Press Releases

Kennedy Krieger and Partek Incorporated Discover Novel 
Method to Reveal Genetic Relatedness Between Individuals

Researchers find unexpected familial relationships in 
data widely used by biomedical research community

ST. LOUIS — November 15, 2011 — At a time when profound gaps remain in our understanding of how one person’s genes differ from another person’s, developing accurate methods to interpret the human genome is essential to uncover population history, population relationships and the genetic basis of some of the most common diseases affecting society. Recently published in PLoS Genetics, new research conducted by the children’s health focused Kennedy Krieger Institute, in collaboration with biotechnology software company Partek Incorporated has uncovered a novel mathematical method that combines two commonly used genotype association approaches to reveal the often opaque genetic distinction between individuals.

“Our results come at a time when the research community is beginning to make huge strides in our understanding of the molecular pathways within our own genome,” said Dr. Jonathan Pevsner, senior study author and Director of Bioinformatics at the Kennedy Krieger Institute. “What is so exciting is that our approach gives the research community a more accurate and improved method to evaluate genome-wide studies and improve the field of genomics research as we know it.”

Currently, genome-wide association studies (GWAS) are conducted to examine genes of different individuals to determine genetic variation from individual to individual. In genetic disease studies, researchers are most interested in unrelated individuals with the same disease that share common alleles (versions of a gene). If two unrelated individuals with the same disease randomly have common alleles at a given chromosomal region, researchers can potentially link that region to the disease.

“With so many unanswered questions about the human genome, we need to continually look for new methods to more precisely define relationships,” said Thomas Downey, study author and President of Partek Inc. “Identifying genetic biomarkers within the population will allow the research community to better understand the relationship between an inherited disease and its genetic cause.”

A variety of tools are currently available to make sense of genetic data. However, Dr. Pevsner and his colleagues developed a new mathematical method, in collaboration with Partek Inc., to estimate the relatedness between populations by combining information about how genetic material is shared between any two people, and how it is transmitted from parents to their children. In contrast to the existing methods, using the new calculation, Dr. Pevsner’s team was able to decipher the following without reliance on any prior data:
• Previously unknown familial relationships and population relatedness in broad genomic data
• The nature of relatedness between particular individuals
• Fewer false positives (defined as individuals who are unrelated, but who are called as related)

Using this information, researchers can narrow down the possible candidates for a given inherited disease by identifying multiple common single nucleotide polymorphisms (SNPs), or genetic variations in a single DNA sequence, within a haplotype (combination of alleles). Haplotype SNPs often serve as significant clinical biomarkers in drug discovery and development.

“Our results not only reveal new insights into human evolution, but also provide the research community with better tools to identify biomarkers for disease,” said Dr. Pevsner. “With more precise biomarkers, we will be able to develop more targeted treatments against genetic diseases that afflict the population.”

Notably, when testing their method on the Human Variation Panel, Dr. Pevsner and his colleagues found previously unidentified identical, parent-child, and full-sibling relationships. Studies that calculate the associations between alleles, like the ones above, rely on unbiased representative sampling of population subsets to ensure validity. Consequently, samples are biased when unreported familial relationships are present in the dataset, causing a more frequent occurrence of common SNPs and likely misinterpretation of data and potentially unreliable findings.

“Surprisingly, when applying our new method to the Human Variation Panel, we found previously undeclared relationships,” said Dr. Pevsner. “Our findings have an immediate impact on researchers studying this collection and perhaps an even more widespread impact on any findings that were based on the Human Variation Panel.”

Dr. Pevsner and his colleagues will continue to apply this method to other population subsets in hopes of further decoding the links between our genes and disease.

Support for this study was provided by a National Institutes of Health grant jointly awarded to Kennedy Krieger Institute and Partek Inc.

Joining Dr. Jonathan Pevsner and Thomas Downey as study authors were Eric Stevens, Elisha Roberson, and Joseph Baugher, all graduate students working in Dr. Pevsner’s research laboratory at Kennedy Krieger Institute in Baltimore, and Greg Heckenberg of Partek Inc. in St. Louis.

About the Kennedy Krieger Institute

Internationally recognized for improving the lives of children and adolescents with disorders and injuries of the brain and spinal cord, the Kennedy Krieger Institute in Baltimore, MD serves more than 16,000 individuals each year through inpatient and outpatient clinics, home and community services and school-based programs. Kennedy Krieger provides a wide range of services for children with developmental concerns mild to severe, and is home to a team of investigators who are contributing to the understanding of how disorders develop while pioneering new interventions and earlier diagnosis. For more information on Kennedy Krieger Institute, visit www.kennedykrieger.org. www.kennedykrieger.org.

