Category Archives: Genome

ScienceDaily (Oct. 3, 2012) Investigators at Children's Mercy Hospitals and Clinics in Kansas City have just reported the first use of whole genome information for diagnosing critically ill infants. As reported in Science Translational Medicine, the team describes STAT-Seq, a whole genome sequencing approach -- from blood sample to returning results to a physician -- in about 50 hours. Currently, testing even a single gene takes six weeks or more.

Speed of diagnosis is most critical in acute care situations, as in a neonatal intensive care unit (NICU), where medical decision-making is made in hours not weeks. Using STAT-Seq, with consent from parents, the investigators diagnosed acutely ill infants from the hospital's NICU. By casting a broad net over the entire set of about 3,500 genetic diseases, STAT-Seq demonstrates for the first time the potential for genome sequencing to influence therapeutic decisions in the immediate needs of NICU patients.

"Up to one third of babies admitted to a NICU in the U.S. have genetic diseases," said Stephen Kingsmore, M.B. Ch.B., D.Sc., FRCPath, Director of the Center for Pediatric Genomic Medicine at Children's Mercy. "By obtaining an interpreted genome in about two days, physicians can make practical use of diagnostic results to tailor treatments to individual infants and children."

Genetic diseases affect about three percent of children and account for 15 percent of childhood hospitalizations. Treatments are currently available for more than 500 genetic diseases. In about 70 of these, such as infantile Pompe disease and Krabbe disease, initiation of therapy in newborns can help prevent disabilities and life-threatening illnesses.

STAT-Seq uses software that translates physician-entered clinical features in individual patients into a comprehensive set of relevant diseases. Developed at Children's Mercy, this software substantially automates identification of the DNA variations that can explain the child's condition. The team uses Illumina's HiSeq 2500 system, which sequences an entire genome at high coverage in about 25 hours.

Although further research is needed, STAT-Seq also has the potential to offer cost-saving benefits. "By shortening the time-to-diagnosis, we may markedly reduce the number of other tests performed and reduce delays to a diagnosis," said Kingsmore. "Reaching an accurate diagnosis quickly can help to shorten hospitalization and reduce costs and stress for families."

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The above story is reprinted from materials provided by Children's Mercy Hospital, via EurekAlert!, a service of AAAS.

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Fifty-hour whole genome sequencing provides rapid diagnosis for children with genetic disorders

Peering into the underlying causes of breast cancer, researchers and oncologists are increasingly turning to genome analysis of patients to identify the mutated genes that drive the leading cause of cancer fatalities for women across the world.

The last year has already yielded studies that will spur clinical trials and possibly new drug treatments within the next few years, offering hope to women with common, rare and aggressive forms of breast cancer.

Things now move so much faster, said Dr. Ian Krop, a professor at Harvard Medical School and oncologist at Dana-Farber Cancer Institute in Boston. Within the next year, were going to know whether these drugs work for these types of cancer. Then, it will be more than a year or two to be absolutely sure of the magnitude of the benefit. Were going to know pretty quickly.

At major cancer treatment centers such as Dana Farber, genome analysis of breast cancer patients has become the norm only in the last 12 months, fueled by the $$131.4 million spent on genome research, which Krop called the next big wave for treating and attacking cancers.

The genetic screening at Dana Farber tests tumor tissue for 471 mutations across 41 genes.

The most obvious benefit of genome analysis is that it gives doctors a breadth of detail theyve never had before -- which genes are involved in the cancer.

As weve started having the ability to look at the DNA of individual cancers, its become clear that breast cancers -- even though they make look the same under microscope -- are clearly different, said Krop. They are driven by different alterations in their DNA.

Dr. Matthew Meyerson, a pathologist at Dana Farber and a senior co-author of a breast cancer genome study released in June, described the results as groundbreaking.

We found a lot of genes that are mutated in breast cancer that were previously only found in leukemia, he said.

The discovery could open up a new treatment, using leukemia-fighting drugs to inhibit the cancer-driving protein called PI3 kinase.

