Multi-omics analysis of SFTS virus infection in Rhipicephalus microplus cells reveals antiviral tick factors

The increasing prevalence of tick-borne arboviral infections worldwide necessitates advanced control strategies, particularly those targeting vectors, to mitigate the disease burden. However, the cellular interactions between arboviruses and ticks, especially for negative-strand RNA viruses, remain largely unexplored. Here, we employ a proteomics informed by transcriptomics approach to elucidate the cellular response of the Rhipicephalus microplus-derived BME/CTVM6 cell line to severe fever with thrombocytopenia syndrome virus (SFTSV) infection. We generate the de novo transcriptomes and proteomes of SFTSV- and mock-infected tick cells, identifying key host responses and regulatory pathways. Additionally, interactome analysis of the viral nucleoprotein (N) integrated host responses with viral replication and dsRNA-mediated gene silencing screen reveals two anti-SFTSV effectors: the N interacting RNA helicases DHX9 and UPF1. Collectively, our results provide insights into the antiviral responses of R. microplus vector cells and highlight critical SFTSV restriction factors, while enriching transcriptomic and proteomic resources for future research.

Genome-Wide Mining of lncRNAs Reveals Their Potential Regulatory Role in the Evolution of Viviparity

Reproduction in vertebrates usually involves egg-laying (oviparity) or live-bearing (viviparity). Oviparity is the ancestral trait from which viviparity has independently evolved more than 100 times in squamate reptiles. This transition involves a series of physiological and structural changes, including the degeneration of eggshell and the evolution of a placenta and differences in the temporal and spatial expression patterns of some functional genes that drive the structural transformation. Long non-coding RNAs (lncRNAs) play important roles in the regulation of gene expression, yet it remains unclear whether they participate in gene expression shifts during the transition from oviparity to viviparity, and if so how. Therefore, we employ deep mining to identify novel lncRNAs of a closely related oviparous-viviparous pair of lizards (Phrynocephalus przewalskii and P. vlangalii). We construct cis- and trans-regulatory networks between lncRNAs and target genes using the transcriptomic data of oviduct or uteri tissues across reproductive periods. Results show that lncRNAs that regulate eggshell gland developmental genes in the oviparous lizard are lost or less expressed in the viviparous lizard. A number of lncRNAs involved in the regulation of placental development and embryo attachment in viviparous species have no orthologs in oviparous species, and others show little or no expression. Accordingly, lncRNAs may play important regulatory roles in the physiological and structural changes in the transition from oviparity to viviparity. These results open doors to the further elucidation of genetic regulatory networks.

Comparative transcriptomes reveal insights into different host responses associated with Fusarium head blight resistance in wheat

Fusarium head blight (FHB) has become a major challenge in global wheat production, causing severe yield losses and exacerbating food safety concerns. In recent years, FHB-related research has focused on understanding resistance mechanisms, identifying genetic markers, and breeding resistant varieties to mitigate the disease's impact on yield and quality. This study comparatively analyzed transcriptome data from six wheat materials with differing levels of resistance following infection by Fusarium graminearum (F. graminearum). The results displayed that a total of 26,767 protein-coding genes and 2,463 long non-coding RNAs (lncRNAs) showed differential expression levels between normal and FHB treatment in at least one material. Among them, 14,130 FHB-responsive protein-coding genes and 913 lncRNAs were identified as material-specific, with functions related to the unique disease resistance mechanisms of the respective materials. Some of these genes have previously been reported to participate in physiological processes related to wheat FHB resistance, including Pm3-like resistance proteins, lactoylglutathione lyase, serine/threonine protein phosphatases, NBS-LRR resistance proteins, glutathione S-transferase (GST), and RPM1 resistance proteins. Additionally, we integrated FHB-responsive genes and lncRNAs with previously reported FHB QTLs, and constructed an interaction regulatory network between pathogen and host through a co-expression network. Based on this network, we identified five genes (one gene encoding glutathione synthetase and four genes encoding glutathione transferase) in the glutathione metabolism pathway, which overlapped with Fhb2 QTLs regions and exhibited material-specific expression patterns. These results will provide new insights into further dissecting of the functional genes and lncRNAs involved in wheat FHB resistance.

LMFE: A Novel Method for Predicting Plant LncRNA Based on Multi-Feature Fusion and Ensemble Learning

Background/Objectives: Long non-coding RNAs (lncRNAs) play a crucial regulatory role in plant trait expression and disease management, making their accurate prediction a key research focus for guiding biological experiments. While extensive studies have been conducted on animals and humans, plant lncRNA research remains relatively limited due to various challenges, such as data scarcity and genomic complexity. This study aims to bridge this gap by developing an effective computational method for predicting plant lncRNAs, specifically by classifying transcribed RNA sequences as lncRNAs or mRNAs using multi-feature analysis. Methods: We propose the lncRNA multi-feature-fusion ensemble learning (LMFE) approach, a novel method that integrates 100-dimensional features from RNA biological properties-based, sequence-based, and structure-based features, employing the XGBoost ensemble learning algorithm for prediction. To address unbalanced datasets, we implemented the synthetic minority oversampling technique (SMOTE). LMFE was validated across benchmark datasets, cross-species datasets, unbalanced datasets, and independent datasets. Results: LMFE achieved an accuracy of 99.42%, an F1score of 0.99, and an MCC of 0.98 on the benchmark dataset, with robust cross-species performance (accuracy ranging from 89.30% to 99.81%). On unbalanced datasets, LMFE attained an average accuracy of 99.41%, representing a 12.29% improvement over traditional methods without SMOTE (average ACC of 87.12%). Compared to state-of-the-art methods, such as CPC2 and PLEKv2, LMFE consistently outperformed them across multiple metrics on independent datasets (with an accuracy ranging from 97.33% to 99.21%), with redundant features having minimal impact on performance. Conclusions: LMFE provides a highly accurate and generalizable solution for plant lncRNA prediction, outperforming existing methods through multi-feature fusion and ensemble learning while demonstrating robustness to redundant features. Despite its effectiveness, variations in performance across species highlight the necessity for future improvements in managing diverse plant genomes. This method represents a valuable tool for advancing plant lncRNA research and guiding biological experiments.

TetraRNA, a tetra-class machine learning model for deciphering the coding potential derivation of RNA world

CncRNAs (coding and noncoding RNAs) are a class of bifunctional RNAs that that has both coding and noncoding biological activity. An increasing number of cncRNAs are being identified, prompting reassessment of our knowledge of RNA. However, most existing RNA classification tools are based on binary classification models which are not effective in distinguishing cncRNAs from mRNAs or long noncoding RNAs (lncRNAs). Our statistical analysis demonstrated that mRNA-derived cncRNAs (untranslated mRNAs, untr-mRNAs) and lncRNA-derived cncRNAs (translated ncRNAs, tr-ncRNAs) do not fall in the same cluster. Therefore, in this study, we devised a novel tetra-class RNA classification model that is systematically optimized for RNA feature extraction. According to our model, all human RNAs can be reclassified into one of four categories - mRNA, untr-mRNA, lncRNA, and tr-ncRNA - representing a novel RNA classification system and allowing the discovery of more potential cncRNAs. Further analysis revealed significant differences among the four types of RNAs in tissue-specific expression, functional annotation, sequence composition, and other factors, providing insights into their divergent evolution trajectories. Moreover, investigation of the small tr-ncRNA peptides demonstrated that their evolution is coordinated with that of the the conserved functional small RNAs associated with them. All analysis results have been integrated into a database - TetraRNADB accessible online (http://tetrarnadb.liu-lab.com/).

Transcriptomics-based investigation of resistance differences to swine fever between large white pigs and min pigs

The genetic foundations underlying the observed disease resistance in certain indigenous pig breeds, notably the Min pigs of China, present a compelling underexplored subject of study. Exploring the mechanisms of disease resistance in these breeds could lay the groundwork for genetic improvements in pig immunity, potentially augmenting overall pig productivity. In this study, whole blood samples were collected from pre- and post- swine fever vaccinated Min and Large White pigs for transcriptome sequencing. The mRNA and lncRNA in both pig breeds were analyzed, and intra-group and inter-group comparisons were also conducted. The results indicated that a greater number of immune-related pathways such as the JAK-STAT and PI3K-AKT signaling were enriched in Min pigs. Furthermore, genes involved in inflammation and antiviral responses, including IL16, IL27, USP18, and DHX58, were upregulated in post-vaccination Min pigs compared to post-vaccination Large White pigs. This heightened immune responsiveness could contribute to the observed differences in disease resistance between Min pigs and Large White pigs.

Analysis of TNS3-203 and LRRFIP1-211 Transcripts as Oral Cancer Biomarkers

INTRODUCTION

A recent pan-cancer transcriptome analysis indicated differential activity of alternative promoters of genes TNS3 and LRRFIP1 in head and neck squamous cell carcinoma compared to non-cancerous tissue. The promoters upregulated in head and neck squamous cell carcinoma regulate expression of transcripts TNS3-203 and LRRFIP1-211.

OBJECTIVE

Our aim was to investigate the biomarker potential of TNS3-203 and LRRFIP1-211 transcripts in oral cancer, the most common type of head and neck cancer.

MATERIALS AND METHODS

An in silico approach was used to characterize the promoters and transcripts of interest. Relative expression of TNS3-203 and LRRFIP1-211 transcripts was evaluated by qRT-PCR in a group of 46 oral cancer patients in samples of cancer and adjacent non-cancerous tissue.

