Biology subjects

Zeng, D.

Publications and source records attributed to Zeng, D..

3 recordsLinked to original sources

bioRxiv2018

Structure simulation of thrombopoietin receptor C-MPL with missense SNPs and its geographical distribution

Mpl is a key gene controlling the process of proliferation and differentiation of megakaryocyte and several studies reported that the mutation of mpl will even cause accurate megakaryocyte leukemia. By overlapping the missense mutation in NCBI and recorded SNP in 1000 genome database, we sorted out 4 SNPs(rs190983971, rs563996763, rs546510242, rs373621350) to find out its conformational changes. With Phyre v2.0, we simulated the secondary and tertiary structure change caused by the SNP and compared it with the original structure. The significant changes indicated its potential in leading to diseases associated with platelet reproduction. Finally, according to 1000 genome database, we constructed the geographically distribution of different populations and its SNPs carrying rate.

bioinformatics↗

bioRxiv2018

An Integrative Boosting Approach for Predicting Survival Time With Multiple Genomics Platforms

Recent technological advances have made it possible to collect multiple types of genomics data on the same set of patients. It is of great interest to integrate multiple genomics data types together for predicting disease outcomes. We propose a variable selection method, termed Integrative Boosting (I-Boost), that makes proper use of all available clinical and genomics data in predicting individual patient survival time. Through simulation studies and applications to data sets from The Cancer Genome Atlas, we demonstrate that I-Boost provides substantially higher prediction accuracy than existing variable selection methods. Using I-Boost, we show that (1) the integration of multiple genomics platforms with clinical variables significantly improves the prediction accuracy for survival time over the use of clinical variables alone; (2) gene expression values are typically more prognostic of survival time than other genomics data types; and (3) gene modules/signatures are at least as prognostic as the collection of individual gene expression data.

bioinformatics↗

bioRxiv2017

Separating an allele associated with late flowering and slow maturation of Arabidopsis thaliana from population structure

Genome-wide association analysis is a powerful tool to identify genomic loci underlying complex traits. However, the application in natural populations comes with challenges, especially power loss due to population stratification. Here, we introduce a bivariate analysis approach to a GWAS dataset of Arabidopsis thaliana. We demonstrate the efficiency of double-phenotype analysisto uncover hidden genetic loci masked by population structure via a series of simulations. In real data analysis, acommon allele, strongly confounded with population structure, is discovered to be associated with late flowering and slow maturation of the plant. The discovered genetic effect on flowering time is further replicated in independent datasets. Using Mendelian randomization analysis based on summary statistics from our GWAS and expression QTL scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis indicates that this locusis co-selected with flowering-time-related genes. The discovered pleiotropic genotypephenotype map provides new insights into understanding the genetic correlation of complex traits.

genetics↗