Identification Of Alternative Splicing Research Articles

RNA-binding protein AZGP1 inhibits epithelial cell proliferation by regulating the genes of alternative splicing in COPD

BackgroundChronic Obstructive Pulmonary Disease (COPD) is characterized by high morbidity, disability, and mortality rates worldwide. RNA-binding proteins (RBPs) might regulate genes involved in oxidative stress and inflammation in COPD patients. Single-cell transcriptome sequencing (scRNA-seq) offers an accurate tool for identifying intercellular heterogeneity and the diversity of immune cells. However, the role of RBPs in the regulation of various cells, especially AT2 cells, remains elusive. Materials and methodsA scRNA-seq dataset (GSE173896) and a bulk RNA-seq dataset acquired from airway tissues (GSE124180) were employed for data mining. Next, RNA-seq analysis was performed in both COPD and control patients. Differentially expressed genes (DEGs) were identified using criteria of fold change (FC ≥ 1.5 or ≤ 1.5) and P value ≤ 0.05. Lastly, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and alternative splicing identification analyses were carried out. ResultsRBP genes exhibited specific expression patterns across different cell groups and participated in cell proliferation and mitochondrial dysfunction in AT2 cells. As an RBP, AZGP1 expression was upregulated in both the scRNA-seq and RNA-seq datasets. It might potentially be a candidate immune biomarker that regulates COPD progression by modulating AT2 cell proliferation and adhesion by regulating the expression of SAMD5, DNER, DPYSL3, GBP5, GBP3, and KCNJ2. Moreover, AZGP1 regulated alternative splicing events in COPD, particularly DDAH1 and SFRP1, holding significant implications in COPD. ConclusionRBP gene AZGP1 inhibits epithelial cell proliferation by regulating genes participating in alternative splicing in COPD.

In silico Identification of Alternatively Spliced Variants from Transcriptome Data of Rice Lines Exhibiting Complete Panicle Exsertion

Alternative splicing (AS) is a molecular mechanism governing gene expression, particularly in plants, wherein a single gene can yield multiple mRNA transcripts, thereby diversifying the resulting protein isoforms. Panicle exsertion (PE) is an important trait associated with grain yield in rice. We deployed the mRNA sequencing (transcriptome) data from incompletely exserted panicle genotype, BPT-5204 and its ethyl methanesulphonate (EMS) mutant lines viz., CPE-109 and CPE-110 exhibiting completely exserted panicle for identification of Alternative Splicing (AS) events. Our systematic analysis using rMATS package revealed 414 and 368 genes alternatively spliced upon the comparison of CPE-109 with BPT-5204 and CPE-110 with BPT-5204 respectively. We identified alternative 3′ splice site (A3SS) as the predominant AS type upon comparison of CPE-109 with BPT-5204 (51.20% A3SS) and CPE-110 with BPT-5204 (48.91% A3SS) at panicle initiation stage. In total 23 and 19 genes emanated multiple transcripts via., AS. Remarkably, upon comparison of splicing data of CPE-109 with BPT-5204 and CPE-110 with BPT-5204, we found three common genes namely, Os07g0406600 encoding DDHD domain containing protein, Os10g0442100 encoding tRNA methyltransferase and Os04g0675800 encoding H0103C06.10 protein, that generated more than two transcripts via., AS. These genes can be further validated for determining its role in panicle exsertion through gene expression studies, overexpression and functional characterization.

Identification of alternative splicing associated with clinical features: from pan-cancers to genitourinary tumors.