About Partek
Partek Incorporated (www.partek.com) develops and globally markets quality software for life sciences research. Its flagship product, Partek® Genomics Suite™, provides innovative solutions for integrated genomics. Partek Genomics Suite is unique in supporting all major microarray and next generation sequencing platforms. Workflows offer streamlined analysis for: Gene Expression (incl. SAGE), miRNA Expression, Exon, Copy Number, Allele Specific Copy Number, LOH, Association, Trio analysis, Tiling, ChIP-Seq, RNA-Seq, DNA-Seq, DNA Methylation and qPCR. Since 1993, Partek, headquartered in St. Louis, Missouri USA, has been turning data into discovery®.

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Partek and Genomics Suite are trademarks of Partek Incorporated. The names of other companies and products mentioned herein may be the trademarks of their respective owners.

ST. LOUIS — Feb. 3, 2011 — Partek Incorporated, a global leader in bioinformatics software, today announced the signing of a distribution agreement with Ion Torrent Systems, Inc., a provider of next-generation DNA sequencing technology. The agreement makes Partek® Genomics Suite™ available directly through Ion Torrent's online store as a featured solution for analyzing data generated by Ion Torrent's next generation sequencing (NGS) devices.

"Ion Torrent's vision has always been to democratize sequencing with a system that is fast, simple and scalable so that everyone has access to sequencing technology," said Mike Lelivelt, Ph.D., Director of Bioinformatics and Software Products at Ion Torrent. "Partek shares that vision. They build software that makes sequence analysis simple and accessible to everyone, and that makes this partnership a great fit for everyone, especially customers."

Leveraging an 18-year commercial history—founded on sound statistical analysis and more than a decade of microarray analysis—Partek Genomics Suite is a comprehensive solution for the analysis, comparison and integration of the massive amounts of genomic data that can now be readily produced using semiconductor-based sequencing. Used by thousands of scientists worldwide at leading universities, hospitals, government institutions, biotechnology firms and pharmaceutical companies, Partek Genomics Suite was cited in more than one peer-reviewed publication per day in 2010. It is unique in its ability to support all microarray and next generation sequencing technologies for RNA-, DNA- and gene regulation applications in a single software package, allowing also for the integration of multiple applications in a user-friendly way.

"Partek has a great working relationship with Ion Torrent, and we're pleased to have reached this agreement," said Tom Downey, President of Partek. "The Ion Personal Genome Machine (PGMâ„¢) is increasing accessibility to genomic sequencing, resulting in new data that has to be interpreted to be useful. Partek continues to be on the forefront of providing the necessary tools to streamline and simplify the analysis of genomic data such as product by Ion Torrent's semiconductor sequencing technology."

About Partek

Partek Incorporated (www.partek.com) develops and globally markets quality software for life sciences research. Its flagship product, Partek® Genomics Suite™, provides innovative solutions for integrated genomics. Partek Genomics Suite is unique in supporting all major microarray and next generation sequencing platforms. Workflows offer streamlined analysis for: Gene Expression (incl. SAGE), miRNA Expression, Exon, Copy Number, Allele Specific Copy Number, LOH, Association, Trio analysis, Tiling, ChIP-Seq, RNA-Seq, DNA-Seq, DNA Methylation and qPCR. Since 1993, Partek, headquartered in St. Louis, Missouri USA, has been turning data into discovery®.

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Partek and Genomics Suite are trademarks of Partek Incorporated. The names of other companies and products mentioned herein may be the trademarks of their respective owners.

St. Louis, Missouri – August 15, 2008 – The Munich Leukemia Laboratory (MLL) has purchased Partek^® Genomics Suite^TM (Partek GS) software Partek Incorporated announced today.

Researchers at MLL will use Partek GS to analyze SNP data from research studies focused in Leukemia. Partek GS can analyze expression, digital gene expression, ChIP-seq/ChIP-chip, exon/alternative splicing, SNP genotyping, and next generation sequencing data. In addition, data can be seamlessly imported from a variety of file formats.

Partek Incorporated is a leading provider of statistical analysis and interactive data visualization software for the scientific research community. Partek software enables researchers to quickly identify and quantify patterns in data, including data resulting from genomic and proteomic studies, high-throughput screening campaigns, and computer aided drug design.

St. Louis, Missouri – August 8, 2008 – The Institute for Regenerative Medicine (IRM) at Texas A&M has purchased Partek^® Genomics Suite^TM (Partek GS) software Partek Incorporated announced today.

Researchers at the Institute for Regenerative Medicine will use Partek GS to analyze stem cell research data. The IRM was founded in August 2008 and is researching ways to use adult stem cells to treat patient illnesses, such as diabetes, heart disease, and arthritis.

Partek GS can analyze expression, digital gene expression, ChIP-seq/ChIP-chip, exon/alternative splicing, SNP genotyping, and next generation sequencing data. In addition, data can be seamlessly imported from a variety of file formats.

Partek Incorporated is a leading provider of statistical analysis and interactive data visualization software for the scientific research community. Partek software enables researchers to quickly identify and quantify patterns in data, including data resulting from genomic and proteomic studies, high-throughput screening campaigns, and computer aided drug design.