Recently, with the development of RNA sequencing technologies such as next-generation sequencing (NGS) for RNA, numerous variations of alternatively processed RNAs made by alternative splicing, RNA editing, alternative maturation of microRNA (miRNA), RNA methylation, and alternative polyadenylation have been uncovered. Furthermore, abnormally processed RNAs can cause a variety of diseases, including obesity, diabetes, Alzheimer’s disease, and cancer. Especially in cancer development, aberrant RNAs caused by deregulated RNA modifiers or regulators are related to progression. Accumulating evidence has reported that aberrant RNAs promote carcinogenesis in many cancers, including liver cancer, leukemia, melanoma, lung cancer, breast cancer, and other cancers, in which abnormal RNA processing occurs in normal cells. Therefore, it is necessary to understand the precise roles and mechanisms of disease-related RNA processing in various cancers for the development of therapeutic interventions. In this review, the underlying mechanisms of variations in the RNA life cycle and the biological impacts of RNA variations on carcinogenesis will be discussed, and therapeutic strategies for the treatment of tumor malignancies will be provided. We also discuss emerging roles of RNA regulators in hepatocellular carcinogenesis. A single gene can generate a variety of RNA products, and changes in this final RNA output can directly contribute to cancer onset and progression. The initial transcription of each DNA sequence yields a raw RNA strand that subsequently undergoes a variety of modification processes that shape its function. Hee Doo Yang and Suk Woo Nam, The Catholic University of Korea, Seoul, have reviewed the potential impact of these mechanisms on malignancy. Some cancers, for example, express RNA sequences that have been inappropriately edited by an enzymatic process called splicing, yielding abnormal RNAs that drive metastasis. Other tumors contain RNAs with atypical chemical modifications, or in which individual nucleotides have been enzymatically converted into other nucleotides. A deeper understanding of these RNA alterations and their impacts could lead to more effective and targeted cancer treatments. Most cancer cells establish a resistant state via the epigenetic regulation of genes and/or through aberrant alterations regulating physiological conditions in various environments that provide a survival advantage in response to the selective elimination performed by the host2. These pre-RNAs made by RNA variations are translated into variant proteins with functional regions omitted because of splicing3, or they regulate noncanonical targets4. Especially, more altered RNA products can be made in cancer than in normal tissues, and they affect cancer progression.The advent of high-throughput transcriptome NGS has provided a wealth of information on RNA variation on a genome-wide scale. It has been uncovered by NGS that most human genes have resultant RNA variants, which give a single gene the potential to produce functionally multiple and distinct precursor RNAs (pre-RNAs)In this review, RNA variations are categorized into alternative splicing, RNA editing, microRNAs variation, RNA methylation and alternative polyadenylation, all of which yield alternative transcripts. These transcripts affect the functions of protein products or RNA by changing the target molecules, regulating stability, and removing miRNA-mediated translation inhibition or mediating mRNA–protein interactions and protein localization. We also describe the mechanistic functions of RNA variations and focus on cancer progression, especially hepatocellular carcinogenesis. In addition, we discuss ongoing efforts toward targeting-modified RNA and regulating altered mechanisms of RNA variations in cancer therapy.5. These transcript variants are made from alternative splicing of pre-mRNA. Since alternative splicing is a process by which multiple exons are differentially removed from the pre-mRNA transcript, a combination of various exons can be produced, resulting in the production of multiple final mRNA species. Examples of alternative RNA splicing mechanisms include cassette exon inclusion/exclusion, intron retention, mutually exclusive exons, alternative 5′ splice sites, and alternative 3′ splice sites  Consortium, each protein-coding gene has seven different transcript variants in generaltes Fig. 6.Fig. 1S7. Additionally, mutation of splicing factors may induce alternative splicing. According to Alsafadi and colleagues, mutation of splicing factor 3B subunit 1A (SF3B1) occurs frequently and results in deregulated splicing at a subset of junctions, mostly by the use of alternative 3′ splice sites8.In general, gene expression changes of splicing factors may result in alternative splicing. For example, serine/arginine-rich splicing factor 1 , pre-mRNA-splicing factor SF2 (SF2) or ASF1/SF2) is frequently overexpressed in various solid cancers with amplification of chromosome 17q23, and it induces alternative splicingcis-elements6. These cis-elements, such as enhancers of exon/intron splicing, are recognized by serine and arginine proteins (SR proteins) that function as trans-acting elements of RNA splicing to promote splice site recognition and exon formation2. In contrast, silencers of exon/intron splicing usually relate to trans-acting factors such as heterogeneous nuclear ribonucleoproteins (hnRNPs), which suppress splice site recognition and improve exon inclusion9.At least three major mechanisms regulating alternative splicing have been reported. First, alternative RNA splicing is regulated by 10, suggesting that alternative splicing is a critical step in cancer progression. Another RNA splicing process is connected with transcription initiation and elongation rates11. Promoter activities and RNA polymerase II elongation rates influence the recruitment of splicing factors to splice sites in a time-dependent way and therefore regulate the final RNA products11. Strongly activated promoters enhance transcription initiation and result in increased recognition of pre-mRNA by the spliceosome. Additionally, the increase in transcription elongation speed after transcription initiation raises the likelihood for the spliceosome to fail at weak splice sites on pre-mRNAs, which would be dependent on the elongation rate.In addition, single-nucleotide polymorphisms (SNPs) near splice sites can result in RNA splicing alterations. Human genome mutation databases have reported that among disease-causing SNPs, 15% of SNPs are found at splice sites, and over 20% of SNPs are located at splicing enhancers or splicing silencers of exons/introns12. Additionally, the interaction between H3K36Me3 and the adaptor protein Psip1/Ledgf recruits the splicing factor ASF/SF2, and alternative splicing is promoted13. Alternative splicing is regulated not only by the expression/function of RNA splicing factors but also by genomic mutations/SNPs, transcription and elongation rates, and epigenetic modifications. All of these complicated mechanisms contribute to the production of alternatively spliced RNA.The third alternative splicing mechanism is related to histone modification. Histone modification near RNA splice sites can affect RNA alternative splicing through recruitment of splicing-regulating proteins and RNA splicing factors. The adaptor protein MORF-related gene 15 (MRG15) interacts with epigenetically modified histone H3 Lys36 trimethylation (H3K36Me3), and hnRNPI  is recruited to regulate the inclusion of alternatively spliced exons14. Since then, the study of adenosine deaminases acting on RNA (ADARs) has increased. In mammals, A-to-I conversion is the most common type of RNA editing 17. Among the UTRs, the A-to-I editing frequency seems to occur more frequently in 3′ UTR sites than in 5′ UTRs18. Additionally, Alu repeats, a repetitive short interspersed element (SINE), are the most frequently edited sites. The human genome has a total of 919,035 Alu elements, and RNA editing sites are used in 305,337 Alu elements19. In addition, miRNAs are processed by ADARs (ADAR1 and ADAR2) that regulate miRNA biogenesis by A-to-I editing during miRNA maturation20.The unwinding of double stranded RNA (dsRNA) for adenosine to inosine (A-to-I) RNA editing was first found in oocytes of Xenopus laevising Fig. . There a21. APOBEC1 site-specifically edits the APOB gene and makes premature stop codons, including a short protein isoform of ApoB22. Recent reports of transcriptome sequencing showed additional RNA editing sites, mostly in the 3′ UTRs23. APOBEC3A, another site-specific C-to-U editing enzyme, showed editing functions after specific stimulation in monocytes and macrophages24. In contrast to those edited by ADARs, most targets edited by APOBEC3A are very site-specific and often contain coding regions, resulting in missense/nonsense alterations25. Whether other APOBECs, including APOBEC2 APOBEC3C, APOBEC3D, APOBEC3F, APOBEC3G, APOBEC3H, and APOBEC4, also edit cellular RNAs in specific physiological circumstances is unknown25. While some APOBEC3 proteins deaminate viral genetic substances or cancer genomes, the cytidine deaminase functions of these enzymes under normal physiologic conditions have not been demonstrated26.The activation-induced cytidine deaminase /apolipoprotein B editing complex (APOBEC) family contains evolutionarily conserved cytidine deaminases that have an intrinsic deamination activity for not only C-to-U RNA editing but also for dC (deoxycytidine)-to-dU (deoxyuridine) DNA editing Fig. . In huma4.With advances in NGS for RNA, it has been suggested that a single miRNA locus can make different miRNA isoforms (isomiRs) that differ in length and/or sequence composition. IsomiRs can be categorized into 5′ isomiRs and 3′ isomiRs, depending on the region of heterogeneity Fig. . Studies27. Furthermore, structural defects affect imprecise Drosha cleavage in the lower stem, altering the overall helical structure of the pri-miRNA, as well as disrupting the interaction between Drosha and the sequence motif of the lower stem28. RNA-binding proteins such as hnRNPA1 control Drosha cleavage by changing