Biology subjects

Li, J.-L.

Publications and source records attributed to Li, J.-L..

24 records · Page 2Linked to original sources

bioRxiv2020

Template-independent genome editing and repairing correct frameshift disease in vivo

Frameshift mutation caused by small insertions/deletions (indels) often generate truncated and non-functional proteins, which underlies 22% inherited Mendelian disorders in humans. However, there is no efficient in vivo gene therapy strategies available to date, especially in postmitotic systems. Here, we leveraged the non-homologous end joining (NHEJ) mediated non-random editing profiles to compensate the frameshift mutation in a USH1F mouse model - av3j. After treatment by the selected gRNA, about 50% editing products showed reading-frame restoration, and more than 70% targeted hair cells recovered mechanotransduction. In vivo treatment ameliorated the hearing and balance symptoms in homozygous mutant mice. Furthermore, a scale-up analysis of 114 gRNAs targeting 40 frameshift deafness mutations reveals that 65% loci have at least one gRNA with predicted therapeutic potential. Together, our study demonstrates that the NHEJ-mediated frame restoration is a simple and highly efficient therapeutic strategy for small-indel induced frameshift mutations.

neuroscience↗

bioRxiv2020

Reduction of neuronal activity mediated by blood-vessel regression in the brain

The brain vasculature supplies neurons with glucose and oxygen, but little is known about how vascular plasticity contributes to brain function. Using longitudinal in vivo imaging, we reported that a substantial proportion of blood vessels in the adult brain sporadically occluded and regressed. Their regression proceeded through sequential stages of blood-flow occlusion, endothelial cell collapse, relocation or loss of pericytes, and retraction of glial endfeet. Regressing vessels were found to be widespread in mouse, monkey and human brains. Both brief occlusions of the middle cerebral artery and lipopolysaccharide-mediated inflammation induced an increase of vessel regression. Blockage of leukocyte adhesion to endothelial cells alleviated LPS-induced vessel regression. We further revealed that blood vessel regression caused a reduction of neuronal activity due to a dysfunction in mitochondrial metabolism and glutamate production. Our results elucidate the mechanism of vessel regression and its role in neuronal function in the adult brain.

neuroscience↗

bioRxiv2020

Similarity between mutation spectra in hypermutated genomes of rubella virus and in SARS-CoV-2 genomes accumulated during the COVID-19 pandemic

Genomes of tens of thousands of SARS-CoV2 isolates have been sequenced across the world and the total number of changes (predominantly single base substitutions) in these isolates exceeds ten thousand. We compared the mutational spectrum in the new SARS-CoV-2 mutation dataset with the previously published mutation spectrum in hypermutated genomes of rubella - another positive single stranded (ss) RNA virus. Each of the rubella isolates arose by accumulation of hundreds of mutations during propagation in a single subject, while SARS-CoV-2 mutation spectrum represents a collection events in multiple virus isolates from individuals across the world. We found a clear similarity between the spectra of single base substitutions in rubella and in SARS-CoV-2, with C to U as well as A to G and U to C being the most prominent in plus strand genomic RNA of each virus. Of those, U to C changes universally showed preference for loops versus stems in predicted RNA secondary structure. Similarly, to what was previously reported for rubella, C to U changes showed enrichment in the uCn motif, which suggested a subclass of APOBEC cytidine deaminase being a source of these substitutions. We also found enrichment of several other trinucleotide-centered mutation motifs only in SARS-CoV-2 - likely indicative of a mutation process characteristic to this virus. Altogether, the results of this analysis suggest that the mutation mechanisms that lead to hypermutation of the rubella vaccine virus in a rare pathological condition may also operate in the background of the SARS-CoV-2 viruses currently propagating in the human population.

genetics↗

bioRxiv2020

A Comprehensive Multi-Center Cross-platform Benchmarking Study of Single-cell RNA Sequencing Using Reference Samples

Single-cell RNA sequencing (scRNA-seq) has become a very powerful technology for biomedical research and is becoming much more affordable as methods continue to evolve, but it is unknown how reproducible different platforms are using different bioinformatics pipelines, particularly the recently developed scRNA-seq batch correction algorithms. We carried out a comprehensive multi-center cross-platform comparison on different scRNA-seq platforms using standard reference samples. We compared six pre-processing pipelines, seven bioinformatics normalization procedures, and seven batch effect correction methods including CCA, MNN, Scanorama, BBKNN, Harmony, limma and ComBat to evaluate the performance and reproducibility of 20 scRNA-seq data sets derived from four different platforms and centers. We benchmarked scRNA-seq performance across different platforms and testing sites using global gene expression profiles as well as some cell-type specific marker genes. We showed that there were large batch effects; and the reproducibility of scRNA-seq across platforms was dictated both by the expression level of genes selected and the batch correction methods used. We found that CCA, MNN, and BBKNN all corrected the batch variations fairly well for the scRNA-seq data derived from biologically similar samples across platforms/sites. However, for the scRNA-seq data derived from or consisting of biologically distinct samples, limma and ComBat failed to correct batch effects, whereas CCA over-corrected the batch effect and misclassified the cell types and samples. In contrast, MNN, Harmony and BBKNN separated biologically different samples/cell types into correspondingly distinct dimensional subspaces; however, consistent with this algorithms logic, MNN required that the samples evaluated each contain a shared portion of highly similar cells. In summary, we found a great cross-platform consistency in separating two distinct samples when an appropriate batch correction method was used. We hope this large cross-platform/site scRNA-seq data set will provide a valuable resource, and that our findings will offer useful advice for the single-cell sequencing community.

