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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Precision Livestock Genome Editing in India: From CRISPR Innovation to Sustainable Animal Production

Authors: Dr Raakib Rasool Janbaz1, Dr Mohsin Ayoub Mir1, Dr Rakesh Nehra2, Dr Pallavi Chaudhary;

Precision Livestock Genome Editing in India: From CRISPR Innovation to Sustainable Animal Production

Abstract

Genome editing technologies particularly CRISPR-Cas systems are revolutionizing livestock improvement by enabling precise modifications to the genetic code of animals. This review explores the evolution of genome editing tools from early protein-based platforms such as ZFNs and TALENs to the current RNA-guided CRISPR-Cas systems which offer unprecedented precision, efficiency and affordability. We highlight key applications in disease resistance, productivity enhancement and animal welfare, with a specific focus on Indian livestock species such as Murrah buffalo, Deccani sheep and indigenous goat breeds. Ongoing research initiatives at Indian institutions including SKUAST-Kashmir, NDRI, CIRB and IVRI are tailoring CRISPR technologies to address local challenges such as mastitis, heat stress and low productivity. The regulatory landscape in India is also discussed alongside emerging tools such as base editing, prime editing and rumen microbiome engineering. This paper underscores the transformative potential of genome editing in building climate-resilient, productive and ethically managed livestock systems, while emphasizing the evolving role of veterinarians as genetic advisors and science translators in this new era. 

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green