RESULTS

TNS3-203 was significantly overexpressed in oral cancer compared with matched non-cancerous tissue, so this transcript can potentially be used as a diagnostic biomarker. There were no differences in LRRFIP1-211 level between analyzed tissues. None of the investigated transcripts has prognostic potential in oral cancer.

CONCLUSION

The results obtained indicate the diagnostic potential of TNS3-203, but not LRRFIP1-211 transcript and its role in oral carcinogenesis.

Integrative multi-omics analysis reveals the translational landscape of the plant-parasitic nematode Meloidogyne incognita

Root-knot nematodes (RKNs) of the genus Meloidogyne pose the most significant threats to global food security due to their destructive nature as plant-parasitic nematodes. Although significant attention has been devoted to investigating the gene transcription profiling of RKNs, our understanding of the translational landscape of RKNs remains limited. In this study, we elucidated the translational landscape of Meloidogyne incognita through the integration of translatome, transcriptome and quantitative proteome analyses. Our findings revealed numerous previously unannotated translation events and refined the genome annotation. By investigating the genome-wide translational dynamics of M. incognita during parasitism, we revealed that the genes of M. incognita undergo parasitic stage-specific regulation at the translational level. Interestingly, we identified 470 micropeptides (containing fewer than 100 amino acids) with the potential to function as effectors. Additionally, we observed that the effector-coding genes in M. incognita exhibit higher translation efficiency (TE). Further analysis suggests that M. incognita has the potential to regulate the TE of effector-coding genes without simultaneous alterations in their transcript abundance, facilitating effector synthesis. Collectively, our study provides comprehensive datasets and explores the genome-wide translational landscape of M. incognita, shedding light on the contributions of translational regulation during parasitism.

A chromosome-level genome assembly of the cabbage aphid Brevicoryne brassicae

The cabbage aphid, Brevicoryne brassicae, is a major pest on Brassicaceae plants, causing significant yield losses annually. However, the lack of genomic resources has hindered progress in understanding this pest at the molecular level. Here, we present a high-quality, chromosomal-level genome assembly for B. brassicae, based on PacBio HiFi long-read sequencing and Hi-C data. The final assembled genome size was 429.99 Mb, with a scaffold N50 of 93.31 Mb. Notably, 96.19% of the assembled sequences were anchored to eight chromosomes. The genome covered 99.24% of BUSCO genes and 95.16% of CEGMA genes, indicating a high level of completeness. By integrating high-coverage transcriptome data, we annotated 22,671 protein-coding genes and 3,594 lncRNA genes. Preliminary comparative genomic analyses focused on genes related to host colonization, such as chemosensory- and detoxification-related genes, as well as cross-kingdom lncRNA Ya. In summary, this study presents a contiguous and complete genome for B. brassicae, which will advance our understanding of the molecular mechanisms underlying its host adaptation, pest behavior, and interaction with Brassicaceae plants.

Comprehensive genome annotation of the model ciliate Tetrahymena thermophila by in-depth epigenetic and transcriptomic profiling

The ciliate Tetrahymena thermophila is a well-established unicellular model eukaryote, contributing significantly to foundational biological discoveries. Despite its acknowledged importance, current studies on Tetrahymena biology face challenges due to gene annotation inaccuracy, particularly the notable absence of untranslated regions (UTRs). To comprehensively annotate the Tetrahymena macronuclear genome, we collected extensive transcriptomic data spanning various cell stages. To ascertain transcript orientation and transcription start/end sites, we incorporated data on epigenetic marks displaying enrichment towards the 5' end of gene bodies, including H3 lysine 4 tri-methylation (H3K4me3), histone variant H2A.Z, nucleosome positioning and N6-methyldeoxyadenine (6mA). Cap-seq data was subsequently applied to validate the accuracy of identified transcription start sites. Additionally, we integrated Nanopore direct RNA sequencing (DRS), strand-specific RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) data. Using a newly developed bioinformatic pipeline, coupled with manual curation and experimental validation, our work yielded substantial improvements to the current gene models, including the addition of 2,481 new genes, updates to 23,936 existing genes, and the incorporation of 8,339 alternatively spliced isoforms. Furthermore, novel UTR information was annotated for 26,687 high-confidence genes. Intriguingly, 20% of protein-coding genes were identified to have natural antisense transcripts characterized by high diversity in alternative splicing, thus offering insights into understanding transcriptional regulation. Our work will enhance the utility of Tetrahymena as a robust genetic toolkit for advancing biological research, and provides a promising framework for genome annotation in other eukaryotes.

Prediction of transcript isoforms and identification of tissue-specific genes in cucumber

BACKGROUND

Identification of global transcriptional events is crucial for genome annotation, as accurate annotation enhances the efficiency and comparability of genomic information across species. However, the annotation of transcripts in the cucumber genome remains to be improved, and many transcriptional events have not been well studied.

RESULTS

We collected 1,904 high-quality public cucumber transcriptome samples from the National Center for Biotechnology Information (NCBI) to identify and annotate transcript isoforms in the cucumber genome. Over 44.26 billion Q30 clean reads were mapped to the cucumber genome with an average mapping rate of 92.75%. Transcriptome assembly identified 151,453 transcripts spanning 20,442 loci. Among these, 12.7% of transcripts exactly matched annotated genes in the cucumber reference genome. More than 80% of the transcripts were classified as novel isoforms. Approximately 96.6% of these isoforms originated from known gene loci, while around 3.3% were derived from novel gene loci. Coding potential prediction identified 4,543 long non-coding RNAs (lncRNAs) across 3,376 loci. Building on these results, we identified tissue-specific transcripts in 10 tissues. Among that, 1,655 annotated genes and 4,214 predicted transcripts were considered as tissue-specific. The root exhibited the highest number of tissue-specific transcripts, followed by shoot apex. Subsequent selective pressure analysis revealed that tissue-specific regions experienced stronger directional selection compared to non-specific regions.

CONCLUSIONS

By analyzing thousands of published transcriptome data, we identified abundant transcriptional events and tissue-specific transcripts in cucumbers. This study presented here adds the great value to the public data and offers insights for further exploration of a more comprehensive tissue regulatory network in cucumber.

Integrated analysis of microRNAs and lncRNAs expression profiles reveals regulatory modules during adventitious shoot induction in Moringa oleifera Lam

BACKGROUND

Embryogenic callus (EC) has strong regenerative potential, useful for propagation and genetic transformation. miRNAs have been confirmed to play key regulatory roles in EC regeneration across various plants. However, challenges in EC induction have hindered the breeding of drumstick (Moringa oleifera Lam.), a tree with significant commercial potential. Understanding the regulatory networks of miRNAs-lncRNAs during EC formation in drumstick is crucial for overcoming these barriers.

RESULTS

In this study, three drumstick EC small RNA libraries were sequenced using an Illumina Nova 6000 system. We identified 50 known miRNAs and 233 novel miRNAs. Target prediction and functional analysis showed that these miRNAs are involved in plant hormone signal transduction. Notably, miR319a and miR319b were upregulated throughout the entire process, while miR171 and miR160 were downregulated in the earlier stage but upregulated in the later stage. The expression patterns of 6 miRNAs detected by qRT-PCR were consistent with those observed in RNA-seq. The regulatory relationships between 6 selected highly expressed miRNAs and their target genes generally conformed to a negative regulatory pattern. Furthermore, miR156 and MolncRNA2275 were identified as key regulators in miRNA-mRNA-lncRNA network.

CONCLUSIONS

In summary, our study provides valuable insights into the molecular mechanisms underlying EC formation and enhances the understanding of the miRNA networks involved in this process.

Pervasiveness of Microprotein Function Amongst Drosophila Small Open Reading Frames (SMORFS)

Small Open Reading Frames (smORFs) of less than 100 codons remain mostly uncharacterised. About a thousand smORFs per genome encode peptides and microproteins about 70-80 aa long, often containing recognisable protein structures and markers of translation, and these are referred to as short Coding Sequences (sCDSs). The characterisation of individual sCDSs has provided examples of smORFs' function and conservation, but we cannot infer the functionality of all other metazoan smORFs from these. sCDS function has been characterised at a genome-wide scale in yeast and bacteria, showing that hundreds can produce a phenotype, but attempts in metazoans have been less successful. Either most sCDSs are not functional, or classic experimental techniques do not work with smORFs due to their shortness. Here, we combine extensive proteomics with bioinformatics and genetics in order to detect and corroborate sCDS function in Drosophila. Our studies nearly double the number of sCDSs with detected peptides and microproteins and an experimentally corroborated function. Finally, we observe a correlation between proven sCDS protein function and bioinformatic markers such as conservation and GC content. Our results support that sCDSs peptides and microproteins act as membrane-related regulators of canonical proteins, regulators whose functions are best understood at the cellular level, and whose mutants produce little, if any, overt morphological phenotypes.

RNA-Seq and miRNA-Seq data from Epstein-Barr virus-infected tree shrews reveal a ceRNA network contributing to immune microenvironment regulation

Epstein-Barr virus (EBV) infection in humans is ubiquitous and associated with various diseases. Remodeling of the immune microenvironment is the primary cause of EBV infection and pathogenesis; however, the underlying mechanism has not been fully elucidated. In this study, we used whole-transcriptome RNA-Seq to detect mRNAs, long non-coding RNAs (lncRNA), and microRNA (miRNA) profiles in the control group, 3 days, and 28 days after EBV infection, based on the tree shrew model that we reported previously. First, we estimated the proportion of 22 cell types in each sample using CIBERSORT software and identified 18 high-confidence DElncRNAs related to immune microenvironment regulation after EBV infection. Functional enrichment analysis of these differentially expressed lncRNAs primarily focused on the autophagy, endocytosis, and ferroptosis signalling pathways. Moreover, EBV infection affects miRNA expression patterns, and many miRNAs are silenced. Finally, three competing endogenous RNA regulatory networks were built using lncRNAs that significantly correlated with immune cell types, miRNAs that responded to EBV infection, and potentially targeted the mRNA of the miRNAs. Among them, MRPL42-AS-5 might act as an hsa-miR-296-5p "sponge" and compete with target mRNAs, thus increasing mRNA expression level, which could induce immune cell infiltration through the cellular senescence signalling pathway against EBV infection. Overall, we conducted a complete transcriptomic analysis of EBV infection in vivo for the first time and provided a novel perspective for further investigation of EBV-host interactions.

