Characterizing Milk Production Related Genes in Holstein Using RNA-seq

Genome-Wide Gene-Environment Interaction Analysis Identifies Novel Candidate Variants for Growth Traits in Beef Cattle

Complex traits are widely considered to be the result of a compound regulation of genes, environmental factors, and genotype-by-environment interaction (G × E). The inclusion of G × E in genome-wide association analyses is essential to understand animal environmental adaptations and improve the efficiency of breeding decisions. Here, we systematically investigated the G × E of growth traits (including weaning weight, yearling weight, 18-month body weight, and 24-month body weight) with environmental factors (farm and temperature) using genome-wide genotype-by-environment interaction association studies (GWEIS) with a dataset of 1350 cattle. We validated the robust estimator's effectiveness in GWEIS and detected 29 independent interacting SNPs with a significance threshold of 1.67 × 10-6, indicating that these SNPs, which do not show main effects in traditional genome-wide association studies (GWAS), may have non-additive effects across genotypes but are obliterated by environmental means. The gene-based analysis using MAGMA identified three genes that overlapped with the GEWIS results exhibiting G × E, namely SMAD2, PALMD, and MECOM. Further, the results of functional exploration in gene-set analysis revealed the bio-mechanisms of how cattle growth responds to environmental changes, such as mitotic or cytokinesis, fatty acid β-oxidation, neurotransmitter activity, gap junction, and keratan sulfate degradation. This study not only reveals novel genetic loci and underlying mechanisms influencing growth traits but also transforms our understanding of environmental adaptation in beef cattle, thereby paving the way for more targeted and efficient breeding strategies.

Genetic legacy and adaptive signatures: investigating the history, diversity, and selection signatures in Rendena cattle resilient to eighteenth century rinderpest epidemics

BACKGROUND

Rendena is a dual-purpose cattle breed, which is primarily found in the Italian Alps and the eastern areas of the Po valley, and recognized for its longevity, fertility, disease resistance and adaptability to steep Alpine pastures. It is categorized as 'vulnerable to extinction' with only 6057 registered animals in 2022, yet no comprehensive analyses of its molecular diversity have been performed to date. The aim of this study was to analyse the origin, genetic diversity, and genomic signatures of selection in Rendena cattle using data from samples collected in 2000 and 2018, and shed light on the breed's evolution and conservation needs.

RESULTS

Genetic analysis revealed that the Rendena breed shares genetic components with various Alpine and Po valley breeds, with a marked genetic proximity to the Original Braunvieh breed, reflecting historical restocking efforts across the region. The breed shows signatures of selection related to both milk and meat production, environmental adaptation and immune response, the latter being possibly the result of multiple rinderpest epidemics that swept across the Alps in the eighteenth century. An analysis of the Rendena cattle population spanning 18 years showed an increase in the mean level of inbreeding over time, which is confirmed by the mean number of runs of homozygosity per individual, which was larger in the 2018 sample.

CONCLUSIONS

The Rendena breed, while sharing a common origin with Brown Swiss, has developed distinct traits that enable it to thrive in the Alpine environment and make it highly valued by local farmers. Preserving these adaptive features is essential, not only for maintaining genetic diversity and enhancing the ability of this traditional animal husbandry to adapt to changing environments, but also for guaranteeing the resilience and sustainability of both this livestock system and the livelihoods within the Rendena valley.

A review of the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle

In the past few decades, genomic selection and other refined strategies have been used to increase the growth rate and lean meat production of beef cattle. Nevertheless, the fast growth rates of cattle breeds are often accompanied by a reduction in intramuscular fat (IMF) deposition, impairing meat quality. Transcription factors play vital roles in regulating adipogenesis and lipogenesis in beef cattle. Meanwhile, understanding the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle has gained significant attention to increase IMF deposition and meat quality. Therefore, the aim of this paper was to provide a comprehensive summary and valuable insight into the complex role of transcription factors in adipogenesis and lipogenesis in beef cattle. This review summarizes the contemporary studies in transcription factors in adipogenesis and lipogenesis, genome-wide analysis of transcription factors, epigenetic regulation of transcription factors, nutritional regulation of transcription factors, metabolic signalling pathways, functional genomics methods, transcriptomic profiling of adipose tissues, transcription factors and meat quality and comparative genomics with other livestock species. In conclusion, transcription factors play a crucial role in promoting adipocyte development and fatty acid biosynthesis in beef cattle. They control adipose tissue formation and metabolism, thereby improving meat quality and maintaining metabolic balance. Understanding the processes by which these transcription factors regulate adipose tissue deposition and lipid metabolism will simplify the development of marbling or IMF composition in beef cattle.

