DNA Barcoding and integrative

taxonomy of bees Packer L.;

Gibbs J.

York

University

Agapostemon

virescens

OUTLINE

Importance of bees

The taxonomic impediment

Some detailed examples of the use of DNA barcoding in bees

Progress towards barcoding the bees of the world (problems, prognosis)

Importância das abelhas

O ImpedimentoTaxonômico

Exemplos da aplicaçãodo DNA barcoding aoestudo de abelhas

Avanços no projeto de barcoding das abelhas do mundo

SUMÁRIO

A Importância das Abelhas

Polinazação de frutas e vegetais

Polinazação de plantas nativas

Biologia dapolinazação

Monitoramentoambiental

Bees are responsible for25%, 33% (?) of our food.Abelhas são reponsaveis por 25%, 33% (?) dos alimentos produzidos.

“If the bee disappeared off the surface

of the globe then man would only

have four years of life left.”Einstein (?)

& without

flies!

The Taxonomic Impediment

O Impedimento Taxonômico

There are over 19,500 described bee species

There are several genera with more than 1,000 species

There are very few people capable of identifying more than a small proportion of the total

Há mais de 19.500 espécies de abelhasdescritas

Há vários gêneros com mais de 1.000 espécies

Há muito poucas pessoascapazes de identificarmais que uma pequenaparte deste total

Bee Experts

% correct identification as a bee by experts!% de identificação correta como abelhas, por especialistas

% correct identification as a bee by experts!% de identificação correta como abelhas, por especialistas

Hyleoides – 57%

Euryglossina

leyburnensis – 15%

Experts got 75% right, beginners 64%Sucesso de 75% para especialistas e 64% para iniciantes

Photo Steve

Buchman

Um exemplo de um erro

Em uma coleção, eu encontrei uma únicaespécie identificada como pertencendo a trêsgêneros diferentes, de duas famílias distintas, por três taxônomos diferentes (um especialistada fauna local, um especialista da fauna do paíse um especialista da fauna mundial de abelhas)

Em uma coleção, eu encontrei uma únicaespécie identificada como pertencendo a trêsgêneros diferentes, de duas famílias distintas, por três taxônomos diferentes (um especialistada fauna local, um especialista da fauna do paíse um especialista da fauna mundial de abelhas)

Todas as identificações genéricas estavamincorretas.

Um exemplo de um erro

Sometimes there are no keys for identificationÀs vezes não há chaves de identificação

Example: the bee family Colletidae

146 higher level taxa

30% have no revision or key

45% of colletid species are not identifiable with available literature

32/33 keys for one subfamily were written by one researcher

Only four groups have been revised more than once

Exemplo: família Colletidae

146 táxons supraespecíficos

30% nunca foram revisados; não há chaves disponíveis paraidentificação

45% das espécies de Colletidaenão são identificáveis apenascom a literatura taxonômica

32/33 chaves para uma das subfamílias foram propostaspor um único pesquisador

Apenas quatro táxons foramrevisados mais de uma vez

Some examples of

the success of DNA

barcoding

An early example: Halictus ligatus

In North America is two species

As duas espécies são

indistinguíveis

morfologicamente,

mas possuem diferenças

genéticas reconhecíveis:

possuem 8 diferenças

fixadas,

dentre 32 locos de alozimas

Morphologically theyare exactly the same

but genetically,they have 8 fixed differences out of32 allozyme loci

Halictus ligatus/poeyi

The morphological gap is 0.0%

The allozyme gap is 25%

The barcode gap is 4%

There are probably >3 species

A diferençamorfológica é 0,0%

As diferençasdetectáveis com alozimas são 25%

As diferençasdetectáveis com obarcode são de 4%

Provavelmente há ≥3 espécies

DNA BARCODING A NIGHTMARE TAXONDNA Barcoding de um pesadelotaxonômico

Subfamily Halictinae

“sweat bees”

3rd most speciose subfamily (3423 spp.)

Abundant, cosmopolitan

Often 40 – 80 % of bees in surveys

Funding provided by:

The Halictinae

(Sweat bees):

Apresentam enormevariação de comportamentosocial

Muitas espéciessolitárias

Algumas espécieseusociais, com ninhos que abrigammais de 1000 operárias.

