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High-probability grants
According to our matching algorithm, Yin Shen is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2017 — 2021 |
Gan, Li Shen, Yin [⬀] Song, Hongjun (co-PI) [⬀] |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Functional Characterization of Alzheimer's Disease Associated Genetic Variants @ University of California, San Francisco
Project Summary/Abstract Alzheimer's disease (AD) is a devastating complex neurological degenerative disorder affecting 10% of people over 65 with no cure. The overarching goal of the proposed study is to identify and functionally characterize AD-associated SNPs utilizing novel functional genomic approaches and iPSC-derived cellular models. Our plans include: (1) Determine the functional significance of candidate SNPs in three iPSC-drived 2D AD relevant cell types. (2) Identify genes regulated by distal non-coding SNPs in three iPSC-drived 2D AD relevant cell types. (3) Test the biological consequences of high confidence AD rSNPs from (1) and (2) in isogenic iPSC- derived 2D cell cultures and 3D minibrain organoids. The designed study will be very first comprehensive investigation of AD associated SNPs, thus will shed light on how non-coding genetic variations contribute to AD. Obtaining knowledge for the fundamental genetic mechanisms of AD will expand our horizons to develop improved preventative and diagnostic methods, and also yield targets for novel therapeutic interventions, ultimately leading to a cure for AD.
|
0.966 |
2017 — 2021 |
Ren, Bing (co-PI) [⬀] Shen, Yin [⬀] |
UM1Activity Code Description: To support cooperative agreements involving large-scale research activities with complicated structures that cannot be appropriately categorized into an available single component activity code, e.g. clinical networks, research programs or consortium. The components represent a variety of supporting functions and are not independent of each component. Substantial federal programmatic staff involvement is intended to assist investigators during performance of the research activities, as defined in the terms and conditions of the award. The performance period may extend up to seven years but only through the established deviation request process. ICs desiring to use this activity code for programs greater than 5 years must receive OPERA prior approval through the deviation request process. |
High Throughput Crispr-Mediated Functional Validation of Regulatory Elements @ University of California, San Francisco
Project Summary The overarching goal of the proposed study is to functionally characterize a large number of candidate functional elements in the mammalian genome. The ENCODE projects have revealed millions of putative regulatory elements across more than one hundred cell types and tissues. While these maps have significantly expanded our knowledge of non-coding sequences, there are still large gaps between having descriptive maps of functional elements and understanding the biology of these elements underlying gene regulation. These include: (a) few candidate functional elements predicted by the ENCODE experiments are functionally validated; (b) Epigenomic studies have not given/revealed information on the target genes of candidate functional elements. Therefore, it is still a challenge to interpret the biological functions of non-coding DNA sequences. To address these issues, the objective of this UM1 application is to perform large scale functional characterization of candidate functional elements in their native chromatin context. We will first identify candidate regulatory elements utilizing ENCODE data and generate reporter tagged genes of interest in cell lines utilizing a high throughput, automated platform. Second, we will interrogate candidate functional elements in their native chromatin contexts utilizing two complementary high throughput CRIPSR/Cas9 mediated genome editing approaches. We anticipate these analyses will significantly advance our knowledge of the biological functions of candidate regulatory regions and gene regulation in mammalian cells.
|
0.966 |
2017 — 2021 |
Shen, Yin [⬀] |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Transcriptional Regulation of Best1 in Retina Pigment Epithelium. @ University of California, San Francisco
Abstract The overarching goal of this study is to understand how BEST1 expression is modulated by cis-regulatory elements in the retinal pigment epithelium (RPE). The variability of retinal phenotypes and age of onset of visual loss, even in individuals who carry the same causative mutation, is one of the biggest mysteries for BEST1 related diseases. Genetic variations in non-coding regulatory elements can serve as an attractive model to provide the molecular basis for the observed various onsets of BEST1 vitelliform macular dystrophy (BVMD) in patients. Therefore understanding the transcriptional control mediated by cis-regulatory elements in the RPE will give us insight into novel target regions for therapeutic editing of the enhancer elements identified by this study. We are utilizing human induced pluripotent stem cells (iPSCs)-derived RPEs as a model to understand cell type-specific transcriptional controls of BEST1. We are also utilizing integrative, unbiased, and high throughput epigenomic and genetic tools to achieve the following aims: (1) We will use a high resolution 4C-seq analysis to identify potential regulatory elements that interact with the BEST1 promoter in human primary RPE. (2) In Aim 2, we will generate BEST1 dual allele reporter lines and use these lines to interrogate cis-regulatory elements of BEST1 in their native chromatin contexts utilizing high throughput CRIPSR/Cas9 mediated genome editing approach. (3) Finally, we will test the utilities of allelic specific enhancer deletion to modulate allelic expression of BEST1. We expect these analyses will significantly advance our knowledge of the precise control of BEST1 transcription in RPEs.
|
0.966 |