Genomic selection pressure discovery using site-frequency spectrum and reduced local variability statistics in Pakistani Dera-Din-Panah goat

BACKGROUND

Population geneticists have long sought to comprehend various selection traces accumulated in the goat genome due to natural or human driven artificial selection through breeding practices, which led the wild animals to domestication, so understanding evolutionary process may helpful to utilize the full genetic potential of goat genome.

METHODS AND RESULTS

As a step forward to pinpoint the selection signals in Pakistani Dera-Din-Panah (DDP) goat, whole-genome pooled sequencing (n = 12) was performed, and 618,236,192 clean paired-end reads were mapped against ARS1 reference goat assembly. Five different selection signature statistics were applied using four site-frequency spectrum (SFS) methods (Tajima's D ([Formula: see text]), Fay and Wu's H ([Formula: see text]), Zeng's E ([Formula: see text]), [Formula: see text]) and one reduced local variability approach named pooled heterozygosity ([Formula: see text]). The under-selection regions were annotated with significant threshold values of [Formula: see text]≥4.7, [Formula: see text]≥6, [Formula: see text]≥2.5, Pool-HMM ≥ 12, and [Formula: see text]≥5 that resulted in accumulative 364 candidate gene hits. The highest genomic selection signals were observed on Chr. 4, 6, 10, 12, 15, 16, 18, 20, and 27 and harbor ADAMTS6, CWC27, RELN, MYCBP2, FGF14, STIM1, CFAP74, GNB1, CALML6, TMEM52, FAM149A, NADK, MMP23B, OPN3, FH, MFHAS1, KLKB1, RRM1, KMO, SPEF2, F11, KIT, KMO, ERI1, ATP8B4, and RHOG genes. Next, the validation of our captured genomic hits was also performed by more than one applied statistics which harbor meat production, immunity, and reproduction associated genes to strengthen our hypothesis of under-selection traits in this Pakistani goat breed. Furthermore, common candidate genes captured by more than one statistical method were subjected to gene ontology and KEGG pathway analysis to get insights of particular biological processes associated with this goat breed.

CONCLUSION

Current perception of genomic architecture of DDP goat provides a better understanding to improve its genetic potential and other economically important traits of medium to large body size, milk, and fiber production by updating the genomic insight driven breeding strategies to boost the livestock and agriculture-based economy of the country.

Transcriptome-wide mapping of milk somatic cells upon subclinical mastitis infection in dairy cattle

BACKGROUND

Subclinical intramammary infection (IMI) represents a significant problem in maintaining dairy cows' health. Disease severity and extent depend on the interaction between the causative agent, environment, and host. To investigate the molecular mechanisms behind the host immune response, we used RNA-Seq for the milk somatic cells (SC) transcriptome profiling in healthy cows (n = 9), and cows naturally affected by subclinical IMI from Prototheca spp. (n = 11) and Streptococcus agalactiae (S. agalactiae; n = 11). Data Integration Analysis for Biomarker discovery using Latent Components (DIABLO) was used to integrate transcriptomic data and host phenotypic traits related to milk composition, SC composition, and udder health to identify hub variables for subclinical IMI detection.

