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SNP Based Parentage Assignment in Sheep: Application in Australian Flocks
PART 2: James Kijas 1, Julius van der Werf 6,7, Mohammad Ferdosi 6,7, Amy Bell 1,6, Sam Gill 6,8, Klint Gore 6, Jill Maddox 3 and John Henshall1,6.
1 CSIRO Livestock Industries, Australia. 2 AgResearch, New Zealand. 3 Port Melbourne, Australia. 4 USDA, USA. ,
PART 1: James Kijas 1, John McEwan 2, Shannon Clarke 2, Hannah Henry 2, Jill Maddox 3, Mike Heaton 4, for the International Sheep Genomics Consortium 5
CSIRO Livestock Industries, Australia. AgResearch, New Zealand. Port Melbourne, Australia. USDA, USA. ,Australia. 5 www.sheephapmpa.org. 6 Sheep Cooperative Research Center, Australia. 7 University of New England,Australia. 8 Meat Livestock Australia.
? ? ?
Background and Aims
Current Industry Practises:
1. Syndicate matings- no information about paternity in large management groups- inability to track sire merit through progeny performance
2. Single Sire matings- requires dedicated infrastructure (eg fences)
3. Mothering up to construct dam pedigree- labour intensive (costly)- not that accurate
Aims for development of a SNP Panel for Parentage:
1. Develop a Core Panel of SNP with international application- robust on multiple genotyping platforms- high MAF across many sheep breeds- promote to ISAG
2. Trial a panel of Core + Performance SNP within Australian flocks- test needs to be $10 / animal to drive industry adoption- high exclusion in populations with high relatedness (sires and ewe base)
Outline
PART 1: Technical Development of a Core Panel of SNP
PART 2: Trialling a Core + Performance Panel of SNP within Australian Flocks
International Sheep Genomics Consortium
History of developing tools for the sheep genome
- reference genome assembly (now v3.0 !)- SNP50 BeadChip- HD SNP by January 2013
1. Core Panel
6021 SNP Identified by
Sanger Sequencing
GoldenGate Infinium
1536 SNP chip
22 breeds
2009
PLoS ONE 4:e4668
50K SNP chip
70+ breeds
2012
PLoS Biology 10:e1001258
Golden Gate and
Infinium testing
across populations
Prune on MAF, call
rate and position
Formatted for genotyping
Prune on inheritance
in IMF and trios
ISGC panel of 88 SNP
+ male specific oY1 SNP
6021 SNP Identified by
Sanger Sequencing40.0
50.0
60.0
Pro
po
rtio
n o
f S
NP
(%
)
International Sheep Genomics Consortium
History of developing tools for the sheep genome
- reference genome assembly (now v3.0 !)- SNP50 BeadChip
1. Core Panel
Golden Gate and
Infinium testing
across populations
Prune on MAF, call
rate and position
Formatted for genotyping
Prune on inheritance
in IMF and trios
ISGC panel of 88 SNP
+ male specific oY1 SNP
0.0
10.0
20.0
30.0
40.0
0 > 0.0 - < 0.1 ≥ 0.1 - < 0.2 ≥ 0.2 - < 0.3 ≥ 0.3 - < 0.4 ≥ 0.4 - < 0.5P
rop
ort
ion
of
SN
P (
%)
Minor Allele Frequency Bin
MAF Calculated across global collection of 74 breeds
MAF distributions for all 49034 SNP (red)
and the 89 SNP in the parentage panel (green)
Designed to work across diverse range of breeds
ISGC Parentage SNP Chr Mb Allele MAF Filter 1 Filter 2 Filter 3 Filter 4 5k Chip
Pos Re-seq Fluidigm SQ_AgR SQ_CLI
DU290101_408.1 1 7.8 A 0.337
DU518561_359.1 1 14.2 G 0.381
DU351298_316.1 1 69.6 A 0.445
DU232924_365.1 1 95.8 G 0.250
DU271929_382.1 1 97.5 A 0.483
DU502334_443.1 2 19.1 A 0.437
DU469454_586.1 2 26.2 G 0.394
DU425907_184.1 2 50.1 G 0.358
DU501115_497.1 2 62.8 A 0.239
DU492516_411.1 2 63.4 T 0.478
DU470875_383.1 2 91.5 G 0.357
1. Core Panel
Filter 1: Re-sequencingLoci Sanger re-sequenced
to examine sequence context.
(Mike Heaton USDA)
Filter 2: Fluidigm TestingGenotyping accuracy tested
using GT.96.96 format.