Alternative splicing events (ASEs) are vital causes of tumor heterogeneity in genitourinary tumors and many other cancers. However, the clinicopathological relevance of ASEs in cancers has not yet been comprehensively characterized. By analyzing splicing data from the TCGA SpliceSeq database and phenotype data for all TCGA samples from the UCSC Xena database, we identified differential clinical feature-related ASEs in 33 tumors. CIBERSORT immune cell infiltration data from the TIMER2.0 database were used for differential clinical feature-related immune cell infiltration analysis. Gene function enrichment analysis was used to analyze the gene function of ASEs related to different clinical features in tumors. To reveal the regulatory mechanisms of ASEs, we integrated race-related ASEs and splicing quantitative trait loci (sQTLs) data in kidney renal clear cell carcinoma (KIRC) to comprehensively assess the impact of SNPs on ASEs. In addition, we predicted regulatory RNA binding proteins in bladder urothelial carcinoma (BLCA) based on the enrichment of motifs around alternative exons for ASEs. Alternative splicing differences were systematically analyzed between different groups of 58 clinical features in 33 cancers, and 30 clinical features in 24 cancer types were identified to be associated with more than 50 ASEs individually. The types of immune cell infiltration were found to be significantly different between subgroups of primary diagnosis and disease type. After integrating ASEs with sQTLs data, we found that 63 (58.9%) of the race-related ASEs were significantly SNP-correlated ASEs in KIRC. Gene function enrichment analyses showed that metastasis-related ASEs in KIRC mainly enriched Rho GTPase signaling pathways. Among those ASEs associated with metastasis, alternative splicing of GIT2 and TUBB3 might play key roles in tumor metastasis in KIRC patients. Finally, we identified several RNA binding proteins such as PCBP2, SNRNP70, and HuR, which might contribute to splicing differences between different groups of neoplasm grade in BLCA. We demonstrated the significant clinical relevance of ASEs in multiple cancer types. Furthermore, we identified and validated alternative splicing of TUBB3 and RNA binding proteins such as PCBP2 as critical regulators in the progression of urogenital cancers.

Advances in alternative splicing identification: deep learning and pantranscriptome.

In plants, alternative splicing is a crucial mechanism for regulating gene expression at the post-transcriptional level, which leads to diverse proteins by generating multiple mature mRNA isoforms and diversify the gene regulation. Due to the complexity and variability of this process, accurate identification of splicing events is a vital step in studying alternative splicing. This article presents the application of alternative splicing algorithms with or without reference genomes in plants, as well as the integration of advanced deep learning techniques for improved detection accuracy. In addition, we also discuss alternative splicing studies in the pan-genomic background and the usefulness of integrated strategies for fully profiling alternative splicing.

Identification of alternative splicing and RNA-binding proteins involved in myocardial ischemia-reperfusion injury.

Alternative splicing (AS) and RNA-binding proteins (RBPs) have been implicated in various cardiovascular diseases. Yet, a comprehensive understanding of their role in myocardial ischemia-reperfusion injury (MIRI) remains elusive. We aimed to identify potential therapeutic targets for MIRI by studying genome-wide changes in AS events and RBPs. We analyzed RNA-seq data from ischemia-reperfusion mouse models and the control group from the GSE130217 data set using Splicing Site Usage Variation Analysis software. We identified 28 regulated alternative splicing events (RASEs) and 47 differentially expressed RBP (DE-RBP) genes in MIRI. Most variable splicing events were involved in cassette exon, alternative 5' splice, alternative 3' splice, and retained intron types. Gene Ontology and Kyoto Encyclopedia of Genes (KOBAS 2.0 server) and Genomes pathway enrichment analyses showed that the differentially expressed variable splicing and RBP genes were mainly enriched in pathways related to myocardial function. The RBP-RASE network demonstrated a common variance relationship between DE-RBPs and RASEs, indicating that RBPs regulate variable shear events in MIRI. This study systematically identified important alterations in RASEs and RBPs in MIRI, expanding our understanding of the underlying pathogenesis of MIRI.

Genome-wide identification of alternative splicing and splicing regulated in immune infiltration in osteosarcoma patients.

Background: Osteosarcoma typically occurs in adolescents, and the survival rate of patients with metastatic and recurrent osteosarcoma remains low. Abnormal regulation of alternative splicing is associated with the development of osteosarcoma. However, there is no genome-wide analysis of the function and regulatory mechanisms of aberrant alternative splicing associated with osteosarcoma. Methods: Published transcriptome data on osteosarcoma (GSE126209) derived from osteosarcoma patient tissue were downloaded. Gene expression profiling by high-throughput sequencing was performed on 9 normal samples and 10 tumor samples for genome-wide identification of osteosarcoma-related alternative splicing events. The potential function of osteosarcoma-associated alternative splicing events was examined by immune infiltration and correlation analysis. Regulation of aberrantly expressed RNA-binding proteins (RBPs) related to alternative splicing in osteosarcoma was clarified by co-expression analysis. Results: A total of 63 alternative splicing events, which are highly credible and dominant, were identified. GO enrichment analysis indicated that alternative splicing may be closely related to the immune response process. Immune infiltration analysis showed significant changes in the percentages of CD8 T cells, resting memory CD4 T cells, activated memory CD4 T cells, monocytes, resting dendritic cells, and activated mast cells in tumors compared to normal tissues, indicating the involvement of these immune cell types in the occurrence of osteosarcoma. Moreover, the analysis identified alternative splicing events that were co-altered with resting memory CD4 T cells, resting dendritic cells, and activated mast cells, events that may be associated with regulation of the osteosarcoma immune microenvironment. In addition, a co-regulatory network (RBP-RAS-immune) of osteosarcoma-associated RBPs with aberrant alternative splicing and altered immune cells was established. These RBPs include NOP58, FAM120C, DYNC1H1, TRAP1, and LMNA, which may serve as molecular targets for osteosarcoma immune regulation. Conclusion: These findings allow us to further understand the causes of osteosarcoma development and provide a new research direction for osteosarcoma immunotherapy or targeted therapy.

