PRESENTED BY:

Kush Shrivastava

PRESENTED BY:

Kush Shrivastava

CONCEPT OF GENOMIC SELECTION:

A NEW BREEDING PARADIGM

Traditional breeding methods have been quite successful so far, without the knowledge of the genes acting on quantitative traits.Traditional breeding methods have been quite successful so far, without the knowledge of the genes acting on quantitative traits.

Breeders have enhanced production traits in their herds by selecting superior individuals as progenitors for the next generations.Breeders have enhanced production traits in their herds by selecting superior individuals as progenitors for the next generations.

Conventional selection – based on individual records, pedigree Conventional selection – based on individual records, pedigree or progeny performance or family performance.or progeny performance or family performance.

BREEDING VALUE

GENES ?

DNA DNA MarkersMarkers

Direct Genetic Marker

GENES

MARKER

A B

MARKERS

GENES

Indirect Genetic Marker

Phenotype

Estimated Breeding Value

Selection

Molecular Genetic MarkersEnvironment

Individual observatio

n

Information from

relatives

Genes

QTL

Requires prior knowledge of gene alleles or Requires prior knowledge of gene alleles or

markers that are associated with the traits markers that are associated with the traits

of interest.of interest.

Explains only a limited part of the genetic Explains only a limited part of the genetic

differences between individuals.differences between individuals.

Require families !Require families !

Whole genome SNPs are available for major Whole genome SNPs are available for major

livestock species.livestock species.

Whole genome genetic markers Whole genome genetic markers

Segregation of entire genome (and not merely Segregation of entire genome (and not merely

a set of specific regions of interest) can be a set of specific regions of interest) can be

followed.followed.

Paternal relationships not required !Paternal relationships not required !

MARKERS

Genomic selection was first described by Genomic selection was first described by

Meuwissen Meuwissen et alet al. (2001). (2001)..

Large number of SNPs are required.Large number of SNPs are required.

Distributed throughout the genome.Distributed throughout the genome.

Some might be close to region of interest.Some might be close to region of interest.

Can be used to explain variation in trait(s).Can be used to explain variation in trait(s).

Select on the basis of SNP effects of entire Select on the basis of SNP effects of entire

genome.genome.

(Eggen, 2012)(Eggen, 2012)

REFERENCE POPULATIONREFERENCE POPULATION

GENOTYPING

GENOTYPING

(Hayes (Hayes et alet al., 2009, 2013)., 2009, 2013)

PHENOTYPING

PHENOTYPING

PREDICTION EQUATION BASED ON SNP

PREDICTION EQUATION BASED ON SNP

W1X1 + W2X2 + W3X3 + W4X4…..

W1X1 + W2X2 + W3X3 + W4X4…..MOST OF THE GENETIC VARIATION

IN CAPTUREDMOST OF THE GENETIC VARIATION

IN CAPTURED

SELECTION ON CANDIDATES BASED ON GEBV ONLY

SELECTION ON CANDIDATES BASED ON GEBV ONLY

SUBSEQUENT GENERATIONS

Case I: MAS – consider a single SNP marker with Case I: MAS – consider a single SNP marker with

allele A & B allele A & B

Allele A: +4 AND Allele B: - 4Allele A: +4 AND Allele B: - 4

Animal no. Marker (SNP) allele

Value MAS- EBV

1 AA +8 +8

2 AB 0 0

3 BB - 8 - 8

Case II: Genomic selection - Consider 4 SNPs ; allele A vs. Case II: Genomic selection - Consider 4 SNPs ; allele A vs.

BB

SNP 1 – Allele A: +4 AND Allele B: -4SNP 1 – Allele A: +4 AND Allele B: -4

SNP 2 – Allele A: +2 AND Allele B: -2SNP 2 – Allele A: +2 AND Allele B: -2

SNP 3 – Allele A: +1 AND Allele B: -1SNP 3 – Allele A: +1 AND Allele B: -1

SNP 4 – Allele A: -3 AND Allele B: +3SNP 4 – Allele A: -3 AND Allele B: +3

(Eggen, 2012)

Genomic selection builds on existing Genomic selection builds on existing

breeding programs.breeding programs.

Better selection accuracy while reducing Better selection accuracy while reducing

the generation interval.the generation interval.

In cattle, more than 15 countries are now In cattle, more than 15 countries are now

using genomic breeding values.using genomic breeding values.

Schaeffer (2006)Schaeffer (2006) showed that using genomic selection, the showed that using genomic selection, the

genetic gain per year could be doubled in dairy cattle.genetic gain per year could be doubled in dairy cattle.

Fig. Timeline of a traditional artificial insemination breeding program based on progeny Fig. Timeline of a traditional artificial insemination breeding program based on progeny testing. EBV = estimated breeding value.testing. EBV = estimated breeding value.

0 yrs0 yrs

Bull A is born and is

selected based on

EBV

Bull A is born and is

selected based on

EBV

1 yrs 3mo1 yrs 3mo

Bull A is put to

progeny testing

Bull A is put to

progeny testing

2 yr2 yr

Progeny of Bull A is

born

Progeny of Bull A is

born

4 yr4 yr

Progeny of Bull A calves

Progeny of Bull A calves

4 yr 6 mo

4 yr 6 mo

Milk production

data of progeny of

Bull A become

available.

