Biology subjects

Li, P.

Publications and source records attributed to Li, P..

345 records · Page 20Linked to original sources

bioRxiv2017

PHASIS: A computational suite for de novo discovery and characterization of phased, siRNA-generating loci and their miRNA triggers

Phased, secondary siRNAs (phasiRNAs) are found widely in plants, from protein-coding transcripts and long, non-coding RNAs; animal piRNAs are also phased. Integrated methods characterizing \"PHAS\" loci are unavailable, and existing methods are quite limited and inefficient in handling large volumes of sequencing data. The PHASIS suite described here provides complete tools for the computational characterization of PHAS loci, with an emphasis on plants, in which these loci are numerous. Benchmarked comparisons demonstrate that PHASIS is sensitive, highly scalable and fast. Importantly, PHASIS eliminates the requirement of a sequenced genome and PARE/degradome data for discovery of phasiRNAs and their miRNA triggers.

bioinformatics↗

bioRxiv2017

Systematic Effects Of mRNA Secondary Structure On Gene Expression And Molecular Function In Budding Yeast

Dynamic control of gene expression is crucial for cellular adaptation to environmental challenges. mRNA secondary structure is known to be associated with mRNA and protein abundance, but little is known about how mRNA secondary structure affects gene expression dynamics. We report a genome-wide computational analysis of mRNA secondary structure, codon usage, and gene expression in budding yeast. We show that mRNA secondary structure combined with codon optimality regulates gene expression in multiple ways, from transcription to mRNA stability to translation. Moreover, we find that the effect of mRNA secondary structure on mRNA abundance is primarily mediated by transcription, not mRNA stability. Notably, genes with low mRNA secondary structure were substantially enriched for functions relevant to stress response, acting in the mitochondrion, endoplasmic reticulum, and ribosome. On the other hand, genes with high mRNA secondary structure were enriched for functions relevant to cellular maintenance, including macromolecular metabolism and biosynthesis. Our results suggest that mRNA secondary structure affects gene expression through coordination of multiple stages in protein biogenesis, with important consequences for stress response. The coupling of transcription to mRNA stability to translation makes concerted changes in mRNA and protein abundance possible and may amplify the effect of regulation to make quick responses to environmental variations.

genetics↗

bioRxiv2016

HBP: an integrative and flexible pipeline for the interaction analysis of Hi-C dataset

BackgroundThe spatial organization of interphase chromatin in the nucleus play an important role in gene expression regulation and function. With the rapid development of revolutionized chromosome conformation capture technology and its genome-wide derivatives such as Hi-C, investigation of the genome folding becomes more efficient and convenient. How to robustly deal with these massive datasets and infer accurate 3D model and within-nucleus compartmentalization of chromosomes becomes a new challenge.\n\nResultThe implemented pipeline HBP (Hi-C BED file analysis Pipeline) integrates existing pipelines focusing on individual steps of Hi-C data processing into an all-in-one package with adjustable parameters to infer the consensus 3D structure of genome from raw Hi-C sequencing data. Whats more, HBP could assign statistical confidence estimation for chromatin interactions, and clustering interaction loci according to enrichment tracks or topological structure automatically.\n\nConclusionThe freely available HBP is an optimized and flexible pipeline for analyzing the folding of whole chromosome and interactions between some specific sites from the Hi-C raw sequencing reads to the partially processed datasets. The other complex genetic and epigenetic datasets from public sources such as GWAS, ENCODE consortiums etc. will also easily be integrated into HBP, hence the final output results of HBP could provide a comprehensive in-depth understanding for the specific chromatin interactions, potential molecular mechanisms and biological significance. We believe that HBP is a reliable tool for the rapidly analysis of Hi-C data and will be very useful for a wide range of researchers, particularly those who lack of background in computational biology. HBP is freely accessible at https://github.com/hechao0407/HBP/blob/master/HBP_1.0.tar.gz.

bioinformatics↗