Bioinformatics and Gene Network Analyses of the Swine Mammary Gland Transcriptome during Late Gestation

A cell transcriptomic profile provides insights into adipocytes of porcine mammary gland across development

BACKGROUND

Studying the composition and developmental mechanisms in mammary gland is crucial for healthy growth of newborns. The mammary gland is inherently heterogeneous, and its physiological function dependents on the gene expression of multiple cell types. Most studies focused on epithelial cells, disregarding the role of neighboring adipocytes.

RESULTS

Here, we constructed the largest transcriptomic dataset of porcine mammary gland cells thus far. The dataset captured 126,829 high-quality nuclei from physiological mammary glands across five developmental stages (d 90 of gestation, G90; d 0 after lactation, L0; d 20 after lactation, L20; 2 d post natural involution, PI2; 7 d post natural involution, PI7). Seven cell types were identified, including epithelial cells, adipocytes, endothelial cells, fibroblasts cells, immune cells, myoepithelial cells and precursor cells. Our data indicate that mammary glands at different developmental stages have distinct phenotypic and transcriptional signatures. During late gestation (G90), the differentiation and proliferation of adipocytes were inhibited. Meanwhile, partly epithelial cells were completely differentiated. Pseudo-time analysis showed that epithelial cells undergo three stages to achieve lactation, including cellular differentiation, hormone sensing, and metabolic activation. During lactation (L0 and L20), adipocytes area accounts for less than 0.5% of mammary glands. To maintain their own survival, the adipocyte exhibited a poorly differentiated state and a proliferative capacity. Epithelial cells initiate lactation upon hormonal stimulation. After fulfilling lactation mission, their undergo physiological death under high intensity lactation. Interestingly, the physiological dead cells seem to be actively cleared by immune cells via CCL21-ACKR4 pathway. This biological process may be an important mechanism for maintaining homeostasis of the mammary gland. During natural involution (PI2 and PI7), epithelial cell populations dedifferentiate into mesenchymal stem cells to maintain the lactation potential of mammary glands for the next lactation cycle.

CONCLUSION

The molecular mechanisms of dedifferentiation, proliferation and redifferentiation of adipocytes and epithelial cells were revealed from late pregnancy to natural involution. This cell transcriptomic profile constitutes an essential reference for future studies in the development and remodeling of the mammary gland at different stages.

Characterization and comparative analysis of transcriptional profiles of porcine colostrum and mature milk at different parities

BACKGROUND

Porcine milk is a complex fluid, containing a myriad of immunological, biochemical, and cellular components, made to satisfy the nutritional requirements of the neonate. Whole milk contains many different cell types, including mammary epithelial cells, neutrophils, macrophages, and lymphocytes, as well nanoparticles, such as milk exosomes. To-date, only a limited number of livestock transcriptomic studies have reported sequencing of milk. Moreover, those studies focused only on sequencing somatic cells as a proxy for the mammary gland with the goal of investigating differences in the lactation process. Recent studies have indicated that RNA originating from multiple cell types present in milk can withstand harsh environments, such as the digestive system, and transmit regulatory molecules from maternal to neonate. Transcriptomic profiling of porcine whole milk, which is reflective of the combined cell populations, could help elucidate these mechanisms. To this end, total RNA from colostrum and mature milk samples were sequenced from 65 sows at differing parities. A stringent bioinformatic pipeline was used to identify and characterize 70,841 transcripts.

RESULTS

The 70,841 identified transcripts included 42,733 previously annotated transcripts and 28,108 novel transcripts. Differential gene expression analysis was conducted using a generalized linear model coupled with the Lancaster method for P-value aggregation across transcripts. In total, 1667 differentially expressed genes (DEG) were identified for the milk type main effect, and 33 DEG were identified for the milk type x parity interaction. Several gene ontology (GO) terms related to immune response were significant for the milk type main effect, supporting the well-known fact that immunoglobulins and immune cells are transferred to the neonate via colostrum.