genomics↗

bioRxiv2019

Genomic profiling of circulating tumor DNA reveals genetics and residual disease in NK/T lymphoma

BackgroundExtranodal NK/T-cell lymphoma, nasal type (ENTKL), is an aggressive hematological malignancy with poor prognosis. Early detection of tumors at initial diagnosis or during routine surveillance is important for improving survival outcomes. Molecular profiling of circulating tumor DNA (ctDNA) is a promising noninvasive tool for monitoring disease status. Here, we investigated the feasible of ctDNA detection in ENTKL. MethodsPlasma ctDNA was assessment were based on blood specimens that were collected from 65 patients recently diagnosed with ENKTL at the hematology medical center of Xinqiao Hospital, longitudinal samples collected under chemotherapy also included. Gene mutation spectrum of ENKTL was analyzed via cancer personalized profiling sequencing (CAPP-Seq). This study is registered with ClinicalTrials.gov (ChiCTR1800014813) ResultsFrom February 2017 to September 2019, 65 patients were enrolled, we found that the most frequently mutated genes were KMT2D (23.1%), APC (12.3%), ATM (10.8%), ASXL3 (9.2%), JAK3 (9.2%), SETD2 (9.2%), TP53 (9.2%), NOTCH1 (7.7%). The mutation frequencies of KMT2D was significantly higher in stage III-IV, and mutations in KMT2D, ASXL3 and JAK3 were significantly correlated with the metabolic tumor burden of the patients. Compared with tumor tissue DNA, ctDNA profiling showed good concordance. Serial ctDNA analysis showed that treatment with chemotherapy could decrease the number and mutation allele frequency of genes. Compared with PET/CT, ctDNA has more advantages for tracking residual disease in patients. In addition, we also found that mutated KMT2D predicted poor prognosis in patients. ConclusionCollectively, our results provide evidence that ctDNA may serve as a novel precision medicine biomarker in ENKTL.

genomics↗

bioRxiv2019

Patterns, Profiles, and Parsimony: dissecting transcriptional signatures from minimal single-cell RNA-seq output with SALSA

Single-cell RNA sequencing (scRNA-seq) technologies have precipitated the development of bioinformatic tools to reconstruct cell lineage specification and differentiation processes with single-cell precision. However, start-up costs and data volumes currently required for statistically reproducible insight remain prohibitively expensive, preventing scRNA-seq technologies from becoming mainstream. Here, we introduce single-cell amalgamation by latent semantic analysis (SALSA), a versatile workflow to address those issues from a data science perspective. SALSA is an integrative and systematic methodology that introduces matrix focusing, a parametric frequentist approach to identify fractions of statistically significant and robust data within single-cell expression matrices. SALSA then transforms the focused matrix into an imputable mix of data-positive and data-missing information, projects it into a latent variable space using generalized linear modelling, and extracts patterns of enrichment. Last, SALSA leverages multivariate analyses, adjusted for rates of library-wise transcript detection and cluster-wise gene representation across latent patterns, to assign individual cells under distinct transcriptional profiles via unsupervised hierarchical clustering. In SALSA, cell type assignment relies exclusively on genes expressed both robustly, relative to sequencing noise, and differentially, among latent patterns, which represent best-candidates for confirmatory validation assays. To benchmark how SALSA performs in experimental settings, we used the publicly available 10X Genomics PBMC 3K dataset, a pre-curated silver standard comprising 2,700 single-cell barcodes from human frozen peripheral blood with transcripts aligned to 16,634 genes. SALSA identified at least 7 distinct transcriptional profiles in PBMC 3K based on <500 differentially expressed Profiler genes determined agnostically, which matched expected frequencies of dominant cell types in peripheral blood. We confirmed that each transcriptional profile inferred by SALSA matched known expression signatures of blood cell types based on surveys of 15 landmark genes and other supplemental markers. SALSA was able to resolve transcriptional profiles from only [~]9% of the total count data accrued, spread across <0.5% of the PBMC 3K expression matrix real estate (16,634 genes x 2,700 cells). In conclusion, SALSA amalgamates scRNA-seq data in favor of reproducible findings. Furthermore, by extracting statistical insight at lower experimental costs and computational workloads than previously reported, SALSA represents an alternative bioinformatics strategy to make single-cell technologies affordable and widespread.

bioinformatics↗