Single Nucleotide Polymorphism (SNP) Calling from Next-Gen Sequencing (NGS) data for Bacterial Phylogenetics

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1 Single Nucleotide Polymorphism (SNP) Calling from Next-Gen Sequencing (NGS) data for Bacterial Phylogenetics Taj Azarian, MPH Doctoral Student Department of Epidemiology College of Medicine and College of Public Health and Health Professions

2 Phylogenetic/dynamic Analysis The melding of immunodynamics, epidemiology, and evolutionary biology to understand the inter- and intrahost evolution of pathogens Applications: Tracking a pathogen s emergence Understanding the demographic history of a pathogen e.g. changes in effective population size Understanding the intra-host evolution e.g. HIV, HCV, HBV

3 Genomic Epidemiology The use of whole-genome sequencing (WGS) data as an approach to outbreak investigation Applications: Aid in the investigation of infectious disease outbreaks Discerning sporadic and outbreak cases and Identify epidemiologically important strains Identify transmission chains/events and link cases Study virulence Advances in NGS have allowed for these methods to be applied to bacterial pathogens

4 What everyone thinks it looks like Bacterial Isolate Phylogenetic Dendogram

5 What it really looks like Sequence1 Sequence2 Sequence3 c t a a a g a c t t g a t t a c t a t a t g c t t c a t c t c t a t a g a g t t c a t t a

6 Altmann A, Weber P, Bader D, et al. (2012) A beginners guide to SNP calling from high-throughput DNAsequencing data. Hum Genet 131: doi: /s z

7 Raw Reads Filtered Reads Mapping Genome-wide SNP analysis pipeline Variant Calling Variant Filtering Filtered SNP Alignment Demographic history Annotation Report SNP Annotation Codon Alignment Phylogenetic Analysis Selection Analysis

8 Example: Vibrio cholerae in Haiti Currently studying the ongoing cholera epidemic in Haiti that began in 2010 Understand the etiology of the outbreak strain and track the emergence Conducted WGS and phylogenetic analysis on 28 cholera isolates

9 V. cholerae Genome V. cholerae has two circular chromosomes totaling 4,033,460 base pairs (bp). Chromosome 1 = 2,961,146 bp Chromosome 2 = 1,072,314 bp Majority of genes for cell functions and pathogenicity are located on the large chromosome.

10 1. gdna Isolation and Sequencing Genomic DNA (gdna) isolation performed using the Roche High Pure PCR kit Sequencing conducted on Illumina HiSeq to produce 2x100 paired end reads 7.6 million forward and reverse reads (15 million total) Currently use Illumina MiSeq to produce 2x250 paired end reads

11 2. Quality Control and Filtering Filter reads by length and Phred quality score (min=20-30) using Sickle -> removed ~500k reads BEFORE AFTER Sickle Adaptive Window FASTQ Trimming Tool

12 3. Reference Based Assembly/Mapping Mapped reads to V. cholerae N16961 reference sequence downloaded from GenBank and indexed in Galaxy Used BWA but have tried other including Bowtie2 so that unmapped reads could be exported

13 4. Post-processing Remove duplicate reads and conduct local realignment around insertions and deletions Add read group to BAM Picard Mark and remove duplicate reads Picard INDEL Realigner GATK Tools Paired-end read mate fixer Picard Base quality score recalibration?

14 5. Visualization: Integrative Genome Viewer ~19,000 bp deletion of the CTX region spanning 25 genes

15 5. Visualization: Tablet Genome Viewer

16 6. Variant Calling, Filtering, & Annotation FreeBayes Bayesian Variant Detector Can handle haploid genomes Optimized for multiple samples SNP Filtering using VCFtools Genotype likelihood/frequencies, quality, and depth Annotation using SnpEff Extract codons to identify identify dn and ds

17 Unfiltered VCF File from FreeBayes Output

18 VCF Visualization: Integrative Genome Viewer

19 Final filtered and annotated SNP example Chromosome Index Reference Variant Effect Codon Change Gene ID Gene name SYNONYMOUS amino acid ABC transporter ATPbinding NC_ G A CODING gtc/gtt GI: protein NON- SYNONYMOUS NC_ C T CODING Gcc/Acc GI: thiol:disulfide interchange protein NC_ A C NON- SYNONYMOUS CODING gat/gag GI: sun protein SYNONYMOUS NC_ G A CODING aag/aaa GI: sensory box/ggdef family protein NC_ T C SYNONYMOUS CODING agt/agc GI: cell division protein FtsY SYNONYMOUS NC_ T C CODING tat/tac GI: cell division protein FtsX NON- SYNONYMOUS GI: trna (uracil-5-)-methyltransferase NC_ G A CODING gcg/gtg NC_ C T NON- SYNONYMOUS CODING tgc/tac GI: alkaline serine protease SYNONYMOUS NC_ T G CODING gca/gcc GI: multidrug resistance protein NC_ C T NON- SYNONYMOUS CODING GI: hypothetical protein tcg/ttg

20 7. VCF -> FASTA SNP Alignment

21 8. Phylogenetic Analysis Nucleotide substitution model testing Mega PAUP* v4.0 Maximum Likelihood Phylogenetics RAxML Bayesian Phylogenetics BEAST (now 1.8) Selection Analysis HyPhy

22

23 Assessing Selection - Comparison of dn/ds in Backbone Branches

24 Future Directions Improve SNP Filtering Reduce false positive SNP calls De novo assembly using Velvet How to deal with contigs Genome alignment using Mauve Recombination? BRAT NextGen TreePuzzle

25 Special thanks to: Alex Moskalenko and the UFIT Research Computing Unit Dr. Salemi s lab Dr. Ali s lab Questions?

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