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(Mithun) and (yak) are crucial to the culture, food security, and economy of Southeast Asia, especially in India and China, respectively. Their genetic closeness to (indicine cattle) and (taurine cattle) necessitates precise methods for meat origin authentication. This study introduces a DNA-based technique to distinguish Mithun and yak species using the alkaline lysis (AL) protocol for DNA extraction, followed by species-specific polymerase chain reaction (PCR) to amplify unique mitochondrial D-loop regions, yielding 489 bp and 422 bp amplicons, respectively. The AL-PCR method showed high specificity for both species, with no cross-amplification with other related species. The method's effectiveness was validated across various sample preparations, including raw, cooked, autoclaved, microwaved, and fried samples. The AL-PCR assay is highly sensitive, detecting as little as 1 pg of Mithun DNA and 100 pg of yak DNA, and can identify down to 0.1% of these species in binary mixtures. This approach is rapid and cost-effective, offering significant benefits for consumer protection, promoting Mithun and yak farming, and addressing food safety and traceability issues.
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http://dx.doi.org/10.3390/molecules30040934 | DOI Listing |
Acta Trop
August 2025
ICAR-National Institute on Foot and Mouth Disease, ICFMD, Arugul, Bhubaneswar 752050, India.
India, with over 535 million livestock, is one of the largest and most densely populated countries in Asia in terms of livestock population. Transboundary animal diseases, such as foot and mouth disease (FMD), pose significant constraints on the development of progressive livestock enterprises in developing countries. During 2021-2022, a relatively higher number of suspected FMD outbreaks were reported across multiple species in most states and union territories (UTs).
View Article and Find Full Text PDFTrop Anim Health Prod
March 2025
Farm Section, Indian Council of Agricultural Research-National Research Centre on Mithun, Medziphema, Dimapur, Nagaland, India.
Indian mithun (Bos frontalis), a rare ruminant species, is exclusively found in northeastern hill region of India and reared under semi-intensive system. Subclinical ketosis (SCK) is caused by an imbalance between energy supply and the needs of cows during lactation. To date, SCK prevalence is not known in mithun and biomarkers for its prediction have not been standardized.
View Article and Find Full Text PDFMolecules
February 2025
ICAR-National Research Centre on Mithun, Medziphema 797106, Nagaland, India.
(Mithun) and (yak) are crucial to the culture, food security, and economy of Southeast Asia, especially in India and China, respectively. Their genetic closeness to (indicine cattle) and (taurine cattle) necessitates precise methods for meat origin authentication. This study introduces a DNA-based technique to distinguish Mithun and yak species using the alkaline lysis (AL) protocol for DNA extraction, followed by species-specific polymerase chain reaction (PCR) to amplify unique mitochondrial D-loop regions, yielding 489 bp and 422 bp amplicons, respectively.
View Article and Find Full Text PDFActa Parasitol
February 2025
ICAR-NRC on Mithun, Medziphema, Nagaland, 797106, India.
Purpose: To investigate the seroprevalence and molecular characterization of Anaplasma parasites in mithun (Bos frontalis) and their tick vectors in Nagaland and Arunachal Pradesh, India using serological and molecular methods.
Methods: Mithun sera were screened for Anaplasma antibodies using a competitive ELISA targeting the MSP5 antigen. Blood samples and ticks collected from mithun were analyzed using PCR targeting the RNA polymerase subunit beta (rpoB) gene for Anaplasma species detection, followed by sequencing and phylogenetic analysis of positive samples.
OMICS
October 2024
Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, India.
Identifying genomic regions under selection is essential for understanding the genetic mechanisms driving species evolution and adaptation. Traditional methods often fall short in detecting complex, spatially varying selection signals. Recent advances in deep learning, however, present promising new approaches for uncovering subtle selection signals that traditional methods might miss.
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