Current and future uses of genetic improvement technologies in livestock breeding programs

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:畜産遺伝改良の排出削減効果と導入障壁に関する実証的知見を提供。

🏢実務担当者:畜産経営における遺伝改良技術の導入判断に有用。

🏛政策担当者:途上国支援や遺伝子編集規制の政策設計に示唆。

• Genetic improvement has been a key contributor to the sustainability of animal agriculture, but these changes in overall production and efficiency have not been universal, and many low- and middle-income countries (LMIC) have production systems with high emission intensities. • The adoption of cost-effective, genetic, feed, and nutrition practices, and improving livestock health in LMIC are seen as one of the most promising interventions to reduce emissions resulting from projected increased demand for animal-source food through 2050. • Genetic improvement has a proven track record of productivity enhancements, and following implementation, genetic improvement is permanent and cumulative. • Gene editing offers an approach to introduce useful genetic variation into future cattle breeding programs in the absence of the linkage drag that typically accompanies traditional introgression of useful alleles through crossbreeding, although its adoption will likely depend on whether global regulatory approaches facilitate public acceptance and free trade of milk, meat, and germplasm derived from GnEd animals. • Delaying access to genetic improvement technologies to tackle otherwise intractable problems like animal disease, as happened with genetic engineering, is associated with a high opportunity cost of unrealized benefits. Genetic improvement of food-producing species is a powerful tool for improving the sustainability of animal agriculture. Conventional selection programs, beginning with selective breeding using statistical prediction methods, such as estimated breeding values and more recently genomic selection, in synergistic combination with reproductive technologies (e.g., artificial insemination), have accelerated the rate of genetic gain by enabling more accurate selection and intense utilization of genetically superior parents for the next generation. The aims of this article were to review the current uses and opportunities to use existing genetic improvement technologies to improve milk and beef production efficiencies, with an emphasis on the large cattle populations in low- and middle-income countries (LMIC). Then, future opportunities that might arise from gene editing (GnEd) are considered, with some focus on the regulatory status of extant GnEd food animal applications and public perception. For GnEd to be adopted, it must be able to scale and integrate smoothly into the operation of existing cattle genetic improvement schemes. Finally, the opportunity cost of inaction and delays in the adoption of genetic improvement technologies is discussed in the context of animal breeding. In 2022, the global cattle (155.2 billion) and buffalo (205.1 million) population (Figure 1) collectively produced 76.3 MMT of bovine meat and 753 and 144 MMT of cow and buffalo milk, respectively. The United States produced 18.6% (12.9 MMT) of the world’s beef with 6% (92.1 million) of the world’s cattle in 2022. Brazil with 15% (225 million) of the world’s cattle population produced 15% (10.4 MMT) of the beef, whereas India with 194 million cattle and 112 million buffalo produced only 5.8% (4.35 MMT) of bovine meat. Similarly, the African continent with almost 25% of the world’s cattle produced around 9.0% beef. There are a myriad of reasons for these differences including the fact that cattle are also raised for milk, hides, manure, and draught power and that cattle serve religious and other roles not captured by the single metric of beef output. Cattle and buffalo numbers by country 2022 (FAO, 2024). Where and how cattle are raised has important implications on the efficiency and greenhouse gas (GHG) emissions intensity (emissions produced per unit of product) of beef and milk production. Many LMICs have production systems with high emission intensities (Figure 2), and this is important because LMICs are home to 76% of the global cattle herd and contribute 75% of the global ruminant GHG emissions. The adoption of cost-effective, genetic, feed, and nutrition practices, and improving livestock health in LMIC are seen as the most promising interventions to reduce emissions resulting from projected increased terrestrial animal-source food demand through 2050 (FAO, 2023). It has been estimated that as compared to a baseline where emission intensities are held constant in the future, improving livestock production efficiencies in the 10 countries with the largest emission reduction potential (Madagascar, Morocco, Niger, South Africa, Tanzania), Asia (China, India, Iran, Turkey) and South America (Brazil) could contribute 60% to 65% of the global reduction in livestock emissions by 2050 (Chang et al., 2021). GHG emissions intensity per kg beef produced per region through 2031. OECD calculations based on FAOSTAT-Emissions Totals, Statistical Division of the Food and Agriculture Organization of the United Nations (FAO), Rome (OECD and FAO, 2022). Milk