CONCLUSIONS

This is the first study to perform global transcriptome analysis from whole milk samples in sows from different parities. Our results provide important information and insight into synthesis of milk proteins and innate immunity and potential targets for future improvement of swine lactation and piglet development.

Milk somatic cell derived transcriptome analysis identifies regulatory genes and pathways during lactation in Indian Sahiwal cattle (Bos indicus)

BACKGROUND

The present study is an effort to understand the genomic drivers of lactation in Sahiwal (Bos indicus), the best milch cattle breed of the tropics.

METHODS

RNA sequencing of four animals from early, mid and late lactation stages was performed using milk somatic cells as source of RNA.

RESULTS

The genes encoding the milk casein and whey proteins showed highest expression in early and mid lactation, with a declining trend towards the late stage. The enhanced expression of PLIN2, FABP5 and FABP3 genes in mid lactation suggests enrichment of the PPARα pathway which is linked to fatty acid metabolism. A gradual decline in the percentage of genes involved in metabolism of proteins, mRNA and insulin synthesis from early to late lactation reflected transition from lactogenesis to involution. Major biological pathways maintained throughout lactation were adaptive immune system, FGF signaling, EGFR signaling, activated TLR4 signaling, NFkB and MAP kinases activation mediated by TLR4 signaling repertoire. Differential expression analysis revealed 547, 1010 and 1313 differentially expressed genes (p < 0.05) between early-late, early-mid and mid-late stages, respectively. The topmost regulatory genes identified by network analysis from the differentially expressed genes, were involved in Chemokine receptor, GPCR and EGFR1 pathways.

CONCLUSION

The genes and pathways delineated in this study have regulatory implications in cell morphogenesis, lipid droplet formation and protein synthesis in the course of lactation. The study provides an insight into the expression profile of genes influencing milk properties and lactation in Sahiwal cattle.

Cortical Granule Distribution and Expression Pattern of Genes Regulating Cellular Component Size, Morphogenesis, and Potential to Differentiation are Related to Oocyte Developmental Competence and Maturational Capacity In Vivo and In Vitro

Polyspermia is an adverse phenomenon during mammalian fertilization when more than one sperm fuses with a single oocyte. The egg cell is prepared to prevent polyspermia by, among other ways, producing cortical granules (CGs), which are specialized intracellular structures containing enzymes that aim to harden the zona pellucida and block the fusion of subsequent sperm. This work focused on exploring the expression profile of genes that may be associated with cortical reactions, and evaluated the distribution of CGs in immature oocytes and the peripheral density of CGs in mature oocytes. Oocytes were isolated and then processed for in vitro maturation (IVM). Transcriptomic analysis of genes belonging to five ontological groups has been conducted. Six genes showed increased expression after IVM (ARHGEF2, MAP1B, CXCL12, FN1, DAB2, and SOX9), while the majority of genes decreased expression after IVM. Using CG distribution analysis in immature oocytes, movement towards the cortical zone of the oocyte during meiotic competence acquisition was observed. CGs peripheral density decreased with the rise in meiotic competence during the IVM process. The current results reveal important new insights into the in vitro maturation of oocytes. Our results may serve as a basis for further studies to investigate the cortical reaction of oocytes.

GLUT1 and lactose synthetase are critical genes for lactose synthesis in lactating sows

Background

Lactose synthesis rate is an important factor in milk production and quality in mammals. Understanding the lactose synthesis mechanism is crucial for the improvement of milk quantity and quality. However, research on the temporal gene changes regarding lactose synthesis during the whole lactation is still limited. The objective of this study was to determine gene expression profiles related to lactose synthesis in sows during lactation, and further identify the critical steps or key factors in the lactose synthesis pathway.

Methods

To determine the temporal change of factors related to lactose synthesis in sows, milk from eight multiparous Yorkshire sows (parity 3 to 6) was collected at 0 h, 2 h, 6 h, 12 h, 24 h, day 2, 3, 4, 7, 14, and 21 after birth of the first piglet. Lactose content, prolactin and progesterone concentration, and gene or protein expression related to lactose synthesis were measured.

