Targeted next generation sequencing for population genomics and phylogenomics in Ambystomatid salamanders

1. Preliminary Results Targeted next generation sequencing for population genomics and phylogenomics in Ambystomatid salamanders Eric M. O’Neill David W. Weisrock Photograph by Stephen Dalton/Animals Animals - Earth Scenes

2. Ambystoma tigrinum complex

3. Coalescent Processes • Stochastic • Incomplete lineage sorting • Gene tree incongruence • Capture variance • Many loci Degnan and Rosenberg, 2006 PLOS Genetics

4. Goals • Sequence >100 independent loci from 100s of samples • both alleles • Population genetics • Species delimitation • Gene phylogenies • Species phylogeny Jeremiah Smith

5. Past Option • Sanger Sequencing • expensive • cloning or computational phasing alleles • low throughput

6. 454 (Roche) Next Generation Sequencing 1 million reads × 400 bp each = 400 Million bp

7. Barcoding Meyer et al. 2008 Nature Protocols

9. Methods • Screened ~250 EST loci across 16 representative samples • Found >100 variable loci that amplify well at the same temperature • Amplified 95 loci for one individual in one plate • 94 individuals • 8930 amplicons • Pooled across 95 loci for each individual • Barcoded 94 individuals and pooled • UKY-AGTC: 454 Libraries, emPCR, 454 sequencing

10. Preliminary Results • Two test runs: 1/8th picotiter plate • 65K + 20K sequences • One final run: 1/4th picotiter plate • 225K sequences • Total ~ 300K sequences • Coverage of about 34X per sample per locus • Sorted >95%

11. 1664 seqs / 95 loci = 18X coverage 96% loci have sequence 45 loci had >10X coverage

12. Genotyping • Clonal amplification through emPCR • Each sequence is derived from a single DNA strand • Identify both alleles without bacterial cloning

13. Errors • Homopolymer regions • Single nucleotide mismatches

14. Automated Statistical Genotyping Hohenlohe et al., 2010 PLOS Genetics

15. Genotyping • Let n be the total number of reads per site • Let n = n1 + n2 + n3, where ni is the read count for each possible nucleotide at the site • For diploid, there are 10 possible genotypes • 4 homozygous (AA, TT, GG, CC) • 6 heterozygous (AT, AG, AC, TG, TC, GC) • Calculate the likelihood of each possible genotype using a multinomial sampling distribution, which gives the probability of observing a set of read counts (n1,n2,n3,n4)

16. Likelihood of a Homozygote

17. Likelihood of a Heterozygote

18. Assigning Genotypes • The 2 equations give the likelihoods of the two most likely hypotheses out of 10 • Use a LRT to compare the Homo vs. Het hypotheses (df=1) • If the test is significant, we assign the most likely genotype at that site for that individual • If the test is not significant, we do not assign a genotype • This process tests for each SNP independently, but we want to genotype the entire sequence

19. 8 ways to be Het at 3 SNPs: C—T—C G—T—C C—C—C G—C—C C—T—T G—T—T C—C—T G—C—T We need to maintain the correct info.

20. Desired Workflow • 454 data received as FASTA files • Sort by barcode • Tommy has some code for this • Assemble by locus (alignments) • Currently in Geneious, what other options? • Genotype (phase the alleles) • Need to implement automated method • Quality scores • Export data as sequences for phylogenetic analysis • Export data as alleles for population genetic analysis