RESULTS

A total of 1,682 and 2,427 differentially expressed genes (DEGs) were identified when comparing Prototheca spp. and S. agalactiae to healthy animals, respectively. Pathogen-specific pathway analyses evidenced that Prototheca's infection upregulated antigen processing and lymphocyte proliferation pathways while S. agalactiae induced a reduction of energy-related pathways like the tricarboxylic acid cycle, and carbohydrate and lipid metabolism. The integrative analysis of commonly shared DEGs between the two pathogens (n = 681) referred to the core-mastitis response genes, and phenotypic data evidenced a strong covariation between those genes and the flow cytometry immune cells (r² = 0.72), followed by the udder health (r² = 0.64) and milk quality parameters (r² = 0.64). Variables with r ≥ 0.90 were used to build a network in which the top 20 hub variables were identified with the Cytoscape cytohubba plug-in. The genes in common between DIABLO and cytohubba (n = 10) were submitted to a ROC analysis which showed they had excellent predictive performances in terms of discriminating healthy and mastitis-affected animals (sensitivity > 0.89, specificity > 0.81, accuracy > 0.87, and precision > 0.69). Among these genes, CIITA could play a key role in regulating the animals' response to subclinical IMI.

CONCLUSIONS

Despite some differences in the enriched pathways, the two mastitis-causing pathogens seemed to induce a shared host immune-transcriptomic response. The hub variables identified with the integrative approach might be included in screening and diagnostic tools for subclinical IMI detection.

Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis

Mastitis, inflammation of the mammary gland, is the most prevalent disease in dairy cattle that has a potential impact on profitability and animal welfare. Specifically designed multi-omics studies can be used to prioritize candidate genes and identify biomarkers and the molecular mechanisms underlying mastitis in dairy cattle. Hence, the present study aimed to explore the genetic basis of bovine mastitis by integrating microarray and RNA-Seq data containing healthy and mastitic samples in comparative transcriptome analysis with the results of published genome-wide association studies (GWAS) using a literature mining approach. The integration of different information sources resulted in the identification of 33 common and relevant genes associated with bovine mastitis. Among these, seven genes—CXCR1, HCK, IL1RN, MMP9, S100A9, GRO1, and SOCS3—were identified as the hub genes (highly connected genes) for mastitis susceptibility and resistance, and were subjected to protein-protein interaction (PPI) network and gene regulatory network construction. Gene ontology annotation and enrichment analysis revealed 23, 7, and 4 GO terms related to mastitis in the biological process, molecular function, and cellular component categories, respectively. Moreover, the main metabolic-signalling pathways responsible for the regulation of immune or inflammatory responses were significantly enriched in cytokine–cytokine-receptor interaction, the IL-17 signaling pathway, viral protein interaction with cytokines and cytokine receptors, and the chemokine signaling pathway. Consequently, the identification of these genes, pathways, and their respective functions could contribute to a better understanding of the genetics and mechanisms regulating mastitis and can be considered a starting point for future studies on bovine mastitis.

Transcriptome study underling difference of milk yield during peak lactation of Kazakh horse

This study was designed to provide a basis for further understanding of the mechanism of lactation based on mRNA expression differences in milk fat between different milk yields in Kazakh horses. Total RNA was extracted from the milk fat during the peak of lactation period. A total of 310 differentially expressed genes (DEGs) were identified by comparative transcriptome analysis of the high-yield and low-yield group. These DEGs regulate lactation by participated in AMPK signaling pathway, FoxO signaling pathway, ErbB signaling pathway, VEGF signaling pathway. In addition, we performed quantitative PCR to validated 5 selected DEGs and the results were in agreement with RNA-seq analysis. A new profile has been established for revealing the mechanism of equid's mammalian lactation.

Lactation Associated Genes Revealed in Holstein Dairy Cows by Weighted Gene Co-Expression Network Analysis (WGCNA)

Simple Summary

Weighted gene coexpression network analysis (WGCNA) is a novel approach that can quickly analyze the relationships between genes and traits. In the past few years, studies on the gene expression changes of dairy cow mammary glands were only based on transcriptome comparisons between two lactation stages. Few studies focused on the relationships between gene expression of the dairy mammary gland and lactation stage or milk composition in a lactation cycle. In this study, we detected milk yield and composition in a lactation cycle. For the first time, we constructed a gene coexpression network using WGCNA on the basis of 18 gene expression profiles during six stages of a lactation cycle by transcriptome sequencing, generating 10 specific modules. Genes in each module were performed with gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Module–trait relationship analysis showed a series of potential candidates related to milk yield and composition. The current study provides an important theoretical basis for the further molecular breeding of dairy cows.

