A targeted subgenomic approach for phylogenomics based on microfluidic pcr and high throughput sequencing
0 likes870 views
The document discusses a targeted subgenomic approach for phylogenomics using microfluidic PCR and high-throughput sequencing, detailing the design of primer pairs and their success rates across various plant species. It presents findings from the 1000 Plants Project, emphasizing the successful validation of primers for nuclear and chloroplast regions with varying success rates. The research highlights the efficiency of this method in generating genomic data for phylogenetic studies.
A targeted subgenomic approach for phylogenomics based on microfluidic pcr and high throughput sequencing
- 1. A targeted subgenomic approach for phylogenomics based on microfluidic PCR and high-throughput sequencing Simon Uribe-Convers, Matt L. Settles and David C. Tank University of Idaho www.simonuribe.com@uribe_convers
- 2. The era of Genomics
- 3. The era of Genomics Sequence Capture Genome Skimming GBS/RADSeq Transcriptomes Whole Genome
- 4. The era of Genomics Illumina platform Genomic Library Amplification Sequencing
- 5. http://www.dddmag.com/sites/dddmag.com/files/legacyimages/Articles/2009_11/fluidigm.jpg Targeted (sub-) genomics -Using Fluidigm Access Array -48 x 48 (2304 PCRs) -Ready for next-gen sequencing Microfluidic PCR
- 6. Modifiedfrom:http://www.dddmag.com/sites/dddmag.com/files/legacyimages/Articles/2009_11/fluidigm.jpg Primer: forward & reverse Conserved sequence Barcodes Sequencing adaptors -4 primer reaction -Dual barcodes and adapters are incorporated in the reaction -No need for library preparation! Microfluidic PCR
- 7. Primer design criteria 700bp -Variable regions between 400-900bp -Conserved flanking regions -Every primer has the same annealing temperature (60°C)
- 9. 1000 Plants Project (1KP) MarkerMiner
- 10. Chloroplast data -Six complete plastomes (via long PCR) -Most variable regions in the chloroplast -Designed 74 primer pairs
- 11. -53 primer pairs were successfully validated -72% success rate -The 48 most informative ones were chosen average variability 2.7% (0.8%-7.5%) LSC IRB SSC Small Single CopyLarge Single Copy Inverted Repeat Chloroplast data
- 12. -Low coverage genomic data -Shotgun sequencing for four sample - three species HiSeq 2000 - 100bp paired-end reads Nuclear data
- 13. Orthology, yes! -Compared our reads to public databases PPR gene family COSII ! -Pipeline: BLAT Keeps reads and gene MAFFT IntronFinder from SolGenomics Nuclear data
- 14. R primer ExonExon Target gene F primer 400-800 bp
- 16. Raw reads
- 17. -Trimming (optional) -different values for R1 and R2 ! -Merge reads -Min. 20 bp overlap -Red colors are joined reads -Grey colors are unpaired ! -Very little missing data ! !
- 18. Sample 1 Sample 2 Sample3 Raw reads -Split reads into samples by dual barcodes (demultiplexing)
- 19. Region 1 Region 2 Region 3 Sample 1 -Split reads into amplicons by primers -Up to 2 primer mismatches -4 last bp of primers must match to produce clean ends
- 20. Sample 1 - Region 1
- 21. Sample 1 - Region 1 40% 40% 15% 5% Minimum 5 reads and 5% of all reads
- 22. Sample 1 - Region 1 21% Minimum 5 reads and 5% of all reads 21% 21% 21% 12.5% 4.1%
- 23. Neobartsia - Orobanchaceae (Uribe-Convers et al. in prep; UIdaho) 576 samples Nuclear: 21 PPR, 24 COSII, 1 ITS, 1 ETS, 1 Phototropin2 Chloroplast: 48 most variable regions Total: ~50,000 bp Gene Family No. Primer Pairs Validated Primer Pairs Success rate PPR 44 26 59.09 COSII 130 25 19.23 ITS 4 3 75 ETS 4 4 100 Phototropin1 3 0 0 Phototropin2 3 3 100 Total 188 61 32.44
- 25. Castilleja - Orobanchaceae 96 samples Nuclear: In primer design Chloroplast: 48 most variable regions Total: ~25,000 bp CNMR.8 CNMR12 CACC17 CNMR.9 CNRM.4 CAPB28 CACC10 CAPB.1 CAPB29 CNRM.1 CATB26 CATB23 CACC13 CNRM30 CNAC21 CNAC10 CNAC22 CNAC19 CNNR28 CAMD.4 CAMD.2 CAMD.7 CASCS13 CWMT.1 CWMT.2 CMPAL29 CMPAL.8 CMPAL20 CAPRC.8 CAPRC.9 CAPRL.8 CAPRD.6 CNPH12 CNPC21 CNPC15 CNPC.9 CNPH14 CNPH13 CNNR30 CASC31 CASC.1 CMJH21 CMJH20 CMJH10 CLiWA26 CLiWA30 CLiWA16 CLaPL.6 CLaPL.1 CLaPL.4 CLaGP.5 CLaGP.3 1103a 1103b CWMB.5 CWBH.1 CWMB.6 CWMB.1 CWBH20 767d 770 771a CLiHD15 CLiPP21 CLIPP16 CLIHD13 CMNP19 CLIHD10 CLiTB18 CMNP25 CMNP13 CLiSW15 CLiSW16 CLiSW14 CLiPP12 CMMP.2 CMMP.9 CMMP10 CAAR.1 CAAR10 CAAR11 CLiDN.5 CLiDN.4 CLiDN16 CLiDN17 CLiTB.2 BS ≥ 75% BS ≥ 90% BS = 100% C. affinis var. affinis C. affinis var. neglecta C. affinis var. inflata C. affinis var. contentiosa C. affinis var. insularis C. wightii C. mendocinensis C. latifolia C. litoralis A C D E F G B A B C D E F G Castilleja affinis vars. affinis/neglecta/inflata Castilleja mendocinensis / C. wightii Castilleja latifolia Castilleja affinis var. contentiosa Castilleja wightii Castilleja affinis var. insularis Castilleja litoralis / C. mendocinensis Tank et al. in prep
- 26. Lachemilla - Rosaceae (Diego Morales-Briones et al., UIdaho) 288 samples Nuclear: 48 genes, Chloroplast: 48 most variable regions Total: ~55,000 bp Autopolyploidy Allopolyploidy
- 27. Cucurbita - Cucurbitaceae (Heather-Rose Kates et al.; UFlorida) 22 species Nuclear: 48 genes Draba and Solanum - Solanaceae (Ingrid Jordon-Thaden et al.; Bucknell University) Nuclear: Genes based on transcriptomes using MarkerMiner
- 28. Tank lab Diego Morales-Briones, Hannah Marx Sarah Jacobs, Maribeth Latvis ! IBEST Sam Hunter, Dan New, Tamara Max ! Acknowledgments @uribe_convers