The Thai dairy sector provided an ideal testing ground for this question. The country’s multibreed cattle population emerged from decades of systematic crossbreeding between taurine breeds — Holstein, Jersey, Brown Swiss, and Red Dane — and indicine breeds including Brahman, Sahiwal, Red Sindhi, and Thai Native cattle. The goal was to combine the tropical adaptability of indicine ancestry with the milk production capacity of taurine genetics. The result is a continuous gradient of breed composition rather than discrete breed groups, with the vast majority of cows — 92.75 percent — carrying Holstein fractions of 75 percent or greater. This admixture, spread across 1,312 smallholder farms in five regions of Thailand, makes accurate estimation of genetic relationships both within and across breeds and generations critically important, and correspondingly difficult.

The research team assembled an impressive dataset: phenotypic records from 14,239 first-lactation cows that calved between 1989 and 2019, a pedigree file covering 25,551 animals, and genotypes from 5,175 animals. The genotypes came from eight different GeneSeek GGP chips ranging from about 9,000 to 150,000 markers, all imputed to a common density of 117,796 single-nucleotide polymorphisms using the Findhap 4 algorithm, which reconstructs haplotypes by combining pedigree transmission information with population linkage disequilibrium patterns. Notably, the imputation pipeline allowed the team to infer genotypes for 172 previously non-genotyped animals — mostly influential sires — whose haplotypes could be reconstructed from chromosomal segments shared among their genotyped offspring. Three economically important traits were analyzed: 305-day milk yield, 305-day fat percentage, and age at first calving.

The heart of the experiment lay in nine carefully constructed pedigree omission scenarios. The first scenario used all available pedigree information as a reference. The next three progressively removed sire identification, dam identification, or both for all genotyped animals, simulating decisions about which animals to prioritize for genotyping when resources are limited. The remaining five scenarios excluded pedigree information for 10, 20, 30, 40, and finally 50 percent of animals with phenotypic records, following a cumulative nested design in which each scenario contained all animals from the previous one plus newly affected individuals. This design ensured that differences between scenarios reflected the incremental loss of pedigree connectivity rather than random re-sampling noise. Each scenario was then run through a three-trait single-step genomic–polygenic model, the workhorse of modern genetic evaluation, which blends pedigree, genomic, and phenotypic information into a single combined relationship matrix.

The results revealed that losing pedigree data does not simply degrade evaluations uniformly — it reshapes them in trait-specific ways. As pedigree completeness declined, additive genetic variance estimates for milk yield tended to increase, rising from 143,550 square kilograms in one intermediate scenario to 177,440 square kilograms under the most extreme omission, and heritability for milk yield climbed from 0.25 to 0.30. This inflation likely reflects a redistribution of variance as the model leaned more heavily on genomic relationships, which alone cannot capture all additive genetic connections in the population. Fat percentage behaved differently: its additive genetic variance stayed relatively stable, but its heritability plummeted from 0.19 to 0.06. Age at first calving proved most fragile, with additive genetic variance dropping from 3.75 to as low as 1.72 square months and heritability falling from 0.18 to 0.10.

These divergent patterns trace back to a fundamental statistical principle: low-heritability traits are the most vulnerable to missing relationship information. Fertility traits such as age at first calving are heavily influenced by environmental factors, leaving a thin additive genetic signal that depends strongly on accurate pedigree-based covariances among relatives to be detected at all. When pedigree links vanish, the model loses the information needed to separate genetic from environmental causes, and the estimated genetic signal shrinks or destabilizes. The genetic correlations between traits also drifted as pedigree completeness declined — the correlation between milk yield and fat percentage became increasingly negative, shifting from −0.40 to −0.91 — indicating growing instability in the estimated covariance structure rather than any real biological change.

The consequences for breeding value prediction were equally revealing. When pedigree information was removed only from genotyped animals, correlations between breeding values from the complete and incomplete scenarios remained high, between 0.95 and 0.99, showing that genomic relationships largely preserved genetic connectedness for these individuals. Moderate random omissions were also tolerable: with up to 20 percent of phenotyped animals lacking pedigree records, correlations stayed above 0.90 for all three traits. But beyond that threshold, the situation deteriorated rapidly. Under the most extreme scenario, with 50 percent of phenotyped animals missing pedigree information, correlations with the reference evaluation fell to 0.86 for milk yield, 0.51 for fat percentage, and 0.76 for age at first calving. Genomic data, the study concluded, can partially compensate for moderate pedigree gaps, but that compensatory capacity is trait-specific and ultimately limited.