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Genome analysis promises hope for breast cancer patients

Sampling and sequencing

The cultivated and wild rice accessions were all from large collections of rice accessions preserved at the China National Rice Research Institute in Hangzhou, China, and the National Institute of Genetics in Mishima, Japan. The accessions were selected on the basis of the germplasm database records of phenotypic data and sampling localities to maximize genetic and geographic diversity. The collection was maintained by selfing in the laboratories. For each accession, genomic DNA from a single plant was used for sequencing, and seeds derived from the same plant were used for following field trials. In total, the genomes of 1,083 O. sativa accessions, 446 O. rufipogon accessions and 15 accessions of outgroup species were sequenced on the Illumina Genome Analyzer IIx generating 73-bp (or 117-bp) paired-end reads, each to approximately onefold (for O. sativa accessions), twofold (for O. rufipogon accessions) or threefold (for outgroup species) coverage. The detailed information, including geographic origin and sequencing coverage of the rice accessions, was listed in Supplementary Tables 2, 7 and 8. Library construction and sequencing of these accessions were performed as described21. One representative accession of O. rufipogon, W1943, was sequenced on the Illumina HiSeq2000, generating 100-bp paired-end reads with 100-fold genome coverage. An amplification-free method of library preparation49 was used in deep sequencing of the rice accession, which reduced the incidence of duplicate sequences, thus facilitating genome assembly and variation analysis.

The paired-end reads of all the rice accessions were aligned against the rice reference genome (IRGSP 4.0) using the software Smalt (version 0.4) with the parameters of -pair 50, 700 and -mthresh 50. SNPs were called using the Ssaha Pileup package (version 0.5) with detailed procedure described previously21. Genotypes of the rice accessions, including 1,083 O. sativa accessions, 446 O. rufipogon accessions and 15 accessions of outgroup species, were further called at the SNP sites from the Ssaha Pileup outputs. The genotype calls in 15 accessions of outgroup species were used to determine the ancestral states of SNPs in O. sativa and O. rufipogon. SNPs in coding regions, which were defined based on the gene models in the RAP-DB (release 2), were then annotated to be synonymous or non-synonymous for calculating the non-synonymous/synonymous ratio and dN/dS ratio. The genotype data set of the 1,529 rice accessions (1,083 O. sativa accessions and 446 O. rufipogon accessions) was generated on the basis of the calls in each rice accession. Seven sets of genome sequences, which included bacterial-artificial-chromosome-based Sanger sequences and high-coverage resequencing data, were used to assess the accuracy of the genotype data sets (Supplementary Table 6). The wild rice accessions with sequencing coverage >9 were selected to investigate the heterozygosity based on the overlapped reads that were aligned onto the reference sequence. For each accession, the proportion of heterozygosity genotypes was calculated at the polymorphic sites (Supplementary Table 3).

The software Haploview was used to calculate linkage disequilibrium with default settings, using SNPs with information in 446 O. rufipogon accessions50. Pairwise r2 was calculated for all the SNPs and then averaged across the whole genome. The matrix of pairwise genetic distance derived from simple SNP-matching coefficients was used to construct phylogenetic trees using the software PHYLIP51 (version 3.66). The software TreeView and MEGA5 were used for visualizing the phylogenetic trees. Principal component analysis of the SNPs was performed using the software EIGENSOFT52. The sequence diversity statistics () and the population-differentiation statistics (FST) were computed using a 100-kb window. The value of was calculated for each group in O. rufipogon and O. sativa, respectively, and the ratio of in the full population (or each clade) of O. rufipogon to that in the full population (or corresponding subspecies) of O. sativa was used to detect selective sweeps. The genomic regions where both O. rufipogon and O. sativa show a low level of genetic diversity were excluded for further analysis. To adopt appropriate thresholds to reduce the false-positive rate but also retain true selection signals, thresholds were chosen on the basis of both whole-genome permutation tests and signals at known loci. Permutation tests were performed to estimate the genome-wide type I error rate and determine the threshold to call selective sweeps (see Supplementary Information section 2 for details)53. The method cross-population extended haplotype homozygosity (XP-EHH) was also tested for detecting selective sweeps using the software xpehh54 (http://hgdp.uchicago.edu/Software/) (Supplementary Fig. 20). The genetic distance between two clades was computed based on the matrix of pairwise genetic distance, where the distance of all pairs of accessions from the two clades were retrieved and averaged. A custom Perl script was developed to plot all O. rufipogon accessions, using the public geographic information of world borders from the Thematic Mapping data set (version 0.3). The computational simulations under different demographic scenarios were performed using the program SFS_CODE40.

