Ingenuity http://www.ingenuity.com Intuitive web-based applications for quickly analyzing and accurately interpreting the biological meaning in your genomics data Sat, 29 Aug 2015 00:46:07 +0000 en-US hourly 1 http://wordpress.org/?v=4.0.7 Publication Roundup: Ingenuity Pathway Analysis in the Literaturehttp://www.ingenuity.com/blog/customer-stories/publication-roundup-ingenuity-pathway-analysis-literature http://www.ingenuity.com/blog/customer-stories/publication-roundup-ingenuity-pathway-analysis-literature#comments Sat, 29 Aug 2015 00:46:07 +0000 http://www.ingenuity.com/?p=6351 Continuing our series looking at recent publications citing products from QIAGEN Bioinformatics, today we recap several fascinating papers from customers who made use of Ingenuity® Pathway Analysis™ to understand the meaning of changes in gene expression. Long-Term Mild, rather than … Read More

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IPA

Continuing our series looking at recent publications citing products from QIAGEN Bioinformatics, today we recap several fascinating papers from customers who made use of Ingenuity® Pathway Analysis to understand the meaning of changes in gene expression.

Long-Term Mild, rather than Intense, Exercise Enhances Adult Hippocampal Neurogenesis and Greatly Changes the Transcriptomic Profile of the Hippocampus
First author: Koshiro Inoue

In this PLoS One publication, scientists from the University of Tsukuba and other institutes in Japan used rats to understand why mild exercise shows benefits to spatial memory while intense exercise does not. Focusing on a stress biomarker, they performed microarray analysis and found that mild exercise regulated more genes. IPA reported that genes influenced by mild exercise were mostly connected to lipid metabolism and protein synthesis, while intense exercise was linked to a negative effect on hippocampal neuroadaptation.

Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction
First author: Cielito Reyes-Gibby

MD Anderson Cancer Center scientists report in this BMC Systems Biology paper a study of the genetic basis for alcohol, smoking, and opioid addiction. Using IPA, they found candidate genes as well as common pathways; for example, ERK1/2 was connected in all of the addiction networks.

Targeting of multiple oncogenic signaling pathways by Hsp90 inhibitor alone or in combination with berberine for treatment of colorectal cancer
First author: Yen-Hao Su

Published in Biochimica et Biophysica Acta – Molecular Cell Research, this paper demonstrates the use of heat shock protein 90 inhibitors to treat colorectal cancer, also finding that herbal medicine berberine can improve drug sensitivity. A separate data supplement shows results from IPA that contributed to a global molecular network of the significant genes studied.

Macrophage Gene Expression Associated with Remodeling of the Prepartum Rat Cervix: Microarray and Pathway Analyses
First author: Abigail Dobyns

Scientists from Loma Linda University School of Medicine and the University of Edinburgh describe in this PLoS One paper a study of differences in cervical physiology between pregnant and nonpregnant rats. IPA was used to determine that changes in resident macrophages indicate networks of genes that are collectively up- or down-regulated prior to birth. Associated pathways were linked to wound healing and inflammation.

Serial expression analysis of breast tumors during neoadjuvant chemotherapy reveals changes in cell cycle and immune pathways associated with recurrence and response
First authors: Mark Jesus M. Magbanua, Denise M. Wolf, Christina Yau

Scientists from the University of California, San Francisco, published in Breast Cancer Research the results of a breast cancer transcriptome study designed to elucidate response to neoadjuvant chemotherapy. Gene expression data were analyzed with IPA to map genes to pathways and gene ontology groups, revealing that poor response was linked to lower expression of cell cycle inhibitors.

(1) Characterization of a novel chicken muscle disorder through differential gene expression and pathway analysis using RNA-sequencing and (2) Messenger RNA sequencing and pathway analysis provide novel insights into the biological basis of chickens’ feed efficiency
First authors: Marie Mutryn and Nan Zhou

This pair of papers from scientists at the University of Delaware and Maple Leaf Farms are both highly accessed publications in BMC Genomics. The first uses RNA-seq to study an emerging muscle disorder seen recently in chickens. IPA was used to interpret the 1,500 genes differentially expressed between affected and unaffected chickens and resulted in new leads about the biological mechanism behind the disorder. In the second paper, RNA-seq data was generated to help explain the differences between chickens with high or low feed efficiency. The team used IPA for functional and canonical pathways, molecule activity prediction, and analysis of upstream regulators.

