Transcript Slide 1

Utilizing Genomics in genetic
improvement
Molecular genetics as a tool in wildlife
breeding, management and conservation
(An African Buffalo case study)
Ben Greyling
ARC-API, Irene
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 Role of Mol. Gen. in wildlife management/conservation/breeding
 The ABC of DNA
 The African buffalo: A case study
 Genomics: Where do we stand?
 The Cattle model: from genetic variation, to marker assisted
selection to quantitative variation
 Cape buffalo – recent developments
Primary objective of conservation and management
To protect diversity, ensure sustainable use of the resource
 Driving forces: need to qualify and quantify
Role of Mol tools: Supply baseline info
Levels of genetic variation, inbreeding
 Pop structure – genetic distances/assignment?
 Gene flow between populations?
 Effective population size vs. census size
 Admixture (Genomics..)
 Relationship between variation and fitness/adaptation
 Gene regulation/expression under environmental control

More applications…
 Forensics and traceability: Individual ID
 Parentage verification (selection and management tool)
 Hybrid identification
 Genomics: Quantitative variation – from genotype to
phenotype
 Epigenetics: Environments effect on genes - heritable
trait expression..
…AACGTGTTGACGCCGTAATGCATAAT
CTHISWILLEVENTUALLYDRIVEYOUC
RAZYCGCTAGCCTTCGGCAATC...
The value of Mol Gen tools:
Making sense of “useless information”
3000 000 000 letters per cell…
T
Point mutation (SNP)
A A C
G
C T
T T G C G A
insertion
T A
deletion
G C
A T C
T A
G A
T
G C
C
T C
G A
A
G T
African buffalo: A major role player in our
ecosystems/metapopulation
 Largest populations confined to conservancies
 Model species with regard to pop. dynamics - factors
affecting it
 Genetic variation, structure, gene flow, disease status, etc.
Contributed immensely to conservation and
management strategies
Case studies: Population structure
 KNP vs. HiP
99% accurate assignment of individuals to pops due to genetic
distance
Distribution of the Log likelihood of assignment for KNP and HiP
40
Log likelihood of assignment to HiP
35
30
25
20
15
10
5
0
0
5
10
HiP
KNP
15
20
25
Log likelihood of assignment to KNP
30
35
40
Case studies: Genetic variation
Periods of low Ne for some populations in SA:
?? sustainability of genetic variation
?? compromised adaptation in response to changing
environment?
Example: Genetic erosion in HiP: 1% per year
East vs. southern African subpopulations?
 Little genetic differentiation
East/southern African population a separate management
unit, differ substantially from central/west African lineage
 Substantial variation in both sub-populations
Gene expression/regulation: The Y-Chromosome
Its raining men
 Environment and body condition: switch on/switch off…
 Sex ratio distorted: more males in the wet season
 Particular genotypes dominate depending on
environment (season) – affect sex ratio
 Sex ratio and BTB-link?
Heterozygote-fitness-correlation (HFC)
 Low genetic variation = low body condition – affect genes
on the “Y”
 Bad genes expressed in southern KNP, link to BTB, what
the Y is going on?….
 Females can also affect sex ratio…
 Epigenetic factors?
 BTB susceptibility may have an epigenetic link –
heritable..
Ranches: management-scenario’s
 Small populations, restricted gene flow
 Controlled breeding (non-random mating)
 Fragmented populations and “lines”
 Breeding and selection among “lines”, e.g. Addo-Lowveld
 Preference for market-desired phenotypes
Potential consequences of ranching
Reduction in genetic variation (inbreeding?)
Increase in frequency of deleterious alleles
Loss of adaptive genes/fitness
disease resistance, reproduction, growth etc.
Reduction in effective pop size – sustainability of
variation?
Admixture – potential outbreeding depression
Compromised adaptability
Genomics to the rescue: Linking the DNA code to
performance and phenotype (amongst others…)
 SNP vs. full genome sequences – from a good amount of
info to a desired amount of info
 Powerful tools to address needs of wildlife industry
 Substantially applied to livestock
 Quantitative genetics: Selection tool for superior
genetics
 Fast track genetic improvement
Genomics for buffalo?
 3K SNP panel already developed identified using
next generation sequencing technology
 Projects in pipeline using the 3K panel = more
powerful approach
 Buffalo and quantitative genetics: Breeding values
on the horizon?
 Scope for genomic breeding values…
Requirements for Genomics:
 Accurate pedigrees
 Phenotypic records
 Reference populations
 DNA (SNP) profiles
 Test populations
The future is now with this technology
Are we ready to adopt?