Todd Osmundson - Algae, Protists & Fungi Plenary

APPLICATIONS OF INTENSIVE DNA BARCODING PROJECTS FOR ADDRESSING

GAPS IN FUNGAL BIODIVERSITY KNOWLEDGE

Matteo M. Garbelotto1, Vincent Robert2, Conrad Schoch3, Todd Osmundson1

1 University of California, Berkeley, CA, USA2 Centraalbureau voor Schimmelcultures, Utrecht, The

Netherlands 3 National Center for Biotechnology Information, Bethesda, MD,

USA

MatteoU.C. Berkeley Forest Pathology & Mycology Lab

INTRODUCTION VENICE HERBARIUM MOOREA BIOCODE CONCLUSIONS

Fungi are diverse and poorly-known

Most are cryptic over the majority of their life cycle

Many are economically important:

- Pathogens- Mutualists- Foods, medicines,

industrial products

Unknowns:

• Diversity of life cycle stages (e.g., endophyte to pathogen transitions)

• Host ranges• Geographic ranges / biogeography• Community ecology


Unknowns:




All of these characters are relevant to understanding ecology and evolution of fungi, and tracking the spread of fungal species.

Unknowns:




DNA Barcoding is a useful and important tool for identifying fungi (rapid • able to detect cryptic fungi) and thereby understanding these factors…

Unknowns:




… However, utility of this tool is dependent upon existence of comprehensive sequence databases and methods for confidently assigning taxonomic identities via sequence comparisons.


Large-scale barcoding projects can aid in closing the sequencing gap.

Types of foci:

- Institutional

- Geographic

- Ecological


2 recent projects:

• Barcoding the Venice Museum of Natural History Fungal Collection (Institutional)

• The Moorea Biocode Project (Geographic ) Issues/Questions:

• What types of target are most effective?• What types of sampling are most effective?• What are the implications for barcoding

strategy?


BARCODING THE VENICE FUNGAL COLLECTION

Institutional strategy – barcode large number of samples from a single herbarium

Strengths:• Links to Italy’s largest amateur mycological society

(Associazione Micologica Bresadola)• Collaboration with taxonomic experts• Taxonomic diversity of collections• Collections relatively recent• Habitat diversity (Alps plains Apennines

Mediterranean)


Sampling Localities


Sampling :

• Focus on breadth• Attempt to obtain Barcode for every macrofungal species in the collection (~ 6000)• Replication for well-represented species• Good coverage for Agaricales; additional coverage within Basidiomycota & Ascomycota


Results

~31K collections

~5K collections sampled2763 specimens PCR positive [Age; taxon]1400 specimens Sequence positive [Sequencing failure; contamination; paralogy]:

• 1100 double-stranded• ~300 single-stranded


Collection age affects sequencing success:

1980s 1990s 2000s0

20

40

60

80

100

Percent Suc-cessful

Pearson Chi-square test of independence (N=2648, DF=2):p < 0.0001


Taxon (controlled for collection age) affects sequencing success:

Pearson Chi-square tests of independence):p < 0.0001

Panaeolus

Crinipellis

Cystolepiota

Cuphophyllus

Crepidotus

Conocybe

Hebelom

aPleurotus

Pluteus

Inocybe

Galerina

Agaricus

Omphalina

Xerocom

usCoprinus

Cortinarius

Marasmius

0102030405060708090

100

Series1

Series2

1980s-90s

2000s


Classification potential of ITS barcodes:• Can ITS barcodes predict membership in genera and families based on overall similarity?

• Distance / UPGMA approach based on ITS1 + ITS2 distance matrices

• Functionalities available in BioloMICS software (www.bio-aware.com)

UPGMA tree showing sequence assignment to genera and families; genus Cortinarius (family Cortinariaceae) shown

Cluster-based (NMDS) assignments to genera

Cluster-based (NMDS) assignments to families


Classification potential of ITS barcodes:• May reveal errors in classification; e.g., segregate genera in Coprinoid fungi


Is there a ‘barcoding gap’?•Compared number of nucleotide

differences within and between identified taxa

•Assessed 2 types of potential error:- False negative (same ITS for different species)- False positive (>1 ITS for one species)

Is there a ‘percent similarity’ threshold for assignment to genera’?