To try Ingenuity Pathway Analysis, request a trial.

Did we miss your paper? Please contact us; we would love to feature you!

 

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UC Davis Scientists Spot Mutations in Circulating Tumor DNA with Ingenuity Variant Analysishttp://www.ingenuity.com/blog/customer-stories/uc-davis-scientists-spot-mutations-circulating-tumor-dna-ingenuity-variant-analysis http://www.ingenuity.com/blog/customer-stories/uc-davis-scientists-spot-mutations-circulating-tumor-dna-ingenuity-variant-analysis#comments Wed, 19 Aug 2015 16:09:22 +0000 http://www.ingenuity.com/?p=6341 As Technical Director of the Genomics Shared Resource at the University of California, Davis, Comprehensive Cancer Center, Cliff Tepper routinely faces a series of challenges: monitoring new technologies; adapting platforms for translational use; interrogating a broad array of cancers; and … Read More

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Cliff Tepper, Technical Director, UC Davis Comprehensive Cancer Center

Cliff Tepper, Technical Director, UC Davis Comprehensive Cancer Center

As Technical Director of the Genomics Shared Resource at the University of California, Davis, Comprehensive Cancer Center, Cliff Tepper routinely faces a series of challenges: monitoring new technologies; adapting platforms for translational use; interrogating a broad array of cancers; and tailoring results reports for investigators with diverse expertise ranging from molecular biology to clinical oncology.

To meet these challenges, Tepper works closely with scientists and physicians — both at the cancer center and at other institutions — and keeps an eye on peer-reviewed research for the latest information about technologies and cancer studies. He also invests in leading informatics solutions to get the best results for his clients. Recently, he began using Ingenuity® Variant Analysis™ from QIAGEN, an application that he calls “phenomenal.”

In a recent study that Tepper presented at this year’s annual meeting of the American Association for Cancer Research, his team used Variant Analysis to filter variants found in circulating tumor DNA from patients with pancreatic cancer. The project aimed to generate proof-of-principle data to understand the utility of circulating DNA for this type of cancer in samples from a cohort of nearly 30 patients. To figure out whether KRAS mutations found in circulating DNA — associated with a poor patient prognosis — were truly representative of the tumor, they also sequenced tumor samples from three of the patients.

“In general what we found was that if we manually looked through the data, the assay does pick up the KRAS mutations in all of the samples,” Tepper says. The challenge is that with some analysis tools, standard threshold settings are too high to detect variants at the low levels seen in the data. “Sometimes these mutants weren’t being called even though the reads were there,” he adds.

But loading the data into Variant Analysis revealed the whole picture. “We can see the mutations there,” Tepper says. “We got a good idea of what somatic mutations were present in the tumor just based on the circulating DNA.” The ability to easily adjust thresholds and change filters in the application is a big advantage for the genomics core team. They can set up a filter cascade for various traits they’re interested in, such as depth of coverage, sequencing quality, common variants, as well as more specialized filters for variants implicated in cancer, mutations associated with cancer therapeutics, and expression levels. Essential information, such as gene location and base change, is shown clearly. And the tool’s inclusion of the COSMIC database makes it a cinch to pick out known somatic mutations.

With his translational focus, the real payoff for Tepper is generating results that can be easily understood by all of his clients. A clinical pathologist who looked over the Variant Analysis results “liked the presentation a lot because it is easy to examine the data, and it’s very clear what it means as well,” Tepper says. “The interface is very user-friendly and you can organize the columns based on the things you’re most interested in seeing. That helps us share this data with oncologists.”

To learn more about Tepper’s research, check out this case study

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Big Data Getting Bigger: Analysis and Sharing Critical as Genomics Grows Uphttp://www.ingenuity.com/blog/news/big-data-getting-bigger-analysis-sharing-critical-genomics-grows http://www.ingenuity.com/blog/news/big-data-getting-bigger-analysis-sharing-critical-genomics-grows#comments Wed, 12 Aug 2015 19:43:16 +0000 http://www.ingenuity.com/?p=6336 Recently PLoS Biology published a paper about big data in genomics from lead author Zachary Stephens, senior author Gene Robinson, and their collaborators at the University of Illinois at Urbana-Champaign and Cold Spring Harbor Laboratory. The perspective offers a bold vision … Read More

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Recently PLoS Biology published a paper about big data in genomics from lead author Zachary Stephens, senior author Gene Robinson, and their collaborators at the University of Illinois at Urbana-Champaign and Cold Spring Harbor Laboratory.

