Kompetitive Allele Specific PCR Genotyping of 89 SNPs in Romanian Spotted and Romanian Brown Cattle Breeds and Their Association with Clinical Mastitis.

Mastitis is the most common production disease in the dairy sector worldwide, its incidence being associated with both cows' exposure to bacteria and the cows' genetic make-up for resistance to pathogens. The objective of our study was to analyse 89 missense SNPs belonging to six genes (CXCR2, CXCL8, TLR4, BRCA1, LTF, BOLA-DRB3), which were found to be associated with genetic resistance or susceptibility to mastitis. A total of 298 cattle (250 Romanian Spotted and 48 Romanian Brown) were genotyped by Kompetitive Allele Specific PCR (KASP) and a chi-squared test was used for genetic association studies with clinical mastitis. A total of 35 SNPs (39.3%) among the selected 89 SNPs were successfully genotyped, of which 31 markers were monomorphic. The polymorphic markers were found in two genes: TLR4 (rs460053411) and BOLA-DRB3 (rs42309897, rs208816121, rs110124025). The polymorphic SNPs with MAF > 5% and call rates > 95% were used for the association study. The results showed that rs110124025 in the BOLA-DRB3 gene was significantly associated with mastitis prevalence (p ≤ 0.05) in both investigated breeds. Current results show that the SNP rs110124025 in the BOLA-DRB3 gene can be used as a candidate genetic marker in selection for mastitis resistance in Romanian dairy cattle.

Simultaneous Occurrence of Hypospadias and Bilateral Cleft Lip and Jaw in a Crossbred Calf: Clinical, Computer Tomographic, and Genomic Characterization.

Congenital abnormalities in animals, including abnormalities of the cleft lip and jaw and hypospadias have been reported in all domesticated species. They are a major concern for breeders due to the increased economic loss they entail. In this article, we described a congenital bilateral cheilognathoschisis (cleft lip and jaw) with campylognathia in association with penile hypospadias and preputial hypoplasia with failure of preputial fusion in a Bos taurus crossbred Piedmontese × Wagyu calf. Clinical examination, computed tomography, and whole genome sequencing were performed to describe and identify a possible cause of the abnormalities. Clinical examination revealed a bilateral cheilognathoschisis of approximately 4 cm in length and 3 cm in width in the widest part, with computer tomography analyses confirming the bilateral absence of the processus nasalis of the incisive bone and the lateral deviation of the processus palatinus towards the left side. Genomic data analyses identified 13 mutations with a high impact on the products of the following overlapped genes: ACVR1, ADGRA2, BHMT2, BMPR1B, CCDC8, CDH1, EGF, F13A1, GSTP1, IRF6, MMP14, MYBPHL, and PHC2 with ADGRA2, EGF, F13A1, GSTP1, and IRF6 having mutations in a homozygous state. The whole genome investigation indicates the involvement of multiple genes in the birth defects observed in this case.

Polymorphism of the Prolactin (PRL) Gene and Its Effect on Milk Production Traits in Romanian Cattle Breeds.

In the present study, we investigated one polymorphism of the PRL gene (rs211032652 SNP) and assessed its influence on milk production and chemical composition in two Romanian cattle breeds. A total of 119 cattle from two breeds reared in Western Romania (64 Romanian Spotted and 55 Romanian Brown) were included in the research herd. A PCR-RFLP genotyping assay was used for the identification of the rs211032652 SNP variants. Shapiro's test and Levene's test were used to verify ANOVA assumptions and ANOVA and Tukey's test were employed to test the associations between PRL genotypes and five milk traits. Among the studied breeds, our results showed that PRL genotypes were significantly associated (p < 0.05) with fat and protein percentage in the milk of Romanian Brown cattle. The AA genotype was associated with a higher fat percentage in milk (4.76 ± 0.28) compared to the GG genotype (4.04 ± 0.22, p = 0.048), as well as a higher protein percentage (3.96 ± 0.32% vs. 3.43 ± 0.15%, p = 0.027) in Romanian Brown cattle. Moreover, the PRL locus favored a significantly higher fat (p = 0.021) and protein (p = 0.028) percentage in the milk of Romanian Brown cattle compared to the Romanian Spotted breed, with a difference of 0.263% and 0.170%, respectively.

Application potential of chicken DNA chip in domestic pigeon species - Preliminary results.