For the O. rufipogon population, approximately five seeds for each accession from the collection of wild rice were germinated and planted in the experimental field (in Sanya, China at N 18.65, E 109.80) from March 2011. The leaf sheath colour was observed and scored directly and the tiller angle was measured for each plant. The mapping population of 210 backcross inbred lines (BILs) and 61 chromosome segment substitution lines (CSSLs) was derived from a cross between O. sativa ssp. indica cv. Guangluai-4 and O. rufipogon accession W1943. The BILs were developed by one generation of backcross to Guangluai-4 followed with six generations of self-fertilization. The CSSLs were developed by five generations of backcross to Guangluai-4 followed with three generations of self-fertilization. Phenotyping was conducted in the experimental field (in Shanghai, China at N 31.13, E 121.28) from May to October, 2011. The fifteen traits that we phenotyped for this study include germination rate, tiller angle, heading date, stigma colour, the degree of stigma exsertion, plant height, panicle length, the degree of shattering, awn length, grain number per panicle, grain length, grain width, grain weight per 1,000 grains, hull colour and pericarp colour. The degree of stigma exsertion was scored based on the observation of ~20 randomly sampled spikelets of each line, on a scale of 13 (no, incomplete or complete exertion). Seed germination rate was measured by using mature seeds which were placed in a plastic Petri dishes kept at 30C in the dark for 48h5. Other traits were phenotyped and scored as described previously21, 22, 29.

For the genotype data set in O. rufipogon, genotypes of 446 O. rufipogon accessions were called specifically at the ~5 million SNP sites that were polymorphic in the O. rufipogon population. In the panel for GWAS, only the SNPs that have a minor allele frequency (MAF) of more than 5% and contain genotype calls of more than 100 accessions were left for subsequent imputation. The k-nearest neighbour algorithm-based imputation method was used for inferring missing calls21. The specificity of the genotype data set before and after imputation was assessed using three sets of genome sequences (Supplementary Table 6). Association analysis was conducted using the compressed mixed linear model55. The top five principle components were used as fixed effects and the matrix of genetic distance was used to model the variancecovariance matrix of the random effect. Permutation tests were used to define the threshold of association signals of the GWAS in the wild rice population. A total of 20 permutation analyses were performed (10 independent permutation tests for each of the two traits, sheath colour and tiller angle), which resulted in two association signals with the thresholds we set53. Hence, there were an average of 0.1 false positives (that is, totally two false positives in 20 permutation tests) in a single whole-genome scanning analysis. Simulation tests were used to compare the performance of GWAS between the populations of cultivated and wild rice.

Genomic DNA of each line in the mapping population was sequenced on the Illumina Genome Analyzer IIx, each to approximately 0.5 coverage. Both parents of the population, Guangluai-4 and W1943, were sequenced with at least 20 genome coverage, in a previous work21 and in this study, respectively. SNP identification between parents was conducted as described previously41. Genotype calling, recombination breakpoint determination and bin map construction was performed using the software SEG-Map (http://www.ncgr.ac.cn/software/SEG/). QTL analysis of the fifteen traits was conducted with the composite interval mapping (CIM) method implemented in the software Windows QTL Cartographer56 (version 2.5) with a window size of 10cM and a step size of 2cM. QTL with LOD value higher than 3.5 were called, of which the location was described according to its LOD peak location. The phenotypic effect (r2) of each QTL was computed using Windows QTL Cartographer. QTLs located within selective sweep regions were further used to associate the selected regions with their biological functions. It needs to be noted that we adopted a stringent threshold in the QTL calling (LOD>3.5), and the genomic regions with LOD ranging from 2.5 to 3.5 may include many minor QTLs (the threshold was set to 2.5 in most studies).

