Jin Zhang

Bio: Jin Zhang is an academic researcher from University of California, Davis. The author has contributed to research in topics: Gene knockdown & Messenger RNA. The author has an hindex of 39, co-authored 110 publications receiving 3861 citations. Previous affiliations of Jin Zhang include University of Alabama at Birmingham & University of Texas at Austin.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Abstract: Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

Methodological implementation of mixed linear models in multi-locus genome-wide association studies.

Abstract: The mixed linear model has been widely used in genome-wide association studies (GWAS), but its application to multi-locus GWAS analysis has not been explored and assessed. Here, we implemented a fast multi-locus random-SNP-effect EMMA (FASTmrEMMA) model for GWAS. The model is built on random single nucleotide polymorphism (SNP) effects and a new algorithm. This algorithm whitens the covariance matrix of the polygenic matrix K and environmental noise, and specifies the number of nonzero eigenvalues as one. The model first chooses all putative quantitative trait nucleotides (QTNs) with ≤ 0.005 P-values and then includes them in a multi-locus model for true QTN detection. Owing to the multi-locus feature, the Bonferroni correction is replaced by a less stringent selection criterion. Results from analyses of both simulated and real data showed that FASTmrEMMA is more powerful in QTN detection and model fit, has less bias in QTN effect estimation and requires a less running time than existing single- and multi-locus methods, such as empirical Bayes, settlement of mixed linear model under progressively exclusive relationship (SUPER), efficient mixed model association (EMMA), compressed MLM (CMLM) and enriched CMLM (ECMLM). FASTmrEMMA provides an alternative for multi-locus GWAS.

PRMT5 is required for cell-cycle progression and p53 tumor suppressor function.

Abstract: Protein arginine methyltransferases (PRMTs) mediate the transfer of methyl groups to arginines in proteins involved in signal transduction, transcriptional regulation and RNA processing. Tumor suppressor p53 coordinates crucial cellular processes, including cell-cycle arrest and DNA repair, in response to stress signals. Post-translational modifications and interactions with co-factors are important to regulate p53 transcriptional activity. To explore whether PRMTs modulate p53 function, we generated multiple cell lines in which PRMT1, CARM1 and PRMT5 are inducibly knocked down. Here, we showed that PRMT5, but not PRMT1 or CARM1, is essential for cell proliferation and PRMT5 deficiency triggers cell-cycle arrest in G1. In addition, PRMT5 is required for p53 expression and induction of p53 targets MDM2 and p21 upon DNA damage. Importantly, we established that PRMT5 knockdown prevents p53 protein synthesis. Furthermore, we found that PRMT5 regulates the expression of translation initiation factor eIF4E and growth suppression mediated upon PRMT5 knockdown is independent of p53 but is dependent on eIF4E. Taken together, we uncovered that arginine methyltransferase PRMT5 is a major pro-survival factor regulating eIF4E expression and p53 translation.

MicroRNA let-7c is downregulated in prostate cancer and suppresses prostate cancer growth

Abstract: Purpose Prostate cancer (PCa) is characterized by deregulated expression of several tumor suppressor or oncogenic miRNAs. The objective of this study was the identification and characterization of miR-let-7c as a potential tumor suppressor in PCa. Experimental Design Levels of expression of miR-let-7c were examined in human PCa cell lines and tissues using qRT-PCR and in situ hybridization. Let-7c was overexpressed or suppressed to assess the effects on the growth of human PCa cell lines. Lentiviral-mediated re-expression of let-7c was utilized to assess the effects on human PCa xenografts. Results We identified miR-let-7c as a potential tumor suppressor in PCa. Expression of let-7c is downregulated in castration-resistant prostate cancer (CRPC) cells. Overexpression of let-7c decreased while downregulation of let-7c increased cell proliferation, clonogenicity and anchorage-independent growth of PCa cells in vitro. Suppression of let-7c expression enhanced the ability of androgen-sensitive PCa cells to grow in androgen-deprived conditions in vitro. Reconstitution of Let-7c by lentiviral-mediated intratumoral delivery significantly reduced tumor burden in xenografts of human PCa cells. Furthermore, let-7c expression is downregulated in clinical PCa specimens compared to their matched benign tissues, while the expression of Lin28, a master regulator of let-7 miRNA processing, is upregulated in clinical PCa specimens. Conclusions These results demonstrate that microRNA let-7c is downregulated in PCa and functions as a tumor suppressor, and is a potential therapeutic target for PCa.