Perhaps most striking were the effects on animal rankings, which translate directly into real-world selection decisions. Under the highest selection intensity — the top 5 percent of animals — rank correlations between the complete and most incomplete scenarios collapsed from 0.86 to 0.21 for milk yield in sires and from 0.83 to 0.20 for fat percentage in cows. In practical terms, a breeding program operating on such a compromised dataset would select an almost entirely different set of elite animals than one with complete records, squandering resources and slowing genetic progress. The study also found that losing both parental records hurt more than losing just one, and that dam information mattered slightly more than sire information — a useful guide for farmers and breeding programs deciding which records to prioritize when documentation is incomplete.

For tropical smallholder dairy systems, where infrastructure for systematic record-keeping is often lacking, the message is both cautionary and actionable. Genomic–polygenic evaluations can remain viable when up to 20 percent of pedigree data are missing, offering a realistic buffer for imperfect real-world conditions. But beyond that point, the accuracy of selection quietly erodes, with the damage concentrated in exactly the traits — fertility and milk composition — that determine long-term profitability. The authors argue that promoting systematic pedigree recording among farmers is not a relic of pre-genomic breeding but a foundational requirement for reliable genomic selection. In multibreed, smallholder populations, where crossbreeding already complicates pedigree tracking, the family tree and the SNP chip must work together; neither can carry the weight of genetic improvement alone.

Subject of Research: Impact of pedigree completeness on genomic–polygenic genetic evaluations in Thai multibreed dairy cattle

Article Title: Impact of pedigree completeness on genomic–polygenic evaluations for milk yield, fat percentage, and age at first calving in Thai multibreed dairy cattle

Article References: Jattawa, D., Thiengpimol, P., Suwanasopee, T., Elzo, M. A., Laodim, T., & Koonawootrittriron, S. (2026). Impact of pedigree completeness on genomic–polygenic evaluations for milk yield, fat percentage, and age at first calving in Thai multibreed dairy cattle. Archives Animal Breeding, 69(3), 455-467. https://doi.org/10.5194/aab-69-455-2026

Image Credits: AI Generated

DOI: 10.5194/aab-69-455-2026

Keywords: genomic selection, pedigree completeness, dairy cattle, multibreed populations, heritability, breeding values, single-step genomic BLUP, smallholder farming, Thailand, milk yield, age at first calving, animal breeding

The study, published in the journal Discover Agriculture by Erica Auguste of Trinidad and Tobago’s Ministry of Agriculture and Fisheries and colleagues Martin Hughes and Sivakumar Karuppusamy at the University of the West Indies, set out to answer a question with real economic stakes. Dairy farming across the tropics is dominated by smallholders, and their productivity is chronically low. In Trinidad and Tobago, national milk production collapsed from roughly 9.4 million kilograms in 2001 to about 1.6 million kilograms in 2024. Jamaica saw annual yields fall by around 57 percent over a comparable period. Understanding which biological factors actually constrain output on these farms is therefore not an academic exercise but a matter of livelihood and food security.

The Centeno Livestock Station occupies about 502 acres of flat to gently sloping land in El Carmen, St. Helena, in the county of Caroni. Its soils belong to the Cunupia series — heavy clays with impeded drainage and a pH between 4.5 and 5.4 — and the climate is classically tropical, with average annual rainfall near 1,877 millimetres and temperatures ranging from 22.7 to 31.3 degrees Celsius. A wet season runs from July to December and a dry season from January to June, during which pasture quality and quantity typically decline. The dairy herd of roughly 60 cows grazes rotationally on Brachiaria arrecta and unimproved native grasses, is milked twice daily with an automated system, and receives about 2.0 to 2.5 kilograms of an 18 percent crude protein concentrate at each milking.

Two breeds dominate the herd: the Centeno Crossbred, a Bos taurus × Bos indicus animal developed in the late 1970s by crossing Holstein-Friesians with Zebu-type breeds to combine high yield with heat tolerance and resistance to tick fever, and the Jersey. The researchers deliberately excluded a small group of graded Holstein-Friesians because so few were lactating and in poor condition. Breeding is carried out by artificial insemination, and the cows range from three to twelve years old. It was this herd, managed under consistent conditions, that provided the retrospective dataset spanning 2014 to 2019.

