Biology subjects

Niu, L.

Publications and source records attributed to Niu, L..

41 records · Page 3Linked to original sources

bioRxiv2019

Amplification-free Library Preparation Improves Quality of Hi-C Analysis

PCR amplification of Hi-C libraries introduces unusable duplicates and results in a biased representation of chromatin interactions. We present a simplified, fast, and economically efficient Hi-C library preparation procedure that generates sufficient non-amplified ligation products for deep sequencing from 30 million Drosophila cells. Comprehensive analysis of the resulting data indicates that amplification-free Hi-C preserves higher complexity of chromatin interaction and lowers sequencing depth dramatically for the same number of unique paired reads. For human cells which has a large genome, this method recovers an amount of ligated fragments enough for direct high-throughput sequencing without amplification on as low as 250 thousand of cells. Comparison with published in situ Hi-C on millions of human cells reveals that amplification introduces distance-dependent amplification bias, which results in increasing background noise level against genomic distance. With amplification bias avoided, our method may produce a chromatin interaction network more faithfully reflecting the real three-dimensional genomic architecture.

genomics↗

bioRxiv2019

NWB:N 2.0: An Accessible Data Standard for Neurophysiology

Neurodata Without Borders: Neurophysiology (NWB:N) is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build common analysis tools for neurophysiology data. With NWB:N version 2.0 (NWB:N 2.0) we made significant advances towards creating a usable standard, software ecosystem, and vibrant community for standardizing neurophysiology data. In this manuscript we focus in particular on the NWB:N data standard schema and present advances towards creating an accessible data standard for neurophysiology.

neuroscience↗

bioRxiv2018

Plasma proteome profiling to detect and avoid sample-related biases in biomarker studies

Plasma and serum are rich sources of information regarding an individuals health state and protein tests inform medical decision making. Despite major investments, few new biomarkers have reached the clinic. Mass spectrometry (MS)-based proteomics now allows highly specific and quantitative read-out of the plasma proteome. Here we employ Plasma Proteome Profiling to define contamination marker panels to assess plasma samples and the likelihood that suggested biomarkers are instead artifacts related to sample handling and processing. We acquire deep reference proteomes of erythrocytes, platelets, plasma and whole blood of 20 individuals (>6000 proteins), and compare serum and plasma proteomes. Based on spike-in experiments we determine contamination-associated proteins, many of which have been reported as biomarker candidates as revealed by a comprehensive literature survey. We provide sample preparation guidelines and an online resource (www.plasmaproteomeprofiling.org) to assess overall sample-related bias in clinical studies and to prevent costly miss-assignment of biomarker candidates.

epidemiology↗

bioRxiv2018

Global Quantitative Mapping of Enhancers in Rice Genome by STARR-seq

Identification of enhancers has been a challenge in plants. STARR-seq measures enhancer activity of millions fragments in parallel. Here we present a global map of rice enhancers quantitatively determined using STARR-seq. Most enhancers are mapped within genes, especially at the 5 untranslated regions (5 UTR) and the coding sequences. Silent and low expressed genes in genomic regions enriched with transposable elements (TEs) are frequently found containing proximal enhancers. Analysis of enhancer epigenetic features at their endogenous loci revealed that most enhancers do not co-localize with DNase I hypersensitive sites (DHSs) and are lack of H3K4me1. Clustering enhancers by their epigenetic modifications revealed that about 40% of identified enhancers carry one or more epigenetic marks. Repressive H3K27me3 is frequently enriched with positive marks of H3K4m3 and/or H3K27ac, which together may bookmark poised enhancers. Intergenic enhancers were predicted based on the location of DHS relative to genes, which overlap poorly with functionally identified enhancers. In summary, enhancers were quantitatively identified by functional analysis in a model plant genome, which provides a valuable resource for further mechanistic studies in different biological contexts.

genomics↗

bioRxiv2018

Modified TCA/acetone precipitation of proteins for proteomic analysis

Protein extracts obtained from cells or tissues often require removal of interfering substances for the preparation of high-quality protein samples in proteomic analysis. A number of protein extraction methods have been applied to various biological samples. TCA/acetone precipitation and phenol extraction, a common method of protein extraction, is thought to minimize protein degradation and activity of proteases as well as reduce contaminants like salts and polyphenols. However, the TCA/acetone precipitation method relies on the complete pulverization and repeated rinsing of tissue powder to remove the interfering substances, which is laborious and time-consuming. In addition, by prolonged incubation in TCA/acetone, the precipitated proteins are more difficult to re-dissolve. We have described a modified method of TCA/acetone precipitation of plant proteins for proteomic analysis. Proteins of cells or tissues were extracted using SDS-containing buffer, precipitated with equal volume of 20% TCA/acetone, and washed with acetone. Compared to classical TCA/acetone precipitation and simple acetone precipitation, this protocol generates comparable yields, spot numbers, and proteome profiling, but takes less time (ca. 45 min), thus avoiding excess protein modification and degradation after extended-period incubation in TCA/acetone or acetone. The modified TCA/acetone precipitation method is simple, fast, and suitable for proteomic analysis of various plant tissues in proteomic analysis.

biochemistry↗