Introducing the SNP technology to pigeon breeding will enhance the competitiveness of a sector that produces one of the healthiest and best quality meats. The present study aimed to test the applicability of the Illumina Chicken_50K_CobbCons array on 24 domestic pigeon individuals from the Mirthys hybrids and Racing pigeon breeds. A total of 53,313 SNPs were genotyped. Principal component analysis shows a significant overlap between the two groups. The chip performed poorly in this data set, with a call rate per sample of 0.474 (49%). The low call rate was likely due to an increase in the evolutionary distance. A total of 356 SNPs were retained after a relatively strict quality control. We have demonstrated that it is technically feasible to use a chicken microarray chip on pigeon samples. Presumably, with a larger sample size and by assigning phenotypic data, efficiency would be improved, allowing more thorough analyses, such as genome-wide association studies.

Assessing Phenotypic Variability in Some Eastern European Insular Populations of the Climatic Relict Ilex aquifolium L.

Through its natural or cultivated insular population distribution, Ilex aquifolium L. is a paramount species which is exceptionally suitable for studying phenotypic variability and plasticity through the assessment of morphological, physiological, biochemical and genomic features with respect to acclimation and/or adaptation efficiency. The current study is focused on four insular populations of Ilex aquifolium from Eastern Europe (i.e., in Romania, Hungary, Serbia and Bulgaria), and presents an initial evaluation of phenotypic variability in order to conclude our research on phylogenetic relationships and phytochemical profiles, including several descriptive and quantitative morphological traits. Taken together, the data from different methods in this paper indicate that the Bulgarian and Romanian populations can be distinguished from each other and from Serbian and Hungarian populations, while the latter show a higher level of resemblance with regards to their quantitative morphological traits. It is likely that these morphological traits are determined through some quantitative trait loci implicated in stress responses generated by light, temperature, soil water, soil fertility and salinity conditions that will need to be analysed in terms of their physiological, genomic and metabolomics traits in future studies.

Knowledge, Attitudes and Practices Regarding Antibiotic Use and Antibiotic Resistance: A Latent Class Analysis of a Romanian Population.

Considering the major limitations of the latest studies conducted in Romania on the knowledge, attitudes and practices (KAPs) of antibiotic use and antibiotic resistance, we conducted this study to assess this major public health threat. A cross-sectional survey based on a validated questionnaire was conducted among the general population of Romania for a period of 5 months, i.e., September 2021-January 2022. The questionnaire was distributed using Google Form and it covered demographic characteristics and KAP assessments consisting of 12 items on knowledge, 10 items on attitudes and 3 items on practices. Latent class analyses (LCAs) were conducted to group respondents based on their responses. The response rate was 77%, of which females responded in a greater number (n = 1251) compared to males (n = 674). For most of the respondents (67.32%, n = 1296), the education level was high school, while 23.58% (n = 454) of respondents were college graduates. One in three Romanians (33.3%) know the WHO predictions related to this topic. Overall, the Romanian population is less disciplined when it comes to completing antibiotic treatments, as 29.19% of the respondents stop the course of antibiotic administration if their symptoms improve. The key findings from the present study may help policy makers in designing targeted interventions to decrease confusion, ambiguity or misconceptions about antibiotic use.

Genome-Wide Association Studies for Milk Somatic Cell Score in Romanian Dairy Cattle.

Mastitis is one of the most frequently encountered diseases in dairy cattle, negatively affecting animal welfare and milk production. For this reason, contributions to understanding its genomic architecture are of great interest. Genome-wide association studies (GWAS) have identified multiple loci associated with somatic cell score (SCS) and mastitis in cattle. However, most of the studies have been conducted in different parts of the world on various breeds, and none of the investigations have studied the genetic architecture of mastitis in Romanian dairy cattle breeds up to this point in time. In this study, we report the first GWAS for SCS in dairy cattle breeds from Romania. For GWAS, we used an Axiom Bovine v3 SNP-chip (>63,000 Single Nucleotide Polymorphism -SNPs) and 33,330 records from 690 cows belonging to Romanian Spotted (RS) and Romanian Brown (RB) cattle. The results found one SNP significantly associated with SCS in the RS breed and 40 suggestive SNPs with -log10 (p) from 4 to 4.9 for RS and from 4 to 5.4 in RB. From these, 14 markers were located near 12 known genes (AKAP8, CLHC1, MEGF10, SATB2, GATA6, SPATA6, COL12A1, EPS8, LUZP2, RAMAC, IL12A and ANKRD55) in RB cattle, 3 markers were close to ZDHHC19, DAPK1 and MMP7 genes, while one SNP overlapped the HERC3 gene in RS cattle. Four genes (HERC3, LUZP2, AKAP8 and MEGF10) associated with SCS in this study were previously reported in different studies. The most significant SNP (rs110749552) associated with SCS was located within the HERC3 gene. In both breeds, the SNPs and position of association signals were distinct among the three parities, denoting that mastitis is controlled by different genes that are dependent according to parity. The current results contribute to an expansion in the body of knowledge regarding the proportion of genetic variability explained by SNPs for SCS in dairy cattle.

