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Beauvericin (BEA), an ionophoric cyclic hexadepsipeptide mycotoxin, is able to increase oxidative stress by altering membrane ion permeability and uncoupling oxidative phosphorylation. A toxicogenomic study was performed to investigate gene expression changes triggered by BEA exposure (1.5, 3 and 5 μM; 24 h) in Jurkat cells through RNA-sequencing and differential gene expression analysis. Perturbed gene expression was observed in a concentration dependent manner, with 43 differentially expressed genes (DEGs) overlapped in the three studied concentrations. Gene ontology (GO) analysis showed several biological processes related to electron transport chain, oxidative phosphorylation, and cellular respiration significantly altered. Molecular functions linked to mitochondrial respiratory chain and oxidoreductase activity were over-represented (q-value < 0.01). Pathway analysis revealed oxidative phosphorylation and electron transport chain as the most significantly altered pathways in all studied doses (z-score > 1.96; adj p -value < 0.05). 77 genes involved in the respiratory chain were significantly down-regulated at least at one dose. Moreover, 21 genes related to apoptosis and programmed cell death, and 12 genes related to caspase activity were significantly altered, mainly affecting initiator caspases 8, 9 and 10. The results demonstrated BEA-induced mitochondrial damage affecting the respiratory chain, and pointing to apoptosis through the caspase cascade in human lymphoblastic T cells. [ABSTRACT FROM AUTHOR]

The amount and distribution of water inside the meat has a considerable influence on its properties. High losses of fluid in the form of drip may affect financial output, nutritional value, consumer appeal and/or technological properties of porcine meat. Therefore, a deeper insight into the traits water-holding capacity (WHC) and drip is favourable on behalf of producers, industry and consumers. Similar to most meat quality traits, WHC and drip loss (DRIP) are moderately heritable. The genetic correlation between these two traits is high. Correlation to other meat quality traits, such as pH value, cooking loss, reflectance, etc. is existent as predictable. Two major genes are known, RYR1 on chromosome 6 and RN on chromosome 15, to influence meat quality in general and WHC in particular. Furthermore, a number of candidate genes exist, e.g. phosphoglycerate mutase 2. Within the variety of quantitative trait loci (QTL) experiments, a number of QTL have been identified. QTL for DRIP and/or WHC have been found on chromosome 1, 2, 4, 5, 6, 11, 13, 14, 15, 18; for cooking loss on 7, 14 and18, and for pH value on nearly all chromosomes. Recently, a QTL study for meat quality and body composition traits in a Duroc–Pietrain (DUPI) resource population has been conducted at the University of Bonn, Germany. Four QTL for DRIP were identified on chromosomes 2, 3, 5 and 18. The QTL regions are in agreement with previously published QTL for this and other related traits. Further research and finemapping has begun and candidate genes located within the QTL regions are currently under investigation. Combination and comparison of results should lead to deeper insights in the genetic background of meat quality and DRIP. [ABSTRACT FROM AUTHOR]

We performed a genome-wide QTL scan for production traits in a line cross between Duroc and Pietrain breeds of pigs, which included 585 F2 progeny produced from 31 full-sib families genotyped with 106 informative microsatellites. A linkage map covering all 18 autosomes and spanning 1987 Kosambi cM was constructed. Thirty-five phenotypic traits including body weight, growth, carcass composition and meat quality traits were analysed using least square regression interval mapping. Twenty-four QTL exceeded the genome-wide significance threshold, while 47 QTL reached the suggestive threshold. These QTL were located at 28 genomic regions on 16 autosomal chromosomes and QTL in 11 regions were significant at the genome-wide level. A QTL affecting pH value in loin was detected on SSC1 between marker-interval S0312- S0113 with strong statistical support ( P < 3.0 × 10−14); this QTL was also associated with meat colour and conductivity. QTL for carcass composition and average daily gain was also found on SSC1, suggesting multiple QTL. Seventeen genomic segments had only a single QTL that reached at least suggestive significance. Forty QTL exhibited additive inheritance whereas 31 QTL showed (over-) dominance effects. Two QTL for trait backfat thickness were detected on SSC2; a significant paternal effect was found for a QTL in the IGF2 region while another QTL in the middle of SSC2 showed Mendelian expression. [ABSTRACT FROM AUTHOR]

