Genomic Perspectives on Evolution in Bracken Fern

Genomic Perspectives on Evolution in Bracken Fern

Joshua DerDepartment of Biology

PhD Defense, 27 May 2010

1Friday, May 28, 2010

Collage by Kristal Watrous

Photo Credits: fruit fly: André Karwath; mosquito: Ashok Prabhakaran; honeybee: Allie Caulfield; sea urchin: Jerry Kirkhart; green anole lizard: Clinton & Charles Robertson; opossum: Mike Keeling; platypus: Jon Hooper; horse: Pete Birkinshaw; cow: Kevek Law; rhesus macaque: Paul Asman & Jill Lenoble; nematode: Flickr user snickclunk; dog: John Wright; sea squirt: Silke Baron; chicken: Ernst Vikne; human: Lindsey Wilson; chimp: Frank Wouters; mouse: Kim Carpenter; pufferfish: Julien Mouille; Arabidopsis: Sui-setz; rice: FotoosVanRobin; grape: Tomomarusan; papaya: geishaboy500; yeast: David O. Morgan; diatom: Minami Himemiya; giant panda: Aaron Logan; black cottonwood: Dave Powell; woolly mammoth: Mauricio Anton; wine glass: Klaus Post




They all have complete sequenced genomes!


Fruit fly Mouse

Model organisms (usually with small genomes)




Yeast Grapes

Economically important species

Wine

+ =




Rice Humans

Economically important species




Platypus Lycophyte

Important evolutionary lineages

Sea Squirt




Genomics in model organisms

• Generally have small genomes

• Decipher gene and genome function

• Understand networks of molecular interactions (i.e. systems biology)

• Translate new discoveries to benefit people (e.g. crop improvement and human health)


The age of genomics

0

375

750

1125

1500

1995 1997 1999 2001 2003 2005 2007 2009

Number of complete genome sequences in Genbank, Feb. 2010(Data from Genomes OnLine Database v.3.0: www.genomesonline.org)


“Next-generation” sequencing revolution

• Massive throughput

• Avoid sequence bias and labor associated with molecular cloning

• Huge reduction in cost per base

• Target sequencing for information-rich templates (e.g. gene space and transcriptomes)


Next-generation platforms

• Second-generation (in vitro clonal amplification)

• Illumina

• SOLiD

• Roche 454

• Third-generation (single molecule sequencing)

• Helicos

• Pacific Biosciences

• Oxford Nanopore


Genome-scale analyses can be performed on ANY organism

What’s your favorite organism?



Woolly Mammoth

• Genome sequenced 2008

• Roche 454

Credit: Mauricio Anton



Giant Panda

• Genome sequenced 2010

• Illumina

Photo: Aaron Logan



• 1000 Genomes (human)

• 1001 Genomes (Arabidopsis)

• 1000 Plant and Animal Reference Genomes Project

• Genome 10K (vertebrates)

• OneKP (plant transcriptomes)

Let’s just sequence it all!

Photo: Natalie Maynor


Reality check!

• We have limited resources

• Current technology still has limits

• Instrument capacity

• Throughput

• Read lengths


So, how do we choose?

• Plants, of course!

• Two papers give us some guidance


So, how do we choose?

• Choice must be considered within a phylogenetic framework

• Once we choose:

Do we need the full genome (yet)?


Among plants, what is the last major (i.e. large and diverse) lineage

unsampled in a genome-scale project?

Ferns!

Photo: Robbin Moran


Fern evolution

• Sister to seed plants

• Ancient lineage (Devonian)

• ~9000 extant species

• Geographic and ecological diversity

• Evolved and maintain independent gametophyte and sporophyte generations

Ferns

Lycophytes

Bryophytes

Seed Plants


Fern evolution

• Sister to seed plants

• Ancient lineage (Devonian)

• ~9000 extant species

• Geographic and ecological diversity

• Evolved and maintain independent gametophyte and sporophyte generations

haploid spores (n)

meiosis

sperm (n)

egg (n)

zygote (2n)

Fern life cycle

syngamysporophyte (2n)

gametophyte (n)


Challenges in fern genomics

• Limited agronomic importance

• Large genome sizes (avg. 10 Gb)

• High chromosome numbers (avg. n = 57)

• Extensive history of hybridization and polyploidy

Photo: Mike Windham


Bracken fern: Pteridium

• Worldwide distribution

• Toxic to livestock and weedy in pasture

• Highly adaptable and phenotypically plastic

• Established culture techniques

• Paleopolyploid with diploid gene expression

• Genome size: 1C = 9.8 GbLindman. 1917-1926. Bilder ur Nordens Flora-508


Bracken fern: Pteridium

Model system in the study of:

• Fern lifecycle

• Apomixis, apogamy, apospory

• Gametophyte development

• Pheromonal sex determination

• Cyanogenesis/Carcinogenesis

• Invasion ecology

• Climate change

Photo: John Thomson


Dissertation outline1. Global phylogeny and biogeography of bracken

• Establish an evolutionary framework

2. Characterization of the bracken gametophyte transcriptome

• Leverage 454 sequencing to sample the expressed component of the huge nuclear genome

3. Chloroplast genome and RNA editing in bracken

• Combine genomic and expressed 454 sequence data to study chloroplast RNA metabolism


1. Global phylogeny and biogeography of bracken

Citation: Joshua P. Der, John A. Thomson, Jeran K. Stratford and Paul G. Wolf. 2009. Global chloroplast phylogeny and biogeography of bracken (Pteridium: Dennstaedtiaceae). American Journal of Botany 96 (5): 1441-1449.


