Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, with rapid progression and a poor prognosis. More and more studies have shown that there are small open reading frames (sORFs) on the molecular sequences of a large number of non-coding RNAs (ncRNAs), which can encode conserved peptides that play an important role in controlling the occurrence and development of HCC. This article introduces the discovery, prediction, and validation methods of ncRNA-encoding polypeptides and reviews its research progress, with the aim of providing new targets and ideas for early-stage diagnosis, targeted therapy, and prognosis assessment of HCC.
肝细胞癌（HCC）是最常见的恶性肿瘤之一，其进展迅速，预后不良。越来越多的研究表明大量非编码RNA（ncRNA）的分子序列上存在小的开放阅读框（sORFs），这些sORFs可编码保守的多肽，而这些保守多肽在调控HCC的发生、发展中起着重要作用。现介绍ncRNA编码多肽的发现、预测与验证方法，并对其在HCC中的研究进展进行综述，以期为HCC的早期诊断、靶向治疗以及预后评估等方面提供新的靶点和思路。.

The identification and function determination of long non-coding RNAs (lncRNAs) can help to better understand the transcriptional regulation in both normal development and disease pathology, thereby demanding methods to distinguish them from protein-coding (pcRNAs) after obtaining sequencing data. Many algorithms based on the statistical, structural, physical, and chemical properties of the sequences have been developed for evaluating the coding potential of RNA to distinguish them. In order to design common features that do not rely on hyperparameter tuning and optimization and are evaluated accurately, we designed a series of features from the effects of open reading frames (ORFs) on their mutual interactions and with the electrical intensity of sequence sites to further improve the screening accuracy. Finally, the single model constructed from our designed features meets the strong classifier criteria, where the accuracy is between 82% and 89%, and the prediction accuracy of the model constructed after combining the auxiliary features equal to or exceed some best classification tools. Moreover, our method does not require special hyper-parameter tuning operations and is species insensitive compared to other methods, which means this method can be easily applied to a wide range of species. Also, we find some correlations between the features, which provides some reference for follow-up studies.

Long non-coding RNAs (lncRNAs), which are RNA transcripts exceeding 200 nucleotides were believed to lack any protein-coding capacity. But advancements in -omics technology have revealed that some lncRNAs have small open reading frames (sORFs) that can be translated by ribosomes to encode peptides, some of which have important biological functions. These encoded peptides subserve important biological functions by interacting with their targets to modulate transcriptional or signalling axes, thereby enhancing or suppressing cardiovascular disease (CVD) occurrence and progression. In this review, we summarize what is known about the research strategy of lncRNA-encoded peptides, mainly comprising predictive websites/tools and experimental methods that have been widely used for prediction, identification, and validation. More importantly, we have compiled a list of lncRNA- encoded peptides, with a focus on those that play significant roles in cardiovascular physiology and pathology, including ENSRNOT (RNO)-sORF6/RNO-sORF7/RNO-sORF8, dwarf open reading frame (DOWRF), myoregulin (NLN), etc. Additionally, we have outlined the functions and mechanisms of these peptides in cardiovascular physiology and pathology, such as cardiomyocyte hypertrophy, myocardial contraction, myocardial infarction, and vascular remodelling. Finally, an overview of the existing challenges and potential future developments in the realm of lncRNA-encoded peptides was provided, with consideration given to prospective avenues for further research. Given that many lncRNA-encoded peptides have not been functionally annotated yet, their application in CVD diagnosis and treatment still requires further research.

Comparative analysis of the genomic sequences of multiple hepatitis E virus (HEV) isolates has revealed extensive genomic diversity among them. Recently, a variety of genetically distinct HEV variants have also been isolated and identified from large numbers of animal species, including birds, rabbits, rats, ferrets, bats, cutthroat trout, and camels, among others. Furthermore, it has been reported that recombination in HEV genomes takes place in animals and in human patients. Also, chronic HEV infection in immunocompromised individuals has revealed the presence of viral strains carrying insertions from human genes. This paper reviews current knowledge on the genomic variability and evolution of HEV.

