Transcript Slide 1

Identification of Molecular Markers to
Improve Fertility of Beef Cattle
(USDA-NRI 200835205-18751)
Milt Thomas, Department of Animal and Range Sciences
Outline
I. Molecular markers and research - background.
II. Fertility traits in beef cattle –background.
III.Evolution of a fertility project.
IV.Fertility project specifics.
A. Team of scientists.
B. Hypothesis and objectives (I and II).
C. Populations.
D. Additional efforts.
V. Questions.
Milt Thomas, Department of Animal and Range Sciences
Molecular Markers – Background
Important Definitions
Quantitative Trait Loci (QTL): chromosomal-locus associated with a quantitative trait.
Genetic Marker: unique DNA sequence passed from parent to progeny (molecular alleles).
Marker Assisted Selection (MAS): using genetic marker(s) in selection.
Marker Assisted Management (MAM): using genetic markers for management decisions.
bovineSNP50: a genotyping tool containing ~54,000 SNP across the bovine genome.
gEPD: genetic marker information used in EPD estimation.
Whole Genome Selection (WGS): using genetic markers across the genome in selection
Linkage disequilibrium: non-random association of alleles at 2 or more loci.
Milt Thomas, Department of Animal and Range Sciences
Molecular Markers – Background
Research approach: QTL Detection
http://www.animalgenome.org/QTLdb/cattle.html
Trait = pregnancy rate
Milt Thomas, Department of Animal and Range Sciences
Molecular Markers – Background
Research approach:
Fine mapping/resequencing of genes under a QTL
SOCS2 (15.4 Mb)
LCTN (16.2 Mb)
IGFBP6 (20.5 Mb)
STAT6 (32.5 Mb)
STAT2 (33.3 Mb)
Eth10
PMCH (37.7 Mb)
IGF1 (38 Mb)
DeAtley, K. L., G. Rincon, C. R. Farber, J. F. Medrano, R. M. Enns, G. A. Silver, and M. G.
Thomas. 2008. Association of microsatellite ETH10 genotypes with growth and carcass trait
levels in Brangus cattle. Proc. West. Sect. Am. Soc. Anim. Sci. 59:69-71.
Milt Thomas, Department of Animal and Range Sciences
Molecular Markers – Background
Research approach: identify important/functional markers
ANGUS
1993002
1/2 BRAH:
ANGUS
1/2 ANGUS
2002001
2002026
GG
BRAHMAN
2000128
AG
GG
ANGUS
Growth and carcass QTL on
Chromosome 20.
AA
Growth hormone receptor
gene underlies the QTL
3/4 BRAH:1/4 ANGUS
2004087
2004102
GG
AG
3/8 BRAH:5/8 ANGUS
2006047
Resequenced ~1,000 bp
flanking GT-SSR
Discovered A/G tag SNP
(ss86273136) segregating in
Brangus
GG
Garrett, A.J., G. Rincon, J.F. Medrano, M.A. Elzo, G.A. Silver, and M.G. Thomas. 2008. Promoter region of the bovine
growth hormone receptor gene: single nucleotide polymorphisms discovery in cattle and association with performance
in Brangus bull. J. Anim. Sci. published ahead of print: doi:10.2527/jas.2008-0990.
Milt Thomas, Department of Animal and Range Sciences
Molecular Markers – Background
Research approach: association of genotype:phenotype
Table 4. Least squares means among tag SNP ss86273136 genotypes in the GHR gene in Brangus bulls.
Genotypes
Pooled
SE
P>F
Item
AA
AG
GG
n
87
283
180
205-d weight, kg
271.85
267.44
273.39
4.37
0.2114
365-d weight, kg
510.34
500.00
499.14
6.07
0.1855
Test ADG, kg/d
1.57
1.52
1.51
0.04
0.1558
Scrotal circumference, cm
35.42
35.14
35.08
0.35
0.3525
Intramuscular fat, %
3.56
3.55
3.64
0.06
0.1202
LM area/BW, cm2/kg
0.17
0.17
0.17
0.002
0.8178
LM area, cm2
81.81
81.27
82.01
1.18
0.6062
Rib fat, cm
0.62
0.62
0.66
0.015
0.0204
+
Milt Thomas, Department of Animal and Range Sciences
Molecular Markers – Background
Validation:
Milt Thomas, Department of Animal and Range Sciences
Fertility traits – Background
Important Definitions:
Age at puberty: number of Julian days from birth until puberty is achieved (h2 ~0.4).
