M ole c ul ar markers in plant systematics and population biology

1. Molecular markers in plant systematicsand population biology 7. DNA sequencing

2. DNA sequencing • detection the order of nucleotides in a DNA strand…ATATATAGGCAAGGAATCTCTATTATTAAATCATT… • use the information to model evolutionary processes • make hypothesis about similarity and relationships among taxa

3. Sequencing principle • PCR with a primer pair • amplification of the target region • cycle sequencing (dideoxy, Sanger) • use of one primer only • dNTP as well as ddNTP are present in the mixture • produce fragmens differing by exactly one base • electrophoretic separation of fragments in the gel • automated sequencer

4. 2´, 3´- dideoxy NTPs dTTP ddTTP 3´-CTGGACTGCA-5´ 5´-GACCT

5. primer 3´-TACG-5´ 5´-ATGCATGC-3´ template ddGTP ddCTP ddATP ddTTP GTACG CGTACG ACGTACG TACGTACG ATGCATGC ATGCATGC ATGCATGC ATGCATGC Cycle sequencing

6. exon 1 intron exon 2 intergenic spacer exon GENE 1 GENE 2 Genome structure • genetic information – order of nucleotides (ACGT) • coding regions – exons – conserved • non-coding regions – introns, spacers – variable • nuclear, chloroplast and mitochondrial genome

7. Sequence evolutionary rate

8. Types of variability in DNA sequences 5bp indel point mutations

9. Chloroplast genome • many genesare single-copy(only 1 copy in the whole genome) • conserved evolution of the chloroplast genome • disadvantage when studying intraspecific or population variability • many conserved regions can be used as priming sites • structuralrearrangements of chloroplast genome • mainly on larger evolotionary scale • inversion – e.g., 30kb inversiondifferentiate bryophytes and higher plants • extensive deletions • loss of specific genes and intrones • chloroplast capture • chloroplast transfer from one species to another by introgression • can influence phylogeny in a wrong way (when not recognized)

10. Repeatedly sequenced cpDNA regions + many others…

11. rbcL • genefor large subunit of ribuloso-1,5-bisphosphate-carboxylase/oxygenase (RUBISCO) • about 1428, 1431 or 1434 bp in length – indelsare extremely rare • one of the first sequenced genes • very conserved, systematics at the family or generic level, in some groups at the species level

12. ndhF • codesa subunit of chloroplast NADH-dehydrogenase • 2233 bp in length (tobacco) • about 2x more substitutions thenrbcL • for the generic level atpB • genecoding beta subunit of ATP synthase • 1497 bp in length, indels not found • similar use as rbcL

13. matK • genecoding maturase (splicing of plastid genes) • about 1550 bp in length – low number of indels • systematics at the family and generic level

14. trnLUAA trnLUAA trnFGAA 5´exon 3´exon intron spacer trnL intron and spacer between trnL andtrnF • tRNA genes – secondary structure • accumulation of insertions/deletionswith the same rate as nucleotide substitutions • alignment problems, especially in distant organisms (sometimes already at family level) • suitable for systematics of (closely) related species

15. atpB-rbcL • spacer of about 900-1000 bp in length • systematics at family and generic level

16. Variable non-coding cpDNA regionsShaw et al. (2005): The tortoise and the hare II: relative utility of 21 noncoding chloroplast DNA sequences for phylogenetic analysis. Am. J. Bot.92: 142-166 psbM- trnD ycf6-psbM trnC-ycf6 trnS-trnfM trnD-trnT trnL-trnF trnT-trnL rpS4-trnT trnS-rpS4 rpoB-trnC trnG-trnG trnS-trnG 5´rpS12-rpL20 rpS16 psbB-psbH psbA-trnK trnH-psbA rpL16

17. Use of chloroplast sequences • phylogeny of angiosperms • among-species relationships within a genus • within-species phylogeography (hyplotype definition) • hybridization – inference of the maternal taxon (individual) – cpDNA maternaly inherited in angiosperms