the secondary structure of the pri-miRNA, which might be one of the reasons why such proteins regulate alternative cleavage by Drosha29. Likewise, the cleavage site of Dicer affects the relative position of the pri-miRNA, pre-miRNA loops, structural uncertainty30 and Dicer co-factors such as trans-activation responsive RNA-binding protein (TRBP)31.Since sequence modifications at the 5′ end of miRNAs after maturation are rare, most 5′ isomiRs are made from imprecise cleavage by either Drosha or Dicer in the processing of miRNA biogenesis. Alternative cleavage by Drosha and/or Dicer frequently arising in miRNA biogenesis has been revealed from NGS for RNA, but it is generally unknown how these variations occur. Some studies have shown that deviations from the expected cleavage site between the basal junction and the apical junction of a pri-miRNA can result in alternative cleavage by Drosha32. These modifications basically include trimming  and tailing . Therefore, isomiRs include nontemplated nucleotides; for these reasons, it is difficult to track the origin of isomiRs33.Although alternative selection of cleavage sites by Drosha and Dicer during miRNA biogenesis contributes to the production of 3′ isomiRs, most 3′ isomiRs result from postmaturation modifications that occur almost exclusively at the 3′ end of miRNAs, unlike 5′ isomiRs34, and it is catalyzed by an RNA methyltransferase complex , while METTL14 plays a structural role in recognizing substrates36. Sometimes, the METTL3-METTL14 heterodimer requires adaptor proteins such as Wilms tumor 1-associated protein (WTAP)35. Furthermore, WTAP recruits many proteins and lncRNAs, indicating that WTAP functions as a gatherer of other factors to the methyltransferase complex37. Additionally, other adaptor proteins, such as KIAA142938, RNA-binding motif protein 15 (RBM15) and RBM15B39, have been reported to interact with the METTL3 complex, and downregulation of these adaptor proteins decreases the cellular m6A level. Additionally, METTL16 has been recently discovered as an m6A methyltransferase, which mainly methylates adenosine in 3ʹ UTRs, and its knockdown induced a decrease in m6A of up to 20%40. In contrast, fat mass and obesity-associated (FTO) and AlkB homolog 5 (ALKBH5) are the only identified m6A demethylases. Their activity depends on Fe(ii) and α-ketoglutarate, as they use ferrous iron as a co-factor and α-ketoglutarate as a cosubstrate to oxidize the N-methyl group of the m6A site, and as expected, depletion or overexpression of these compounds altered the m6A status41.N6-methyladenosine (m6A) is one of the common RNA modifications in mammals. m6A RNA methylation plays key roles in the regulation of posttranscriptional gene expression, including effects on mRNAs, miRNAs and long noncoding RNAs (lncRNAs). In addition, m6A methylation regulates various aspects of RNA metabolism, including RNA structure, maturation, stability, splicing, export, translation and decaylex Fig. . Methylt42. The readers interact with RNAs by two different mechanisms: direct reading or indirect reading. Direct reading means selective binding to the m6A site of RNAs by m6A reader proteins; in contrast, indirect binding implies that the secondary structure of RNAs is changed by m6A modification, which contributes to the accessibility of the sequence by RNA-binding proteins (referred to as the “m6A switch”)43. YT521-B homology (YTB) family proteins, including YTHDF1-344 and YTHDC145, can directly bind to m6A-modified RNAs. Additionally, among the nuclear RNA-binding proteins related to pre-RNA processing, hnRNPA2B1 and hnRNPC are responsible for reading the m6A site in a direct and indirect way, respectively. hnRNPA2B1 can directly bind to m6A-modified RNA and regulate miRNA processing46. In addition, the presence of m6A modification in RNAs provides hnRNPC with greater access to their U-tract motifs47.Similar to DNA methylation, the biological functions of N-methylation in the m6A site are regulated by m6A “readers”48.For RNAs, 3′ end processing is also critical, similar to other RNA maturation mechanisms. After pre-RNAs are made by RNA polymerase II, the RNA must be processed through 3′ end cleavage and polyadenylation, referred to as simply polyadenylation. One pre-RNA can have multiple polyadenylation sites and generate multiple transcripts that only differ in 3′ terminal sequences, known as alternative polyadenylation (APA) Fig. . At leascis-elements near the polyadenylation site (PAS). In mammals, upstream elements of the PAS include the sequence A[A/U]UAAA, U-rich elements and UGUA elements, and downstream elements consist of U-rich and GU-rich  elements48. As with other elements, CA sequences, UAUA elements, and G-rich sequences are found near PASs49. As mentioned above, alternatively polyadenylated variants are commonly generated, particularly from upstream APA sites50. For example, the AAGAAA sequence in upstream APA sites is frequently observed50. Additionally, other APA elements, such as upstream UGUA sequences and downstream GU-rich sequences, are found less frequently50. These sites have weaker polyadenylation potential and may regulate cell proliferation and differentiation in development or disease processes.Polyadenylation is regulated by 51. In addition, mRNAs can interact with RNA-binding proteins (RBPs) through the 3′ UTR region. In view of this fact, Berkovits and Mayr reported that altered 3′ UTR regions could function as scaffolds interacting with nascent proteins that affect cellular translocation52. Although most APA takes place in the 3′ UTR, the sequence upstream of the last exons, usually within introns, is also used to an APA site. Sites of APA upstream of the last exon [termed intronic polyadenylation (IpA) sites when polyadenylated within introns] can alter the translation regions of RNA, similar to making protein variants via alternative splicing. Additionally, proteins without apparent functions can be generated by APA in promoter-proximal introns53.Most APA sites are detected in the 3′ UTR and give rise to mRNA isoforms with different 3′ UTR lengths. 3′ UTR APA influences posttranscriptional regulation in diverse ways. For example, more than half of miRNAs target mRNAs by interacting with UTRs. By shortening the 3′ UTR of mRNAs, miRNA-mediated translation inhibition is broken, resulting in increased translation54. These phenomena may be linked to single-nucleotide variants (SNVs) within the genes that break the sequences necessary for canonical splicing. Tumor suppressors, but not oncogenes, are alternatively spliced due to SNV-induced mRNA sequence frameshifts resulting in intron retention (IR)54.Over the past decade, The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) Program have increased the amount of cancer genome and transcriptome data for cancer tissues and normal tissues, respectively Fig. . From th54. Interestingly, these alternative splicing events occurring in cancer cells elicit disturbances in the expression of certain genes, such as the immune-checkpoint blockade molecules programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) and T cell-associated genes. The alternatively spliced PD-L1 gene leads to the production of a truncated and alternatively polyadenylated mRNA and secretion rather than membrane localization and can also negatively regulate T cell function55. It was also reported in glioma tissues that some antiangiogenic factors, for example, vascular endothelial growth factor A (VEGFA), can be changed into pro-angiogenic isoforms in carcinogenesis56. In melanoma cells, overexpression of alternatively spliced Bcl-2-like protein 1  variants confers apoptotic resistance57. Furthermore, CD44, which promotes metastasis, has more than 20 alternatively spliced variants and these are common in various cancers58. In addition, it has been reported that more than 50% of nucleotide changes can induce splicing changes60. For instance, according to Supek and colleagues, silent mutations in cancer can affect RNA splicing in oncogenes61. As expected, RNAs with long introns are inclined to frequently cause splicing errors and result in the expression of protein-coding isoforms62.Comprehensive analysis of alternative splicing across 32 TCGA cancer types from 8705 patients also showed novel splicing sites caused by mutations66. However, a recent investigation has shown elevated editing levels in noncoding regions, such as intergenic, intronic and 3′ UTR regions, in thyroid, head and neck, breast and lung cancers compared to the levels in corresponding normal tissues, and these increases indicated poor patient survival67. These reports indicated potential roles of RNA editing in cancer progression and clinical outcomes.Transcriptome analysis of different types of cancers revealed various forms and levels of RNA editing in cancer cells Fig. . For ins68. In addition, RNA editing enzymes, such as ADARs, can play reciprocally oncogenic and tumor suppressive roles through their catalytic deaminase domains. In gastric cancer, ADAR2-induced editing of the podocalyxin-like (PODXL) gene confers a loss-of- function phenotype that neutralizes the tumorigenic ability of unedited PODXL69. Other RNA editing events in coding regions of the Ras homolog family member Q (RHOQ) gene in colorectal cancer70 and the solute carrier family 22 member 3 (SLC22A3) gene in esophageal cancer71 have been reported to contribute to cancer development.Editing of the protein-coding region has an effect on protein functions. For example, gamma-aminobutyric acid type A receptor alpha 3 subunit (GABRA3) activates the AKT pathway to promote breast cancer cell migration, invasion and metastasis. However, A-to-I-edited GABRA3 has reduced cell surface expression and suppressed the activation of AKT required for cell migration and invasion in breast cancer metastasis72. Given the widespread presence of A-to-I RNA editing sites and microRNA binding sites in the 3′ UTR, RNA editing-regulated miRNA binding might be a common mechanism to control gene expression and may also play a role in physiological and pathophysiological conditions.While the RNA editing sites in coding regions