Genus0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 PanaeolusHebelomaMacrolepiotaXylariaHy-menogasterScutillineaCrepidotusCystolepiotaPleurotusGalerinaTricholomaOtideaPholiotaMelanoleucaConocybeXerocomusHygrophorusCoprinusLyophyllumLepiotaCystodermaLactariusCalocybeTuberHygrocybeEntolomaPluteusCortinariusPholiotinaAmanitaInocybeRussula

Min

imu

m S

imil

ari

ty

0 78 1562343123904685466247027808589360

500

1000

1500

2000

2500

3000

In the same species

Out

Within- and between-species nucleotide divergence (bp)

Nucleotide differences (bp)

Fre

quen

cy o

f pa

irwis

e co

mpari

sons

0 45 90 1351802252703153604054504955405856306757207658108559009459900

2

4

6

8

10

12

14

16

18

20

0 72 1442162883604325045766487207928649360

500

1000

1500

2000

2500

3000

Within-species nucleotide divergence (bp)

~1-2% Nucleotide differences (bp)

Fre

quen

cy o

f pa

irwis

e co

mpari

sons

0 1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334353637380

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Ratio In/Out

Ratio In/...

“Barcoding gap” ratio (within/between species counts) by level of nucleotide dissimilarity

Nucleotide differences (bp)

Rat

io w

ithin

/ b

etw

een

spec

ies


When differentiation fails (same ITS sequence for species identified as different):• 60 pairs with 0 bp difference but not

belonging to the same species:- 59 congeners (synonyms, species

complexes or ‘minor’ misidentifications)- 1 epigeous - sequestrate confamilial pair

(Leucoagaricus medioflavoides + Endoptychum agaricoides)


When differentiation fails (same ITS sequence for species identified as different):• 77 pairs with 1 bp difference but not

belonging to the same species:- 73 congeners- 2 ‘major’ misidentifications or mixed

samples (Boletus vs. Inocybe; Sarcosphaera vs. Psathyrella)

- 1 ‘moderate’ misidentification (Pholiotina vs. Galerina)


Examination of ITS1 and ITS2 as “mini-barcodes”

• Improved sequencing success rate: ITS1 amplified using primers ITS1F + ITS2 for 30 randomly-selected samples previously negative for full-length PCR amplifications (using ITS1F + ITS4) from 3 large genera:

GENUS PCR-POSITIVE SEQUENCE- Cortinarius 30/30 (100%)

24/30 (80%)- Russula 30/30 (100%) 27/30

(90%)- Mycena 27/30 (90%) 4/30

(13%)


Examination of ITS1 and ITS2 as “mini-barcodes”

• Classification potential remains strong

• ITS1 exhibits higher correlation to

full-length ITS

Complete

ITS1 ITS2

Complete

1

ITS1 0.7317 1

ITS2 0.6430 0.5433 1


Conclusions, Venice Herbarium Project:

• Similarity-based taxonomic assignment using ITS sequences works reasonably well at genus and family levels (but not flawless)

• At species level, incorrect assignments (assessed for morphospecies) in both “false negative” and “false positive” directions.

• A 1-2% divergence cutoff eliminates most “false positives” (>1 ITS sequence per morphospecies); however, “false negatives” (>1 taxon per ITS sequence occur even at 0-1 nucleotide difference.


