Beibei Chen

Bio: Beibei Chen is an academic researcher from University of Texas Southwestern Medical Center. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 21, co-authored 32 publications receiving 2231 citations. Previous affiliations of Beibei Chen include Yale University & Chinese Academy of Sciences.

A community computational challenge to predict the activity of pairs of compounds

Abstract: Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

An Argonaute phosphorylation cycle promotes microRNA-mediated silencing

Abstract: MicroRNAs (miRNAs) perform critical functions in normal physiology and disease by associating with Argonaute proteins and downregulating partially complementary messenger RNAs (mRNAs). Here we use clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) genome-wide loss-of-function screening coupled with a fluorescent reporter of miRNA activity in human cells to identify new regulators of the miRNA pathway. By using iterative rounds of screening, we reveal a novel mechanism whereby target engagement by Argonaute 2 (AGO2) triggers its hierarchical, multi-site phosphorylation by CSNK1A1 on a set of highly conserved residues (S824-S834), followed by rapid dephosphorylation by the ANKRD52-PPP6C phosphatase complex. Although genetic and biochemical studies demonstrate that AGO2 phosphorylation on these residues inhibits target mRNA binding, inactivation of this phosphorylation cycle globally impairs miRNA-mediated silencing. Analysis of the transcriptome-wide binding profile of non-phosphorylatable AGO2 reveals a pronounced expansion of the target repertoire bound at steady-state, effectively reducing the active pool of AGO2 on a per-target basis. These findings support a model in which an AGO2 phosphorylation cycle stimulated by target engagement regulates miRNA:target interactions to maintain the global efficiency of miRNA-mediated silencing.

Genome-wide binding site analysis of FAR-RED ELONGATED HYPOCOTYL3 reveals its novel function in Arabidopsis development.

Abstract: FAR-RED ELONGATED HYPOCOTYL3 (FHY3) and its homolog FAR-RED IMPAIRED RESPONSE1 (FAR1), two transposase-derived transcription factors, are key components in phytochrome A signaling and the circadian clock. Here, we use chromatin immunoprecipitation–based sequencing (ChIP-seq) to identify 1559 and 1009 FHY3 direct target genes in darkness (D) and far-red (FR) light conditions, respectively, in the Arabidopsis thaliana genome. FHY3 preferentially binds to promoters through the FHY3/FAR1 binding motif (CACGCGC). Interestingly, FHY3 also binds to two motifs in the 178-bp Arabidopsis centromeric repeats. Comparison between the ChIP-seq and microarray data indicates that FHY3 quickly regulates the expression of 197 and 86 genes in D and FR, respectively. FHY3 also coregulates a number of common target genes with PHYTOCHROME INTERACTING FACTOR 3-LIKE5 and ELONGATED HYPOCOTYL5. Moreover, we uncover a role for FHY3 in controlling chloroplast development by directly activating the expression of ACCUMULATION AND REPLICATION OF CHLOROPLASTS5, whose product is a structural component of the latter stages of chloroplast division in Arabidopsis. Taken together, our data suggest that FHY3 regulates multiple facets of plant development, thus providing insights into its functions beyond light and circadian pathways.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling

Abstract: ‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.