SNPs versus sequences for phylogeography an explora:on using simula:ons and massively parallel sequencing in a non- model bird

Transcription

1 SNPs versus sequences for phylogeography an explora:on using simula:ons and massively parallel sequencing in a non- model bird Michael G. Harvey, Brian T. Smith, Brant C. Faircloth, Travis C. Glenn, and Robb T. Brumfield 100 CH CH CA NA CA SA SA 0 0 SA 100 NA NA

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3 Which method of genera:ng massively parallel sequence data should I use for phylogeography?

4 Outline 1. Overview of methods for genera:ng massively parallel sequencing data 2. Phylogeography of a non- model bird a. Sequence capture of ultraconserved elements (UCEs) b. SNPs from Genotyping by Sequencing 3. Simula=ons: UCEs vs. SNPs for phylogeography 4. Conclusions

5 Outline 1. Overview of methods for genera:ng massively parallel sequencing data 2. Phylogeography of a non- model bird a. Sequence capture of ultraconserved elements (UCEs) b. SNPs from Genotyping by Sequencing 3. Simula=ons: UCEs vs. SNPs for phylogeography 4. Conclusions

6 What are some of the op:ons? Whole genome sequencing Reduced representa:on library sequencing: - PCR amplicon sequencing - RNA sequencing - Sequence capture - Restric:on digest- based methods (RAD tags, GBS, etc.)

7 What are some of the op:ons? Whole genome sequencing Reduced representa:on library sequencing: - PCR amplicon sequencing - RNA sequencing - Sequence capture - Restric:on digest- based methods (RAD tags, GBS, etc.)

8 How do they work?

9 1. Random fragmenta:on 2. Addi:on of barcodes and adapters, PCR Sequence Capture 3. Hybridiza:on to bio:nylated probes 4. Enrichment with streptavidin beads 5. Amplifica:on, Illumina sequencing

10 Sequence Capture probe 1. Random fragmenta:on 2. Addi:on of barcodes and adapters, PCR 3. Hybridiza:on to bio:nylated probes Enrichment Amplifica:on, with Illumina streptavidin sequencing beads

11 Sequence Capture probe 1. Random fragmenta:on 2. Addi:on of barcodes and adapters, PCR Sequences up to 1000 bp 3. Hybridiza:on to bio:nylated probes Enrichment Amplifica:on, with Illumina streptavidin sequencing beads

12 Ultraconserved Elements (UCEs) are useful for sequence capture Frequency of variable positions Core UCE (probe) UCE alignments across all birds (from McCormack et al. 2013) Distance from center of alignment (bp)

13 UCEs are useful for deep phylogeny

14 But do UCEs work at phylogeographic :mescales?

15 Restric:on Digest- based Methods 1. RE diges:on 2. Addi:on of barcodes and adapters 3. (Size selec:on), amplifica:on, Illumina sequencing

16 Restric:on Digest- based Methods 1. RE diges:on 2. Addi:on of barcodes and adapters 3. (Size selec:on), amplifica:on, Illumina sequencing

17 Restric:on Digest- based Methods 1. RE diges:on 2. Addi:on of barcodes and adapters 3. (Size selec:on), amplifica:on, Illumina sequencing Read- length sequences 100 bp

18 Restric:on Digest- based Methods Methods: CRoPs (Van Orsouw et al. 2007) RAD- seq (Baird et al. 2008) Modified CRoPs (Gompert et al. 2010) MSG (Andolfaao et al. 2011) GBS (Elshire et al. 2011) Modified GBS (Parchman et al. 2012) ddrad- seq (Hohenlohe et al. 2012, Peterson et al. 2012) Modified GBS (Poland et al. 2012) SBG (Truong et al. 2012) 2b- RAD- seq (Wang et al. 2012)

19 Restric:on Digest- based Methods Methods: CRoPs (Van Orsouw et al. 2007) RAD- seq (Baird et al. 2008) Modified CRoPs (Gompert et al. 2010) MSG (Andolfaao et al. 2011) GBS (Elshire et al. 2011) Modified GBS (Parchman et al. 2012) ddrad- seq (Hohenlohe et al. 2012, Peterson et al. 2012) Modified GBS (Poland et al. 2012) SBG (Truong et al. 2012) 2b- RAD- seq (Wang et al. 2012)

20 Sequence Capture RD- based Methods Fewer, longer sequences up to 1000 bp Many, read- length sequences 100 bp (SNPs)

21 What have they been used for? Sequence Capture Re- sequencing in model species (e.g. exome) Phylogene:cs RD- based methods GWAS QTL- mapping Popula:on Gene:cs