18. Angiosperm phylogeny Jansen et al. (2007) 81 plastid genes 76,583 nucleotides

19. Relationships among species Capsicum atpB-rbcL spacer Walsh & Hoot (2001)

20. Phylogeography Arabis alpina trnL-trnF Koch et al. 2006

21. Inter-specific hybridization incongruence between cpDNA and nDNA Persicaria matK, psbA-trnH, trnL-trnF versus ITS Kim & Donoghue 2008

22. Data analysis S206 ATATATATATAGGCAAGGAATCTCTATTATTAAATCATTTAGAATCCATA S207 ATATATATA--GGCAAGGAATCTCTATTATTAAATCATTTAGAATCCATA S208 ATATATATA--GGCAAGGAATCTCTATTATTAAATCATTTAGAATCCATA S209 ATATATATA--GGCAAGGAATCTCTATTATTAAATCATTTAGAATCCATA S210 ATATATATA--GGCAAGGAATCTCTATTATTAAATCATTTAGAATCCATA S0G3 ATATATATA--GGCAAGGAATCTCTATTATTAAATCATTTAGAATCCATA TLATATATATATAGGCAAGGAATCTCTATTATTAAATCATTCATAATTCATA • multiple alignment • construction of phylogenetic tree • distance methods • maximum parsimony (MP) • maximum likelihood (ML) • Bayesian inference (BI)

23. Maximum parsimony (MP) • cladistic method • search for the simplest tree (most parsimonious tree) • i.e., tree in which the evolution is explained by minimum number of substitutions • software PAUP * Phylogenetic Analysis Using Parsimony (* and other methods)

24. Maximum likelihood (ML) • search for tree with the highest probability (likelihood – L) • probability that observed sequences evolved under given tree topology (and under given evolutionary model) • software PAUP, PAML, …

25. transition purines A G transversion pyrimidines T C Evolutionary models for DNA sequences • models for sequence changes • parameters • base frequences • substitution types (transitions, transversions) • heterogeneity in substitution rates • proportion of invariant sites

26. a a a a A A G G a a T T C C a b A G a a a a a a a a T C a b b A G a a a a T C b a A G c e b d T C f Substitution models JC(Jukes-Cantor 1969) – same substitution rates – same base frequencies K2P(Kimura 2parameter 1980) – two different substitution rates – same base frequencies F81(Felsenstein 1981) – same substitution rates – different base frequencies Increasing number of parameters HKY(Hasegawa, Kishino & Yano 1985) – two different substitution rates – different base frequencies GTR(General time-reversible model) (Tavaré et al. 1986) – six different substitution rates – different base frequencies

27. Which model to select? • MODELTEST: A tool to select the best-fit model of nucleotide substitution (Posada et al.) • testing 56 different models – selecting the simpliest that výběr toho nejjednoduššího, který sufficiently explain the data using • hierarchical likelihood ratio tests (hLRTs) • Akaike information criterion (AIC) • http://darwin.uvigo.es

28. Saturation • signal and noise in the data • corrected versus uncorrected distance • skewness (g1-statistics), ISS

29. Gene banks – databases of sequences • GenBankNational Centre for Biotechnology Information (NCBI)http://www.ncbi.nlm.nih.gov/ • EMBLEuropean Bioinformatics Institute (EBI) http://www.ebi.ac.uk/embl/

30. Population study Chiang T.Y. & Schaal B.A. (1999): Phylogeography of North American populations of the moss species Hylocomium splendens based on the nucleotide sequence of internal transcribed spacer 2 of nuclear ribosomal DNA. Molecular Ecology 8:1037-1042

31. Systematic study Martins L., Oberprieler C. & Hellwig F.H. (2003): A phylogenetic analysis of Primulaceae s.l. based on internal transcribed spacer (ITS) DNA sequence data. Plant Systematics and Evolution 237: 75-85

32. Literature Soltis D.E. & al. [eds.] (1998): Molecular systematics of plants.II. DNA sequencing. Hollingsworth & al. [eds.] (1999): Molecular systematics and plant evolution. Hall B.G. (2001): Phylogenetic trees made easy. Felsenstein J. (2004): Inferring phylogenies. Lemey P. & al. [eds.] (2009): The phylogenetic handbook. 2nd ed.