Age at first calving: number of Julian days from birth until first parturition (~24 mo).
Pregnant as a yearling: pregnant after yearling breeding season (h2 ~0.2; yes or no).
Calving interval: number of days between successive calvings.
Stayability: probability a cow will remain in the herd until six years of age.
Whole herd reporting: data inventory/recording system for each cow each year.
Milt Thomas, Department of Animal and Range Sciences
Fertility traits – Background
Important Information:
Reproduction has been described as the most economically relevant component in beef
production systems (Willham, 1973 and 1991; Melton, 1995).
National survey results suggest opportunities exist to improve calf survivability and
reproductive efficiency in many beef herds (Dargatz et al., 2004).
Genetic improvement programs for reproductive traits have been much slower to develop
than for growth and carcass traits due to the difficulty in developing whole-herd data
collection systems and the time required to ample data (personal experience with IBBA).
Genetic marker association studies involving fertility are limited as are the number of SNP
within dbSNP that are within functional regions of genes (current research program).
Milt Thomas, Department of Animal and Range Sciences
Evolution of a Fertility Project
NBCEC Large Herd Managers Symposium, KC -2005
Percentages of IGF-I genotypes for categorical reproductive trait
PTrait
CC CT TT χ2 value
First observed estrus
61.8 36.4 1.8 30.0 0.01
Estrus at synchronization
66.3 33.7 0
9.1 0.01
Pregnant during 1st breeding season 57.1 41.9 1.0 53.2 0.01
AI pregnancy
66.7 33.3 0
3.3 0.07
Calved by 2 yr of age
59.2 39.8 1.0 51.6 0.01
– Spring born Brangus (n = 190) heifers
– Born 1997 to 2002
– Progeny of 14 Brangus sires
Konni Shirley, Department of Animal and Range Sciences
Evolution of a Fertility Project
NBCEC Large Herd Managers Symposium, KC -2005
Initial Results from Rex Ranch Project Relative NMSU Angus Heifers
Genotypic Frequency, %
Herd
Pregnancy
Status
Number
of Heifers
CC
CT
TT
1
non-pregnant
160
15
49.4
35.6
1
pregnant
166
19.2
41.6
39.2
3
non-pregnant
75
20
44
36
3
pregnant
85
20
40
40
NMSU
Pregnancy
rate > 90%
110
10
51.8
38.2
Milt Thomas, Department of Animal and Range Sciences
Discussions at the Large Herd Managers helped form a
team of scientist with many industry and ag-experiment
cooperators.
Identification of Molecular Markers to Improve Fertility of Beef
Cattle; USDA-NRI 200835205-18751.
Milt Thomas, PD, New Mexico State University, Reproductive Physiology
Jim Reecy, Co-PD, Iowa State University, Molecular Genetics and Bioinformatics
Rohan Fernando, Co-PD, Iowa State University, Quantitative Genetics (QTL)
Bob Weaber, Supporting Scientist, University of Missouri, Quantitative Genetics
John Pollak, Supporting Scientist, Cornell University, Quantitative Genetics
Sunday Peters, Ph.D. student, New Mexico State University, Molecular Biology
(Associate Professor, Department of Animal Breeding and Genetics, University of
Agriculture, Abeokuta, Nigeria)
Milt Thomas, Department of Animal and Range Sciences
Long-term goal: understand in
molecular detail the genetic
pathways regulating reproductive
performance in beef cattle, with the
intent of using this information to
develop genetic improvement
programs for fertility.
QTL Detection
Fine Mapping
Validation of MAS
tools in commercial
herds across
environments and
production systems.