Identification of Alternative Splicing in Proteomes of Human Melanoma Cell Lines without RNA Sequencing Data.

Alternative splicing is one of the main regulation pathways in living cells beyond simple changes in the level of protein expression. Most of the approaches proposed in proteomics for the identification of specific splicing isoforms require a preliminary deep transcriptomic analysis of the sample under study, which is not always available, especially in the case of the re-analysis of previously acquired data. Herein, we developed new algorithms for the identification and validation of protein splice isoforms in proteomic data in the absence of RNA sequencing of the samples under study. The bioinformatic approaches were tested on the results of proteome analysis of human melanoma cell lines, obtained earlier by high-resolution liquid chromatography and mass spectrometry (LC-MS). A search for alternative splicing events for each of the cell lines studied was performed against the database generated from all known transcripts (RefSeq) and the one composed of peptide sequences, which included all biologically possible combinations of exons. The identifications were filtered using the prediction of both retention times and relative intensities of fragment ions in the corresponding mass spectra. The fragmentation mass spectra corresponding to the discovered alternative splicing events were additionally examined for artifacts. Selected splicing events were further validated at the mRNA level by quantitative PCR.

Identification of Alternative Splicing and LncRNA Genes in Brain Tissues of Fetal Mice at Different Developmental Stages.

Brain development is an extremely complex and precisely regulated process, with about one-third of genes expressed and precisely regulated during brain development. This study aims to explore the molecular mechanisms involved in brain development. We first established the expression profile of long non-coding RNAs (lncRNAs) and mRNAs in brain tissues of fetal mice at 12.5d, 14.5d and 16.5d through high-throughput sequencing. Second, the associated functions, pathways, and networks of the co-differentially expressed lncRNAs and mRNAs were identified via Gene Ontology (GO), pathway analysis, and PPI network. After bioinformatic analysis and screening, 8 differentially expressed lncRNAs and mRNAs with the same genetic origin were verified by RT-qPCR analysis in brain tissues of fetal mice at different developmental stages. The data revealed that there were 972 co-differentially expressed lncRNAs and 992 codifferentially expressed mRNAs in brain tissues of fetal mice at 12.5d, 14.5d and 16.5d. And we discovered 125 differentially expressed lncRNAs and mRNAs, which have the same genetic origin, in brain tissues of fetal mice at 12.5d, 14.5d and 16.5d through sequencing results and bioinformatics analysis. Besides, we proved that 8 lncRNAs, which have had the same genetic origin as differentially expressed mRNAs, were prominently downregulated, while their maternal genes were upregulated during brain development in fetal mice. Our results preliminarily illustrated the differentially expressed lncRNAs and mRNAs, both of which were derived from the same parent genes, during brain development in fetal mice, which suggests that alternative splicing of lncRNA exists during brain development. Besides, our study provides a perspective on critical genes for brain development, which might be the underlying therapeutic targets for developmental brain diseases in children.

Genome-wide identification of alternative splicing associated with histone deacetylase inhibitor in cutaneous T-cell lymphomas.

