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DNA barcoding and evolutionary relationships in Accipiter Brisson,1760 (Aves, Falconiformes: Accipitridae) with a focus on African and Eurasian representatives.

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Presentation on theme: "DNA barcoding and evolutionary relationships in Accipiter Brisson,1760 (Aves, Falconiformes: Accipitridae) with a focus on African and Eurasian representatives."— Presentation transcript:

1 DNA barcoding and evolutionary relationships in Accipiter Brisson,1760 (Aves, Falconiformes: Accipitridae) with a focus on African and Eurasian representatives Title page with from left to right Accipiter fasciatus, trivirgatus, madagascariensis, minullus and cooperii.

2 Nomenclature A. gentilis: Nl; havik, Eng; gosshawk, Fr; Autour des palombes A. nisus: Nl; sperwer, Eng; sparrowhawk, Fr; epervier d’Europe Buteo buteo: Nl; buizerd, Eng; Common buzzard Fr; Buse variable Buteo albicaudatus; Nl; witstaart buizerd, Eng; white tailed hawk, Fr; Buse à queue blanche Justification for using the latin names throughout the presentation rather than vernacular names. Latin is the language used in science at least for names of species and names in different languages are confusing.

3 Introductory “sheet”. (Accipiter are bird hunters)

4 Content DNA barcoding a short introduction Coverage Methods
General DNA barcoding Mini barcodes 10X threshold, best compromise threshold BCM and BM criteria Character based identification Coverage Sample origins The dataset Methods Character based method (CB) The 10 X intraspecific distance threshold (10 X) The Best compromise threshold (BCTh) Best match and best close match explained Results for DNA barcoding Character based identification Different thresholds Phylogeny reconstruction 291 bp dataset 647 bp dartaset Discussion Conclusion

5 DNA barcoding Identification of species with an agreed upon (part of a) gene (COI) 5’-3’ part of Cytochrome C Oxidase subunit I ~650bp in length Polymerase chain reactions and Sanger sequencing What marker do we use, shortly mention PCR and that it is a common technique. The picture serves as the basis for the lower picture where already a first start of DNA barcoding may be seen (as colours the colourfull lines each represent a specimen)

6 Mini barcodes Genetic material from museums is often degraded
Shorter fragments are needed E.g. sequences of bp or, in some cases even shorter, also work for identification purposes Explain that through time and certain environmental influences (temp, water, radioation) DNA degrades. This illustrates the reason for selecting short fragments, because longer fragments are perfectly possible with fresher material. Explain that the shorter sequences mentioned are still part of the DNA barcode region. This is why they are usefull as well for identifying species. Sonet et al. in press

7 Sample coverage and origins
African and European taxa are well represented The new world partially represented Australia and S-E Asia poorly represented Most samples from RMCA/RBINS (n=83/9) Supplemented with available genbank sequences (n=28) Most, currently recognized, species of African and European Accipiter are represented in this study by one or more samples. The new world samples are almost all from genbank (except A. gundlachii). Unfortunatly Australia ans SE Asia are underrepresented. Samples are from all sources, however most of them are from RMCA/RBINS samples. Explain that about half of the samples included is more than 20 years old, which means that they are certainly degraded. Even the moderns samples are degraded when they are not kept properly.

8 The resulting dataset 25 European and African Accipiter species with a total of 140 specimens sequenced for a 291bp (mini) and 647bp (standard) BC fragment of the COI gene three datasets analysed: dataset A: 25 species, 291bp dataset B: 19 species, 647bp dataset C: 19 species, 291bp This sheet continues from the previous one. It details the exact amount of samples used for this study and the division in datasets. Dataset C is used the investigate the effect of species coverage and sequence length in more detail. This is not an important part of this presentation.

9 Character based indentification
Easy it is about detecting unique differences May be unreliable with insufficient sampling No threshold whatsoever is used Here the first analysis method is introduced. Character based identification is intuitive and straight forward. One just compares sequences and notes the differences. Note that you may compare as many sequences together as you like from as many species, as long as a given position uniquely separates it from the others. Note that the position or substitution type does not matter at all.

