Biology subjects

Luo, J.-H.

Publications and source records attributed to Luo, J.-H..

3 recordsLinked to original sources

bioRxiv2024

IFDlong: an isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data

Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearmans correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong.

bioinformatics↗

bioRxiv2021

Deconstruction of the retrosplenial granular cortex for social behavior in the mouse model of fragile X syndrome

Deficits in fragile X mental retardation 1 protein lead to fragile X syndrome (FXS) with mental retardation and social activity disorder. Until now, the neuronal circuits that mediate the social impairments of FXS were mostly unclear. Accidently, we found fewer c-fos expression in RSG of KO than WT mice after social behavior test. Inactivation of RSG neurons decreased social novelty but not the sociability of naive mice. Interestingly, although the RSG neurons of KO mice had higher background activity, fewer social contact-related Ca2+ neurons were observed during social interaction test via one-photon Ca2+ imaging in freely-behaving mice. Strikingly, enhancing the activity of RSG neurons rescued the abnormal social novelty in KO mice. Further studies proved that the innervations from the subiculum and ACC to RSG contributes to the social behavior. Take together, we found that abnormal activity in the retrosplenial granular cortex (RSG) led to social novelty deficits in Fmr1-knockout (KO) mice. Moreover, selective manipulation of RSG neurons may be an effective strategy to treat the social deficits in FXS. One Sentence SummaryDeletion of FMRP leads to lower social-related neuronal activity in the RSG; this causes social novelty deficits in Fmr1-KO mice.

neuroscience↗

bioRxiv2020

Targeted Transcriptome Analysis using Synthetic Long Read Sequencing Uncovers Isoform Reprograming in the Progression of Colon Cancer

Diversity in human gene expression stems, to a large extent, from splicing exons into multiple mRNA isoforms. Characterization of isoforms requires accurate long-read sequencing. However, read lengths, high error rates, low throughput and large input requirements are some of the challenges that remain to be addressed in sequencing technologies. In this study, we used a barcoding-based synthetic long read (SLR) isoform sequencing approach, LoopSeq, to generate sequencing reads sufficiently long and accurate to identify isoforms using standard short read Illumina sequencers. The method identifies isoforms from control RNA samples with 99.4% accuracy and a 0.01% per-base error rate, exceeding the accuracy reported for other long-read sequencing technologies. Applied to targeted transcriptome sequencing of over 10,000 genes from colon cancers and their metastatic counterparts, LoopSeq revealed large scale isoform redistributions from benign colon mucosa to primary colon cancer and metastatic cancer and identified several novel gene fusion isoforms in the colon cancer samples. Strikingly, our data showed that most single nucleotide variants (SNVs) occurred dominantly in specific isoforms and that some SNVs underwent isoform switching in cancer progression. The ability to use short read sequencers to generate accurate long-read isoform information as the raw unit of transcriptional information holds promise as a new and widely accessible approach in RNA isoform analyses.

genomics↗