Resources

Cofactor can produce single-end, paired-end, and mate-pair whole-genome libraries, bisulfite-converted whole genome methylation libraries, DNA binding protein, RNA binding protein, and histone modification ChIP-seq libraries, whole-transcriptome RNA libraries, small RNA libraries, Reduced Representation Sequencing (RRS) libraries, PCR product libraries, Barcoded/ Multiplexed libraries, and FFPE genomic libraries. Other libraries may be possible upon request.

Paired-end libraries provide additional longer-range linking information that allows reads that would otherwise have to be discarded to map back to more repetitive locations. They also allow for the detection of moderately sized indels. Current PE libraries sequence the read-length off of each end of the same DNA fragment (available for RNA/cDNAs too!) and have a defined ~200bp gap in the middle with known standard deviation.
Mate-pair libraries are essentially longer-insert paired-end libraries with insert sizes from 5 to 20kb.

Bisulfite conversion converts non-methylated C’s into Uracil’s that are converted to T’s after one round of PCR. After mapping, this can be used to identify the positions of all methyl-C’s in the genome.

ChIP libraries can be produced from any DNA or RNA you provide us that you have obtained by fragmentation, cross linking, co-immunoprecipitation with your favorite antibody of the DNA now cross-linked to the antibody’s target protein, and subsequent DNA/RNA purification. In this way, you can determine the actual binding sites of proteins in a whole-genome way.

By providing total RNA we can produce and sequence cDNA libraries that allow you to simultaneously define the entire transcribed portion of a genome as well as quantitate the level of transcription of each portion (genic or non-coding). This quantitation is as accurate as qRT- PCR and more broad than a microarray because it requires no a priori knowledge of putatively transcribed regions.
MicroRNA libraries are essentially the same as whole-transcriptome libraries but include only small fragments in a defined range (~20-40bp) that should include many types of non-coding RNAs. This allows you to both discover and quantitate the level of all small RNAs in a genome.

If you want to take measurements from a defined random subset of the genome (to reduce costs, for instance), we can construct libraries from bands of restriction digests so that you have high coverage over a smaller set of genome sites. This can be combined with most other types of libraries.

If you have PCR products or DNA isolated from Formalin-Fixed Paraffin-Embedded (FFPE) tissue, we can create sequencing libraries from these samples using specialized protocols.

There are currently 4 Next-Generation sequencing platforms, the Roche/454 Titanium, the Illumina, Ion Torrent and the Applied Biosystems SOLiD. Each has its own strengths and weaknesses that lead to a segmentation of uses by application. At Cofactor, if you can describe your research question, we can tell you the cost/benefit optimal platform or mix of platforms to achieve your goals.
Briefly:
The Roche/454 with Titanium chemistry has the longest reads at 350-500bp. They produce the most contiguous assemblies and can phase SNPs or other features into blocks. Errors occur mostly at the ends of longer homopolymers (same- nucleotide stretches). Mate-pair libraries can be constructed of many insert sizes (8kb - 20kb) but halve the read length for each end and have a low efficiency.
The Illumina has shorter reads at 36-150bp but produces up to 200 million reads per lane (8 or 16 lanes possible on a HiSeq 2000). The Illumina has the highest *raw* quality scores and its errors are mostly substitutions. All reads are the same length. Paired-end reads with a variety of insert sizes are possible with high efficiency and double the output of the machine by duplicating the read length on each end. Paired-end Illumina reads are suitable for de novo assemblies, especially in combination with the 454. The large number of reads makes the Illumina appropriate for de novo transcriptome studies with simultaneous discovery and quantification of RNAs at qRT-PCR accuracy.
The Applied Biosystems SOLiD has the shortest read length. As with the Illumina, Mate-Pairs double the output by duplicating the read length on each end, and the SOLiD supports a variety of insert lengths like the 454. The SOLiD can also run 2 slides at once to again double the output. SOLiD has the lowest *raw* base qualities but the highest processed base qualities when using a reference due to its 2-base encoding. Because of the number of reads and more advanced library types, we recommend the SOLiD for all RNA and bisulfite sequencing projects. The new IonPGMTM Personal Genome Machine made by Ion Torrent, a part of Life Technologies, employs a method of sequencing based on the detection of hydrogen ions released during polymerization of DNA. The Ion torrent generates reads of 100 -200 base pairs with data ranging from 10Mb to 1Gb based on the chip used. The 314 chip generates 10Mb, 316 generates 100Mb and 318 chip - 1Gb.The major benefits of ion semiconductor sequencing are rapid sequencing speed and affordable cost.
At Cofactor, platform choice and optimization is our job, you don’t have to worry.

