Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.05.08.443047

AutoVEM2: a flexible automated tool to analyze candidate key mutations and epidemic trends for virus

Xi, B.·Li, S.·Liu, W.·Jiang, D.·Bai, Y.·Qu, Y.·Lon, J. R.·Huang, L.·Du, H.
View original source ↗Export metadata ↓

Abstract

In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot module, which can be used modularly or as a whole for any virus, as long as the corresponding reference genome is provided. Therefore, its much more flexible than AutoVEM. Here, we analyzed three existing viruses by AutoVEM2, including SARS-CoV-2, HBV and HPV-16, to show the functions, effectiveness and flexibility of AutoVEM2. We found that the N501Y locus was almost completely linked to the other 16 loci in SARS-CoV-2 genomes from the UK and Europe. Among the 17 loci, 5 loci were on the S protein and all of the five mutations cause amino acid changes, which may influence the epidemic traits of SARS-CoV-2. And some candidate key mutations of HBV and HPV-16, including T350G of HPV-16 and C659T of HBV, were detected. In brief, we developed a flexible automated tool to analyze candidate key mutations and epidemic trends for any virus, which would become a standard process for virus analysis based on genome sequences in the future. HighlightsO_LIAn automatic tool to quickly analyze candidate key mutations and epidemic trends for any virus was developed. C_LIO_LIOur integrated analysis method and tool could become a standard process for virus mutation and epidemic trend analysis based on genome sequences in the future. C_LIO_LIN501Y with the other 16 highly linked mutation sites of SARS-CoV-2 in the UK and Europe were further confirmed, and some valuable mutation sites of HBV and HPV-16 were detected. C_LI

Source connections

Explore related subjects

genomicsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Xi, B., Li, S., Liu, W., Jiang, D., Bai, Y., Qu, Y., Lon, J. R., Huang, L., Du, H.. 2021-05-09. AutoVEM2: a flexible automated tool to analyze candidate key mutations and epidemic trends for virus. https://doi.org/10.1101/2021.05.08.443047

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

SPACE-Tag Enables High-Throughput Spatial Chromatin Profiling With CUT&Tag

Spatial epigenomics maps chromatin states within intact tissues, yet current methods remain limited by accessibility and scale. We developed SPACE-Tag, a spatial CUT&Tag framework that converts epigenetic marks-associated DNA into polyadenylated RNA through T7 based linear amplification, enabling direct integration with standard spatial transcriptomic workflows. Applied to the mouse brain, SPACETag resolved activating and repressive chromatin landscapes, recovered region-specific gene regulatory programs across anatomical domains, and showed strong correlation with existing bulk and single cell reference data. We generated an integrated multimodal atlas of the aging mouse brain, profiling five histone modifications and the transcriptome in parallel across the adult lifespan to establish the largest spatial multimodal dataset to date. This analysis uncovered sharp regional divergence with aging in the brain: fiber tracts showed widespread transcriptional downregulation, often without nearby chromatin state transitions, whereas the isocortex showed coordinated chromatin transcriptome changes, including an H3K4me1 peak module that increased with age, was enriched at super-enhancers and linked to upregulation of neuronal plasticity regulators. These findings highlight the power of multimodal and high throughput spatial genomics in uncovering the divergent regulatory logic that governs tissue-specific vulnerability and resilience in the aging brain.

genomics↗
bioRxiv2026

Long-read DNA sequencing reveals global hypomethylation and focal hypermethylation in SDHx-deficient pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas (PPGL) are highly heritable neuroendocrine tumors of the autonomic ganglia. Genomic DNA in most cancer cells is hypomethylated. However, DNA in PPGLs secondary to mutations in succinate dehydrogenase complex (SDHx) genes is reportedly hypermethylated due to succinate-mediated inhibition of DNA demethylases. We used nanopore long-read sequencing to characterize the methylome of tumor and white blood cell DNA from SDHx and non-SDHx PPGL patients, alongside normal adrenal medulla. We find that both SDHx and non-SDHx PPGLs are globally hypomethylated, particularly at centromeres. In normal adrenal medulla, CpG islands marked by H3K4 methylation are hypomethylated, whereas CpG islands lacking H3K4 methylation are hypermethylated. In SDHx-related PPGL, some H3K4me-marked CpG islands are hypermethylated, but most are not. We propose that DNA methylation in SDHx-related PPGL reflects the global hypomethylation generally observed in tumors, partly offset by succinate-mediated inhibition of TET DNA demethylases. Opposing effects of succinate may alter the balance between DNA methylation (indirect inhibition of the DNMT3A/B DNA methylases via inhibition of H3K4me demethylases) and DNA demethylation (inhibition of TET DNA demethylases) at active CpG islands.

genomics↗
bioRxiv2026

High piRNA abundance is a hallmark of evolutionarily persistent piRNA-producing loci.

PIWI-interacting RNAs (piRNAs) silence transposons in the germline, and the loci that produce them diverge rapidly between species. Yet, some loci retain both their genomic location and their piRNA production across large evolutionary distances, and the basis for this conservation is unclear. To identify the features that distinguish these persistent loci, we compared piRNA production at orthologous loci in three closely related mouse species, contrasting loci that produce piRNAs in all three species with those that do so in only one. Transposon content and UTR features, often linked to piRNA production, did not distinguish the two groups. Transcription extending beyond gene ends (readthrough) was more frequent at conserved loci, but did not explain conservation once the amount of piRNAs produced was taken into account. Instead, we found that the conserved loci are those that produce the most piRNAs. The same association holds true in human and two other primate species. We speculate that most piRNAs expressed in testis are tolerated molecular noise, and that only the highly expressed minority are likely to be functional.

genomics↗