Taxonomic instability• High phenotypic plasticity with

environmental conditions

• Few diagnostic morphological characters recognized

• Intermediate forms between geographic morphotypes

• Hybrid tetraploid species

• Regionally biased studiesThomson JA, Mickel JT, Mehltreter K. Botanical Journal of the Linnean Society, 2008, 157, 1–17.

Over 135 named forms!


Phylogenetic objectives:

1. Establish a phylogenetic framework for the genus worldwide

2. Examine patterns of global biogeography


Phylogeny

• 77 specimens sampled globally

• trnS-rps4 spacer+gene &rpl16 intron

• 43 parsimony informative sites

• 3 indel haplotypes detected


Phylogeny

• 77 specimens sampled globally

• trnS-rps4 spacer+gene &rpl16 intron

• 43 parsimony informative sites

• 3 indel haplotypes detected

AC

B


Biogeography

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Biogeography

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Biogeography

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Phylogenetic conclusions

1. First global phylogenetic analysis in bracken

2. Biogeographic patterns are consistent with paleoclimatic events

3. This work contributes to a revision of the genus


2. Gametophyte transcriptome

Coauthors: Michael S. Barker, Norman J. Wickett, Claude W. dePamphilis, Paul G. Wolf


Transcriptome objectives

1. Develop an extensive expressed sequence resource in ferns

2. Glimpse into the nuclear genome of bracken

3. Characterize the transcriptome & identify active genes in the gametophyte generation


Roche 454 sequence reads

Normalized cDNA derived from mature gametophytes

Reads were quality and length filtered, adapter and polyA/T trimmed

• Cleaned reads:! 681,722

• Mean length:!! 372.60 bp

• Total bases:! ! 254 Mb

Histogram of cleaned reads

Cleaned read length, maximum = 624

Num

ber o

f seq

uenc

es

0 100 200 300 400 500 600

050

0010

000

1500

0


Transcriptome assembly

Histogram of transcriptome unigenes (CAP3)

Unigene length, largest transcript = 4897 bp

Num

ber o

f seq

uenc

es

0 500 1000 1500 2000 25000

2000

4000

6000

Total unigenes = 38889

Mean length = 685.76 bp

Total bases = 26.67 Mp

Unigenes

Number 38,889

Mean length (bp) 685.76

Mode (bp) 476

Range in length (bp) 86 - 4,897

Total bases (Mbp) 26.67


Transcriptome coverage

Wall et. al., 2009. BMC Genomics 10:347

ESTcalc (simulation based model)ESTcalc (simulation based model)

Percent of the unique bases in the transcriptome: 87%

Percent of the genes with at least one read: 100%

19

338

Ultra conserved orthologs

8

155

Shared single copy genes

95%


Transcriptome coverage

95% of unigenes captured after 403K reads sampled

1,357 reads to capture the last 10 unigenes


Functional annotation

Localization of genes is predominantly in the nucleus, mitochondria, and plastids

cellular_component Level 5

endoplasmic reticulum

(317)

nucleoplasm (376)

vacuole (274)

Golgi apparatus

(212)

microbody (119)

plastid (3,613)

cytoskeleton (238)

nucleus (1,325)

endosome (10)

nucleolus (197)

nuclear lumen (555)

cytosol (448)

mitochondrion (1,967)

GO category: Cellular Component



Two main biological processes involve metabolism and cellular machinery

GO category: Biological Processbiological_process Level 2

multicellular organismal

process (166)

localization (1,713)

multi-organism process (15)

growth (41)

establishment of localization

(1,713)

reproduction (73)

biological regulation (853)

developmental process (194)

reproductive process (29)

cellular process (7,432)

regulation of biological

process (716)

response to stimulus (908)

metabolic process (7,641)



Two main molecular functions are binding (DNA, RNA, and protein) and catalytic activity (hydrolase and transferase activity)

GO category: Molecular functionmolecular_function Level 2

enzyme regulator

activity (106)

binding (8,120)

transcription regulator

activity (409)

structural molecule

activity (542)

translation regulator activity (1)

transporter activity (908)

molecular transducer

activity (357)

catalytic activity (7,915)


Comparative genomics

Of 38,889 unigenes, 24,897 had a positive blastx hit

• 23,152 in Arabidopsis

• 22,474 in Physcomitrella

• 16,352 in Selaginella


Transcriptome conclusions

1. First comprehensive analysis of gene expression in a fern

2. Most extensive sequence resource available in ferns


3. RNA editing in the chloroplast genome

Coauthors: Aaron M. Duffy, Matt Kusner, Chen Gu, Paul Overvoorde, Paul G. Wolf


RNA editing in plants• Conversion of C to U or U

to C nucleotide in RNA molecules relative to the encoding DNA

• More abundant in mitochondria than chloroplasts or nuclear genomes

• Most abundant in seed-free vascular plants and hornworts

Ferns (300; ?)