SpliceMutr Enables Pan-Cancer Analysis of Splicing-Derived Neoantigen Burden in Tumors

SIGNIFICANCE

SpliceMutr shows that splicing antigenicity changes in response to ICI therapies and that native modulation of the splicing machinery through mutations increases the contribution of splicing to the neoantigen load of some The Cancer Genome Atlas cancer subtypes. Future studies of the relationship between splicing antigenicity and immune checkpoint inhibitor response pan-cancer are essential to establish the interplay between antigen heterogeneity and immunotherapy regimen on patient response.

Transcriptomic analysis reveals role of lncRNA LOC100257036 to regulate AGAMOUS during cluster compactness of Vitis vinifera cv. sistan yaghooti

Yaghooti grape, as the earliest grape variety in Iran, is considered as more resistant to heat, drought, and salinity than other cultivars. Cluster compactness is regarded as an inappropriate feature for the productivity of Yaghooti grape as a critical commercial and nutritional product. In plants, lncRNAs play a critical role in regulating biological processes related to growth and development. However, the potential role of lncRNAs was not assessed in cluster compactness. Totally, 1549 lncRNAs were identified by RNA-Seq data analysis in three steps of cluster formation, berry formation, and final cluster size after a thorough screening process. In addition, 229 lncRNAs were differentially expressed in the cluster development steps. Based on the functional analysis, lncRNAs are related to AG and MYB, bHLH, LBD, NAC, and WRKY TFs. Further, the target genes enrichment analysis revealed a relationship between lncRNAs with grape growth and development, as well as resistance to abiotic stresses such as heat and drought, plant defense against pathogens, and early grapes ripening. The study identified four lncRNAs as precursors of miRNAs, predicting that 112 other lncRNAs could potentially be targeted by 166 miRNAs. The results provide new insights into the regulatory functions of lncRNAs in Yaghooti grape to improve overall understanding of the molecular mechanisms related to grape compactness.

Irisin-regulated lncRNAs and their potential regulatory functions in chondrogenic differentiation of human mesenchymal stem cells

Objective

Dysregulation of chondrogenic differentiation is associated with osteoarthritis (OA). The myokine irisin is beneficial in OA treatment; yet, the underlying mechanism is not fully understood. Long noncoding RNAs (lncRNAs) act as important regulators of chondrocyte differentiation. This study was conducted to address the role of lncRNAs in mediating irisin-induced chondrocyte differentiation.

Methods

We investigated the irisin-regulated lncRNA profile change in human mesenchymal stem cells (MSCs) using published whole transcriptome sequencing data. We predicted their potential targets and competitive endogenous RNA (ceRNA) prediction and analyzed their molecular functions using functional enrichment analysis.

Results

More differentially expressed lncRNAs (DElncRNAs) were observed in irisin-treated samples. The top irisin-induced lncRNAs were associated with OA or chondrogenic differentiation, including XIST, PAX8-AS1, CASC15, LINC01618, and DLX6-AS1. The DEGs co-expressed with DElncRNAs were enriched in skeletal system development, extracellular matrix (ECM) organization, cell adhesion, and inflammation associated pathways. Several lncRNAs likely acted as ceRNAs to regulate downstream mRNAs including ROR2 and SORBS1 in in OA or chondrogenic differentiation.

Conclusions

We demonstrate the global regulation of lncRNAs by irisin during chondrogenic differentiation of human MSCs. Further study is required to characterize the key irisin-regulated lncRNAs in chondrogenic differentiation.

Full-length transcriptome assembly of black amur bream (Megalobrama terminalis) as a reference resource

BACKGROUND

The genus Megalobrama holds significant economic value in China, with M. terminalis (Black Amur bream) ranking second in production within this group. However, lacking comprehensive genomic and transcriptomic data has impeded research progress. This study aims to fill this gap through an extensive transcriptomic analysis of M. terminalis.

METHODS AND RESULTS

We utilized PacBio Isoform Sequencing to generate 558,998 subreads, totaling 45.52 Gb, which yielded 22,141 transcripts after rigorous filtering and clustering. Complementary Illumina short-read sequencing corrected 967,114 errors across these transcripts. Our analysis identified 12,426 non-redundant isoforms, with 11,872 annotated in various databases. Functional annotation indicated 11,841 isoforms matched entries in the NCBI non-redundant protein sequences database. Gene Ontology analysis categorized 10,593 isoforms, revealing strong associations with cellular processes and binding functions. Additionally, 8203 isoforms were mapped to pathways in the Kyoto Encyclopedia of Genes and Genomes, highlighting significant involvement in immune system processes and complement cascades. We notably identified key immune molecules such as alpha-2-macroglobulin and complement component 3, each with multiple isoforms, underscoring their potential roles in the immune response. Our analysis also uncovered 853 alternative splicing events, predominantly involving retained introns, along with 672 transcription factors and 426 long non-coding RNAs.

CONCLUSIONS

The high-quality reference transcriptome generated in this study provides a valuable resource for comparative genomic studies within the Megalobrama genus, supporting future research to enhance aquaculture stocks.

ETENLNC: An end to end lncRNA identification and analysis framework to facilitate construction of known and novel lncRNA regulatory networks

Long non-coding RNAs (lncRNAs) play crucial roles in the regulation of gene expression and maintenance of genomic integrity through various interactions with DNA, RNA, and proteins. The availability of large-scale sequence data from various high-throughput platforms has opened possibilities to identify, predict, and functionally annotate lncRNAs. As a result, there is a growing demand for an integrative computational framework capable of identifying known lncRNAs, predicting novel lncRNAs, and inferring the downstream regulatory interactions of lncRNAs at the genome-scale. We present ETENLNC (End-To-End-Novel-Long-NonCoding), a user-friendly, integrative, open-source, scalable, and modular computational framework for identifying and analyzing lncRNAs from raw RNA-Seq data. ETENLNC employs six stringent filtration steps to identify novel lncRNAs, performs differential expression analysis of mRNA and lncRNA transcripts, and predicts regulatory interactions between lncRNAs, mRNAs, miRNAs, and proteins. We benchmarked ETENLNC against six existing tools and optimized it for desktop workstations and high-performance computing environments using data from three different species. ETENLNC is freely available on GitHub: https://github.com/EvolOMICS-TU/ETENLNC.

Comprehensive Transcriptome Analysis Expands lncRNA Functional Profiles in Breast Cancer

Breast cancer is a heterogeneous disease that arises as a multi-stage process involving multiple cell types. Patients diagnosed with the same clinical stage and pathological classification may have different prognoses and therapeutic responses due to alterations in molecular genetics. As an essential marker for the molecular subtyping of breast cancer, long non-coding RNAs (lncRNAs) play a crucial role in gene expression regulation, cell differentiation, and the maintenance of genomic stability. Here, we developed a modular framework for lncRNA identification and applied it to a breast cancer cohort to identify novel lncRNAs not previously annotated. To investigate the potential biological function, regulatory mechanisms, and clinical relevance of the novel lncRNAs, we elucidated the genomic and chromatin features of these lncRNAs, along with the associated protein-coding genes and putative enhancers involved in the breast cancer regulatory networks. Furthermore, we uncovered that the expression patterns of novel and annotated lncRNAs identified in breast cancer were related to the hormone response in the PAM50 subtyping criterion, as well as the immune response and progression states of breast cancer across different immune cells and immune checkpoint genes. Collectively, the comprehensive identification and functional analysis of lncRNAs revealed that these lncRNAs play an essential role in breast cancer by altering gene expression and participating in the regulatory networks, contributing to a better insight into breast cancer heterogeneity and potential avenues for therapeutic intervention.

Analysis of differentially expressed lncRNAs and mRNAs associated with slow‑transit constipation

Slow transit constipation (STC) is a refractory gastrointestinal disease, accounting for approximately 13 ∼ 37 % of chronic constipation. However, the molecular mechanism of STC remains poorly understood. Herein, this study aims to identify the key mRNAs and lncRNAs associated with STC. To this end, we performed high-throughput RNA sequencing to identify differentially expressed (DE) mRNAs and lncRNAs in the whole-layer sigmoid intestinal tissues from 4 STC patients and 4 non-STC patients. The identified DE lncRNAs and mRNAs were validated through quantitative real-time PCR. Weighted gene co-expression network analysis (WGCNA) and Pearson correlation analysis were conducted to determine the significantly correlated DE mRNA-lncRNA pairs. A total of 1420 DE lncRNAs and 1634 DE mRNAs were identified. Kyoto Encyclopedia of Genes and Genomes analysis of DE mRNAs indicated that these DE mRNAs might be associated with systemic lupus erythematosus, alcoholism, intestinal immune network for IgA production, inflammatory bowel disease, NF-kappa B signaling pathway. WGCNA and Pearson correlation analyses jointly identified 16,577 significantly correlated DE mRNA-lncRNA pairs. Furthermore, lncRNAs LINC00641, LINC02268, LINC03013 were identified as hub lncRNAs. The protein-protein interaction (PPI) network of proteins encoded by DE mRNAs was established, and PPI-based analysis revealed that Interleukin 2(IL2), CD80 molecule (CD80), interleukin-17A (IL-17A) might play significant roles in the development of STC. This study analyzes the expression profiles of lncRNAs and mRNAs associated with STC. Our findings will contribute to further understanding of the molecular mechanism of STC and provide potential diagnostic or therapeutic biomarkers for STC.