The genome of W1943 was assembled by using a custom pipeline integrating Phusion2 (clustering the raw reads into different groups)57 and Phrap (then assembling all the reads in each group to generate contigs)58. The N50 length of the entire assembly was calculated for the initial contigs with small contigs of <200bp excluded. All the full-length complementary DNA sequences46 of W1943 were aligned with the final assembly of W1943 genome sequence using the software GMAP59 (version 6) with the parameters -K 15000 and -k 0.97. The resulting contigs from whole-genome de novo assembly were anchored to the rice reference genome sequence (IRGSP4.0) using the software MUMmer60 (version 3).

Gene models of the genome of the wild rice W1943 were predicted using the software Fgenesh that was set for a monocot model61 (version 2.0). The resulting proteome of W1943 was compared with protein sequences in Rice Genome Annotation Project (version 7.0) using BLASTP with a cutoff of a minimum of 95% identity. Sequence variants, including SNPs, indels and imbalanced substitutions, were called using the diffseq program in the EMBOSS package62. Indels of large size were called from the alignment results of MUMmer. Effects of the sequence variants were predicted according to the gene models of Nipponbare in the RAP-DB (release 2) across the rice genome. For indels in genic regions and SNPs with large effect around the domestication loci, the effects were mainly based on the reference gene models.

The sequence reads of 1,083 O. sativa accessions, 446 O. rufipogon accessions and 15 outgroup accessions were then aligned against assembled genome sequences of W1943 using the same parameters with those against the reference Nipponbare genome sequences. Genotypes of each accession were called at all sequence variant sites (including SNPs, indels and imbalanced substitutions that were detected from assembled sequences), based on the alignment outputs against the two genome sequences. The allele frequencies at the sequence variant sites were calculated for each clade of O. sativa and O. rufipogon. In each clade, variant sites with information of less than 10 accessions (less than 2 for the outgroups) were then excluded for computing allele frequencies, namely no data available.

See more here:
A map of rice genome variation reveals the origin of cultivated rice

KANSAS CITY, Mo., Oct. 3, 2012 /PRNewswire/ --Today investigators at Children's Mercy Hospitals and Clinics in Kansas City reported the first use of whole genome information for diagnosing critically ill infants. As reported in Science Translational Medicine, the team describes STAT-Seq, a whole genome sequencing approach - from blood sample to returning results to a physician - in about 50 hours. Currently, testing even a single gene takes six weeks or more.

Speed of diagnosis is most critical in acute care situations, as in a neonatal intensive care unit (NICU), where medical decision-making is made in hours not weeks. Using STAT-Seq, with consent from parents, the investigators diagnosed acutely ill infants from the hospital's NICU. By casting a broad net over the entire set of about 3,500 genetic diseases, STAT-Seq demonstrates for the first time the potential for genome sequencing to influence therapeutic decisions in the immediate needs of NICU patients.

"Up to one third of babies admitted to a NICU in the U.S. have genetic diseases," said Stephen Kingsmore, M.B. Ch.B., D.Sc., FRCPath, Director of the Center for Pediatric Genomic Medicine at Children's Mercy. "By obtaining an interpreted genome in about two days, physicians can make practical use of diagnostic results to tailor treatments to individual infants and children."

Genetic diseases affect about three percent of children and account for 15 percent of childhood hospitalizations. Treatments are currently available for more than 500 genetic diseases. In about 70 of these, such as infantile Pompe disease and Krabbe disease, initiation of therapy in newborns can help prevent disabilities and life-threatening illnesses.

STAT-Seq uses software that translates physician-entered clinical features in individual patients into a comprehensive set of relevant diseases. Developed at Children's Mercy, this software substantially automates identification of the DNA variations that can explain the child's condition. The team uses Illumina's HiSeq 2500 system, which sequences an entire genome at high coverage in about 25 hours.

Although further research is needed, STAT-Seq also has the potential to offer cost-saving benefits. "By shortening the time-to-diagnosis, we may markedly reduce the number of other tests performed and reduce delays to a diagnosis," said Kingsmore. "Reaching an accurate diagnosis quickly can help to shorten hospitalization and reduce costs and stress for families."

