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22 Abstracts / Current Opinion in
pectrum of clinical symptoms. Dundar syndrome (Adductedhumb–clubfoot syndrome, ATCS) represents the first disorder ofermatan sulfate biosynthesis and thus a novel form of CDG. It is anutosomal recessive, generalized connective tissue disorder withongenital malformations, contractures of thumbs and feet, a typ-cal facial appearance, and normal cognitive development. ATCSs caused by loss-of-function mutations in CHST14 encoding N-cetylgalactosamine 4-O-sulfotransferase 1 which catalyzes 4-Oulfation of N-acetylgalactosamine in the repeating iduronic acid-lpha1,3-N-acetylgalactosamine disaccharide sequence to formermatan sulfate. This results in an altered pattern of dermatannd chondroitin sulfate chains on their corresponding proteogly-ans. ATCS is the first human disorder that emphasizes roles forermatan sulfate in human development and extracellular matrixaintenance.
oi:10.1016/j.copbio.2011.05.031
SL7
e novo mutations in dysmorphic syndromes
an G. Brunner
Department of Human Genetics, University Medical Center, St Rad-oud, Nijmegen, The Netherlands
-mail address: [email protected]
Many syndromes occur sporadically without a known cause. Its possible that such conditions are due to de novo mutations butntil recently the technology to prove this was rarely available.
I shall show examples from our recent experience on such syn-romes that used next generation sequencing to find the genesor such conditions. Examples include the Schinzel-Giedion syn-rome, the Bohring-Opitz syndrome, the Gomes-Lopez-Hernandesyndrome, and a novel mental retardation syndrome that has notet been named. Collectively, our data show that exome sequencings particularly suited to find the genetic cause in sporadic syndromicatients.
oi:10.1016/j.copbio.2011.05.032
SL8
ransgenic crops: Present status and future develop-ents
scar Vicente
Instituto de Biologia Molecular y Celular de Plantas (UPV-CSIC), Uni-ersidad Politécnica de Valencia, Valencia, Spain
-mail address: [email protected]
In 2010, transgenic crops were cultivated in 148 million hectaresn 29 countries, by 15.4 million farmers — over 90% small farmers ineveloping countries. This area represents an 87-fold increase com-ared to the 1.7 million hectares planted in 1996, when GM plantsere first commercialised. This rapid growth confirms that biotech
rops provide substantial economic benefits for the farmers (higherields and lower production costs); but they are also beneficial forhe environment: lower use of pesticides, reduction in fuel con-umption and CO2 emissions. GM crops will significantly contributeo solving some of the major challenges facing humankind in theext decades, including the foreseeable effects in agriculture of
lobal climate change, with higher average temperatures, increas-ng scarcity of water for irrigation, and longer and more frequentrought periods. Increased cultivation of the herbicide-tolerantgga
hnology 22S (2011) S15–S152
nd insect-resistant biotech crops available today, together withrought and salt-tolerant varieties now under development, willoost crop productivity and help to optimise land use, an urgenteed if we are to feed the growing world population — which willeach 9.2 × 109 people by 2050 — while contributing to a sustain-ble and more environmental-friendly agriculture.
Source: James, C. (2010). ISAAA Brief 42.
oi:10.1016/j.copbio.2011.05.033
SL9
ayesian network based pathway analysis of microarrayata
enol Isci 1, Cengihan Ozturk 1, Jon Jones 2, Hasan Otu 3,4
Bogazici University, Institute of Biomedical Engineering, 34342 Istan-ul, TurkeyDepartment of Urology, Johannes Gutenberg University, 55131ainz, GermanyBIDMC Genomics Center, Department of Medicine, Harvard Medicalchool, Boston, MA, USAIstanbul Bilgi University, Department of Bioengineering, Istanbul,urkey
-mail address: [email protected] (H. Otu)
Analysis of high throughput biological data targeting biochem-cal interactions in the cell is best explained within the context ofetworks and pathways. Such data generally represents stochasticonlinear relations embedded in noise. Bayesian Network (BN) the-ry provides a framework to analyze data regarding gene regulationeasurements as this framework naturally handles aforemen-
ioned obstacles. Here we provide a method that models knowniological pathways as BNs and reflects results of a given microar-ay experiment to find pathways that best explain underlyingnteractions. During this process we convert biological pathwayso directed acyclic graphs and calculate a score measuring fitnessf observed microarray data to a given network. We assess statisti-al significance of these scores by randomization via bootstrappingnd identify relevant pathways with a certainty that can be useds a comparative measure. Our simulations using synthetic andeal data demonstrated robustness of proposed approach. Proposedethod provides improvement over existing similar approaches by
ot considering genes in a pathway simply as a list but incorporat-ng to its model the topology via which genes in a given pathwaynteract with each other.
oi:10.1016/j.copbio.2011.05.034
SL10
omputational recognition of gene boundaries
lham Ayub Shahmuradov
Department of Fundamental Problems of Biological Productivity,ioinformatics Lab, Institute of Botany, Baku, Azerbaijan
-mail address: [email protected]
A typical eukaryotic protein gene consists of open readingrame, a subsequence without post-transcriptionally removedntrons, which code an amino acid sequence, and non-coding′-regions and 3′-regions that play a key role in regulation of
ene expression. Upstream and downstream non-coding regions ofenes include transcription start sites (TSSs) and pre-mRNA cleav-ge/polyadenylation sites (poly(A) sites), gene start and end points