Mannose-binding lectin (MBL) mediates activation of the complement system via the lectin pathway. Two forms of MBL, MBL-A and MBL-C, were characterized in rodents, rabbits, bovine and rhesus monkeys, whereas only one form was identified in humans, chimpanzees and chickens. The two forms are encoded by two distinct genes named MBL1 and MBL2, which have been identified in many species including the pig. In this report, we studied the two porcine genes MBL1 and MBL2. The porcine MBL genes had higher identities to bovine rather than primate and rodent sequences. Both genes were assigned to chromosome 14 by radiation hybrid panel and linkage mapping. Both MBL genes were highly expressed in liver. MBL1 was also found to be expressed in the lung, testis and brain, whereas low expression of MBL2 was detected in the testis and kidney. New single nucleotide polymorphisms of porcine MBL2 gene were found and genotyped in an experimental F2 pig population, together with a previously reported SNP of MBL1. MBL1 genotypes differed in C3c serum concentration, i.e. in vivo complement activity, at P < 0.1. Correspondingly, linkage analysis revealed a quantitative trait locus for C3c serum level close to the position of the MBL genes. The study thus promotes the porcine MBL genes as functional and positional candidate gene for complement activity. [ABSTRACT FROM AUTHOR]

β-actin ( ACTB) was examined as a direct functional candidate gene for the possible association with sperm concentration, motility (MOT), semen volume per ejaculate, plasma droplet rate, abnormal sperm rate (ASR) and the fertility traits, non-return rate and number of piglets born alive (NBA). Three polymorphisms in intron 3 (T>C) and one polymorphism in exon 4 (T>C) of porcine ACTB gene were identified by comparative sequencing of animals of the breeds Pietrain and Hampshire. Association analysis revealed that haplotypes affected the variation of the traits MOT, ASR and NBA. The beneficial haplotypes may provide considerable improvement of sperm quality and fertility in the tested commercial boar population. [ABSTRACT FROM AUTHOR]

To improve the physical and comparative map of chicken chromosome 24 (GGA24; former linkage group E49C20W21) bacterial artificial chromosome (BAC) contigs were constructed around loci previously mapped on this chromosome by linkage analysis. The BAC clones were used for both sample sequencing and BAC end sequencing. Sequence tagged site (STS) markers derived from the BAC end sequences were used for chromosome walking. In total 191 BAC clones were isolated, covering almost 30% of GGA24, and 76 STS were developed (65 STS derived from BAC end sequences and 11 STS derived within genes). The partial sequences of the chicken BAC clones were compared with sequences present in the EMBL/GenBank databases, and revealed matches to 19 genes, expressed sequence tags (ESTs) and genomic clones located on human chromosome 11q22-q24 and mouse chromosome 9. Furthermore, 11 chicken orthologues of human genes located on HSA11q22-q24 were directly mapped within BAC contigs of GGA24. These results provide a better alignment of GGA24 with the corresponding regions in human and mouse and identify several intrachromosomal rearrangements between chicken and mammals. [ABSTRACT FROM AUTHOR]

We have constructed a radiation hybrid (RH) map of chicken chromosome (GGA) 15. This map can be used as a resource to efficiently map genes to this chromosome. The map has been developed using a 6000 rad chicken–hamster whole-genome radiation hybrid panel (ChickRH6). In total, six microsatellite loci, 18 sequence tagged sites (STSs) from BAC end sequences and 11 genes were typed on the panel. The initial framework map comprised eight markers, and an additional 23 markers were then added to generate the final map. The total map length was 334 centiRay6000 (cR6000). The estimated retention frequency for the data set was 18%. Using an estimated physical length of 21 Mb, the ratio between cR6000 and physical distance over GGA15 was estimated to be 0.063 Mb/cR6000. The present map increases the marker density and the marker resolution on GGA15 and enables fast mapping of new chicken genes homologous to genes from human chromosomes 12 and 22. [ABSTRACT FROM AUTHOR]