Abstract

Weighted gene coexpression network analysis (WGCNA) is a novel approach that can quickly analyze the relationships between genes and traits. In this study, the milk yield, lactose, fat, and protein of Holstein dairy cows were detected in a lactation cycle. Meanwhile, a total of 18 gene expression profiles were detected using mammary glands from six lactation stages (day 7 to calving, −7 d; day 30 post-calving, 30 d; day 90 post-calving, 90 d; day 180 post-calving, 180 d; day 270 post-calving, 270 d; day 315 post-calving, 315 d). On the basis of the 18 profiles, WGCNA identified for the first time 10 significant modules that may be related to lactation stage, milk yield, and the main milk composition content. Genes in the 10 significant modules were examined with gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The results revealed that the galactose metabolism pathway was a potential candidate for milk yield and milk lactose synthesis. In −7 d, ion transportation was more frequent and cell proliferation related terms became active. In late lactation, the suppressor of cytokine signaling 3 (SOCS3) might play a role in apoptosis. The sphingolipid signaling pathway was a potential candidate for milk fat synthesis. Dairy cows at 315 d were in a period of cell proliferation. Another notable phenomenon was that nonlactating dairy cows had a more regular circadian rhythm after a cycle of lactation. The results provide an important theoretical basis for the further molecular breeding of dairy cows.

Identification of novel molecular markers of mastitis caused by Staphylococcus aureus using gene expression profiling in two consecutive generations of Chinese Holstein dairy cattle

Background

Mastitis in dairy cows caused by Staphylococcus aureus is a major problem hindering economic growth in dairy farms worldwide. It is difficult to prevent or eliminate due to its asymptomatic nature and long persistence of infection. Although transcriptomic responses of bovine mammary gland cells to pathogens that cause mastitis have been studied, the common responses of peripheral blood leukocytes to S. aureus infection across two consecutive generations of dairy cattle have not been investigated.

Methods

In the current study, RNA-Seq was used to profile the transcriptomes of peripheral blood leukocytes sampled from S. aureus-infected mothers and their S. aureus-infected daughters, and also healthy non-infected mothers and their healthy daughters. Differential gene expression was evaluated as follows: 1) S. aureus-infected cows versus healthy non-infected cows (S vs. H, which include all the mothers and daughters), 2) S. aureus-infected mothers versus healthy non-infected mothers (SM vs. HM), and 3) S. aureus-infected daughters versus healthy non-infected daughters (SMD vs. HMD).

Results

Analysis of all identified expressed genes in the four groups (SM, SMD, HM, and HMD) showed that EPOR, IL9, IFNL3, CCL26, IL26 were exclusively expressed in both the HM and HMD groups, and that they were significantly (P <  0.05) enriched for the cytokine-cytokine receptor interaction pathway. A total of 17, 13 and 10 differentially expressed genes (DEGs) (FDR P_adj. < 0.1 and |FC| > 1.2) were detected in the three comparisons, respectively. DEGs with P <  0.05 and |FC| > 2 were used for functional enrichment analyses. For the S vs. H comparison, DEGs detected included CCL20, IL13 and MMP3, which are associated with the IL-17 signaling pathway. In the SM vs. HM and SMD vs. HMD comparisons, five (BLA-DQB, C1R, C2, FCGR1A, and KRT10) and six (BLA-DQB, C3AR1, CFI, FCAR, FCGR3A, and LOC10498484) genes, respectively, were involved in the S. aureus infection pathway.

Conclusions

Our study provides insights into the transcriptomic responses of bovine peripheral blood leukocytes across two generations of cattle naturally infected with S. aureus. The genes highlighted in this study could serve as expression biomarkers for mastitis and may also contain sequence variation that can be used for genetic improvement of dairy cattle for resilience to mastitis.

