Target-capture full-length double-strand cDNA sequencing for alternative splicing analysis

Computational Comparison of Differential Splicing Tools for Targeted RNA Long-Amplicon Sequencing (rLAS)

RNA sequencing (RNA-Seq) is a powerful technique for the quantification of transcripts and the analysis of alternative splicing. Previously, our laboratory developed the targeted RNA long-amplicon sequencing (rLAS) method, which has the advantage of allowing deep analysis of targeted specific transcripts. The computational tools for analyzing RNA-Seq data have boosted alternative splicing research by detecting and quantifying splicing events. However, the performance of these splicing tools has not yet been investigated for rLAS. Here, we evaluated the performance of four splicing tools (MAJIQ, rMATS, MISO, and SplAdder) using samples with different types of known splicing events (exon-skipping, multiple-exon-skipping, alternative 5' splicing, and alternative 3' splicing). MAJIQ was able to detect all of the types of events, but it was unable to detect one of the exon-skipping events. On the other hand, rMATS was able to detect all of the exon-skipping events. However, rMATS failed to detect other types of events besides exon-skipping events. Both MISO and SplAdder were unable to detect any of the events. These results indicate that MAJIQ presents better performance for the different types of splicing events in rLAS and that rMATS shows better performance for exon-skipping splicing events.

Integrated Analysis of Somatic DNA Variants and DNA Methylation of Tumor Suppressor Genes in Colorectal Cancer

DNA methylation of tumor suppressor genes in cancer is known to be a mechanism for silencing gene expression, but much remains unknown about its extent and relationship to somatic variants at the DNA sequence level. In this study, we comprehensively analyzed DNA methylation and somatic variants of all gene regions across the genome of the major tumor suppressor genes, APC, TP53, SMAD4, and mismatch repair genes in colorectal cancer using a novel next-generation sequencing-based analysis method. The Targeted Methyl Landscape (TML) shows that DNA hypermethylation patterns of these tumor suppressor genes in colorectal cancer are more complex and widespread than previously thought. Extremely high levels of DNA methylation were observed in relatively long regions around exon 1A of APC and exon 1 and surrounding region of MLH1. DNA hypermethylation occurred whether or not somatic DNA variants were present in the tumor. Even in tumors where the loss of heterozygosity has been demonstrated by somatic variants alone, additional methylation of the same gene can occur. Our data demonstrate that somatic variants and hypermethylation of these tumor suppressor genes were considered independent, parallel events, not exclusive of each other or having one event affecting the other.

The mntH gene of Burkholderia cenocepacia influences motility and quorum sensing to control virulence

Quorum sensing (QS) signals widely exist in bacteria to control biological functions in response to populations of cells. Burkholderia cenocepacia, an important opportunistic pathogen in patients with cystic fibrosis (CF), is commonly found in the environment and mostly utilizes the N-acylhomoserine lactone (AHL) and cis-2-dodecenoic acid (BDSF) QS systems to control biological functions. Our previous study illuminated the detailed mechanism by which B.cenocepacia integrates BDSF and cyclic diguanosine monophosphate (c-di-GMP) signals to control virulence. Here, we employed Tn5 transposon mutagenesis to identify genes related to the BDSF QS system. One of the most significantly attenuated mutants had an insertion in the mntH gene. Here, we showed that MntH (Bcam0836), a manganese transport protein, controls QS-regulated phenotypes, including motility, biofilm formation and virulence. We also found that. BDSF production was attenuated at both the gene and signaling levels in the Bcam0836 mutant, and that Bcam0836 influenced the expression of some genes regulated by the BDSF receptor RpfR and the downstream regulator GtrR. These results show that the manganese transport protein. MntH modulates a subset of genes and functions regulated by the QS system in B. cenocepacia.