Expression profile of long noncoding RNAs and comprehensive analysis of lncRNA-cisTF-DGE regulation in condyloma acuminatum

OBJECTIVE

To identify differentially expressed long noncoding RNAs (lncRNAs) in condyloma acuminatum (CA) and to explore their probable regulatory mechanisms by establishing coexpression networks.

METHODS

High-throughput RNA sequencing was performed to assess genome-wide lncRNA expression in CA and paired adjacent mucosal tissue. The expression of candidate lncRNAs and their target genes in larger CA specimens was validated using real-time quantitative reverse transcriptase polymerase chain reaction (RT‒qPCR). Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used for the functional enrichment analysis of these candidate lncRNAs and differential mRNAs. The coexpressed mRNAs of the candidate lncRNAs, calculated by Pearson's correlation coefficient, were also analysed using GO and KEGG analysis. In addition, the interactions among differentially expressed lncRNAs (DElncRNAs)-cis-regulatory transcription factors (cisTFs)-differentially expressed genes (DEGs) were analysed and their network was constructed.

RESULTS

A total of 546 lncRNAs and 2553 mRNAs were found to be differentially expressed in CA compared to the paired control. Functional enrichment analysis revealed that the DEGs coexpressed with DElncRNAs were enriched in the terms of cell adhesion and keratinocyte differentiation, and the pathways of ECM-receptor interaction, local adhesion, PI3K/AKT and TGF-ß signaling. We further constructed the network among DElncRNAs-cisTFs-DEGs and found that these 95 DEGs were mainly enriched in GO terms of epithelial development, regulation of transcription or gene expression. Furthermore, the expression of 3 pairs of DElncRNAs and cisTFs, EVX1-AS and HOXA13, HOXA11-AS and EVX1, and DLX6-AS and DLX5, was validated with a larger number of specimens using RT‒qPCR.

CONCLUSION

CA has a specific lncRNA profile, and the differentially expressed lncRNAs play regulatory roles in mRNA expression through cis-acting TFs, which provides insight into their regulatory networks. It will be useful to understand the pathogenesis of CA to provide new directions for the prevention, clinical treatment and efficacy evaluation of CA.

The Spatio-Temporal Expression Profiles of Silkworm Pseudogenes Provide Valuable Insights into Their Biological Roles

Background

Pseudogenes are sequences that have lost the ability to transcribe RNA molecules or encode truncated but possibly functional proteins. While they were once considered to be meaningless remnants of evolution, recent researches have shown that pseudogenes play important roles in various biological processes. However, the studies of pseudogenes in the silkworm, an important model organism, are limited and have focused on single or only a few specific genes.

Objective

To fill these gaps, we present a systematic genome-wide studies of pseudogenes in the silkworm.

Methods

We identified the pseudogenes in the silkworm using the silkworm genome assemblies, transcriptome, protein sequences from silkworm and its related species. Then we used transcriptome datasets from 832 RNA-seq analyses to construct spatio-temporal expression profiles for these pseudogenes. Additionally, we identified tissue-specifically expressed and differentially expressed pseudogenes to further understand their characteristics. Finally, the functional roles of pseudogenes as lncRNAs were systematically analyzed.

Results

We identified a total of 4410 pseudogenes, which were grouped into 4 groups, including duplications (DUPs), unitary pseudogenes (Unitary), processed pseudogenes (retropseudogenes, RETs), and fragments (FRAGs). The most of pseudogenes in the domestic silkworm were generated before the divergence of wild and domestic silkworm, however, the domestication may also involve in the accumulation of pseudogenes. These pseudogenes were clearly divided into 2 cluster, a highly expressed and a lowly expressed, and the posterior silk gland was the tissue with the most tissue-specific pseudogenes (199), implying these pseudogenes may be involved in the development and function of silkgland. We identified 3299 lncRNAs in these pseudogenes, and the target genes of these lncRNAs in silkworm pseudogenes were enriched in the egg formation and olfactory function.

Conclusions

This study replenishes the genome annotations for silkworm, provide valuable insights into the biological roles of pseudogenes. It will also contribute to our understanding of the complex gene regulatory networks in the silkworm and will potentially have implications for other organisms as well.

RNA Sequencing Analyses Reveal the Potential Anti-Inflammatory Mechanisms of Acacetin Against ODG/R Injuries in Microglia

Background

Acacetin is a natural flavonoid known for its anti-tumor, antioxidant, and anti-inflammatory properties. Our previous studies have shown its protective effects against cerebral ischemia-reperfusion injury (IRI), but the underlying molecular mechanisms remain unclear.

Purpose

The study delves into acacetin's mechanism in mitigating cerebral IRI, with a focus on transcriptomic insights.

Methods

We established the oxygen-glucose deprivation/re-oxygenation (OGD/R) model in BV2 microglia, treating them with 10μM acacetin. Then we assessed cell proliferation using CCK-8 and measured Lactate Dehydrogenase (LDH) release. High-throughput RNA sequencing (RNA-seq) underpinned the analysis of differentially expressed genes (DEGs) and long non-coding RNAs (lncRNAs), functional enrichment, and alternative splicing events (ASEs), validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).

Results

OGD/R injury significantly impaired cell proliferation and increased LDH release, effects mitigated by acacetin. RNA-seq identified 2148 upregulated and 2135 downregulated DEGs post-OGD/R. In contrast, the acacetin-treated group showed 248 upregulated and 240 downregulated DEGs compared to the OGD/R group. All DEGs were enriched in both Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Overlapping analysis indicated that acacetin treatment reversed the expression of 203 genes affected by OGD/R, including inflammation-related genes such as Isg15, Fcgr1, Il1b, and Parp12. Moreover, the oxidative stress-related gene, Mt2, was downregulated post-OGD/R but upregulated following acacetin treatment. We further found that OGD/R and acacetin treatment could modulate gene splicing events, impacting cell apoptosis or inflammatory responses, such as the A3SS splicing event in the Trim47 gene. RNA-seq also highlighted differential expression of numerous lncRNAs, particularly the upregulation of lncRNA Rmrp and Terc post-OGD/R and their subsequent downregulation post-acacetin treatment. These lncRNAs might regulate cell proliferation through mediating target gene expressions. RT-qPCR validation confirmed these findings.

Conclusion

Significant upregulation of genes and ASEs linked to oxidative stress and inflammatory response is observed in cerebral IRI. Acacetin intervention reverses these effects, highlighting its mechanism in alleviating the injury by modulating gene expression and splicing events.

Long Noncoding RNAs in Response to Hyperosmolarity Stress, but Not Salt Stress, Were Mainly Enriched in the Rice Roots

Due to their immobility and possession of underground parts, plants have evolved various mechanisms to endure and adapt to abiotic stresses such as extreme temperatures, drought, and salinity. However, the contribution of long noncoding RNAs (lncRNAs) to different abiotic stresses and distinct rice seedling parts remains largely uncharacterized beyond the protein-coding gene (PCG) layer. Using transcriptomics and bioinformatics methods, we systematically identified lncRNAs and characterized their expression patterns in the roots and shoots of wild type (WT) and ososca1.1 (reduced hyperosmolality-induced [Ca2+]i increase in rice) seedlings under hyperosmolarity and salt stresses. Here, 2937 candidate lncRNAs were identified in rice seedlings, with intergenic lncRNAs representing the largest category. Although the detectable sequence conservation of lncRNAs was low, we observed that lncRNAs had more orthologs within the Oryza. By comparing WT and ososca1.1, the transcription level of OsOSCA1.1-related lncRNAs in roots was greatly enhanced in the face of hyperosmolality stress. Regarding regulation mode, the co-expression network revealed connections between trans-regulated lncRNAs and their target PCGs related to OsOSCA1.1 and its mediation of hyperosmolality stress sensing. Interestingly, compared to PCGs, the expression of lncRNAs in roots was more sensitive to hyperosmolarity stress than to salt stress. Furthermore, OsOSCA1.1-related hyperosmolarity stress-responsive lncRNAs were enriched in roots, and their potential cis-regulated genes were associated with transcriptional regulation and signaling transduction. Not to be ignored, we identified a motif-conserved and hyperosmolarity stress-activated lncRNA gene (OSlncRNA), speculating on its origin and evolutionary history in Oryza. In summary, we provide a global perspective and a lncRNA resource to understand hyperosmolality stress sensing in rice roots, which helps to decode the complex molecular networks involved in plant sensing and adaptation to stressful environments.