The team analysed the records using analysis of variance in SPSS version 27, treating calf sex, breed, parity and the breed-by-parity interaction as fixed effects, with Bonferroni-adjusted comparisons and Tukey’s test to separate means. Data normality was confirmed with the Ryan-Joiner test, and lactations shorter than 140 days in milk were excluded from total-yield calculations. Early lactation was defined as the first 90 days in milk. The statistical verdict was unambiguous: calf sex, breed and the breed-by-parity interaction had no significant effect on milk yield or lactation length.

Parity told a different story. Cows in their fourth through sixth parities produced 849 ± 66 kilograms of milk in early lactation, and those beyond their sixth parity produced 1,005 ± 116 kilograms — both figures significantly higher than the 673 ± 41 kilograms recorded for cows in their first to third parities. Daily milk yield followed the same gradient, at 5.6 ± 0.33 kilograms for the youngest parity group compared with 8.4 ± 1.0 kilograms for cows beyond their sixth lactation. The pattern makes physiological sense: young cows are still growing, so nutrients and energy must be split between body development, gestation and milk synthesis, often pushing them into a deeper negative energy balance. Mature cows, with larger mammary glands and more developed secretory tissue, can channel a greater share of their intake into milk.

Perhaps the most striking finding came from regression analysis. Early lactation milk yield accounted for 73 percent of the variability in total lactation yield — a coefficient of determination of 0.73. In other words, a cow’s output in her first three months of milking is a powerful predictor of her entire lactation. This aligns with a well-established body of literature showing that early lactation is a physiologically critical window in which milk yield peaks while energy demands often exceed dry matter intake. It also suggests that phase-specific management — concentrating feed resources and attention on freshly calved cows — could pay dividends even on smallholder, pasture-based tropical farms, where such approaches are rarely practised.

The null result on calf sex is notable because the literature on sex-biased milk synthesis is genuinely contested. Some studies, including a well-known analysis of Holsteins, reported that cows carrying female fetuses produced around 143 kilograms more milk than those carrying males, possibly because longer gestations for male calves shorten the subsequent lactation. Others found the opposite, attributing higher yields after male births to larger fetal size and elevated placental estrogen, which stimulates prolactin release — though bigger calves also raise the risk of difficult calvings that depress yield. The Centeno findings suggest that such sex effects, where they exist, are contingent on factors like calf size, dam health, parity and production system, and that within a uniform herd under consistent management, they may simply wash out.

The equivalence of the Jersey and Centeno Crossbred cows is equally consequential. Despite their different genetic backgrounds, the two breeds performed comparably under identical conditions, with the crossbreds posting numerically higher early lactation and daily yields while Jerseys showed numerically higher total yield and longer lactations. Since neither difference reached significance, the results hint that both breeds carry similar genetically linked performance characteristics when mature body size and management are held constant. For farmers choosing breeding strategies, that is reassuring: the locally adapted crossbred, bred for heat tolerance and disease resistance, gives up little in productive potential to the imported Jersey.

The sobering counterpoint is that absolute productivity at the station remains very low. Jersey cows elsewhere in subtropical climates yield around 11 kilograms of milk per day, and 20 to 25 kilograms in temperate environments — between 27 and 68 percent more than the CLS herd. Worryingly, low productivity in Centeno Crossbreds was flagged four decades ago, and the new data suggest performance may have declined further, pointing to persistent inadequate nutrition, unimproved pastures, dry-season feed gaps, costly concentrate supplementation and possible genetic depletion. The authors argue that improving pasture quality and quantity, supplemental feeding, reproductive efficiency and heat-stress management — measures that meta-analyses suggest can lift smallholder tropical milk yields by as much as 29 percent — must target cows in fourth and later parities and, above all, cows in early lactation, because that is where milk production is maximized and where the whole lactation is won or lost.

