Novel traits are need of the hour in animal breeding. Hence identification and its utilization should be given utmost priority in the modern animal breeding plans.

1. IDENTIFICATION OF FUNCTIONAL NOVEL TRAITS
IN DAIRY CATTLE
Novel traits?
Need? Identification?
Limitation?
Dr. Sakshi Vaishnav
(PhD Scholar, IVRI)

2. A trait is defined as novel if a heritable change in that trait allows for the exploitation of a new
behavioural or ecological niche or allows population persistence in the face of a challenge that the
population had not previously encountered.
DEFINITION
Word of origin : Latin word novellus meaning “NEW”
Traits that are being introduced to breeding goals in order to satisfy new demands faced by livestock
production or trait that has not previously been widely recorded but are economically, environmentally
or societally important.

3. WHERE DO NOVEL TRAITS COME FROM?

4. NEED OF NOVEL TRAITS?
World population: 9 billion in 2050 (UN reports)
Increase in food production, demand for limited resources
Change in global environment
Change in breeding goal with greater emphasis on novel traits

5. DIFFERENT TYPES OF TRAITS
Functional traits are morphological, biochemical, physiological, structural or behavioural
characteristics that are expressed in phenotypes of individual organism and considered relevant
to response of such organism and/or their effect on ecosystem properties.
Or
Traits that are not directly linked to production and reproduction but indirectly influence them
greatly by playing major role in fitness.
1. Reproduction traits
2. Production traits
3. Functional traits

6. NOVEL TRAITS IN DAIRY CATTLE
• Current breeding goal: Genetic improvement of production traits
• Functional traits- negative correlation- production traits
• Compensation: Identification and selection of novel traits
Traits may be novel in one country and existing in others.
Identification of novel traits
Recording programmes
Use of advanced technologies ( SNP based genotyping, sequencing, metabolomics, proteomics)

7. 1. Direct health traits
• Recording- Treatment , diagnosis
• Data standardisation
• Routine genetic evaluation
• Collaboration and combination of data  coverage of trait
 Genomic evaluation – Jersey cattle (ADSA)
 Traits measured – milk fever, displaced abomasum, ketosis, mastitis, metritis and retained
placenta.
 Genetic evaluation

8. • Mastitis diagnosis, early reproductive disorders, cystic ovaries and milk fever- Austria
• Two new indices:
1. FRW (fertility index) – EREP and CYST
2. EGW (Udder health index)- SCC (70%) and MAS(30%) Udder confirmation traits
C. Fuerst & C. Egger-Danner (2016)

9. 2. Feet and legs traits
• Third reason of culling
• Indicator trait for claw health
• Confirmation recording: Linear type classification
 Locomotion scoring
 Lameness scoring
 Automated lameness detection- activity sensors
• Structural soundness – beef industry – longevity
and welfare
• Enough measurements – genetic evaluation
Rowan(2021)

10. 3. Metabolic status
• Direct traits rarely used
• Milk content traits – early diagnosis
 Limitations - limited predictive ability
 Solution- automated milk recording system
• Subclinical metabolic disorders- ketosis- Non
esterified fatty acids or BHBA concentration
• Body condition score
• Rumen activity
• Body weight change
• Identification of important metabolites

11. 4. Climate resilience
• Heat stress : Impaired welfare  production losses
• Selection for heat stress:
Impact of heat stress in population (PLF technologies)
Define and measure heat stress (THI, MIR-predicted fatty acid C18:1 cis 9 content in milk to heat stress,
heat shock proteins )
Ways to model heat stress
Identification of heat tolerant animals
5. Behavioural traits – subjectively scored
 Temperament
 Milking speed: Slow  production losses ; Fast  Mastitis (optimum: 2 Kg/min)
 Suckling behaviours

12. LIMITATIONS OF NOVEL TRAITS
• Difficult to measure
• Laborious and expensive recording
• Negative correlation with production traits
• Less number of observations available
• Most of the novel traits have low heritability and hence difficult to improve by conventional methods