Genomics and Genome Engineering
Investigators: Kristen Jepsen, Aaron Chang and Pedro Aza-Blanc
The Genomics and Genome Engineering Core (GGEC) provides researchers with a comprehensive array of tools and services for modern genomic analysis and genetic perturbation. It reduces the barrier to entry of next-generation sequencing and genome engineering technologies and maintains up-to-date methods, equipment and expertise in a rapidly-evolving field. It also offers training and education through one-on-one training sessions and workshops.
The GGEC represents a newly-formed partnership between three established and highly functional facilities on the Torrey Pines research mesa:the UCSD Institute for Genomic Medicine Genomics Center, the UCSD Center for Computational Biology & Bioinformatics, and the Sanford Burnham Prebys (SBP) Medical Discovery Institute Functional Genomics Facility.
The GGEC is co-directed by Drs. Kristen Jepsen, Aaron Chang, and Pedro Aza-Blanc. Dr. Jepsen, Director of the UCSD Genomics Center, has over 20 years of research experience in molecular biotechnology and many collaborative, high impact publications. For the past four years, she has been directly involved in generation of genome-wide data sets using next-generation sequencing approaches. Dr. Aaron Chang, Director of the UCSD Center for Computational Biology & Bioinformatics, has previously led bioinformatics groups at the Baylor Institute for Immunology Research in Dallas and at Regulus Therapeutics in La Jolla. At Regulus, Dr Chang’s team discovered two of the flagship miRNA targets for the company which are currently in Phase I development with biopharma partners. Dr. Aza-Blanc, Director of the Functional Genomics Facility at SBP, is an expert in cell-based assays and high throughput screening technology. He has 14 years of experience in functional genomics in academic and industry environments and has performed pioneering work in the application of high-throughput RNAi screening technology in mammalian target discovery and validation.
Sequencing library support
The GGEC supports library preparation protocols for individual research projects. These include but are not limited to RNA-seq, smallRNA-seq, GRO-seq, Ribo-Seq, ChIP-seq, ATAC-seq, and Exome sequencing.
Illumina platform sequencing
The GGEC currently operates HiSeq2500 instruments that can generate data on a large scale, running in either Rapid Run or High-output (V4 reagents) modes. This scale of data generation is applicable to RNA-Seq, miRNA-Seq, Gro-Seq, Ribo-Seq, ChIP-seq and other genome-wide approaches in mammalian systems. Investigators can also access an Illumina MiSeq Benchtop Sequencer, applicable to small genome sequencing, targeted resequencing, and multiplexed amplicon sequencing.
Raw sequencing files are assembled on reference genomes using commonly used alignment programs including Novoalign, BWA, OSA, and Bowtie. DNA variant analysis will be performed using GATK for germline analysis and MuTect, Freebayes, SomaticSniper, Varscan, and/or Strelka for somatic mutations. We will follow the best practices protocols as described by the bcbio pipeline package. Copy number variations will be identified using CNVnator or cn.MOPS. RNA-seq (conventional and small RNA) data analysis will be performed using a combination of RSEM for quantitation and DESeq for differential expression analysis.
Methylome analysis (Illumina HiScan)
DNA methylation for human samples will be interrogated using the Illumina 450K array which examines >485,000 methylation sites per sample at single-nucleotide resolution. Analysis of Illumina 450k methylation arrays is performed using the minfi R package available at bioconductor.org, which includes preprocessing, QC assessments, differential methylation and visualization of results starting from raw two-color channel IDAT files.
PacBio RS II sequencing
The PacBio RS II directly measures individual molecules, using long reads to fully characterize genetic complexity. Long reads are key in determining haplotype phasing, allowing identification of linked mutations hundreds or even thousands of bases apart. The long reads obtained on the PacBio can span entire cDNAs, allowing full characterization of splicing in the transcriptome. Current P6/C4 sequencing chemistry generates average read lengths of >10 kb with reads up to and greater than 40 kb.
Nanostring Technologies nCounter analysis
The nCounter Analysis Systerm is a cost-effective way to profile hundreds of mRNAs, microRNAs, or DNA targets with high sensitivity and precision. The nCounter is an imaging system that uses molecular “barcodes” to detect and count hundreds of unique transcripts in a single reaction without the bias introduced by PCR amplification.
High-throughput functional genomic cellular screening services
Cellular assays are adapted to siRNA transfection or lentiviral transduction (shRNAs or ORFs) conditions and scaled to a 384-well format. Following transfection/ transduction, cells are incubated for 2-6 days before the assay is read, using the Envision plate reader, Celigo Imaging Cytometer, or one of the high-throughput microscopes. Standard practices are used to perform statistical analysis of the data, and a report containing raw data and analyzed results is returned to the researcher. Screen hits are individually picked and retested to confirm their veracity. Additional siRNAs are used to independently validate each of the screening results.
Functional genomic lentiviral CRISPR-CAS9 screening services
The core offers two lentiviral CRISPR-CAS9 libraries. The Sabatini/Lander lenti-sgRNA library uses a dual vector system including an inducible CAS9 vector and covers 7114 targets with 10 sgRNAs per target. The library is organized into subsets such as kinases, cell cycle proteins or nuclear proteins. We also offer the Human Genome GeCKO v2 Library, which uses a 2-vector system and covers 21,700 genes with 6 sgRNA per target.
Cell line engineering services
Knock-out cell lines can be rapidly generated using Cas9 and an appropriate guide RNA. Depending on the Cas9 expression vector, these knock-outs can be either stable (pX458 expresses both Cas9 and eGFP for sorting by FACS) or inducible (pCW-Cas9). Stable knock-in cell lines can be generated
Submit a request for services here