Fowl adenovirus serotype 4 (FAdV-4) is a double-stranded DNA virus that mainly infects broiler chickens and has caused huge economic losses to the poultry industry. Recently, an FAdV-4 strain, SDLC202009, the causative pathogen of hydropericardium-hepatitis syndrome (HHS) in Liaocheng, Shandong, was isolated from commercial laying hens and propagated in specific pathogen free SPF chicken embryos. Pathogenicity studies showed that SDLC202009 could infect SPF chicken embryos and chickens, with a mortality rate of 100%. The complete genome was sequenced, and phylogenetic analysis showed that SDLC202009 belonged to the FAdV-4 cluster, with a genome length of 43, 077 bp. The SDLC202009 had 99.9% identity with the JSJ13 and SD1601, which were recently isolated in China. Compared to the recently isolated strain in China, SDLC202009 had deleted open reading frame 19 (ORF19), ORF27, ORF48, and ORF0. SDLC202009 harbored amino acid site mutations in the main structural proteins hexon, fiber1, and fiber2 similar with those in highly pathogenic strains. Furthermore, SDLC202009 showed unique mutations in hexon A571P, fiber1 E216K, and fiber2 N98K. In summary, our findings provide theoretical support for prevention and control of the HHS.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a high mutation rate and many variants have emerged in the last 2 years, including Alpha, Beta, Delta, Gamma and Omicron. Studies showed that the host-genome similarity (HGS) of SARS-CoV-2 is higher than SARS-CoV and the HGS of open reading frame (ORF) in coronavirus genome is closely related to suppression of innate immunity. Many works have shown that ORF 6 and ORF 8 of SARS-CoV-2 play an important role in suppressing IFN-β signaling pathway in vivo. However, the relation between HGS and the adaption of SARS-CoV-2 variants is still not clear. This work investigates HGS of SARS-CoV-2 variants based on a dataset containing more than 40,000 viral genomes. The relation between HGS of viral ORFs and the suppression of antivirus response is studied. The results show that ORF 7b, ORF 6 and ORF 8 are the top 3 genes with the highest HGS. In the past 2 years, the HGS values of ORF 8 and ORF 7B of SARS-CoV-2 have increased greatly. A remarkable correlation is discovered between HGS and inhibition of antivirus response of immune system, which suggests that the similarity between coronavirus and host gnome may be an indicator of the suppression of innate immunity. Among the five variants (Alpha, Beta, Delta, Gamma and Omicron), Delta has the highest HGS and Omicron has the lowest HGS. This finding implies that the high HGS in Delta variant may indicate further suppression of host innate immunity. However, the relatively low HGS of Omicron is still a puzzle. By comparing the mutations in genomes of Alpha, Delta and Omicron variants, a commonly shared mutation ACT > ATT is identified in high-HGS strain populations. The high HGS mutations among the three variants are quite different. This finding strongly suggests that mutations in high HGS strains are different in different variants. Only a few common mutations survive, which may play important role in improving the adaptability of SARS-CoV-2. However, the mechanism for how the mutations help SARS-CoV-2 escape immunity is still unclear. HGS analysis is a new method to study virus−host interaction and may provide a way to understand the rapid mutation and adaption of SARS-CoV-2.

Accurate prediction of open reading frames (ORFs) is important for studying and using genome sequences. Ribosomes move along mRNA strands with a step of three nucleotides and datasets carrying this information can be used to predict ORFs. The ribosome-protected footprints (RPFs) feature a significant 3-nt periodicity on mRNAs and are powerful in predicting translating ORFs, including small ORFs (sORFs), but the application of RPFs is limited because they are too short to be accurately mapped in complex genomes. In this study, we found a significant 3-nt periodicity in the datasets of populational genomic variants in coding sequences, in which the nucleotide diversity increases every three nucleotides. We suggest that this feature can be used to predict ORFs and develop the Python package \'OrfPP\', which recovers ~83% of the annotated ORFs in the tested genomes on average, independent of the population sizes and the complexity of the genomes. The novel ORFs, including sORFs, identified from single-nucleotide polymorphisms are supported by protein mass spectrometry evidence comparable to that of the annotated ORFs. The application of OrfPP to tetraploid cotton and hexaploid wheat genomes successfully identified 76.17% and 87.43% of the annotated ORFs in the genomes, respectively, as well as 4704 sORFs, including 1182 upstream and 2110 downstream ORFs in cotton and 5025 sORFs, including 232 upstream and 234 downstream ORFs in wheat. Overall, we propose an alternative and supplementary approach for ORF prediction that can extend the studies of sORFs to more complex genomes.