directly alter protein sequences and functions, RNA editing in the 3′ UTR may regulate the binding of miRNAs. The negative correlation between 3′ UTR editing and miR-200 b/c results from repression of mouse double minute 2 homolog (MDM2) by miR-200b/c. Thus, editing in the 3′ UTR of the miRNA binding site of MDM2 may avoid translational repression by miR-200b/c, causing MDM2 overexpression73. In melanoma, reduced editing of miR-455-5p promotes the growth and metastasis of cancer cells by causing it to target the tumor suppressor cytoplasmic polyadenylation element binding protein 1 (CPEB1)74. In glioblastoma, modulation of miR-221/22275 and miR-376a editing showed antitumor effects by targeting the oncogene RAP2A (a member of the Ras family)76. Aberrant overexpression of ADAR1 in lung cancer is associated with poor prognosis in patients, as it enhances the editing frequencies of target transcripts such as Nei-like protein 1 (NEIL1) and miR-38177. Wang and colleagues systematically characterized the miRNA editing profiles of 8595 samples across 20 cancer types from miRNA sequencing data from TCGA and identified 19 A-to-I RNA editing hot spots78. Among these, they demonstrated that edited miR-200b can promote cell invasion and migration through its impaired ability to inhibit ZEB1/ZEB2 and concomitant ability to repress leukemia inhibitory factor receptor (LIFR), a well-characterized metastasis suppressor78.Premature forms of miRNAs, being dsRNA molecules, can undergo A-to-I editing at different stages of biogenesis, affecting their maturation and expression. Editing of miRNAs, particularly in the seed region, can significantly alter their target gene, and many miRNAs are aberrantly edited and change their targets in various cancers79. A major concern regarding the biological function of 5′ isomiRs is that their expression levels are usually lower than those of their canonical form. Nevertheless, some 5′ isomiRs are expressed enough to function in specific tissues or diseased cells , but the 5′ isomiR of miR-9 is generated only from pri-miR-9-1. The unique structure of pri-miR-9-1 causes altered Drosha cleavage at other positions80. Thus, 5′ isomiR creation made by Drosha allows members of pri-miRNA families to achieve functional specialization. Now, this neofunctionalization is of special interest, given that more than 40% of miRNAs are members of a family, and approximately 14% are miRNA paralogs with similar mature sequences81. Likewise, recent studies report that 3′ isomiRs function as regulators of miRNA stability beyond intermediates of miRNA degradation. Additionally, the ratio of the 3′ isomiR to the canonical miRNA can be employed to distinguish different grades of cancer82. Additionally, it has been reported that many 3′ isomiRs have distinct activities from their canonical miRNAs83. However, because 3′ isomiRs, unlike 5′ isomiRs, share their seed region with canonical miRNAs, they may not affect target genes.Multiple lines of evidence suggest that isomiRs possess unique biological roles. Recent reports indicate that naturally existing isoforms have distinct activities in a wide range of biological processes, including regulation of cytokine expression, facilitation of virus proliferation, promotion of apoptosis and repression of tumor progression. Since 5′ isomiRs usually have a different start position from the defined seed region, 5′ isomiRs may affect target interactions by shifting the seed sequences. This change can allow 5′ isomiRs to regulate noncanonical target geneslls Fig. . For exa85. Recently, METTL3, an RNA methyltransferase, was demonstrated to promote translation in the cytoplasm in association with ribosomes in lung cancer86. METTL3 promotes the growth, survival, and invasion of human lung cancer cells by enhancing mRNA translation through an interaction with the translation initiation machinery. On the other hand, the exposure of breast cancer cells to hypoxic conditions, which is a critical feature of the tumor microenvironment, induces m6A demethylation by ALKBH5 and stabilization of NANOG mRNA, thereby promoting the breast cancer stem cell phenotype87. Aberrant m6A modification can affect acute myeloid leukemia (AML). For example, FTO, an m6A eraser, was highly expressed in AMLs with mixed-lineage leukemia (MLL) rearrangements, PML (promyelocytic leukemia)-RARA  translocations, and/or FLT3 (FMS-like tyrosine kinase-3)-ITD  or NPM1 (nucleophosmin 1) mutations88. FTO knockdown also inhibits AML growth, indicating that FTO functions by modulating m6A modification. In glioblastoma, highly expressed ALKBH5, also functioning as an m6A eraser, was associated with a poor prognosis in glioblastoma patients89. Knockdown of ALKBH5 reduced the growth of glioblastoma, which could be recovered by catalytically wild-type ALKBH5 but not H204A-mutated ALKBH589. Differentiated glioblastoma stem cell (GSC) cell lines had an increased m6A level, while primary GSC cell lines showed a lower m6A level90. Inhibition of METTL3 or METTL14 promoted the growth and self-renewal of GSCs, but overexpression of wild-type METTL3 rather than functionally inactive METTL3 inhibited the growth and self-renewal of GSCs, demonstrating that METTL3 can regulate self-renewal of GSCs through its methyltransferase catalytic function90. Overall, m6A modifications and their regulatory proteins play a role in various types of cancers, and therefore, targeting m6A modifications may serve as an effective treatment strategy.N6-methyladenosine (m6A) is the most abundant internal modification in mRNA. Similar to DNA and histone modification, RNA methylation patterns play an important biological function in the regulation of different cellular processes, such as metabolism, embryonic development, and stem cell self-renewal. There have also been links between alterations in m6A levels and abnormal cellular differentiation states present in cancer. m6A modifications have been shown to play a role in leukemia, brain cancer, breast cancer, and lung cancer. m6A modification has been suggested to contribute to cancer progression through alternative pre-mRNA splicing, RNA stability, miRNA processing and lncRNA splicing Fig. 47,84,85.53. Similarly, cyclin D2 is also increased by the loss of the miRNA binding site in its 3′ UTR91. Notably, recent results also suggest that shortening of the 3′ UTR of an mRNA may allow release of miRNAs to suppress the expression of other mRNAs in trans, acting as competing endogenous RNAs (ceRNAs) in lung cancer, breast cancer and colon cancer92.Alternative polyadenylation (APA) is a molecular process that generates diversity at the 3′ end of transcripts from RNA polymerase II. Recent studies have particularly highlighted the importance of APA dysregulation in cancer Fig. . Deregul52. Comprehensive analysis of APA sites and poly A tail lengths in 358 matched tumor-normal samples from seven TCGA datasets suggested that tumor-specific APA events produce the majority of short 3′ UTRs and the subsequent increased gene expression of oncogenes by enabling avoidance of miRNA-mediated gene regulation93. Altogether, APA appears to be highly tumor-specific and tissue-specific depending on the cancer type95.In addition to regulating mRNA expression through APA, 3′ UTRs can also mediate mRNA–protein interactions and protein localization. For instance, APA of short or long isoforms of CD47 mRNA affects the interaction with different protein complexes and thereby guides CD47 localization to either the plasma membrane (long isoform) or the endoplasmic reticulum (short isoform) in breast cancer, cervical cancer, ovarian carcinoma, leukemia, sarcoma, glioblastoma and neuroblastoma96. Aberrant expression of SF3B4 was demonstrated to modulate the expression of cell cycle and EMT proteins through spliceosome effects on the tumor suppressor kruppel-like factor 4 (KLF4) in hepatocellular carcinoma (HCC).RNA splicing is tightly regulated and closely interacts with genetic and epigenetic machinery. Tumor cells often take advantage of aberrant RNA splicing to develop, grow and progress into cancers. Splicing factor 3B subunit 4 (SF3B4) encodes a core protein in the mammalian SF3b complex, which is part of the U2‐type spliceosome that helps tether the U2 snRNP to the branch site. SF3B4 was overexpressed in a large cohort of HCC patients, and this aberrant overexpression was significantly associated with poor prognosis in HCC patients97.ADAR-mediated RNA editing is essential for survival in mammals; however, its dysregulation causes aberrant editing of its targets that may lead to cancer. ADAR1 is commonly overexpressed, for instance, in breast, lung, liver and esophageal cancer as well as in chronic myelogenous leukemia, where it promotes cancer progression. In hepatocellular carcinogenesis, antizyme inhibitor 1 (AZIN1) is edited to AZIN1-S367G, a more stable form of AZIN1 with a stronger affinity for antizyme than canonical AZIN1. Antizyme regulates cell growth by binding and degrading growth-promoting proteins such as ornithine decarboxylase (ODC) and cyclin D1 (CCND1), which are essential determinants of the G1/S cell cycle checkpoint. Compared to wild-type AZIN1, edited AZIN1-S367G has stronger antizyme binding and inhibits antizyme-mediated degradation of ODC and cyclin D1, thereby facilitating entry into the cell cycle and increasing the malignancy of liver cancer cells98. In HCC, METTL14 expression was decreased, and a negative correlation was observed between METTL14 expression and survival in HCC patients. In addition, immunoprecipitation assays showed that METTL14 coprecipitated with DGCR8, recognizing m6A-modified miRNA. miR-126 was decreased and unprocessed pri-miR-126 accumulated in METTL14-depleted cells. It worth noting that METTL14-depleted cells exhibited an enhanced growth rate and metastatic potential, indicating that METTL14 suppressed the malignant properties of HCCs by increasing m6A-dependent miR-126 expression98. However, METTL3 is significantly upregulated in HCC, and its overexpression is associated with poor prognosis in patients with HCC. Through m6A sequencing, suppressor of cytokine signaling 2 (SOCS2) was identified to