Subject of Research: Effects of calf sex, breed and parity on milk yield and lactation length in a tropical dairy herd

Article Title: Effects of calf sex, breed and parity on the lactation performance of dairy cows in Trinidad and Tobago

Article References: Auguste, E., Hughes, M., & Karuppusamy, S. (2026). Effects of calf sex, breed and parity on the lactation performance of dairy cows in Trinidad and Tobago. Discover Agriculture, 4(1), Article 295. https://doi.org/10.1007/s44279-026-00779-x

Image Credits: AI Generated

DOI: 10.1007/s44279-026-00779-x

Keywords: dairy cattle, milk yield, parity, calf sex, lactation length, early lactation, Centeno Crossbred, Jersey, smallholder farming, Trinidad and Tobago, tropical agriculture, animal breeding

Ethiopia holds the largest livestock population in Africa, with roughly 66 million cattle, 46 million goats, 38 million sheep and 41 million chickens. Livestock contribute about 45 percent of agricultural gross domestic product and 13 to 16 percent of total GDP, supplying more than 3.8 billion liters of milk and one million tons of beef each year. Yet the sector is dominated by indigenous breeds: according to the national Central Statistical Agency, 98.24 percent of the country’s cattle are local breeds, with hybrids accounting for just 1.54 percent and exotic breeds a mere 0.22 percent. National milk output falls well short of demand, and the productivity gap between what Ethiopian cows could produce and what they actually produce is one of the defining challenges of the country’s agricultural development.

To understand why, the research team stratified each milk production system into adopters and non-adopters of modern dairy technologies, defining adopters as farmers using at least one improved practice such as artificial insemination or improved forage varieties. Respondents were selected by simple random sampling, with sample size determined using the Yamane formula at a 5 percent precision level. The final sample comprised 141 producers from the urban system, 43 from the peri-urban system and 40 from the rural system. Data were collected through face-to-face interviews using semi-structured questionnaires and analyzed with general linear models in SPSS, treating production system, adoption level and their interaction as fixed effects, with Tukey-adjusted pairwise comparisons and significance declared at p below 0.05.

The reproductive numbers tell a clear story. Crossbred cows reached first service at an average of 20.02 months of age, first calving at 34.30 months, and maintained a calving interval of 11.95 months. Local breed cows lagged far behind, with age at first service of 31.55 months, age at first calving of 45.14 months and a calving interval of 15.09 months. These differences were highly statistically significant across production systems. Reproductive performance matters enormously in dairy economics because every month of delay in first calving or every extension of the calving interval reduces the number of calves and the total liters of milk a cow delivers over her lifetime. The crossbred advantage observed here was shorter than some figures reported elsewhere in Ethiopia, which the authors attribute to differences in feeding and management inputs.

Production performance showed an even starker contrast. Crossbred cows yielded an average of 8.26, 8.31 and 7.05 liters per day in the urban, peri-urban and rural systems respectively, while local cows produced a national-average-level 1.65 liters per day overall. Over a full lactation, local cows gave 355, 294 and 260 liters in the three systems, whereas crossbreds produced 2,374, 2,402 and 2,015 liters. Most tellingly, adopters outperformed non-adopters across the board: average daily milk yield was 9.51 liters for crossbred adopters versus 6.24 liters for non-adopters, and 1.67 versus 1.41 liters for local breeds. Lactation length was 26.1 days longer in adopters’ crossbred cows and 23.4 days longer in their local cows, differences that were highly significant statistically.

Why does adoption matter so much? The study points to the compounding effect of better management. Adopters tend to practice improved feeding, health care, breeding selection, housing and hygiene simultaneously, and these practices reinforce one another. Feed and nutrition alone account for roughly 70 percent of total dairy production costs, and a balanced diet underpins both cow health and milk output. Farmers who treat sick animals promptly, house cows appropriately and breed them at the right time effectively convert the genetic potential of crossbred animals into actual liters of milk. The researchers note that this pattern matches earlier findings from Bangladesh and elsewhere showing higher milk yields among technology adopters, reinforcing the conclusion that the technologies themselves, when actually used, have a positive effect on productivity.

Yet the constraint rankings reveal why so many farmers never make that leap. In feeding, the dominant barriers were the high price and low supply of concentrate feed, shortages of green feed and fodder land, and financial limitations. In calf rearing, shortage of green feed, inadequate farmer knowledge and skill, and shortages of veterinary medicines ranked highest. For housing, land shortage, lack of roofing materials and low awareness topped the list. Breeding services were perhaps the most discouraging bottleneck of all: ill-equipped artificial insemination centers offering negligible service ranked first, followed by inefficient synchronization, inadequate AI knowledge, farmers’ ignorance of mating timing, unskilled technicians and a poor supply of quality bulls. Health constraints included no space to isolate sick animals, poor farmer knowledge of vaccines, weak veterinary infrastructure and poor extension services.

