We study computational and experimental RNA biology.

@article{pmid36449563,

title = {Single-Cell Analysis in Lung Adenocarcinoma Implicates RNA Editing in Cancer Innate Immunity and Patient Prognosis},

author = {Tracey W Chan and Jack P Dodson and Jaron Arbet and Paul C Boutros and Xinshu Xiao},

doi = {10.1158/0008-5472.CAN-22-1062},

issn = {1538-7445},

year  = {2023},

date = {2023-02-01},

journal = {Cancer Res},

volume = {83},

number = {3},

pages = {374--385},

abstract = {RNA editing modifies single nucleotides of RNAs, regulating primary protein structure and protein abundance. In recent years, the diversity of proteins and complexity of gene regulation associated with RNA editing dysregulation has been increasingly appreciated in oncology. Large-scale shifts in editing have been observed in bulk tumors across various cancer types. However, RNA editing in single cells and individual cell types within tumors has not been explored. By profiling editing in single cells from lung adenocarcinoma biopsies, we found that the increased editing trend of bulk lung tumors was unique to cancer cells. Elevated editing levels were observed in cancer cells resistant to targeted therapy, and editing sites associated with drug response were enriched. Consistent with the regulation of antiviral pathways by RNA editing, higher editing levels in cancer cells were associated with reduced antitumor innate immune response, especially levels of natural killer cell infiltration. In addition, the level of RNA editing in cancer cells was positively associated with somatic point mutation burden. This observation motivated the definition of a new metric, RNA editing load, reflecting the amount of RNA mutations created by RNA editing. Importantly, in lung cancer, RNA editing load was a stronger predictor of patient survival than DNA mutations. This study provides the first single cell dissection of editing in cancer and highlights the significance of RNA editing load in cancer prognosis.



SIGNIFICANCE: RNA editing analysis in single lung adenocarcinoma cells uncovers RNA mutations that correlate with tumor mutation burden and cancer innate immunity and reveals the amount of RNA mutations that strongly predicts patient survival. See related commentary by Luo and Liang, p. 351.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36424375,

title = {Kinetics of mRNA nuclear export regulate innate immune response gene expression},

author = {Diane Lefaudeux and Supriya Sen and Kevin Jiang and Alexander Hoffmann and },

doi = {10.1038/s41467-022-34635-5},

issn = {2041-1723},

year  = {2022},

date = {2022-11-01},

journal = {Nat Commun},

volume = {13},

number = {1},

pages = {7197},

abstract = {The abundance and stimulus-responsiveness of mature mRNA is thought to be determined by nuclear synthesis, processing, and cytoplasmic decay. However, the rate and efficiency of moving mRNA to the cytoplasm almost certainly contributes, but has rarely been measured. Here, we investigated mRNA export rates for innate immune genes. We generated high spatio-temporal resolution RNA-seq data from endotoxin-stimulated macrophages and parameterized a mathematical model to infer kinetic parameters with confidence intervals. We find that the effective chromatin-to-cytoplasm export rate is gene-specific, varying 100-fold: for some genes, less than 5% of synthesized transcripts arrive in the cytoplasm as mature mRNAs, while others show high export efficiency. Interestingly, effective export rates do not determine temporal gene responsiveness, but complement the wide range of mRNA decay rates; this ensures similar abundances of short- and long-lived mRNAs, which form successive innate immune response expression waves.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35961439,

title = {Improved zebra finch brain transcriptome identifies novel proteins with sex differences},

author = {Jingyan He and Ting Fu and Ling Zhang and Lucy Wanrong Gao and Michelle Rensel and Luke Remage-Healey and Stephanie A White and Gregory Gedman and Julian Whitelegge and Xinshu Xiao and Barney A Schlinger},

doi = {10.1016/j.gene.2022.146803},

issn = {1879-0038},

year  = {2022},

date = {2022-11-01},

journal = {Gene},

volume = {843},

pages = {146803},

abstract = {The zebra finch (Taeniopygia guttata), a representative oscine songbird species, has been widely studied to investigate behavioral neuroscience, most notably the neurobiological basis of vocal learning, a rare trait shared in only a few animal groups including humans. In 2019, an updated zebra finch genome annotation (bTaeGut1_v1.p) was released from the Ensembl database and is substantially more comprehensive than the first version published in 2010. In this study, we utilized the publicly available RNA-seq data generated from Illumina-based short-reads and PacBio single-molecule real-time (SMRT) long-reads to assess the bird transcriptome. To analyze the high-throughput RNA-seq data, we adopted a hybrid bioinformatic approach combining short and long-read pipelines. From our analysis, we added 220 novel genes and 8,134 transcript variants to the Ensembl annotation, and predicted a new proteome based on the refined annotation. We further validated 18 different novel proteins by using mass-spectrometry data generated from zebra finch caudal telencephalon tissue. Our results provide additional resources for future studies of zebra finches utilizing this improved bird genome annotation and proteome.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36054357,

title = {scAllele: A versatile tool for the detection and analysis of variants in scRNA-seq},

author = {Giovanni Quinones-Valdez and Ting Fu and Tracey W Chan and Xinshu Xiao},

doi = {10.1126/sciadv.abn6398},

issn = {2375-2548},

year  = {2022},

date = {2022-09-01},

journal = {Sci Adv},

volume = {8},

number = {35},

pages = {eabn6398},

abstract = {Single-cell RNA sequencing (scRNA-seq) data contain rich information at the gene, transcript, and nucleotide levels. Most analyses of scRNA-seq have focused on gene expression profiles, and it remains challenging to extract nucleotide variants and isoform-specific information. Here, we present scAllele, an integrative approach that detects single-nucleotide variants, insertions, deletions, and their allelic linkage with splicing patterns in scRNA-seq. We demonstrate that scAllele achieves better performance in identifying nucleotide variants than other commonly used tools. In addition, the read-specific variant calls by scAllele enables allele-specific splicing analysis, a unique feature not afforded by other methods. Applied to a lung cancer scRNA-seq dataset, scAllele identified variants with strong allelic linkage to alternative splicing, some of which are cancer specific and enriched in cancer-relevant pathways. scAllele represents a versatile tool to uncover multilayer information and previously unidentified biological insights from scRNA-seq data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}