Species or host races? The mythology of biotypes

Transcription

1 Species or host races? The mythology of biotypes Paul De Barro Senior Principal Research Scientist VII Brazilian Congress of Entomology, Gramado, Brazil, October 2012

2 The Grand Challenge How can understanding evolutionary relationships within the B. tabaci complex contribute to long term, sustainable management?

3 Assumptions Biology, ecology, phenology, epidemiology E.g. PYLCV - recommendation was to spray chillis to stop PYLCV. PYLCV reality vector only fed on chillis. It reproduced on cassava, and pumpkin that were planted around or under the chilli plants and on weeds. Spraying of chilli was useless, costs farmers $, but no protection.

4 Assumption: Bemisia tabaci is a species made up of biotypes This thinking may well be holding back how we manage the wide range of problems caused by B. tabaci. Not least because it is based on a profound misunderstanding and lack of comprehension of basic biological fundamentals which permeate how we think about this pest.

5 Why is this important? Vector competence; Host use; Landscape ecological processes; Biological control; Capacity to evolve insecticide resistance. May vary depending on the evolutionary relationships & these may be predictable when viewed through the right lens. The answer as to whether we are dealing with a single vector species or complex of related, but different species will have a significant bearing on the applicability and transferability of management practices between regions where the pest occurs. depend on insect biology, behaviour, natural enemies interactions and responses to agricultural chemicals. What works for certain populations may be ineffective for other populations.

6 Myth: Agriculture created the complex

7 Boykin et al BMC Evolutionary Biology mya mya 2 9 mya Take home message Agricultural practice is not responsible for the diversity

8 Myth: Biotypes

9 Early observations Bird 1957: Sida, Jatropha races Burban et al. 1992: host-associated biotypes in West Africa Costa & Russel 1975: host associated races, cassava Critically important point to recognize, Strong connections with biological traits e.g. Host use Mating compatibility Vector competence Induction of physiological changes in the host Differentiation based on assessment of biological traits. Distinctions between sympatric populations NOT allopatric or parapatric populations. Morphologically indistinguishable. Biotypes.

10 Molecular data to the rescue.or not! Allozymes RAPDs SCAR CAPS RFLP rits1 Microsatellites mtcoi AFLPs mt16s Morphologically indistinguishable Biological invasions - Shift to groups that until very recently (i.e. trade): geographically quite separate. Need to distinguish..reliance on molecular data. Shift away from recognising group difference based on biological traits to sole reliance on molecular data. Easy and relatively cheap. Proliferation without delimitation, Fundamental lack of the answer to this question how different do two pieces of molecular data need to be before they are really different. I think therefore it is.

11 Lack of consistency proliferation of biotypes : same critter + different tools = new biotype Not 1:1 AsiaII_1 K = Esterase P = Esterase Others: mtcoi K, PK1 and ZHJ2: identical mtcoi

12 John Innes: Biotypes Dinsdale Species: mtcoi A Arizona cotton New World1 B Israel tomato MEAM1 B2 Yemen cotton MEAM1 C Costa Rica tomato New World1 D Nicaragua squash New World1 E Benin Asystasia Sub Saharan Africa but likely to be a new species. Particla sequence with only 368 bp overlap F Guatemala cotton New World1 G India Kerala, South watermelon AsiaII_5 H India Gujarat, north cotton AsiaI J Nigeria cotton Mediterranean_silverleafing K Pakistan cotton AsiaII_1 L Sudan cotton Mediterranean M Turkey cotton AsiaI N Puerto Rico Jatropha New World1 P Nepal watermelon AsiaII_1 Q Spain cotton Mediterranean R Colombia tomato New World1 S Spain Ipomea Sub Saharan Africa 2

13 I think therefore it is. Assigning structure based on how the tree looks, (Simplification of tools + Simplification of methods) x Lack of deep understanding of application = Proliferation and confusion Different authors using similar data publish different names for the same thing.

14 Massive proliferation of number of biotypes Based almost solely on molecular data. Papers are published without basic molecular data being available during the review process e.g. sequences made available in GenBank after the review process has been completed no chance to pick up the 100s/1000s of errors in GenBank deposited sequences.more on that later. Little or no biological data. Interpretation: Limited understanding of how to use tools and methodologies correctly or appropriately. Names are there to communicate information, simplify messaging

15 Delimitation at last

16 Dinsdale et al Delimitation at last Based on statistical delimitation metrics Measurable, quantifiable, repeatable, transferrable First step

17 Reproductive compatibility Connecting the molecular interpretation of structure back to the biological interpretation using well understand species concepts. 1. Med 2. MEAM1 3. SSA1 4. SSA2 5. Uganda 6. Italy 7. Asia I 8. Australia 1 9. Australia AsiaII_1 11. AsiaII_3 12. AsiaII_5 13. AsiaII_6 14. AsiaII_7 15. China New World Uganda ASL

18 Structure supported by biology Mating and reproductive compatibility assessments Connecting molecular data back to biology Measurable, verifiable structure Clear evidence of, consistent genetic differentiation lack of gene flow numerous examples of, No or limited mate recognition No or limited production of female offspring Species level differentiation: quantifiable, reproducible, transferable, deal with unknowns Biotype concept: subjective, not quantifiable not reproducible not transferrable unable to deal with unknowns objectively

19 Structure

20 Sub-Saharan Africa Mediterranean/North Africa/Asia Minor /Indian Ocean/Sub-Sahara Africa New World Mediterranean/Sub-Sahara Africa /Asia/Australian 20

21 Lipaleyrodes Originated in southern Africa Africa to Middle East to Mediterranean Africa to Middle East to Asia Minor Africa to New World Africa to North Africa/Mediterranean to Asia