Cutaneous T-cell lymphomas (CTCLs) are a kind of non-Hodgkin lymphoma that originates from skin, which is difficult to treat with traditional drugs. Human histone deacetylase inhibitors (HDACi) targeted therapy has become a promising treatment strategy in recent years, but some patients can develop resistance to the drug, leading to treatment failure. There are no public reports on whether alternative splicing (AS) and RNA binding proteins (RBP) affect the efficacy of targeted therapy. Using data from the Gene Expression Omnibus (GEO) database, we established a co-change network of AS events and RBP in CTCLs for the first time, and analyzed the potential regulatory effects of RBP on HDACi-related AS events. The dataset GSE132053, which contained the RNA sequence data for 17 HDACi samples, was downloaded and clean reads were aligned to the human GRCh38 genome by hierarchical indexing for spliced alignment of the transcripts, allowing four mismatches. Gene expression levels were evaluated using exons per million fragments mapped for each gene. Student’s t-tests were performed to evaluate the significance of changes in ratios for AS events, and regulated alternative splicing events (RASEs) were defined as events with p values less than 0.05. To sort the differentially expressed genes functional categories, Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways were identified using the KOBAS 2.0 server. The regulatory mechanisms of the RASEs and RBPs were evaluated using Pearson’s correlation coefficient. Seven indirect events of HDACi resistance or sensitivity were identified: NIR_5151_RP11-977G19.10, NIR_4557_IRAG2, NIR_11870_SUMO1, NIR_5347_ING4, NIR_17935_DNAJC2, NIR_17974_CBLL1, and NIR_422_SLC50A1. The potential regulatory relationships between RBPs and HDACi-sensitive RASEs were also analyzed. LEPR and HNRNPAO significantly affected NIR_11870_SUMO1, suggesting a potential regulatory relationship. Additionally, CNN1 may regulate NIR_5347_ING4, CNOT3 may regulate NIR_17935_DNAJC2, and DQX1 and LENG9 may regulate NIR_422_SLC5A1. Overall, our findings establish a theoretical foundation for the precise targeted treatment of CTCLs with HDACi.

ASTool: An Easy-to-Use Tool to Accurately Identify Alternative Splicing Events from Plant RNA-Seq Data

Alternative splicing (AS) is an essential co-transcriptional regulatory mechanism in eukaryotes. The accumulation of plant RNA-Seq data provides an unprecedented opportunity to investigate the global landscape of plant AS events. However, most existing AS identification tools were originally designed for animals, and their performance in plants was not rigorously benchmarked. In this work, we developed a simple and easy-to-use bioinformatics tool named ASTool for detecting AS events from plant RNA-Seq data. As an exon-based method, ASTool can detect 4 major AS types, including intron retention (IR), exon skipping (ES), alternative 5′ splice sites (A5SS), and alternative 3′ splice sites (A3SS). Compared with existing tools, ASTool revealed a favorable performance when tested in simulated RNA-Seq data, with both recall and precision values exceeding 95% in most cases. Moreover, ASTool also showed a competitive computational speed and consistent detection results with existing tools when tested in simulated or real plant RNA-Seq data. Considering that IR is the most predominant AS type in plants, ASTool allowed the detection and visualization of novel IR events based on known splice sites. To fully present the functionality of ASTool, we also provided an application example of ASTool in processing real RNA-Seq data of Arabidopsis in response to heat stress.

Two Nipped-B-Like Protein A (Nipbla) Gametologs in Chinese Tongue Sole (Cynoglossus semilaevis): The Identification of Alternative Splicing, Expression Pattern, and Promoter Activity Analysis

In mammals, the mutation of nipped-B-like protein (nipbl) leads to Cornelia de Lange Syndrome (CdLS), characterized by low birth weight, short stature, and structural abnormalities of the skeleton, heart, and gut. In Chinese tongue sole (Cynoglossus semilaevis), a typical marine fish exhibiting sexual size dimorphism, the nipbl homolog gene (nipped-B-like protein A (nipbla)) was also screened with female higher expression level by somatotropic and reproductive tissues’ transcriptomic analysis. In this study, two nipbla genes, namely, nipbla-w and nipbla-z, were identified from the W and Z chromosomes of C. semilaevis, respectively. Similar to other mammalian and fish species nipbl, the two homolog proteins of C. semilaevis contained two conserved domains, namely, cohesion_HEAT and Nipped-B_C. The phylogenetic tree analysis showed that these two nipbla gametolog proteins were first clustered together and then grouped with other fish species. At least two types of alternative splicing sites were observed in exon 12 of the nipbla-z gene, which produced nipbla-z-tv1 and nipbla-z-tv2. Also, the sex-biased expression patterns of different nipbla-w and nipbla-z transcripts in female and male tissues were revealed by quantitative PCR (qPCR). The highest expression level of nipbla-w was observed in female gonad. While nipbla-z-tv1 exhibited relatively high expression in the muscle, liver, gonad, and brain, nipbla-z-tv2 only showed its expression superiority in the muscle of male individuals. The promoter regions of nipbla genes were amplified, and their transcription activity was successfully verified by a dual-luciferase reporter system. After nipbla-w and nipbla-z knockdown in the brain cell lines by RNA interference, a series of growth-related genes were influenced, including Bone Morphogenetic Protein 4 (bmp4), Wnt Family Member 11 (wnt11), and Sprouty Related EVH1 Domain Containing 2 (spred2). The prediction of transcription factors suggested that c-Jun, sex-determining region Y (SRY), POU Class 1 Homeobox 1 (POU1F1a), myogenic differentiation antigen (MyoD), signal transducer and activator of transcription 5a (STAT5A), and nuclear factor I C (Nfic) might be the putative upstream regulatory factors for nipbla; among them, c-Jun has been verified to effectively regulate the transcriptional activity of nipbla. The identification of two nipbla genes provided important data for interpreting the sexual size dimorphism in C. semilaevis.

