Sequencing the Genome of Rhipicephalus microplus

Felix D. Guerrero USDA-ARS Knipling-Bushland

U. S. Livestocks Insect Laboratory

Kerrville, TX, USA

on behalf of the Cattle Tick Genome Sequencing Project Team

Historical Background of the Texas Cattle Fever Problem

• Cattle tick was endemic in US

• Problems for cattle industry • 1795 & 1796: Severe outbreaks of

disease in cattle in NC & PA following a shipment of cattle northward from the south

• 1850 – Texas cattle began to be driven through AK, MO, KS & western states: 50-90 % death in cattle

• 1868: disasters in IL & IN left 15,000 cattle dead

$3 billion estimated annual savings in today's dollars realized by livestock industry

• 1200 km Line

• From 70 m -70 km wide

U.S.-Mexico Border

Import >1,000,000 head annually

Mandatory dipping in OP

OP resistant ticks in Mexico

Ticks are Common in Mexico

Based on our belief that the genome holds the key to development of new control technologies!

Critical factors drove us to a two-phase approach Huge genome: 2.4 X larger than human genome

Difficult genome: due to >70% repetitive DNA content

Phase 1 focused on sequencing gene-rich regions

Phase 2 used PacBio to sequence complex genome regions

Phase I Approach: 2004-2009

Identified ~40% of expressed genes in collaboration with TIGR-Vish Nene (2004-7) 50,000 Sanger ESTs sequenced and assembled into Gene Index

~15,000 contigs (currently BmiGI Ver2.1)

Available at http://compbio.dfci.harvard.edu/tgi/ ESTs in GenBank

Murdoch Univ. collaboration produced CattleTickBase http://ccg.murdoch.edu.au/organism/rhipicephalus/

Transcriptome of 28,900 contigs from 24,673,517 bp

Phase I Approach: 2009-2012

Sequence "unique" gene-rich regions of genomic DNA through a reassociation kinetics-based approach

• Cot selection Collaboration with Mississippi State University and

Molecular Research LP (MR DNA)

Phase I Approach: 2009-2012

Genomic DNA Fractions

Highly repetitive: Sequencing technology not available

Moderately repetitive: Available technology too expensive

Unique: Appropriate technology existed Isolate and sequence

Assembly into database

(Database consists of exons, introns, promoter)

Cot Selection Overview

Selection Protocol:

- Use highly purified genomic DNA

- Shear DNA to ~500 bp

- Resuspend DNA in sodium phosphate buffer

- Use DNA renaturation kinetics protocol

Basis of This Approach: DNA Renaturation Kinetics

Rate at which a specific single stranded DNA sequence reassociates in a solution (finds its complement) depends on how often it occurs in the genome. Thus: Repetitive DNA quickly reassociates to double-

stranded DNA Gene-rich low-copy DNA slowly reassociates

boil

Incubate for mathematically determined time and temperature

Dissociation: Reassociation

Stop reassociation with sodium phosphate buffer

ds ss DNA state change

1. Pour over hydroxyapatite resin. Wash resin with 0.03M.

1. Recover ssDNA (has not reassociated) with 0.12M

2. 454 sequencing protocol

Followup with Hydroxyapatite Chromatography

Selective binding of ssDNA using hydroxyapatite

Total Low Cot Data Assembly

Run Total Reads Total Bases

454 FLX 6 runs: 1,365,419 ~0.3 x 109

454 Titanium 6 runs: 5,851,291 ~1.5 x 109

Illumina HiSeq 3 runs: 509,552,505 ~50 x 109

RESULT: Total ~25X coverage of gene-rich region of genome

Overview of Illumina Cot DNA Scaffold Production Methodology

HiSeq Quality-checked Reads

50 x 109 seqs split three ways 50 x 109 seqs

Cap3 assembler (In progress)

Genome assembly

Phase 1 Product: Gene-rich Dataset

CattleTickBase: Website hosts the transcriptome and genome sequencing datasets

Collaboration with Murdoch University, Perth, Australia.

http://ccg.murdoch.edu.au/organism/rhipicephalus/

Transcriptome of 28,900 contigs Reassociation kinetics-based approach for partial genome sequencing of the cattle tick,

Rhipicephalus (Boophilus) microplus. FD Guerrero, P Moolhuijzen, et al., BMC Genomics 11: 374, 2010.

CattleTickBase: An integrated Internet-based bioinformatics resource for Rhipicephalus (Boophilus) microplus. MI Bellgard, PM Moolhuijzen, et al. Intl J Parasitol 42: 161-169, 2012.

Phase 2: Sequencing the Difficult Genome Regions 2012-13

Utilizing Next-Next Gen technology: Pac Bio in long-read mode

Collaboration with National Center for Genome Resources in Santa Fe, New Mexico.

177 Pac Bio SMRT cells (runs)

>200 million reads per SMRT cell New Version 3 cells

New Pac Bio XL enzyme

Avg. sequence read length ~5,000 bp

The Size of the Problem

• Statistics:

• 14,000,000 Pac Bio sequences

• Average read insert length = 2,371

• Maximum read insert length = 26,364

• Total number of tick genome basepairs = 33 x 109 (5X coverage)

• Must error correct PacBio reads before assembly.