10 Average 10 X intraspecific distances and the barcoding gap
Arbitrary Does not always hold (Tephritidae) However, works well in birds Speak shortly about distances (added up differences, see previous sheet) and that thresholds are determined which makes analysis easier and less ad hoc than the previous method. With these methods it already matters what the changes in base comopistion are (mention the K2P parameter here). Mention that it seemed like a good idea to use the average 10 X intra-specific distance value as a good idea for species boundaries. However it is not based on anything other than a majority of tested species met this criteria. Note also that such a value has nothing to do with the biology of a group under study. Then tell that it does not always hold, in particular when intraspecific distances are very small or very big. Note that when analysing DNA barcodes you would like to have a clear difference in the distribution of intra and interspecific distances, but that the figure below approaches the real situations better and that this is an illustration of the difference between the theoretical and the real datasets (which are rarely, if ever, ideal).

11 The Best compromise threshold (BCTh)
Based on the intercept between cumulative intra and interspecific distances Based on the dataset under study rather than a predetermined threshold Results from one dataset not applicable to another Here introduce a different methods. Explain that weak overlap is preferable because you want to identify a high percentage of samples. Refer to the fact that this is not always the case, however this method bases its threshold on the dataset under study and is set up to achieve the highest possible percentage. This allows to also detect new species, id errors, cryptic species are species cluster that are not well defined. Note that this approach only goes for the group/dataset under study. Inclusion of even a few species (especially in a small datset) can lead to a shifting of the threshold, however it reflects the new best optimum rather than simply a predetermined value. Explain what is where. Under circle one are the taxa that are identified on (for instance) morphological basis as species however their sequences overlap with other (ambiguous). This also includes the wrongly identified species. Circle two is where the potentially new taxa are, here taxa with high intraspecific distances are. Give an example if necesary. Example two sequences identified as one species differ more from each other than the threshold. What are they? Lefébure et al. 2006

12 BM and Best Close match Best Match (BM), assignes the species name of its best-matching sequence regardless of how similar the query and reference sequences were. Identification is considered correct when both sequences were from the same species, incorrect if the query species differed from the closest reference species or ambiguous if multiple species were the BM of the query species Best close match (BCM) also considers the threshold This sheet introduces the methods to analyse the dataset with differnt methods. The difference between the methods is in discriminating impossible identifications (pointing to single sequences and new potentially new species). Een nieuwe soort, ‘foutief’ geïdentificeerd als soort A, heeft dan een sequentie met een groter verschil dan de gekozen drempelwaarde.

13 BM vs. BCM example 4 sequences
3 species: A. francesiae (n=2) A. badius (n=1) & A. toussenelii (n=1) BM would assign A. badius and A. toussenelii to the “ambiguous” or “wrong” (dependent on the threshold) categories BCM would classify them as impossible when the difference is larger than the threshold This example dataset is an example and can be used to illustrate the differences between the approaches. Consider the different results for the different approaches with the thresholds of 3% and 10% respectively.

14 Results character based identification
This shows a few results of groups that are closely related or poorly supported by the phylogeny (illustrated later in the presentation). This is more nuanced that blindly looking at the entire sequence. Rather it focuses on the relevant part.

15 Results character based identification
Note that although A. unduliventer has only one unique character, that if you choose only part of the sequences it is still very separable. (Of course a more samples are included it may occur that one A. unduliventer has a mutation at site 96 as well and then the poistion is not unique anymore. Finally identifying either of the three species is possible even if you look at a small part of the gene, lets say the last three bases. The 2nd example show an entire sequence of unique differences between A. minullus and A. erythropus and is straightforward.

16 Results BCTh vs. 10 X distance threshold
An overview of the results. Yellow corresponds the the BCTh and grey to the 10 X thresholds in both figures. Also not the differecences between the BM and the BCM approaches. Here BCM identifies sequences that would otherwise be wrong or ambiguous

17 Results BCTh vs. 10 X distance threshold
Different thresholds Partial overlap Caused by A. nisus/rufiventris A. virgatus/gularis A. cooperii/gundlachi At or just below the BC treshold are A. badius subsp A. gentilis subsp A closer look at the 291bp dataset and the DNA barcoding results. This shows species with very similar sequences (i.e. they are wrongly identified or ambiguous.). Then The A. badius shows the differences between the threshold and shows that they may classified with A. brevipes under the 10 X criterium and as such would be ambiguous or that they would be classified as correct with the BCTh. Even though A. badius sequences may end up in the “incorrect” categorie there because some sequences are now more different from each other than the BCTh threshold.

18 Results BCTh vs. 10 X distance threshold: Accipiter nisus example
A. rufiventris A. nisus These species have similar sequences and are located below the threshold for species identification

19 Results BCTh vs. 10 X distance threshold: A. Badius and A
Results BCTh vs. 10 X distance threshold: A. Badius and A. brevipes example These species are located at or slightly above the BCTh and below the 10 X distances threshold.