The perspective offers a bold vision about the projected growth of data generation and management in the field. The authors compare genomic data to other areas known for their leading data production (astronomy, Twitter, and YouTube) and offer solid documentation for their theory that 10 years from now, genomics could outpace all other big data fields. (Check it out: “Big Data: Astronomical or Genomical?”)

One of the areas they focused on was data analysis, a category that’s near and dear to the QIAGEN Bioinformatics team. Stephens et al. call out variant interpretation as one of the most computationally intensive processes for genomic data. Projecting out to the number of genomes that could be available by 2025, they write, “Variant calling on 2 billion genomes per year, with 100,000 CPUs in parallel, would require methods that process 2 genomes per CPU-hour, three-to-four orders of magnitude faster than current capabilities.”

We think solutions that take advantage of cloud-based computing will be critical for overcoming this hurdle. The less scientists have to move data around and rely on limited in-house clusters to perform complicated queries, the more they can focus on what’s really important: results. This is one of the reasons our applications are web-based. Users of Ingenuity® Variant Analysis™, for instance, simply upload their variant list and let us worry about the computational resources. Clearly, further improvements are needed to analyze genomes at enormous scale, and our R&D team will work closely with others in the field to make sure we’re ready to meet the challenge.

Another great point in the scientists’ perspective was their insistence on data sharing across labs and institutions. “For precision medicine and similar efforts to be most effective, genomes and related ’omics data need to be shared and compared in huge numbers,” the authors write. “If we do not commit as a scientific community to sharing now, we run the risk of establishing thousands of isolated, private data collections, each too underpowered to allow subtle signals to be extracted.”

We heartily support this statement, and are proud to be co-founders of a leading initiative aimed at facilitating this kind of sharing — the Allele Frequency Community. When we and our fellow founders first conceived the community, data sharing was one of our most important goals. That’s why we adopted a share-and-share-alike approach for AFC, letting all scientists use the data as long as they share their own allele frequency data in exchange. This proviso has led to remarkable growth for the community in its first six months, constantly making the resource more valuable to everyone using it. We think there are opportunities to use a similar approach for other types of genomic data and hope others are inspired to try it.

Kudos to Stephens et al. for a thought-provoking commentary that has gotten the whole field talking about what the future of genomics might look like!

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Big Honor for Causal Analysis Tools in IPAhttp://www.ingenuity.com/blog/news/big-honor-causal-analysis-tools-ipa http://www.ingenuity.com/blog/news/big-honor-causal-analysis-tools-ipa#comments Thu, 06 Aug 2015 22:07:26 +0000 http://www.ingenuity.com/?p=6326 We’re honored to learn that a paper we published in Bioinformatics last year was one of the journal’s 10 most cited articles of 2014! This paper is especially important to us because it was our first description and published evaluation … Read More

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Top 10 cited paper in Oxford JournalWe’re honored to learn that a paper we published in Bioinformatics last year was one of the journal’s 10 most cited articles of 2014!

This paper is especially important to us because it was our first description and published evaluation of four important new gene expression tools we introduced to the Ingenuity Pathway Analysis web application: Upstream Regulator Analysis, Mechanistic Networks, Causal Network Analysis, and Downstream Effects Analysis.

Causal analysis approaches in Ingenuity Pathway Analysis” was written by Andreas Kramer, Jeff Green, and Stuart Tugendreich from QIAGEN Bioinformatics, along with Jack Pollard, Jr, of Sanofi-Aventis. In it, the authors describe the new tools, and also present results from experiments using the tools on new datasets.

As IPA users know, the four tools described in the paper are based on Ingenuity Knowledge Base, described in the publication as “a large structured collection of observations in various experimental contexts with nearly 5 million findings manually curated from the biomedical literature or integrated from third-party databases.” Some 40,000 nodes in the network represent mammalian genes and the products, compounds, microRNA molecules, and functions associated with them. Those nodes are linked by nearly 1.5 million edges, which represent cause-effect relationships such as transcription, molecular modification, or binding events. The new tools, like all other features of the Ingenuity applications, reflect our commitment to the idea that new data is made more meaningful when it is interpreted in a context of prior biological knowledge.

