Sage Blog

Size Selection Has Utility for Cell-Free DNA Studies

The rise of research studies and diagnostic tests looking at cell-free DNA — particularly fetal DNA in a mother’s bloodstream — has happened with astonishing speed. Prenatal genetic testing, for instance, has already supplanted many invasive clinical tests such as amniocentesis or chorionic villus sampling. Cell-free DNA is now considered an important source of information about cancer, and will no doubt have many other applications as we learn more about it.

These studies are particularly interesting to us because isolating cell-free DNA involves accurate size selection. Foundational research has consistently found that cell-free fetal DNA is shorter than cell-free maternal DNA: this early study determined that fetal DNA was less than 300 bp, while maternal DNA was larger than 1 Kb, while another study reported a dominant peak of about 160 bp for fetal DNA.

A more recent publication explored various methods of analyzing fragment sizes for a study of cell-free fetal DNA. With paired-end sequencing as well as basic electrophoresis (sizes were read with a Bioanalyzer), the scientists were able to distinguish maternal from fetal DNA. With extremely specific findings of fragment size, they were also able to detect some cases of fetal chromosomal aneuploidy just by observing size aberrations.

We’re excited about the possibilities of applying automated DNA size selection to cell-free DNA studies. Other methods of size selection have not been terribly successful due to the yield challenge; DNA derived from a fetus or tumor is already such a small proportion of DNA in these samples. But with a platform like ours, which significantly boosts yield compared to other sizing techniques, we think there is great potential for enhancing cell-free DNA research.

We’re presenting a poster on this topic at the AGBT Precision Health meeting right now. If you’re attending the conference, check out poster #107 — and if not, we’ll have more details on our blog next week.

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Where Illumina Users Gather, Great Science Is on Display

The Sage team is pleased to be sponsoring the slate of upcoming Illumina user group meetings. We’ve attended many of these events over the years, and they’re excellent venues that showcase truly impressive work from the company’s broad customer base. We learn something new at each meeting we attend!

Sage instruments are important for a number of applications related to Illumina sequencing, from Nextera library preparation and PCR-free libraries to paired-end and mate-pair libraries. For more details on specific applications, check out this resource page.

For a good sense of how Illumina users are applying our Pippin family of automated DNA size selection platforms, don’t miss our frequently updated list of citations from peer-reviewed literature. And if you’ll be at the user group meetings or other upcoming genomics conferences, please stop by the Sage booth! We’d love to meet you and learn more about your research.

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At the University of Delaware, Early Adopter Genomics Core Spots New Science Trends

kingham_bruceThe genomics core facility at the University of Delaware has set itself apart from other service providers by being among the first to adopt new sequencing technologies. The strategy has been a success: today, the facility serves customers around the world, hailing from research and nonprofit institutes, federal agencies, and even foreign governments. While projects range from microbial to human and everything in between, agrigenomic studies are especially popular for users looking to improve growth and disease resistance among crops and livestock.

Bruce Kingham, who runs the genomics core lab, has also focused on adopting state-of-the-art tools to keep the sequencers running happily. Size selection has been essential for delivering optimal results to his user base, from their first Illumina NGS platform in 2007 to the PacBio single-molecule sequencing system. It was the acquisition of the Illumina GA that spurred his team to offer library prep as a service, for which they invested in the Pippin Prep for automated DNA size selection. “That allowed us to not only get a very focused size for the libraries that we were preparing, but more importantly it allowed us to start with a much smaller quantity of DNA,” he says. Prior techniques relied on inefficient fragmentation procedures and gel extraction to isolate the desired fragment size, resulting in a great deal of undesirable sample loss.

Today, Pippin sizing — now with BluePippin — continues to be important for Kingham’s Illumina workflow, including PCR-free projects. “Size selection has been critical because the PCR-free library preparation process can be prone to generating libraries that have a broader size range,” he says. “Illumina technology for a number of reasons does not like libraries that are broad in size.” From clustering efficiency to optical analysis, these sequencers perform best when fed libraries with tightly sized DNA fragments. For Illumina sequencing in general, Kingham says, “downstream analysis, including mapping or de novo assembly, is going to be more efficient and have more statistical significance if the size range of individual libraries is focused.”