Results

The lactose yield increased gradually from D2 to D21 and reached a maximum at D14 (3-fold from D2) during lactation (P < 0.05). A similar trend was observed in IGF-1 and insulin concentrations in milk, both of which were greatest at D3 with a subsequent decrease during middle to late lactation. Conversely, milk prolactin and progesterone concentrations moderately decreased with the progression of lactation. The mRNA or protein expressions related to glucose transportation (GLUT1), glucose-galactose interconversion (HK1 and UGP2), UDP-galactose transportation (SLC35A2), and lactose synthetase (LALBA and B4GALT1) in the lactose synthesis pathway were significantly upregulated during early to middle lactation and plateaued by late lactation (P < 0.05).

Conclusions

These novel findings suggest that the increased lactose synthesis in lactation was related to the coordinated upregulation of genes or enzymes in the lactose synthesis pathway, and glucose transportation (GLUT1) and lactose synthetase (LALBA and B4GALT1) might be the critical steps in the lactose synthesis pathway of sows during lactation.

Transcriptional profiling of swine mammary gland during the transition from colostrogenesis to lactogenesis using RNA sequencing

Background

Colostrum and milk are essential sources of antibodies and nutrients for the neonate, playing a key role in their survival and growth. Slight abnormalities in the timing of colostrogenesis/lactogenesis potentially threaten piglet survival. To further delineate the genes and transcription regulators implicated in the control of the transition from colostrogenesis to lactogenesis, we applied RNA-seq analysis of swine mammary gland tissue from late-gestation to farrowing. Three 2nd parity sows were used for mammary tissue biopsies on days 14, 10, 6 and 2 before (−) parturition and on day 1 after (+) parturition. A total of 15 mRNA libraries were sequenced on a HiSeq2500 (Illumina Inc.). The Dynamic Impact Approach and the Ingenuity Pathway Analysis were used for pathway analysis and gene network analysis, respectively.

Results

A large number of differentially expressed genes were detected very close to parturition (−2d) and at farrowing (+ 1d). The results reflect the extraordinary metabolic changes in the swine mammary gland once it enters into the crucial phases of lactogenesis and underscore a strong transcriptional component in the control of colostrogenesis. There was marked upregulation of genes involved in synthesis of colostrum and main milk components (i.e. proteins, fat, lactose and antimicrobial factors) with a pivotal role of CSN1S2, LALBA, WAP, SAA2, and BTN1A1. The sustained activation of transcription regulators such as SREBP1 and XBP1 suggested they help coordinate these adaptations.

Conclusions

Overall, the precise timing for the transition from colostrogenesis to lactogenesis in swine mammary gland remains uncharacterized. However, our transcriptomic data support the hypothesis that the transition occurs before parturition. This is likely attributable to upregulation of a wide array of genes including those involved in ‘Protein and Carbohydrate Metabolism’, ‘Immune System’, ‘Lipid Metabolism’, ‘PPAR signaling pathway’ and ‘Prolactin signaling pathway’ along with the activation of transcription regulators controlling lipid synthesis and endoplasmic reticulum biogenesis and stress response.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4719-5) contains supplementary material, which is available to authorized users.

Multiplex genomewide association analysis of breast milk fatty acid composition extends the phenotypic association and potential selection of FADS1 variants to arachidonic acid, a critical infant micronutrient

BACKGROUND

Breast milk is the sole nutrition source during exclusive breastfeeding, and polyunsaturated fatty acids (FAs) are critical micronutrients in infant physical and cognitive development. There has been no prior genomewide association study of breast milk, hence our objective was to test for genetic association with breast milk FA composition.

METHODS

We measured the fractional composition of 26 individual FAs in breast milk samples from three cohorts totalling 1142 Bangladeshi mothers whose infants were genotyped on the Illumina MEGA chip and replicated on a custom Affymetrix 30K SNP array (n=616). Maternal genotypes were imputed using IMPUTE.

