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For all the questions your experiments generate, Cofactor can help provide the answers. This begins with a high level of expertise in library design and construction. Read about our Applications.
Applications
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For all the questions your experiments generate, Cofactor can help provide the answers. This begins with a high level of expertise in library design and construction. Read about our Applications.
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Introduction
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We invite you to contact us regardless of sample type or sample size. We have produced a large variety of libraries for multiple applications and from a wide range of sample types. We have outlined here several examples in some detail. For additional libraries, please feel free to contact us.
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Fragment
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Whole genome characterization by single-pass shotgun sequencing of fragments from total DNA, PCR products, etc.
Fragment reads are the most fundamental type of sequencing from DNA samples. Primarily, you use fragment reads to detect SNPs and small indels in previously sequenced genomes of any size. We recommend a minimum coverage of 10X - 10 times the genome size - for haploid genomes and at least 20X for diploids. This provides enough reads to (1) overcome any substantial gaps due to the random placement of reads, (2) overcome sequencing errors in individual reads, and (3) sample sufficiently from both alleles of a diploid genome. Fragment libraries are typically constructed from 5 micrograms of total DNA.
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Paired-End
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Whole genome characterization by shotgun sequencing from both ends of DNA fragments with ~200bp inserts. Specialty large inserts libraries are available upon request for an additional charge.
The Paired-End and Mate-Pair strategies are similar to those previously used to assemble large genomes, like Human and Mouse. Both “ends” of long pieces of DNA with a known size distribution are sequenced. In this way, assemblers can be assured that the reads must be placed within a defined distance of each other.
Paired-End (PE) reads are thus useful for two purposes. It is essential to use PE for any data we plan on assembling. This includes new genomes, genomes suspected to have significant structural variation from sequenced references, or novel transcriptomes.
PE reads can also be used to detect larger structural variants, including chromosomal rearrangements and large indels. The PE linking information can be used to check for significantly large sets of reads with unexpectedly large or small inserts or reads with ends on different chromosomes. PE libraries are similarly made from 5 micrograms of total DNA. Specialty long insert mate-pair libraries (select from 1-10kb inserts) require much larger amounts of DNA as all but the ends are discarded.
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ChIP-Seq
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Discovery & quantitation of protein-DNA interactions by sequencing DNA from immunoprecipitations.
If you can recover it by immunoprecipitation, we can sequence it. Cofactor has vast experience sequencing IP products from transcription factors, histone modifications, and even RNA binding-proteins. Companies like AbCam and Sigma produce antibodies targeting a vast array of proteins and their modifications. Alternatively, we can provide whole-epigenome profiling by sequencing the ChIP products of one or many histone modifications.
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- 1 lane/1 SOLiD barcode is usually sufficient for a transcription factor.
- Histone modifications should be treated more like whole-genome re-sequencing projects.
- For ChIP-seq, you can submit any total amount of DNA but it must include at least 20 nano-grams of DNA in the 150-250 bp size range for Illumina or in the 100-200 bp size range for SOLiD.
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MicroRNA
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Discovery & quantitation of novel microRNAs and isoforms by sequencing cDNAs of microRNAs isolated from total RNA.
Similar to RNA-seq, microRNA sequencing samples quantitatively from the entire small RNA population of the cell, including most RNAs smaller than tRNAs. From this data we can simultaneously discover the expressed microRNA population of the sample as well as build an expression profile that can be compared to other samples.
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- Submit 20 micrograms of total RNA to Cofactor and we will extract the microRNAs, make the cDNAs, construct libraries, sequence and analyze.
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Transcriptome
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Quantitative whole transcriptome profiling (RNA-seq) by sequencing cDNAs constructed from messenger RNA isolated from total RNA.
RNA-Seq is the most popular application at Cofactor. By sampling randomly from total RNA, RNA-Seq yields counts that are as quantitative as qRT-PCR but across a space more broad than a microarray - the entire transcriptome. RNA-Seq is also quantitative over more than five orders of magnitude giving it a much wider dynamic range than microarrays, which are compressed at both the top and bottom ends of detection.
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- To avoid a large number of counts going to highly-expressed ribosomal genes, Cofactor will also perform a PolyA selection or Ribo-Depletion on your sample, depending on the application and your sample.
- RNA-Seq can be combined with Paired-Ends for sequencing transcriptomes from non-model organisms which lack a reference sequence. Even if you do not need the expression data, RNA-Seq can also be a more cost effective strategy for sequencing the gene space of an organism not previously sequenced.
- RNA-Seq profiles are also more versatile than microarray expression profiles as they are amazingly reproducible and can represent an absolute rather than relative quantitation. In this way, data sets produced over many runs can be easily compared. Further, it is possible to make gene-to-gene comparisons instead of only treatment-to-treatment comparisons of the same gene given by a microarray.
- Just submit 10 micrograms of total RNA to Cofactor and let us do the rest.
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Bisulfite
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Genome methylation profiling by sequencing DNA fragments bisulfite treated to convert non-methylated C’s into U's.Using bisulfite conversion, we can determine the positions of all methylated C’s in the genome. This chemical process modifies non-methylated C's so that following PCR they are sequenced as A's. By mapping these reads back to the genome using highly-specialized alignment tools, we can observe originally methylated C's by looking for columns of our bisulfite-induced C to A "mismatches."Tips:
- DNA methylation is just one epigenomic modification that can be revealed by sequencing.
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Capture
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Single-nucleotide polymorphism and insertion/deletion detection by targeted selection and sequencing of discreet genomic regions of interest. Targeted genomic selection is a relatively new technology that enables researchers to investigate variation in specific regions of a genome, at a lower cost and turnaround time, as compared to whole genome sequencing. Cofactor Genomics used the Agilent and Roche kits to selectively isolate, amplify and sequence regions from many types of genomic samples. The analysis output from this type of experiment consists of SNP and indel detection. Cofactor is able to perform whole-exome or custom capture experiments.We recommend a minimum coverage of approximately 100X – 100 times the combined base pair number of all genome targets – for capture experiments. This provides enough reads to overcome (1) the target coverage bias seen with capture platforms, (2) a reduction in specificity - or sequencing reads aligning to targets, and provides sufficient coverage for SNP calling over a large percentage of the target bases.