DNA Barcoding de um pesadelo taxonômico

Morphological characters are often subtle

Revision of the Canadian Dialictus 80 species in total

16 new species

48 new synonymies

3 new combinations

10 new Canadian records

776 ms pages

235 colour plates

Zootaxa in review

Integrative taxonomy

DNA barcodes facilitate taxonomy

Funding provided by:

75 %

L. (D.) tegulare

L. tegulare (Robertson): one of the most easily identifiable Dialictus species

Widespread in eastern USA

L. (D.) tegulare species group But...its actually FIVE species!

Funding provided by:

Character based identification using DNA barcodes

L. tegulare (Robertson) easily identifiable Dialictus species

Widespread in eastern USA

UNIQUE FIXED NUCLEOTIDE SUBSTITUTIONS

tegulare = 2

ellisiae = 7

lepidii = 4

puteulanum = 2

carlinvillense = 3

surianae = 13

L. (D.) petrellum species group

Similar result for L. petrellum species group

Funding provided by:

New synonymies

L. (D.) disparile (Cresson)

Described from Texas

= Dialictus brassicae Mitchell

Described from North Carolina

= Halictus albitarsus Cresson

Described from male

17% of species have identical barcodes

Funding provided by:

More cryptic diversity?

8 %

Dialictus: barcoding aids their taxonomy even without a clear “barcodegap”

Morphological identification accuracy?

0-40%

Barcodingaccuracy?

≥ 75%

Acurácia daidentificaçãomorfológica?

0-40%

Acurácia do barcoding?

≥ 75%

It’s not always such a struggle

Megachile pugnata: image

courtesy Theresa Pitts-Singer

DNA barcoding é excelente para:

Associating sexes

Associating larvae with adults

Associating castes

Finding clusters in problematic taxa to aid in search for morphological differences

Associação de sexos

Associação de larvas eadultos

Associação de castas

Reconhecimento de agrupamentosgeneticamenteidentificáveis, paraauxiliar a busca pordiferenças mofológicas

Resurrecting incorrect synonymies

Providing an independent test of taxonomic hypotheses

Reavaliação de sinonímias incorretas

Fornece um testeindepende das hipóteses taxonômicas

DNA barcoding é excelente para:

May 12th

– 14th

2008 12 – 14 Mayo, 2008

12 – 14 Maio, 2008 5

Inaugural Meeting Reunión Inagural

Reunião Inaugural

Progress We have a

steering committee

We have a website (currently being improved upon)

And we have a lot of data

Melissodes sp.

Progress: Steering committee – in

approximate geographic location

The website: www.bee-bol.org

We have data from:

>27 collaborators

> 76 countries

> 60% of bee

genera

Distribution of specimens barcoded

Stenotritidae:

2 gêneros 21 espécies

2 genera and

3 species barcoded

Ctenocolletes smaragdinus

Colletidae: 55 genera, 2506 species

34 genera and 403 species barcodedXeromelissa rozeni

Colletes inaequalis

Andrenidae: 40 genera, 2895 species

30 genera and 353 species barcodedAndrena erythrogaster

Calliopsis anomoptera

Halictidae: 76 genera, 4238 species

56 genera and 835 species barcodedHalictus ligatus? Agapostemon splendens

Melittidae: 15 genera, 183 species

7 genera and 17 species barcoded

Meganomia binghamiRediviva sp.

Rediviva sp.

Megachilidae: 75 genera 3973 species

37 genera and 631 species barcoded

Anthidium manicatum Megachile sp.

Apidae: 176 genera, 5687 species

141 genera and 1226 species barcodedTriepeolus sp. Apis mellifera

% de espécies barcoded

0

5

10

15

20

25

%

Preliminary

analyses on the

data for all

records of

Colletidae in

the database:

740 sequences

The barcode

gap for the

prelminary

data set for

all Colletidae

“Intraspecific”

