introductiondairy.ifas.ufl.edu/dpc/2015/maltecca.pdfmodiﬁed from de vries and salfer 2014...

How to implement genomic selection for sires and replacement heifers in your herd

Christian Maltecca North Carolina State University

April 29, 2015. Florida Dairy Production Conference

Christian Maltecca NCSU

Introduction


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From the beginning: Selection

J.B.Cole 2014


Genomic Selection: Key Points

∆Gyear = Acc. x

Int. Gen.Varadd Gen.Int.

∆Gyear = genetic progress in a year

Acc. = measures certainty of an individual’s breeding values (

with GS)

Int. = measures how restrictive we are in choosing individuals as

parents ( through management)

Gen.Var =genetic variance in the population (= constant over a

short time period)

gen. int. = time in between two generations ( with GS)


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Decrease in generation interval increase in accuracy with GS Decrease in Generation interval of up to 3 times

(Pryce et al, 2012) From ~6 to ~2 years Increase in Accuracy

Gain in accuracy of 28-108% with GS (Pryce et al, 2012)


Decrease in generation interval increase in accuracy with GS


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Pathways of selection


Increase in the number of genotyped animals

J.B.Cole 2014


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Heifers Genotyping Advantages of genotyping females: Decrease of Generation Interval Increase in Accuracy (Mc Hugh, et al. 2011)

Maximizing Female Genotyping return for the farmer

Increase economic advantage at the farm by priorityzing heifer for replacement Potential gains in lifetime net merit from genomic testing of cows, heifers, and calves

on commercial dairy farms. Weigel, et al. 2012. A review of how dairy farmers can use and profit from genomic technologies. Pryce,

and Hayes. 2012.


Heifers Genotyping Generally at low density (3k or 6k)

Prior only high merit individuals

Producers are now testing heifers with unknow parents With reduction of genotyping costs this will become common


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Heifers Genotyping Flush for commercialization Flush within herd Insemination with sexed semen Insemination beef cross Culling


Heifers Genotyping Return on investment in genotyping heifers depends on several factors: Cost of genotyping

Economic value of a unit SD of breeding goal (NM?) Increased accuracy of GS vs. PA Replacement % Number of Heifers available for replacement

Sexed Semen


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An Example


A typical Scenario


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A typical Scenario


A typical Scenario


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A typical Scenario


Selecting a Replacement

Strategy


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Multiple options Cull at 2 mo. or cull as yearlings

Genotype bottom 50% keep top 90% Genotype top 50%, select top 10-30% Genotype all, sell bottom 10-30% ...


Mating Options

Weigel et. al 2012


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Mating Options

Weigel et. al 2012


A typical Scenario

Weigel et. al 2012


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Heifers Genotyping Culling Flush for commercialization Flush within herd Insemination with sexed semen Insemination beef cross


Sexed Semen

Modified from De Vries and Salfer 2014 Christian Maltecca NCSU

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Sexed Semen and Beef Crosses

Modified from De Vries and Salfer 2014


Impact of reproductive technologies on genetic progess Today Heifers genotyping Genotyping and sexed semen Tomorrow ET OPU Embryo sequencing


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Heifers genotyping Accuracy +

increase reference population

Intensity +/-

+ increase pre-screended

reduction selected

Genetic variation -

limited number of blooklines increased inbreeding

Heritability +

GS new traits

Generation interval +

increased turnover Ponsart et al 2014


Genotyping and sexed semen Accuracy +++

increase reference population

Intensity +

+ increase pre-screened

Genetic Variation ++

with use of genomic mating plans

Heritability +

GS for female traits (fertility)

Generation Interval +

faster identification elite cows Ponsart et al 2014


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Mating Design Mating designs have received little attention. Mating optimization can be worthwhile and choosing appropriate

designs can increase long-term genetic gain (Caballero et al., 1996;

Sonesson and Meuwissen, 2000) As an added benefit most mating designs can be implemented without extra costs or logistical constraints.

Mating plans have important consequences for the long-term genetic variability

reducing inbreeding expression at the herd level

minimizing the variation in the accuracy between selection candidates by increasing the connectedness of the information gathered.


Mating Design

Modified from Sun and VanRaden 2014


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Mating Design

Modified from Sun and VanRaden 2014


Sires Use


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Sires Use Sires use largely depends on # cows in the herd Assume a 100 cows herd choose 5 first crop proven bulls

For the same team “genomic” reliability more young bulls needed 1 (1 rel)/n rel = reliability

n = number bull in the group Pryce and Hayes 2012


Sires Use ~ 10 genomic tested sires with 60% rel Collective reliability of 5 first crop sires with rel ~80%

A safer strategy perhaps chosing a mix of proven and genomic tested young bulls eventually progeny testing phased out need for larger genomic young

groups sequence data could make young bulls more reliable faster Spreading the risk on a larger group of individuals


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Conclusions Sire implementation of GS at the herd level is advantageous and relatively simple

Semen from large groups of young genomic tested sires grants higher

rates of genetic gain

Benefit of genotyping females depends on several factors yet

combination of:

mating plans (reduction of inbreeding)

reproduction technologies (sexed semen) lethal recessives management parentage testing - Make heifer genotyping worthwile

In the future low cost will make it a no brainer

Under current scenarios genotyping strategies still needs to be evaluated


Thank you


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introductiondairy.ifas.ufl.edu/dpc/2015/maltecca.pdfmodiﬁed from de vries and salfer 2014...

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