Cancer is a complex disease where cancer cells express epigenetic and transcriptomic mechanisms to promote tumor initiation, progression, and survival. To extract relevant features from the 2019 Cancer Cell Line Encyclopedia (CCLE), a multi-layer nonnegative matrix factorization approach is used. We used relevant feature genes and DNA promoter regions to construct genomic interaction network to study gene–gene and gene—DNA promoter methylation relationships. Here, we identified a set of gene transcripts and methylated DNA promoter regions for different clusters, including one homogeneous lymphoid neoplasms cluster. In this cluster, we found different methylated transcription factors that affect transcriptional activation of EGFR and downstream interactions. Furthermore, the hippo-signaling pathway might not function properly because of DNA hypermethylation and low gene expression of both LATS2 and YAP1. Finally, we could identify a potential dysregulation of the CD28-CD86-CTLA4 axis. Characterizing the interaction of the epigenome and the transcriptome is vital for our understanding of cancer cell line behavior, not only for deepening insights into cancer-related processes but also for future disease treatment and drug development. Here we have identified potential candidates that characterize cancer cell lines, which give insight into the development and progression of cancers. [ABSTRACT FROM AUTHOR]

Well-established in vitro methods for testing the genotoxic potency of chemicals—such as the Ames/Salmonella test, the mouse lymphoma assay, the micronucleus test and the chromosomal aberration test—show a high false-positive rate for predicting in vivo genotoxicity and carcinogenicity. Thus, there is a need for more reliable in vitro assays. We investigated whether gene expression profiling in metabolically competent primary mouse hepatocytes is capable of discriminating true genotoxic (GTX) compounds from false-positive genotoxic (FP-GTX) compounds. Sandwich-cultured primary hepatocytes from male C57Bl6 mice were treated for 24 and 48 h with five true GTX and five FP-GTX compounds. Whole genome gene expression modifications were analysed by means of Affymetrix mouse genome 430 2.0 microarrays. Filtered genes were used for hierarchical clustering and class prediction methods. Classifiers were generated by prediction analysis of microarray using a leave-one-compound-out method and selecting the genes that were common to the 10 training sets. For the training compounds, all but one were correctly classified. Validation of the classification model with five new compounds resulted in a 100% correct classification at 24 h and 80% at 48 h. The generated classifiers were mostly involved in metabolic and biosynthetic processes, immune responses and apoptosis. Applying genes whose expression change correlates with γH2AX foci, a measure for DNA damage, did not improve the classification. The present study shows that gene expression profiling in primary mouse hepatocytes is capable of discriminating between true GTX and FP-GTX compounds. [ABSTRACT FROM AUTHOR]

The objective of this study was to examine the relationship of the relative abundance of transcripts of myosin heavy chain (MyHC) isoforms and muscling in several diverse pig breeds. The animals used were from 3 pure breeds (Pietrain, Duroc, and Mongcai) and 2 crosses [Duroc x Pietrain (DUPI) and Duroc × Berlin Miniature pigs (DUMI)]. Real-time PCR quantification of MyHC isoforms I, IIa, IIx, and IIb showed that the relative expression of MyHC IIb was greater in pigs with large LM areas in both DUPI (69.6 vs. 53.0%) and DUMI (60.5 vs. 47.5%). In DUPI, similar transcript levels of MyHC I were found in both large and small LM (14.7 and 15.2%), whereas in DUMI animals, these values were 18.4 and 33.5% (P < 0.05). The groups of animals with large and small LM area in the DUPI also tended to differ in MyHC IIa and IIx transcripts. The comparison among different breeds confirmed the trend of high MyHC IIb transcript abundance together with high muscularity. In Pietrain, Duroc, DUPI, and DUMI, MyHC IIb accounted for more than IIalf of the MyHC transcripts (65.4, 59.7, 54.0, and 54.0%). Mongcai showed low MyRC IIb (11.4%) but high type I, IIa, and IIx relative RNA levels (24.1, 28.5, and 35.9%). Frequencies of fibers, determined by muscle fiber staining with ATPase, and relative abundance of MyHC isoforms, determined by quantitative reverse transcription-PCR, of corresponding pairs of type I, IIa, and IIx/IIb were correlated (r = 0.71, 0.67, and 0.52, respectively). The study demonstrates that MyHC IIb fibers are the most prominent in pigs IIaving large LM area and implies that MyHC IIb is the determining fiber contributing to the differentiation of large and small loin eye muscle area in the pig. [ABSTRACT FROM AUTHOR]

