Comparative Genome Analysis and Genome Evolution of Members of the Magnaporthaceae Family of Fungi.

Slides:



Advertisements
Similar presentations
Reproduction Specific Argonaute Genes In Maize and Barley And Their Role In Transposon Silencing Manjit Singh 1, Daniel Grimanelli 2 and Jaswinder Singh.
Advertisements

COMPARATIVE FUNGAL GENOMICS : KNOWN KNOWNS & KNOWN UNKNOWNS. Josh Herr, Plant Biology Interdepartmental Program.
Phylogenetics workshop: Protein sequence phylogeny week 2 Darren Soanes.
Finding regulatory modules from local alignment - Department of Computer Science & Helsinki Institute of Information Technology HIIT University of Helsinki.
Basics of Comparative Genomics Dr G. P. S. Raghava.
Differential insertion of transposable elements in Anopheles gambiae M & S genomes Jenica L. Abrudan, Ryan C. Kennedy, Maria F. Unger, Michael R. Olson,
Tools to analyze protein characteristics Protein sequence -Family member -Multiple alignments Identification of conserved regions Evolutionary relationship.
Investigating the Importance of non-coding transcripts.
An analysis of “Alignments anchored on genomic landmarks can aid in the identification of regulatory elements” by Kannan Tharakaraman et al. Sarah Aerni.
BACKGROUND E. coli is a free living, gram negative bacterium which colonizes the lower gut of animals. Since it is a model organism, a lot of experimental.
Analyses of ORFans in microbial and viral genomes Journal club presentation on Mar. 14 Albert Yu.
Systematic Analysis of Interactome: A New Trend in Bioinformatics KOCSEA Technical Symposium 2010 Young-Rae Cho, Ph.D. Assistant Professor Department of.
TGCAAACTCAAACTCTTTTGTTGTTCTTACTGTATCATTGCCCAGAATAT TCTGCCTGTCTTTAGAGGCTAATACATTGATTAGTGAATTCCAATGGGCA GAATCGTGATGCATTAAAGAGATGCTAATATTTTCACTGCTCCTCAATTT.
Comparative Genomics of the Eukaryotes
Genome projects and model organisms Level 3 Molecular Evolution and Bioinformatics Jim Provan.
Functional Linkages between Proteins. Introduction Piles of Information Flakes of Knowledge AGCATCCGACTAGCATCAGCTAGCAGCAGA CTCACGATGTGACTGCATGCGTCATTATCTA.
Origins and impact of constraints in evolution of gene families Boris E. Shakhnovich and Eugene V.Koonin Genome Research 2006, October 19 Stella Veretnik.
Ultraconserved Elements in the Human Genome Bejerano, G., et.al. Katie Allen & Megan Mosher.
Chapter 26: Phylogeny and the Tree of Life Objectives 1.Identify how phylogenies show evolutionary relationships. 2.Phylogenies are inferred based homologies.
1 Orthology and paralogy A practical approach Searching the primaries Searching the secondaries Significance of database matches DB Web addresses Software.
발표자 석사 2 년 김태형 Vol. 11, Issue 3, , March 2001 Comparative DNA Sequence Analysis of Mouse and Human Protocadherin Gene Clusters 인간과 마우스의 PCDH 유전자.
Finish up array applications Move on to proteomics Protein microarrays.
Genomes and Their Evolution. GenomicsThe study of whole sets of genes and their interactions. Bioinformatics The use of computer modeling and computational.
DNA PACKAGING. 8 histones make up the nucleosome core DNA wraps twice around the 8 histones Histone 1 helps maintain the nucleosome DNA is negatively.
TGCAAACTCAAACTCTTTTGTTGTTCTTACTGTATCATTGCCCAGAATAT TCTGCCTGTCTTTAGAGGCTAATACATTGATTAGTGAATTCCAATGGGCA GAATCGTGATGCATTAAAGAGATGCTAATATTTTCACTGCTCCTCAATTT.
Ch. 21 Genomes and their Evolution. New approaches have accelerated the pace of genome sequencing The human genome project began in 1990, using a three-stage.
Construction of Substitution Matrices
Fea- ture Num- ber Feature NameFeature description 1 Average number of exons Average number of exons in the transcripts of a gene where indel is located.
Protein and RNA Families
Genome Analysis II Comparative Genomics Jiangbo Miao Apr. 25, 2002 CISC889-02S: Bioinformatics.
Genomics and Forensics
1 From Mendel to Genomics Historically –Identify or create mutations, follow inheritance –Determine linkage, create maps Now: Genomics –Not just a gene,
341- INTRODUCTION TO BIOINFORMATICS Overview of the Course Material 1.
Paper Review on Cross- species Microarray Comparison Hong Lu
Construction of Substitution matrices
Ayesha M.Khan Spring Phylogenetic Basics 2 One central field in biology is to infer the relation between species. Do they possess a common ancestor?
BLAST Sequences queried against the nr or grass databases. GO ANALYSIS Contigs classified based on homology to known plant or fungal genes Next.
Bioinformatics What is a genome? How are databases used? What is a phylogentic tree?
Phylogeny and the Tree of Life
Table 2. Evidence of Colonizing Mechanism
Introduction to Bioinformatics Resources for DNA Barcoding
Genomes and their evolution
Basics of Comparative Genomics
Genomes and their evolution
DNA Marker Lecture 10 BY Ms. Shumaila Azam
Genomes and Their Evolution
John Rathjen and group ANU
Genomes and their evolution
Genomes and their evolution
Target selection strategies for the mouse genome
Fig Figure 21.1 What genomic information makes a human or chimpanzee?
KEY CONCEPT Entire genomes are sequenced, studied, and compared.
Relationship between Genotype and Phenotype
KEY CONCEPT Entire genomes are sequenced, studied, and compared.
KEY CONCEPT Entire genomes are sequenced, studied, and compared.
Functional Impact of Transposable Element using Bioinformatic Analysis
Comparative Genomics.
What do you with a whole genome sequence?
BSC1010: Intro to Biology I K. Maltz Chapter 21.
From Mendel to Genomics
The Human Transcription Factors
EST Analysis of the Cnidarian Acropora millepora Reveals Extensive Gene Loss and Rapid Sequence Divergence in the Model Invertebrates  R.Daniel Kortschak,
Volume 39, Issue 2, Pages (October 2016)
Evolution of Genomes Chapter 21.
Transcriptional Rewiring of Fungal Galactose-Metabolism Circuitry
Basics of Comparative Genomics
KEY CONCEPT Entire genomes are sequenced, studied, and compared.
GENOMICS Copyright © 2009 Pearson Education, Inc..
Relationship between Genotype and Phenotype
KEY CONCEPT Entire genomes are sequenced, studied, and compared.
Presentation transcript:

Comparative Genome Analysis and Genome Evolution of Members of the Magnaporthaceae Family of Fungi

Author : Laura H. Okagaki, Joshua K. Sailsbery, Alexander W. Eyre, and Ralph A. Dean Source : BioMed Central of Genomics Speaker : 方廷宇

Abstract Magnaporthaceae cause disease in cereal and turf grasses: Magnaporthe oryzae, Gaeumannomyces graminis var. tritici, and Magnaporthe poae. Observe the corelation between diversifying or purifying selection and distance to repetitive elements or an increased rate of evolution in secreted and small secreted proteins.

CAzymes in fungal proteomes showed for M. oryzae, G. graminis var. tritici, and M. poae that GHs were the most abundant class. Identify genes that may be involved pathogenesis, and identify a core proteome of conserved genes and identify functional clusters that are undergoing rapid diversification.

Results Ortholog clustering Cluster function identification CAZyme identification and analysis Putative transcription factor identification and analysis

Selection analysis of orthologus clusters Identification of function for diversifying and purifying gene clusters Secreted protein identification and analysis

Ortholog clustering Purpose : To identify genes that are unique to and shared among the three Magnaporthaceae species. Method : Genome sequences OrthoMCL

Some genes were eliminated, others were not clustered or were only clustered with genes within in single species.

In ortholog clusters, 1149 clusters were specific to the Magnaporthaceae species and represented 2680 genes.

Orthologs for 74 fungal genomes were clustered by using OrthoMCL.

Cluster function identification Purpose : To identify the types of genes that are conserved and shared among the Magnaporthaceae. Tool : Blast2GO software

Transcriptional regulators are abundant among genes unique to the Magnaporthaceae family of fungi.

Proteins with enzymatic functions and transcriptional regulation proteins may be undergoing higher rates of mutation than genes with other functions.

CAZyme identification and analysis Purpose : To identify OrthoMCL clusters that contained putative CAZymes and the classification of any identified functional domains. Tool : Hmmscan 3.0 software dbCAN database

12 clusters shared between the three species were found to contain putative CAZymes.

5 clusters contained genes identified as GHs, while 4 clusters contained CBMs. Fewer clusters were identified as having CEs, or auxiliary activity.

The majority of M. oryzae CAZymes fell into the GH and CBM categories. For both M. poae and G. graminis var. tritici, GHs were the primary CAZymes identified in the unique genes.

Putative transcription factor identification and analysis Purpose : To identify specific function domains, we further characterized the putative transcription factors identified in our analyses. Tool : InterProScan v5.0 software

The Zn(2)-C6 fungal type DNA binding domain was the most abundant in both data sets, accounting for 15 clusters and over 400 unique genes.

Selection analysis of orthologus clusters Purpose : To exam each Maganporthaceae species of diversifying and purifying selection and their proximity to repetitive elements and putative functions. Method : phylogenetic analysis by maximum likelihood (PAML)

Clusters that contain paralogs are under more selection than those without paralogs, but the selection is not limited to purifying or diversifying.

There is no correlation between proximity to repetitive elements and diversifying or purifying selection.

There is no correlation between PAML score and closest repetitive element.

The degree of mutation is not correlated with the distance to the closest repetitive element.

Identification of function for diversifying and purifying gene clusters Purpose : To identify the functions for genes that exhibit diversifying selection or purifying selection. Tool : InterProScan

Binding, nucleotide binding, and nucleoside and lipid metabolic processes were represented in the purifying clusters.

Regulation of transcription, nucleus, and zinc binding were all represented in the diversifying clusters.

Binding and some subsets of metabolism are conserved while transcription and ion binding are not.

Secreted protein identification and analysis Purpose : To exam the relationship between small secreted proteins and repetitive element location. Method : TargetP and SignalP PAML analysis

M. oryzae contained the highest proportion of secreted proteins with approximately 13 % of the proteins in the genome containing such signal sequences.

There was no significant difference observed in the USP or USP250 inG. graminis var. tritici or M. poae when compared with the whole genome average.

Retrotransposons are the closest repetitive elements the small secreted proteins in M. oryzae. However, these observations cannot be extrapolated to M. poae or G. graminis var. tritici.

Repetitive element proximity does not appear to influence purifying or diversifying selection.

Conclusion There is no evidence for two-speed evolution at the genome level. These is no influence on diversification of purification of orthologous clusters.

Thank you for listening