Conclusions, Venice Herbarium Project (continued):

• “Mini-barcodes” improve success rates and retain ability to classify sequences; ITS1 outperformed ITS2 for the taxa examined


Conclusions , Venice Herbarium Project (continued):

• Value of herbaria in facilitating a large collection approach to barcoding

• Value to herbaria (increase ‘relevance,’ streamline use of collections)


THE MOOREA BIOCODE PROJECT• Geographic/ecological strategy: barcoding

an entire biome

A relatively simplified tropical ecosystem, due to age, size, isolation and location in pacific biodiversity gradient

Species richness

Goal: to develop a fully-characterized tropical island model ecosystem through intensive biotic surveys and generation of DNA barcode libraries


THE MOOREA BIOCODE PROJECT• South Pacific islands an undersampled

region for fungi • Moore Foundation-funded, multi-taxon

ATBI.• Approach: threefold –

Voucher-based collection of macromycetesEnvironmental DNA samplingCulture-based sampling


Sampling Approach:

• Field collection• Voucher information,

photos, and DNA sequence linked together

and made public• Collaboration with

BioMatters, Inc.– Geneious Moorea Biocode

workbench / data pipeline

Macrofungal richness

62% of sequences exhibit < 97% identity to sequences currently in GenBank. This project will therefore make an important contribution to GenBank taxon coverage.

97%

62 percent of sequences exhibit less than 97% best match in Genbank; 23% exhibit best BLAST match to environmental sequence

(cultured or uncultured)


• 62 percent of sequences exhibit less than 97% best match in Genbank:

Incomplete database?Potential radiations?Insular rapid evolution?

• 23% exhibit best BLAST match to environmental sequence (cultured or uncultured)

• Voucher-supported sequences will enhance ecological and biodiversity discovery; underscores importance of collections-based research


For sequences with 98% or greater match:• Suggests recent arrival or slow

evolution• If to named material: sequencing

facilitates ID of Moorea taxa• If to environmental sequences:

Voucher now exists corresponding to the environmental sequence


Moorea Biocode Project:Contributions include:

• Augmenting geographical and taxonomic coverage in GenBank

• Providing vouchers that match environmental sequences

• Providing material for biogeographic studies


CONCLUSIONS:

Large-scale barcoding approaches based on institutional collections and ecosystems contribute to the study of fungal biodiversity, ecology, biogeography, and epidemiology.

Institutional targeting: • Adds barcodes for well vouchered and

identified material• Adds value to herbarium collections• Allows assessment of barcode “behavior”

(laboratory approaches, barcoding gaps, need for multilocus barcodes, etc.) for different taxonomic groups


CONCLUSIONS, continued:Ecosystem targeting:• Increases representation of poorly-sampled

biomes • Aids biogeographic studies• Barcoding speeds time to identification,

facilitating biodiversity surveys

Both Approaches:• Exhibit advantages over focusing on specific

taxonomic groups of expertise or interest• Offer opportunities for collaboration with

taxonomic specialists and amateur enthusiasts


IMPLICATIONS OF LARGE-SCALE STUDIES FOR DNA BARCODING OF FUNGI:

1. Utility of ITS as a barcode locus:• Similarity-based searches are often

sufficient for assignment to genera and families

• Use as a species-specific marker problematic due to false negatives and positives

• A firm “barcoding gap” is lacking, though some level of success is met using 1-2 bp differences; A 98% or 97% similarity threshold appears to be too low; most species-level similarity is on the order of 99% or higher



2. “Environmental species”:• Formal (or semi-formal) recognition of

entities known only from environmental DNA sequences; subject of a formal discussion session at 2011 MSA annual meeting

• Appealing as a means to improve comparison across studies and progress from descriptive or comparative community studies (OTU-based) to a more functional understanding of communities and ecosystems



2. “Environmental species” (continued):• Our results suggest that a simple identity-

or similarity-based approach may be useful for group placement (genera or families), but species-level circumscription is unlikely.



3. Multilocus barcodes:• Already well-recognized that ITS is not a

species-level barcode for some groups of Ascomycota

• Our results strongly suggest that a similar issue exists for Agaricales (Basidiomycota) as well.


Acknowledgements:

Venice:Giovanni RobichLuca MizzanAmy SmithLydia Baker

Moorea:Sarah BergemannNeil DaviesChris MeyerRikke RasmussenNatalie LowellLydia SmithLydia BakerWesley ShipleyGordon & Betty Moore Foundation

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