RESULTS

After running 33 separate FA fraction phenotypes, we found that SNPs known to be associated with serum FAs in the FADS1/2/3 region were also associated with breast milk FA composition (experiment-wise significance threshold 4.2×10^-9). Hypothesis-neutral comparison of the 33 fractions showed that the most significant genetic association at the FADS1/2/3 locus was with fraction of arachidonic acid (AA) at SNP rs174556, with a very large per major allele effect size of 17% higher breast milk AA level. There was no evidence of independent association at FADS1/2/3 with any other FA or SNP after conditioning on AA and rs174556. We also found novel significant experiment-wise SNP associations with: polyunsaturated fatty acid (PUFA) 6/PUFA3 ratio (sorting nexin 29), eicosenoic (intergenic) and capric (component of oligomeric Golgi complex 3) acids; and six additional loci at genomewide significance (<5×10^-8).

CONCLUSIONS

AA is the primary FA in breast milk influenced by genetic variation at the FADS1/2/3 locus, extending the potential phenotypes under genetic selection to include breast milk composition, thereby possibly affecting infant growth or cognition. Breast milk FA composition is influenced by maternal genetics in addition to diet and body composition.

Screening of miRNA profiles and construction of regulation networks in early and late lactation of dairy goat mammary glands

In recent years, studies related to the expression profiles of miRNAs in the dairy goat mammary gland were performed, but regulatory mechanisms in the physiological environment and the dynamic homeostasis of mammary gland development and lactation are not clear. In the present study, sequencing data analysis of early and late lactation uncovered a total of 1,487 unique miRNAs, including 45 novel miRNA candidates and 1,442 known and conserved miRNAs, of which 758 miRNAs were co-expressed and 378 differentially expressed with P < 0.05. Moreover, 76 non-redundant target genes were annotated in 347 GO consortiums, with 3,143 candidate target genes grouped into 33 pathways. Additionally, 18 predicted target genes of 214 miRNAs were directly annotated in mammary gland development and used to construct regulatory networks based on GO annotation and the KEGG pathway. The expression levels of seven known miRNAs and three novel miRNAs were examined using quantitative real-time PCR. The results showed that miRNAs might play important roles in early and late lactation during dairy goat mammary gland development, which will be helpful to obtain a better understanding of the genetic control of mammary gland lactation and development.

Genome-wide association and pathway-based analysis using latent variables related to milk protein composition and cheesemaking traits in dairy cattle

The aim of this study was to perform genome-wide associations (GWAS) and gene-set enrichment analyses with protein composition and cheesemaking-related latent variables (factors; F) in a cohort of 1,011 Italian Brown Swiss cows. Factor analysis was applied to identify latent structures of 26 phenotypes related to bovine milk quantity and quality, protein fractions [α_S1-, α_S2-, β-, and κ-casein (CN), β-lactoglobulin, and α-lactalbumin (α-LA)], coagulation and curd firming at time t (CF_t) measures, and cheese properties [cheese yield (%CY) and nutrients recovery in the curd] of individual cows. Ten orthogonal F were extracted, explaining 74% of the original variability. Factor 1_%CY underlined the %CY characteristics, F2_CFt was related to the CF_t process parameters, F3_Yield was considered as descriptor of milk and solids yield, whereas F4_{Cheese N} underscored the presence of nitrogenous compounds (N) into the cheese. Four more F were related to the milk caseins (F5_αS1-β-CN, F7_β-κ-CN, F8_αS2-CN, and F9_αS1-CN-Ph) and 1 F was linked to the whey protein (F10_α-LA); 1 F underlined the udder health status (F6_{Udder health}). All cows were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc., San Diego, CA). Single marker regression GWAS were fitted. Gene-set enrichment analysis was run on GWAS results, using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases, to reveal ontologies or pathways associated with the F. All F but F3_Yield showed significance in GWAS. Signals in 10 Bos taurus autosomes (BTA) were detected. High peaks on BTA6 (∼87 Mbp) were found for F6_β-κ-CN, F5_αS1-β-CN, and at the tail of BTA11 (∼104 Mbp) for F4_{Cheese N}. Gene-set enrichment analyses showed significant results (false discovery rate at 5%) for F8_αS2-CN, F1_%CY, F4_{Cheese N}, and F10_α-LA. For F8_αS2-CN, 33 Gene Ontology terms and 3 Kyoto Encyclopedia of Genes and Genomes categories were enriched, including terms related to ion transport and homeostasis, neuron function or part, and GnRH signaling pathway. Our results support the feasibility of factor analysis as a dimension reduction technique in genomic studies and evidenced a potential key role of α_S2-CN in milk quality and composition.

