2 different mutations that create a fifth YRRRY motif in the TRS-B of N. Delta creates a deletion converting UAAAAU to UAAAU whereas Omicron has an A to U mutation converting UAAAAU to UUAAAU Figure . NeitherCollectively, these results suggest that preferential co-condensation between N-protein and the TRS-B of N early in infection under limiting N-protein conditions, may provide a selective advantage to SARS-CoV-2 allowing for earlier generation of N-protein to support multiple N-protein mediated functions required for viral replication. Mutations which create additional N-protein condensation promoting YRRRY motifs may lower the protein threshold required for condensation driving the recombination event to occur earlier in infection Figure .Given the key central role of N-protein in genome packaging, we next asked how what we have learned thus far about different types of N-protein/RNA interactions may impact packaging. Particularly, we were interested in the patterning of the YRRRY motif of RBD1 Figure  given ouBased on high-resolution cryo-EM tomography, the genome of SARS CoV-2 is arranged inside virions in a so-called ‘birds-nest’ arrangement with ‘eggs’ made of RNP complexes that are ∼14–20 nm ,66. We pTo address if N-protein mediated condensation is sufficient to compact RNA to RNP- size assemblies cell free, we first asked what size particles form from FS RNA (1000nt in length)? We examined FS RNA as this RNA does not drive macroscopic condensation at 4 μM N-protein and 16–24 nM RNA at room temperature Figure . To thisTo directly visualize cluster formation a second way, we used TEM. Indeed, after 20-min of incubation a relatively monodispersed population of symmetric, circular assemblies form that are centered on 42.9 nm diameter Figure . To asseWe wondered what caused the >2-fold size discrepancy between these RNP assemblies and the RNPs seen in virions? It is established that some droplets age into gel-like or glass-like states that can be associated with compaction , we therWe postulated that FS interactions with N-protein may be heavily dependent on RBD1 rather than RBD2. In support of this hypothesis, the FS RNA contains 24 YRRRY and FS does not engage with RBD2 in a way that alters condensation temperature Figure . To confIn this paper, we elucidate the RNA sequence and structure preferences of SARS-CoV-2 N-protein condensation to understand how these features lead to condensate properties relevant to viral processes in cells. We show that (i) RBD2 prefers dsRNA in a sequence-independent manner (ii) RBD1 prefers TRS-like sequences in an RNA structure-dependent manner Figure . We elucAddition of dsRNA, independent of sequence Figure , resulteWe postulate that the native, more structured stem-loops of the genome ends  are the most efficient binding sites for RBD2 (as evidenced by RBD1 independent crosslinking adjacent to these stem-loops ) and thiThe temperature at which dimerization occurs can be lowered via addition of dsRNA, potentially due to increasing the overall affinity of wildtype N-protein's two RBD2 domains or by offering additional sites of interaction (at a greater distance apart) on the same stem-loop. In support of the latter possibility, the two RNA binding domains are arranged diagonal to each other, and dsRNA binding may force the dimer apart Figure . Cryo-EMOur results also may explain why not all labs reporting N-protein condensation have observed LCST behavior in N-protein RNA interactions as these results show that LCST behavior is specifically encoded in N-protein dsRNA interaction. N-protein dsRNA interaction is unlikely to be observed in reconstitution experiments conducted with less physiological, unstructured RNA (poly U for example). RBD2 also seems to regulate the dimerization domain of N-protein . RBD2 diAs RBD2 may recognize RNA through a complex interaction involving charge, disorder, and transient protein structure. It is highly likely that post-translational modifications (PTMs) play a significant role not only in RBD-2 binding RNA but also dimerization and LCST behavior. This may begin to explain why those labs which purify N-protein from mammalian cells did not observe LCST while those which purify N-protein from bacterial sources did ,32,55. AAdditionally, our results suggest the primary sequence of RBD2 dimerization region is critical for RNA binding and LCST behavior we would postulate that any mutation that arises and is selected for in these regions (in patient isolates or across species) would be particularly informative. Most patient samples appear in the SR rich region of N-protein with comparatively few mutations present in structured regions and RNA binding domains . P326 anImportantly, our results suggest excessive differences in the length of the stem-loops appears to alter temperature encoding behavior with ∼20–24nt of dsRNA  lowering the temperature to as low as 25°C Figure  and C. TRBD1 preferentially crosslinked adjacent to SL3/TRS in the first 1000nt of the SARS-CoV-2 genome  Supplem. Our modDistinct N-protein ‘stickers’ are distributed throughout the genome Figure . This prFuture directions will involve modeling of the SARS-CoV-2 dsRNA and structured TRS-loop-like sequences patterning across the genome to examine if indeed sequence element patterning is sufficient for RNP patterning ,82. Of nOur data Figure  suggestsNotably, increasing RNA order, rather than disorder, through additional RNA structure drives N-protein condensation. These results contrast with those observed by the Mayr lab where increased disordered, single-stranded regions in RNA promoted intramolecular association and condensation . This diOur work suggests that reconstitution experiments of phase separating proteins with similar dsRNA preferences must be carried out with physiological RNA targets to capture biological behavior. DsRNA–protein interactions are not captured with poly A or U. In short, RNA sequence and structure profoundly influence the behavior of phase-separating systems. Finally, this work shows the complexity of the RNA–protein code in determining the kinetics, and emergent properties of biomolecular condensates. We predict that this is the tip of the iceberg in terms of unraveling the information provided by RNA sequence to specify the form and function of condensates.https://www.ncbi.nlm.nih.gov/sra/?term = PRJNA830870.All data are available upon request from C.A.R. or A.S.G. Raw and analyzed RNP-map and SHAPE data are available here GEO: GSE162569 and gkac596_Supplemental_FilesClick here for additional data file.