Here’s a bit more about the tools, as described in the paper:

  • Upstream Regulator Analysis: Determines likely upstream regulators connected to genes in a given dataset through a set of direct or indirect relationships
  • Mechanistic Networks: Builds on predicted upstream regulators by connecting regulators expected to be part of the same signaling or causal mechanism
  • Causal Network Analysis: Connects upstream regulators to molecules in a given dataset and generates a more complete picture by taking advantage of paths with more than one link
  • Downstream Effects Analysis: Infers the impact on disease or biological functions downstream of genes with up- or down-regulated expression in a dataset.

Many thanks to all the scientists who have been using the new IPA tools and citing our paper as they publish. This honor from the Bioinformatics journal is a great indicator that the tools have been every bit as helpful as we’d hoped!

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Publication Roundup: Ingenuity Variant Analysis in the Literaturehttp://www.ingenuity.com/blog/customer-stories/publication-roundup-ingenuity-variant-analysis-literature http://www.ingenuity.com/blog/customer-stories/publication-roundup-ingenuity-variant-analysis-literature#comments Tue, 28 Jul 2015 16:10:57 +0000 http://www.ingenuity.com/?p=6297 Over the years, scientists around the world have been using our bioinformatics solutions in their research. We feel privileged that our applications have been assisting scientists in uncovering greater insights, landmark discoveries, and helping further the research that has a … Read More

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Ingenuity Variant Analysis

Over the years, scientists around the world have been using our bioinformatics solutions in their research. We feel privileged that our applications have been assisting scientists in uncovering greater insights, landmark discoveries, and helping further the research that has a direct impact on humanity.

We are starting a new blog series to showcase some of these research papers from QIAGEN Bioinformatics customers.  Today, we recap a handful of recent publications that used Ingenuity® Variant Analysis to help make sense of complex or hereditary disease phenotypes.

The use of whole-exome sequencing to disentangle complex phenotypes
First author: Hywel J Williams

This paper in the European Journal of Human Genetics comes from University College London’s GOSgene group, including lead author Hywel Williams, one of our featured researchers. Published in June, “The use of whole-exome sequencing to disentangle complex phenotypes” reports the identification of a causative mutation in two children with a previously uncharacterized disease marked by abnormal bronchial widening and peripheral neuropathy. The team used Ingenuity Variant Analysis to study exome sequence data, extracting the variants most likely to be causative. For more information on this paper, click here.

Alternating Hemiplegia of Childhood: Retrospective Genetic Study and Genotype-Phenotype Correlations in 187 Subjects from the US AHCF Registry (PLoS One)
First author: Louis Viollet

In May, a large team of scientists from institutions around the world report an ambitious effort to stratify patients with AHC, a neurological disorder associated with repeated bouts of temporary paralysis. The researchers analyzed mutations and genotype-phenotype correlations in nearly 200 patients, then used Ingenuity Variant Analysis to evaluate mutations detected in sequence data. In addition to finding novel mutations associated with the disorder, the team also determined that one known variant was linked to earlier onset and more severe symptoms, potentially offering a more accurate prognostic indicator (biomarker?) for newly diagnosed patients. You can read more about this work here. 

A nonsense mutation of human XRCC4 is associated with adult‐onset progressive encephalocardiomyopathy
First author: Leonardo Bee

In the April issue of EMBO Molecular Medicine, scientists from Italy, the UK, and the US used exome sequencing to study twins with a progressive neurological syndrome; symptoms included cognitive impairment and depression, and both twins also had dilating cardiomyopathy. The publication reports the discovery of a homozygous nucleotide change affecting a protein associated with DNA repair. Ingenuity Variant Analysis was used to zero in on variants in the XRCC4 gene known to be involved in DNA repair. Using Ingenuity Variant Analysis’ Path to Phenotype™ investigators were able to link impairment of the XRCC4 gene to the subject’s observed developmental disorders. To learn more, click here.

Exome sequencing of case-unaffected-parents trios reveals recessive and de novo genetic variants in sporadic ALS
First author: Karyn Meltz Steinberg

In March, scientists from Washington University in St. Louis and the University of Sydney published this paper in Nature Scientific Reports. In it, they describe exome sequencing of 44 trios of patients with ALS and their unaffected parents. Using Ingenuity Variant Analysis as well as other analysis tools, they found a number of homozygous recessive and de novo variants that may be implicated in the disease. “This trio study indicates that rare private recessive variants could be a mechanism underlying some case of sporadic ALS, and that de novo mutations are also likely to play a part in the disease,” the authors report. Learn more about this work here.