constitutes 67% of the total protein produced by cattle. India, the United States of America, and China are the top three countries in terms of raw milk production from cattle, with the European Union as a region being second only to India. Brazil is the fourth largest milk producer, despite having the world’s largest cattle herd. World milk production is projected to grow at 1.5% p.a. over the next decade to 1,039 MMT in 2032, faster than most other main agricultural commodities. Over half of the increase in total milk production is anticipated to come from India and Pakistan, which will jointly account for over 32% of world production by 2032. According to a 2022 OECD report (OECD and FAO, 2022), “the global level of GHG emissions will largely depend on efficiency gains in India and other countries with high cattle populations and extensive production.” The biggest gains in inventory are predicted to occur in India, Pakistan, and Africa. Genetic improvement is a particularly attractive approach to productivity enhancements, as following implementation genetic improvement is permanent and cumulative. One relatively simple technology that has been adopted by cattle producers in many high-income countries is artificial insemination (AI) to increase the intensity of selection by using genetically superior males. First introduced in the early 1940s (Foote, 2002), its use is widely adopted by the dairy industries in many countries. However, adoption has not been universal and is particularly low in extensive beef production systems where it is difficult to coordinate estrus synchronization protocols and perform AI on cows. The level of adoption of Brazil and India, the two countries with the largest cattle populations (Figure 1), has historically been low (<20%). However, recent efforts to increase adoption in both these countries have had some success. In 1997, India became the largest milk-producing country in the world. In the period from 1951 to 2019, the country’s milk production increased over 1100%, whereas the increase in the bovid population was 24% and 153% for cattle and buffalo, respectively. This increased milk yield per cow was partially due to genetic improvement enabled by the adoption of AI (National Academy of Agricultural Sciences, 2020). The proportion of crossbred dairy cows increased from 17% in 1990–1991 to 38.3% in 2021–2022, and their share in the total cow milk production rose from 33.5% to 61.2% (Thakur and Birthal, 2023). Even so, the average annual milk production per adult female cow in India was only 1777 kg per animal in 2019 to 2020, compared to the global average of 2699 kg (Mitra et al., 2023), and the current U.S. average of almost 10,950 kg. The carbon footprint of milk is more than 2-fold higher on Indian dairy farms with annual milk yield less than 3,500 kg per cow, as compared to farms with greater milk yield (Mech et al., 2023). There is still high variation across states in daily milk yield, ranging from 1.49 to 13.31 kg/day for cows and 1.61 to 9.63 kg/day for buffalo suggesting considerable scope for increasing yields given locally available resources and technologies. The use of X-chromosome-bearing “sexed” sorted semen in AI to increase the proportion of female calves born presents an intriguing opportunity in India (Thakur and Birthal, 2023). Given that cattle are revered in Hinduism, the culling or slaughter of infertile cows and male calves is prohibited, often resulting in these animals being abandoned on the streets or sent to gaushalas. Even absent the wide use of sexed semen, over the last three decades, the Indian cattle population has shifted significantly toward rearing more females (Thakur and Birthal, 2023). From 1992 to 2019, although Indian cattle numbers decreased by ~10 million head, the number of female cattle increased from 102.98 million to 145.91 million, while male cattle declined from 101.59 million to 47.6 million. This was achieved mainly through management, as X-sorted semen has only been available in India since 2017. The Indian government has established AI stations that can produce sexed semen and is helping to encourage uptake by subsidizing the cost of the semen for farmers. Indian commercial dairy farmers’ willingness to pay for sexed semen was positively influenced by education level, herd size and attitude towards public extension systems (Verma et al., 2020). Increased uptake of AI and X-sorted sexed semen from genetically superior bulls in India and Pakistan to produce only female dairy cattle offers an approach to curtail the production of unwanted male calves in these large bovid populations. This would reduce the emission intensity of milk production without disrupting the livelihoods of dairy farmers in these two countries that are jointly on track to produce half of the projected increase in total milk production globally. Brazil has the largest commercial cattle herd in the world at approximately 238 million head, with 43% dairy and 57% beef cattle. Interestingly, AI is more frequently used in the beef

• openalex https://doi.org/10.1093/af/vfae042first seen 2026-08-02 18:12:54