be a target of METTL3-mediated m6A modification. As expected, when the expression of METTL3 was inhibited, SOCS2 mRNA m6A modification was abolished, and its mRNA level was also increased. In addition, m6A-mediated SOCS2 mRNA stability is regulated by YTHDF2, the m6A reader protein, the binding of which shortens the half-life of modified SOCS2 mRNA99. These reports suggest the role of m6A-mediated RNA modification in hepatocellular carcinogenesis.m6A is the most abundant and important internal modification of RNA in viruses and eukaryotes. Accumulating evidence suggests that aberrant regulation of m6A turnover is associated with multiple types of cancer, including acute myeloid leukemia, breast cancer, glioblastoma, lung cancer, and liver cancer. The liver is a vital metabolic and digestive organ in pathophysiological processes. Recent studies have suggested that m6A RNA modification highly regulates hepatic function and the development of liver diseases. m6A modification is reduced in HCC tissues compared to normal hepatic tissues100. Low expression of NUDT21 is associated with poor prognosis in terms of overall and disease-free survival in patients with HCC. NUDT21 inhibited HCC proliferation, metastasis and tumorigenesis, at least in part, by suppressing proteasome subunit beta type-2 (PSMB2) and CXXC-type zinc finger protein 5 (CXXC5), acting as a tumor suppressor in hepatocellular carcinogenesis.The 3′ UTR alterations induced by APA are regulated by a variety of members of the cleavage and polyadenylation machinery. Nudix hydrolase 21 , an essential factor for RNA 3′ cleavage and polyadenylation, is involved in APA in HCCOverall, various RNA regulating factors may have critical roles in hepatocellular carcinogenesis Fig. .Fig. 3Sc101. Therefore, in cancers, changes in the levels of both RNA variants and RNA variation-associated factors are likely to be potential molecular markers for cancer diagnosis and may provide new targets for research and contribute to the development of clinical molecular targeted therapies.Although major developments in our understanding of cancer genomics and molecular biology have been made, the contribution of RNA variations and RNA variation-associated factors to cancer pathogenesis has not been fully elucidated. In this review, we summarized the role of RNA variations and their regulatory factors in diverse aspects of cancer development and progression. Indeed, with advanced technology, as increasingly advanced RNA variants are identified and intracellular functions become known, the pathogenic roles of these RNA variants in cancer development will become more detailed. The identification of functionally important pathologic RNA variants opens up the possibility of therapeutic interventions targeting RNA variants or RNA variation-associated factors in cancers. Thus, regulation of RNA variations could be an effective therapeutic approach for cancer therapy, and a number of approaches have been taken to develop compounds that can experimentally, and sometimes clinically, affect splicing control, resulting in potential novel therapeutics


Comfortable beds play an important role in increasing the ruminant and milk production efficiency of dairy buffalo. In loose housing systems, cow lying comfort depends on both the bedding materials and bed base.P < 0.01). No significant difference in the cow comfort index (CCI) was detected between S-10a and S-15; however, both showed higher CCI than that of the S-20 bed. In Exp2, buffaloes spent more time lying on the wood shavings at depth of 15 cm (WS-15) bed followed by the WS-20 and S-10b beds, respectively (P < 0.01), and CCI was greater in the WS-15 bed than in the S-10b and WS-20 beds (P < 0.05).Buffaloes spent more lying time on sand beds at depth of 15 and 20 cm (S-15 and S-20) than on beds of 10 cm (S-10a) beds or in the feed alley in Exp1 (A depth of sand or wood shavings at 15 cm can meet the lying comfort requirements of dairy buffaloes when bedding materials are used above drainage beds. India, China and Pakistan contain most of the world’s buffalo population. India produces 70% of the world’s buffalo milk, and buffalo milk from Pakistan, China and Egypt make up 20, 5 and 4% of the world’s production, respectively [There are 199 million buffaloes in the world, with 194 million buffaloes distributed in Asia  The bottom layer that was made from impervious concrete with a 2% slope; (2) The middle layer that was made from rubble stone with a depth of 30 cm; and (3) The top layer that was made from 20 cm deep cobblestone, followed by 10 cm of gravel. The bed base was divided into three cubicles (12.5 m × 4.0 m) with round-timber and the buffaloes had access to all three cubicles in Exp1. The three cubicles were covered with sand at a depth of 10 cm (S-10a), 15 cm (S-15) and 20 cm (S-20)  met the requirements for lying areas for buffaloes. Buffaloes were fed a whole corn silage and concentrate, and they had free access to fresh drinking water.The study was conducted in Dehong, China in December 2018. Fifteen healthy buffaloes with similar body conditions were used in the study and each bedding area (50 mThe cow comfort index (CCI) was used to evaluate the lying comfort of each bed covered with the different bedding materials to certain depths. We recorded the number of buffaloes lying on a bedding area at 10:00, 16:00 and 20:00 h to calculate CCI. CCI is calculated by dividing the number of buffaloes lying on a bedding surface by the total number of buffaloes . Faeces Fifteen dairy buffaloes were observed using continuous sampling for 96 h. Buffalo behaviours including standing, lying and defecation were measured. A buffalo was considered to be lying when her body trunk was in contact with the ground. Buffaloes were considered standing when their body weight was supported by four legs. Defecation was defined as occurring when faeces was observed dropping down from the anus. After finishing the field trail, animal behavioural data were extracted from video files to evaluate the preferences of buffalo for bedding surfaces.Analyses were performed using IBM SPSS 21.0 . Behavioural parameters  were obtained from individual buffaloes. Behavioural data and the amount of faeces were analysed using one-way analysis of variance.P < 0.01). In terms of standing without feeding, buffaloes spent less time in the feed alley and the S-10a bed than in the S-15 and S-20 beds, and no significant difference was detected between the S-15 and S-20 beds (P > 0.05). No buffalo selected the feed alley as a lying area. The most preferred bedding surface was S-15, followed by S-20. Buffaloes spent the least time lying in the S-10a bed. No differences in the time budgets for defecation was detected between the feed alley and the three bedding surfaces (P < 0.05).The total time budgets of the dairy buffaloes in Exp1 are summarised in Table P > 0.05); however, standing time was significantly higher than that for the S-10 b and WS-15 beds (P < 0.01). After subtracting the feeding time, buffaloes spent less standing time in the feed alley than that of the three bedding surfaces. No buffalo selected the feed alley as a lying area in Exp2 and time spent lying was significantly different between the S-10b, WS-15 and WS-20 beds (P < 0.01). Buffaloes preferred to lie on the WS-15 bed rather than the WS-20 and S-10b beds. Defecation time in the feed alley was lower than that of the S-10b, WS-15 and WS-20 beds.Dairy buffalo behaviours in Exp2 are shown in Table P < 0.05). In Exp2, buffaloes in the WS-15 bed had a higher CCI than those in the S-10b and WS-20 beds; however, no significant difference was detected between the S-10b and WS-20 beds (P > 0.05).The CCI for dairy buffaloes is summarised in Table P < 0.01); however, no significant differences were detected among the three bed in Exp2 (P > 0.05).The amount of faeces at different locations is shown in Table Lying is a high priority for dairy cattle  and beddDairy buffaloes showed a preference for lying in S-15 beds rather than S-20 beds in Exp1, which is contrary to a previous study that showed lying time decreased on a thin layer of sand bed . Dry sanP < 0.01), with the least favourite bed being the S-10b bed . Wood shavings may provide greater lying comfort in temperate climates and support when transitioning between standing and lying. Another possible explanation is that the WS-15 beds could provide a comfortable lying environment when the depth of the WS is manually groomed and replenished in a timely manner to keep it at a similar depth above the drainage bed. The key characteristic of this bed base is that it keeps bedding materials dry and clean by draining away urine, which may increase the lying time for buffaloes.Consistent with the results in Exp1, buffaloes also had a higher preference for lying on WS-15 rather than WS-20 beds (The CCI was inconsistent with the time budget for lying in Exp1. Cook et al.  also faiDefecation time in the feed alley was lower than that in the S-10b, WS-15 and WS-20 beds, and most of the buffalo faeces were distributed in the feed alley. As there are no special feed alleys in many small-scale and family farms, buffalo body surfaces are often very dirty, which affects milk quality and their welfare. Based on the distribution of faeces, it is necessary to design a special feed alley to decrease the amount of faeces above the bedding material. Based on this evaluation of the defecation behaviour and faeces distribution, faeces were collected twice daily, making bedding surfaces dry and clean. We therefore did not evaluate buffalo cleanliness. Wood shavings, as a type of organic bedding material, may cultivate fly larvae and coliforms, as occurs in long straw, resulting in mastitis outbreaks , 25. FutThe results from the present study indicated that sand at a depth of 15 cm on drainage beds can meet the requirements for lying comfort of dairy buffaloes. When using wood shavings as bedding material on a drainage bed, dairy buffaloes preferred to lie on it at a depth of 15 cm. A special feed alley design for feed and defecation can keep bedding material dry and clean to increase lying comfort.