CleanUpRNAseq: An R/Bioconductor Package for Detecting and Correcting DNA Contamination in RNA-Seq Data

RNA sequencing (RNA-seq) has become a standard method for profiling gene expression, yet genomic DNA (gDNA) contamination carried over to the sequencing library poses a significant challenge to data integrity. Detecting and correcting this contamination is vital for accurate downstream analyses. Particularly, when RNA samples are scarce and invaluable, it becomes essential not only to identify but also to correct gDNA contamination to maximize the data's utility. However, existing tools capable of correcting gDNA contamination are limited and lack thorough evaluation. To fill the gap, we developed CleanUpRNAseq, which offers a comprehensive set of functionalities for identifying and correcting gDNA-contaminated RNA-seq data. Our package offers three correction methods for unstranded RNA-seq data and a dedicated approach for stranded data. Through rigorous validation on published RNA-seq datasets with known levels of gDNA contamination and real-world RNA-seq data, we demonstrate CleanUpRNAseq's efficacy in detecting and correcting detrimental levels of gDNA contamination across diverse library protocols. CleanUpRNAseq thus serves as a valuable tool for post-alignment quality assessment of RNA-seq data and should be integrated into routine workflows for RNA-seq data analysis. Its incorporation into OneStopRNAseq should significantly bolster the accuracy of gene expression quantification and differential expression analysis of RNA-seq data.

Comparison of RNA-Sequencing Methods for Degraded RNA

RNA sequencing (RNA-Seq) is a powerful technique and is increasingly being used in clinical research and drug development. Currently, several RNA-Seq methods have been developed. However, the relative advantage of each method for degraded RNA and low-input RNA, such as RNA samples collected in the field of clinical setting, has remained unknown. The Standard method of RNA-Seq captures mRNA by poly(A) capturing using Oligo dT beads, which is not suitable for degraded RNA. Here, we used three commercially available RNA-Seq library preparation kits (SMART-Seq, xGen Broad-range, and RamDA-Seq) using random primer instead of Oligo dT beads. To evaluate the performance of these methods, we compared the correlation, the number of detected expressing genes, and the expression levels with the Standard RNA-Seq method. Although the performance of RamDA-Seq was similar to that of Standard RNA-Seq, the performance for low-input RNA and degraded RNA has decreased. The performance of SMART-Seq was better than xGen and RamDA-Seq in low-input RNA and degraded RNA. Furthermore, the depletion of ribosomal RNA (rRNA) improved the performance of SMART-Seq and xGen due to increased expression levels. SMART-Seq with rRNA depletion has relative advantages for RNA-Seq using low-input and degraded RNA.

An optimized cocktail of small molecule inhibitors promotes the maturation of dendritic cells in GM-CSF mouse bone marrow culture

Dendritic cells (DCs) are the most potent antigen-presenting cells, playing an essential role in the pathogen and tumor recognition, and anti-tumor immunity, and linking both the innate and adaptive immunity. The monocyte-derived DCs generated by ex vivo culture, have been used for cancer immunotherapy to eliminate tumor; however, the clinical efficacies are not sufficient, and further improvement is essential. In this study, we established a method to generate DCs using small molecule compounds for cancer immunotherapy. We observed an increase in the percentage of CD11c+I-A/I-Ehigh cells, representing DCs, by adding four small molecular inhibitors: Y27632, PD0325901, PD173074, and PD98059 (abbreviated as YPPP), in mouse bone marrow (BM) culture with granulocyte-macrophage colony stimulating factor (GM-CSF). BM-derived DCs cultured with YPPP (YPPP-DCs) showed high responsiveness to lipopolysaccharide stimulation, resulting in increased interleukin (IL) -12 production and enhanced proliferation activity when co-cultured with naïve T cells compared with the vehicle control. RNA-seq analysis revealed an upregulation of peroxisome proliferator - activated receptor (PPAR) γ associated genes increased in YPPP-DCs. In tumor models treated with anti-programmed death (PD) -1 therapies, mice injected intratumorally with YPPP-DCs as a DCs vaccine exhibited reduced tumor growth and increased survival. These findings suggested that our method would be useful for the induction of DCs that efficiently activate effector T cells for cancer immunotherapy.