For PacBio sequencing, Kingham’s team uses both BluePippin and SageELF for size selection. Because the BluePippin is so useful for eliminating small fragments and keeping the PacBio platform focused on generating the longest reads possible, it dramatically improves the quality of results. “With the volume of sequencing that we do, the BluePippin paid for itself in a couple of months,” Kingham says. By increasing average read length and N50 read length, BluePippin “lowers the cost of the data that needs to be generated to achieve a certain sequencing goal, such as the lowest number of contigs,” he adds. The lab uses SageELF for Iso-Seq protocols, where it significantly reduces the amount of input DNA required.

Looking ahead, Kingham sees increased demand from scientists for pairing genomics and proteomics data. It’s a trend that fits nicely at his home institute, which has a mission of promoting interdisciplinary research. To that end, his team has already begun evaluating the SageELF for use in protein fractionation. “That could be a welcome service, and I’m always looking for new services to provide,” Kingham says. “I want to see my instruments running as much as possible.”

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PELE-seq Increases SNP Calling Accuracy by Reducing Sequencing Errors

Scientists at the University of Oregon have published a new method to detect PCR and sequencing errors that should help other researchers track rare SNPs with greater accuracy. PELE-seq, which gets our vote for best new protocol name, can be used with ddRAD-seq, targeted amplicon sequencing, and many other genotyping methods.

From lead author Jessica Preston and senior author Eric Johnson, “High-specificity detection of rare alleles with Paired-End Low Error Sequencing (PELE-Seq)” came out in BMC Genomics. The scientists embarked on this project to reduce the current error rate in NGS studies, which they peg at about 1% and say “leads to the generation of millions of sequencing errors in a single experiment.”

The team uses barcoded adapters as well as overlapping paired-end reads on size-selected DNA molecules to maximize accuracy. The barcoding process reduces false-positive SNP calls, while the overlapping reads reduce sequencing errors. The team used our Pippin Prep automated DNA sizing platform to collect tight DNA bands prior to paired-end

sequencing on Illumina. Scientists tested the PELE-seq protocol on E. coli and Caenorhabditis remanei, finding improved specificity and sensitivity for accurately detecting rare variants.

“We have demonstrated that the PELE-Seq method of variant calling is highly specific at detecting rare SNPs found at below 1% in a population,” the scientists write. “There were zero instances of false positive SNPs called from PELE-sequenced control E. coli libraries containing rare alleles present at known frequencies, whereas standard NGS DNA-Seq libraries contained 30–50% false-positive SNPs.”

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Low-Coverage Sequencing No Challenge for Structural Variant Detection

Is it really possible to detect somatic structural variants accurately from a single sequencing read? A new protocol from scientists at the Albert Einstein College of Medicine in New York and Voronezh State University in Russia was designed to do just that.

In the Nature Methods paper entitled “Quantitative detection of low-abundance somatic structural variants in normal cells by high-throughput sequencing,” lead author Wilber Quispe-Tintaya, senior author Alexander Maslov, and collaborators describe a method called Structural Variant Search (SVS).

“The key feature of SVS is its ability to definitively call [a structural variant] using a single sequencing read that spans the breakpoint, without the need for multiple supporting reads,” the scientists report. The workflow relies on preparing a chimera-free library and on a new algorithm that calls structural variants without using consensus data. The variant caller uses a split-read method for identifying potential structural variants, filters out artifacts, and then separates somatic from germline variants.

They demonstrate the workflow on a cell line known to harbor integration events from human papillomavirus. SVS called 20 integration sites; 17 had previously been reported, and two of the three novel findings were confirmed by PCR testing. “Most likely these two HPV inte­gration sites had not been detected previously because of their low abundance, underscoring the unique capability of SVS to detect low-frequency [structural variants],” the authors note.

The team’s library prep procedure included size-selection on a PippinHT instrument, after which the samples were sequenced using the Ion Torrent Proton platform.

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