Evaluation of three bovine Y specific microsatellite loci as an alternative biomarkers for semen quality traits in crossbred bull

Development of a RAPD marker-based classification criterion for quality semen production in Holstein crossbred bulls

In cattle production systems, an intense selection pressure for production traits has resulted in the decline of fertility traits. To optimize an efficient reproduction system, the inclusion of both male and female fertility traits in the selection process is very much essential. RAPD (Random Amplified Polymorphic DNA) was developed as a molecular biology tool and has been extensively used, to study intra- and interspecific genetic diversity. The present study was undertaken to utilize RAPD primers to investigate the association between DNA markers and semen quality traits viz. Sperm concentration, total sperm count ejaculate and initial sperm motility and thereby to identify good/poor semen producers. DNA isolated from the blood samples of healthy bulls was subjected to RAPD-PCR. The multiple regression analysis followed by independent t test was carried out to identify suitable markers. Based on the results, only 12 bands were identified as marker suitable for any of the quality trait. This includes, OPA2 ~ 760, OPA2 ~ 700, OPA6 ~ 1,200, OPA9 ~ 400, OPA9 ~ 380, OPA12 ~ 970, OPA14 ~ 715, OPA14 ~ 605, OPA16 ~ 485, OPA17 ~ 860 and OPA18 ~ 480. Multiple regression analysis selected, OPA2 ~ 760 and OPA2 ~ 1,750 for sperm concentration and OPA2 ~ 760, OPA2 ~ 700, OPA9 ~ 620, OPA4 ~ 670 and OPA18 ~ 1,015 for total sperm count/ejaculate. But the t test revealed a significant association between OPA2 ~ 760 and total sperm count. Further, discriminant function analysis also identified this marker in the first step itself. The results of the present study can be exploited as a low-cost alternative strategy for identification of good /poor semen producers in crossbred bulls at an early age.

Marker-assisted selection vis-à-vis bull fertility: coming full circle-a review

Bull fertility is considered an indispensable trait, as far as farm economics is concerned since it is the successful conception in a cow that provides calf crop, along with the ensuing lactation. This ensures sustainability of a dairy farm. Traditionally, bull fertility did not receive much attention by the farm managers and breeding animals were solely evaluated based on phenotypic predictors, namely, sire conception rate and seminal parameters in bull. With the advent of the molecular era in animal breeding, attempts were made to unravel the genetic complexity of bull fertility by the identification of genetic markers related to the trait. Marker-Assisted Selection (MAS) is a methodology that aims at utilizing the genetic information at markers and selecting improved populations for important traits. Traditionally, MAS was pursued using a candidate gene approach for identifying markers related to genes that are already known to have a physiological function related to the trait but this approach had certain shortcomings like stringent criteria for significance testing. Now, with the availability of genome-wide data, the number of markers identified and variance explained in relation to bull fertility has gone up. So, this presents a unique opportunity to revisit MAS by selection based on the information of a large number of genome-wide markers and thus, improving the accuracy of selection.

Evolution of Frieswal cattle: A crossbred dairy animal of India

Frieswal cattle is one of the crossbred strains having 5/8 Holstein Friesian and 3/8 Sahiwal inheritance, develo pedby ICAR-Central Institute for Research on Cattle, Meerut, in collaboration with Ministry of Defence. The projectwas started in 1987 for the evolution of a new crossbred national milch breed: Frieswal – (Holstein×Sahiwal), yielding 4,000 kg of milk with 4% butter fat in a mature lactation of 300 days. It is the only project in the country where such a huge population of animals (more than 20,000) is available with accurate production and pedigree records of each and every animal over generations, with well-established progeny testing network in 37 military farms to cover all the agro-climatic zones of the country. In this review, an attempt has been made to analyze the genesis, present status and future prospects of Frieswal cattle in India.

Designing of an artificial neural network model to evaluate the association of three combined Y-specific microsatellite loci on the actual and predicted postthaw motility in crossbred bull semen

The freezing of bull semen significantly hamper the motility of sperm which reduces the conception rate in dairy cattle. The prediction of postthaw motility (PTM) before freezing will be useful to take the decision on discarding or freezing of the germplasm. The artificial neural network (ANN) methodology found to be useful in prediction and classification problems related to animal science, and hence, the present study was undertaken to compare the efficiency of ANN in prediction of PTM on the basis of the number of ejaculates, volume, and concentration of sperms. The combined effect of Y-specific microsatellite alleles on the actual and predicted PTM was also studied. The results revealed that the prediction accuracy of PTM based on the semen quality parameters was comparatively lower because of higher variability in the data set. The ANN gave better prediction accuracy (34.88%) than the multiple regression analysis models (32.04%). The root mean square error was lower for ANN (8.4353) than that in the multiple regression analysis (8.6168). The haplotype or combined effect of microsatellite alleles on actual and predicted PTM was found to be highly significant (P < 0.01). On the basis of results, it was concluded that the ANN methodology can be used for prediction of PTM in crossbred bulls.