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澳大利亚知名专家全英文研究性教学公开课:“组学”在家畜育种和遗传学中的应用

地点:文汇路校区7号楼附楼2楼学术研讨室

Class location: Academic Meeting room, the building attaching the 7# Building, Wenhui Road campus. Yangzhou University.

课程:组学在家畜育种和遗传学中的应用  

Course: Application of ‘OMICS’ to Livestock Breeding and Genetics

教师:澳大利亚联邦科学与工业研究组织(CSIRO)首席科学家 Dr.Toni Reverter

Instructor Name: Toni Reverter, senior principal research scientist of Commonwealth Scientific and Industrial Research Organisation (CSIRO)

组织单位:动物科学技术bbin真人/畜牧学优势学科;教育部国际合作联合实验室

Organization unit: College of Animal Science and Technology/ Animal science preponderant discipline, The Ministry of Joint International Research Laboratory

 

教学内容与时间安排

 Course Arrangement

Unit

Date

Topic

Unit 1: lecture Monday

Oct. 7

8:00 - 12:00

1.       Introduction to ‘OMICS”, Course Outline and   Transcriptomics Data Analysis

1)        PREAMBLE   – GENERAL (OPEN) SEMINAR

How   much Mathematics does a Biologist need, and vice-versa?

COURSE OUTLINE

2)        REVIEW   OF MOLECULAR CELL BIOLOGY

                                                          i.              Prokaryotes   vs Eukaryotes

                                                        ii.              Sub-cellular   components and organelles

                                                      iii.              Basic   cell functions: Replication, Transcription, and Translation

                                                       iv.              Organic   compounds: Carbohydrates, Lipids, and Proteins

                                                         v.              The   ABC of Metabolism

Unit 2: lecture Monday

Oct. 7

14:00 - 18:00

2.       Introduction to ‘OMICS”, Course Outline and   Transcriptomics Data Analysis

3)        REVIEW   OF MOLECULAR ‘OMICS’ DATA

                                                          i.              Genomics

                                                        ii.              Epigenomics

                                                      iii.              Transcriptomics

                                                       iv.              Proteomics

                                                         v.              Metabolomics

                                                       vi.              Metagenomics/Microbiomics

4)        INTRODUCTION   TO TRANSCRIPTOMICS (RNA-SEQ) DATA ANALYSIS

                                                          i.              Data   preparations, Edits, Transformation and Normalization

                                                        ii.              Differential   expression and Functional categories of interest

                                                      iii.              Gene   Ontology (GO), GO Enrichment and The GOrilla tool

                                                       iv.              Cluster   analysis and the PermutMatrix software:

5)        HOMEWORK   #1

                                                          i.              PermutMatrix

                                                        ii.              Data   from Cánovas et al. (2014):

Unit 3: lecture Tuesday

Oct. 8

8:00 - 12:00

3.       Beyond Differential Expression and Gene   Co-Expression Networks

1)        REVIEW   OF HOMEWORK #1

                                                          i.              Data   from Alexandre et al. (2019):

2)        BEYOND   DIFFERENTIAL EXPRESSION

                                                          i.              The   quest for causal mutations

                                                        ii.              eQTL:   for the inference of gene networks: Random vs Scale-Free networks.

Unit 4: lecture Wednesday

Oct. 9

8:00 - 12:00

4.           Beyond Differential Expression and Gene Co-Expression   Networks

3)      GENE   CO-EXPRESSION NETWORKS

                                                          i.              Basic network   metrics: Motifs, connectivity degree and clustering coefficient

                                                        ii.              Algorithms for the   inference of gene networks: Random vs Scale-Free networks

                                                      iii.              The Cytoscape   software:

4)      HOMEWORK   #2

                                                          i.              NetSimul F90 Program:   Simulate random and scale-free networks

                                                        ii.              Replicate the network   from Alexandre et al. (2019)

                                                      iii.              Scripts for the   Co-Authorship network

Unit 5: lecture Thursday

Oct. 10

8:00 - 12:00

5.       Analytical Methods for Gene Network Inference

1)        REVIEW OF HOMEWORK #2

                                                          i.              Edge and node attributes to the   visualization scheme

2)        THE PCIT ALGORITHM AND RIF METRICS

                                                          i.              PCIT – Partial Correlation and   Information Theory

                                                        ii.              RIF – Regulatory Impact Factors

Unit 6: lecture Friday

Oct. 11

14:00 - 18:00

6.       Analytical Methods for Gene Network Inference

3)      GENE   CO-ASSOCIATION NETWORKS

                                                          i.              AWM – Association   Weight Matrix

                                                        ii.              Fortes et al. 2010.   Proc Natl Acad Sci USA 107:13642-13647

                                                      iii.              Reverter and Fortes.   2013. Methods Mol Biol. 1019:437-447

3)      FURTHER   RECENT APPLICATIONS TO LIVESTOCK

                                                          i.              Beef meat tenderness: Ramayo-Caldas et al. 2016. Genet Sel Evol 48:37

                                                        ii.              Broiler feed efficiency:  Bottje et al. 2017. BMC Syst Biol. 11:29

                                                      iii.              Atlantic salmon:   Mohamed et al. 2018. Front Genet 9:369

 

 

教师简介:

Dr. Toni Reverter-Gomez澳大利亚联邦科学与工业研究组织(CSIRO)首席科学家,博士生导师。1989年于西班牙巴塞罗那大学获得兽医学学士学位,1994年于美国科罗拉多州立大学获得统计学硕士学位和动物科学(数量遗传学方向)博士学位,1994-1995年于西班牙农业部进行博士后研究。1995年至2002年先后任职于西班牙巴塞罗那大学和澳大利亚新英格兰大学,2002年起任职于澳大利亚联邦科学与工业研究组织。主要从事家畜基因组学,转录组学,表观遗传学和代谢组学的大数据分析研究,在国际家畜数量遗传研究领域上享有极高的知名度。在BioinformaticsPhysiological Genomics BMC Genomics17个国际知名杂志担任编委,截至2018年已培养博士后6名。先后在Animal Production Science , J Anim SciBMC GenomicsBMC Syst Biol,等国际知名期刊上发表论文134篇,累计影响因子300以上,论文被引次数近3000次。先后主持或参与澳大利亚国家资助、州立资助、学校等部门科研项目12项,累计获科研经费近700万澳元,。

 

Dr. Toni Reverter-Gomez, senior principal research scientist of Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia, a global well-known scientist in livestock quantity genetic research field, with over 100 refereed publications and been cited more than 2,900 times, as well as invited and contributed papers to international meetings, book chapters, patents and reports. Dr. Toni’s research interest focuses on livestock genomic, transcriptomic, epigenetic and metabolomics, especially Big data analysis in animal science, constantly committed to develop creative analytical methods and capabilities in this area.

 

欢迎广大师生参加学习!

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