Overview of Folic Acid Supplementation Alone or in Combination with Vitamin B12 in Dairy Cattle during Periparturient Period

The periparturient period is the period from three weeks before calving to three weeks post-calving. This period is important in terms of health, productivity and profitability, and is fundamental to successful lactation. During this period, the animal experiences stress because of hormonal changes due to pregnancy and the significant rise in milk production. In addition, a negative energy balance usually occurs, because the demand for nutrients to sustain milk production increases by more than the nutrient supply during the periparturient period. The immunity of dairy cattle is suppressed around parturition, which increases their susceptibility to infections. Special care regarding nutrition can reduce the risks of metabolism and immunity depression, which dairy cattle face during the periparturient span. Folic acid is relevant in this regard because of its critical role in the metabolism to maintain lactational performance and to improve health. Being a donor of one-carbon units, folic acid has a vital role in DNA and RNA biosynthesis. Generally, the folic acid requirements of dairy cattle can be met by the microbial synthesis in the rumen; however, in special cases, such as during the periparturient period, the requirement for this vitamin strictly increases. Vitamin B12 also has a critical role in the metabolism as a coenzyme of the enzyme methionine synthase for the transfer of a methyl group from folic acid to homocysteine for the regeneration of methionine. In the current review, we highlight the issues facing periparturient dairy cattle, and relevant knowledge and practices, and point out future research directions for utilization of the associated vitamins in ruminants, especially during the periparturient period.

Comparison of the Transcriptome of the Ovine Mammary Gland in Lactating and Non-lactating Small-Tailed Han Sheep

Small-Tailed Han (STH) sheep are known for their high fecundity, but the survival of lambs is compromised and influences the commercial return from farming these sheep, with this being attributed in part to starvation from insufficient milk production by the ewes. In this study, the transcriptome profiles of the mammary gland of lactating and non-lactating STH ewes were investigated using paired-end RNA sequencing (RNA-Seq). An average of 14,447 genes were found to be expressed at peak-lactation in the STH sheep, while 15,146 genes were expressed in non-lactating ewes. A total of 4,003 differentially expressed genes (DEGs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the DEGs were associated with a wide range of cellular components, biological processes and metabolic pathways, including binding activities, signaling pathways, cellular structures, and immune responses. The most highly expressed genes at peak-lactation included CSN2, LGB, LALBA, CSN1S1, CSN1S2, and CSN3, and the 10 most highly expressed genes accounted for 61.37% of the total Reads Per Kilobase of transcript, per Million mapped reads (RPKM). The most highly expressed genes in the mammary gland of non-lactating ewes included IgG, THYMB4X, EEF1A1, IgA, and APOE, and the 10 most highly expressed genes accounted for only 12.97% of the total gene RPKM values. This suggests that the sheep mammary gland undergoes a substantial development in milk protein synthesis infrastructure and promotion of protein transportation during lactation.

Folic acid supplementation regulates milk production variables, metabolic associated genes and pathways in perinatal Holsteins

Perinatal period is the critical time in dairy cattle due to negative energy balance and high milk production stress. Being a key role in biosynthesis and methylation cycle, folic acid is considered essential for lactational and metabolic performance in dairy cattle. Thus, the current study was designed to evaluate the effect of folic acid supplementation on milk production phenotypic traits in periparturient cows. Transcriptomic screening was performed for milk production and metabolism-associated differentially expressed genes. The 123 cows having similar parity, weight and expected date of calving were randomly selected and divided into three groups; A (n = 41, folic acid 240 mg/500 kg cow/day), B (n = 40, FA 120 mg/500 kg cow/day) and C (Control, n = 42). Folic acid was supplemented for 21 days (14 days pre- and seven days post-calving), and three samples of blood lymphocytes were taken on day seven post-calving from each folic acid-treated and control group. In addition, the milk samples for each folic acid-treated group have been collected at 2nd, 3rd and 4th month of lactation. The increase in average milk yield noticed in group B were significantly (p-value < .05) higher than C and A. However, the data showed no noteworthy differences for milk fat and milk protein among the three groups. The transcriptomic analysis revealed that folic acid treatment regulated many key metabolic-related genes (DGAT2, ALOX5, LAP3, GPAT3, GGH, ALDOA, TKT) and pathways (glycolysis, folate biosynthesis, glutathione metabolism, etc.) in periparturient dairy cattle. It was concluded from the above findings that 120 mg/500 kg of folic acid quantity could be considered as a standard during the periparturient period to enhance the milk production performance of dairy cows. The transcriptomic profile revealed several metabolic and milk production-associated genes which could be a useful addition to the marker selection for the enhancement of metabolism and milk production of periparturient dairy cows.

