Solid to set new standards for genetic analysis

Applied Biosystems reports the worldwide commercial availability of the Solid system, its 'next-generation' DNA sequencing platform.

Solid is already enabling new ways of performing genetic analysis applications, which may set new standards for how scientists are able to approach complex challenges associated with understanding the biological basis for health and disease, it says.

This new era of life-science research calls for technologies that can help scientists to cost-effectively identify how genetic variation and patterns of gene expression contribute to disease, and the manner in which individual genotypes impact how people may respond to various treatments.

Solid system is distinguished by unparalleled throughput, scalability, accuracy, and application flexibility that set new expectations of discovery for researchers striving to conduct a wide range of applications, says the company.

It began an early-access programme for Solid in June of this year.

Since then, its says the platform has improved throughput four-fold and increased read lengths by 40%.

The current system is capable of delivering up to four billion bases of sequence data per run, establishing it as the highest throughput next-generation sequencing platform available today.

Data accuracy, another critical performance metric, remains at the highest level of accuracy among next-generation systems.

Higher throughput and higher data accuracy result in lower costs for sequencing projects.

As part of its early-access programme, Applied Biosystems worked closely with customers and collaborators to expand the variety of applications now supported by the system.

"In the new era of next-generation life sciences, higher-throughput sequencing technologies with application flexibility should enable researchers to use a single system to make meaningful associations between variations in the kinds and amounts of DNA sequences and disease," said Shaf Yousaf, president of Applied Biosystems's molecular and cell biology systems division.

"New approaches to studying genetic variation are expected to profoundly affect pharmaceutical development programs as researchers study how individual genotypes are linked to how people respond to treatments for disease".

Virtually all human diseases have genetic underpinnings.

Currently, researchers studying complex diseases such as cancer, diabetes, and heart disease rely on reference human DNA sequences from large-scale DNA sequencing projects to broadly associate genetic variations to these diseases.

Scientists also use a variety of methods to associate activity or level of expression of specific genes with characteristics of disease.

Although life-science researchers have studied genetic variation and differential gene expression using a wide range of technologies, the use of Solid is expected to simplify the identification, collection, and analysis of genetic information.

Leading research institutions around the world, including the Hubrecht Institute in the Netherlands, Columbia University, the University of Queensland in Australia, and the University of Tokyo, among others, are already using the Solid system to conduct a wide range of applications.

These include rare variant detection, epigenetic profiling, transcriptome analysis, and serial analysis of gene expression (Sage).

Rare variant detection at the Hubrecht Institute
Researchers at the Hubrecht Institute in the Netherlands are studying gene function in animal models, such as C elegans (roundworm), zebrafish, and rats, so that they can understand the function of similar genes in humans.

To discover rare and low frequency mutations, scientists manipulate the genes of these model organisms by chemically altering their DNA, which disrupts or knocks-out the function of the altered genes.

The team then observes how the appearance or behavior of the organism changes when specific genes are not functioning.

After creating random mutations, the researchers are using Solid to sequence DNA samples from thousands of different animals with up to 10,000 times coverage of genomic regions of interest.

This allows them to identify the specific mutations that have been introduced into these genomes.

Researchers then associate these varied sequences with observed changes to the organisms.

This process helps them to understand gene function in these animal models.

"Our need to detect low-frequency mutations requires an ultra-high throughput sequencing technology with an extremely low error rate," said Edwin Cuppen, group leader for functional genomics and bioinformatics at the Hubrecht Institute.

"The Solid system's two-base encoding mechanism, which discriminates between random or systematic errors and true mutations, helps us to increase the discovery rate of real mutations".

Epigenetic profiling at Columbia University.

At Columbia University, John Edwards, associate research scientist at the university's genome center, and Timothy Bestor, a professor in the department of genetics and development, are using Solid to compare whole-genome methylation patterns in breast cancer.

Methylation is a naturally occurring chemical modification to DNA.

In their research, the scientists are investigating how these patterns change in the progression from normal to tumour tissue, how they differ between tumours, and what roles abnormal patterns of methylation might play in carcinogenesis - the formation of cancer.

Methylation of specific regions of DNA sequence in the genome has been reported to inactivate expression of genes that suppress cancer, while demethylation of repetitive elements may lead to genomic instability and gene expression changes.

Researchers believe that methylated regions of DNA may potentially serve as markers for genes that play a role in cancer.

Solid system is making it possible for the Columbia University researchers to characterise the methylation status of repetitive elements in the genome, and will enable the group to expand their studies to examine methylation patterns that could be treated as biomarkers for cancer.

"The throughput of the Solid system is tremendous, quickly reaching the point where we can plan for routine whole-genome methylation profiling of many samples," said Edwards.