20 Phylogeny reconstruction
Hypothesis of evolution Clades are units of supported taxa (related by direct descent) This dataset is only suited for low taxonomic level inferences One genegene tree rather than species tree Comparison with the current taxonomy based on morphology and morphometrics This explain the possibilities and limitations of the dataset under study when applying phylogenetic analyses to it. The first two points define to terms the 2nd two explain the limitations and the thirds servers to explain the use.

21 Phylogeny based on 291bp 11 supported clades [tachiro] A. minullus
A. tachiro subclades A. minullus A. francesiae/ soloensis [cooperii] A. badius/ brevipes A. nisus/ striatus/ erythronemius A. ovampensis/ madagascariensis [virgatus] including A. fasciatus An overview of the phylogeny based on 291bp of COI. Dashed boxes indicate clades supported by three (any three) of the analysis methods used. They are still counted as supported, thus the number of 11 is reached

22 Phylogeny based on 291bp a closer look
This details two clades of the phylogeny.

23 Phylogeny based on 291bp a closer look: Accipiter tachiro example
The clade with A. tachiro in it is worth noting because it clearly includes A. castanilius as sister to all the other taxa and it shows the distinctive position of A. unduliventerwithin the wider A. tachiro clade.

24 Phylogeny based on 291bp a closer look: Accipiter badius and A
Phylogeny based on 291bp a closer look: Accipiter badius and A. brevipes example The clade with A. badius and A. brevipes is remarkable because A. badius is not supported as monophyletic, rather the relationship with A. brevipes remains unresolved

25 Phylogeny based on 647bp 19 supported clades [tachiro]
A. tachiro A. toussenelii & subsp A. soloensis & A. francesiae subsp [gentilis] [cooperii] [nisus] (without A. ovampensis/ madagascariensis [minullus] (without A. erythropus) [virgatus] including A. fasciatus An overview of the phylogeny based on 647bp of COI. Dashed boxes indicate clades supported by three (any three) of the analysis methods used. They are still counted as supported, thus the number of 19 is reached, this more than the 11 with the 291bp dataset. It shows that longer sequences carry more signal.

26 Phylogeny based on 647bp a closer look
Detailed observations on the phylogeny.

27 Phylogeny based on 647bp a closer look: The example from Accipiter soloensis and A. francesiae
The clade of A. francesiae with A. soloensis is remarkable because A. soloensis is from Asia and A. francesiae is from the Comoros and Madagascar. They are sisterspecies. This implies some colonisatioin event in the past. Presumable from Asia, although without prior knowledge that cannot be concluded from this dataset. The last common ancestor must have occured over a wider range or may have had different migration routes. Also worth noting is the support of some of A. francesiae’s subspecies.

28 Phylogeny based on 647bp a closer look: an example with Accipiter gentilis and A. melanoleucus
The clade with A. gentilis and A. melanoleucus is noteworthy because it remains unresolved. A. gentilis atricapillis is not closer related to A. gentilis gentilis than it is to A. melanoleucus. This implies some morphological evolution in A. melanoleucus. This clade clearly deserves more study. Based on these results the species or subspecies status of either of the taxa is debatable. (A. melanoleucus is a species and A. g. gentilis and A.g. atricapillus are ranked as susbspecies)

29 Discussion Thresholds Species concepts Support values Sampling
The 10 X threshold would have considered A. brevipes and A. badius, as well as A. gentilis and A. melanoleucus as belonging to the same species and Species concepts Morphological Distances based Phylogenetic Support values Models and interpretation remain issues of discussion Sampling Incomplete or lacking in some cases Take home message: The different threshold may have (subtle) influence on the outcome of the DNA barcoding analysis The species concept used and tested against must always be kept in memory and must be well defined. The three mentioned here are all compared in the study. Morphological was being tested. The distances based appraoch was treated via DNA barcodig and the phylogenetic concept with the phylogeny reconstruction The values remain debated, but the ones observed here are generally very good and as all four usually confirm each other there is some confidence in the observed patterns Sampling must be increased as it can be seen that sister species have spread all over the world (also not this in the A. nisus/striatus/erythronemius clade)

30 Conclusions Molecular techniques provide a powerfull method for reviewing taxonomy Museum material works! The content of the dataset matters COI can identify 19 out of the 25 species included COI carries a phylogenetic signal suitable for molecular taxonomy on a low taxonomic level Parts of genus Accipiter may need revision

31 Thank you for your attention
If this ever happens to you, now you know what birds to look for for help Thank you for your attention


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