Brazilian Experience in Selection for Fertility in

Zebu Breeds including Incorporation of DNA

Marker Technology

USP, ANCP, EMBRAPA, ECOLOG, UFBA

Raysildo B. Lôbo, Cláudio Magnabosco, Luís G. G. Figueiredo, Daniel P. Lôbo,

Thereza C. Bittencourt

BEEF AUSTRALIA 2012

INTERNATIONAL BEEF CATTLE GENETICS CONFERENCE

Regions

• Brazil is divided into 5 major regions with 26 states:

• North (16.1 million people)

• Northeast (53.5 million people)

• Midwest (14.2 million people)

• Southeast (81.0 million people),

• South (27.6 million people)

Brazilian Population (2011)

192.4 million people

7 billion worldwide

3

Macuni do Salto

Birth date. Sept/2002 MGT = 13,55 (Top 2%)

HERD, SLAUGHTERING AND CARCASS WEIGHT OF

CATTLE IN BRAZIL

Brazilian Exports (US$ bilhões)

58.3 60.4 73.2

96.7

118.5

137.8

160.6

197.9

153.0

201.9

256.0

23.9 24.8 30.6

39.0 43.6 49.5

58.4 71.8

64.8 76.4

95.0

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

HISTORICAL EVOLUTION

Total Exports

Total Agribusiness

The Genetics of Beef Cattle Reproduction

Reproductive performance and longevity

are economically relevant traits that

determine the number of beef cattle

available each year as replacements and

for slaughter in beef cattle production.

The beef cattle industry is considered to

be one of the most important economic

activities in Brazilian agribusiness and

Zebu breeds; the Nelore is the most

important beef cattle breed in Brazil.

In this presentation, we will be stressing

on our results of fertility selection in zebu

breeds, and make application on how to

integrate of genomic information into

genetic evaluation of Brazilian Nellore

cattle.

Fertility is a complex trait in beef

production systems and genetic

evaluation procedures.

The ANCP has initiated a

program of selection for sexual

precocity in females, challenging

heifers from 14 to 17 months old in

the Nellore breed.

Results of the program of sexual precocity in Rancho da

Matinha, ANCP Associate.

Birth Year Number

Exposed

Number

Pregnant % Pregnancy

1998 77 6 7.79

1999 122 1 0.82

2000 122 16 13.11

2001 142 27 19.01

2002 159 86 54,09

2003 159 77 48,43

2004 149 77 51,68

2005 162 57 35,19

2006 113 81 71,68

2007 151 110 72,85

2008 141 103 73,05

2009 166 124 74,70

2010 177 138 77,97

Source: Rancho da Matinha, 2012

Rancho da Matinha

Mandarin FIV Matinha

Birth date.: Oct/2008

Maia FIV Matinha

Birth date: Sept/2008

12

Genetic Trends (mo) in Nellore Cattle for AFC

-0.48

-0.52

-0.57

-0.62 -0.61

-0.66

-0.74

-0.80

-0.70

-0.60

-0.50

-0.40

2001 2002 2003 2004 2005 2006 2007

IPP

(m

es

es

)

Source: ANCP/CTAG, 2012

Genetic Trends in Nellore Cattle for Heifer

Pregnancy Rate (%)

47.93

47.98

48.16

48.27 48.27

48.18

48.32

47.90

47.95

48.00

48.05

48.10

48.15

48.20

48.25

48.30

48.35

2001 2002 2003 2004 2005 2006 2007

D3P

(%

)

Source: ANCP/CTAG, 2012

Genetic Trends in Nellore Cattle for Stayability (%)

52.53

52.72

52.87

52.84

53.16

53.53

53.75

52.40

52.80

53.20

53.60

54.00

2003 2004 2005 2006 2007 2008 2009

STA

Y (

%)

Source: ANCP/CTAG, 2012

Genetic Trends (cm) in Nellore Cattle SC365

-0.02

0.00

0.03 0.02

0.07

0.13

0.17

-0.05

0.00

0.05

0.10

0.15

0.20

2003 2004 2005 2006 2007 2008 2009

PE

36

5 (

cm

)

Source: ANCP/CTAG, 2012

Implementation of DNA Markers to

Produce Genomic EPDs

• One way to implement the genomic information into

genetic improvement programs is to simply integrate

the genomic predictions into traditional genetic

evaluation.

• This approach combines traditional EBVs based on

phenotype and pedigree with the genomic breeding

values based on the markers.

Implementation of DNA Markers to Produce Genomic

EPDs

• The Nellore Genetic Evaluation of the Brazilian

Association of Farmers and Researchers (ANCP)

published last year (2011) enhanced EPDs for growth

and reproduction traits.

• The molecular markers (Clarifide® - Pfizer) were

analyzed as a correlated trait.

• Last April (2012) we launched for Nellore Brazil Program the genetic

evaluation for 1.1 million animals with Enhanced Genomic EPDs.

