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Background The detection of physiologically relevant protein isoforms encoded by the human genome is critical to biomedicine. Mass spectrometry (MS)-based proteomics is the preeminent method for protein detection, but isoform-resolved proteomic analysis relies on accurate reference databases that match the sample; neither a subset nor a superset database is ideal. Long-read RNA sequencing (e.g., PacBio or Oxford Nanopore) provides full-length transcripts which can be used to predict full-length protein isoforms. Results We describe here a long-read proteogenomics approach for integrating sample-matched long-read RNA-seq and MS-based proteomics data to enhance isoform characterization. We introduce a classification scheme for protein isoforms, discover novel protein isoforms, and present the first protein inference algorithm for the direct incorporation of long-read transcriptome data to enable detection of protein isoforms previously intractable to MS-based detection. We have released an open-source Nextflow pipeline that integrates long-read sequencing in a proteomic workflow for isoform-resolved analysis. Conclusions Our work suggests that the incorporation of long-read sequencing and proteomic data can facilitate improved characterization of human protein isoform diversity. Our first-generation pipeline provides a strong foundation for future development of long-read proteogenomics and its adoption for both basic and translational research.

Background RNA-seq has brought forth significant discoveries regarding aberrations in RNA processing, implicating these RNA variants in a variety of diseases. Aberrant splicing and single nucleotide variants (SNVs) in RNA have been demonstrated to alter transcript stability, localization, and function. In particular, the upregulation of ADAR, an enzyme that mediates adenosine-to-inosine editing, has been previously linked to an increase in the invasiveness of lung adenocarcinoma cells and associated with splicing regulation. Despite the functional importance of studying splicing and SNVs, the use of short-read RNA-seq has limited the community’s ability to interrogate both forms of RNA variation simultaneously. Results We employ long-read sequencing technology to obtain full-length transcript sequences, elucidating cis-effects of variants on splicing changes at a single molecule level. We develop a computational workflow that augments FLAIR, a tool that calls isoform models expressed in long-read data, to integrate RNA variant calls with the associated isoforms that bear them. We generate nanopore data with high sequence accuracy from H1975 lung adenocarcinoma cells with and without knockdown of ADAR . We apply our workflow to identify key inosine isoform associations to help clarify the prominence of ADAR in tumorigenesis. Conclusions Ultimately, we find that a long-read approach provides valuable insight toward characterizing the relationship between RNA variants and splicing patterns.

Background Functional genomic analyses rely on high-quality genome assemblies and annotations. Highly contiguous genome assemblies have become available for a variety of species, but accurate and complete annotation of gene models, inclusive of alternative splice isoforms and transcription start and termination sites, remains difficult with traditional approaches. Results Here, we utilized full-length isoform sequencing (Iso-Seq), a long-read RNA sequencing technology, to obtain a comprehensive annotation of the transcriptome of the ant Harpegnathos saltator . The improved genome annotations include additional splice isoforms and extended 3′ untranslated regions for more than 4000 genes. Reanalysis of RNA-seq experiments using these annotations revealed several genes with caste-specific differential expression and tissue- or caste-specific splicing patterns that were missed in previous analyses. The extended 3′ untranslated regions afforded great improvements in the analysis of existing single-cell RNA-seq data, resulting in the recovery of the transcriptomes of 18% more cells. The deeper single-cell transcriptomes obtained with these new annotations allowed us to identify additional markers for several cell types in the ant brain, as well as genes differentially expressed across castes in specific cell types. Conclusions Our results demonstrate that Iso-Seq is an efficient and effective approach to improve genome annotations and maximize the amount of information that can be obtained from existing and future genomic datasets in Harpegnathos and other organisms.

Alternative splicing is a key regulator of immune regulation by enabling rapid and context-specific responses. However, the role of splicing regulators such as CDC-like kinase 1 (CLK1) in monocyte biology remains poorly defined. Here, we identify and characterize distinct CLK1-splice isoforms in human CD14 monocytes using long-read RNA sequencing. In resting monocytes, we observe predominant expression of a truncated isoform lacking exon 4 (CLK1Δ4), which undergoes nonsense-mediated decay resulting in minimal protein output. Lipopolysaccharide (LPS) stimulation induces a shift toward the full-length isoform (CLK1+4), associated with increased transcript stability and protein expression. This splicing switch was confirmed by RT-qPCR, short-read RNA sequencing, and Western blot analysis. Pharmacological inhibition of CLK1 selectively reduced TNFα production without affecting cell viability, implicating that the isoform shift enhances pro-inflammatory signaling. These findings uncover a stimulus-dependent splicing mechanism that modulates monocyte activation through differential CLK1 isoform expression and suggest a potential therapeutic avenue by targeting splicing regulators in immune-related disease with an established role of activated monocytes.