TAIL). In this paper, using size exclusion chromatography (SEC), SEC-multi-angle laser light scattering (SEC-MALLS) analysis, surface plasmon resonance (SPR) and fluorescence anisotropy, we provide the first comparative study designed to dissect the interaction between the four NPTAILs and four importins-α identified as partners. All interactions between NPTAILs and importins-α have high association and dissociation rates and present a distinct and specific behaviour. D/NPTAIL interacts strongly with all importins-α while B/NPTAIL shows weak affinity for importins-α. A/NPTAIL and C/NPTAIL present preferential importin-α partners. Mutations in B/NPTAIL and D/NPTAIL show a loss of importin-α binding, confirming key NLS residues. Taken together, our results provide essential highlights of this complex translocation mechanism.Influenza viruses are negative single-stranded RNA viruses with nuclear transcription and replication. They enter the nucleus by using the cellular importin-α/-β nuclear import machinery. Influenza nucleoproteins from influenza A, B, C and D viruses possess a nuclear localization signal (NLS) localized on an intrinsically disordered extremity (NP Orthomyxoviridae family and form the genus Influenzavirus. Up to now, the International Committee officially recognizes four types  in its Taxonomy of Viruses (ICTV), but because of actual large-scale meta-transcriptomic approaches new specimens are regularly discovered, making this classification a constantly evolving entity. While influenza viruses were thought to be uniquely warm-blooded organism pathogens, a study has recently uncovered their existence in fish and amphibians in China [Influenzavirus is based on their tropism. Influenza type A viruses (IAV) are viruses from water fowl but some of the viruses can also infect a range of hosts from chickens to swine and humans; type B (IBV) almost exclusively infect humans; type C (ICV) can infect both human and swine whereas type D (IDV) has a broad host tropism but limited to mammals. Influenza viruses are negative-sense single-stranded RNA viruses with segmented genomes. The RNA segments are packaged in ribonucleoproteins (RNPs), a complex architecture made by a single RNA molecule encapsidated by multiple copies of the nucleoprotein (NP) and the heterotrimeric RNA-dependent RNA polymerase (RdRp) bound to the strictly conserved 3′ and 5′ end [Influenza viruses are part of the in China . A firstd 5′ end ,3. The nUnlike most RNA viruses, influenza viruses transcribe and replicate their genome in the nucleus of infected cells. In general, the access to the nuclear compartment is through the highly regulated nuclear pore complex (NPC) ,5,6,7. Sterminal for A/ and B/NP or in Cterminal for C/ and D/NP (TAIL) and D (D/NPTAIL) NPs. We showed that the NLS of B/NPTAIL is highly extended from residues 30 to 71, around a single basic Lysine-Arginine (44-KR-45) patch, with a low affinity of 844 nM for the human importin-α7. In the case of the Cterminal D/NPTAIL, the NLS was composed of two basic KR patches, respectively 514-KR-515 and 532-KR-533. Both contribute to the nuclear trafficking and we estimated that the affinity of D/NPTAIL for the human importin-α7 was at 100 nM by surface plasmon resonance (SPR). The literature also contains several studies detailing the relation between A/NP and C/NP and importins-α [The human genome encodes for seven importins-α and at least twenty importins-β ,18,19, mand D/NP . A minorortins-α ,41,42,43ortins-α ,35,44,45TAILs) of all types of influenza NPs and the different human importin-α isoforms described in the literature. Our strategy was design, with a specific focus upon the short NLS sequences, and built with the objective of avoiding the inherent oligomerization of NPs, while guaranteeing the architecture of the tails in a unique globular environment. Using size exclusion chromatography experiments, we show that all NPTAILs interact with importins-α in solution and then used surface plasmon resonance measurements to determine the affinity and binding kinetics of these interactions. In the current paper, we show that D/NPTAIL interacts with all importins-α isoforms with strong affinity. Both A/NPTAIL and C/NPTAIL interact with varying affinities with the corresponding importins-α. On the other hand, B/NPTAIL shows a completely different behaviour, with even faster association and dissociation rates and a low affinity with all the human importins-α we measured.Because we were confronted with a wide range of values (from 26 nM to 72 µM) obtained using different techniques and a plethora of different partner constructs, we wanted to establish a systematic comparative study of the in vitro interaction between the flexible extremities (NPTAILs from strains A/WSN/1933 (residues 1 to 21), B/Memphis/13/03 (residues 1 to 71), C/Ann-Arbor/1/50 (residues 508 to 565) and D/bovine/France/2986/2012 (residues 505 to 552) were ordered from GeneART, fused to a biotinylation sequence in Cterminal (TAILs were fused to the yellow fluorescent protein (YFP) either in Cterminal (C/NPTAIL and D/NPTAIL) or in Nterminal  according to their native localization; at the other YFP extremity, the biotinylation sequence was added . The control peptide was a synthetic peptide  corresponding to a GLA domain-derived polypeptide of the human coagulation factor X [Human importin-α1 (residues 69 to 529), -α3 (residues 64 to 521) and -α5 (residues 66 to 538) DNA coding sequences were bought at GENEART GmbH  and subcloned into pETM11 bacterial expression vector (EMBL) without their importin-β (IBB) domains. Human importin-α7 (residues 58 to 536) cloning was described in . NLS-beaterminal . The NPTas added . NPTAILsfactor X .Escherichia coli BL21 RIL (DE3) cells  were used for protein expression. Cultures were supplemented with biotin  to biotinylate the proteins in cellulo, induced for 12 h by adding 0.3 mM isopropyl-β-D-thiogalactopyranoside  at 18 °C and collected by centrifugation. Pellets were resuspended in 50 mM Tris-HCl pH 7.5, 300 mM NaCl, 2 mM β-mercaptoethanol  and cOmplete™, ethylenediaminetetraacetic acid (EDTA)-free protease inhibitor cocktail  before sonication. All purifications included a nickel affinity chromatography , a Tobacco Etch Virus (TEV) protease cleavage, a second nickel affinity chromatography and a size-exclusion chromatography (SEC). SEC was performed on a NGC system  with a S75 10/300 GL column . The final buffer composition for all proteins was 10 mM Hepes pH 7.5, 150 mM NaCl. NPTAILs-YFP protein concentrations were determined by measuring the absorbance at 280 nm and using the theoretical extinction coefficients (ε) 28,942 M−1·cm−1 for A/NPTAIL-YFP and C/NPTAIL-YFP, of 27,452 M−1·cm−1 for B/NPTAIL-YFP, D/NPTAIL-YFP and YFP control. ε at 280 nm used for ΔIBB importins-α protein concentrations were 50,607 M−1·cm−1 for importin-α1, 42,190 M−1·cm−1 for importin-α3, 52,285 M−1·cm−1 for importin-α5 and 46,785 M−1·cm−1 for importin-α7. The concentrations were then obtained using the Beer–Lambert law.TM 200 increase 10/300GL column  for YFP-NPTAIL fusion proteins and a SuperdexTM 75 10/300GL column  for all the other NPTAILs. Samples were diluted to be used at 30 μM for YFP-NPTAIL fusion proteins, 60 μM for NPTAILs and 25 μM importin-α7 in 300 μL. They were incubated for one hour at room temperature before injection on a NGC system (Bio-Rad).All size exclusion chromatography (SEC) experiments were performed in the same buffer  using a SuperdexTM 200 increase 10/300 GL or Superdex 75 10/300 GL) equilibrated with 10 mM Hepes pH 7.5, 150 mM NaCl. Analytical runs were performed at 20 °C with a flow rate of 0.5 mL·min−1. Multi-angle laser light scattering (MALLS) detection was performed with a DAWN-HELEOS II detector  using a laser emitting at 690 nm and protein concentration was measured on-line with the use of differential refractive-index measurements, with an Optilab T-rEX detector (Wyatt Technology) and a refractive-index increment, dn/dc of 0.185 mL·g−1. Data were analyzed and weight-averaged molar masses were calculated using the ASTRA software .Size exclusion chromatography (SEC) followed by multi-angle laser light scattering (MALLS) and refractometry (RI) analysis allow the determination of the molecular mass of a protein or a complex in solution that is independent of its dimensions and shape . SEC was−1 in 50 mM acetate buffer pH 4.5; Sigma) was first immobilized on a Serie S CM5 sensor chip  surface through amine coupling chemistry according to the manufacturer instructions, until a coupling level of about 17,000 resonance units (RUs) was reached. The biotinylated NPTAIL-YFP (1–10 μg·mL−1) or biotinylated YFP control (1–10 μg·mL−1) were then captured in surfactant-supplemented HBS-N running buffer  at a flow rate of 30 μL·min−1 until a coupling level of 100–200 RU was obtained. A flow-cell with immobilized avidin only was used as negative control while the flow-cell with the avidin: biotinylated NPTAIL–YFP complex was used as active flow-cell. For kinetic measurements, importins-α were serial-diluted in surfactant-supplemented HBS-N running buffer. Each concentration was injected in triplicate on both the reference and active flow-cells. Analyte injection and following buffer injection times were set between 55–180 s and 55–200 s respectively, depending on the examined partners, at a flow-rate of 30 μL·min−1. Regeneration was required and achieved by pulse injection of 5 M NaCl. All sensorgrams were reference-subtracted. Data were analyzed with Steady State Analysis using the Biacore T200 Evaluation software  under a Langmuir 1:1 binding model, assuming that the binding is equivalent and independent for all binding site. Chi2 values for the fitting were kept below 1 for most of the analysis with a maximum of 2.5, and T-value means for the dissociation constant above 10.Surface plasmon resonance (SPR) experiments were carried out at 25 °C on a Biacore T200 . Avidin , Aexp is the anisotropy value observed for one given importin-α1 concentration, and Amin and Amax stand for the fluorescence anisotropy values of the free YFP-NPTAIL and bound YFP-NPTAIL, respectively. Titrations were then fitted to the GraphPad Prism model “Single binding site with Hill slope (h)”.Fluorescence anisotropy experiments were performed on a Clariostar microplate reader  set and dedicated to fluorescence anisotropy measurements, with excitation and emission wavelengths fixed at 482 and 530 nm, respectively. Importin-α1 was serially diluted in buffer  and mixed in dilution series with the YFP-fused NPTAILs. We designed our study with a specific focus upon these short sequences that do not address