Epigenetic disruptions in the offspring hypothalamus in response to maternal infection.

DNA methylation is an epigenetic modification that can alter gene expression, and the incidence can vary across developmental stages, inflammatory conditions, and sexes. The effects of viral maternal viral infection and sex on the DNA methylation patterns were studied in the hypothalamus of a pig model of immune activation during development. DNA methylation at single-base resolution in regions of high CpG density was measured on 24 individual hypothalamus samples using reduced representation bisulfite sequencing. Differential over- and under-methylated sites were identified and annotated to proximal genes and corresponding biological processes. A total of 120 sites were differentially methylated (FDR-adjusted p-value < 0.05) between maternal infection or sex groups. Among the 66 sites differentially methylated between groups exposed to inflammatory signals and control, most sites were over-methylated in the challenged group and included sites in the promoter regions of genes SIRT3 and NRBP1. Among the 54 differentially methylated sites between females and males, most sites were over-methylated in females and included sites in the promoter region of genes TNC and EIF4G1. The analysis of the genes proximal to the differentially methylated sites suggested that biological processes potentially impacted include immune response, neuron migration and ensheathment, peptide signaling, adaptive thermogenesis, and tissue development. These results suggest that translational studies should consider that the prolonged effect of maternal infection during gestation may be enacted through epigenetic regulatory mechanisms that may differ between sexes.

Immune and metabolic challenges induce changes in pain sensation and related pathways in the hypothalamus.

The hypothalamic molecular processes participate in the regulation of the neuro-immune-endocrine system, including hormone, metabolite, chemokine circulation, and corresponding physiological and behavioral responses. RNA-sequencing profiles were analyzed to understand the effect of juvenile immune and metabolic distress 100 days after virally elicited maternal immune activation during gestation in pigs. Over 1,300 genes exhibited significant additive or interacting effects of gestational immune activation, juvenile distress, and sex. One-third of these genes presented multiple effects, emphasizing the complex interplay of these factors. Key functional categories enriched among affected genes included sensory perception of pain, steroidogenesis, prolactin, neuropeptide, and inflammatory signaling. These categories underscore the intricate relationship between gestational immune activation during gestation, distress, and the response of hypothalamic pathways to insults. These effects were sex-dependent for many genes, such as Prdm12, Oprd1, Isg20, Prl, Oxt, and Vip. The prevalence of differentially expressed genes annotated to proinflammatory and cell cycle processes suggests potential implications for synaptic plasticity and neuronal survival. The gene profiles affected by immune activation, distress, and sex pointed to the action of transcription factors SHOX2, STAT1, and REST. These findings underscore the importance of considering sex and postnatal challenges when studying causes of neurodevelopmental disorders and highlight the complexity of the "two-hit" hypothesis in understanding their etiology. Our study furthers the understanding of the intricate molecular responses in the hypothalamus to gestational immune activation and subsequent distress, shedding light on the sex-specific effects and the potential long-lasting consequences on pain perception, neuroendocrine regulation, and inflammatory processes.NEW & NOTEWORTHY The interaction of infection during gestation and insults later in life influences the molecular mechanisms in the hypothalamus that participate in pain sensation. The response of the hypothalamic transcriptome varies between sexes and can also affect synapses and immune signals. The findings from this study assist in the identification of agonists or antagonists that can guide pretranslational studies to ameliorate the effects of gestational insults interacting with postnatal challenges on physiological or behavioral disorders.

Complete Blood Count Analysis on Beef Cattle Exposed to Fescue Toxicity and Rumen-Protected Niacin Supplementation.