Nutrigenomic Role of Acetate and β-Hydroxybutyrate in Bovine Mammary Epithelial Cells

Acetate and β-hydroxybutyrate (BHBA) are the predominant substrates for de novo fatty acid (FA) synthesis in mammary gland of dairy cow. To investigate the nutrigenomic role of acetate and BHBA in bovine mammary epithelial cells during milk fat production, RNA sequencing (RNA-seq) transcriptomic analysis was used to identify differentially expressed genes (DEGs) between acetate- and BHBA-treated cells (high-milk fat cells) and control cells. A total of 625 DEGs (358 upregulated and 267 downregulated) were identified between the high-milk fat cells and control cells. Gene ontology enrichment analysis revealed that the upregulated genes in high-milk fat cells were mainly involved in lipid biosynthetic process, steroid biosynthetic process, oxidation-reduction process, receptor binding, and vesicle and small molecule biosynthetic process. The downregulated genes were mainly associated with immune response, cytokine production, negative regulation of biological process, and peptidyl-threonine modification. Pathway analysis indicated that FA metabolism and steroid biosynthesis were significantly enriched for the upregulated genes in the high-milk fat cells, while apoptosis was enriched for the downregulated genes. This work provides a profile of gene expression changes that occur during acetate- and BHBA-induced milk fat synthesis in bovine mammary epithelial cells, which furthers our understanding of the molecular regulation of lipid metabolism.

Transcriptome Analysis Reveals Potential Regulatory Genes Related to Heat Tolerance in Holstein Dairy Cattle

Heat stress affects the physiology and production performance of Chinese Holstein dairy cows. As such, the selection of heat tolerance in cows and elucidating its underlying mechanisms are vital to the dairy industry. This study aimed to investigate the heat tolerance associated genes and molecular mechanisms in Chinese Holstein dairy cows using a high-throughput sequencing approach and bioinformatics analysis. Heat-induced physiological indicators and milk yield changes were assessed to determine heat tolerance levels in Chinese Holstein dairy cows by Principal Component Analysis method following Membership Function Value Analysis. Results indicated that rectal temperature (RT), respiratory rate (RR), and decline in milk production were significantly lower (p < 0.05) in heat tolerant (HT) cows while plasma levels of heat shock protein (HSP: HSP70, HSP90), and cortisol were significantly higher (p < 0.05) when compared to non-heat tolerant (NHT) Chinese Holstein dairy cows. By applying RNA-Seq analysis, we identified 200 (81 down-regulated and 119 up-regulated) significantly (|log2fold change| ≥ 1.4 and p ≤ 0.05) differentially expressed genes (DEGs) in HT versus NHT Chinese Holstein dairy cows. In addition, 14 of which were involved in protein–protein interaction (PPI) network. Importantly, several hub genes (OAS2, MX2, IFIT5 and TGFB2) were significantly enriched in immune effector process. These findings might be helpful to expedite the understanding for the mechanism of heat tolerance in Chinese Holstein dairy cows.

Whole blood transcriptome analysis reveals footprints of cattle adaptation to sub-arctic conditions

Indigenous cattle breeds in northern Eurasia have adapted to harsh climate conditions. The local breeds are important genetic resources with cultural and historical heritages, and therefore, their preservation and genetic characterization are important. In this study, we profiled the whole‐blood transcriptome of two native breeds (Northern Finncattle and Yakutian cattle) and one commercial breed (Holstein) using high‐throughput RNA sequencing. More than 15 000 genes were identified, of which two, 89 and 162 genes were significantly upregulated exclusively in Northern Finncattle, Yakutian cattle and Holstein cattle respectively. The functional classification of these significantly differentially expressed genes identified several biological processes and pathways related to signalling mechanisms, cell differentiation and host–pathogen interactions that, in general, point towards immunity and disease resistance mechanisms. The gene expression pattern observed in Northern Finncattle was more similar to that of Yakutian cattle, despite sharing similar living conditions with the Holstein cattle included in our study. In conclusion, our study identified unique biological processes in these breeds that may have helped them to adapt and survive in northern and sub‐arctic environments.