the effect of domains beyond the NPTAILS. In order to decipher the specificities of the different NPTAILs for importins-α, we first use the corresponding peptides, in size exclusion chromatography (SEC) experiments combined with surface plasmon resonance (SPR) measurements to determine the affinity and binding kinetics. The first method was used to confirm the ability of the tails to interact with its partner in solution, whereas the second method was used for the determination of the kinetic parameters of the interactions. In SPR, one partner  is immobilized onto a biosensor surface. The interacting partner  diluted in a buffer is then continuously flowed across the biosensor surface, where it binds to the ligand. The binding is measured as a change in resonance units (RUs) on the biosensor surface. Measuring the increase in binding over time for a given analyte set of concentrations gives the association rate (onk) up to the point where the system is at equilibrium . Ceasing flow and changing to buffer alone then allows the analyte to wash off the ligand. Measuring the decrease in bound partner over time gives the dissociation rate (offk). The equilibrium dissociation constant (dK) is calculated from the kinetic association and dissociation rates (offk/onk). When both association and dissociation rates are too fast, it is possible to use the equilibrium part of the curves to extract the dissociation constant, without relying on the rates. For the SPR experiments, we chose to immobilize the tails on the biosensor surface by using the importins-α as the analytes. The immobilization of the tails was done by fusing a biotinylation sequence in Cterminal (−1 biotin in the growth media) and purified. We first tested their ability to interact with importin-α7 by SEC experiments. They all formed a stable complex in solution with importin-α7  and kinetic parameters values (onk and offk)). Gradient concentration of importin-α7 were injected into the SPR flowing channels at a speed of 30/µL·min−1 for 50–180/s to reach equilibrium. As shown in TAILs in a quick “in and out” manner. Equilibrium analysis was then chosen to derive affinity binding constants (dK) for the interaction between the immobilized NPTAILs and the importin-α7 in solution. Our reference was the data obtained for the interaction between D/NPTAIL and importin-α7 previously measured using the same method and the same strategy [dK of 99 nM ± 9 nM for this interaction and 29 nM ± 1 nM using a new generation Biacore T200. This time, we were able to fully exploit the SPR data obtained with all NPTAILs. In particular, we showed that the architecture of the NLS (mono- or bipartite NLS) has no importance for importin-α7; the affinity for the non-conventional monopartite A/NPTAIL was better than for the bipartite C/NPTAIL, with dK of 73 ± 4 nM and 146 ± 8 nM respectively, but weaker than D/NPTAIL. B/NPTAIL appeared to be the lowest value with a dK of 405 ± 5 nM, but comparable to the value obtained using isothermal titration calorimetry [on rates, suggesting that very little energy is needed to form the interaction, but also very high off rates. Both association and dissociation rates were close to the upper detection limits of the apparatus, respectively around 10−6 M−1·s−1 and 0.1 s−1 and even above in the case of the B/NPTAIL . On the contrary, the architecture of the NLS seems essential for recognition by importin-α3. The two bipartite NLS tails  have a higher affinity than the two monopartite  which both show identical values. Based on these results, we further deciphered the interactions by introducing point mutations in the positive charge patches of the NLSs which we had analyzed in the past  [TAIL seems to present a cooperative behaviour in importin-α binding. On the other hand, importin-α7 seems to be more prompt in compensating for mutations in the first patch whereas importin-α3 looks more permissive to mutations in the second. The results obtained with B/NPTAIL mutant confirm our nuclear magnetic resonance (NMR) observations on the major contribution of the whole tail, from residues 30 to 71, in the interaction with importins-α, and not only the regions surrounding the KR motif [TAIL mut1-YFP, even if we were not able to quantify precisely the equilibrium dissociation constants from the raw data, probably because importin-α require a longer injection period to saturate all the ligand binding sites in this condition, the sensorgrams show clear concentration dependent-responses in contrast to the YFP-D/NPTAIL mut3 construct  ,38. We sonstruct .–α7 were similar to the theoretical values, the results obtained with ΔIBB importin-α1 suggest a propensity for dimerization of this construct. The corresponding sample was eluted precociously from the S200 column with an apparent molecular mass of 88 kDa rather than the theoretical 50 kDa  B/NPTAIL shows even faster association and dissociation rates with very low affinity.In this paper, we provide a comparative characterization of the interactions between four importin-α isoforms with the tails from A/NP, B/NP, C/NP and D/NP. The affinities are between the nanomolar and the low micromolar range, with association and dissociation rates surprisingly high. Two different behaviours were identified: (i) A/NPTAIL was isolated from a human strain of influenza A virus and interacted preferentially with importin-α7. This is consistent with the importins-α expression pattern in the human respiratory track [TAIL to importin-α3 is consistent with the fact that importin-α3 tends not to interact well with monopartite NLS; while A/NPTAIL is not a monopartite NLS per se, it possesses only a short NLS motif. In contrast, C/NPTAIL presents a higher affinity for importin-α3. Importin-α3 has a low auto-inhibition and a unique intrinsic flexibility, acting as an adapter for unusual and complex NLS sequences or NLS close to globular domains [TAIL is similar to a bipartite NLS, with two basic patches, but separated by a long linker sequence (more than 20 residues). Such a sequence could require the flexibility of importin-α3 to achieve optimal binding. D/NPTAIL is a textbook case of bipartite NLS, which binds tightly to importins-α, using both the minor and major binding pockets [TAIL strongly interacts with all tested importins with a high affinity (20–41 nM), in the same range as other bipartite NLSs (dK ≈ 10 nM) [in cellulo is in the micromolar range. Addition of cytosol in in vitro assays led to the destabilization of importin: NLS complexes, even in the case of bacterial lysate, highlighting the contribution of non-specific interaction and competition in this cellular process [The A/NPry track  as well ry track . It is ory track . The poo domains ,54. Such pockets ,56,57. D≈ 10 nM) ,58. In o process ,59. ImpoTAIL and D/NPTAIL along with the affinities resulting from D/NPTAIL mutations clearly suggest that the interaction follows a 1:1 binding model with cooperativity. At the other end of the spectrum, B/NPTAIL behaviour towards importins-α is still puzzling. It is possible that the B/NPTAIL is not properly processed in our settings. It is well known that A/NP and B/NP nuclear import are regulated through post-translational modifications (PTM), in particular through phosphorylation [CORE in our experiment could also be responsible for the lack of functionality of B/NPTAIL: three-dimensional context could matter for importin specificity, with putative additional contacts and constrains, and for NLS docking [terminal tail. Such a tail could be involved in the formation of liquid phase separation and help with protein recruitment [The sensorgram shapes of C/NPrylation ,61. A dirylation ,64,65,66 docking ,28,53,67 docking ,69. Co-i docking ,71. Therruitment ,73. If Bruitment ,75,76.tails were derived from human viruses. However, due to the high conservation of these importins through evolution (Our work focuses on human importins-α, as three out of the four NPvolution , it is lTAILs with importins-α1, -α3, -α5 and -α7. NPCORE involvement, NP oligomerization, cellular environment, IBB domain contribution, and post-translational modification of both partners are other factors which need to be investigated in the future, in the hope of fully dissecting this host-pathogen interaction and trying to target and disrupt this essential hijacking mechanism.While a lot of work is still required to fully understand the mechanistic and specificity of the interactions between influenza nucleoproteins and importins-α, we provide here this first comparative study on the interaction of NPTAIL, C/NPTAIL and D/NPTAIL interact strongly with one or several importins-α. On the contrary, the human specific B/NPTAIL interacts poorly with selected importins-α, raising new questions about this essential interaction in the influenza virus cycle.While the interactions between influenza NPs and importins-α have been extensively studied, this has mainly been done through the prism of A/NP, with a large number of highly different methods and sometimes without the essential focus required on importins-α. Whereas each method and study brought useful characterization insights, it is a complex task to compare affinity from widely different assays, with significant changes in conditions, partners, settings and analysis. Here, we provide the first comparative study to dissect several interactions between influenza NPs and importins-α using the same strategy and under the same conditions. We showed that A/NP