22 Indian Ocean (West Africa & Indian Ocean Is) Mediterranean SubSaharan Africa Middle East Asia Minor 1 See WTT this meeting Middle East Asia Minor 2 MEAM1 80 haplotypes 44: invasive 1: 80%, 37 countries 1: 2%, 6 countries 1: 4%, 5 countries 8.9% sequences home range

23 Mediterranean Mediterranean + beyond Majority of invasive haplotypes come from western Mediterranean Historically significant: Gennadius 1889, Greece Wee Tek Tay will delver more deeply into historical records 63: haplotypes 12: invasive 2: >2 countries 59.1%: home range

24 The challenge We have generated lots of trees identified lots of diversity Identified lots of species Made lots of mistakes and continue to do so because we are not taking enough care with the primary data New Challenge Having solved the biotype question, let s do a better job with the species question.

25 Complicating the complicated Check your sequences carefully, Stop codons - Poor data integrity processes Questionable SNPs - Poor data integrity processes hybrid mtcois - PCR contamination Reliance on partial mtcoi

26 Stop codons: Poor data integrity processes Wee Tek Tay, National Plant Biosecurity Diagnostic Network - Whitefly Diagnostic Workshop (Goddard building, Univ. Queensland, Brisbane; 22nd June 2017

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28 Blast ARG2

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30 Pseudo genes Errors here too!

31 Stop codons in the 5 end MEAM2 3 mtcoi What we do not usually sequence: MiSeq What we usually sequence Reliance on partial gene sequence is a problem

32 Questionable SNPs Species SSA2 & SSA4 Wosula et al Genome Biology and Evolution Samia Elfekih & WTT, April 2018

33 Source of reference sequences

34 When you check against a gold standard e.g. MiSeq MEAM1 & MED mtcoi

35 Wosula et al. used a bad reference sequence

36 13 GenBank MEAM1 vs MiSeq MEAM1 mtcoi (KY951450) WTT, April 2018 Study the AA translation Review the AA translation: if an AA in a position that is conserved between species shows a change within a species be suspicious

37 MEAM1 vs CHINA AA changes Gaps Premature stop codons Suspicious SNPs in conserved positions WTT, April 2018

38 hybrid mtcois - PCR contamination new species MEAM3 Took 3 putative MEAM3 species and aligned against our MiSeq MEAM1 mtcoi WTT, April 2018

39 What does it all mean? Interpretation requires caution Relying on a single partial mitochondrial gene COI. Using universal primers not designed for Hemiptera. Confident that we have a species complex. Mapping phenotypic traits to an evolutionary framework requires a sound scaffold on which to build. Bemisia tabaci is complex, but there may be fewer real species in the complex than the literature suggests. Much less real intra-species diversity. Care and attention to detail is needed when interpreting sequence data

40 How will this contribute to the knowing the enemy better? Phenotypic traits - underpin the problems Evolution of host insecticide resistance Helicoverpa. Evolution of host utilisation despite all the years of research, much of our data is patchy and non-quantitative are we missing the key drivers that under pin landscape ecological processes? Co-evolution with Begomoviruses only makes sense if you have two sound evolutionary stories. Begomovirus whitefly interactions species level variation. Host parastoid interactions species level variation. Evolution of invasiveness all the invaders are closely related.

41 Species level variation in traits Parasitoids

42 Eretmocerus mundus APF 88% Species matters. Parasitoids may do better on different members of the complex Eretmocerus mundus APF 5% Eretmocerus hayati 100% 42 Presentation title Presenter name

43 Eretmocerus mundus Eretmocerus hayati

44 Species level variation in traits Begomovirus transmission

45 Efficiency of transmission varies MEAM1& Asia II_3 -TYLCCNV: similar MEAM1 & AsiaII_3 - TbCSV: similar MEAM1 - TYLCCNV OK versus MED - TYLCCNV unable to transmit TYLCV MED + MEAM1: Similar vs AsiaII_1: Poor Wei et al TbCSV MEAM1: Poor retention vs AsiaII_1: Whole of life Li et al Jiu et al % of the approx 1000 plant pathogenic viruses are whitefly transmitted.

46 Papaya leaf curl China virus: MEAM1 MED Asia 1 AsiaII_7 Guo et al Tomato yellow leaf curl Thailand virus: MEAM1 MED Weng et al Tomato leaf curl Taiwan virus: MEAM1 MED Weng et al Chino del tomate virus: New World 1 MEAM1 Idris et al Mung bean yellow mosaic virus: Asia 1 AsiaII_1 Anokhe et al Bhendi yellow vein mosaic virus: MEAM1 Asia1 Venkataravanappa et al Cotton leaf curl disease: Asia II_1 Ahmed et al MEAM1

47 Are all MEAM1 the same? Cotton leaf curl disease Asia II_1 MEAM1 Ahmed et al Invaded range Home range

48 Species level variation in traits Begomovirus influence on whitefly biology

49 Assymmetrical influence on whitefly biology TYLCCNV MEAM1: AsiaII_3: AsiaII_1: MED: No sig. influence on development, survival, fecundity Sig. reduction Marginal increase in longevity, fecundity Sig. increase in longevity, fecundity Liu et al Liu et al TYLCV MEAM1: AsiaII_3: AsiaII_1: MED: No sig. influence on development, survival, fecundity Sig. reduction No sig. influence on development, survival, fecundity No sig. influence on development, survival, fecundity Liu et al Li et al. 2011

50 Wrap up Bemisia tabaci is a species complex There is considerable biological differentiation between species in the complex genetic differentiation How we use our tools and methodologies is critical It s important to understand this problem assessment, management decisions

51 Thank you