(Katica Ilic, Fluidigm)
Filter 3: Sequenom TestingDU470875_383.1 2 91.5 G 0.357
250506CS_*1 2 100.9 G 0.345
DU191879_495.1 2 157.6 A 0.335
DU480434_533.1 2 192.2 A 0.480
DU260201_585.1 2 226.7 A 0.422
DU503161_123.1 2 237.2 A 0.352
DU425259_620.1 3 21.4 A 0.461
DU231007_156.1 3 59.0 G 0.463
DU225323_218.1 3 91.0 A 0.467
DU260081_579.1 3 108.8 A 0.383
DU394537_289.1 3 181.6 G 0.371
CL635241_413.1 3 181.9 A 0.455
DU408817_431.1 3 205.0 A 0.343
DU202116_405.1 4 58.2 A 0.444
DU460511_423.1 4 61.1 G 0.443
DU305004_417.1 4 70.1 A 0.270
DU369175_467.1 4 73.0 G 0.375
DU446213_412.1 5 12.5 A 0.394
Filter 3: Sequenom TestingSNP formatted into SQ
multiplexes and tested
across pedigrees.
(JMcW, SC at AgResearch)
Filter 4: Sequenom TestingSNP formatted into SQ
multiplexes and tested
across pedigrees.
(JK, FD at MLA and CSIRO)
5K ChipMembership on 5K ILMN
Array
1. Core Panel: Accreditation Through ISAG
We (International Sheep Genomics Consortium) would like to propose:
1. That ISAG consider adopting the panel of 89 SNP as the standard for sheep
2. That ISAG hold a panel of DNA samples from multiple breeds (n = 96) with known genotype
3. Provide accreditation to interested providers of genotyping services
Test DNA
Test Genotypes
Accreditation
Discuss this afternoon
et al.,
Outline
1. Technical Development of the Core Panel of SNP
Recognise 89 SNP is unlikely to be sufficient for many applications. The model therefore likely to involve addition of ‘country specific’ SNP content
- Europeans interested in PNRP- Europeans interested in PNRP- Locally (Oz): Horn / Poll; pigmentation, muscularity etc
2. Trialling a Core + Performance Panel within Australian Flocks
2. Trialling a Core + Performance Panel within Australian Flocks
Sequenom Testing (CSIRO, MLA, Sequenom Brisbane)
- key methodology given price structure for delivery- mature technology imbedded in companies like GeneSeek
Designed 6 multiplexes containing 383 SNP (between 63 – 67 SNP / plex)
- 89 Core SNP- Performance SNP including:
� horn / poll � horn / poll � myostatin� hoof pigmentation
- Additional ‘filler’ SNP to make up the number of 383
Collected samples from 1600 animals (blood cards)
- 5 industry flocks (progeny, ewes, sires)
- mainly Merino
Genotyped using all 6 SQ plexs: assessed power
Defined assignment thresholds using simulation
- 1000 simulated lambs, each with one correct sire- LOD is the log of ratio (likelihood correct/incorrect)- the most likely sire given mLOD1(blue if correct, red if wrong)
- difference between mLOD1 and the next best sire is ∆1
- second most likely sire given mLOD2 (light blue)
2 SQ plexes
127 SNP (64 core)
Sires with high mLOD and Δ1
These all correct (no red dots)
2 SQ plexes
127 SNP (64 core)
Most likely sire is correct sire, however
the next best is very nearly as likely (low Δ)
The next best sire (light blue) would get
selected as the true sire in some cases
3 SQ plexes
190 SNP (84 core)Using 3 plexes makes big difference !
The next best sire (light blue) is never
selected as the true sire using the
defined threshold
Very high confidence for analysis
of the real data
Progeny that are unlikely to have
a sire in the group genotyped.
Producer confirmed this was possible
Most assignments made
where next best sire
is not very likely (Δ well
above threshold)
Simulated Data Real Data
Conclusions
1. Technical Development of the Core Panel of SNP
- identified technically robust SNP- suitable for use across sheep breeds- promoting the core panel to ISAG for accreditation
2. Trialling a Core + Performance Panel within Australian Flocks
- in our flocks, 190 SNP gives good confidence in assignment- expect to release a commercial test in 2013
Acknowledgements
Core Panel
John McEwanShannon ClarkeHannah HenryJill MaddoxMike HeatonThe International Sheep Genomics Consortium
Testing in Australian Flocks
Julius van der WerfDaniel Pomp and JeremyMohammad FerdosiAmy BellSam GillKlint GoreJill Maddox and John Henshall