The socioeconomic picture compounds these technical problems. Many farmers lack capital to invest in animals, sheds and feed, credit facilities are scarce, interest rates are high, and training on new technologies is limited. The survey found that 68.3 percent of households were male-headed, that the average farmer was 46.2 years old with a family of 5.3 members, and that 30.3 percent of respondents were illiterate while 45.1 percent had only primary schooling. Education and farming experience both correlated with higher adoption rates, consistent with the idea that awareness and decision-making capacity drive uptake of new agricultural practices. Age showed a negative association with adoption in some cited studies, and family size was statistically larger among non-adopters in rural and urban systems, a pattern the authors suggest may reflect better family management awareness among adopters.

The authors’ conclusion is direct: extension services and the use of improved technologies should be intensified across all milk production systems, but especially in the rural system and among non-adopters, where the productivity gap is widest. Rural households in Genfel, dependent on subsistence farming of teff and sorghum, rely on dairying primarily for household nutrition rather than cash income and have minimal exposure to modern technologies due to lack of finance, knowledge and infrastructure. Bridging that gap, the study argues, would raise cow performance where it matters most for food security. The researchers also flag a critical caveat for future work: the benefits of higher productivity can only be realized if dairy farmers have reliable market access for their milk, a factor that remains to be interrogated in this context. For now, the message from Tigray is that the genetics and the technologies exist; the challenge is getting them into farmers’ hands.

Subject of Research: Dairy cattle productivity and adoption of improved dairy technologies among smallholder farmers in Tigray, northern Ethiopia

Article Title: Dairy cattle performance and technology adoption constraints in Tigray, Northern Ethiopia

Article References: Woldegebriel, D., Atsbha, T., Gebremariam, T., & Begashaw, T. (2025). Dairy cattle performance and technology adoption constraints in Tigray, Northern Ethiopia. BMC Agriculture, 1(1), Article 21. https://doi.org/10.1186/s44399-025-00022-w

Image Credits: AI Generated

DOI: 10.1186/s44399-025-00022-w

Keywords: dairy farming, Ethiopia, Tigray, crossbred cattle, technology adoption, milk yield, artificial insemination, smallholder farmers, reproductive performance, feed constraints, extension services, livestock

The research team, led by scientists at Guangxi University in collaboration with the Guangxi Buffalo Research Institute and international partners, performed an integrated transcriptomic analysis on milk-derived RNA from Murrah buffaloes at mid-lactation. The animals were divided into two clearly separated groups based on lactation performance. High-yield buffaloes produced an average of roughly 3,804 kilograms of milk per lactation, while low-yield animals averaged about 1,928 kilograms, a difference of nearly a factor of two. By sequencing the complete RNA content of milk from both groups, the researchers set out to identify the transcriptional features that accompany, and possibly underpin, this dramatic divergence in productivity.

The choice of milk as the sampling medium is one of the study’s most practical innovations. Mammary epithelial cells and other milk-associated cells are shed continuously into milk, meaning a simple sample of the fluid carries a molecular record of the secretory activity inside the udder. Unlike a mammary gland biopsy, milk collection is non-invasive, repeatable, and stress-free for the animal, which matters both for animal welfare and for the feasibility of scaling such measurements to breeding programs. The study’s authors note that no animals were euthanised, anaesthetised, or subjected to invasive procedures, and that the work was approved by the Animal Experiment Ethics Review Committee of Guangxi University.

Sequencing the milk RNA revealed a remarkably complex transcriptomic landscape. In total, the team identified 17,735 messenger RNAs, the protein-coding workhorses of the cell, alongside 2,641 long non-coding RNAs, 6,668 circular RNAs, and 578 microRNAs. This catalogue of four distinct RNA classes is what makes the study integrated rather than a conventional single-layer gene expression analysis. Long non-coding RNAs and circular RNAs can act as molecular sponges that bind microRNAs, thereby modulating how much protein gets produced from messenger RNA transcripts, a regulatory architecture known as the competing endogenous RNA, or ceRNA, network. Capturing all of these layers simultaneously from the same samples allowed the researchers to begin mapping how they interact.