Comprehensive transcriptome sequencing of silkworm Midguts: Uncovering extensive isoform diversity and alternative splicing in BmNPV-Sensitive and BmNPV-resistant strains

The silkworm, Bombyx mori, stands out as one of the few economically valuable insects within the realm of model organisms. However, Bombyx mori nucleopolyhedrovirus (BmNPV) poses a significant threat, decreasing the quality and quantity of silkworm cocoons. Over the past few decades, a multitude of researchers has delved into the mechanisms that underlie silkworm resistance to BmNPV, employing diverse methodologies and approaching the problem from various angles. Despite this extensive research, the role of alternative splicing (AS) in the silkworm's response to BmNPV infection has been largely unexplored. This study leveraged both third-generation (Oxford Nanopore Technologies) and second-generation (Illumina) high-throughput sequencing technologies to meticulously identify and analyze AS patterns in the context of BmNPV response, utilizing two distinct silkworm strains-the susceptible strain 306 and the resistant strain NB. Consequently, we identified five crucial genes (Dsclp, LOC692903, LOC101743583, LOC101742498, LOC101743809) that are linked to the response to BmNPV infection through AS and differential expression. Additionally, a thorough comparative analysis was conducted on their diverse transcriptomic expression profiles, including alternative polyadenylation, simple sequence repeats, and transcription factors.

Multiple strategies, including 6mA methylation, affecting plant alternative splicing in allopolyploid peanut

Alternative splicing (AS), an important post-transcriptional regulation mechanism in eukaryotes, can significantly increase transcript diversity and contribute to gene expression regulation and many other complicated developmental processes. While plant gene AS events are well described, few studies have investigated the comprehensive regulation machinery of plant AS. Here, we use multi-omics to analyse peanut AS events. Using long-read isoform sequencing, 146 464 full-length non-chimeric transcripts were obtained, resulting in annotation corrections for 1782 genes and the identification of 4653 new loci. Using Iso-Seq RNA sequences, 271 776 unique splice junctions were identified, 82.49% of which were supported by transcriptome data. We characterized 50 977 polyadenylation sites for 23 262 genes, 12 369 of which had alternative polyadenylation sites. AS allows differential regulation of the same gene by miRNAs at the isoform level coupled with polyadenylation. In addition, we identified many long non-coding RNAs and fusion transcripts. There is a suppressed effect of 6mA on AS and gene expression. By analysis of chromatin structures, the genes located in the boundaries of topologically associated domains, proximal chromosomal telomere regions, inter- or intra-chromosomal loops were found to have more unique splice isoforms, higher expression, lower 6mA and more transposable elements (TEs) in their gene bodies than the other genes, indicating that chromatin interaction, 6mA and TEs play important roles in AS and gene expression. These results greatly refine the peanut genome annotation and contribute to the study of gene expression and regulation in peanuts. This work also showed AS is associated with multiple strategies for gene regulation.

Genome-wide analysis of long noncoding RNAs as cis-acting regulators of transcription factor-encoding genes in IgA nephropathy

BACKGROUND

IgA nephropathy (IgAN) is the most common form of primary glomerulonephritis in the world, but the disease pathogenesis noncoding is yet to be elucidated. Previous studies have revealed regulatory functions for long noncoding RNA (lncRNA) in various diseases; however, the roles of lncRNA in IgAN and regulation of transcription factors (TFs) have been scarcely investigated.

METHODS

Renal tissue samples (n = 5) from patients with IgAN and control samples (n = 4) were collected and RNA sequencing (RNA-seq) was performed. Four software programs were employed for lncRNA prediction. GO (Gene Ontology)/KEGG (Kyoto Encyclopedia of Genes and Genomes) were employed for analysis of the identified differentially expressed genes (DEGs). A regulatory network model of DE lncRNA-TF-DEG was developed, and the levels of expression of key lncRNAs, TFs, and corresponding target genes were assessed using qRT-PCR and immunofluorescence.

RESULTS

The current study identified 674 upregulated and 1,011 downregulated DE mRNAs and 260 upregulated and 232 downregulated DE lncRNAs in IgAN samples compared with control samples. The upregulated DE mRNAs showed enrichment in cell adhesion and collagen glial fiber organization pathways. The DE lncRNAs-DE mRNAs showing co-expression are associated with transmembrane transport. A novel regulatory network model of lncRNA-TF-DEG has been developed. This study identified seven TFs that are cis-regulated by 6 DE lncRNAs, and show co-expression with 132 DEGs (correlation coefficient ≥ 0.8, P ≤ 0.01), generating 158 pairs that showed co-expression. The lncRNAs NQO1-DT and RP5-1057120.6 were found to be highly expressed in IgAN samples. The TFs vitamin D Receptor (VDR) and NFAT5, along with their target genes were also aberrantly expressed.

CONCLUSION

Key lncRNAs and TFs centrally associated with IgAN have been identified in this study. A regulatory network model of lncRNA-TF-mRNA was constructed. Further studies on the genes identified herewith could provide insight into the pathogenesis of IgAN.

Combined full-length transcriptomic and metabolomic analysis reveals the molecular mechanisms underlying nutrients and taste components development in Primulina juliae

BACKGROUND

Primulina juliae has recently emerged as a novel functional vegetable, boasting a significant biomass and high calcium content. Various breeding strategies have been employed to the domestication of P. juliae. However, the absence of genome and transcriptome information has hindered the research of mechanisms governing the taste and nutrients in this plant. In this study, we conducted a comprehensive analysis, combining the full-length transcriptomics and metabolomics, to unveil the molecular mechanisms responsible for the development of nutrients and taste components in P. juliae.

RESULTS

We obtain a high-quality reference transcriptome of P. juliae by combing the PacBio Iso-seq and Illumina sequencing technologies. A total of 58,536 cluster consensus sequences were obtained, including 28,168 complete protein coding transcripts and 8,021 Long Non-coding RNAs. Significant differences were observed in the composition and content of compounds related to nutrients and taste, particularly flavonoids, during the leaf development. Our results showed a decrease in the content of most flavonoids as leaves develop. Malate and succinate accumulated with leaf development, while some sugar metabolites were decreased. Furthermore, we identified the different accumulation of amino acids and fatty acids, which are associated with taste traits. Moreover, our transcriptomic analysis provided a molecular basis for understanding the metabolic variations during leaf development. We identified 4,689 differentially expressed genes in the two developmental stages, and through a comprehensive transcriptome and metabolome analysis, we discovered the key structure genes and transcription factors involved in the pathways.

CONCLUSIONS

This study provides a high-quality reference transcriptome and reveals molecular mechanisms associated with the development of nutrients and taste components in P. juliae. These findings will enhance our understanding of the breeding and utilization of P. juliae as a vegetable.

LncRNA GAS6-AS1 contributes to 5-fluorouracil resistance in colorectal cancer by facilitating the binding of PCBP1 with MCM3

5-Fluorouracil (5-FU) resistance has always been a formidable obstacle in the adjuvant treatment of advanced colorectal cancer (CRC). In recent years, long non-coding RNAs have emerged as key regulators in various pathophysiological processes including 5-FU resistance. TRG is a postoperative pathological score of the chemotherapy effectiveness for CRC, of which TRG 0-1 is classified as chemotherapy sensitivity and TRG 3 as chemotherapy resistance. Here, RNA-seq combined with weighted gene correlation network analysis confirmed the close association of GAS6-AS1 with TRG. GAS6-AS1 expression was positively correlated with advanced clinicopathological features and poor prognosis in CRC. GAS6-AS1 increased the 50% inhibiting concentration of 5-FU, enhanced cell proliferation and accelerated G1/S transition, both with and without 5-FU, both in vitro and in vivo. Mechanistically, GAS6-AS1 enhanced the stability of MCM3 mRNA by recruiting PCBP1, consequently increasing MCM3 expression. Furthermore, PCBP1 and MCM3 counteracted the effects of GAS6-AS1 on 5-FU resistance. Notably, the PDX model indicated that combining chemotherapeutic drugs with GAS6-AS1 knockdown yielded superior outcomes in vivo. Together, our findings elucidate that GAS6-AS1 directly binds to PCBP1, enhancing MCM3 expression and thereby promoting 5-FU resistance. GAS6-AS1 may serve as a robust biomarker and potential therapeutic target for combination therapy in CRC.

miR-306-5p is involved in chitin metabolism in Aedes albopictus pupae via linc8338-miR-306-5p-XM_019678125.2 axis

Aedes albopictus can transmit several lethal arboviruses. This mosquito has become a sever public health threat due to its rapidly changing global distribution. Chitin, which is the major component of the cuticle and peritrophic membrane (PM), is crucial for the growth and development of insect. microRNAs (miRNAs) play important roles in the posttranscriptional level regulation of gene expression, thereby influencing many biological processes in insects. In this study, an attempt was made to evaluate the role of miR-306-5p in regulating chitin metabolism in Ae. albopictus pupae. Overexpression of miR-306-5p resulted in a significantly reduced survival rate in pupae and an increased malformation rate in adults. Both in vivo and in vitro evidence confirmed the presence of the competing endogenous RNA (ceRNA) regulatory axis (linc8338-miR-306-5p-XM_019678125.2). RNAi of linc8338 and XM_019678125.2 had effects on pupae similar to those of miR-306-5p. The highest expression level of miR-306-5p was found in the midgut, and alteration in the expression of miR-306-5p, XM_019678125.2 and linc8338 induced increased transcript levels of chitin synthase 2 (AaCHS2) and decreased chitinase 10 (AaCht10); as well as increased thickness of the midgut and enlarged midgut epithelial cells. The results of this study highlight the potential of miR-306-5p as a prospective target in mosquito control and confirm that the ceRNA mechanism is involved in chitin metabolism. These findings will provide a basis for further studies to uncover the molecular mechanisms through which ncRNAs regulate chitin metabolism.