Impaired Telomere Maintenance and Decreased Canonical WNT Signaling but Normal Ribosome Biogenesis in Induced Pluripotent Stem Cells from X-Linked Dyskeratosis Congenita Patients
First Author: Bai-Wei Gu

Finally, this May PLoS One publication from researchers at the Children’s Hospital of Philadelphia reports the use of induced pluripotent stem cells from patients with dyskeratosis congenita, a rare syndrome affecting bone marrow. By comparing these cell lines to ones with knocked-in wild type genes correcting the dysfunction, the scientists could analyze changes in telomere activity associated with the syndrome. The team used both Ingenuity Variant Analysis and Ingenuity Pathway Analysis (IPA) to look at mutations and gene expression data, finding decreased WNT signaling in mutant cells. Research paper is available here.

Did we miss your paper? Please contact us; we would love to feature you!

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In Dublin, ISMB Celebrates Bioinformaticianshttp://www.ingenuity.com/blog/events/dublin-ismb-celebrates-bioinformaticians http://www.ingenuity.com/blog/events/dublin-ismb-celebrates-bioinformaticians#comments Thu, 23 Jul 2015 15:40:10 +0000 http://www.ingenuity.com/?p=6292 When it comes to bioinformatics — the kind of equation-rich, in-the-weeds technical detail that makes many a molecular biologist want to run the other way — there’s no event quite as geek-chic as ISMB. (It also has a unique family … Read More

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When it comes to bioinformatics — the kind of equation-rich, in-the-weeds technical detail that makes many a molecular biologist want to run the other way — there’s no event quite as geek-chic as ISMB. (It also has a unique family atmosphere.) This year, the 23rd annual International Conference on Intelligent Systems for Molecular Biology was held in conjunction with the 14th European Conference on Computational Biology in Dublin.

It was a privilege for QIAGEN Bioinformatics to serve as a sponsor of this event, and a treat for our team to attend and exhibit. After all, we’re still a bunch of computational folks who feel most at home hashing over the code of an algorithm to get it just right. So we fit right in with the other 1,500 attendees vying for the best view of the presentations and poster sessions!

Keynote presentations this year came from scientists including Stanford’s Michael Levitt, Eileen Furlong from EMBL, Kenneth Wolfe from the University College Dublin, and Amos Bairoch at the Swiss Institute of Bioinformatics. Stellar award presentations honored the Broad Institute’s Curtis Huttenhower and Cyrus Chothia of the MRC Laboratory of Molecular Biology; it was inspiring to hear about their experiences and advice for the field.

It was clear that genomics has entered the world of big data, as several speakers focused on data compression and methods for quickly discarding data that isn’t needed for future analysis. This will continue to be a major challenge in this field as databases grow. After all, biologists are trained to save every bit of data, but long-term storage won’t make sense for many applications. We’ll need to find clever approaches like the ones that have worked so well in astronomy and other fields facing an overwhelming volume of data.

Alex Kaplun, PhD, one of our team members from Global Informatics Solutions & Support also enjoyed giving a talk about a comparison of predicted promoters in two different builds of the human reference genome. In addition to the data, he shared insights that were gained about how regulatory features, such as transcription factor binding sites, are distributed.

We’re already looking forward to next year’s ISMB! In the meantime, we’re going back to the office and giving our brains a quick break before we start to think of exciting new ways to take advantage of everything we learned in Dublin.

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IPA Summer Release 2015http://www.ingenuity.com/blog/news/ipa-summer-release-2015 http://www.ingenuity.com/blog/news/ipa-summer-release-2015#comments Tue, 14 Jul 2015 18:22:06 +0000 http://www.ingenuity.com/?p=6254   We are very pleased to announce the annual summer release of IPA.  Since IPA was launched in 2003 (Beta in 2002), we have released new updates to the product every spring, summer, fall, and winter. Today, IPA has been broadly … Read More

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IPA Summer Release email banner 600x200

We are very pleased to announce the annual summer release of IPA.  Since IPA was launched in 2003 (Beta in 2002), we have released new updates to the product every spring, summer, fall, and winter. Today, IPA has been broadly adopted by the life science research community and is cited in more than 139,00 peer-reviewed journal articles.

One significant benefit of IPA is the ability to reveal potential causal associations hidden in your datasets of differentially expressed genes. A major new feature in this summer’s release is a new gene-level heatmap tool that provides greater clarity into which genes are up- or down-regulated in a particular pathway, upstream regulator, or downstream disease or function across conditions.

