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Agricultural Research Council Biotechnology Platform

Agricultural Research Council Biotechnology Platform. Purpose of the Biotechnology Platform. Vision Statement To create a world class biotechnology platform to lead research in agriculture in Africa. Service and Research Facilities Model. Technology Focus of Unit.

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Agricultural Research Council Biotechnology Platform

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  1. Agricultural Research Council Biotechnology Platform

  2. Purpose of the Biotechnology Platform Vision Statement To create a world class biotechnology platform to lead research in agriculture in Africa

  3. Service and Research Facilities Model Technology Focus of Unit Key technologies being performed with the sub-platform as services to research groups and pipelines with the ARC and to outside clients Unit Each sub-platform to have a development group responsible for introducing new technology and applications into the core services Core Services Internal Research teams, lead by SR, SpR, PR level scientists. With MSc, PhD and PD level students as the major part of each team. Primarily externally funded with competitive grants Development group Research teams within platform Research teams at Institutes External Research teams, led by SR, SpR, PR level scientists.MSc, PhD and PD level students are the major part of each team. Primarily externally funded with competitive grants

  4. Bioinformatics Genomic Selection Genomics Databases Annotation Assembly Expression Analysis Molecular Modeling and Docking High throughput DNA Isolation Genotyping Informatics Mutation Breeding Double Haploids DNA Isolation Next Gen Sequencing Genotyping Genetic Mapping Quantitative Genetics Genome Engineering Plant Phenotyping Plant Transformation Reverse Genetics Gene Silencing Male Sterile Technology Targeted Mutagenesis High throughput imaging and sensing GC MS/MS Informatics Tissue Culture Construct development Transformation Regeneration

  5. Shift in Paradigm from Finding Animals/Plants to Finding the right genes/genotypes OLD PARADIGM Finding the right Animals/Plants NEW PARADIGMFinding the right genotypes

  6. Genomics Applications Sequencing applications SNP applications GWAS Association Genetics Cultivar and Breed ID Genomic Selection SNP validation Candidate Genes Diversity studies Methylation • Genomes, • De novo and re-sequencing • SNPs and CNV calling • Transcriptomes, • De novo and re-sequencing • SNPs and splicing variation • Expression profiling • Small RNA • discovery and expression analysis

  7. Illumina HiScanSQ Platform (Feb 2011) • Dual function system • SNPs and Sequencing • High throughput SNPs • Infinium and GoldenGate technology • 1k to 2.5M SNP chips • Next Generation Sequencing • 150 Gb of DNA sequence per run • Paired end sequencing • 800 M filtered clusters per flow cell • 8 lanes per flow cell • Sample Multiplexing up to 48 samples per lane • Up to 384 samples per flow cell (up to 10 000 samples next year)

  8. Focused Genotyping

  9. SNP genotyping projects since February 2011 • 816 Bovine SNP50 • 48 Bovine HD • 336 Caprine SNP50 • 192 Ovine SNP50 • 432 Chicken iselect SNP50

  10. Illumina MiSeq Platform (August 2012) • Next Generation Sequencing • Initial Specification (2012) was 1.5Gb per run • Now: 15 Gb of DNA sequence per run (25Gb in 2014) • Paired end sequencing • 40 M filtered clusters per flow cell • 1 lane per flow cell • Sample Multiplexing up to 96 samples per lane • Third indexing will provide thousands of samples at very low cost (R100 per sample). • Sequencing costs higher then that HiSeq2500

  11. Illumina HiSeq2500 Platform (Feb 2014) • Dual function system • Rapid mode and standard mode sequencing • Rapid Mode • 150 Gb of DNA sequence in 27 hours (current) • 1000 Gb of DNA sequence in 6 days (new chemistry) • Standard Mode • 600 Gb DNA sequence in 11 days • Paired end sequencing • 1800 M filtered clusters per flow cell • 8 lanes per flow cell • Sample Multiplexing up to 96 samples per lane • Up to 384 samples per flow cell (up to 10 000 samples next year)

  12. Illumina HiSeq2500 Platform (Feb 2014) • Biggest DNA sequencer in Africa • Data for 10 human genomes every 6 days • Or Cow, Sheep, Chicken, Sunflower, wheat, maize

  13. Liquid Handling Robotics for “1000 samples a day” • jasper

  14. Laser Capture Micro-dissection

  15. What to cut…. Laser capture of samples • Automated sample collection and object recognition • Cutting: Manual, interactive and automated image object recognition(AxioVision) CZ South Africa Grant Martin

  16. Livestock Genomics • Genomic Selection • Livestock Genomics Consortium • Population diversity studies - SNPs • Cattle, goats, chickens • Diversity studies – genome sequencing • Nguni Cattle, buffalo • Genetic studies • Swakara sheep; pig disease

  17. Livestock Pathogens • Many projects at OVI now using Illumina sequencing • BTP genomics work on Anthrax, TB, E. coli • BTP molecular modeling on FMD • Tick genomics

  18. New applications for Sequencing • Meat Species ID – new DAFF project • Metagenomicsof bacterial communities • Pathogen discovery and testing • Genotype-by-sequencing for mapping and Marker Assisted Breeding

  19. How much will it cost you???

  20. DNA Sequencing – now even faster and cheaper Jan 2014 – 1000 Gb/6 days July 2012 – 120 Gb/day July 2011 – 150 Gb/10 days March 2011 – 55 Gb/10 days March 2008 – 300Mb/3 days

  21. Cost of sequencing • MiSeq • R1500 sample prep • R2500/GB data generated ~ R2000 to generate data for a complete mitochondrial genome of 1 animal @ X30 coverage • Sample multiplexing options

  22. Cost of sequencing • HSeq2500 • R1100 sample prep • R1100/GB data generated ~ R95 000 to generate data for a complete genome of 1 bull @ X30 coverage

  23. Cost of genotyping • 50-60K SNP chips R1100-R1300 landing cost of chips/animal genotyped • 10% processing cost • ~ R1200-R1500 for genotyping an animal • Cost expected to go down with increased genotyping

  24. Biotech Platform Jan 2013

  25. Contacts Dr. Jasper Rees: ReesJ@arc.agric.za Dr. Farai Muchadeyi: MuchadeyiF@arc.agric.za Mr. Jonathan Featherston: FeatherstonJ@arc.agric.za

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