Offspring born to dams genetically tested for resistance to fescue toxicity were separated in groups based on their dams' resistance level (tolerant vs. susceptible). Rumen-protected niacin (RPN) is proposed as a potential alleviator for vasoconstriction produced by fescue toxicity. Complete blood count (CBC) analysis was utilized for detection of significant responses to treatments applied. Our objectives were as follows: (a) to analyze changes in CBC due to fescue toxicity, maternal resistance level, and RPN in growing offspring; and (b) to assess the effects of maternal resistance level when consuming endophyte-infected tall fescue seeds in addition to RPN in offspring performance. Body weight, average daily gain, or health status were not improved by RPN or the genetic test to detect fescue toxicity resistance. Typical signs of alkaloids intoxication and heat stress were noticed in offspring. Particularly, rectal temperature was greater for susceptible control heifers. Results showed that susceptible control offspring presented signs of anemia denoted by low mean corpuscular hemoglobin (MCH) and mean corpuscular volume (MCV). High levels of white blood cells (WBC) and basophils in combination to low neutrophils to lymphocytes ratio were the signs of infection or inflammation detected in the CBC analysis, especially in tolerant niacin steers. Furthermore, offspring of control heifers had a greater percentage of reticulocytes and RDW, denoting signs of anemia.

Bivariate genome-wide association analysis of the growth and intake components of feed efficiency.

Single nucleotide polymorphisms (SNPs) associated with average daily gain (ADG) and dry matter intake (DMI), two major components of feed efficiency in cattle, were identified in a genome-wide association study (GWAS). Uni- and multi-SNP models were used to describe feed efficiency in a training data set and the results were confirmed in a validation data set. Results from the univariate and bivariate analyses of ADG and DMI, adjusted by the feedlot beef steer maintenance requirements, were compared. The bivariate uni-SNP analysis identified (P-value <0.0001) 11 SNPs, meanwhile the univariate analyses of ADG and DMI identified 8 and 9 SNPs, respectively. Among the six SNPs confirmed in the validation data set, five SNPs were mapped to KDELC2, PHOX2A, and TMEM40. Findings from the uni-SNP models were used to develop highly accurate predictive multi-SNP models in the training data set. Despite the substantially smaller size of the validation data set, the training multi-SNP models had slightly lower predictive ability when applied to the validation data set. Six Gene Ontology molecular functions related to ion transport activity were enriched (P-value <0.001) among the genes associated with the detected SNPs. The findings from this study demonstrate the complementary value of the uni- and multi-SNP models, and univariate and bivariate GWAS analyses. The identified SNPs can be used for genome-enabled improvement of feed efficiency in feedlot beef cattle, and can aid in the design of empirical studies to further confirm the associations.

Single nucleotide polymorphisms and haplotypes associated with feed efficiency in beef cattle.

BACKGROUND: General, breed- and diet-dependent associations between feed efficiency in beef cattle and single nucleotide polymorphisms (SNPs) or haplotypes were identified on a population of 1321 steers using a 50 K SNP panel. Genomic associations with traditional two-step indicators of feed efficiency - residual feed intake (RFI), residual average daily gain (RADG), and residual intake gain (RIG) - were compared to associations with two complementary one-step indicators of feed efficiency: efficiency of intake (EI) and efficiency of gain (EG). Associations uncovered in a training data set were evaluated on independent validation data set. A multi-SNP model was developed to predict feed efficiency. Functional analysis of genes harboring SNPs significantly associated with feed efficiency and network visualization aided in the interpretation of the results. RESULTS: For the five feed efficiency indicators, the numbers of general, breed-dependent, and diet-dependent associations with SNPs (P-value < 0.0001) were 31, 40, and 25, and with haplotypes were six, ten, and nine, respectively. Of these, 20 SNP and six haplotype associations overlapped between RFI and EI, and five SNP and one haplotype associations overlapped between RADG and EG. This result confirms the complementary value of the one and two-step indicators. The multi-SNP models included 89 SNPs and offered a precise prediction of the five feed efficiency indicators. The associations of 17 SNPs and 7 haplotypes with feed efficiency were confirmed on the validation data set. Nine clusters of Gene Ontology and KEGG pathway categories (mean P-value < 0.001) including, 9nucleotide binding; ion transport, phosphorous metabolic process, and the MAPK signaling pathway were overrepresented among the genes harboring the SNPs associated with feed efficiency. CONCLUSIONS: The general SNP associations suggest that a single panel of genomic variants can be used regardless of breed and diet. The breed- and diet-dependent associations between SNPs and feed efficiency suggest that further refinement of variant panels require the consideration of the breed and management practices. The unique genomic variants associated with the one- and two-step indicators suggest that both types of indicators offer complementary description of feed efficiency that can be exploited for genome-enabled selection purposes.

Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival.

BACKGROUND: Glioblastoma is a complex multifactorial disorder that has swift and devastating consequences. Few genes have been consistently identified as prognostic biomarkers of glioblastoma survival. The goal of this study was to identify general and clinical-dependent biomarker genes and biological processes of three complementary events: lifetime, overall and progression-free glioblastoma survival. METHODS: A novel analytical strategy was developed to identify general associations between the biomarkers and glioblastoma, and associations that depend on cohort groups, such as race, gender, and therapy. Gene network inference, cross-validation and functional analyses further supported the identified biomarkers. RESULTS: A total of 61, 47 and 60 gene expression profiles were significantly associated with lifetime, overall, and progression-free survival, respectively. The vast majority of these genes have been previously reported to be associated with glioblastoma (35, 24, and 35 genes, respectively) or with other cancers (10, 19, and 15 genes, respectively) and the rest (16, 4, and 10 genes, respectively) are novel associations. Pik3r1, E2f3, Akr1c3, Csf1, Jag2, Plcg1, Rpl37a, Sod2, Topors, Hras, Mdm2, Camk2g, Fstl1, Il13ra1, Mtap and Tp53 were associated with multiple survival events.Most genes (from 90 to 96%) were associated with survival in a general or cohort-independent manner and thus the same trend is observed across all clinical levels studied. The most extreme associations between profiles and survival were observed for Syne1, Pdcd4, Ighg1, Tgfa, Pla2g7, and Paics. Several genes were found to have a cohort-dependent association with survival and these associations are the basis for individualized prognostic and gene-based therapies. C2, Egfr, Prkcb, Igf2bp3, and Gdf10 had gender-dependent associations; Sox10, Rps20, Rab31, and Vav3 had race-dependent associations; Chi3l1, Prkcb, Polr2d, and Apool had therapy-dependent associations. Biological processes associated glioblastoma survival included morphogenesis, cell cycle, aging, response to stimuli, and programmed cell death. CONCLUSIONS: Known biomarkers of glioblastoma survival were confirmed, and new general and clinical-dependent gene profiles were uncovered. The comparison of biomarkers across glioblastoma phases and functional analyses offered insights into the role of genes. These findings support the development of more accurate and personalized prognostic tools and gene-based therapies that improve the survival and quality of life of individuals afflicted by glioblastoma multiforme.

Quantitative peptidomics reveal brain peptide signatures of behavior.

The honey bee genome predicts approximately 100 peptides from 36 prohormones, but the functions of many of these peptides are unknown. We used differential isotope labeling combined with mass spectrometric analysis to quantify approximately 50% of known bee brain peptides in the context of foraging, with 8 showing robust and dynamic regulation. Some showed differences in brain abundance as a function of experience; specifically, nectar and pollen collection led to quick changes in abundance. These changes were related to the act of food collection, not ingestion, because foragers bring food back to the hive for storage rather than eating it themselves. Other peptide differences in brain abundance were seen in bees that either flew to a nectar feeder or a pollen feeder, but did not yet collect any food. These differences likely reflect well-known predispositions of some bees to collect either nectar or pollen, but not both. Tachykinin, PBAN, and sNPF were among the peptides with the strongest changes in association with nectar and pollen foraging. These peptides are known to be involved in regulating food intake in solitary insects, suggesting an evolutionary connection between that behavior and social foraging. These results demonstrate that it is now possible to use quantitative peptidomics to help determine which brain peptides are bioactive and to elucidate their function in the regulation of behavior.