Contents Retinol-binding protein 4 ( RBP4), androgen receptor ( AR), relaxin ( RLN), acrosin ( ACR) and osteopontin (polymorphism in intron 6 named OPNin6; polymorphism in promoter region named OPNprom) were addressed as functional candidate genes for sperm quality and boar fertility and investigated for their association with sperm concentration, motility, semen volume per ejaculate, plasma droplets rate, abnormal spermatozoa rate as well as non-return rate and number of piglets born alive. Therefore 356 AI boars of the purebred Pietrain (PI) and crossbred Pietrain × Hampshire (PI × HA) were genotyped at these loci. Analysis of variance revealed significant associations of RBP4 (p < 0.05), ACR (p < 0.01), and OPNin6 (p < 0.05) with sperm motility. OPNin6 (p < 0.05) was also associated with number of piglets born alive. Moreover, AR (p < 0.05) and OPNprom (p < 0.05) were significantly associated with abnormal spermatozoa rate. For RLN (p < 0.01) there was evidence for effects on sperm volume and ACR significantly affected sperm concentration (p < 0.05) as well as non-return rate (p < 0.05). No significant effects of any locus on plasma droplets rate were observed. [ABSTRACT FROM AUTHOR]

The assessment of the carcinogenic potential of chemicals with alternative, human-based in vitro systems has become a major goal of toxicogenomics. The central read-out of these assays is the transcriptome, and while many studies exist that explored the gene expression responses of such systems, reports on robustness and reproducibility, when testing them independently in different laboratories, are still uncommon. Furthermore, there is limited knowledge about variability induced by the data analysis protocols. We have conducted an inter-laboratory study for testing chemical carcinogenicity evaluating two human in vitro assays: hepatoma-derived cells and hTERT-immortalized renal proximal tubule epithelial cells, representing liver and kidney as major target organs. Cellular systems were initially challenged with thirty compounds, genome-wide gene expression was measured with microarrays, and hazard classifiers were built from this training set. Subsequently, each system was independently established in three different laboratories, and gene expression measurements were conducted using anonymized compounds. Data analysis was performed independently by two separate groups applying different protocols for the assessment of inter-laboratory reproducibility and for the prediction of carcinogenic hazard. As a result, both workflows came to very similar conclusions with respect to (1) identification of experimental outliers, (2) overall assessment of robustness and inter-laboratory reproducibility and (3) re-classification of the unknown compounds to the respective toxicity classes. In summary, the developed bioinformatics workflows deliver accurate measures for inter-laboratory comparison studies, and the study can be used as guidance for validation of future carcinogenicity assays in order to implement testing of human in vitro alternatives to animal testing. [ABSTRACT FROM AUTHOR]

Mechanistically relevant information on responses of humans to xenobiotic exposure in relation to chemically induced biological effects, such as micronuclei (MN) formation can be obtained through large-scale transcriptomics studies. Network analysis may enhance the analysis and visualisation of such data. Therefore, this study aimed to develop a ‘MN formation’ network based on a priori knowledge, by using the pathway tool MetaCore. The gene network contained 27 genes and three gene complexes that are related to processes involved in MN formation, e.g. spindle assembly checkpoint, cell cycle checkpoint and aneuploidy. The MN-related gene network was tested against a transcriptomics case study associated with MN measurements. In this case study, transcriptomic data from children and adults differentially exposed to ambient air pollution in the Czech Republic were analysed and visualised on the network. Six genes from the network, i.e. BAX, DMNT1, PCNA, HIC1, p21 and CDC20, were retrieved. Based on these six genes and in combination with p53 and IL-6, a dedicated network was created. This dedicated network is possibly suited for the development of a reporter gene assay that could be used to screen populations complementary to the current MN test assay. In conclusion, we have shown that network analysis of transcriptomics data in relation to the formation of MN is possible and provides a novel mechanistic hypothesis by indicating which genes are regulated and influence others. [ABSTRACT FROM AUTHOR]