Milk production

data of progeny of

Bull A become

available.

EBV of bull A is estimated using progeny performance & can be

used as sire

EBV of bull A is estimated using progeny performance & can be

used as sire

5 yr 3 mo

5 yr 3 mo

Sons of Bull A are

born

Sons of Bull A are

born

Generation Interval = 63monthsGeneration Interval = 63months

(Schefers and Weigel, 2012)

Fig. Timeline of an aggressive artificial insemination breeding program based on the use of Fig. Timeline of an aggressive artificial insemination breeding program based on the use of genomic bulls as sires of sons. GEBV = genomic estimated breeding value; EBV = estimated genomic bulls as sires of sons. GEBV = genomic estimated breeding value; EBV = estimated breeding value.breeding value.

0 yrs0 yrs

Bull B is born &

selected on basis on

GEBV

Bull B is born &

selected on basis on

GEBV

1 yrs1 yrs

Bull B reaches sexual

maturity & can be used as

sire

Bull B reaches sexual

maturity & can be used as

sire

1 yr 9 mo

1 yr 9 mo

Progeny of Bull B is

born

Progeny of Bull B is

born

2 yr 9 mo

2 yr 9 mo

Progeny of Bull B

reaches sexual

maturity and can be

used as sire of sons.

Progeny of Bull B

reaches sexual

maturity and can be

used as sire of sons.

3 yr 6 mo

3 yr 6 mo

Grandson of Bull B are born

Grandson of Bull B are born

Grandson of Bull B reaches sexual maturity and can be used as sire of

sons

Grandson of Bull B reaches sexual maturity and can be used as sire of

sons

4 yr 6 mo

4 yr 6 mo

Milk production data from progeny of bull B are available

for calculation

of EBV

Milk production data from progeny of bull B are available

for calculation

of EBV

Generation Interval = 21 months

Generation Interval = 21 months

(Schefers and Weigel, 2012)

5 yr 3 mo

5 yr 3 mo

Great grandson of Bull B are born

Great grandson of Bull B are born

Started since 2008 in Started since 2008 in United States, Canada, New United States, Canada, New

Zealand, France, Netherlands.Zealand, France, Netherlands.

Genomic predictions values were more accurate Genomic predictions values were more accurate

than traditional pedigree index, specially for low than traditional pedigree index, specially for low

for low heritability traitsfor low heritability traits

Reduction of breeding bulls due to higher Reduction of breeding bulls due to higher

selection intensity in NZ. selection intensity in NZ.

(Van Raden et al. 2009)

(Spelman et al. 2010)

Genomic selection has not yet been implemented Genomic selection has not yet been implemented

in small ruminants.in small ruminants.

Pilot genomic evaluations have been implemented Pilot genomic evaluations have been implemented

in New Zealand.in New Zealand.

SNP chip still not available for goats.SNP chip still not available for goats.

However, due to limitation in current data However, due to limitation in current data

recording schemes - GS might produce inferior recording schemes - GS might produce inferior

results.results. (Van der Werf, 2009)

Pig breeding – Still under research & experimentation.Pig breeding – Still under research & experimentation.

SNP chips for pig is available.SNP chips for pig is available.

GI is low in pigs, therefore, to increase response, GS will be GI is low in pigs, therefore, to increase response, GS will be

effective for traits with low accuracy of selection (e.g., low effective for traits with low accuracy of selection (e.g., low

heritable traits, slaughter traits etc.)heritable traits, slaughter traits etc.)

Population size for low heritable traits – Approx. 10 times larger. Population size for low heritable traits – Approx. 10 times larger.

Increase of 68% in accuracy of the breeding values of the Increase of 68% in accuracy of the breeding values of the

experimental population over traditional selection.experimental population over traditional selection.

(Ibañez-Escriche and Gonzalez-Recio., 2011)

(Goddard, 2009)

(Forni et al. 2010)

(Ibañez-Escriche and Gonzalez-Recio., 2011)

Sequenced genome available in 2004.Sequenced genome available in 2004.

Three SNP panels of sizes 6, 12 and 42 K are Three SNP panels of sizes 6, 12 and 42 K are

available.available.

Experimental GS results are available.Experimental GS results are available.

Why should commercial breeder takes up GS ?Why should commercial breeder takes up GS ?

Cost effectiveness yet to be verified !Cost effectiveness yet to be verified !

(Hiller et al., 2004)

(Long et al. 2007; González-Recio et al. 2008 ,2009)

(Ibañez-Escriche and Gonzalez-Recio., 2011)

Sequencing data of almost all important livestock Sequencing data of almost all important livestock

species is available.species is available.