When choosing how many reads you need purchase for your experiment, several factors come into play. Remember you do not have to decide this by yourself. Cofactor specialists will ensure you get the right number of reads for your experimental goal at no additional charge.
First, read start-site coverage is random across the genome, so the distribution of final read depth across sites is almost exactly as expected from a Poisson distribution. What does this mean? If you sequence 1x as many bases as your genome has sites, you will only cover 63% of the genome sites in the average experiment because many reads will overlap with each other. Therefore, you need to sequence more to overcome these random effects.
Second, although many next-gen platforms actually have lower-error rates (about 1 in 1,000) than traditional sequencing platforms, when you consider how many sites you are sequencing (millions or billions) those little errors add up. To get correct calls at a majority of sites, you need to sequence more.
Therefore, for standard diploid genomic-type projects, you need about 30x coverage of the genome. For de novo assembly, you need more like 100x coverage for current short-read assemblers to give decent results.
Third, if you are sequencing from a mixed population of samples, you need to sequence enough to ensure you have sampled from all constituent individuals. If you are sequencing a library of transformants, you need to sequence enough to observe your low-level transformants several times. For these types of experiments you may need a fold coverage 10 – 100 thousand.
Fourth, if you are sequencing from RNA, not all sites have the same expression level. Actually, gene expression in almost all organisms is given by a power-law distribution with a parameter of about 2. What does this mean? Some genes are very highly expressed and some have lower copies per total fragments of RNA. Because the distribution is so lop-sided, you need to sequence much more in total so that you have a sufficient number of counts of lowly-expressed genes to identify and quantitate them accurately. For the Human transcriptome, 40 million reads is a good starting place.
For larger and de novo projects, you should also consider a mixture of several platforms, long and short reads, and single and paired-end/mate-pair reads of various insert sizes. Cofactor software and experts can help you choose this mixture in a cost-optimal way for a variety of extant and simulated genomes.

The amount of data produced by Next-Gen sequencers is huge, therefore projects are shipped FedEx on fast external hard drives. You must have a computer with a USB2 port. Drives can be formatted for either PC or Mac/Linux. You will always receive the raw reads in FASTA, and FASTQ, as well as raw alignments and several analysis intermediates so that you may re-start your own analysis without going back to the beginning.
We are able to produce a custom computational analysis, which can consist of almost anything you dream up, existing or novel. The custom analysis will be placed on the drive and will consist of tab-delimited, FASTA, and/or image files customized to your experimental goals. Most projects are sufficiently specialized that no exact format or set of outputs is defined until we create them for your project. If you have an existing format that you would like your results in, we can produce output in that format for an additional charge.

Unlike some other service providers, Cofactor understands that many small labs have neither the need nor the budget for 100 million reads so we sell down to the individual sequencing unit for any number of libraries.
A given flowcell or slide can be mixed and matched with libraries types of the same ended-ness (single or paired/mate) from many projects and organisms.
However, if you purchase less than a full flowcell or slide, your samples must be run concurrently with samples from other customers to fill the batch so your wait time will be both longer and more variable. As mentioned above, you can pool your own separate experiments or experiments with your collaborators on a single flowcell or slide if you like.
You can do your part to minimize the total wait-time by submitting your samples as soon as you choose Cofactor, making your 1/2 upfront payment as quickly as possible, and ensuring that you have submitted sufficient, high-quality samples by assaying their quality before mailing.