Contents This study was conducted to determine the effect of Nitric oxide (NO) inhibition in bovine in vitro development and expression analysis of the three Nitric oxide synthase (NOS) isoforms: endothelial (eNOS), neuronal (nNOS) and inducible (iNOS), mRNA and protein in bovine oocytes and embryos. Selective inhibitor of NOS, N- ω-nitro-l-arginine methyl ester (l-NAME) was applied at different doses (0, 0.1, 1 and 10 mm) in maturation (experiment 1A), culture medium (experiment 1B) and in both maturation and culture media (experiment 1C). No significant differences were observed in cleavage and blastocyst rates when oocytes were matured in the presence ofl-NAME as long as the inhibitor was omitted during fertilization and culture. However, significantly lower blastocyst rates were observed whenl-NAME was present at higher level (10 mm) in culture medium alone and in both maturation and culture media. In experiment 2, mRNA isolated from triplicate pools of oocytes and embryos (n = 15–20) was subjected to quantitative real time reverse transcription polymerase chain reaction to investigate the expression of eNOS, iNOS and nNOS mRNA in normal IVP bovine oocytes and embryos. While eNOS and iNOS transcripts were detected at higher level in oocytes (immature and mature), two-cell and four-cell stage embryos, the nNOS was detected only in immature oocyte, two-cell and morula stages. In experiment 3, eNOS and iNOS protein expression analysis was performed in IVP oocytes and embryos and both proteins were detected in the cytoplasm and the nuclei (weak) of oocytes and embryos. These data provide the first evidence for the role of NO production and the presence of mRNA and protein products of NOS isoforms during bovine embryogenesis. [ABSTRACT FROM AUTHOR]

α-Actinins (ACTN1andACTN4) andγ-actin (ACTG2), were investigated as candidate genes on the basis of their known functions, for their possible association with sperm concentration, motility, semen volume per ejaculate, plasma droplets rate, abnormal sperm rate and the fertility traits, non-return rate and number of piglets born alive. Polymorphisms were identified in intron 18 (G>A) of the porcineACTN1gene and in exon 22 (A>C) of the porcineACTN4gene by comparative sequencing of animals from the Pietrain (PI) and Hampshire (HA) breeds. Pietrain (n = 244) and crossbreed PI × HA (n = 112) boars from an artificial insemination boar station were genotyped for the single nucleotide polymorphisms (SNPs) withinACTN1andACTN4as well as for a previously described microsatellite withinACTG2. The study provides evidence for effects ofACTN1on fertility and ofACTG2on sperm quality traits, while no indication of impact ofACTN4on any of these traits was found. [ABSTRACT FROM AUTHOR]

Background: The development of high throughput sequencing techniques provides us with the possibilities to obtain large data sets, which capture the effect of dynamic perturbations on cellular processes. However, because of the dynamic nature of these processes, the analysis of the results is challenging. Therefore, there is a great need for bioinformatics tools that address this problem. Results: Here we present DynOVis, a network visualization tool that can capture dynamic dose-over-time effects in biological networks. DynOVis is an integrated work frame of R packages and JavaScript libraries and offers a force-directed graph network style, involving multiple network analysis methods such as degree threshold, but more importantly, it allows for node expression animations as well as a frame-by-frame view of the dynamic exposure. Valuable biological information can be highlighted on the nodes in the network, by the integration of various databases within DynOVis. This information includes pathway-to-gene associations from ConsensusPathDB, disease-to-gene associations from the Comparative Toxicogenomics databases, as well as Entrez gene ID, gene symbol, gene synonyms and gene type from the NCBI database. Conclusions: DynOVis could be a useful tool to analyse biological networks which have a dynamic nature. It can visualize the dynamic perturbations in biological networks and allows the user to investigate the changes over time. The integrated data from various online databases makes it easy to identify the biological relevance of nodes in the network. With DynOVis we offer a service that is easy to use and does not require any bioinformatics skills to visualize a network. [ABSTRACT FROM AUTHOR]