(Fan et al., 2010; Eggen, 2012)

1HD = High Density; LD = Low Density

2 Illumina Inc., San Diego, CA; Affymetrix, Santa Clara, CA.

(Eggen, 2012)

??Low Density = Low Cost;

lesser genome coverage

High Density = More Cost;

more genome coverage

Habier Habier et al.et al. (2009) (2009) and and Weigel Weigel et alet al. (2009; 2010) . (2009; 2010)

confirmed small losses in accuracy on the genomic confirmed small losses in accuracy on the genomic

predictions on using LD chips.predictions on using LD chips.

Strategy I - Strategy I - Weigel Weigel et alet al. (2009). (2009), select only based on , select only based on

SNPs that show strong association thus might be SNPs that show strong association thus might be

neglecting small effects.neglecting small effects.

2242

SNP

60000

SNPTrait

Goddard and Hayes (2008)Goddard and Hayes (2008) : Ancestors are genotyped with dense : Ancestors are genotyped with dense

panels and the selection candidates are genotyped with standard panels and the selection candidates are genotyped with standard

low-density panelslow-density panels

But it require pedigree, not a big deal for dairy cattle in developed But it require pedigree, not a big deal for dairy cattle in developed

nations.nations.

Success depends on 2 factors Success depends on 2 factors (Goddard, 2009)(Goddard, 2009): :

Size of the founder population

Size of the founder population

Choice of the ancestor

Choice of the ancestor

11 22 33 44

Reference populationReference population

700000 SNPs

700000 SNPs

2000 SNPs2000 SNPs

(Weigel et al., 2010)

High Density SNP map

High Density SNP map

Weigel Weigel et al.et al., (2010) – Utilizing genomic information from ancestor or relatives, , (2010) – Utilizing genomic information from ancestor or relatives,

there is only 4 % reduction in estimated breeding value by using LD chips as there is only 4 % reduction in estimated breeding value by using LD chips as

compared to HD chips.compared to HD chips.

Re- estimation of GEBV (after approx.7 generation) by using current population

as reference

Re- estimation of GEBV (after approx.7 generation) by using current population

as reference

Planned mating – Based on genetic relationshipPlanned mating – Based on genetic relationship

(Buch et al. 2012 )

High density SNP chips – Up to 7 lakh SNPsHigh density SNP chips – Up to 7 lakh SNPs

Whole genome sequencing & re- sequencing.Whole genome sequencing & re- sequencing.

Sequence based selectionSequence based selection

Inclusion of sequence dataInclusion of sequence data

40 % gain in accuracy of predicted breeding value40 % gain in accuracy of predicted breeding value

(Meuwissen and Goddard, 2010)

Accuracy maintained up to 10 generations

Accuracy maintained up to 10 generations

Livestock have large numbers of symbionts, Livestock have large numbers of symbionts,

(bacteria and protozoa) in digestive tract.(bacteria and protozoa) in digestive tract.

Affect some key traits – feed conversion efficiency.Affect some key traits – feed conversion efficiency.

Rumen microbiome profile is important – methane Rumen microbiome profile is important – methane

production.production.

Beef cattle – more methane production.Beef cattle – more methane production.

Emission depends upon type of ruminal microbes Emission depends upon type of ruminal microbes (Johnson and Johnson, 1995)

Microbes carried by an animal depend on features of the Microbes carried by an animal depend on features of the

animal (to some extent).animal (to some extent).

Can be regarded as part of the phenotype of the animal and Can be regarded as part of the phenotype of the animal and

subject to genetic variation.subject to genetic variation.

Bensen Bensen et alet al., 2010; Identified QTL in mice affecting gut ., 2010; Identified QTL in mice affecting gut

mircoflora.mircoflora.

Selection of cattle for “desirable” gut microflora.Selection of cattle for “desirable” gut microflora.Look for genome wide SNPs that favour the desirable gut ecosystemLook for genome wide SNPs that favour the desirable gut ecosystem

Manipulation of microbes be external effects (like feed etc.)Manipulation of microbes be external effects (like feed etc.)

(Hayes et al., 2013)

Treated genome as a “Black Box”Treated genome as a “Black Box”

Not necessary to know what's Not necessary to know what's

INSIDE it.INSIDE it.

No “credit” for function of individual No “credit” for function of individual

gene.gene.GENES !!GENES !!

Phenotype

E

Markers

Function of each gene(& the variation within)

Understanding of the biology of the animal that makes phenotypic variations significant

OP

EN

I

T

OP

EN

I

T

(Eggen, 2012)

Limited by the absence of programs that record phenotypes on Limited by the absence of programs that record phenotypes on

pedigreed animals pedigreed animals

lack of evaluation or national testing programs to assess the lack of evaluation or national testing programs to assess the

genetic value of germplasm.genetic value of germplasm.

Genomic approaches should help in identifying critical populations Genomic approaches should help in identifying critical populations

for preservation for preservation

Conservation of some local well-adapted breeds.Conservation of some local well-adapted breeds.

Genomics = manage what we canGenomics = manage what we can measuremeasure

Collecting a minimum number of phenotypes in the field is one of Collecting a minimum number of phenotypes in the field is one of

the critical and challenging steps to further deployment of genomic the critical and challenging steps to further deployment of genomic

selection in developing countries.selection in developing countries.(Eggen, 2012)