Identifying Hub Genes for Heat Tolerance in Water Buffalo (Bubalus bubalis) Using Transcriptome Data

Heat stress has a detrimental effect on the physiological and production performance of buffaloes. Elucidating the underlying mechanisms of heat stress is challenging, therefore identifying candidate genes is urgent and necessary. We evaluated the response of buffaloes (n = 30) to heat stress using the physiological parameters, ELISA indexes, and hematological parameters. We then performed mRNA and microRNA (miRNA) expression profiles analysis between heat tolerant (HT, n = 4) and non-heat tolerant (NHT, n = 4) buffaloes, as well as the specific modules, significant genes, and miRNAs related to the heat tolerance identified using the weighted gene co-expression network analysis (WGCNA). The results indicated that the buffaloes in HT had a significantly lower rectal temperature (RT) and respiratory rate (RR) and displayed a higher plasma heat shock protein (HSP70 and HSP90) and cortisol (COR) levels than those of NHT buffaloes. Differentially expressed analysis revealed a total of 753 differentially expressed genes (DEGs) and 16 differentially expressed miRNAs (DEmiRNAs) were identified between HT and NHT. Using the WGCNA analysis, these DEGs assigned into 5 modules, 4 of which were significantly correlation with the heat stress indexes. Interestingly, 158 DEGs associated with heat tolerance in the turquoise module were identified, 35 of which were found within the protein-protein interaction network. Several hub genes (IL18RAP, IL6R, CCR1, PPBP, IL1B, and IL1R1) were identified that significantly enriched in the Cytokine-cytokine receptor interaction. The findings may help further elucidate the underlying mechanisms of heat tolerance in buffaloes.

Transcriptional profiling of two different physiological states of the yak mammary gland using RNA sequencing

Yak milk is superior to common cow milk in nutrients including protein, fat and calories. However, the milk yield of the yak is very much lower compared with other dairy bovines. To understand the molecular mechanisms of lactogenesis, lactation and mammary gland development, mammary tissue samples were taken from five yaks during a dry period (DP, n = 3) and lactation period (LP, n = 2). Two types of cDNA sequence libraries that reflected the different physiological states of the mammary gland were constructed using RNA sequencing technology. After removing reads containing adapters, reads containing poly-N and low-quality reads from the raw data, 45,423,478 to 53,274,976 clean reads were obtained from these libraries. A total of 74.72% to 80.65% of the high-quality sequence reads were uniquely aligned to the BosGru v2.0 yak reference genome. Using the DESeq R package, 360 differentially expressed genes were detected between the two groups when the adjusted P value (padj < 0.05) was used as the cutoff value; this included 192 upregulated and 168 downregulated genes in the yak mammary gland tissue of the DP compared to the LP. A gene ontology analysis revealed that the most enriched GO terms were protein binding, multi-organism process, immune system and others. KEGG pathway analysis indicated that the differentially expressed genes were mostly enriched in Hippo signaling, insulin signaling, steroid biosynthesis and others. The analysis of the up- and downregulated genes provides important insights into the molecular events involved in lactogenesis, lactation and mammary gland development and will guide further research to enhance milk yield and optimize the constituents of yak milk.

Transcriptomic profiles of the bovine mammary gland during lactation and the dry period