About Children's Mercy Hospitals and Clinics Children's Mercy Hospitals and Clinics, located in Kansas City, Mo., is one of the nation's top pediatric medical centers. The 333-bed hospital provides care for children from birth through the age of 21, and has been ranked by U.S. News & World Report as one of "America's Best Children's Hospitals" and recognized by the American Nurses Credentialing Center with Magnet designation for excellence in nursing services. Its faculty of 600 pediatricians and researchers across more than 40 subspecialties are actively involved in clinical care, pediatric research, and educating the next generation of pediatric subspecialists. For more information about Children's Mercy and its research, visit childrensmercy.org or download our mobile phone app CMH4YOU for all phone types. For breaking news and videos, follow us on Twitter, YouTube and Facebook.

About The Center for Pediatric Genomic Medicine at Children's Mercy Hospital The first of its kind in a pediatric setting, The Center for Pediatric Genomic Medicine combines genome, computational and analytical capabilities to bring new diagnostic and treatment options to children with genetic diseases. For more information about STAT-Seq, diagnostic tests and current research, visit http://www.pediatricgenomicmedicine.com.

Melissa Novak Phone: (816) 346-1341 E-mail: mdnovak@cmh.edu

Carin Ganz Phone: (212) 373-6002 E-mail: cganz@golinharris.com

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50-Hour Whole Genome Sequencing Provides Rapid Diagnosis for Children With Genetic Disorders

Analysis of the genome sequence of the fruit known as the gift of the gods has shown that pears have some surprising differences to apple at the DNA level.

The European pear genome - sequenced by a team of scientists at Plant & Food Research in New Zealand and the Istituto Agrario di San Michele allAdige (IASMA) in Italy - has 600 million base pairs of DNA encoding around 51,000 genes on 17 chromosomes. By comparison, apple has 25% more DNA (750 million base pairs) with 57,000 genes on the same number of chromosomes. Many of the differences between the two correspond to areas of the genome that switch genes on or off.

"In ancient Greece, pears were lauded by the poet Homer as the gift of the gods, thanks to their melting texture and the unmistakeable aromatic pear flavour," says Dr David Chagn, the leader of the project. "We hope that by sequencing the genome of the European pear, with its melting flesh and wonderful flavours, and comparing it with the genome sequence of apple and Asian pears, which tend to be crisper, we will be able to identify how flesh texture in these fruits is controlled. Ultimately, this will allow us to develop tools to speed up the breeding of new varieties of pear with novel combinations of texture and flavours."

Most surprising to the science team was that the number of genes controlling texture, which was expected to be higher in pears due to the way the flesh melts in the mouth, were the same as that of apple. However, the research showed that in pears one family of these genes in particular, known as expansins, was significantly more active.

Dr Sue Gardiner, the leader of Plant & Food Researchs Breeding Technologies Group, believes the project is one of the fastest genome sequencing projects undertaken so far, taking only two years from inception to completion.

"This genome sequence project was led by scientists at Plant & Food Research, and the hard work and strong collaboration between all the scientists involved, both in Italy and New Zealand, has meant the sequence has taken much less time to deliver than other genome sequencing projects," she says.

Apples and pears evolved from a common ancestor around 35-50 million years ago, about 20 million years after this ancestor diverged from other fruits in the same family, such as strawberries and peaches. This divergence from other members of the Rosaceae family was caused by a duplication of the genome and corresponds to an era of major evolutionary activity, thought to be a genetic survival response to an event that caused the extinction of many species, including the dinosaurs.

Dr Gardiner is presenting the findings of the research at the Rosaceous Genomics Conference at IASMA in Trento, Italy this week.

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Surprising differences between apples and pears

Back in early 2010, molecular geneticist Michael Snyder, then a trim 54-year-old, decided to put his genetic blueprint under the microscope and make the results public. Swabbing saliva from his cheek with a sterile sponge and drawing blood to obtain his DNA samples, the Stanford scientist became the subject of one of the first clinical studies to analyze the blueprint of a healthy individual rather than someone known to be sick.

Snyder's study took advantage of recent technological advances that have now made it possible to rapidly and much less expensively sequence a genome--the instruction manual, contained in virtually every cell of a person, for making a human being. Containing some 3.2 billion pieces of genetic information, the genome determines a broad spectrum of human traits such as eye color, height, general health, and whether someone might be more likely to be a basketball player or a biologist.