Target-capture full-length double-stranded cDNA long-read sequencing through Nanopore revealed novel intron retention in patient with tuberous sclerosis complex

Tuberous sclerosis complex (TSC) is a relatively common autosomal dominant disorder characterized by multiple dysplastic organ lesions and neuropsychiatric symptoms caused by loss-of-function mutation of either TSC1 or TSC2. The genetic diagnosis of inherited diseases, including TSC, in the clinical field is widespread using next-generation sequencing. The mutations in protein-coding exon tend to be verified because mutations directly cause abnormal protein. However, it is relatively difficult to verify mutations in the intron region because it is required to investigate whether the intron mutations affect the abnormal splicing of transcripts. In this study, we developed a target-capture full-length double-stranded cDNA sequencing method using Nanopore long-read sequencer (Nanopore long-read target sequencing). This method revealed the occurrence of intron mutation in the TSC2 gene and found that the intron mutation produces novel intron retention splicing transcripts that generate truncated proteins. The protein-coding transcripts were decreased due to the expression of the novel intron retention transcripts, which caused TSC in patients with the intron mutation. Our results indicate that Nanopore long-read target sequencing is useful for the detection of mutations and confers information on the full-length alternative splicing of transcripts for genetic diagnosis.

A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing

Carcinoma of unknown primary (CUP) is a type of metastatic cancer with tissue-of-origin (TOO) unidentifiable by traditional methods. CUP patients typically have poor prognosis but therapy targeting the original cancer tissue can significantly improve patients' prognosis. Thus, it's critical to develop accurate computational methods to infer cancer TOO. While qPCR or microarray-based methods are effective in inferring TOO for most cancer types, the overall prediction accuracy is yet to be improved. In this study, we propose a cross-cohort computational framework to trace TOO of 32 cancer types based on RNA sequencing (RNA-seq). Specifically, we employed logistic regression models to select 80 genes for each cancer type to create a combined 1356-gene set, based on transcriptomic data from 9911 tissue samples covering the 32 cancer types with known TOO from the Cancer Genome Atlas (TCGA). The selected genes are enriched in both tissue-specific and tissue-general functions. The cross-validation accuracy of our framework reaches 97.50% across all cancer types. Furthermore, we tested the performance of our model on the TCGA metastatic dataset and International Cancer Genome Consortium (ICGC) dataset, achieving an accuracy of 91.09% and 82.67%, respectively, despite the differences in experiment procedures and pipelines. In conclusion, we developed an accurate yet robust computational framework for identifying TOO, which holds promise for clinical applications. Our code is available at http://github.com/wangbo00129/classifybysklearn .

Poly(A) capture full length cDNA sequencing improves the accuracy and detection ability of transcript quantification and alternative splicing events

The full-length double-strand cDNA sequencing, one of the RNA-Seq methods, is a powerful method used to investigate the transcriptome status of a gene of interest, such as its transcription level and alternative splicing variants. Furthermore, full-length double-strand cDNA sequencing has the advantage that it can create a library from a small amount of sample and the library can be applied to long-read sequencers in addition to short-read sequencers. Nevertheless, one of our previous studies indicated that the full-length double-strand cDNA sequencing yields non-specific genomic DNA amplification, affecting transcriptome analysis, such as transcript quantification and alternative splicing analysis. In this study, it was confirmed that it is possible to produce the RNA-Seq library from only genomic DNA and that the full-length double-strand cDNA sequencing of genomic DNA yielded non-specific genomic DNA amplification. To avoid non-specific genomic DNA amplification, two methods were examined, which are the DNase I-treated full-length double-strand cDNA sequencing and poly(A) capture full-length double-strand cDNA sequencing. Contrary to expectations, the non-specific genomic DNA amplification was increased and the number of the detected expressing genes was reduced in DNase I-treated full-length double-strand cDNA sequencing. On the other hand, in the poly(A) capture full-length double-strand cDNA sequencing, the non-specific genomic DNA amplification was significantly reduced, accordingly the accuracy and the number of detected expressing genes and splicing events were increased. The expression pattern and percentage spliced in index of splicing events were highly correlated. Our results indicate that the poly(A) capture full-length double-strand cDNA sequencing improves transcript quantification accuracy and the detection ability of alternative splicing events. It is also expected to contribute to the determination of the significance of DNA variants to splicing events.