“Interspecific”1 2 3 4 >5

5 10 15 20

10%

50%

25%

5%

74%

7%

12%

7%

Acurácia do barcoding/taxônomo: Colletidae, n = 740 sequências

Barcoding/Taxonomist accuracy: Colletidae, n = 740 sequences

consistent

identified by barcoding

unidentified

inconsistent

10%

72%

6% 12%

Razões para inconsistência, n = 50 sequênciasCauses of inconsistency, n = 50 sequences

nonsense

misidentification

uncertain assignment

wrong sequence

75%

3%

22% consistent

inconsistent

unidentified

Acurácia do barcoding/taxônomo Accurácia, n = 250 "clusters“

Barcoding/Taxonomist Accuracy, n = 250 clusters

12%

25%

63%

Razões para inconsistência: n = 8 “espécies”Causes of inconsistency: n = 8 “species”

new species

synonymies

diff spp. = sequences

Problemas Curating all of the incoming

data is impossible on a part-time basis.

Trabalho de curadoria de todo o material recebido é impossível quando esta é uma dentre várias funçõesdo pesquisador.

Obtaining accurate identifications.

Identificações confiáveis.

Problems

Specimens are difficult to obtain from some countries.

Dificuldade de obtenção de material de alguns países

Some preferred collection methods are suboptimal for barcoding.

Alguns dos métodos maispopulares para coleta de espécimes são subóptimospara barcoding.

$$

Soluções para os Problemas Full-time assistance is now available for 6 months

for database curation. Material transfer agreements are being developed. Museum specimens, new collections. A team of experts is being amalgamated.

Auxílio técnico “full-time” disponibilizado por 6 meses/ano para curadoria dos bancos de dados.

Acordos para envio de material estão sendofirmados.

Espécimes de museus, expedições de coleta. Um extenso grupo de especialistas está sendo

formado.

Prognosis Caupolicana fulvicollis

With funds…

- Excellent!Nolanomelissa toroi

CONCLUSÕES Identificação de abelhas é uma tarefa difícil

O impedimento taxonômico é enorme

Barcoding funciona para a maior parte da melitofauna do Canadá 100% sucesso para Megachile

100% sucesso para Dufourea

100% sucesso para abelhas de Nova Scotia

75% sucesso para o “grupo pesadelo”–Dialictus

Associação de sexos, castas, estágios do desenvolvimento, correção de sinonímiaserrôneas, testes de hipóteses taxonômicas

Barcoding is a useful tool for taxonomy even in the absence of a “barcode gap”

Barcoding é uma ferramenta útilpara taxonomia mesmo quando umaseparação pelo barcode (“barcode gap”) não é evidente.

Barcoding works most of the time for the Canadian fauna 100% success in Megachile

100% success in Dufourea

100% for the bees of Nova Scotia

75% success for the nightmare group –Dialictus

Associates sexes, castes, life stages, correcting erroneous synonymies, tests taxonomic hypotheses

It certainly does not threaten the future of traditional taxonomy, indeed, in Canada, it has saved it from extinction.

Barcoding não representa um perigopara o futuro da taxonomiatradicional. Na verdade, no Canadá, o perigo de extinção da taxonomiaestá sendo eliminado graças ao

barcoding.

There are problems to overcomeHá problemas a seremsuperados

They are all related to time and money.

Todos eles relacionam-se a tempo e dinheiro

Acknowledgements Sam Droege (United States Geological Survey, Patuxent Wildlife Research Center), Terry Griswold (United States Department of

Agriculture, Agricultural Research Service), Ralph Grundel (United States Geological Survey, Great Lakes Science Center), Andrea Patenaude (University of Manitoba), Julianna Tuell (Michigan State University), John Ascher (American Museum of Natural History), Rob Jean (Indiana State University), Joan Milan (University of Massachusetts Amherst), Elizabeth Elle (Simon Fraser University), Miriam Richards (Brock University), Amy Wolf (University of Wisconsin Green Bay), Peter Hallett (University of Toronto), Bryan Danforth (Cornell University), Mike Arduser (Missouri Department of Conservation), Jennifer Hopwood (University of Kansas), Charles Michener (Kansas University Natural History Museum), Bob Minckley (University of Rochester), Paul Catling (Agriculture and Agri-Food Canada), Victoria MacPhail (University of Guelph), Rebecca Andres (North Dakota State University), Stephen Hendrix (University of Iowa), Matthias Buck (Royal Alberta Museum), Jack Neff (Central Texas Melittological Institute), Doug Yanega (University of California at Riverside), Jen Frye (Maryland Department of Natural Resources)