What the Stanford researcher found surprised him. His genetic tests showed that he had a higher-than-average risk for developing adult onset, or type 2, diabetes even though he wasn't overweight, nor did he have any known family history of the disease. But during the 14-month study, in which Snyder's health was closely monitored using a battery of tests, his glucose levels spiked and remained high following a respiratory infection. Only after six months of increased exercise and a change in diet did Snyder's glucose levels drop back to normal, he and colleagues reported in the March 16 issue of the journal Cell.

[See 7 Mind-Blowing Benefits of Exercise]

The $1,000 mark. Without the genetic testing, Snyder says, he would not have known of his diabetes risk or been able to address it so quickly. And with the cost of genome mapping already as low as a few thousand dollars and likely to reach a much-ballyhooed benchmark of $1,000 by next year, Snyder and other scientists see the procedure as a crucial part of medicine for everyone, not just the affluent or the curious.

Many experts, though, like Eric Topol, director of the Scripps Translational Science Institute in San Diego, caution that science is only in the embryonic stage of understanding the composition and inner workings of the human genome. Essentially, each person carries two copies of each gene--one from each parent--in every cell (except mature red blood cells). Within these cells, genetic information is divided into 23 pairs of smaller packages, called chromosomes, that store the 20,000 or so genes in the human body, along with other bits of genetic information. The genes in turn are made up of deoxyribonucleic acid, or DNA, molecules whose two strands wrap around each other like vines, forming the iconic double helix structure. Using a four-letter alphabet, scientists have identified and labeled the four building blocks, or bases: adenine (A), thymine (T), guanine (G), and cytosine (C), which combine in each DNA molecule according to precise rules, somewhat like the rungs on a ladder. An A must always seek out a T on its partner strand, while a G must always pair with a C.

If the bases are the musical notes that make up the genome's keyboard, then their exact ordering determines whether the genetic symphony is harmonious or discordant. Just as extra or missing notes can wreck a musical passage, an extra or missing A or T can increase a person's risk of developing a particular disease or, in rare cases, cause an incurable illness.

[See How to Avoid the Biggest Health Risks]

The challenge with genome mapping is that large portions of the map reflect uncharted territory. Researchers understand the role of genes in the body fairly well: They dictate how proteins--the compounds necessary for building and repairing muscles and other tissue--are made. But protein-coding genes account for only 1.5 percent of the human genome. A lot of the action appears to be happening in the other 98.5 percent. Once referred to as "junk DNA," this vast but little-explored portion of the genetic blueprint is now believed to play a critical role in regulating gene activity and carrying out unidentified functions that contribute to a person's being predisposed to a disease.

"People will need to be prepared for the fact that these tests are so new that the physician may have limited ideas of what to make of it and what to do with it," says genetic counselor Barbara Biesecker of the National Human Genome Research Institute in Bethesda, Md.

Continued here:
Should You Get Your Genome Mapped?

Public release date: 1-Oct-2012 [ | E-mail | Share ]

Contact: ESMO PRESS OFFICE media@esmo.org European Society for Medical Oncology

VIENNA, Austria, 1 October 2012 For the first time, researchers have conducted a large trial in which they tested the entire genome of individual breast cancers to help personalize treatment. They released their findings at the ESMO 2012 Congress of the European Society for Medical Oncology in Vienna.

In recent years, a number of drugs have been developed that target specific genetic alterations in cancer. To choose which of these drugs are suitable for individual patients, some genetic testing is performed. "In most of these cases, these genetic testing approaches only analyze a limited number of genes," said study author Dr Fabrice Andr from Institute Gustave Roussy, Villejuif, France.

The theoretical benefit of whole genome testing is that this approach can identify both frequent and rare unexpected genomic events. "In addition, it allows us to quantify the level of genomic instability, and to detect whether driver mutations are associated with genomic alterations involved in resistance to targeted agents," Dr Andr said.

In terms of healthcare delivery and policy, developing whole-genome approaches also means new bioassays do not need to be designed for each new target discovered in cancer.