Lnc-PKNOX1-1 inhibits tumor progression in cutaneous malignant melanoma by regulating NF-κB/IL-8 axis

Cutaneous malignant melanoma is one of the most lethal cutaneous malignancies. Accumulating evidence has demonstrated the potential influence of long non-coding RNAs (lncRNAs) in biological behaviors of melanoma. Herein, we reported a novel lncRNA, lnc-PKNOX1-1 and systematically studied its functions and possible molecular mechanisms in melanoma. Reverse transcription-quantitative PCR assay showed that lnc-PKNOX1-1 was significantly decreased in melanoma cells and tissues. Low lnc-PKNOX1-1 expression was significantly correlated with invasive pathological type and Breslow thickness of melanoma. In vitro and in vivo experiments showed lnc-PKNOX1-1 dramatically inhibited melanoma cell proliferation, migration and invasion. Mechanically, protein microarray analysis suggested that interleukin-8 (IL-8) was negatively regulated by lnc-PKNOX1-1 in melanoma, which was confirmed by western blot and ELISA. Western blot analysis also showed that lnc-PKNOX1-1 could promote p65 phosphorylation at Ser536 in melanoma. Subsequent rescue assays proved IL-8 overexpression could partly reverse the tumor-suppressing function of lnc-PKNOX1-1 overexpression in melanoma cells, indicating that lnc-PKNOX1-1 suppressed the development of melanoma by regulating IL-8. Taken together, our study demonstrated the tumor-suppressing ability of lnc-PKNOX1-1 in melanoma, suggesting its potential as a novel diagnostic biomarker and therapeutic target for melanoma.

Fascin actin-bundling protein 1 regulates non-small cell lung cancer progression by influencing the transcription and splicing of tumorigenesis-related genes

Background

High mortality rates are prevalent among patients with non-small-cell lung cancer (NSCLC), and effective therapeutic targets are key prognostic factors. Fascin actin-bundling protein 1 (FSCN1) promotes NSCLC; however, its role as an RNA-binding protein in NSCLC remains unexplored. Therefore, we aimed to explore FSCN1 expression and function in A549 cells.

Method

We screened for alternative-splicing events and differentially expressed genes (DEGs) after FSCN1 silence via RNA-sequencing (RNA-seq). FSCN1 immunoprecipitation followed by RNA-seq were used to identify target genes whose mRNA expression and pre-mRNA alternative-splicing levels might be influenced by FSCN1.

Results

Silencing FSCN1 in A549 cells affected malignant phenotypes; it inhibited proliferation, migration, and invasion, and promoted apoptosis. RNA-seq analysis revealed 2,851 DEGs and 3,057 alternatively spliced genes. Gene ontology-based functional enrichment analysis showed that downregulated DEGs and alternatively splicing genes were enriched for the cell-cycle. FSCN1 promoted the alternative splicing of cell-cycle-related mRNAs involved in tumorigenesis (i.e., BCCIP, DLGAP5, PRC1, RECQL5, WTAP, and SGO1). Combined analysis of FSCN1 RNA-binding targets and RNA-seq data suggested that FSCN1 might affect ACTG1, KRT7, and PDE3A expression by modulating the pre-mRNA alternative-splicing levels of NME4, NCOR2, and EEF1D, that were bound to long non-coding RNA transcripts (RNASNHG20, NEAT1, NSD2, and FTH1), which were highly abundant. Overall, extensive transcriptome analysis of gene alternative splicing and expression levels was performed in cells transfected with FSCN1 short-interfering RNA. Our data provide global insights into the regulatory mechanisms associated with the roles of FSCN1 and its target genes in lung cancer.

Transcript CD81-215 may be a long noncoding RNA of stromal origin with tumor-promoting role in colon cancer

The role of tetraspanin CD81 in malignant transformation is best studied in colorectal cancer, and it appears that other transcripts beside the fully coding mRNA may also be dysregulated in malignant cells. Recent data from a comprehensive pan-cancer transcriptome analysis demonstrated differential activity of two alternative CD81 gene promoters in malignant versus nonmalignant gut mucosa. The promoter active in gut mucosa gives rise to transcripts CD81-203 and CD81-213, while the promoter active in colon and rectal cancer gives rise to transcripts CD81-205 and CD81-215. Our study aimed to explore the biomarker potential of the transcripts from the alternative CD81 gene promoters in colon cancer, as well as to investigate their structure and potential function using in silico tools. The analysis of the transcripts' expression in several colon cell lines cultivated in 2D and 3D and a set of colon cancer and healthy gut mucosa samples by qPCR and RNA sequencing suggested their low expression and stromal origin. Expression patterns in tumor and nontumor tissue along with in silico data suppose that the transcript CD81-215 may be a noncoding RNA of stromal origin with possible involvement in signaling related to malignant transformation.

Identification of key genes affecting sperm motility in chicken based on whole-transcriptome sequencing

Sperm motility is an important index for the evaluation of semen quality. Improving sperm motility is important to improve reproductive performance, promote breeding process, and reduce production cost. However, the molecular mechanisms regulating sperm motility in chickens remain unclear. In this study, histological observation and whole-transcriptome analysis were performed on testicular tissue of chickens with high and low sperm motility. Histological observations showed that roosters with high sperm motility exhibited better semen quality than those with low sperm motility. In addition, the germinal epithelial cells of roosters with low sperm motility were loosely arranged and contained many vacuoles. RNA-seq results revealed the expression of 23,033 mRNAs, 2,893 lncRNAs, and 515 miRNAs in chicken testes. Among them, there were 417 differentially expressed mRNAs (DEmRNAs), 106 differentially expressed lncRNAs (DElncRNAs), and 15 differentially expressed miRNAs (DEmiRNAs) between high and low sperm motility testes. These differentially expressed genes were involved in the G protein-coupled receptor signaling pathway, cilia structure, Wnt signaling, MAPK signaling, GnRH signaling, and mTOR signaling. By integrating the competitive relationships between DEmRNAs, DElncRNAs, and DEmiRNAs, we identified the regulatory pathway of MSTRG.3077.3/MSTRG.9085.1-gga-miR-138-5p-CADM1 and MSTRG.2290.1-gga-miR-142-3p-GNAQ/PPP3CA as crucial in the modulation of chicken sperm motility. This study provides new insights into the function and mechanism of ceRNAs in regulating sperm motility in chicken testes.

Genome-Wide Identification and Involvement in Response to Biotic and Abiotic Stresses of lncRNAs in Turbot (Scophthalmus maximus)

Long non-coding RNAs (lncRNAs) play crucial roles in a variety of biological processes, including stress response. However, the number, characteristics and stress-related expression of lncRNAs in turbot are still largely unknown. In this study, a total of 12,999 lncRNAs were identified at the genome-wide level of turbot for the first time using 24 RNA-seq datasets. Sequence characteristic analyses of transcripts showed that lncRNA transcripts were shorter in average length, lower in average GC content and in average expression level as compared to the coding genes. Expression pattern analyses of lncRNAs in 12 distinct tissues showed that lncRNAs, especially lincRNA, exhibited stronger tissue-specific expression than coding genes. Moreover, 612, 1351, 1060, 875, 420 and 1689 differentially expressed (DE) lncRNAs under Vibrio anguillarum, Enteromyxum scophthalmi, and Megalocytivirus infection and heat, oxygen, and salinity stress conditions were identified, respectively. Among them, 151 and 62 lncRNAs showed differential expression under various abiotic and biotic stresses, respectively, and 11 lncRNAs differentially expressed under both abiotic and biotic stresses were selected as comprehensive stress-responsive lncRNA candidates. Furthermore, expression pattern analysis and qPCR validation both verified the comprehensive stress-responsive functions of these 11 lncRNAs. In addition, 497 significantly co-expressed target genes (correlation coefficient (R) > 0.7 and q-value < 0.05) for these 11 comprehensive stress-responsive lncRNA candidates were identified. Finally, GO and KEGG enrichment analyses indicated that these target genes were enriched mainly in molecular function, such as cytokine activity and active transmembrane transporter activity, in biological processes, such as response to stimulus and immune response, and in pathways, such as protein families: signaling and cellular processes, transporters and metabolism. These findings not only provide valuable reference resources for further research on the molecular basis and function of lncRNAs in turbot but also help to accelerate the progress of molecularly selective breeding of stress-resistant turbot strains or varieties.

Development of Nanopore sequencing-based full-length transcriptome database toward functional genome annotation of the Pacific oyster, Crassostrea gigas

The Pacific oyster (Crassostrea gigas) is a widely cultivated shellfish in the world, while its transcriptome diversity remains less unexplored due to the limitation of short reads. In this study, we used Oxford Nanopore sequencing to develop the full-length transcriptome database of C. gigas. We identified 77,920 full-length transcripts from 21,523 genes, and uncovered 9668 alternative splicing events and 87,468 alternative polyadenylation sites. Notably, a total of 16,721 novel transcripts were annotated in this work. Furthermore, integrative analysis of 25 publicly available RNA-seq datasets revealed the transcriptome diversity involved in post-transcriptional regulation in C. gigas. We further developed a Drupal based webserver, Cgtdb, which can be used for transcriptome visualization, sequence alignment, and functional genome annotation analyses. This work provides valuable resources and a useful tool for integrative analysis of various transcriptome datasets in C. gigas, which will serve as an essential reference for functional annotation of the oyster genome.