An optimized FAIRE procedure for low cell numbers in yeast.

We report an optimized low-input FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements-sequencing) procedure to assay chromatin accessibility from limited amounts of yeast cells. We demonstrate that the method performs well on as little as 4 mg of cells scraped directly from a few colonies. Sensitivity, specificity and reproducibility of the scaled-down method are comparable with those of regular, higher input amounts, and allow the use of 100-fold fewer cells than existing procedures. The method enables epigenetic analysis of chromatin structure without the need for cell multiplication of exponentially growing cells in liquid culture, thus opening the possibility of studying colony cell subpopulations, or those that can be isolated directly from environmental samples.

Metabolic differentiation of surface and invasive cells of yeast colony biofilms revealed by gene expression profiling.

BACKGROUND: Yeast infections are often connected with formation of biofilms that are extremely difficult to eradicate. An excellent model system for deciphering multifactorial determinants of yeast biofilm development is the colony biofilm, composed of surface ("aerial") and invasive ("root") cells. While surface cells have been partially analyzed before, we know little about invasive root cells. In particular, information on the metabolic, chemical and morphogenetic properties of invasive versus surface cells is lacking. In this study, we used a new strategy to isolate invasive cells from agar and extracellular matrix, and employed it to perform genome wide expression profiling and biochemical analyses of surface and invasive cells. RESULTS: RNA sequencing revealed expression differences in 1245 genes with high statistical significance, indicating large genetically regulated metabolic differences between surface and invasive cells. Functional annotation analyses implicated genes involved in stress defense, peroxisomal fatty acid ß-oxidation, autophagy, protein degradation, storage compound metabolism and meiosis as being important in surface cells. In contrast, numerous genes with functions in nutrient transport and diverse synthetic metabolic reactions, including genes involved in ribosome biogenesis, biosynthesis and translation, were found to be important in invasive cells. Variation in gene expression correlated significantly with cell-type specific processes such as autophagy and storage compound accumulation as identified by microscopic and biochemical analyses. Expression profiling also provided indications of cell-specific regulations. Subsequent knockout strain analyses identified Gip2p, a regulatory subunit of type 1 protein phosphatase Glc7p, to be essential for glycogen accumulation in surface cells. CONCLUSIONS: This is the first study reporting genome wide differences between surface and invasive cells of yeast colony biofilms. New findings show that surface and invasive cells display very different physiology, adapting to different conditions in different colony areas and contributing to development and survival of the colony biofilm as a whole. Notably, surface and invasive cells of colony biofilms differ significantly from upper and lower cells of smooth colonies adapted to plentiful laboratory conditions.

Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

Evaluating a common semi-mechanistic mathematical model of gene-regulatory networks.

Modeling and simulation of gene-regulatory networks (GRNs) has become an important aspect of modern systems biology investigations into mechanisms underlying gene regulation. A key challenge in this area is the automated inference (reverse-engineering) of dynamic, mechanistic GRN models from gene expression time-course data. Common mathematical formalisms for representing such models capture two aspects simultaneously within a single parameter: (1) Whether or not a gene is regulated, and if so, the type of regulator (activator or repressor), and (2) the strength of influence of the regulator (if any) on the target or effector gene. To accommodate both roles, "generous" boundaries or limits for possible values of this parameter are commonly allowed in the reverse-engineering process. This approach has several important drawbacks. First, in the absence of good guidelines, there is no consensus on what limits are reasonable. Second, because the limits may vary greatly among different reverse-engineering experiments, the concrete values obtained for the models may differ considerably, and thus it is difficult to compare models. Third, if high values are chosen as limits, the search space of the model inference process becomes very large, adding unnecessary computational load to the already complex reverse-engineering process. In this study, we demonstrate that restricting the limits to the [-1, +1] interval is sufficient to represent the essential features of GRN systems and offers a reduction of the search space without loss of quality in the resulting models. To show this, we have carried out reverse-engineering studies on data generated from artificial and experimentally determined from real GRN systems.