In the SAFIR01 trial, Dr Andr and colleagues developed a program where the entire genome from a biopsy of a metastatic lesion was analyzed prospectively for individual patients with metastatic breast cancer. They used array CGH (aCGH) and Sanger sequencing to identify the genetic alterations in the metastatic tissue, which allowed them to identify which genes were mutated, amplified or deleted. This genomic information was prospectively used to propose different targeted therapies. The study was conducted and sponsored by UNICANCER and funded by the French National Cancer Institute.

As of 23 September 2012, biopsies had been performed in 402 breast cancer patients, including 26 patients for whom analyses are ongoing. Of those, a genomic result could be generated in 276 patients, including whole genome analysis in 248. A genomic alteration "targetable" by an anticancer drug was found in 172 of those patients, Dr Andr said. Interestingly, around 20% of the patients presented a very rare and sometimes unexpected genomic alteration, highlighting the need for whole genome approaches.

"The main message is that whole genome approaches can be delivered in the context of daily practice in large cohorts, allowing us to identify targets that can be inhibited in a high proportion of patients, leading to anti-tumor effects. This study suggests that time has come to bring personalized medicine to the cancer field," Dr Andr said.

Although only a minority of patients needed an investigational agent since the biopsy, 26 patients so far received a targeted agent matched to the genomic alteration. The goal is to reach more than 80 patients treated with a targeted agent.

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First large scale trial of whole-genome cancer testing for clinical decision-making reported

CAMBRIDGE, Mass.--(BUSINESS WIRE)--

Knome Inc. announced today that it is taking orders for the knoSYS100, the first plug-and-play, fully integrated hardware and software system designed to help researchers in medical and academic institutions interpret human whole genomes. The knoSYS100 was developed to help geneticists discover relevant genetic variation, investigate diseases of unknown cause, and create next generation in silico gene tests. Units will begin shipping in Q4, 2012.

Starting at $125,000, the knoSYS100 is based on Knomes big data informatics technology. The system will accept next generation sequence data from leading sequencers, including those sold by Illumina (ILMN), Life Technologies (LIFE), and Complete Genomics (GNOM).

Breaking the genome interpretation bottleneck

The difficulty and cost associated with human genome sequencing has largely been addressed, with the cost of sequencing a whole genome expected to decline to under $1,000 in 2013. But it still takes a team of researchers weeks to months to annotate, compare, and interpret genome data. This slow pace and the lack of robust tools have significantly limited the ability of researchers to scale the process of interpreting human genomes.

With an average throughput of one genome per day, the knoSYS100 eliminates the current informatics bottleneck in whole genome interpretationmatching the speed of todays fastest sequencers.

In the first half of this year, we saw the demand for genome interpretation surge as researchers in many of the worlds leading medical institutions started preparing for the broad utilization of whole genome interpretation for patient care, said Martin Tolar, MD, PhD, Chief Executive Officer of Knome. All of these institutions face the same issuehow to industrialize genome interpretation so that it is not only accurate, but fast.

More than a dozen of the worlds top medical institutions have joined an early access program to pilot Knomes genome interpretation technology, including: ARUP Laboratories, Cedars-Sinai Medical Center, Cincinnati Childrens Hospital, The Hospital for Sick Children (SickKids) in Toronto, Hyundai Cancer Institute at CHOC Childrens, University of Liverpool, and University of Verona.

An in silico genetic testing lab in a box

In addition to providing geneticists with query and visualization applications for conducting in-depth research into sets of whole genomes, the knoSYS100 ships with tools and libraries that allow developers to create in silico gene tests that can be run at the push of a button.

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Knome Introduces the knoSYS™100; First Plug-and-Play Human Genome Interpretation System

WORCESTER Two professors at the University of Massachusetts Medical School are playing a role in a global effort to unlock the mysteries of the human genome, which is the complete set of genetic instructions for humans.

Medical school professors Job Dekker and Zhiping Weng participated in an international consortium of scientists from 32 institutions that made headlines this month with its findings. The scientists involved in the Encyclopedia of DNA Elements project, or ENCODE, announced that parts of the genome often dismissed in the past as junk DNA actually play an important role in regulating what genes do.