Pathway-based genome-wide association analysis of milk coagulation properties, curd firmness, cheese yield, and curd nutrient recovery in dairy cattle

It is becoming common to complement genome-wide association studies (GWAS) with gene-set enrichment analysis to deepen the understanding of the biological pathways affecting quantitative traits. Our objective was to conduct a gene ontology and pathway-based analysis to identify possible biological mechanisms involved in the regulation of bovine milk technological traits: coagulation properties, curd firmness modeling, individual cheese yield (CY), and milk nutrient recovery into the curd (REC) or whey loss traits. Results from 2 previous GWAS studies using 1,011 cows genotyped for 50k single nucleotide polymorphisms were used. Overall, the phenotypes analyzed consisted of 3 traditional milk coagulation property measures [RCT: rennet coagulation time defined as the time (min) from addition of enzyme to the beginning of coagulation; k₂₀: the interval (min) from RCT to the time at which a curd firmness of 20 mm is attained; a₃₀: a measure of the extent of curd firmness (mm) 30 min after coagulant addition], 6 curd firmness modeling traits [RCT_eq: RCT estimated through the CF equation (min); CF_P: potential asymptotic curd firmness (mm); k_CF: curd-firming rate constant (% × min^-1); k_SR: syneresis rate constant (% × min^-1); CF_max: maximum curd firmness (mm); and t_max: time to CF_max (min)], 3 individual CY-related traits expressing the weight of fresh curd (%CY_CURD), curd solids (%CY_SOLIDS), and curd moisture (%CY_WATER) as a percentage of weight of milk processed and 4 milk nutrient and energy recoveries in the curd (REC_FAT, REC_PROTEIN, REC_SOLIDS, and REC_ENERGY calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk), milk pH, and protein percentage. Each trait was analyzed separately. In total, 13,269 annotated genes were used in the analysis. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases were queried for enrichment analyses. Overall, 21 Gene Ontology and 17 Kyoto Encyclopedia of Genes and Genomes categories were significantly associated (false discovery rate at 5%) with 7 traits (RCT, RCT_eq, k_CF, %CY_SOLIDS, REC_FAT, REC_SOLIDS, and REC_ENERGY), with some being in common between traits. The significantly enriched categories included calcium signaling pathway, salivary secretion, metabolic pathways, carbohydrate digestion and absorption, the tight junction and the phosphatidylinositol pathways, as well as pathways related to the bovine mammary gland health status, and contained a total of 150 genes spanning all chromosomes but 9, 20, and 27. This study provided new insights into the regulation of bovine milk coagulation and cheese ability that were not captured by the GWAS.

Using GO-WAR for mining cross-ontology weighted association rules

The Gene Ontology (GO) is a structured repository of concepts (GO terms) that are associated to one or more gene products. The process of association is referred to as annotation. The relevance and the specificity of both GO terms and annotations are evaluated by a measure defined as information content (IC). The analysis of annotated data is thus an important challenge for bioinformatics. There exist different approaches of analysis. From those, the use of association rules (AR) may provide useful knowledge, and it has been used in some applications, e.g. improving the quality of annotations. Nevertheless classical association rules algorithms do not take into account the source of annotation nor the importance yielding to the generation of candidate rules with low IC. This paper presents GO-WAR (Gene Ontology-based Weighted Association Rules) a methodology for extracting weighted association rules. GO-WAR can extract association rules with a high level of IC without loss of support and confidence from a dataset of annotated data. A case study on using of GO-WAR on publicly available GO annotation datasets is used to demonstrate that our method outperforms current state of the art approaches.