Environmental temperature is one of the important abiotic factors that influence the normal physiological function and productive performance of dairy cattle. Temperature stress evokes complex responses that are essential for safeguarding of cellular integrity and animal health. Post-transcriptional regulation of gene expression by miRNA plays a key role cellular stress responses. The present study investigated the differential expression of miRNA in Frieswal (Holstein Friesian × Sahiwal) crossbred dairy cattle that are distinctly adapted to environmental temperature stress as they were evolved by using the temperate dairy breed Holstein Friesian. The results indicated that there was a significant variation in the physiological and biochemical indicators estimated under summer stress. The differential expression of miRNA was observed under heat stress when compared to the normal winter season. Out of the total 420 miRNAs, 65 were differentially expressed during peak summer temperatures. Most of these miRNAs were found to target heat shock responsive genes especially members of heat shock protein (HSP) family, and network analysis revealed most of them having stress-mediated effects on signaling mechanisms. Being greater in their expression profile during peak summer, bta-miR-2898 was chosen for reporter assay to identify its effect on the target HSPB8 (heat shock protein 22) gene in stressed bovine PBMC cell cultured model. Comprehensive understanding of the biological regulation of stress responsive mechanism is critical for developing approaches to reduce the production losses due to environmental heat stress in dairy cattle.
The Attappady Black goat is a native goat breed of Kerala in India and is mainly known for its valuable meat and skin. In this work, a comparative study of connectionist network [also known as artificial neural network (ANN)] and multiple regression is made to predict the body weight from body measurements in Attappady Black goats. A multilayer feed forward network with backpropagation of error learning mechanism was used to predict the body weight. Data collected from 824 Attappady Black goats in the age group of 0-12 months consisting of 370 males and 454 females were used for the study. The whole data set was partitioned into two data sets, namely training data set comprising of 75 per cent data (277 and 340 records in males and females, respectively) to build the neural network model and test data set comprising of 25 per cent (93 and 114 records in males and females, respectively) to test the model. Three different morphometric measurements viz. chest girth, body length and height at withers were used as input variables, and body weight was considered as output variable. Multiple regression analysis (MRA) was also done using the same training and testing data sets. The prediction efficiency of both models was compared using the R 2 value and root mean square error (RMSE). The correlation coefficients between the actual and predicted body weights in case of ANN were found to be positive and highly significant and ranged from 90.27 to 93.69%. The low value of RMSE and high value of R 2 in case of connectionist network (RMSE: male-1.9005, female-1.8434; R 2 : male-87.34, female-85.70) in comparison with MRA model (RMSE: male-2.0798, female-2.0836; R 2 : male-84.84, female-81.74) show that connectionist network model is a better tool to predict body weight in goats than MRA.
Loop-mediated isothermal amplification (LAMP) is a diagnostic method for amplification of DNA with rapid and minimal equipment requirement. In the present study, we applied the LAMP assay for rapid detection of cow components adulteration in buffalo milk/meat samples. The test can be completed within around 1 h 40 min starting from DNA extraction and can be performed in water bath without requirement of thermocycler. The cow DNA in buffalo samples were identified in the developed LAMP assay by either visualizing with SYBR Green I/HNB dyes or observing the typical ladder pattern on gel electrophoresis. The test can detect up to 5 % level of cow milk/meat mixed in buffalo counterparts. Due to the simplicity and specificity, the developed LAMP test can be easily adapted in any laboratory for rapid detection of cow species identification in livestock by products.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.