• Using LSC Pac Bio error correcting program

• http://www.healthcare.uiowa.edu/labs/au/LSC/

• Such a large PacBio read set covering an entire complex eukaryotic

genome been never been reported as assembled.

Phase 2 Product: Draft Quality Genome Sequence

~12X genome coverage 52 x 109 bp from Illumina/454

33 x 109 bp from Pac Bio

2 x 109 bp from BAC library clone sequencing Collaboration with Amplicon Express

Assembly underway at Murdoch University Anticipate manuscripts in late-2014 and having draft

sequence available to scientific community through GenBank and CattleTickBase.

(1) Low cot 454

(2) Low Cot Illumina

(3) 18,000 BACs

Combined sets 1, 2

Soap, Ray, cap3 assemblers Combined

sets 1, 2, 3

(4) LSC Pacbio error correction

(5) 15K BAC

scaffolds

Combined sets 1,2,3,4

Combined sets 1,2,3,4

cap3 assembler

cap3, MIRA4 assemblers

cap3 Completed Ongoing Pending

Assembly Overview

12X-Coverage in CattleTickBase

Whole Genome of R. microplus 7.1 Gbp

High and Moderate Repetitive Unique Gene-rich

Phase II PacBio + BACs

Phase I ESTs + low Cot

Human Genome 3.2 Gbp

By comparison >>>

Route to Anti-Cattle Tick Vaccine

Genome studies identified tick genes and sequence

Bioinformatics computational analysis helps identify gene function

For vaccine development, we focus on tick genes/proteins with critical function Development

Feeding

Pathogen transmission

Vaccine Antigen Candidates Selection Criteria

Selected from tissue-specific transcriptomes

Verified expression in gut or ovary membrane.

Low sequence similarity to mammalian proteins.

Exclude members of large gene families. Prefer single or low copy genes to avoid functional

redundancy among gene family members.

Critical function to the tick.

Genome Project-Selected Vaccine Candidates

Name Basis for Selection Status

Antigen 1 (Aquaporin) In silico structure and function In cattle trials

Antigen 2 Midgut/saliva protein Upregulated w/Babesia inf.

In cattle trials

Antigen 4 Midgut upregulated w/Babesia inf. + outperformed Bm86 during in vitro tick feeding

In cattle trials

Antigen 5 Antigen 6 Antigen 7 Antigen 8

Upregulated in adult gut, receptor binding function Adult gut protein upregulated after Babesia infection Adult ovary protein upregulated after Babesia infection Protein upregulated in ovary and salivary glands after Babesia infection

Lab scale up Lab scale up Lab scale up Lab scale up

Acknowledgements

Consortium Leadership Team Felix D. Guerrero, USDA-ARS Kerrville, TX, USA

Matthew I. Bellgard, Murdoch University, Murdoch, WA, Australia

Robert J. Miller, USDA-ARS Edinburg, TX, USA

Collaborating Organizations U. S. Dept. of Agriculture, Agricultural Research Service

Kerrville, TX, Edinburg, TX, and Beltsville, MD

Murdoch University, Murdoch, WA, Australia

National Center for Genome Resources, Santa Fe, NM, USA

Purdue University, West Layfayette, IN, USA

Mississippi State University, Starkville, MS, USA

J. Craig Venter Institute, Rockville, MD, USA

Queensland Alliance for Ag. and Food Innovation, Brisbane, QLD, Australia

Amplicon Express, Pullman, WA, USA

Molecular Research LP, Shallowwater, TX, USA

Acknowledgements

Individuals from each organization (apologies to any that might have been left off) U. S. Dept. of Agriculture, Agricultural Research Service

Felix D. Guerrero

Robert J. Miller

Adalberto Perez de Leon

Kylie G. Bendele

John E. George

Daniel Strickman

Murdoch University, Murdoch, WA, Australia Matthew I Bellgard

Roberto Barrero

Paula Moolhuijzen

Adam Hunter

John McCook

Michael Black

National Center for Genome Resources, Santa Fe, NM, USA Ernie Retzel

Callum Bell

Andrew Farmer

Jennifer Jacobi

Nico Devitt

Peter Ngam

Patricia Mena

Faye Schilkey

Acknowledgements

Purdue University, West Layfayette, IN, USA Catherine Hill

Mississippi State University, Starkville, MS, USA Daniel G. Peterson

J. Craig Venter Institute/TIGR, Rockville, MD, USA Vish Nene

Appolinaire Djikeng

Shelby Bidwell

Lis Caler

Mathangi Thiagarajan

Linda Hannick

Vinita Joardar

Queensland Alliance for Ag. and Food Innovation, Brisbane, QLD, Australia Ala Lew-Tabor

Manuel Rodriguez Valle

Amplicon Express, Pullman, WA, USA Robert Bogden

Evan Hart

Suresh Iyer

Amy Mraz

Bandie Harrison

Travis Ruff

Molecular Research LP, Shallowater, TX, USA Scot E. Dowd