The initiation and maintenance of lactation are complex phenomena governed by biochemical and endocrine processes in the mammary gland (MG). Although DNA-based approaches have been used to study the onset of lactation, more comprehensive RNA-based techniques may be critical in furthering our understanding of gene alterations that occur to support lactation in the bovine MG. To further determine how gene profiles vary during lactation compared with the dry period, RNA-seq transcriptomic analysis was used to identify differentially expressed genes (DEG) in bovine MG tissues from animals that were lactating and not lactating. A total of 881 DEG (605 upregulated and 276 downregulated) were identified in MG of 3 lactating Chinese Holstein dairy cows versus the 3 dry cows. The subcellular analysis showed that the upregulated genes were most abundantly located in "integral to membrane" and "mitochondrion," and the top number of downregulated genes existed in "nucleus" and "cytoplasm." The functional analysis indicated that the DEG were primarily associated with the support of lactation processes. The genes in higher abundance were most related to "metabolic process," "oxidation-reduction process," "transport" and "signal transduction," protein synthesis-related processes (transcription, translation, protein modifications), and some MG growth-associated processes (cell proliferation/cycle/apoptosis). The downregulated genes were mainly involved in immune-related processes (inflammatory/immune/defense responses). The KEGG analysis suggested that protein synthesis-related pathways (such as protein digestion and absorption; protein processing in endoplasmic reticulum; and glycine, serine, and threonine metabolism) were highly and significantly enriched in the bovine MG of lactating cows compared to dry cows. The results suggested that the dry cows had decreased capacity for protein synthesis, energy generation, and cell growth but enhanced immune response. Collectively, this reduced capacity in dry cows supports the physiological demands of the next lactation and the coordinated metabolic changes that occur to support these demands. A total of 51 identified DEG were validated by RT-PCR, and consistent results were found between RT-PCR and the transcriptomic analysis. This work provides a profile of gene-associated changes that occur during lactation and can be used to facilitate further investigation of the mechanisms underlying lactation in dairy cows.

Genome-wide association studies to identify quantitative trait loci affecting milk production traits in water buffalo

Water buffalo is the second largest resource of milk supply around the world, and it is well known for its distinctive milk quality in terms of fat, protein, lactose, vitamin, and mineral contents. Understanding the genetic architecture of milk production traits is important for future improvement by the buffalo breeding industry. The advance of genome-wide association studies (GWAS) provides an opportunity to identify potential genetic variants affecting important economical traits. In the present study, GWAS was performed for 489 buffaloes with 1,424 lactation records using the 90K Affymetrix Buffalo SNP Array (Affymetrix/Thermo Fisher Scientific, Santa Clara, CA). Collectively, 4 candidate single nucleotide polymorphisms (SNP) in 2 genomic regions were found to associate with buffalo milk production traits. One region affecting milk fat and protein percentage was located on the equivalent of Bos taurus autosome (BTA)3, spanning 43.3 to 43.8 Mb, which harbored the most likely candidate genes MFSD14A, SLC35A3, and PALMD. The other region on the equivalent of BTA14 at 66.5 to 67.0 Mb contained candidate genes RGS22 and VPS13B and influenced buffalo total milk yield, fat yield, and protein yield. Interestingly, both of the regions were reported to have quantitative trait loci affecting milk performance in dairy cattle. Furthermore, we suggest that buffaloes with the C allele at AX-85148558 and AX-85073877 loci and the G allele at AX-85106096 locus can be selected to improve milk fat yield in this buffalo-breeding program. Meanwhile, the G allele at AX-85063131 locus can be used as the favorable allele for improving milk protein percentage. Genomic prediction showed that the reliability of genomic estimated breeding values (GEBV) of 6 milk production traits ranged from 0.06 to 0.22, and the correlation between estimated breeding values and GEBV ranged from 0.23 to 0.35. These findings provide useful information to understand the genetic basis of buffalo milk properties and may play a role in accelerating buffalo breeding programs using genomic approaches.

RNA-seq analysis for detecting quantitative trait-associated genes

Many recent RNA-seq studies were focused mainly on detecting the differentially expressed genes (DEGs) between two or more conditions. In contrast, only a few attempts have been made to detect genes associated with quantitative traits, such as obesity index and milk yield, on RNA-seq experiment with large number of biological replicates. This study illustrates the linear model application on trait associated genes (TAGs) detection in two real RNA-seq datasets: 89 replicated human obesity related data and 21 replicated Holsteins’ milk production related RNA-seq data. Based on these two datasets, the performance between suggesting methods, such as ordinary regression and robust regression, and existing methods: DESeq2 and Voom, were compared. The results indicate that suggesting methods have much lower false discoveries compared to the precedent two group comparisons based approaches in our simulation study and qRT-PCR experiment. In particular, the robust regression outperforms existing DEG finding method as well as ordinary regression in terms of precision. Given the current trend in RNA-seq pricing, we expect our methods to be successfully applied in various RNA-seq studies with numerous biological replicates that handle continuous response traits.