For example, if you were to perform two different analyses using different experimental conditions, IPA might predict that a particular upstream regulator is increasing in activity but these may not involve exactly the same set of genes across different datasets or analyses. The new gene heat maps found via IPA’s Comparison Analysis functionality can help you quickly examine and identify significant expression differences across those conditions.

Fig 1

 

Make it easier to launch by installing the IPA client on your computer

This installer will enable you to access IPA like other desktop applications on your computer (though still requiring an internet connection). You will no longer need to launch IPA through a browser and no longer need to install Java.

You can try this new functionality by downloading the IPA Client installer from this link:

https://analysis.ingenuity.com/pa/installer/select and following the instructions.

 

 

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At Oxford, Scientists Use Ingenuity ® Variant Analysis ™ to Uncover Rare Neurological Mutationshttp://www.ingenuity.com/blog/customer-stories/oxford-scientists-use-ingenuity-variant-analysis-uncover-rare-neurological-mutations http://www.ingenuity.com/blog/customer-stories/oxford-scientists-use-ingenuity-variant-analysis-uncover-rare-neurological-mutations#comments Wed, 08 Jul 2015 16:05:58 +0000 http://www.ingenuity.com/?p=6236 At the Oxford Biomedical Research Center (BRC), scientists used Ingenuity Variant Analysis from QIAGEN Bioinformatics in a family study to pinpoint unknown mutations causing abnormal brain development. Now, a family with a history of conceiving babies with severe brain malformations … Read More

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Alistair Pagnamenta

Alistair Pagnamenta, Post Doc at Oxford Biomedical Research Center (BRC

At the Oxford Biomedical Research Center (BRC), scientists used Ingenuity Variant Analysis from QIAGEN Bioinformatics in a family study to pinpoint unknown mutations causing abnormal brain development. Now, a family with a history of conceiving babies with severe brain malformations has a new path toward having a healthy child. And the program that helped them could make a difference for many other families in similar situations as well.

Alistair Pagnamenta, a postdoc who has focused on neurological disorders since joining the center in 2010, was the lead author on a recent paper in Human Molecular Genetics reporting results for this family. They had had three pregnancies terminated due to the detection of abnormalities including polymicrogyria, a brain anomaly where poor organization of neurons results in an increased number of small folds in the cortex, instead of a smaller number of large folds to maximize the brain’s surface area. The condition can lead to intellectual disability, muscle weakness or paralysis, seizures, and more.

One challenge Pagnamenta and his colleagues faced early on was limited access to DNA samples from the three fetuses. With those precious samples as well as DNA from the parents, the team performed exome sequencing on all five individuals. Using Ingenuity Variant Analysis, they generated a list of genes already known to be associated with polymicrogyria and quickly determined that in this family, none of them was faulty. They would have to search for a novel gene.

But whole exome data from five people is a lot of DNA to comb through, so the team focused the search for a causal variant on genomic regions where all three fetuses had inherited the same chromosome segments from each parent. Targeting these identical-by-descent regions allowed the scientists to narrow their search to just 8.6 percent of the genome. “Then we searched within those regions and looked at all the variants present — how many of them were rare, how many were predicted deleterious,” Pagnamenta says. Within that subset of variants, they scanned for homozygous and compound heterozygous mutations.

The inheritance pattern for the variant of interest was unknown going into the project, Pagnamenta notes. “We thought it was most likely to be a recessive condition because there were multiple affected fetuses and the parents were unaffected,” he says. “But we couldn’t be absolutely sure. It could also have been germline mosaicism — a de novo mutation that was present in all three fetuses but not in DNA from the parents’ blood.”

Testing both modes of inheritance was another way that Ingenuity Variant Analysis proved to be a handy tool. “Having this software was quite useful because you can change the order that all the filtering is performed, and you can very quickly switch from the recessive mechanism to this de novo parental mosaicism model,” Pagnamenta says.

The team’s analysis turned up one very strong candidate that matched the expected autosomal recessive inheritance mode — compound heterozygous mutations in PI4KA on chromosome 22, one causing a premature stop and the other a missense substitution at a conserved location. The variants affect “an enzyme that’s part of a well-known signaling pathway,” Pagnamenta says. “Mutations in other components of this pathway were known to cause related brain malformations.”

To learn more about this study and BRC’s exome sequencing efforts, check out our full case study of Alistair Pagnamenta’s work.

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