Resources

Genome Analysis and Technology Core

GATC Poster

Single Cell Genomics Capabilities in the SOM Genome Analysis & Technology Core PDF

10X Genomics Single Cell/Nuclei sample prep

Start with hundreds to hundreds of thousands of cells/nuclei. Follow best practices for washing, counting, and concentrating to minimize the presence of cellular aggregates, and retrieve high-quality single cell single/ nuclei suspensions ready for the 10X Genomics emulsion step.

Explore lab tested protocols by searching STAR Protocols an open access journal from Cell Press https://star-protocols.cell.com/

Here are additional protocols available from the vendor's web site:

Illumina Next Generation Sequencing

See Below Illumina resources to help you design your NGS project.

Planning an NGS experiment

Before starting your NGS experiments, please contact us for a free consultation on project design.

How to Match Your NGS Research Goal with Core Technologies

RNA-Seq experiments should be performed with at least three or more biological replicates.

The first step in any successful sequencing experiment is the preparation of the RNA to be sequenced. The number of RNA samples that can be analyzed on the core’s sequencers will depend on RNA quality, depth of sequencing needed (Goal) and Output of the sequencing kit.

NextSeq2000 P3 generates 1.2 to 1.4 Billion reads per run, while the P2 generates from 400-500 million reads.

Mi-Seq V2 and V3 sequencing kits can generate respectively 17 and 25 million reads per run. We also have MiSeq QC runs affording 1 M reads (nano kit) and 4M reads (micro kit) per run.

Below are recommendations for typical RNA-Seq applications.

Goal #1 : I want to focus on the coding transcriptome and I want to quantify gene expression at the gene level, with one abundance value generated per gene.	Method: Gene expression Profiling – mRNA-seq ≥ 25 Million reads per sample, 1 x 50 bp Library prep: mRNA stranded Next Seq P2: 16 sample pool Next Seq P3: 40 sample pool
Goal #2 : I want to focus on the RNA exome and I want to quantify gene expression by analyzing abundance values for every transcript isoform from each and identify novel transcript isoforms, SNVs, gene fusions, and/or identify allele-specific expression.	Method: mRNA-Seq ≥ 25 Millions reads per sample, 2 x 50 bp Library prep: mRNA stranded Next Seq P2: 16 sample pool Next Seq P3: 40 sample pool
Goal #3: I want to focus on the abundance values of both coding and multiple forms of noncoding RNA and identify novel transcript isoforms, SNVs, gene fusions, and/or identify allele-specific expression.	Method: Total RNA Sequencing – rRNA depleted ≥ 50 Million reads for QC samples, 2 x 50 bp ≥ 100 Million for degraded samples, 2 x 100 bp Library prep: stranded total RNA ribo-depletion Next Seq P2: 8 sample pool Next Seq P3: 20 sample pool

How to estimate and achieve the desired NGS Coverage for DNA sequencing will depends on the application used and best practice as recommended by the scientific community.

Whole genome recommendation is 10X to 30X, while CHIP-Seq is 100X.The Lander/Waterman equation is a method for computing coverage: C = LN / G. Thus, the total number of reads needed N =CxG/L, where C is the coverage, G size of haploid genome and L is the read length (e.g.100 base-long reads).

Examples of popular DNA sequencing applications are shown below (inquire for additional examples).

Goal #1: I want to sequence the known exome at 50X mean coverage	Method: Whole Exome Sequencing WES Next Seq P2: 9 sample Next Seq P3: 28 sample pool
Goal #2: I want to sequence a small genome 130 Mb at 30X coverage 2X150bp	Method: Small Whole Genome Sequencing Next Seq P2: 30 sample Next Seq P3: 90 sample pool
Goal #3: I want to sequence 12Mb region at 20X	Method: targeted sequencing Next Seq P2: 36 sample Next Seq P3: 110 sample pool
Goal #4: I want to sequence the 16S bacterial ribosomal genes	Methods: Metagenomics 16S MiSeq 600 Cycle kit, 25 Million reads Up to 96 samples

Storage requirements and performance parameters for the NextSeq 2000 Sequencing System

Table 1:

Read Length	Storage	Run Time/Output P2 flow cell	Run time/Output P3 flow cell
2 × 50 bp	20 GB	13 hours / 40GB	19 hours / 100GB
2 × 100 bp	40 GB	21 hours / 80GB	33 hours / 200GB
2 × 150 bp	55 GB	29 hours / 120GB	48 hours / 300GB

The instrument capacity as illustrate in Table 2 offers great flexibility in sample throughput.

Run Capacity

Table 2:

Applications	P2 Flow Cell	P3 Flow Cell
Sc. ATAC-Seq 50,000 reads/cell	3 samples	7 samples
Sc. 5’TCR/BCR 5,000 reads/cell	25 samples	65 samples
Sc. RNA Seq 20,000 reads/cell	7 samples	17 samples
Bulk mRNA Seq 25M reads/sample	16 samples	40 samples
Total RNA Seq 50M reads/sample	8 samples	20 samples
Whole Exome Seq 100X mean coverage	8 samples	20 samples
Sc. Single cell, TCR/BCR T or B cell receptor	samples	samples