Biology subjects

Luo, F.

Publications and source records attributed to Luo, F..

5 recordsLinked to original sources

bioRxiv2018

DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning

The Oxford Nanopore sequencing enables to directly detect methylation sites in DNA from reads without extra laboratory techniques. In this study, we develop DeepSignal, a deep learning method to detect DNA methylated sites from Nanopore sequencing reads. DeepSignal construct features from both raw electrical signals and signal sequences in Nanopore reads. Testing on Nanopore reads of pUC19, E. coli and human, we show that DeepSignal can achieve both higher read level and genome level accuracy on detecting 6mA and 5mC methylation comparing to previous HMM based methods. Moreover, DeepSignal achieves similar performance cross different methylation bases and different methylation motifs. Furthermore, DeepSignal can detect 5mC and 6mA methylation states of genome sites with above 90% genome level accuracy under just 5X coverage using controlled methylation data.

bioinformatics↗

bioRxiv2018

Transcriptome analysis of differential gene expression in Dichomitus squalens during interspecific mycelial interactions and the potential link with laccase induction

Interspecific mycelial interactions between white rot fungi are always accompanied by increased production of laccase. In this study, the potential of white rot fungi Dichomitus squalens for enhancing laccase production during interaction with two other white rot fungi Trametes versicolor or Pleurotus ostreatus was identified. To probe the mechanism of laccase induction and the role of laccase played during the combative interaction, we analyzed the laccase induction response to stressful conditions during fungal interaction related to the differential gene expression profile. We further confirmed the expression patterns of 16 selected genes by qRT-PCR analysis. We noted that many differential expression genes (DEGs) encoding proteins were involved in xenobiotics detoxification and ROS generation or reduction, including aldo/keto reductase, glutathione S-transferases, cytochrome P450 enzymes, alcohol oxidases and dehydrogenase, manganese peroxidase and laccase. Furthermore, many DEG-encoding proteins were involved in antagonistic mechanisms of nutrient acquisition and antifungal properties, including glycoside hydrolase, glucanase, chitinase and terpenoid synthases. DEGs analysis effectively revealed that laccase induction was likely caused by protective responses to oxidative stress and nutrient competition during fungal interspecific interaction.

bioinformatics↗

bioRxiv2017

N6-Methyladenine DNA Modification in Human Genome

DNA N6-methyladenine (6mA) modification is the most prevalent DNA modification in prokaryotes, but whether it exists in human cells and whether it plays a role in human diseases remain enigmatic. Here, we showed that 6mA is extensively present in human genome, and we cataloged 881,240 6mA sites accounting for [~]0.051% of the total adenines. [G/C]AGG[C/T] was the most significantly associated motif with 6mA modification. 6mA sites were enriched in the coding regions and mark actively transcribed genes in human cells. We further found that DNA N6-methyladenine and N6-demethyladenine modification in human genome were mediated by methyltransferase N6AMT1 and demethylase ALKBH1, respectively. The abundance of 6mA was significantly lower in cancers, accompaning with decreased N6AMT1 and increased ALKBH1 levels, and down-regulation of 6mA modification levels promoted tumorigenesis. Collectively, our results demonstrate that DNA 6mA modification is extensively present in human cells and the decrease of genomic DNA 6mA promotes human tumorigenesis.

genomics↗

bioRxiv2017

DNA 5-Hydroxymethylcytosines from Cell-free Circulating DNA as Diagnostic Biomarkers for Human Cancers

DNA modifications such as 5-methylcytosines (5mC) and 5-hydroxymethylcytosines (5hmC) are epigenetic marks known to affect global gene expression in mammals(1, 2). Given their prevalence in the human genome, close correlation with gene expression, and high chemical stability, these DNA epigenetic marks could serve as ideal biomarkers for cancer diagnosis. Taking advantage of a highly sensitive and selective chemical labeling technology(3), we report here genome-wide 5hmC profiling in circulating cell-free DNA (cfDNA) and in genomic DNA of paired tumor/adjacent tissues collected from a cohort of 90 healthy individuals and 260 patients recently diagnosed with colorectal, gastric, pancreatic, liver, or thyroid cancer. 5hmC was mainly distributed in transcriptionally active regions coincident with open chromatin and permissive histone modifications. Robust cancer-associated 5hmC signatures in cfDNA were identified with specificity for different cancers. 5hmC-based biomarkers of circulating cfDNA demonstrated highly accurate predictive value for patients with colorectal and gastric cancers versus healthy controls, superior to conventional biomarkers, and comparable to 5hmC biomarkers from tissue biopsies. This new strategy could lead to the development of effective blood-based, minimally-invasive cancer diagnosis and prognosis approaches.

cancer biology↗

bioRxiv2016

MECAT: an ultra-fast mapping, error correction and de novo assembly tool for single-molecule sequencing reads

The high computational cost of current assembly methods for the long, noisy single molecular sequencing (SMS) reads has prevented them from assembling large genomes. We introduce an ultra-fast alignment method based on a novel global alignment score. For large human SMS data, our method is 7X faster than MHAP for pairwise alignment and 15X faster than BLASR for reference mapping. We develop a Mapping, Error Correction and de novo Assembly Tool (MECAT) by integrating our new alignment and error correction methods, with the Celera Assembler. MECAT is capable of producing high quality de novo assembly of large genome from SMS reads with low computational cost. MECAT produces reference-quality assemblies of Saccharomyces cerevisiae, Arabidopsis thaliana, Drosophila melanogaster and reconstructs the human CHM1 genome with 15% longer NG50 in only 7600 CPU core hours using 54X SMS reads and a Chinese Han genome in 19200 CPU core hours using 102X SMS reads.

bioinformatics↗