An Analysis Pipeline for Identification of RNA Modification, Alternative Splicing and Polyadenylation Using Third Generation Sequencing

Nanopore sequencing based on Oxford Nanopore Technologies (ONT) and Pacific BioSciences (PacBio) single-molecule real-time (SMRT) long-read isoform sequencing (Iso-Seq) have shown great potential in detecting post-transcriptional regulation. Direct RNA sequencing (DRS) has the advantages in capturing RNA modification due to without PCR amplification which is the limitation of the next-generation sequencing (NGS). Here, we provide a comprehensive computational procedure for the quantification of RNA modification in single-base resolution based on DRS data. Moreover, we also provide procedure on the identification of alternative splicing (AS) and alternative polyadenylation (APA) based on both DRS and PacBio Iso-Seq data. The entire step was based on two packages (Nanom6A and PRAPI), which were based on Python language on Linux system.Graphical abstract: The flowchart for identification of RNA modification, alternative splicing and alternative polyadenylation based on third generation sequencing technology., [摘要]基于 Oxford Nanopore Technologies (ONT) 和 Pacific 的纳米孔测序 BioSciences (PacBio) 单分子实时 (SMRT) 长读长异构体测序 (Iso-Seq) 在检测转录后调控方面显示出巨大潜力。直接 RNA测序 (DRS) 由于没有 PCR 扩增而在捕获 RNA 修饰方面具有优势，这是下一代测序(NGS)的限制。在这里，我们提供了一个全面的计算程序，用于基于 DRS 数据以单碱基分辨率量化 RNA 修饰。此外，我们还提供了基于 DRS 和 PacBio Iso-Seq 数据识别选择性剪接(AS)和选择性多聚腺苷酸化(APA)的程序。整个步骤基于两个包（Nanom6A 和 PRAPI），它们基于 Linux 系统上的 Python 语言。关键词： 纳米孔直接 RNA 测序，PacBio Iso-Seq，RNA 修饰， N 6 -甲基腺苷，选择性剪接，选择性多聚腺苷酸化图文摘要：基于第三代测序技术的RNA修饰、选择性剪接和选择性多聚腺苷酸化鉴定流程图。[背景]转录组为理解基因表达和生长发育的调控提供了深入的视角。 随着第三代测序技术的快速发展，基于长读长测序的数据在揭示转录后调控方面具有很大优势（ Smith et al ., 2019） 。转录后 调控被认为是一个复杂的生物学过程，在影响 RNA 的剪接、输出、定位和翻译方面发挥着重要作用（Keene，2007） 。例如，选择性多聚腺苷酸化 (APA) 在维持 RNA 的结构和稳定性方面起着至关重要的作用 （Di Giamartino等人，2011 年，Tian 和 Manley，2017 年） 。选择性剪接(AS) )根茎相关发育的调控 (Wang et al ., 2017)和激素反应(Zhang et al ., 2018) 。在与生物合成途径相关的关键基因中可以发现多种 AS 事件(Chen et al ., 2020) 。 PacBio Iso-Seq 可以在同种型范围内捕获全长 mRNA以分析 转录后处理事件，例如AS 和 APA （Rhoads 和 Au，2015 年） 。准确性和可靠性工具对于识别转录后事件很重要。短读平台上的AS base d可以被几个优秀的软件识别，如rMATS （Shen等人，2014 年）和 SUPPA2 （Trincado等人，2018 年） 。然而，由于转录组组装的限制，短读长平台在检测全长异构体方面表现出劣势（ Rhoads和 Au，2015 年） 。 TAPIS (Abdel-Ghany et al ., 2016)和 FLAIR (Tang et al ., 2020) 已被开发用于基于长读序列识别 AS 事件。然而，TAPIS 不提供转录后事件的定量分析（ Abdel -Ghany等，2016） 。 FLAIR 可以检测亚型，但缺少 APA 检测模块（Tang等 人。 , 2020) 。 因此，我们为AS 和 APA的识别和可视化提供了一个全面且用户友好的管道 (PRAPI) (Gao et al ., 2018) 。在这里，我们提供了使用基于 Iso-Seq 异构体和短读数据的 PRAPI 进行数据处理、可视化、识别 AS 和 APA 的详细程序。除了 PacBio 平台， Oxford Nanopore Technologies (ONT) 平台还应用了独特的测量方法，将 RNA 分子通过特殊孔隙的信息作为电信号保持 （Garalde等人，2018 年） ， 它可以识别包括N 6 -甲基腺苷 (m 6 A) (Linder et al ., 2015; Zhang et al ., 2019) 、假尿苷(Ψ) 和 2'-O-甲基化 (Nm)在内的 RNA 修饰 （贝吉克等人，2021） 基于天然 RNA 的单核苷酸分辨率。此外，Nanopore DRS 能够确定 RNA 二级结构(Aw et al ., 2021) ，并检测天然去折叠蛋白序列中的氨基酸(Hu et al ., 2021) 。基于 ONT 数据检测 RNA 修饰的方法已在包括Epinano在内的多个软件包中报告 （刘等人，2019） ， xPore （普拉坦瓦尼奇 等人，2021 年） ，MINES （洛伦兹等人，2020 年） ， NanoDoc (Ueda, 2021) 、Nanom6A (Gao et al ., 2021) 、 Tombo (斯托伊伯 等人，2017） 。 Epinano 、 xPore 、Nanom6A 和 MINES 可以实现单碱基分辨率的准确度。然而，由于依赖碱基调用错误， Epinano无法将 m 6 A 与其他修饰碱基（例如 m 1 A）区分开来（Liu et al ., 2019） 。此外， xPore需要 m 6 A writer 敲除线作为比较，并且可能由于其在 DRACH 基序中的强富集而存在偏差（Pratanwanich等人，2021） 。最后，MINES 仅检测到 4 个 RRACH 基序（AGACT、GGACA、GGACC 和 GGACT），而忽略了其他 8 个 RRACH 基序（Lorenz等人，2020） 。 Nanom6A提供了使用 Nanopore 直接 RNA 读数来鉴定定性和定量 m 6 A 的方法，基于XGBoost算法以单碱基分辨率修改，提供 m 6 A 的高精度全转录组鉴定、定量和序列上下文 (RRACH )修改（Gao et al ., 2021） 。在这项研究中，我们提供了详细的程序 定量精度高 以单碱基分辨率进行 RNA 修饰。简而言之，我们提供了基于 DRS 或 PacBio Iso-Seq 数据鉴定AS 、 APA 和 m 6 A的综合程序。用于 Nanom6A 和 PRAPI 分析的 Linux Bash Shell 和脚本现已在https://github.com/GuInNGS/NanoPrapi中提供 和https://github.com/Bio-protocol/Pipeline_for_Identification_m6A_AS_and_APA_with_Long_Read 。