(EBV:2)

• We analyzed 12 (twelve) traits:

Analysis of Nellore Data

Age at first calving (AFC);

Heifer pregnancy rate (HPR);

Stayability (STAY);

Accumulated production (CAP);

120-day weight (WT120);

Weights at 365/450 days (WT365/450);

Scrotal circumference at 365/450 days (SC365/450);

Rib eye area (REA);

Fat Thickness (FAT).

Statistical Analysis

The data were analyzed using two animal

models: a traditional single trait model, and a

three-traits model where the Pfizer molecular

value was included as a correlated trait.

All mixed model analysis were performed using

the statistical software ASREML 3.0, and SELMA

(CTAG, 2011).

In the next figures are illustrated the benefits of

including the Pfizer MVP into actual accuracy.

The green portion of the bars shows the accuracy

before the inclusion of genomic markers and the

blue shows the increase in accuracy after the

inclusion of the MVP.

Nellore Cattle

145.00% 80.00%

49.00%

28.00%

16.00%

11.00%

4.00%

1.00%

0.00%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.11 A 0.20 0.21 A 0.30 0.31 A 0.40 0.41 A 0.50 0.51 A 0.60 0.61 A 0.70 0.71 A 0.80 0.81 A 0.90 0.91 A 0.99

A

c

c

u

r

a

c

y

Accuracy Class

AGE AT FIRST CALVING ACTUAL ACCURACY

Nellore Cattle

102.00%

49.00%

29.00%

16.00%

9.00%

5.00%

2.00%

1.00%

0.00%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.11 A 0.20 0.21 A 0.30 0.31 A 0.40 0.41 A 0.50 0.51 A 0.60 0.61 A 0.70 0.71 A 0.80 0.81 A 0.90 0.91 A 0.99

A

c

c

u

r

a

c

y

Accuracy Class

HEIFER PREGNANCY RATE ACTUAL ACCURACY

Nellore Cattle

83.00%

40.00%

23.00%

11.00%

6.00%

3.00%

2.00%

0.00%

0.00%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.11 A 0.20 0.21 A 0.30 0.31 A 0.40 0.41 A 0.50 0.51 A 0.60 0.61 A 0.70 0.71 A 0.80 0.81 A 0.90 0.91 A 0.99

A

c

c

u

r

a

c

y

Accuracy Class

YEARLING SCROTAL CIRCUMFERENCE (ACTUAL ACC)

Nellore Cattle

137.00%

67.00%

35.00%

23.00%

12.00%

8.00%

3.00%

1.00%

0.00%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.11 A 0.20 0.21 A 0.30 0.31 A 0.40 0.41 A 0.50 0.51 A 0.60 0.61 A 0.70 0.71 A 0.80 0.81 A 0.90 0.91 A 0.99

A

c

c

u

r

a

c

y

Accuracy Class

STAYABILITY (ACTUAL ACC)

The early graphs show that animals

with lower accuracy have more benefit

with the inclusion of genomic markers. On

the other hand, the benefits decline as the

actual accuracy increases. The benefits

dissipate for actual accuracy great than

0.5.

TRAITS h2 r

Change in

ACCBIF

(from 0.08*)

Approx.

Progeny

Equivalents

AFC 0.11 0.40 0.15 14

HPR 0.24 0.32 0.07 6

SC365 0.38 0.28 0.12 3

STAY 0.12 0.38 0.11 9

CAP 0.20 0.27 0.11 10

* These changes are less for higher initial accuracy values; h2 =

Heritability; r = Genetic correlation estimates between target trait

and respective MVPs.

Change in BIF accuracy (ACCBIF) from the incorporation of Pfizer MVP into young sires with no

other phenotypic information (i.e. parent-average EPDs; ACCBIF = 0.08), and average number of

progeny records (Approx. progeny equivalents) it would require to obtain a similar ACCBIF increase

based on progeny test records.

Traits h2 r(%) Vg(%)

Age at First Calving 0.11 40 16

Heifer Pregnancy Rate 0.24 32 10

Scrotal Circumference at 365 days 0.38 28 8

Stayability 0.12 38 14

Accumulated production 0.20 27 7

aNellore breed; h2 Heritability; r=Genetic correlation estimates

between target trait and MVPs; Vg = Portion of genetic variance

explained by MVP.

Genetic correlations among Pfizer MVP and

reproductive traits a

Source: ANCP & Pfizer (2012)

Conclusions

Results showed that the incorporation of

molecular markers information into genetic

evaluation resulted in increased accuracy of

young sires as compared to the accuracy of

traditional genetic evaluation.

Conclusions

The effect of the inclusion of genomic markers

decline as the actual accuracy increases in Nellore

breed.

The benefits of including genomic information

dissipate when accuracy is over 0.5 for most traits

studied.

GE-EPD will be an effective tool to enable faster

genetic improvement of fertility and growth traits in

Nellore cattle in Brazil.

Thank you so much!