Animal Genetics & Breeding

Name of Scholars

Major Advisor

Thesis title

Brief recommendations

Year of Completion

Ph.D (AGB)

Dr.Syed Shanaz

Prof TAS Ganai

Exploring association of polymorphism of some fiber related genes with production and quality traits in chanthangi goats.

Gene based marker selection is possible for improvement of fibre quality attributes.


Dr.Feroz-u-din Sheikh

Prof TAS Ganai

Study of genetic diversity for enhancing productivity in pashmina goats of ladakh

Substantial genetic variation and polymorphism could be used for overall genetic improvement of changthangi got for meat and pashmina production


Dr.Rukhsana Majid

Prof N.A.Ganai

Exploring candidate gene approach for selection of dairy animals for high yield and better quality milk

Effect of haplotypes significant on all milk production traits under study


Dr.Nusrat Nabi

Prof N.A.Ganai

inbreeding and its effect on growth and fitness traits in a closed flock of Corriedale sheep in Kashmir

Signals the time to act to widen the genetic base by introduction of new blood into the flock (ONBS)


Dr.Mir Shabir

Prof N.A.Ganai

Expression profile of certain disease resistance genes coding for some specific interleukins and chemokines with respect to salmonellosis in poultry

Expression profile pattern of the genes revealed broilers are more susceptible and Vanraja more resistant

Humoral immune response (IgG) more in broiler chicks

Significant haemato-biochemical alterations constituted the clinical indicators for


infection in chicks


Dr.Zaffar Iqbal

Prof N.A. Ganai

Transcriptional profiling of Cashmere hair cycle using RNA seq

Transcriptional profiling revealed  different phase transitions of Pashmina hair cycle : Governed by the molecular mechanisms involving integrin/ chemokine signalling pathways


Dr.Saba Bukhari

Prof N.A. Ganai

Study on genetic variability of growth and reproductive traits of poll Dorset and its crosses under temperate climatic conditions of J & K

The accurate data recording in a organized farm will improve reliability of the data, help in identification of best animals and consequently improve the accuracy of the gene assisted selection in future breeding programmes of the farm.


Dr Ambreen Hamadani

Prof N. A. Ganai

Exploration of Artificial intelligence for the Prediction of Genetic Merit in Sheep