Transcriptome Screening of Long Noncoding RNAs and Their Target Protein-Coding Genes Unmasks a Dynamic Portrait of Seed Coat Coloration Associated with Anthocyanins in Tibetan Hulless Barley

Many plants have the capability to accumulate anthocyanins for coloration, and anthocyanins are advantageous to human health. In the case of hulless barley (Hordeum vulgare L. var. nudum), investigation into the mechanism of anthocyanin formation is limited to the level of protein-coding genes (PCGs). Here, we conducted a comprehensive bioinformatics analysis to identify a total of 9414 long noncoding RNAs (lncRNAs) in the seed coats of purple and white hulless barley along a developmental gradient. Transcriptome-wide profiles of lncRNAs documented several properties, including GC content fluctuation, uneven length, a diverse range of exon numbers, and a wide variety of transcript classifications. We found that certain lncRNAs in hulless barley possess detectable sequence conservation with Hordeum vulgare and other monocots. Furthermore, both differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs) were concentrated in the later seed development stages. On the one hand, DElncRNAs could potentially cis-regulate DEPCGs associated with multiple metabolic pathways, including flavonoid and anthocyanin biosynthesis in the late milk and soft dough stages. On the other hand, there was an opportunity for trans-regulated lncRNAs in the color-forming module to affect seed coat color by upregulating PCGs in the anthocyanin pathway. In addition, the interweaving of hulless barley lncRNAs and diverse TFs may function in seed coat coloration. Notably, we depicted a dynamic portrait of the anthocyanin synthesis pathway containing hulless barley lncRNAs. Therefore, this work provides valuable gene resources and more insights into the molecular mechanisms underlying anthocyanin accumulation in hulless barley from the perspective of lncRNAs, which facilitate the development of molecular design breeding in crops.

CircPCBL: Identification of Plant CircRNAs with a CNN-BiGRU-GLT Model

Circular RNAs (circRNAs), which are produced post-splicing of pre-mRNAs, are strongly linked to the emergence of several tumor types. The initial stage in conducting follow-up studies involves identifying circRNAs. Currently, animals are the primary target of most established circRNA recognition technologies. However, the sequence features of plant circRNAs differ from those of animal circRNAs, making it impossible to detect plant circRNAs. For example, there are non-GT/AG splicing signals at circRNA junction sites and few reverse complementary sequences and repetitive elements in the flanking intron sequences of plant circRNAs. In addition, there have been few studies on circRNAs in plants, and thus it is urgent to create a plant-specific method for identifying circRNAs. In this study, we propose CircPCBL, a deep-learning approach that only uses raw sequences to distinguish between circRNAs found in plants and other lncRNAs. CircPCBL comprises two separate detectors: a CNN-BiGRU detector and a GLT detector. The CNN-BiGRU detector takes in the one-hot encoding of the RNA sequence as the input, while the GLT detector uses k-mer (k = 1 - 4) features. The output matrices of the two submodels are then concatenated and ultimately pass through a fully connected layer to produce the final output. To verify the generalization performance of the model, we evaluated CircPCBL using several datasets, and the results revealed that it had an F1 of 85.40% on the validation dataset composed of six different plants species and 85.88%, 75.87%, and 86.83% on the three cross-species independent test sets composed of Cucumis sativus, Populus trichocarpa, and Gossypium raimondii, respectively. With an accuracy of 90.9% and 90%, respectively, CircPCBL successfully predicted ten of the eleven circRNAs of experimentally reported Poncirus trifoliata and nine of the ten lncRNAs of rice on the real set. CircPCBL could potentially contribute to the identification of circRNAs in plants. In addition, it is remarkable that CircPCBL also achieved an average accuracy of 94.08% on the human datasets, which is also an excellent result, implying its potential application in animal datasets. Ultimately, CircPCBL is available as a web server, from which the data and source code can also be downloaded free of charge.

Long Non-Coding RNAs of Plants in Response to Abiotic Stresses and Their Regulating Roles in Promoting Environmental Adaption

Abiotic stresses triggered by climate change and human activity cause substantial agricultural and environmental problems which hamper plant growth. Plants have evolved sophisticated mechanisms in response to abiotic stresses, such as stress perception, epigenetic modification, and regulation of transcription and translation. Over the past decade, a large body of literature has revealed the various regulatory roles of long non-coding RNAs (lncRNAs) in the plant response to abiotic stresses and their irreplaceable functions in environmental adaptation. LncRNAs are recognized as a class of ncRNAs that are longer than 200 nucleotides, influencing a variety of biological processes. In this review, we mainly focused on the recent progress of plant lncRNAs, outlining their features, evolution, and functions of plant lncRNAs in response to drought, low or high temperature, salt, and heavy metal stress. The approaches to characterize the function of lncRNAs and the mechanisms of how they regulate plant responses to abiotic stresses were further reviewed. Moreover, we discuss the accumulating discoveries regarding the biological functions of lncRNAs on plant stress memory as well. The present review provides updated information and directions for us to characterize the potential functions of lncRNAs in abiotic stresses in the future.

A wheat integrative regulatory network from large-scale complementary functional datasets enables trait-associated gene discovery for crop improvement

Gene regulation is central to all aspects of organism growth, and understanding it using large-scale functional datasets can provide a whole view of biological processes controlling complex phenotypic traits in crops. However, the connection between massive functional datasets and trait-associated gene discovery for crop improvement is still lacking. In this study, we constructed a wheat integrative gene regulatory network (wGRN) by combining an updated genome annotation and diverse complementary functional datasets, including gene expression, sequence motif, transcription factor (TF) binding, chromatin accessibility, and evolutionarily conserved regulation. wGRN contains 7.2 million genome-wide interactions covering 5947 TFs and 127 439 target genes, which were further verified using known regulatory relationships, condition-specific expression, gene functional information, and experiments. We used wGRN to assign genome-wide genes to 3891 specific biological pathways and accurately prioritize candidate genes associated with complex phenotypic traits in genome-wide association studies. In addition, wGRN was used to enhance the interpretation of a spike temporal transcriptome dataset to construct high-resolution networks. We further unveiled novel regulators that enhance the power of spike phenotypic trait prediction using machine learning and contribute to the spike phenotypic differences among modern wheat accessions. Finally, we developed an interactive webserver, wGRN (http://wheat.cau.edu.cn/wGRN), for the community to explore gene regulation and discover trait-associated genes. Collectively, this community resource establishes the foundation for using large-scale functional datasets to guide trait-associated gene discovery for crop improvement.

Prediction of protein-coding small ORFs in multi-species using integrated sequence-derived features and the random forest model

Proteins encoded by small open reading frames (sORFs) can serve as functional elements playing important roles in vivo. Such sORFs also constitute the potential pool for facilitating the de novo gene birth, driving evolutionary innovation and species diversity. Therefore, their theoretical and experimental identification has become a critical issue. Herein, we proposed a protein-coding sORFs prediction method merely based on integrative sequence-derived features. Our prediction performance is better or comparable compared with other nine prevalent methods, which shows that our method can provide a relatively reliable research tool for the prediction of protein-coding sORFs. Our method allows users to estimate the potential expression of a queried sORF, which has been demonstrated by the correlation analysis between our possibility estimation and codon adaption index (CAI). Based on the features that we used, we demonstrated that the sequence features of the protein-coding sORFs in the two domains have significant differences implying that it might be a relatively hard task in terms of cross-domain prediction, hence domain-specific models were developed, which allowed users to predict protein-coding sORFs both in eukaryotes and prokaryotes. Finally, a web-server was developed and provided to boost and facilitate the study of the related field, which is freely available at http://guolab.whu.edu.cn/codingCapacity/index.html.

Whole transcriptome analysis reveals that immune infiltration- lncRNAs are related to cellular apoptosis in liver transplantation

Introduction

In most instances, liver transplantation (LT) is the only available treatment for end-stage liver diseases. However, LT could also induce serious liver diseases or injury, and the underlying mechanisms of LT-induced complications remain largely unknown, especially the mechanisms of the dysfunction of the immune system mediated by long noncoding RNAs (lncRNAs).

Methods

In this study, we globally analyzed the proportion of immune cells by using the transcriptome sequencing data (RNA-seq) of needle-core liver biopsies from pre- and post-transplantation recipients. Dysregulated lncRNAs were found to be correlated with the altered fractions of immune cells. We finally explored the potential targets of dysregulated lncRNAs and analyzed their functions in LT.

Results

We found that in the samples, some immune cells changed significantly after LT, including CD4 T cells, NK cells and mast cells. The proportion of macrophages in different polarization states also changed significantly, with M0 macrophages increasing and M2 macrophages decreasing. Through weighted gene co-expression network analysis (WGCNA), 7 gene expression modules related to LT were identified. These modules were related to changes in the proportion of different immune cells. The functions of these modules represent the response modes of different functional genes after LT. Among these modules, MEtan and MEyellow modules were primarily enriched in apoptosis and inflammatory pathways. Twelve immunity-related lncRNAs were identified for the first time, and the regulatory network co-changing with immune cells was also identified. The co-expressed genes of these lncRNAs were highly enriched in apoptosis-related pathways. Many apoptosis-related genes were found to be up-regulated after LT.

Discussion

In summary, we speculated that the expression and regulation of these apoptotic genes may be related to the changes in the proportion of immune cells. Some of these lncRNAs and apoptosis-related genes have been reported to be related to cell proliferation and apoptosis. They are also potential biomarkers or therapeutic targets.

Advances in peptides encoded by non-coding RNAs: A cargo in exosome

The metastasis of malignant tumors determines patient prognosis. This is the main reason for the poor prognosis of patients with cancer and the most challenging aspect of treating malignant tumors. Therefore, it is important to identify early tumor markers and molecules that can predict patient prognosis. However, there are currently no molecular markers with good clinical accuracy and specificity. Many non-coding RNA (ncRNAs)have been identified, which can regulate the process of tumor development at multiple levels. Interestingly, some ncRNAs are translated to produce functional peptides. Exosomes act as signal carriers, are encapsulated in nucleic acids and proteins, and play a messenger role in cell-to-cell communication. Recent studies have identified exosome peptides with potential diagnostic roles. This review aims to provide a theoretical basis for ncRNA-encoded peptides or proteins transported by exosomes and ultimately to provide ideas for further development of new diagnostic and prognostic cancer markers.