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data.

As well as the typical analysis of RNA-Seq to measure differential gene expression (DGE) across experimental/biological conditions, RNA-seq data can also be utilized to explore other complex regulatory mechanisms at the exon level. Alternative splicing and polyadenylation play a crucial role in the functional diversity of a gene by generating different isoforms to regulate gene expression at the post-transcriptional level, and limiting analyses to the whole gene level can miss this important regulatory layer. Here, we demonstrate detailed step by step analyses for identification and visualization of differential exon and polyadenylation site usage across conditions, using Bioconductor and other packages and functions, including DEXSeq, diffSplice from the Limma package, and rMATS.

IsoSplitter: identification and characterization of alternative splicing sites without a reference genome.

Long-read transcriptome sequencing is designed to sequence full-length RNA molecules and advantageous for identifying alternative splice isoforms; however, in the absence of a reference genome, it is difficult to accurately locate splice sites because of the diversity of patterns of alternative splicing (AS). Based on long-read transcriptome data, we developed a versatile tool, IsoSplitter, to reverse-trace and validate AS gene “split sites” with the following features: (i) IsoSplitter initially invokes a modified SIM4 program to find transcript split sites; (ii) each split site is then quantified, to reveal transcript diversity, and putative isoforms are grouped into gene clusters; (iii) an optional step for aligning short reads is provided, to validate split sites by identifying unique junction reads, and revealing and quantifying tissue-specific alternative splice isoforms. We tested IsoSplitter AS prediction using data sets from multiple model and nonmodel plant species and showed that the IsoSplitter pipeline is efficient to handle different transcriptomes with high accuracy. Furthermore, we evaluated the IsoSplitter pipeline compared with that of the splice junction identification tools, Program to Assemble Spliced Alignments (PASA software needs a reference genome for AS identification) and AStrap, using data from the model plant Arabidopsis thaliana. We found that IsoSplitter determined more than twice as many AS events than AStrap analysis, and 94.13% of the IsoSplitter predicted AS events were also identified by the PASA analysis. Starting from a simple sequence file, IsoSplitter is an assembly-free tool for identification and characterization of AS. IsoSplitter is developed and implemented in Python 3.5 using the Linux platform and is freely available at https://github.com/Hengfu-Yin/IsoSplitter.

