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Jefferson U Wins $1M Keck Grant to Analyze Functions of Computationally Predicted Repetitive Motifs

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By Uduak Grace Thomas

Researchers and physicians at Thomas Jefferson University have been awarded a $1 million Keck Foundation medical research grant to uncover how repetitive genomic sequences called pyknons could be involved in the onset and progression of diseases.

Led by Isidore Rigoutsos, who heads up TJU's computational medicine center, the team also comprises researchers and physicians from Thomas Jefferson University and Hospital; the Children's Hospital of Philadelphia; the University of North Carolina at Chapel Hill; and the University of Texas' MD Anderson Cancer Research Center.

Together, they will study the functions of these sequence motifs in the context of several types of cancers including prostate, colon, and pancreatic cancers and chronic lymphocytic leukemia; hyper- and hypo-reactivity in platelets; multiple and systemic sclerosis; and type-1 diabetes.

More specifically, they will investigate the presence of pyknon-marked non-coding RNAs in these conditions and try to determine the rules that govern the biogenesis, processing, and regulatory mechanisms of these transcripts with the assistance of both computational analyses and experimental techniques.

Rigoutsos used computational methods to predict the existence of thousands of pyknons around five years ago, and since that time a number of research teams have validated their existence and biological functions.

Now, Rigoutsos told BioInform, his team will focus its efforts on data generation and analysis in the context of "pyknon-related questions" using samples that it will analyze in house via sequencing and microarrays, as well as data from partners in other institutions.

The timeline for the grant was not disclosed.

The university houses two sequencers including a Life Technologies SOLiD platform and a Roche 454 system.

The researchers won't be developing new software for the project, but Rigoutsos expects that the team will at some point use Teiresias, an unsupervised pattern-recognition algorithm that he developed during his time at IBM Research, where he led the bioinformatics and pattern-discovery group until joining Jefferson last year.

Teiresias has been used for a number of projects, including the analysis of data from a cocoa sequencing project led by candymaker Mars and the United States Department of Agriculture (BI 7/7/2008), and it was the primary method that Rigoutsos used to computationally predict the existence of pyknons.

Rigoutsos said the pyknon project will require "substantial computational power" and as a result the center plans to ramp up its compute infrastructure.

He declined to provide details about the center's current computational capacity, the planned increase, and which hardware vendors were being considered for the job.

Valuable Junk

Rigoutsos used Teiresias to discover pyknons — named after the Greek word for "frequent — in 2005. In a paper published in the Proceedings of the National Academy of Sciences in 2006, Rigoutsos and colleagues noted that they found the repetitive motifs by processing human intergenic and intronic regions and cataloguing all "variable-length patterns with identically conserved copies and multiplicities above what is expected by chance." Among these patterns were nearly 130,000 that were also present in protein-coding regions and had a number of characteristics suggesting that they play a key role in genomic regulation.

Since that time, researchers have discovered that pyknon motifs mark transcribed, non-coding RNA sequences that appear to have a hand in several human biological conditions.

Currently, "there is disconnected evidence" regarding the biological function of pyknons, Rigoutsos said in a statement, adding that one aim of the project is "to assemble all the pieces."

Making sense of pyknons and non-coding RNAs in general has dominated Rigoutsos' time since he departed IBM — after an18-year tenure — for Jefferson a little over a year ago.

"People are beginning to realize that this is an unexplored territory that deserves attention," he explained to BioInform. "Historically in the [scientific] community, we basically focus on two percent of the human genome that codes for amino acid sequences" and refer to the unexplained portion as junk DNA.

"The flow of events was from protein coding regions to the non-coding parts and it occurred to me that nobody went the other way," he said, describing his motivation for the work that led to the initial discovery of pyknons. "What I set out to do was answer the question, what would happen if I took the genome, removed everything that has to do with protein-coding sequences and then looked at the rest? Is there anything there and ... can I connect it to the protein-coding sequences?"

The computationally predicted pyknons that Rigoutsos and his team reported in the 2006 PNAS paper were later experimentally validated by other research groups. For example, several months after the paper was published, an independent research group found some of these sequences, called piwi-interacting RNAs, using next-generation sequencing.

Additionally in 2009, two papers published in Nature and Current Biology reported results from the analysis of Drosophila, mouse, human, and Xenopus that showed that mRNA was responsible for producing short RNAs of the same length as the predicted pyknons.

Other research groups have discovered pyknons at work in some disease conditions. A paper published in 2007 in Cancer Cell by a team at Ohio State University and their collaborators revealed two pyknons in ultraconserved genes that were differentially expressed in diseased and normal colon cancer samples. Similarly, another paper published earlier this year in Cancer Research found two pyknons in a region of a gene that’s differentially transcribed in melanoma versus normal samples.

These findings among others provide evidence "that regions containing these motifs are transcribed differentially," Rigoutsos concluded.

"We have quite a lot of parts to the big[ger] picture but we still lack … understanding [of] the relationships [these parts] have with one another," he noted "Its that thing that has been attracting my attention for quite a few years and ever since I moved to Jefferson."

With the Keck grant, he and his colleagues hope to answer questions about the mechanisms by which these pyknons are generated, as well as what activates them and what their targets are after they have been made and processed.

As the researchers gain a better understanding of pyknon roles, the next step would be to validate the findings in large sample sets, Rigoutsos said.

"Anything that looks interesting in a set of 20 [samples] may be diluted and disappear if you do 1,000 [samples]," he said. "You need to make sure that its repeatable ... [and] you want to ensure that you sample the population as uniformly as possible."

Once that’s done, "then presumably you want to start figuring out the mechanisms," he continued. "If we understand how they are made and how they are processed, that’s a very powerful thing [because] it might allow us eventually to predict more of them."


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