22 What have they been used for? Sequence Capture RD- based methods Phylogene:cs Phylogeography? Popula:on Gene:cs

23 Outline 1. Overview of methods for genera:ng massively parallel sequencing data 2. Phylogeography of a non- model bird a. Sequence capture of ultraconserved elements (UCEs) b. SNPs from Genotyping by Sequencing 3. Simula=ons: UCEs vs. SNPs for phylogeography 4. Conclusions

24 Outline 1. Overview of methods for genera:ng massively parallel sequencing data 2. Phylogeography of a non- model bird a. Sequence capture of ultraconserved elements (UCEs) b. SNPs from Genotyping by Sequencing 3. Simula=ons: UCEs vs. SNPs for phylogeography 4. Conclusions

25 Let s try them out! Xenops minutus (Aves; Furnariidae) Smith et al. (in prep.) See talk this agernoon! Peruvian B, 3:30pm Photo: L. C. Ribenboim

26 Study Design UCEs 2 individuals / popula:on 2,560 probes targe:ng 2,386 UCEs ~1/5 lane of Illumina HiSeq (PE) Bioinforma:cs (illumiprocessor, Velvet, phyluce, BWA, MAFFT) ultraconserved.org SNPs 8 individuals / popula:on (+ outgroup) Ins:tute for Genomic Diversity (Cornell Univ.) ~2/3 lane of Illumina HiSeq (SE) Bioinforma:cs (UNEAK)

27 Challenges read quality manual edi:ng sample size thresholds mt excess paralogy keeping indexes straight hybridiza:on contamina:on CPU :me run:mes failed runs qpcr sucks enrichment? file size computa:on memory number of popula:ons

28 UCE Sequence Capture Results

29 1,368 UCE Alignments 834 bp = snps dark gray = missing data

30 UCE Intraspecific Varia:on

31 UCE Tree Reconstruc:on 1.0 *BEAST (Heled and Drummond 2010) 137 loci 9.0E NA SA CA CH

32 UCE Tree Reconstruc:on 1.0 *BEAST (Heled and Drummond 2010) 137 loci 9.0E NA SA CA CH

33 UCE Tree Reconstruc:on 1.0 *BEAST (Heled and Drummond 2010) 137 loci 9.0E NA SA CA CH

34 UCE Demographic Modeling 1.0 G- PhoCS (Gronau et al. 2011) 1,368 loci 9.0E SA NA CA CH

35 UCE Demographic Modeling Time before present (My) SA NA CA CH 0.0

36 Genotyping by Sequencing Results

37 GBS Dataset Summary 106,784 SNPs pre- filtering 2,355 SNPs with data for all individuals

38 SNP Tree Reconstruc:on Methods Concatena:on SNAPP (Bryant et al. 2012) TreeMix (Pickrell and Pritchard 2012)

39 SNP Tree Reconstruc:on Methods Concatena:on SNAPP (Bryant et al. 2012) TreeMix (Pickrell and Pritchard 2012)

40 SNP Tree 100 TreeMix (Pickrell and Pritchard 2012) NA SA CA CH

41 SNP vs. UCE Trees E NA SA CA CH NA SA CA CH

42 SNP Demography Allele Frequency Spectra 16 a i (Gutenkunst Recent High Unequal migra:on divergence et al. N 2009) e Popula:on Popula:on 2 16

43 SNP Demography Allele Frequency Spectra 16 Popula:on Popula:on 2 16

44 SNP Demography Allele Frequency Spectra Popula:on Popula:on 2 16

45 SNP Demography Allele Frequency Spectra Unequal N e Popula:on Popula:on 2 16

46 SNP Demography Allele Frequency Spectra Recent divergence Popula:on Popula:on 2 16

47 SNP Demography Allele Frequency Spectra High migra:on Popula:on Popula:on 2 16

48 SNP Demography Allele Frequency Spectra a i (Gutenkunst et al. 2009) Popula:on Popula:on 2 16

49 SNP Demographic Modeling data model

50 SNP Demographic Modeling NA SA CA CH

51 SNP Demographic Modeling NA NASA SA CA CACH CH

52 SNP Demographic Modeling data model ((NASA) (CACH)) NA NASA SA CA CACH CH

53 SNP Demographic Modeling data model ((NASA) (CACH)) ((NA)(SA)) NA SA CA CH

54 SNP Demographic Modeling data model ((NASA) (CACH)) ((NA)(SA)) NA SA CA CH ((CA)(CH))

55 SNP Demographic Modeling Time before present (My) SA NA CA CH 0.0

56 SNP vs UCE Demography Time before present (My) SA NA CA CH SA NA CA CH 0.0

57 Summary of Empirical Results Species trees are similar between datasets Demographic models differ somewhat in parameter es:mates between datasets