Increasing evidence has indicated that long noncoding RNAs (lncRNAs) play various important roles in the development of cancers. The widespread applications of ribosome profiling and ribosome nascent chain complex sequencing revealed that some short open reading frames of lncRNAs have micropeptide-coding potential. The resulting micropeptides have been shown to participate in N6-methyladenosine modification, tumor angiogenesis, cancer metabolism, and signal transduction. This review summarizes current information regarding the reported roles of lncRNA-encoded micropeptides in cancer, and explores the potential clinical value of these micropeptides in the development of anti-cancer drugs and prognostic tumor biomarkers.

The intact open reading frame (ORF) of foot-and-mouth disease virus (FMDV) Asia I/XJ strain was amplified by RT-PCR and inserted into the transfer vector pVL1393 to generate plasmid pVL-ORF. Bm-N cells were transfected with pVL-ORF and linearized Bm-BacPAK6 DNA, and the recombinant silkworm baculovirus Bm-ORF containing the full ORF of FMDV was obtained. The results of indirect immunofluorescence assay (IFA) showed that Bm-ORF could be expressed efficiently in Bm-N cell. After inoculating the early 5th instar larvae of silkworm, the polyprotein of FMDV could be detected by sandwich ELISA and empty capsid-like particles could be observed under the electron microscope. Expression products from silkworm were used as the antigen to immunize the cattle. The specific antibody was induced in all vaccinated animals. The immunized cattle were challenged with the virulent FMDV Asia I/XJ strain, two of the four cattle were completely protected and clinical symptoms were alleviated and delayed in the others. The results suggest that this strategy might be used to develop the new subunit FMDV vaccine.

BACKGROUND: Sacbrood virus (SBV) is one of the most pathogenic honeybee viruses that exhibits host specificity and regional variations. The SBV strains that infect the Chinese honeybee Apis cerana are called Chinese SBVs (CSBVs).
METHODS: In this study, a CSBV strain named AmCSBV-SDLY-2016 (GenBank accession No. MG733283) infecting A. mellifera was identified by electron microscopy, its protein composition was analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis and agar gel immunodiffusion assay, and its nucleotide sequence was identified using a series of reverse-transcription polymerase chain reaction fragments of AmCSBV-SDLY-2016 generated using SBV/CSBV-specific primers. To investigate phylogenetic relationships of the CSBV isolates, a phylogenetic tree of the complete open reading frames (ORF) of the CSBV sequences was constructed using MEGA 6.0; then, the similarity and recombination events among the isolated CSBV strains were analyzed using SimPlot and RDP4 software, respectively.
RESULTS: Sequencing results revealed the complete 8,794-nucleotide long complete genomic RNA of the strain, with a single large ORF (189-8,717) encoding 2,843 amino acids. Comparison of the deduced amino acid sequence with the SBV/CSBV reference sequences deposited in the GenBank database identified helicase, protease, and RNA-dependent RNA polymerase domains; the structural genes were located at the 5\' end, whereas the non-structural genes were found at the 3\' end. Multiple sequence alignment showed that AmCSBV-SDLY-2016 had a 17-amino acid (aa) and a single aa deletion at positions 711-729 and 2,128, respectively, as compared with CSBV-GD-2002, and a 16-aa deletion (positions 711-713 and 715-728) as compared with AmSBV-UK-2000. However, AmCSBV-SDLY-2016 was similar to the CSBV-JLCBS-2014 strain, which infects A. cerana. AmCSBV-SDLY-2016 ORF shared 92.4-97.1% identity with the genomes of other CSBV strains (94.5-97.7% identity for deduced amino acids). AmCSBV-SDLY-2016 was least similar (89.5-90.4% identity) to other SBVs but showed maximum similarity with the previously reported CSBV-FZ-2014 strain. The phylogenetic tree constructed from AmCSBV-SDLY-2016 and 43 previously reported SBV/CSBV sequences indicated that SBV/CSBV strains clustered according to the host species and country of origin; AmCSBV-SDLY-2016 clustered with other previously reported Chinese and Asian strains (AC genotype SBV, as these strains originated from A. cerana) but was separate from the SBV genomes originating from Europe (AM genotype SBV, originating from A. mellifera). A SimPlot graph of SBV genomes confirmed the high variability, especially between the AC genotype SBV and AM genotype SBV. This genomic diversity may reflect the adaptation of SBV to specific hosts, ability of CSBV to cross the species barrier, and the spatial distances that separate CSBVs from other SBVs.