They used cryo–electron microscopy to determine a 2.9-angstrom-resolution structure of the RNA-dependent RNA polymerase nsp12, which catalyzes the synthesis of viral RNA, in complex with two cofactors, nsp7 and nsp8. nsp12 is a target for nucleotide analog antiviral inhibitors such as remdesivir, and the structure may provide a basis for designing new antiviral therapeutics.Many in the scientific community have mobilized to understand the virus that is causing the global coronavirus disease 2019 (COVID-19) pandemic. Gao Science, this issue p. 779 The structure of the COVID-19 virus polymerase essential for viral replication provides a basis for the design of new antiviral drugs. A novel coronavirus [severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2)] outbreak has caused a global coronavirus disease 2019 (COVID-19) pandemic, resulting in tens of thousands of infections and thousands of deaths worldwide. The RNA-dependent RNA polymerase  is the central component of coronaviral replication and transcription machinery, and it appears to be a primary target for the antiviral drug remdesivir. We report the cryo–electron microscopy structure of COVID-19 virus full-length nsp12 in complex with cofactors nsp7 and nsp8 at 2.9-angstrom resolution. In addition to the conserved architecture of the polymerase core of the viral polymerase family, nsp12 possesses a newly identified β-hairpin domain at its N terminus. A comparative analysis model shows how remdesivir binds to this polymerase. The structure provides a basis for the design of new antiviral therapeutics that target viral RdRp. Coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus [severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2)] that emerged in December 2019 (Coronaviruses (CoVs) employ a multisubunit machinery for replication and transcription. A set of nonstructural proteins (nsps) produced as cleavage products of the ORF1a and ORF1ab viral polyproteins  was incubated with nsp7 (residues S1 to Q83) and nsp8 (residues A1 to Q198), and the complex was then purified (fig. S1). Cryo-EM grids were prepared using this complex, and preliminary screening revealed excellent particle density with good dispersion. After the collection and processing of 7994 micrograph movies, we obtained a 2.9-Å resolution three-dimensional reconstruction of an nsp12 monomer in complex with one nsp7-nsp8 pair and an nsp8 monomer, as was previously observed for SARS-CoV (The structure of the COVID-19 virus nsp12 contains a right-hand RdRp domain (residues S367 to F920) and a nidovirus-specific N-terminal extension domain (residues D60 to R249) that adopts a nidovirus RdRp-associated nucleotidyltransferase (NiRAN) . An addiThe overall architecture of the COVID-19 virus nsp12-nsp7-nsp8 complex is similar to that of SARS-CoV with a root mean square deviation (RMSD) value of 0.82 for 1078 Cɑ atoms (fig. S4C). However, there are key features that distinguish the two. The cryo-EM map allowed us to build the complete structure of COVID-19 virus nsp12, including all residues except S1 to D3 and G897 to D910. In contrast, the first 116 residues were not resolved in SARS-CoV nsp12 . In the The polymerase domain adopts the conserved architecture of the viral polymerase family . The catpol (residue D233)  . Motif CIn this structure, as in other RNA polymerases, the primer-template entry, NTP entry, and nascent strand exit paths are positively charged and solvent accessible, and they converge in a central cavity where the RdRp motifs mediate template-directed RNA synthesis . The conRemdesivir, the single Sp isomer of the 2-ethylbutyl L-alaninate phosphoramidate prodrug . The latThe rapid global spread of COVID-19 virus has emphasized the need for the development of new coronavirus vaccines and therapeutics. The viral polymerase nsp12 appears to be an excellent target for new therapeutics, especially given the fact that lead inhibitors already exist in the form of compounds such as remdesivir. Considering the structural similarity of nucleoside analogs, the binding mode and inhibition mechanism discussed here may also be applicable to other similar drugs or drug candidates such as favipiravir, which has proven effective in clinical trials (


Diadema antillarum density, among reef locations, and as a function of recreational use. Nearshore reefs reflected higher percent macroalgal cover, likely due to increased exposure from both recreational activities and nearby unsustainable land-use practices. However, nearshore reefs still support a high abundance of the endangered reef-building coral Orbicella annularis, highlighting the need to conserve these natural shoreline protectors. There is an opportunity for local stakeholders and regulatory institutions to collaboratively implement sea-urchin propagation, restoration of endangered Acroporid coral populations, and zoning of recreational densities across reefs. Our results illustrate vulnerable reef hotspots where these management interventions are needed and recommend guidelines to address them.Caribbean coral reefs provide essential ecosystem services to society, including fisheries, tourism and shoreline protection from coastal erosion. However, these reefs are also exhibiting major declining trends, leading to the evolution of novel ecosystems dominated by non-reef building taxa, with potentially altered ecological functions. In the search for effective management strategies, this study characterized coral reefs in front of a touristic beach which provides economic benefits to the surrounding coastal communities yet faces increasing anthropogenic pressures and conservation challenges. Haphazard photo-transects were used to address spatial variation patterns in the reef’s benthic community structure in eight locations. Statistically significant differences were found with increasing distance from the shoreline, reef rugosity,  Coral reefs are biodiverse and socio-economically important ecosystems , yet havDiadema antillarum  to 14% (±7.2 95% CI) in 2013 , suggests it is transitioning into a coral-depleted, novel reef. However, this historical data is limited to two spatially clustered sites and does not reflect the site’s recent increases in recreational uses and adjacent coastal development . TherefoCulebra Island is located between the eastern Greater Antilles and the northern Lesser Antilles of the Caribbean Sea, approximately 27 km east of PR. It encompasses a total area of 2,728 hectares and a cluster of 26 cays. The local climate is greatly influenced by the seasonal Atlantic tropical storms between June and November. This is the season in which most of the 1,120.3 mm of annual rainfall is received . Culebra does not have permanent rivers or aquifers, which has historically reduced coastal sedimentation. However, it does exhibit ephemeral streams and highly erodible clay soils, which can result in high sediment loading to critical coastal habitats . The wat2) is frequently used by recreationists, which facilitated observations from the reef users and focused efforts on the most accessible and potentially threatened reefs.Flamenco Bay was chosen as the study location due to its diverse reef habitats and recreational popularity. It is a horse-shoe shaped bay facing north, open to the predominant swell direction and therefore a dynamic and heterogenous coastline. While the eastern area is characterized by a fringing reef formation, the center and western sections are composed of sand, algae turfs, and beach rock formations. The site has distinct reef zones, including a barrier reef, a spur and groove back-reef, and a deep channel accompanied by patches of shoreline reefs. All zones exhibit a mixture of linear reefs, aggregate reefs, pavement, and rubble seafloor, with differing benthic heterogeneity. The bay has an extensive hard coral cover, but algae dominate the biological cover on patchy structures, suggesting that reef flats, back reefs, and shoreline fringing reefs are in declining ecological health . The stuA total of eight distinct reef locations were sampled across the bay during July–September 2017. These reef locations were selected through stratified sampling according to homogenous features in benthic maps. Locations were chosen not just for their inherent spatial variation but for their similarity in aggregate reef geomorphology and varying degrees of rugosity. Benthic ecological parameters were measured at these reef locations, each composed of five, 10 m length replicate photo-transects, for a total of 40 transects across the study area . This le2 quadrats were laid on top of the measuring tape at two-meter intervals and photographed vertically with a camera, for a total of six images per transect. Posteriorly, 48 regular grid points over these photos were used to identify the benthic structure inside each quadrat to the species level, including the percent of live scleractinian, hydrocoral, octocoral, sponge, macroalgae, algal turf, crustose coralline algae (CCA), erect calcareous algae (ECA), cyanobacteria cover, plus the percent cover of sand, pavement or rubble. Several guides were used to identify species  across all locations. Benthic cover plots were created in the package ggplot2 in “R” statistical software , with location, distance from the shoreline, recreation index, rugosity index and ibutions . Two-wayibutions  to undeributions .A modified version of the Inverse Distance Weighting (IDW) spatial interpolation was used on 12 environmental variables to estimate unknown values based on sampled points and illustrate reef hotspots for targeted conservation strategies . This waLastly, a coral reef resilience index (CRRI) was applied to each location to summarize results to managers. The CRRI is composed of thirteen benthic variables grouped into coral, threatened species, and algal components. It was developed to enable a quantitative comparison from a single survey event between different reef types and an indication of the trend in health rather than only the current state of the reef. Therefore, it is a rapid assessment method to survey novel coral reef assemblages and a useful tool for managers and decision-makers for both small-and large-scale monitoring .Without taking into consideration spatial variations, macroalgae exhibited the highest mean live benthic cover (22.8% ± 3.0% CI), while the combination of live scleractinian and hydrocoral cover (16.7% ± 3.1% CI) ranked as the second most widespread live cover type. See Despite being selected for their similarities in geomorphological structure, transect-averaged reef locations varied in benthic composition . ScleracD. antillarum densities, did not vary remarkably across locations (0.1–0.3 m−2), except for back-reef E, where the population density reached 0.75 m−2. Furthermore, hard coral recruit densities did not surpass 2.0 m−2, except for offshore location G (2.7 ± 1.0 m−2). See Herbivory, in the form of the long-spine urchin F = 5.0895; p = 0.0007). A pair-wise test revealed significant relationships (p < 0.05) among reef locations. Specifically, inshore locations had higher rugosity than offshore zones , with notable differences (p < 0.05) between locations B and E, D and H, plus D and E.Rugosity was highest at nearshore locations B and D, with mean indexes of 1.7 and 1.8, respectively. Location B exhibited the distinct characteristic of deep crevasses running across the transect, which influenced this result. Meanwhile, low rugosity values were found mostly at offshore locations, notably front reefs G and H, and back reef E . A One-way PERMANOVA test indicated significant differences among some locations . A follow-up pair-wise test indicated that the only significance (p = 0.0330) was between the “critical” and “good” categories of this herbivory parameter. The largest variability