A survey of the full-length transcriptome of Gracilariopsis lemaneiformis using single-molecule long-read sequencing

BACKGROUND

Posttranscriptional processing of precursor mRNAs contributes to transcriptome and protein diversity and gene regulatory mechanisms in eukaryotes. However, this posttranscriptional mechanism has not been studied in the marine macroalgae Gracilariopsis lemaneiformis, which is the most cultivated red seaweed species in China.

RESULTS

In the present study, third-generation sequencing (Pacific Biosciences single-molecule real-time long-read sequencing, SMRT-Seq) was used to sequence the full-length transcriptome of G. lemaneiformis to identify alternatively spliced transcripts and alternative polyadenylation (APA) sites in this species. RNAs were isolated from G. lemaneiformis under various treatments including abiotic stresses and exogenous phytohormones, and then equally pooled for SMRT-Seq. In summary, 346,544 full-length nonchimeric reads were generated, from which 13,630 unique full-length transcripts were obtained in G. lemaneiformis. Compared with the known splicing events in the gene models, more than 3000 new alternative splicing (AS) events were identified in the SMRT-Seq reads. Additionally, 810 genes were found to have poly (A) sites and 91 microRNAs (miRNAs), 961 long noncoding RNAs and 1721 novel genes were identified in G. lemaneiformis. Moreover, validation experiments showed that abiotic stresses and phytohormones could induce some specific AS events, especially intron retain isoforms, cause some alterations to the relative ratios of transcripts annotated to the same gene, and generate novel 3' ends because of differential APA. The growth of G. lemaneiformis was inhibited by Cu stress, while this inhibition was alleviated by ACC treatment. RNA-Seq analysis further revealed that 211 differential alternative splicing (DAS) events and 142 DAS events was obtained in CK vs Cu and Cu vs Cu + ACC, respectively, suggesting that AS of functional genes could be regulated by Cu stress and ACC. Compared with Cu stress, the expression of transcripts with DAS events mainly involved in the carbon fixation in photosynthetic organisms and oxidative phosphorylation pathway was upregulated in Cu + ACC treatment, revealing that ACC alleviated the growth inhibition by Cu stress by increasing carbon fixation and oxidative phosphorylation.

CONCLUSIONS

Our results provide the first comprehensive picture of the full-length transcriptome and posttranscriptional mechanism in red macroalgae, including transcripts that appeared in the presence of common abiotic stresses and phytohormones, which will improve the gene annotations of Gracilariopsis and contribute to the study of gene regulation in this important cultivated seaweed.

A large-scale benchmark study of tools for the classification of protein-coding and non-coding RNAs

Identification of protein-coding and non-coding transcripts is paramount for understanding their biological roles. Computational approaches have been addressing this task for over a decade; however, generalized and high-performance models are still unreliable. This benchmark study assessed the performance of 24 tools producing >55 models on the datasets covering a wide range of species. We have collected 135 small and large transcriptomic datasets from existing studies for comparison and identified the potential bottlenecks hampering the performance of current tools. The key insights of this study include lack of standardized training sets, reliance on homogeneous training data, gradual changes in annotated data, lack of augmentation with homology searches, the presence of false positives and negatives in datasets and the lower performance of end-to-end deep learning models. We also derived a new dataset, RNAChallenge, from the benchmark considering hard instances that may include potential false alarms. The best and least well performing models under- and overfit the dataset, respectively, thereby serving a dual purpose. For computational approaches, it will be valuable to develop accurate and unbiased models. The identification of false alarms will be of interest for genome annotators, and experimental study of hard RNAs will help to untangle the complexity of the RNA world.

LncBook 2.0: integrating human long non-coding RNAs with multi-omics annotations

LncBook, a comprehensive resource of human long non-coding RNAs (lncRNAs), has been used in a wide range of lncRNA studies across various biological contexts. Here, we present LncBook 2.0 (https://ngdc.cncb.ac.cn/lncbook), with significant updates and enhancements as follows: (i) incorporation of 119 722 new transcripts, 9632 new genes, and gene structure update of 21 305 lncRNAs; (ii) characterization of conservation features of human lncRNA genes across 40 vertebrates; (iii) integration of lncRNA-encoded small proteins; (iv) enrichment of expression and DNA methylation profiles with more biological contexts and (v) identification of lncRNA-protein interactions and improved prediction of lncRNA-miRNA interactions. Collectively, LncBook 2.0 accommodates a high-quality collection of 95 243 lncRNA genes and 323 950 transcripts and incorporates their abundant annotations at different omics levels, thereby enabling users to decipher functional significance of lncRNAs in different biological contexts.

Flnc: Machine Learning Improves the Identification of Novel Long Noncoding RNAs from Stand-Alone RNA-Seq Data

Long noncoding RNAs (lncRNAs) play critical regulatory roles in human development and disease. Although there are over 100,000 samples with available RNA sequencing (RNA-seq) data, many lncRNAs have yet to be annotated. The conventional approach to identifying novel lncRNAs from RNA-seq data is to find transcripts without coding potential but this approach has a false discovery rate of 30-75%. Other existing methods either identify only multi-exon lncRNAs, missing single-exon lncRNAs, or require transcriptional initiation profiling data (such as H3K4me3 ChIP-seq data), which is unavailable for many samples with RNA-seq data. Because of these limitations, current methods cannot accurately identify novel lncRNAs from existing RNA-seq data. To address this problem, we have developed software, Flnc, to accurately identify both novel and annotated full-length lncRNAs, including single-exon lncRNAs, directly from RNA-seq data without requiring transcriptional initiation profiles. Flnc integrates machine learning models built by incorporating four types of features: transcript length, promoter signature, multiple exons, and genomic location. Flnc achieves state-of-the-art prediction power with an AUROC score over 0.92. Flnc significantly improves the prediction accuracy from less than 50% using the conventional approach to over 85%. Flnc is available via GitHub platform.

Population transcriptomic analysis identifies the comprehensive lncRNAs landscape of spike in wheat (Triticum aestivum L.)

BACKGROUND

Long noncoding RNAs (lncRNAs) are emerging as the important regulators involving in growth and development as well as stress response in plants. However, current lncRNA studies were mainly performed at the individual level and the significance of it is not well understood in wheat.

RESULTS

In this study, the lncRNA landscape of wheat spike was characterized through analysing a total of 186 spike RNA-seq datasets from 93 wheat genotypes. A total of 35,913 lncRNAs as well as 1,619 lncRNA-mRNA pairs comprised of 443 lncRNAs and 464 mRNAs were obtained. Compared to coding genes, these lncRNAs displayed rather low conservation among wheat and other gramineous species. Based on re-sequencing data, the genetic variations of these lncRNA were investigated and obvious genetic bottleneck were found on them during wheat domestication process. Furthermore, 122 lncRNAs were found to act as ceRNA to regulate endogenous competition. Finally, association and co-localization analysis of the candidate lncRNA-mRNA pairs identified 170 lncRNAs and 167 target mRNAs significantly associated with spike-related traits, including lncRNA.127690.1/TraesCS2A02G518500.1 (PMEI) and lncRNA.104854.1/TraesCS6A02G050300.1 (ATG5) associated with heading date and spike length, respectively.

CONCLUSIONS

This study reported the lncRNA landscape of wheat spike through the population transcriptome analysis, which not only contribute to better understand the wheat evolution from the perspective of lncRNA, but also lay the foundation for revealing roles of lncRNA playing in spike development.

Characterization of peripheral white blood cells transcriptome to unravel the regulatory signatures of bovine subclinical mastitis resistance

Subclinical bovine mastitis is a pathogenic infection of the breast characterized by a marked decrease in milk production and quality. As it has no obvious clinical symptoms, diagnosis and treatment are challenging. Therefore, searching for biomarkers in cows’ peripheral white blood cells is valuable for preventing and treating subclinical mastitis. Thus, in this study, the transcriptome of peripheral blood from healthy and subclinical mastitis cows was characterized to find the regulatory signatures of bovine subclinical mastitis using RNA-seq. A total of 287 differentially expressed genes (DEGs) and 70 differentially expressed lncRNAs (DELs) were detected, and 37 DELs were documented near known Quantitative Trait Loci (QTL) associated with the mastitis of cows. Bioinformatic analysis indicated that lncRNAs MSTRG25101.2, MSTRG.56327.1, and MSTRG.18968.1, which are adjacent to the SCS QTL and SCC QTL, may be candidate lncRNAs that influence the pathogenesis of mastitis in cows by up-regulating the expression of genes TLR4, NOD2, CXCL8, and OAS2. Moreover, the alternative splicing (AS) pattern of transcriptional sequence differences between healthy cows and subclinical mastitis cows suggested a molecular mechanism of mastitis resistance and susceptibility. A total of 2,212 differential alternative splicing (DAS) events, corresponding to 1,621 unique DAS genes, were identified in both groups and significantly enriched in immune and inflammatory pathways. Of these, 29 DAS genes were subject to regulation by 32 alternative splicing SNPs, showing diverse and specific splicing patterns and events. It is hypothesized that the PIK3C2B and PPRPF8 splice variants associated with AS SNPs (rs42705933 and rs133847062) may be risk factors for susceptibility to bovine subclinical mastitis. Altogether, these key blood markers associated with resistance to subclinical mastitis and SNPs associated with alternative splicing of genes provide the basis for genetic breeding for resistance to subclinical mastitis in cows.