58 Outline 1. Overview of methods for genera:ng massively parallel sequencing data 2. Phylogeography of a non- model bird a. Sequence capture of ultraconserved elements (UCEs) b. SNPs from Genotyping by Sequencing 3. Simula=ons: UCEs vs. SNPs for phylogeography 4. Conclusions

59 Outline 1. Overview of methods for genera:ng massively parallel sequencing data 2. Phylogeography of a non- model bird a. Sequence capture of ultraconserved elements (UCEs) b. SNPs from Genotyping by Sequencing 3. Simula=ons: UCEs vs. SNPs for phylogeography 4. Conclusions

60 Simula:on Treatments Tau (species divergence =me) 0.1, 0.2, 0.4, 0.8, 1.6 θ :me Theta (4N e μ) 0.2, 0.4, 0.8, 1.6, 3.2 θ τ Migra=on rate (N e m) 0, 0.1, 0.3, 0.7, 1.5 github.com/mgharvey/mps- sim θ m m θ m m m m θ τ / 2

61 Divergence Time Es:mate Accuracy a I and 50,000 GBS SNPs G- PhoCS and 1,000 UCEs 3e+06 2 Divergence :me 1 2e+06 1e+06 P 0e+00 Tau treatment Tau Treatment Tau treatment

62 Effec:ve Popula:on Size Es:mate Accuracy a I and 50,000 GBS SNPs G- PhoCS and 1,000 UCEs 5 5e+06 Migrants per genera:on e+06 3e+06 2e+06 1e+06 0e+00 Theta treatment Theta treatment Theta Treatment

63 Migra:on Es:mate Accuracy a I and 50,000 GBS SNPs G- PhoCS and 1,000 UCEs Migrants per genera:on e+00 Migra:on treatment Migration Treatment Migra:on treatment

64 Summary of Simula:on Results SNPs+ a i and sequences+g- PhoCS es:mate divergence :mes with similar accuracy SNPs+ a i es:mate N e and migra:on with higher accuracy

65 Why the Varia:on in Accuracy? 1. Varia:on across datasets 2. Number of loci 3. Number of individuals 4. Analy:cal method

66 Outline 1. Overview of methods for genera:ng massively parallel sequencing data 2. Phylogeography of a non- model bird a. Sequence capture of ultraconserved elements (UCEs) b. SNPs from Genotyping by Sequencing 3. Simula=ons: UCEs vs. SNPs for phylogeography 4. Conclusions

67 Outline 1. Overview of methods for genera:ng massively parallel sequencing data 2. Phylogeography of a non- model bird a. Sequence capture of ultraconserved elements (UCEs) b. SNPs from Genotyping by Sequencing 3. Simula=ons: UCEs vs. SNPs for phylogeography 4. Conclusions

68 Xenops minutus Popula:on History 9.0E Time before present (My) NA SA CA CH SA NA CA CH 0.0

69 Sequences vs. SNPs Sequences from Sequence Capture SNPs from Genotyping by Sequencing CH CH 100 CA CA NA SA SA NA NA 0 0 SA θ 9.0E-5 θ θ τ NA SA CA CH θ m θ m τ m / 2

70 Which method of genera:ng massively parallel sequence data should I use for phylogeography? Sequence Capture RD- based methods Phylogene:cs Popula:on Gene:cs

71 Which method of genera:ng massively parallel sequence data should I use for phylogeography? Sequence Capture RD- based methods Phylogene:cs Phylogeography Popula:on Gene:cs

72 Harvey Commiaee Members Mike Hellberg Jeremy Brown James V. Remsen Brumfield Lab John McCormack Liz Derryberry Glenn Seeholzer Caroline Duffie James Maley Sarah Hird Andrés Cuervo Gustavo Bravo Discussion Bryan Carstens John Andersen Eric Riameyer Clare Brown Noah Reid LSU Bird Lunch LSU Museum of Natural Science LSU Biological Sciences Acknowledgements LSU High Performance Compu:ng Le Yan Bhupender Thakur Support Society of Systema:c Biologists Na:onal Science Founda:on For UCE probe sets, protocols, and code: ultraconserved.org For simula:on code: github.com/mgharvey/mps- sim