Through the projects research, scientists have gained an understanding of 80.4 percent of the human genome, the UMass Medical School professors said.

That is a tremendous improvement in our understanding of the genome, said Mr. Dekker, who holds a doctorate and is professor of biochemistry and molecular pharmacology and co-director of the schools Systems Biology program.

Researchers involved in the project used a range of experimental approaches to understand what pieces of DNA are regulating genes. The research labs of Mr. Dekker and Ms. Weng, who holds a doctorate and is the director of the medical schools program in bioinformatics and integrative biology, worked on separate projects that contributed to the effort.

The findings of the international project appeared in 30 papers published in the journals Nature, Genome Research and Genome Biology. Mr. Dekker was the lead author of one of the Nature papers. The results of Ms. Wengs efforts were published in Genome Research. The consortiums work received funding from the National Human Genome Research Institute, part of the National Institutes of Health.

The professors touted the data produced by ENCODE which built upon the Human Genome Project completed in 2003 as the basis for further study in the genetic causes of human disease and a potential boon for pharmaceutical and other medical research.

For the past decade, Mr. Dekker has helped develop methods to create three-dimensional models of folded chromosomes. Those models can be used to determine which parts of the genome touch each other, according to the medical school.

Scientists have believed for a number of years that a regulatory element could control a gene by physically interacting with that gene, Mr. Dekker said. His goal is to measure the three-dimensional structure to see which regulatory elements physically touch what genes, he said.

We have gone from this view of the genome where we have here and there a gene and then large sections of unknown of territory, Mr. Dekker said. We now have a much richer picture of the genome, where we can see genes, and we can set lots and lots of these regulatory elements.

Link:
UMass Med professors are sleuths of the genome

September 29, 2012

redOrbit Staff & Wire Reports Your Universe Online

Thanks to a grassroots fundraising campaign, researchers were able to sequence the genome of the critically endangered Puerto Rican Parrot the only surviving member of its species in the United States.

The project, which was funded primarily through community donations, was published Friday in BioMed Central and BGIs open access journal GigaScience. It is the first of the large Neotropical Amazona birds to be studied at the genomic level, the journal said in a prepared statement.

The Puerto Rican Parrot (or Amazona vittata) could once be found throughout the Caribbean archipelago, but experienced a severe population decline in the 19th century due to agriculturally-motivated deforestation. As of approximately 40 years ago, it was believed that only a handful of the birds had survived, and despite the success of captive breeding programs, there are still very few of these parrots living in the wild.

In this project we managed to cover almost 76% of the A. vittata genome using money raised in art and fashion shows, and going door to door asking for the support of Puerto Rican people and local businesses, Dr. Taras Oleksyk, organizer of the campaign to sequence the genome, said. When we compared our sequence of our parrot, Iguaca, from Rio Abajo to other species of birds, we found that she had 84.5% similarity to zebra finches and 82.7% to a chicken, but her genome was highly rearranged.

We are very proud of our project and even more proud to be part of a local community dedicated to raising awareness and furthering scientific knowledge of this endangered bird, Dr. Oleksyk added. All the data from this project is publically available which we hope will be a starting point for comparative studies across avian genome data, and will be used to develop and promote undergraduate education in genome science in the Caribbean. Community involvement may be the key for the future of conservation genetics, and many projects like this are needed reverse the current rate of extinction of birds across the globe.

The project was funded in a handful of unique and creative ways, according to GigaScience. Student groups organized art shows and fashion shows, while other community members turned to social networking websites and even chipped in with private donations from regular citizens to help raise the $3 billion required to sponsor the research.

What is remarkable here is that it shows how accessible genomic technology has become, GigaScience officials said in a statement. This project serves as a signal that work on large-scale whole-genome projects is becoming more democratized, and opens the door for more creative input from outside the large genome centers.

As for the actual genome, the scientists report that it is approximately half the size of the human genome (approximately 1.58 genomic biomarker panels or Gbp). The research was carried out at the University of Puerto Rico-Mayaguez (UPRM) biology department.

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Community Fundraising Effort Helps Researchers Sequence Parrot Genome