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讲 座 提 纲

讲 座 提 纲. 1 什么是分子育种 2 历史回顾 3 全基因组策略 4 基因型鉴定 5 表现型鉴定 6 环境 型鉴定 ( etyping ) 7 标记 - 性状关联分析 8 标记 辅助 选择 9 决策支撑系统 10 展望. Link network in a background of organism. Metagenomics. Genes to Network. Protein-DNA ChIP on Sequencing.

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讲 座 提 纲

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  1. 讲 座 提 纲 1 什么是分子育种 2 历史回顾 3 全基因组策略 4 基因型鉴定 5 表现型鉴定 6 环境型鉴定 (etyping) 7 标记-性状关联分析 8 标记辅助选择 9 决策支撑系统 10 展望

  2. Link network in a background of organism Metagenomics Genes to Network Protein-DNA ChIP on Sequencing mRNA, ncRNA, small RNA, miRNA, regulatory RNA Gene expression Finding genes whole transcriptome shotgun Studying gene regulation DNAmethylation, whole genome/targeted region resequencing SVs, SNP identifying, Exome sequencing whole genome sequencing targeted region sequencing Improve health and design better crops & sequencing sequencing sequencing Network

  3. Development of Sequencing Technology

  4. Environmental factors Pedigree Air Light Humidity Temperature Mechanical Nutrients Water Pathogens Symbionts Genotype Genome Phenotype Metablome Transcriptome Proteome Pathways Networks Data Tsunami

  5. Data Tsunami - Examples Genotype data Kb level: All available germplasm Maize (27,000 accessions, CIMMYT) Wheat (148,000 accessions, CIMMYT Rice (113,000 accessions, IRRI) Mb level: Marker X Accessions 10K X 100K for variety protection & MAS 50K X 100K for genetic diversity 2-5M X 10K for GWAS (maize) Tb level: Omics data DNA sequence Resequencing 100 maize inbreds at 10X 100 inbreds X 10X depths X 2.5Gb =2.5Tb RNA sequence Protein sequence

  6. Bioinformatics and Computing Are Needed in Plant Breeding Breeders need help with breeding informatics tools to get out of the data tsunami We need to work together to make this happen Revised from Gary Atlin Breeder

  7. Integration of Information of Multiple Sources • Genotypic data from large numbers of accessions/ individuals across populations and germplasm collections • Phenotypic data collected worldwide and multi-location trials for the genotyped accessions/individuals • Environmental data collected from the environments where the phenotyping is performed Super Computation Platform

  8. Breeding Informatics Information Collection Information Integration Data standardization Development of generic databases Use of controlled vocabularies/ontologies Interoperable query system Redundant data condensing Database integration Tool-based information integration Information retrieval and mining Information management systems G-P-E

  9. Missing Data Imputation and HaplotypeAnalysis I II III Missing data rate: 66% Missing data rate: 2% Average accuracy: ~98% (based on four sets of BACs-based sequences and high-coverage sequence data for quality control)

  10. Decision Support Tools Germplasm management, evaluation, and enhancement Breeding population management and improvement Building up heterotic patterns Prediction of hybrid performance Marker-assisted inbred and synthetic creation Genetic map construction Marker-trait association identification and validation Marker-assisted selection methodologies and implementation Genotype by environment interaction analysis Intellectual property right and plant variety protection Breeding design through simulation and modeling G-P-E Xu 2010 Molecular Plant Breeding. CABI

  11. ICIS Integrated IMS for molecular breeding LIMS and Analytical Tools for Genetic Improvement DataToolsOutput Genotype Sequences Markers Maps Genealogy Gene functional analysis Genetic diversity Germplasm evaluation Germpalsm classification Variety identification Genetic mapping Marker-trait association Marker-assisted selection GXE interaction Environmental classification Variety stability/adaptability BLASTN/X… Mapmaker MultiQTL GeneFlow QTL Cartographer SAS/JAMP Structure GeneMapper PowerMarker Arlequin BiPlot CMTV TASSEL …….. Phenotype Yield Quality Agronomy Stress response Environment Water Fertilizer Soil Temperature Precipitation GIS Day length Xu 2010 Molecular Plant Breeding. CABI

  12. Integrated Breeding Platform (IBP) https://www.integratedbreeding.net/ • A web-based, consolidated vehicle for dissemination of knowledge, tools and services, enabling broad access to and proactive distribution of • Crop information and breeding material • Molecular, genomics and informatics technology • Cost-effective high-throughput genotyping services • Capacity-building programs to design and carry out crop breeding projects • Coordinated by the Generation Challenge Programmeof the CGIAR.

  13. IBP provides tools to help breeders in • designing experiments • managing experiments • collecting data • storing data • conducting analyses The tools are available for download as a single consolidated application – the Integrated Breeding Workflow System (IBWS). More information from Gary Atlin and Jean-Marcel Ribaut (2014)

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