A Comprehensive Map of mRNAs and Their Isoforms across All 14 Renal Tubule Segments of Mouse.

The repertoire of protein expression along the renal tubule depends both on regulation of transcription and regulation of alternative splicing that can generate multiple proteins from a single gene. A full-length, small-sample RNA-seq protocol profiled transcriptomes for all 14 renal tubule segments microdissected from mouse kidneys. This study identified >34,000 transcripts, including 3709 that were expressed in a segment-specific manner. All data are provided as an online resource (https://esbl.nhlbi.nih.gov/MRECA/Nephron/). Many of the genes expressed in unique patterns along the renal tubule were solute carriers, transcription factors, or G protein-coupled receptors that account for segment-specific function. Mapping the distribution of transcripts associated with Wnk-SPAK-PKA signaling, renin-angiotensin-aldosterone signaling, and cystic diseases of the kidney illustrated the applications of the online resource. The method allowed full-length mapping of RNA-seq reads, which facilitated comprehensive, unbiased characterization of alternative exon usage along the renal tubule, including known isoforms of Cldn10, Kcnj1 (ROMK), Slc12a1 (NKCC2), Wnk1, Stk39 (SPAK), and Slc14a2 (UT-A urea transporter). It also identified many novel isoforms with segment-specific distribution. These included variants associated with altered protein structure (Slc9a8, Khk, Tsc22d1, and Scoc), and variants that may affect untranslated, regulatory regions of transcripts (Pth1r, Pkar1a, and Dab2). Full-length, unbiased sequencing of transcripts identified gene-expression patterns along the mouse renal tubule. The data, provided as an online resource, include both quantitative and qualitative differences in transcripts. Identification of alternative splicing along the renal tubule may prove critical to understanding renal physiology and pathophysiology.

Genome-Wide Identification and Characterization of Potato Long Non-coding RNAs Associated With Phytophthora infestans Resistance.

Long non-coding RNA (lncRNA) is a crucial regulatory mechanism in the plant response to biotic and abiotic stress. However, their roles in potato (Solanum tuberosum L.) resistance to Phytophthora infestans (P. infestans) largely remain unknown. In this study, we identify 2857 lncRNAs and 33,150 mRNAs of the potato from large-scale published RNA sequencing data. Characteristic analysis indicates a similar distribution pattern of lncRNAs and mRNAs on the potato chromosomes, and the mRNAs were longer and had more exons than lncRNAs. Identification of alternative splicing (AS) shows that there were a total of 2491 lncRNAs generated from AS and the highest frequency (46.49%) of alternative acceptors (AA). We performed R package TCseq to cluster 133 specific differentially expressed lncRNAs from resistance lines and found that the lncRNAs of cluster 2 were upregulated. The lncRNA targets were subject to KEGG pathway enrichment analysis, and the interactive network between lncRNAs and mRNAs was constructed by using GENIE3, a random forest machine learning algorithm. Transient overexpression of StLNC0004 in Nicotiana benthamiana significantly suppresses P. infestans growth compared with a control, and the expression of extensin (NbEXT), the ortholog of the StLNC0004 target gene, was significantly upregulated in the overexpression line. Together, these results suggest that lncRNAs play potential functional roles in the potato response to P. infestans infection.