Technology Transfer
Milt Thomas, Department of Animal and Range Sciences
Identification of Molecular Markers to Improve
Fertility of Beef Cattle (USDA-NRI 200835205-18751)
Objectives
Objective 1: Conduct a SNP-based whole-genome scan to
identify QTL associated with heifer pregnancy rate.
Objective 2: Develop data and DNA resources from large
commercial beef operations to serve as test populations for
validation and technology transfer created by achieving
Objective 1 and other future candidate gene association
efforts.
Milt Thomas, Department of Animal and Range Sciences
Objective 1: Conduct a SNP-based whole-genome scan to identify QTL
associated with heifer pregnancy rate.
Use Brangus cattle as admixed populations
of livestock have proven useful in detecting QTL.
Relationship fostered from
efforts of IBBA –BIC.
Milt Thomas, Department of Animal and Range Sciences
Population for Objective 1: Registered Brangus heifers from Camp Cooley Ranch
1. Brangus heifer pregnancy records collected since 1993.
2. DNA and phenotypes on >800 heifers from 54 sires born 2005, 2006, 2007.
3. Brangus generation, 4.5 ± 0.04
4. Trait, pregnant as a yearling, yes (80.6%) or no (19.4%).
5. Pregnancy success appears similar among heifers born in the fall vs. spring
6. Good success rate with AI.
7. Simple statistics for growth and carcass traits:
Birth weight
77.2 ± 0.4 lbs
205-day weight
532.2 ± 2.2 lbs
365-day weight
799.0 ± 3.3 lbs
Ribeye area
9.8 ± 0.05 in2
Fat thickness
0.24 ± 0.002 in
intramuscular fat %
4.24 ± 0.032 %
100
80
Not Pregnant
Heifer
Pregnancy
Percent
Pregnant
70
80
Number
60
Spring
Fall
60
50
40
of Sires
40
30
20
10
20
0
0
03
20 1
0
20 9
9
19 7
9
19 5
9
19 3
9
19
03
20
01
20
99
19
97
19
95
19
93
19
Milt Thomas, Department of Animal and Range Sciences
Lab work and Statistical Analyses for Objective 1.
1. DNA extraction of WBC-buffy coat at NMSU.
2. bovineSNP50 genotyping (54,000 SNP across the genome).
3. QTL detection at ISU using a Bayesian approach (Meuwissen et al.,
2001 and XU, 2003).
4. QTL visualization: QTLdb
http://www.animalgenome.org/QTLdb/cattle.html
Trait = pregnancy rate
Milt Thomas, Department of Animal and Range Sciences
Objective 2: Develop data and DNA resources from large commercial beef
operations to serve as test populations for validation and technology
transfer created by achieving Objective 1 and other future candidate gene
association efforts.
1. Varied production systems and environments which
represent the beef industry in the U.S.
2. Obtain resources that could grow into additional trait
evaluations (1st calf heifer rebreeding, stayability, etc.)
Note: failure of the 1st-calf heifer to rebreed has been considered to be one
of the largest economic drains on the beef industry (Clark et al., 2005).
Milt Thomas, Department of Animal and Range Sciences
Locations of Cooperators (numbers 1-19) and Research Scientists (letters A-D) Working to Study:
Identification of Molecular Markers to Improve Fertility in Beef Cattle
7
C
8
16
5
14
18
12
9
B
4
D
19
11
A 1
13
15
10
3
172
6
Milt Thomas, Department of Animal and Range Sciences
Additional Efforts
1. Whole genome breeding value estimates
(collaboration with Dorian Garrick, ISU).
2. Transcriptome sequencing of important tissues (i.e., hypothalamus-NCGR)
and evaluate bovineSNP50 QTL-SNP relative gene expression loci.
Milt Thomas, Department of Animal and Range Sciences
Identification of Molecular Markers to Improve
Fertility of Beef Cattle
(USDA-NRI 200835205-18751)
1.Conclusions
2.Acknowledgements
3.Questions/Discussion
Milt Thomas, Department of Animal and Range Sciences