A comparison of mRNA sequencing (RNA-Seq) library preparation methods for transcriptome analysis

BACKGROUND

mRNA sequencing is a powerful technique, which is used to investigate the transcriptome status of a gene of interest, such as its transcription level and splicing variants. Presently, several RNA sequencing (RNA-Seq) methods have been developed; however, the relative advantage of each method has remained unknown. Here we used three commercially available RNA-Seq library preparation kits; the traditional method (TruSeq), in addition to full-length double-stranded cDNA methods (SMARTer and TeloPrime) to investigate the advantages and disadvantages of these three approaches in transcriptome analysis.

RESULTS

We observed that the number of expressed genes detected from the TeloPrime sequencing method was fewer than that obtained using the TruSeq and SMARTer. We also observed that the expression patterns between TruSeq and SMARTer correlated strongly. Alternatively, SMARTer and TeloPrime methods underestimated the expression of relatively long transcripts. Moreover, genes having low expression levels were undetected stochastically regardless of any three methods used. Furthermore, although TeloPrime detected a significantly higher proportion at the transcription start site (TSS), its coverage of the gene body was not uniform. SMARTer is proposed to be yielded for nonspecific genomic DNA amplification. In contrast, the detected splicing event number was highest in the TruSeq. The percent spliced in index (PSI) of the three methods was highly correlated.

CONCLUSIONS

TruSeq detected transcripts and splicing events better than the other methods and measured expression levels of genes, in addition to splicing events accurately. However, although detected transcripts and splicing events in TeloPrime were fewer, the coverage at TSS was highest. Additionally, SMARTer was better than TeloPrime with regards to the detected number of transcripts and splicing events among the understudied full-length double-stranded cDNA methods. In conclusion, for short-read sequencing, TruSeq has relative advantages for use in transcriptome analysis.

Targeted Double-Stranded cDNA Sequencing-Based Phase Analysis to Identify Compound Heterozygous Mutations and Differential Allelic Expression

Simple Summary

Phase analysis to distinguish between in cis and in trans heterozygous mutations is important for clinical diagnosis because in trans compound heterozygous mutations cause autosomal recessive diseases. However, conventional phase analysis is limited because of the large target size of genomic DNA. Here, we performed a targeted double-stranded cDNA sequencing-based phase analysis to resolve the limitation of distance using direct adapter ligation library preparation and paired-end sequencing; we elucidated that two heterozygous mutations on a patient with Wilson disease are in trans compound heterozygous mutations. Furthermore, we detected the differential allelic expression. Our results indicate that a targeted double-stranded cDNA sequencing-based phase analysis is useful for determining compound heterozygous mutations and confers information on allelic expression.

Abstract

There are two combinations of heterozygous mutation, i.e., in trans, which carries mutations on different alleles, and in cis, which carries mutations on the same allele. Because only in trans compound heterozygous mutations have been implicated in autosomal recessive diseases, it is important to distinguish them for clinical diagnosis. However, conventional phase analysis is limited because of the large target size of genomic DNA. Here, we performed a genetic analysis on a patient with Wilson disease, and we detected two heterozygous mutations chr13:51958362;G>GG (NM_000053.4:c.2304dup r.2304dup p.Met769HisfsTer26) and chr13:51964900;C>T (NM_000053.4:c.1841G>A r.1841g>a p.Gly614Asp) in the causative gene ATP7B. The distance between the two mutations was 6.5 kb in genomic DNA but 464 bp in mRNA. Targeted double-stranded cDNA sequencing-based phase analysis was performed using direct adapter ligation library preparation and paired-end sequencing, and we elucidated they are in trans compound heterozygous mutations. Trio analysis showed that the mutation (chr13:51964900;C>T) derived from the father and the other mutation from the mother, validating that the mutations are in trans composition. Furthermore, targeted double-stranded cDNA sequencing-based phase analysis detected the differential allelic expression, suggesting that the mutation (chr13:51958362;G>GG) caused downregulation of expression by nonsense-mediated mRNA decay. Our results indicate that targeted double-stranded cDNA sequencing-based phase analysis is useful for determining compound heterozygous mutations and confers information on allelic expression.