Using Multivariate Statistics

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The Self-Organizing Map

Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

Senescence-Associated Secretory Phenotypes Reveal Cell-Nonautonomous Functions of Oncogenic RAS and the p53 Tumor Suppressor

Abstract: PLoS BIOLOGY Senescence-Associated Secretory Phenotypes Reveal Cell-Nonautonomous Functions of Oncogenic RAS and the p53 Tumor Suppressor Jean-Philippe Coppe 1 , Christopher K. Patil 1[ , Francis Rodier 1,2[ , Yu Sun 3 , Denise P. Mun oz 1,2 , Joshua Goldstein 1¤ , Peter S. Nelson 3 , Pierre-Yves Desprez 1,4 , Judith Campisi 1,2* 1 Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America, 2 Buck Institute for Age Research, Novato, California, United States of America, 3 Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America, 4 California Pacific Medical Center Research Institute, San Francisco, California, United States of America Cellular senescence suppresses cancer by arresting cell proliferation, essentially permanently, in response to oncogenic stimuli, including genotoxic stress. We modified the use of antibody arrays to provide a quantitative assessment of factors secreted by senescent cells. We show that human cells induced to senesce by genotoxic stress secrete myriad factors associated with inflammation and malignancy. This senescence-associated secretory phenotype (SASP) developed slowly over several days and only after DNA damage of sufficient magnitude to induce senescence. Remarkably similar SASPs developed in normal fibroblasts, normal epithelial cells, and epithelial tumor cells after genotoxic stress in culture, and in epithelial tumor cells in vivo after treatment of prostate cancer patients with DNA- damaging chemotherapy. In cultured premalignant epithelial cells, SASPs induced an epithelial–mesenchyme transition and invasiveness, hallmarks of malignancy, by a paracrine mechanism that depended largely on the SASP factors interleukin (IL)-6 and IL-8. Strikingly, two manipulations markedly amplified, and accelerated development of, the SASPs: oncogenic RAS expression, which causes genotoxic stress and senescence in normal cells, and functional loss of the p53 tumor suppressor protein. Both loss of p53 and gain of oncogenic RAS also exacerbated the promalignant paracrine activities of the SASPs. Our findings define a central feature of genotoxic stress-induced senescence. Moreover, they suggest a cell-nonautonomous mechanism by which p53 can restrain, and oncogenic RAS can promote, the development of age-related cancer by altering the tissue microenvironment. Citation: Coppe JP, Patil CK, Rodier F, Sun Y, Mun oz DP, et al. (2008) Senescence-associated secretory phenotypes reveal cell-nonautonomous functions of oncogenic RAS and the p53 tumor suppressor. PLoS Biol 6(12): e301. doi:10.1371/journal.pbio.0060301 Introduction Cancer is a multistep disease in which cells acquire increasingly malignant phenotypes. These phenotypes are acquired in part by somatic mutations, which derange normal controls over cell proliferation (growth), survival, invasion, and other processes important for malignant tumorigenesis [1]. In addition, there is increasing evidence that the tissue microenvironment is an important determinant of whether and how malignancies develop [2,3]. Normal tissue environ- ments tend to suppress malignant phenotypes, whereas abnormal tissue environments such at those caused by inflammation can promote cancer progression. Cancer development is restrained by a variety of tumor suppressor genes. Some of these genes permanently arrest the growth of cells at risk for neoplastic transformation, a process termed cellular senescence [4–6]. Two tumor suppressor pathways, controlled by the p53 and p16INK4a/pRB proteins, regulate senescence responses. Both pathways integrate multiple aspects of cellular physiology and direct cell fate towards survival, death, proliferation, or growth arrest, depending on the context [7,8]. Several lines of evidence indicate that cellular senescence is a potent tumor-suppressive mechanism [4,9,10]. Many poten- tially oncogenic stimuli (e.g., dysfunctional telomeres, DNA PLoS Biology | www.plosbiology.org damage, and certain oncogenes) induce senescence [6,11]. Moreover, mutations that dampen the p53 or p16INK4a/pRB pathways confer resistance to senescence and greatly increase cancer risk [12,13]. Most cancers harbor mutations in one or both of these pathways [14,15]. Lastly, in mice and humans, a senescence response to strong mitogenic signals, such as those delivered by certain oncogenes, prevents premalignant lesions from progressing to malignant cancers [16–19]. Academic Editor: Julian Downward, Cancer Research UK, United Kingdom Received June 27, 2008; Accepted October 22, 2008; Published December 2, 2008 Copyright: O 2008 Coppe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Abbreviations: CM, conditioned medium; DDR, DNA damage response; ELISA, enzyme-linked immunosorbent assay; EMT, epithelial–mesenchymal transition; GSE, genetic suppressor element; IL, interleukin; MIT, mitoxantrone; PRE, presenescent; PrEC, normal human prostate epithelial cell; REP, replicative exhaustion; SASP, senescence-associated secretory phenotype; SEN, senescent; shRNA, short hairpin RNA; XRA, X-irradiation * To whom correspondence should be addressed. E-mail: jcampisi@lbl.gov [ These authors contributed equally to this work. ¤ Current address: Genomics Institute of the Novartis Research Foundation, San Diego, California, United States of America December 2008 | Volume 6 | Issue 12 | e301

Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Abstract: Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.