Person:
Cong, L

Profile Picture

Email Address

AA Acceptance Date

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Cong

First Name

L

Name

Cong, L

Filters

2012 - 20153

Settings

Author's Publications: search.filters.isAuthorOfPublication.ea2ed7bf-a6ae-4448-800d-3aa9e47961ee

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Publication
    Genome Engineering Technology and Its Application in Mammalian Cells
    (2014-06-06) Cong, L; Church, George McDonald; Zhang, Feng; Zhang, Yi; Hyman, Steven; Wong, Wilson; Cepko, Constance
    The advancement of high-throughput, large-scale biochemical, biophysical, and genetic technologies has enabled the generation of massive amounts of biological data and allowed us to synthesize various types of biomaterial for engineering purposes. This enabled improved observational methodologies for us to navigate and locate, with unprecedented resolution, the potential factors and connections that may contribute to biological and biomedical processes. Nonetheless, it leaves us with the increasing demand to validate these observations to elucidate the actual causal mechanisms in biology and medicine. Due to the lack of powerful and precise tools to manipulate biological systems in mammalian cells, these efforts have not been able to progress at an adequate pace.
  • Thumbnail Image
    Publication
    Sequence determinants of improved CRISPR sgRNA design
    (Cold Spring Harbor Laboratory Press, 2015) Xu, Han; Xiao, Tengfei; Chen, Chen-Hao; Li, Wei; Meyer, Clifford; Wu, Qiu; Wu, Di; Cong, L; Zhang, Feng; Liu, Jun; Brown, Myles; Liu, Xiaole
    The CRISPR/Cas9 system has revolutionized mammalian somatic cell genetics. Genome-wide functional screens using CRISPR/Cas9-mediated knockout or dCas9 fusion-mediated inhibition/activation (CRISPRi/a) are powerful techniques for discovering phenotype-associated gene function. We systematically assessed the DNA sequence features that contribute to single guide RNA (sgRNA) efficiency in CRISPR-based screens. Leveraging the information from multiple designs, we derived a new sequence model for predicting sgRNA efficiency in CRISPR/Cas9 knockout experiments. Our model confirmed known features and suggested new features including a preference for cytosine at the cleavage site. The model was experimentally validated for sgRNA-mediated mutation rate and protein knockout efficiency. Tested on independent data sets, the model achieved significant results in both positive and negative selection conditions and outperformed existing models. We also found that the sequence preference for CRISPRi/a is substantially different from that for CRISPR/Cas9 knockout and propose a new model for predicting sgRNA efficiency in CRISPRi/a experiments. These results facilitate the genome-wide design of improved sgRNA for both knockout and CRISPRi/a studies.
  • Thumbnail Image
    Publication
    Genome-Scale Promoter Engineering by Coselection MAGE
    (Nature Publishing Group, 2012) Wang, Harris He; Kim, Hwangbeom; Cong, L; Jeong, Jaehwan; Bang, Duhee; Church, George
    Multiplex Automated Genome Engineering (MAGE) employs short oligonucleotides to scarlessly modify genomes. However, insertions of >10 bases are still inefficient, but can be improved substantially by selection of highly modified chromosomes. Here, we describe Co-Selection MAGE (CoS-MAGE) to optimize biosynthesis of aromatic amino acid derivatives by combinatorially inserting multiple T7 promoters simultaneously into 12 genomic operons. Promoter libraries can be quickly generated to study gain-of-function epistatic interactions in gene networks.