Both cis - and trans -regulation could cause differential expression between the parental alleles in diploid species that might have broad biological implications. Due to the relatively distant genetic divergence between cattle and yak, as well as their differential adaptation to high-altitude environments, we investigated genome-wide allelic differential expression (ADE) in their F1 hybrids using Nanopore long-read RNA-seq technology. From adult F1 hybrids raised in high-altitude, ten lung and liver tissues were individually sequenced for producing 31.6 M full-length transcript sequences. Mapping against autosomal homologous regions between cattle and yak, we detected 17,744 and 14,542 protein-encoding genes expressed in lung and liver tissues, respectively. According to the parental assignments of transcript sequences, a total of 3,381 genes were detected to show ADE in at least one sample. There were 186 genes showing ubiquitous ADE in all the studied animals, and among them 135 and 37 genes had consistent higher expression of yak and cattle alleles, respectively. Functional analyses revealed that the genes with favoring expression of yak alleles have been involved in the biological progresses related with hypoxia adaptation and immune response. In contrast, the genes with favoring expression of cattle alleles have been enriched into different biological progresses, such as secretion of endocrine hormones and lipid metabolism. Our results would support unequal contribution of parental genes to environmental adaptation in the F1 hybrids of cattle and yak.

plays a crucial role in mammalian spermatogenesis. Here, we integrated single-molecule long-read and short-read sequencing to comprehensively examine expression patterns in adult Baoshan pig (BS) testes. We identified the most important transcript ENSSSCT00000000120 of , obtaining its full-length coding sequence (CDS) spanning 1254 bp. Gene structure analysis located on pig chromosome 5 with 14 exons. Protein structure analysis reflected that PICK1 consisted of 417 amino acids containing two conserved domains, PDZ and BAR_PICK1. Phylogenetic analysis underscored the evolutionary conservation and homology of PICK1 across different mammalian species. Evaluation of protein interaction network, KEGG, and GO pathways implied that interacted with 50 proteins, predominantly involved in glutamatergic synapses, amphetamine addiction, neuroactive ligand-receptor interactions, dopaminergic synapses, and synaptic vesicle recycling, and PICK1 exhibited significant correlation with DLG4 and TBC1D20. Functional annotation identified that PICK1 was involved in 9 GOs, including seven cellular components and two molecular functions. ceRNA network analysis suggested BS was regulated by seven miRNA targets. Moreover, qPCR expression analysis across 15 tissues highlighted that was highly expressed in the bulbourethral gland and testis. Subcellular localization analysis in ST (Swine Tesits) cells demonstrated that PICK1 significantly localized within the cytoplasm. Overall, our findings shed new light on 's role in BS reproduction, providing a foundation for further functional studies of .

The broad application of single-cell RNA profiling in plants has been hindered by the prerequisite of protoplasting that requires digesting the cell walls from different types of plant tissues. Here, we present a protoplasting-free approach, flsnRNA-seq, for large-scale full-length RNA profiling at a single-nucleus level in plants using isolated nuclei. Combined with 10x Genomics and Nanopore long-read sequencing, we validate the robustness of this approach in Arabidopsis root cells and the developing endosperm. Sequencing results demonstrate that it allows for uncovering alternative splicing and polyadenylation-related RNA isoform information at the single-cell level, which facilitates characterizing cell identities.

RNA sequencing using the latest single-molecule sequencing instruments produces reads that are thousands of nucleotides long. The ability to assemble these long reads can greatly improve the sensitivity of long-read analyses. Here we present StringTie2, a reference-guided transcriptome assembler that works with both short and long reads. StringTie2 includes new methods to handle the high error rate of long reads and offers the ability to work with full-length super-reads assembled from short reads, which further improves the quality of short-read assemblies. StringTie2 is more accurate and faster and uses less memory than all comparable short-read and long-read analysis tools.

Recent research into structural variants (SVs) has established their importance to medicine and molecular biology, elucidating their role in various diseases, regulation of gene expression, ethnic diversity, and large-scale chromosome evolution—giving rise to the differences within populations and among species. Nevertheless, characterizing SVs and determining the optimal approach for a given experimental design remains a computational and scientific challenge. Multiple approaches have emerged to target various SV classes, zygosities, and size ranges. Here, we review these approaches with respect to their ability to infer SVs across the full spectrum of large, complex variations and present computational methods for each approach.

Transcription of eukaryotic genomes involves complex alternative processing of RNAs. Sequencing of full-length RNAs using long reads reveals the true complexity of processing. However, the relatively high error rates of long-read sequencing technologies can reduce the accuracy of intron identification. Here we apply alignment metrics and machine-learning-derived sequence information to filter spurious splice junctions from long-read alignments and use the remaining junctions to guide realignment in a two-pass approach. This method, available in the software package 2passtools ( https://github.com/bartongroup/2passtools ), improves the accuracy of spliced alignment and transcriptome assembly for species both with and without existing high-quality annotations.