ANSP: Academy of Natural Sciences, Philadelphia, Pennsylvania (J. Weintraub); AMNH: American Museum of Natural History, New York, New York (J.G Rozen, Jr., and J.S. Ascher); ARC: Albert J. Cook Arthropod Research Collection, Michigan State University, Lansing, Michigan (G.L. Parsons); BCLU: Utah State University Bee Biology and Systematics Laboratory, Logan, Utah (T.L. Griswold); BDUC: University of Calgary–Entomology, Calgary, Alberta (J. Swann and R. Longair); BLNP: Badlands National Park, Interior, South Dakota (M. Cherry); BMNH: Natural History Museum, London, England (D. Notton); CAS: California Academy of Science, San Francisco, California (W.J. Pulawski and V. Lee); CNC: Canadian National Collection of Insects, Arachnids and Nematodes, Ottawa, Ontario (A. Bennett); CTMI: Central Texas Melittological Institute, Austin, Texas (J.L. Neff); CUIC: Cornell University Insect Collection, Ithaca, New York (E.R. Hoebeke and B.N. Danforth); DEBU: University of Guelph Insect Collections, Guelph, Ontario (S.A. Marshall); FSCA: Florida State Collection of Arthropods, Gainesville, Florida (L. Stange and J. Wiley); GSNP: Great Smoky Mountains National Park, Gatlinburg, Tennessee (A. Mayor); IDNL: Indiana Dunes National Lakeshore, Porter, Indiana (R. Grundel); INHS: Illinois Natural History Survey, Champaign, Illinois (P.P. Tinarella); JHRC: James Hanula research collection, USDA Forest Service, Southern Research Station, Athens, Georgia (J. Hanula). (Eventually to be deposited in Georgia Museum of Natural History); MCZ: Harvard University Museum of Comparative Zoology, Cambridge, Massachusetts (P.D. Perkins); NCSU: North Carolina State University, Raleigh, North Carolina (B.Blinn); NMNH: National Museum of Natural History, Washington, D.C. (D. Furth, B. Harris, and S.G. Brady); PCYU: Packer Collection at York University, Toronto, Ontario (L. Packer). (Subsamples of this material will eventually be deposited in institutional collections managed by C. Sheffield, L. Best, and the author when appropriate); PHPC: Peter Hallett private collection, Toronto, Ontario (P.E. Hallett); PMAE: Royal Alberta Museum, Edmonton, Alberta (M. Buck); RBCM: Royal British Columbia Museum, Victoria, British Columbia (R. Cannings); ROM: Royal Ontario Museum, Toronto, Ontario (B. Hubley); RWRU: Rachael Winfree research collection, Rutgers University, New Brunswick, New Jersey (R. Winfree); SEMC: Snow Entomological Museum, (Kansas University Natural History Museum), Lawrence, Kansas (C.D. Michener and J.C. Thomas); UCMC: University of Colorado Museum of Natural History, Boulder, Colorado (V.L. Scott); UCR: University of California Riverside Entomology Research Museum, Riverside, California (D. Yanega); UNSM: University of Nebraska State Museum, Lincoln, Nebraska (B. Ratcliffe and M.J. Paulsen); UWGB: University of Wisconsin (Richter Museum of Natural History), Green Bay, Wisconsin (T. Erdman)

CCDB and BIO at the University of Guelph for sequencing. Funding from Genome Canada, NSERC and other sponsors listed at www.BOLNET.ca is greatly appreciate.

FUNDING

• The Gordon and Betty Moore Foundation, Natural Sciences and

Engineering Research Council (Canada), Canada Research Chairs

program, Ontario Foundation for Innovation and Genome Canada

through the Ontario Genomics Institute to PDNH

• Fonds québécois de la recherche sur la nature et les technologies B3.

• CBOL – funded the May workshop

• York University

EDUARDO (EDDY) ALMEIDA for translation

• Sujeevan Ratnasingham (BOLD)

PARTNERS IN FUNDING AND IN-KIND SUPPORT

¡Gracias!

Photo

courtesy Dr.

S.F. Sakagami