22 research outputs found
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Transcriptomic Profiles of Monocyte-Derived Macrophages in Response to Escherichia coli is Associated with the Host Genetics.
Reactive Nitrogen Species (RNS) are a group of bactericidal molecules produced by macrophages in response to pathogens in a process called oxidative burst. Nitric oxide (NO-) is a member of RNS produced from arginine by inducible Nitric Oxide Synthase (iNOS) enzyme. The activity of iNOS and production of NO- by macrophages following stimulation is one of the indicators of macrophage polarization towards M1/proinflammatory. Production of NO- by bovine monocyte-derived macrophage (MDM) and mouse peritoneal macrophages has been shown to be strongly associated with host genetic with the heritability of 0.776 in bovine MDM and 0.8 in mouse peritoneal macrophages. However, the mechanism of genetic regulation of macrophage response has remained less explored. In the current study, the transcriptome of bovine MDMs was compared between two extreme phenotypes that had been classified as high and low responder based on NO- production. The results showed that 179 and 392 genes were differentially expressed (DE) between high and low responder groups at 3 and 18 hours after exposure to Escherichia coli, respectively. A set of 11 Transcription Factors (TFs) (STAT1, IRF7, SPI1, STAT4, IRF1, HIF1A, FOXO3, REL, NFAT5, HIC1, and IRF4) at 3 hours and a set of 13 TFs (STAT1, IRF1, HIF1A, STAT4, ATF4, TP63, EGR1, CDKN2A, RBL1, E2F1, PRDM1, GATA3, and IRF4) at 18 hours after exposure to E. coli were identified to be differentially regulated between the high and low responder phenotypes. These TFs were found to be divided into two clusters of inflammatory- and hypoxia-related TFs. Functional analysis revealed that some key canonical pathways such as phagocytosis, chemotaxis, antigen presentation, and cell-to-cell signalling are enriched among the over-expressed genes by high responder phenotype. Based on the results of this study, it was inferred that the functional characteristics of bovine MDMs are associated with NO-based classification. Since NO- production is strongly associated with host genetics, this study for the first time shows the distinct proinflammatory profiles of macrophages are controlled by the natural genetic polymorphism in an outbred population. In addition, the results suggest that genetics can be considered as a new dimension in the current model of macrophage polarization which is currently described by the combination of stimulants, only
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Non-Coding RNA Sequencing of Equine Endometrium During Maternal Recognition of Pregnancy.
Maternal recognition of pregnancy (MRP) in the mare is not well defined. In a non-pregnant mare, prostaglandin F2α (PGF) is released on day 14 post-ovulation (PO) to cause luteal regression, resulting in loss of progesterone production. Equine MRP occurs prior to day 14 to halt PGF production. Studies have failed to identify a gene candidate for MRP, so attention has turned to small, non-coding RNAs. The objective of this study was to evaluate small RNA (<200 nucleotides) content in endometrium during MRP. Mares were used in a cross-over design with each having a pregnant and non-mated cycle. Each mare was randomly assigned to collection day 11 or 13 PO (n = 3/day) and endometrial biopsies were obtained. Total RNA was isolated and sequencing libraries were prepared using a small RNA library preparation kit and sequenced on a HiSeq 2000. EquCab3 was used as the reference genome and DESeq2 was used for statistical analysis. On day 11, 419 ncRNAs, representing miRNA, snRNA, snoRNA, scaRNA, and vaultRNA, were different between pregnancy statuses, but none on day 13. Equine endometrial ncRNAs with unknown structure and function were also identified. This study is the first to describe ncRNA transcriptome in equine endometrium. Identifying targets of these ncRNAs could lead to determining MRP
SNP discovery in the bovine milk transcriptome using RNA-Seq technology