The comparative analysis between high-yield and low-yield animals produced a coherent biological story. Buffaloes with higher milk output showed coordinated upregulation of genes involved in oxidative phosphorylation, the mitochondrial process that converts nutrients into cellular energy in the form of ATP. Genes tied to glucose metabolism, cellular metabolism in general, and protein synthesis were also elevated in the high-yield group. Taken together, these patterns point to an enhanced bioenergetic and biosynthetic state in the milk-associated cells of productive animals. In essence, the secretory cells of high-yielding buffaloes appear to run a hotter metabolic engine, burning more glucose through their mitochondria and building more protein, which is exactly what one would expect from tissue tasked with secreting roughly twice the volume of milk.

Equally telling was what was turned down. Transcripts associated with signal transduction, transporter activity, and apoptosis-related processes showed reduced expression in the high-yield group. Lower expression of apoptosis-related genes suggests that the milk cells of productive animals may resist programmed cell death, potentially sustaining secretory activity for longer. Reduced signalling and transporter transcripts hint at a shift in cellular priorities: rather than communicating with their environment or shuttling molecules across membranes, the cells of high-yield animals appear to channel resources into synthesis and secretion. The researchers are careful to frame these as associations rather than proven causes, describing the work as an exploratory framework, but the consistency of the metabolic signature across functional categories lends it weight.

By integrating the messenger RNA data with the non-coding RNA layers, the team constructed putative ceRNA networks that connect microRNAs, their messenger RNA targets, and the long non-coding and circular RNAs that sequester them. Within these networks, two candidate genes emerged as potentially associated with milk yield-related cellular pathways: SNX25, which encodes sorting nexin 25, a protein involved in intracellular trafficking, and DHPR, which encodes dihydropyridine reductase, an enzyme in the metabolic recycling pathway. These genes now stand as priority targets for future functional validation, the experimental step needed to determine whether they merely correlate with high yield or actively contribute to it.

The implications for buffalo breeding are potentially significant. Traditional genetic selection for milk yield in buffalo has been slowed by long generation intervals, limited pedigree and genomic records in many producing countries, and the sheer difficulty of measuring lactation traits early in an animal’s life. A transcriptomic marker panel derived from milk, measurable without harming the animal and potentially early in a lactation, could complement genomic selection by providing a functional readout of the actual secretory machinery. If the metabolic and ceRNA signatures identified here hold up in larger cohorts and across breeds, they could help identify high-potential animals sooner and guide the development of genetic improvement strategies tailored to buffalo biology rather than borrowed wholesale from dairy cattle.

The study also contributes a substantial public resource to the emerging field of livestock transcriptomics. Cataloguing nearly 18,000 messenger RNAs and thousands of non-coding transcripts from buffalo milk provides a reference for other researchers studying mammary biology, lactation physiology, and even milk quality traits, since many of the same metabolic pathways that drive yield also influence fat and protein composition. The raw sequencing data have been deposited in the Sequence Read Archive, allowing independent verification and reuse. The work was supported by the Guangxi Key Research and Development Program and the National Natural Science Foundation of China, reflecting the strategic importance of buffalo dairy production in southern China and across South Asia.

As with any exploratory transcriptomic study, caveats remain. The findings describe molecular features associated with divergent yield phenotypes at a single lactation stage in one breed, and the ceRNA networks are computational predictions that require experimental confirmation in mammary cells. The authors themselves position the work as a framework and a source of candidate targets rather than a definitive mechanism. Even so, the study marks a step toward a future in which a routine milk sample, already collected on every dairy farm every day, doubles as a molecular diagnostic window into the animal’s productive capacity. For an industry built on the biology of secretion, reading the transcriptome in the milk itself may prove to be one of the most elegant shortcuts breeding science has found in decades.

Subject of Research: Transcriptomic analysis of milk-derived RNA linked to divergent milk yield in buffalo

Article Title: Integrated transcriptomic analysis of milk-derived RNA associated with divergent milk yield phenotypes in buffalo

Article References: Integrated transcriptomic analysis of milk-derived RNA associated with divergent milk yield phenotypes in buffalo. (n.d.). https://doi.org/10.1186/s12864-026-13363-w

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13363-w

Keywords: buffalo, milk yield, transcriptomics, RNA sequencing, non-coding RNAs, ceRNA network, oxidative phosphorylation, lactation, molecular breeding, gene expression, Murrah buffalo, BMC Genomics