The address for submitting samples (with accompanying gel pictures, and NanoDrop and Agilent Bioanalyzer traces) to Cofactor is:
Cofactor Genomics Attn: Sample Submission, 3139 Olive St. St. Louis, MO 63103 USA
Pictures/Traces can also be emailed ahead, to avoid delays due to poor-quality samples, to Sara Ahmed at sara_ahmed@cofactorgenomics.com
For all samples, we request that you submit the sample submission form. This will ensure easier tracking of your project, and will help us minimize the turnaround time.
For DNA samples, you are welcome to follow your favorite extraction method, as long as it preserves high-molecular-weight fragments. There should essentially be no migration, only a 1% agarose gel run for ~1 hour @ 120V.
The best cleanup method is phenol/chloroform extraction followed by ethanol precipitation with several washes. This tends to produce cleaner preps than columns. Samples must be treated with RNAse. Clean samples should have a 260/280 ratio between 1.7 and 1.9 and a 260/230 ratio >2. Samples should be resuspended in TE buffer and sent with a cold pack or dried down completely and sent at room temperature.
For genomic projects, you should submit a minimum of 5 micrograms (mg) of DNA at a minimum concentration of 100 nanograms / microliter. Double that amount would be optimal.
For ChIP-seq you can submit any total amount, provided there are at least 20 nanograms in the 150-250 basepair size range. You can observe this concentration-by-fragment-length distribution on a BioRad Experion or Agilent Bioanalyzer 2100. For the best results, the researcher should design the Chip-seq experiment with a control gene that can be used for qPCR validation of the library prior to shipment.
For RNA samples, we recommend the mirVana extraction kit from Ambion (http:// www.ambion.com/catalog/CatNum.php?1560). If you read the protocol, you will notice there are two paths through the protocol, one for total RNA and one for microRNAs. We recommend this kit for both–just follow the correct path for your sample.
The 260/280 ratio of your RNA sample should be >1.9, and your sample should be resuspended in nuclease-free or DEPC water. RNA samples should be mailed overnight on dry ice, or pelleted and dried at room temperature. Pelleting is the preferred method for international samples.
For microRNA projects, submit at least 30 micrograms of total RNA. For whole-transcriptome projects, submit at least 20 micrograms of total RNA. For PolyA projects, submit at least 20 micrograms. Cofactor will perform the microRNA or PolyA selection in-house, and even with the best methods, recovery is quite low. Thus, it is prudent to submit as much RNA as possible.
On a gel, high-quality RNA should have prominent 18S and 28S bands and a prominent smear from .5 to 12kb. On an Agilent Bioanalyzer 2100, RNA should have an RNA Integrity Number (RIN) >=8.

To ensure the highest quality, Cofactor has chosen to integrate and optimize across all facets of Next-Gen sequencing experiments, from library construction to sequencing to analysis. Cofactor cannot discount projects if you would like to make your own libraries or do your own analysis. If you would like us to refrain from analyzing your data for confidentiality reasons, we will honor your request and charge the standard price. You are welcome to submit your own libraries and pay the standard price, but Cofactor cannot make any guarantees about your data output or quality. It is our policy to re-run Cofactor libraries from QC'ed samples that fail, but this does not apply to customer-submitted libraries.

Once you have chosen Cofactor for your project, please submit your samples right away, without regard for the purchasing process. To do otherwise will cause unnecessary delays. To keep prices and working capital requirements low, and to keep schedules accurate and fair, Cofactor requires all customers to pay at least 50% of their total project up-front. The smallest of projects may need to be paid in full before services begin. We will email you a summary of your final analysis when it is complete, and require payment in full before we ship your data and analysis.
To keep the queue fair and prices low, understand that Cofactor is under no obligation to begin your libraries, sequencing, or analysis until your up-front payment is made. These delays are not factored into any expected wait time you are quoted. Delays at this stage will not result in a linear increase in wait time — rather they often push projects over critical points that result in discontinuous, cascading, non-linear increases in wait time.
When you are quoted, you will also receive a matching invoice for 50% of the total to be passed to your purchasing department who may contact us directly by phone (Johnitha Jones - 314.531.4647) or email (johnitha_jones@cofactorgenomics.com) to have Cofactor setup as a new vendor in your University’s or corporation’s database.
You are welcome to submit a PO for your order, but it will not be accepted as a form of up-front payment.
For your convenience, we accept payments by check, credit card, or wire transfer. International payments are accepted by wire-transfer only. You may simply call us at any time or leave a message with your credit card information.
Checks should be mailed to:
Cofactor Genomics
3139 Olive St.
St. Louis, MO 63103