High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. However, it also is an efficient way to discover coding SNPs. The objective of this study was to perform a SNP discovery analysis in the milk transcriptome using RNA-Seq. Seven milk samples from Holstein cows were analyzed by sequencing cDNAs using the Illumina Genome Analyzer system. We detected 19,175 genes expressed in milk samples corresponding to approximately 70% of the total number of genes analyzed. The SNP detection analysis revealed 100,734 SNPs in Holstein samples, and a large number of those corresponded to differences between the Holstein breed and the Hereford bovine genome assembly Btau4.0. The number of polymorphic SNPs within Holstein cows was 33,045. The accuracy of RNA-Seq SNP discovery was tested by comparing SNPs detected in a set of 42 candidate genes expressed in milk that had been resequenced earlier using Sanger sequencing technology. Seventy of 86 SNPs were detected using both RNA-Seq and Sanger sequencing technologies. The KASPar Genotyping System was used to validate unique SNPs found by RNA-Seq but not observed by Sanger technology. Our results confirm that analyzing the transcriptome using RNA-Seq technology is an efficient and cost-effective method to identify SNPs in transcribed regions. This study creates guidelines to maximize the accuracy of SNP discovery and prevention of false-positive SNP detection, and provides more than 33,000 SNPs located in coding regions of genes expressed during lactation that can be used to develop genotyping platforms to perform marker-trait association studies in Holstein cattle
Transcriptome Profiling of Bovine Milk Oligosaccharide Metabolism Genes Using RNA-Sequencing
This study examines the genes coding for enzymes involved in bovine milk oligosaccharide metabolism by comparing the oligosaccharide profiles with the expressions of glycosylation-related genes. Fresh milk samples (n = 32) were collected from four Holstein and Jersey cows at days 1, 15, 90 and 250 of lactation and free milk oligosaccharide profiles were analyzed. RNA was extracted from milk somatic cells at days 15 and 250 of lactation (n = 12) and gene expression analysis was conducted by RNA-Sequencing. A list was created of 121 glycosylation-related genes involved in oligosaccharide metabolism pathways in bovine by analyzing the oligosaccharide profiles and performing an extensive literature search. No significant differences were observed in either oligosaccharide profiles or expressions of glycosylation-related genes between Holstein and Jersey cows. The highest concentrations of free oligosaccharides were observed in the colostrum samples and a sharp decrease was observed in the concentration of free oligosaccharides on day 15, followed by progressive decrease on days 90 and 250. Ninety-two glycosylation-related genes were expressed in milk somatic cells. Most of these genes exhibited higher expression in day 250 samples indicating increases in net glycosylation-related metabolism in spite of decreases in free milk oligosaccharides in late lactation milk. Even though fucosylated free oligosaccharides were not identified, gene expression indicated the likely presence of fucosylated oligosaccharides in bovine milk. Fucosidase genes were expressed in milk and a possible explanation for not detecting fucosylated free oligosaccharides is the degradation of large fucosylated free oligosaccharides by the fucosidases. Detailed characterization of enzymes encoded by the 92 glycosylation-related genes identified in this study will provide the basic knowledge for metabolic network analysis of oligosaccharides in mammalian milk. These candidate genes will guide the design of a targeted breeding strategy to optimize the content of beneficial oligosaccharides in bovine milk
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Transcription initiation mapping in 31 bovine tissues reveals complex promoter activity, pervasive transcription, and tissue-specific promoter usage
Characterizing transcription start sites is essential for understanding the regulatory mechanisms that control gene expression. Recently, a new bovine genome assembly (ARS-UCD1.2) with high continuity, accuracy, and completeness was released; however, the functional annotation of the bovine genome lacks precise transcription start sites and contains a low number of transcripts in comparison to human and mouse. By using the RAMPAGE approach, this study identified transcription start sites at high resolution in a large collection of bovine tissues. We found several known and novel transcription start sites attributed to promoters of protein-coding and lncRNA genes that were validated through experimental and in silico evidence. With these findings, the annotation of transcription start sites in cattle reached a level comparable to the mouse and human genome annotations. In addition, we identified and characterized transcription start sites for antisense transcripts derived from bidirectional promoters, potential lncRNAs, mRNAs, and pre-miRNAs. We also analyzed the quantitative aspects of RAMPAGE to produce a promoter activity atlas, reaching highly reproducible results comparable to traditional RNA-seq. Coexpression networks revealed considerable use of tissue-specific promoters, especially between brain and testicle, which expressed several genes in common from alternate loci. Furthermore, regions surrounding coexpressed modules were enriched in binding factor motifs representative of each tissue. The comprehensive annotation of promoters in such a large collection of tissues will substantially contribute to our understanding of gene expression in cattle and other mammalian species, shortening the gap between genotypes and phenotypes
