Identification of somatic/ mosaic SV and transposon activity and their crosstalk to DNA epigenetic Modifications
Identification of somatic/ mosaic SV and transposon activity and their crosstalk to DNA epigenetic Modifications
批准号:
10662143
负责人:
Fritz J Sedlazeck
金额:
$29.48万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-04-15 至 2025-03-31
关键词:
AddressAlgorithmsAttentionAwarenessBeliefBenchmarkingBiologyBloodBrainCatalogsCollaborationsCommunitiesComplexComputer softwareComputing MethodologiesDNADNA SequenceDNA Sequence AlterationDNA Transposable ElementsDataDetectionDiseaseElementsEnsureEpigenetic ProcessEthnic OriginEvaluationEventFeedbackFosteringFrequenciesGene ExpressionGenesGenomeGenomic SegmentHumanHuman GenomeIndividualKnowledgeLaboratoriesLiverLocationMachine LearningMalignant NeoplasmsMeasuresMethodologyMethodsMethylationModificationMosaicismMovementMutationPhasePopulationProductionRecording of previous eventsResearch PersonnelResolutionShapesShort Tandem RepeatSignal TransductionSingle Nucleotide PolymorphismSomatic MutationStatistical ModelsTandem Repeat SequencesTechnologyTissuesVariantWorkanalytical methodcostgenetic varianthackathonhuman reference genomeimprovedinsightmethod developmentmethylation patternmosaicmosaic variantnoveltoolvariant detection
中文摘要
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英文摘要
Studies of somatic mutation have so far focused on cancer or other severe diseases, with little attention
to the basic biology of this important class of variation. As a consequence, the somatic variation catalog
to be produced by the SMaHT network fills an essential need. To build this catalog, novel methods and
approaches are required since current methods cannot comprehensively assess somatic structural
variation (SV) nor transposon activation at scale, or with adequate resolution. We will develop novel
computational methods based on long-read sequencing and will make the methods broadly available
across the SMaHT network. The approaches will leverage new algorithmic and machine learning
approaches, be scalable and provide a reduced error rate, at lower cost. There will be a special focus
on the identification of the movement of transposons across the genome. For this we will implement
better annotation and characterization of insertions and translocations that are evidence for
transposition. In addition, we will identify methylation signals from long-read sequencing data.
Correlation of methylation changes and somatic & mosaic mutations will reveal how these genomic
alterations shape the methylation patterns in critical regions and likely impact genes. To foster the
collaboration with other groups we will closely work together with SMaHT sequencing and analysis
centers. Multiple activities such as the formation of a NIST & SMaHT somatic variation benchmarks, as
well as annual Hackathons, will engage investigators from around the world. The group’s history of
successful methods development will ensure that the SMaHT network will receive useful and
comprehensive new tools to extend the knowledge of somatic and mosaic SVs and transposition.
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