Biology subjects

Leng, J.

Publications and source records attributed to Leng, J..

3 recordsLinked to original sources

bioRxiv2020

Nanoscale pattern extraction from relative positions of sparse 3D localisations

We present a method for extracting high-resolution ordered features from localisation microscopy data by analysis of relative molecular positions in 2D or 3D. This approach allows pattern recognition at sub-1% protein detection efficiencies, in large and heterogeneous samples, and in 2D and 3D datasets. We used this method to infer ultrastructure of the nuclear pore, the cardiomyocyte Z-disk, DNA origami structures and the centriole.

cell biology↗

bioRxiv2019

LESSeq: Local event-based analysis of alternative splicing using RNA-Seq data

Alternative splicing, which can be observed genome-wide by RNA-Seq, is important in cellular development and evolution. Comparative RNA-Seq experiments between different cellular conditions allow alternative splicing signatures to be detected. However, inferring alternative splicing signatures from short-read technology is unreliable and still presents many challenges before biologically significant signatures may be identified. To enable the robust discovery of differential alternative splicing, we developed the Local Event-based analysis of alternative Splicing using RNA-Seq (LESSeq) pipeline. LESSeq utilizes information of local splicing events (i.e., the partial structures in genes where transcript-splicing patterns diverge) to identify unambiguous alternative splicing. In addition, LESSeq quantifies the abundance of these alternative events using Maximum Likelihood Estimation (MLE) and provides their significance between different cellular conditions. The utility of LESSeq is demonstrated through two case studies relevant to human variation and evolution. Using an RNA-Seq data set of lymphoblastoid cell lines in two human populations, we examined within-species variation and discovered population-differential alternative splicing events. With an RNA-Seq data set of several tissues in human and rhesus macaque, we studied cross-species variation and identified lineage-differential alternative splicing events. LESSeq is implemented in C++ and R, and made publicly available on GitHub at: https://github.com/gersteinlab/LESSeq

bioinformatics↗

bioRxiv2018

Nationwide population genetic screening improves outcomes of newborn screening for hearing loss in China

PurposeConcurrent newborn hearing and genetic screening has been reported, but its benefits have not been statistically proven due to limited sample sizes and outcome data. To fill this gap, we analyzed outcomes of a large number of newborns with genetic screening results.\n\nMethodsNewborns in China were screened for 20 hearing-loss-related genetic variants from 2012-2017. Genetic results were categorized as positive, at-risk, inconclusive, or negative. Hearing screening results, risk factors, and up-to-date hearing status were followed-up via phone interviews.\n\nResultsWe completed genetic screening on one million newborns and followed up 12,778. We found that a positive genetic result significantly indicated a higher positive predictive value of the initial hearing screening (60% vs. 5.0%, P<0.001) and a lower rate of loss-to-follow-up (5% vs. 22%, P<0.001) than an inconclusive one. Importantly, 42% of subjects in the positive group with reported or presymptomatic hearing loss were \"missed\" by conventional hearing screening. Furthermore, genetic screening identified 0.23% of subjects predisposed to preventable ototoxicity.\n\nConclusionOur results demonstrate that limited genetic screening identified additional cases, reduced loss-to-follow-up, and informed families of ototoxicity risks, providing convincing evidence to support integrating genetic screening into universal newborn hearing screening programs.

genetics↗