Lycophytes (?; 1450)

Mosses (1; 11)

Seed Plants (30; 500)

Hornworts (900; 600)

Leafy liverworts (?; 600)Thalloid liverwort (none)

Lineage (cp; mt)


Chloroplast genome objectives:

1. Reconstruct the complete chloroplast genome from total genomic Roche 454 data

2. Use expressed transcript data to identify RNA editing sites, de novo


Chloroplast genomeGenomic 454 read lengths

Read length (maximum = 1363)

Num

ber o

f rea

ds

0 100 200 300 400 500 600 700

050

0015

000

2500

035

000

711,178 reads216.19 Mbp

152,362 bp34.5x coverage


Genome annotation

Ribosomal RNAs 4Transfer RNAs 29Photosystem I 5Photosystem II 15Cytochrome 6ATP synthase 6Rubisco (rbcL) 1Chlorophyll biosynthesis 3NADH dehydrogenase 11Ribosomal proteins 22RNA polymerase 4Intron maturase (matK) 1Miscellaneous proteins 5Hypothetical proteins 5

117 total genes


RNA editing

Percent chloroplast transcripts 2.8%Percent of chloroplast genome 80.67%Percent of chloroplast sites edited 0.73%Total RNA editing sites detected 851

C to U RNA editing 551U to C RNA editing 300RNA editing in the Inverted Repeat 233

RNA editing in protein coding sequence 660Modified start codons 26Premature stop codon repair 37Repair proper stop codon 6

RNA editing in tRNA genes 15RNA editing in rRNA genes 168RNA editing in introns 12


RNA editing


Chloroplast genome conclusions

1. Utilized a novel method to reconstruct the chloroplast genome

• Pteridium aquilinum has the chloroplast gene set and gene order of Adiantum capillis-veneris

2. First to use deep RNA sequencing to identify RNA editing in chloroplasts

• Identified a large number of RNA editing sites in the chloroplast genome







Conclusions1. Next generation sequencing has enabled

genome-scale studies in non-model organisms

2. Large data sets present new challenges for analysis

3. Incredible opportunities for novel studies and analyses in new organisms

Friday, May 28, 2010


Future work

1. Extract mitochondrial genome sequences

2. Sequence the sporophyte transcriptome

3. Explore gene space and transposable elements in the nuclear genome




AcknowledgmentsPhD Committee: Coauthors: Claude dePamphilisPaul Wolf Mike Pfrender Jeran Stratford Aaron DuffyCarol VonDohlen Karen Mock John Thomson Chen GuPaul Cliften (Geno Schupp) Mike Barker Matt Kusner

Other supportive roles (e.g. research or editorial assistance, samples, scripts, data, photographs, etc.)Other supportive roles (e.g. research or editorial assistance, samples, scripts, data, photographs, etc.)

Norm Wickett Paul OvervoordeOther supportive roles (e.g. research or editorial assistance, samples, scripts, data, photographs, etc.)Other supportive roles (e.g. research or editorial assistance, samples, scripts, data, photographs, etc.) Funding Agencies:Funding Agencies:

Katrina Dlugosch Ninglin Yin Utah State University: Department of Biology; Vice President for Research; Center for Integrated Biosystems; Center for High Performance Computing; Ecology Center

Utah State University: Department of Biology; Vice President for Research; Center for Integrated Biosystems; Center for High Performance Computing; Ecology Center

Eric Wafula Jacob Parnell


Utah State University: Department of Biology; Vice President for Research; Center for Integrated Biosystems; Center for High Performance Computing; Ecology CenterJacob Davidson Keithanne Mockaitis



Alan Smith Elizabeth Sheffield National Science FoundationNational Science Foundation

Jeffrey Boore Tom Ranker Genomics Education Partnership, Howard Hughes Medical Institute and The Genome Center at Washington University

Genomics Education Partnership, Howard Hughes Medical Institute and The Genome Center at Washington UniversityBrent Mishler Laura Forrest

Genomics Education Partnership, Howard Hughes Medical Institute and The Genome Center at Washington University

Genomics Education Partnership, Howard Hughes Medical Institute and The Genome Center at Washington University

Kenneth White Brian Joy Dedication: Kristal, Cora, and TylerThis one’s for you. Thanks.Dedication: Kristal, Cora, and TylerThis one’s for you. Thanks.Daryll DewaldDedication: Kristal, Cora, and TylerThis one’s for you. Thanks.Dedication: Kristal, Cora, and TylerThis one’s for you. Thanks.





Documents

Genomic Perspectives on Evolution in Bracken Fern