Full-length transcriptome analysis of asparagus roots reveals the molecular mechanism of salt tolerance induced by arbuscular mycorrhizal fungi

Soil salinity is one of the most serious abiotic stresses that limit agricultural productivity and the distribution of crops worldwide. Arbuscular mycorrhizal fungi (AMF) can improve the salt tolerance of host plants. A systematic study on plant responses to AMF under salinity stress may provide insights into the acquired salt tolerance. Here, we performed transcriptome sequencing using the Oxford Nanopore Technologies (ONT) MinION platform for asparagus (Asparagus officinalis L.) roots with 4 treatments: non-inoculated plants under optimal growth conditions (NI), inoculated plants under optimal growth conditions (AMF), non-inoculated plants under salinity stress conditions (NI + S), and inoculated plants under salinity stress conditions (AMF + S). A total of 6124 differentially expressed transcripts (DETs) were determined. Based on Venn diagram analysis, 391 DETs were specially regulated by AMF under salinity stress rather than under optimal growth conditions, which may be linked to the salinity stress adaptation mediated by AMF. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed that these transcripts mainly involved the regulation of ROS-scavenging capacity, water and nutrient status, and cell wall synthesis and modification. Furthermore, 23 differentially expressed transcription factors (TFs) were identified in the NI + S and AMF + S comparison, which are known to be associated with plant abiotic and biotic stress responses and regulation. Moreover, the identification of alternative splicing (AS) events indicated a more comprehensive response to AMF at the post-transcriptional level, which mainly occurs in genes involved in cell wall-related processes, transport, regulation of transcription, and response to abiotic stimulus. These results provide important insights into the salt tolerance induced by AMF and a solid basis for the future enhancement of plant tolerance to salinity stress.

Modern Approaches for Transcriptome Analyses in Plants.

The collection of all transcripts in a cell, a tissue, or an organism is called the transcriptome, or meta-transcriptome when dealing with the transcripts of a community of different organisms. Nowadays, we have a vast array of technologies that allow us to assess the (meta-)transcriptome regarding its composition (which transcripts are produced) and the abundance of its components (what are the expression levels of each transcript), and we can do this across several samples, conditions, and time-points, at costs that are decreasing year after year, allowing experimental designs with ever-increasing complexity. Here we will present the current state of the art regarding the technologies that can be applied to the study of plant transcriptomes and their applications, including differential gene expression and coexpression analyses, identification of sequence polymorphisms, the application of machine learning for the identification of alternative splicing and ncRNAs, and the ranking of candidate genes for downstream studies. We continue with a collection of examples of these approaches in a diverse array of plant species to generate gene/transcript catalogs/atlases, population mapping, identification of genes related to stress phenotypes, and phylogenomics. We finalize the chapter with some of our ideas about the future of this dynamic field in plant physiology.

Identification of novel alternative splicing biomarkers for breast cancer with LC/MS/MS and RNA-Seq

BackgroundAlternative splicing isoforms have been reported as a new and robust class of diagnostic biomarkers. Over 95% of human genes are estimated to be alternatively spliced as a powerful means of producing functionally diverse proteins from a single gene. The emergence of next-generation sequencing technologies, especially RNA-seq, provides novel insights into large-scale detection and analysis of alternative splicing at the transcriptional level. Advances in Proteomic Technologies such as liquid chromatography coupled tandem mass spectrometry (LC–MS/MS), have shown tremendous power for the parallel characterization of large amount of proteins in biological samples. Although poor correspondence has been generally found from previous qualitative comparative analysis between proteomics and microarray data, significantly higher degrees of correlation have been observed at the level of exon. Combining protein and RNA data by searching LC–MS/MS data against a customized protein database from RNA-Seq may produce a subset of alternatively spliced protein isoform candidates that have higher confidence.ResultsWe developed a bioinformatics workflow to discover alternative splicing biomarkers from LC–MS/MS using RNA-Seq. First, we retrieved high confident, novel alternative splicing biomarkers from the breast cancer RNA-Seq database. Then, we translated these sequences into in silico Isoform Junction Peptides, and created a customized alternative splicing database for MS searching. Lastly, we ran the Open Mass spectrometry Search Algorithm against the customized alternative splicing database with breast cancer plasma proteome. Twenty six alternative splicing biomarker peptides with one single intron event and one exon skipping event were identified. Further interpretation of biological pathways with our Integrated Pathway Analysis Database showed that these 26 peptides are associated with Cancer, Signaling, Metabolism, Regulation, Immune System and Hemostasis pathways, which are consistent with the 256 alternative splicing biomarkers from the RNA-Seq.ConclusionsThis paper presents a bioinformatics workflow for using RNA-seq data to discover novel alternative splicing biomarkers from the breast cancer proteome. As a complement to synthetic alternative splicing database technique for alternative splicing identification, this method combines the advantages of two platforms: mass spectrometry and next generation sequencing and can help identify potentially highly sample-specific alternative splicing isoform biomarkers at early-stage of cancer.