Molecular Phylogeny and SNP Variation of Polar Bears (Ursus Maritimus), Brown Bears (U. Arctos), and Black Bears (U. Americanus) Derived from Genome Sequences
We assessed the relationships of polar bears (Ursus maritimus), brown bears (U. arctos), and black bears (U. americanus) with high throughput genomic sequencing data with an average coverage of 25× for each species. A total of 1.4 billion 100-bp paired-end reads were assembled using the polar bear and annotated giant panda (Ailuropoda melanoleuca) genome sequences as references. We identified 13.8 million single nucleotide polymorphisms (SNP) in the 3 species aligned to the polar bear genome. These data indicate that polar bears and brown bears share more SNP with each other than either does with black bears. Concatenation and coalescence-based analysis of consensus sequences of approximately 1 million base pairs of ultraconserved elements in the nuclear genome resulted in a phylogeny with black bears as the sister group to brown and polar bears, and all brown bears are in a separate clade from polar bears. Genotypes for 162 SNP loci of 336 bears from Alaska and Montana showed that the species are genetically differentiated and there is geographic population structure of brown and black bears but not polar bears
Data from: Molecular phylogeny and SNP variation of polar bears (Ursus maritimus), brown bears (U. arctos) and black bears (U. americanus) derived from genome sequences
We assessed the relationships of polar bears (Ursus maritimus), brown bears (U. arctos), and black bears (U. americanus) with high throughput genomic sequencing data with an average coverage of 25X for each species. A total of 1.4 billion 100-bp paired-end reads was assembled using the polar bear and annotated giant panda (Ailuropoda melanoleuca) genome sequences as references. We identified 13.8 million single nucleotide polymorphisms (SNP) in the three species aligned to the polar bear genome. These data indicate that polar bears and brown bears share more SNP with each other than either does with black bears. Concatenation and coalescence-based analysis of consensus sequences of approximately one million base pairs of ultra-conserved elements (UCE) in the nuclear genome resulted in a phylogeny with black bears as the sister group to brown and polar bears, and all brown bears are in a separate clade from polar bears. Genotypes for 162 SNP loci of 336 bears from Alaska and Montana showed that the species are genetically differentiated and there is geographic population structure of brown and black bears but not polar bears
Prediction of transcript isoforms in 19 chicken tissues by Oxford Nanopore long-read sequencing.
To identify and annotate transcript isoforms in the chicken genome, we generated Nanopore long-read sequencing data from 68 samples that encompassed 19 diverse tissues collected from experimental adult male and female White Leghorn chickens. More than 23.8 million reads with mean read length of 790 bases and average quality of 18.2 were generated. The annotation and subsequent filtering resulted in the identification of 55,382 transcripts at 40,547 loci with mean length of 1,700 bases. We predicted 30,967 coding transcripts at 19,461 loci, and 16,495 lncRNA transcripts at 15,512 loci. Compared to existing reference annotations, we found ∼52% of annotated transcripts could be partially or fully matched while ∼47% were novel. Seventy percent of novel transcripts were potentially transcribed from lncRNA loci. Based on our annotation, we quantified transcript expression across tissues and found two brain tissues (i.e., cerebellum and cortex) expressed the highest number of transcripts and loci. Furthermore, ∼22% of the transcripts displayed tissue specificity with the reproductive tissues (i.e., testis and ovary) exhibiting the most tissue-specific transcripts. Despite our wide sampling, ∼20% of Ensembl reference loci were not detected. This suggests that deeper sequencing and additional samples that include different breeds, cell types, developmental stages, and physiological conditions, are needed to fully annotate the chicken genome. The application of Nanopore sequencing in this study demonstrates the usefulness of long-read data in discovering additional novel loci (e.g., lncRNA loci) and resolving complex transcripts (e.g., the longest transcript for the TTN locus)
BearUCE_with_PartitionsRob
Nexus file of 996,381 nucleotides of concatenated Ultra Conserved Elements sequences from polar, brown, and black bears and other carnivora