in J’c was at C, due to the remnant dominance of Acropora palmata. Shannon’s diversity index (H’c) and the average taxonomic distances (Δ*) both varied significantly  across reef locations, suggesting the existence of coral phylogenetic diversity.Hard coral species richness was highest at offshore reefs F, G and H with mean values of 14.0 ± 3.3, 12.8 ± 3.9 and 8.8 ± 3.2, respectively. Backreef location E had the lowest richness 5.4 ± 2.9. Meanwhile, coral species evenness (J’c) was similar across all locations, ranging from 0.98 to 0.99 and without statistical differences in any factors except the D. antillarum, and distance from the shoreline (p = 0.0005), implying the adequacy of continuing to use S as an intuitive biodiversity measurement (p < 0.05). Variations in S were significant when considering interactions between location and the frequency of aquatic recreation (p = 0.0007). Moreover, H’c also was significantly different among reef locations (p = 0.0006), while all other factors were not. Location and recreation index (p = 0.0008), plus location and D. antillarum index (p = 0.0249) were also significant when tested against H’c.Species richness (S) of scleractinian corals was not significantly influenced by rugosity, horeline . Howeversurement . Pair-wiO. annularis, while other inshore locations, such as A and B, variability was explained more by brown macroalgae Padina spp. and Dictyota spp. Meanwhile, variation in offshore locations was mostly explained by P. strigosa, Gorgonia flabellum, and different CCA species. When interactions between factors were analyzed for the whole benthic community, all interactions with distance, location, rugosity, recreation and D. antillarum were statistically significant , which were significant among locations (p = 0.001) and distance to the shoreline (p = 0.0131). Furthermore, Metric Dimensional Scaling (MDS) plots of fourth root-transformed species abundances in a Bray–Curtis dissimilarity space of benthic averages showed how all reef locations were likely (95% CI) different from each other . The recreation index yielded significant relationships with benthic community structure (p = 0.0001) across all categories. The D. antillarum index also showed significant relationships with benthic community structure (p = 0.0024). Almost all reef locations fell under the “critical” and “poor” categories, and the few “fair” and “good” transects were clustered around offshore locations . The interaction between distance and recreation was also significant (p = 0.0001). This sustains that recreation exhibited a diminishing frequency gradient the farther the reef is from the shore, while coral cover increased the farther the reef is from shore. Pair-wise tests indicated that the significant relationship between live coral existed only when interacting with “low x moderate” recreational use (p = 0.0002). Similarly, coral biodiversity varied significantly (p = 0.0002) in response to coral diseases . A pair-wise follow-up test confirmed 12 distinct location combinations had statistically different (p < 0.05) macroalgae covers. The brown macroalga Dictyota spp. was abundant in all locations, also evidenced through a PCO explaining 55.4% of the variance in benthic cover (p = 0.0229). Pair-wise tests across 12 distinct location combinations confirmed that macroalgae were highest in nearshore reefs. The dominance of CCA, especially (Peyssonnelia spp. and P. pachydermum) on offshore reefs was evident through PCO analysis and contrasted to the clustered abundance of macroalgae community in the nearshore reefs .Cyanobacteria were most abundant at inshore reef B, near the recreationist swimmer’s area, followed by offshore reef H. Variances in rugosity and p = 0.000005 at a distance of 24.5 m), which indicated a very high positive spatial dependency and validated the appropriateness of performing IDW on tightly spaced samples over similar depths  were smaller than those expected by a random dispersion (53.1 units), which generated a nearest neighbor ratio of 0.225 and indicated a clustering tendency. The global autocorrelation quantified through Moran’s I covariance index equaled 0.923 , implies changes in the benthic community in comparison to historical assemblages. Indeed, since 1986 live coral cover has significantly decreased while macroalgae cover has significantly increased in two reefs in the vicinity of contemporary localities C and D of Flamenco Bay  densities were observed in back-reef E, which is consistent with previous findings associating higher populations to protected back-reefs , below their capacity sustain critical herbivory functions (2 in 2016), Flamenco’s low densities are more comparable to more heavily impacted urban locations in north-eastern Puerto Rico  and sedimentation from unsustainable land-use practices. Different types of recreational activities occur across reef locations, with the highest frequency taking place at nearshore reefs easily accessible to individual snorkelers and where commercial charters provide un-guided snorkeling tours. Statistical analysis reveals that the frequency of aquatic recreational activity is correlated with significant variances in benthic community structure, specifically rises in macroalgae and cyanobacteria, plus decreased coral cover. Although the reef’s degradation has not been causally linked to recreationists, we recommend minimizing this human stressor by establishing reef-specific recreational carrying capacities to both individual recreationists and touristic businesses , with a special focus to limiting the density of snorkelers. Additionally, efforts to educate best behavior practices in and around the reefs, such as signs and symbolic pledges when renting snorkeling and camping space, would minimize physical harm to corals and should be implemented by both businesses and the local management agency (Authority for the Conservation and Development of Culebra (ACDEC)). Since coastal management is often more efficient when considering the behaviors and perceptions of stakeholders , furtherO. annularis and A. cervicornis at reef C), overlap with the areas of high recreational densities and with areas close to recurrent turbid runoff outflows. Sediment particles inhibit larvae settlement and reduce coral diversity  % Cover of scleractinian and hydrocoral species between distance zones and (B) % Scleractinian cover among localities. Offshore locations exhibit higher coral cover, but inshore locality C stands out for its scleractinian dominance.Click here for additional data file.10.7717/peerj.10080/supp-2Supplemental Information 2Arrow bars represent the 95% confidence intervals. Colors represent different benthic components, grouped by similar characteristics.Click here for additional data file.10.7717/peerj.10080/supp-3Supplemental Information 3Diadema antillarum) population densities, used very as a measure of reef herbivory, based on abundance counts every 20 m2 for each transect. (B) Mean sclerectinian coral recruit densities based on 0.5 m2 quadrats.Arrow bars represent the 95% confidence intervals for five transects. (A) Mean spiny sea-urchin  Species richness, highest at offshore sites. (B) Shannon diversity index (H’c), (C) Species evenness index (J’c) (D) Average taxonomic distinctness (Δ*).Arrow bars represent the 95% confidence intervals for five transects. Click here for additional data file.10.7717/peerj.10080/supp-5Supplemental Information 5(A) Distance from the shoreline. (B) Spatial variation of the relative recreational intensity index.Click here for additional data file.10.7717/peerj.10080/supp-6Supplemental Information 6Pseudodiploria strigosa reef-building coral species. (B) Orbicella annularis reef-building coral species. (C) Porites astreoides, a weedy coral species. (D) Dictyota spp., a common brown macroalgae genus in the Caribbean.Values represent fourth root transformed counts. (A) Click here for additional data file.10.7717/peerj.10080/supp-7Supplemental Information 7(A) Macroalgae % cover, including red, green and brown taxon showing high abundance across the study area, especially inshore locations. (B) Less abundant cyanobacteria % cover in comparison to macroalgae, but still notably present in offshore location H and inshore location B.Click here for additional data file.10.7717/peerj.10080/supp-8Supplemental Information 8Peyssonnelia spp. (B) Porolithon pachydermum.(A) Click here for additional data file.10.7717/peerj.10080/supp-9Supplemental Information 9n = 21), differing from the photo-cuadrat sampling in 2017. Arrow bars represent the 95% confidence intervals. Localities 1 and 2 correspond to the vicinity of comptemporary localitites C and D, respectively.(A) Percent live cover of sclearactinian corals. (B) Percent macroalgae cover. Percent cover were based on measurements based on point counts every 0.5 m across a 10 m transect , while the combination of live scleractinian and hydrocoral cover (16.7% ± 3.1%) ranked as the second most widespread cover type. This was closely followed by the presence of CCA (16.0% ± 3.4%) and later by the inorganic combination of sand, pavement and rubble (12.3% ± 3.9%), but with high variability. Octocorals (10.8% ± 2.1%) and algal turf (6.8% ± 1.7%) occupied a middle rank. However, Click here for additional data file.10.7717/peerj.10080/supp-13Supplemental Information 13Click here for additional data file.10.7717/peerj.10080/supp-14Supplemental Information 14Click here for additional data file.10.7717/peerj.10080/supp-15Supplemental Information 15The default weighting exponential (α) for IDW interpolations is 2. However, we did not assume that the distance-decay relationship is constant over space, and adjusted this power value according to the nearest neighbor statistic in order to increase spatial predictive accuracy in our clustered samples, as recommended by Lu et al. (2008). Therefore, the α was adjusted to optimize the cross validation of predicted values at unknown location by both maximining the regression function between expected and observed values and minimizing its root mean squared error (RMSE).Click here for additional data file.10.7717/peerj.10080/supp-16Supplemental Information 16A. palmata, A. cervicornis, O. annularis, O. faveolata) and Algal Index .The CRRI is composed of fifteen indicators grouped in to the Coral Index , threatened species , has an acceptable stress level, lower than the 2D explanation (0.27).Click here for additional data file.10.7717/peerj.10080/supp-18Supplemental Information 18Click here for additional data file.10.7717/peerj.10080/supp-19Supplemental Information 19Click here for additional data file.