"The scalability allows us to confidently make plans to expand our studies and develop new applications and analysis methods for epigenetic profiling that will help us to better understand what role methylation patterns play in carcinogenesis".

Transcriptome analysis at the University of Queensland.

At the University of Queensland in Australia, researchers are studying the transcriptome to better understand important cellular processes such as cell differentiation, kidney damage and repair, and tumour initiation and progression.

The transcriptome is the set of all messenger RNA (mRNA) transcripts produced from genes and genomic regulatory regions of one or an entire population of cells.

These researchers are using Solid for transcriptome analysis to measure the amounts of relevant variant mRNA transcripts expressed in animal models.

The system is making it possible for them to detect both rarely expressed mRNA transcripts and rare variants of known transcripts.

"Due to the unsurpassed high throughput and the high accuracy of sequence data generated, there is a potential to sequence the transcriptome in its entirety using short read lengths," said Sean Grimmond, group leader in the genomics and computational group at the Institute of Molecular Bioscience.

"Understanding the transcriptome in a biological context will help us to uncover breakdowns in molecular pathways that lead to complex disease".

Serial analysis of gene expression at the University of Tokyo.

Researchers at the University of Tokyo are studying promotor regions of the genome - the switches that turn genes on and off - to better understand how patterns of gene expression contribute to disease, regulatory networks, and cell differentiation.

These scientists are using Solid to profile transcription start sites (TSS), because to effectively analyse promoter regions it is necessary to determine the location of TSS.

The team adapted a gene expression technique known as Sage for use on the system to profile TSS in the study of colon cancer.

Sage is a gene expression technique developed more than a decade ago to rapidly identify differences between cancer cells and normal cells based on differences in patterns of gene expression between the two types of cells.

They subsequently modified this technique for use with Solid, dubbing this method 5'-end-Solid, because of the significance of the 5'-end of the target gene, which is where mRNA transcription start sites are located.

Using this technique makes it possible for the scientists to capture gene expression data that identifies where TSS are located in different genomes.

By profiling TSS regions in colon cancer cell lines, they better understand how epigenetic drugs influence patterns of gene expression in these cell lines.

"Until we incorporated the use of the Solid system into our gene expression studies of colon cancer cell lines, it was difficult to find genes that showed marked increases or decreases in expression levels," said Shinichi Hashimoto, assistant professor in the department of molecular preventative medicine at the University of Tokyo.

"Using the 5'-end Solid technique, we have had great success identifying changes in expression levels of genes, even for those that are normally expressed at very low levels".

Setting standard for next-generation sequencing.

Solid is an end-to-end next-generation genetic analysis solution comprised of the sequencing unit, chemistry, a computing cluster and data storage.

The platform is based on sequencing by oligonucleotide ligation and detection.

Unlike polymerase sequencing approaches, Solid utilises a proprietary technology called stepwise ligation, which generates high-quality data for applications including whole genome sequencing, chromatin immunoprecipitation (Chip), microbial sequencing, digital karyotyping, medical sequencing, genotyping, gene expression, and small RNA discovery, among others.

There are several attributes that distinguish Solid from other next-generation sequencing platforms, including unparalleled throughput, scalability, accuracy, and application flexibility.

The system can be scaled to support a higher density of sequence per slide through bead enrichment.

Beads are an integral part of the system's open-slide format architecture, enabling the system to exceed 4gigabases of sequence data per run in Applied Biosystems's development laboratories.

The combination of the open-slide format, bead enrichment, and software algorithms provide the infrastructure for allowing it to scale to even higher throughput, without significant changes to the platform's current hardware or software.

Solid has a raw base accuracy greater than 99.94% after two-base encoding, a mechanism that discriminates random or systematic errors from true single nucleotide polymorphisms (SNPs).

This represents a five-fold higher accuracy than any data currently published to date on alternative next-generation sequencing platforms.

The platform's high accuracy, combined with mate-pair analysis, enables detection of sequence variation including SNPs, gene copy number variations, single-base duplications, inversions, insertions, and deletions.

Mate-pair sample preparation is a method that enables highly accurate sequence assembly, which is necessary for the analysis of complex genomes such as human, mouse and other model organisms.

"The Solid system continues our tradition of commercialising innovative DNA sequencing technologies," said Kim Caple, vice president and general manager for Applied Biosystems's next-generation sequencing business.

"We selected the technology platform for the Solid system because we believed it would prove to be the platform of choice for next-generation DNA sequencing.

"Based on the feedback we've received from customers and collaborators from some of the world's leading institutions, we are confident that we have developed a system that will help scientists make more meaningful associations between genetic variation and medical conditions."