Follicular fluid (FF), an important microenvironment for the development of oocytes, contains many proteins that are glycosylated with N -linked glycans. This study aimed i) to present an initial analysis of the N -linked glycan profile of bovine FF using hydrophilic interaction liquid chromatography, anion exchange chromatography, high performance liquid chromatography (HPLC)-based separations and subsequent liquid chromatography–mass spectrometry/mass spectrometry analysis; ii) to determine differences in the N -glycan profile between FF from dominant and subordinate follicles from dairy heifers and lactating dairy cows and iii) to identify alterations in the N -glycan profile of FF during preovulatory follicle development using newly selected, differentiated (preovulatory) and luteinised dominant follicles from dairy heifers and lactating cows. We found that the majority of glycans on bovine FF are based on biantennary hypersialylated structures, where the glycans are sialylated on both the galactose and N -acetylglucosamine terminal sugars. A comparison of FF N -glycans from cows and heifers indicated higher levels of nonsialylated glycans with a lower proportion of sialylated glycans in cows than in heifers. Overall, as the follicle develops from Selection, Differentiation and Luteinisation in both cows and heifers, there is an overall decrease in sialylated structures on FF N -glycans.
Domestication of the now-extinct wild aurochs, Bos primigenius, gave rise to the two major domestic extant cattle taxa, B. taurus and B. indicus. While previous genetic studies have shed some light on the evolutionary relationships between European aurochs and modern cattle, important questions remain unanswered, including the phylogenetic status of aurochs, whether gene flow from aurochs into early domestic populations occurred, and which genomic regions were subject to selection processes during and after domestication. Here, we address these questions using whole-genome sequencing data generated from an approximately 6,750-year-old British aurochs bone and genome sequence data from 81 additional cattle plus genome-wide single nucleotide polymorphism data from a diverse panel of 1,225 modern animals. Phylogenomic analyses place the aurochs as a distinct outgroup to the domestic B. taurus lineage, supporting the predominant Near Eastern origin of European cattle. Conversely, traditional British and Irish breeds share more genetic variants with this aurochs specimen than other European populations, supporting localized gene flow from aurochs into the ancestors of modern British and Irish cattle, perhaps through purposeful restocking by early herders in Britain. Finally, the functions of genes showing evidence for positive selection in B. taurus are enriched for neurobiology, growth, metabolism and immunobiology, suggesting that these biological processes have been important in the domestication of cattle. This work provides important new information regarding the origins and functional evolution of modern cattle, revealing that the interface between early European domestic populations and wild aurochs was significantly more complex than previously thought.
Abstract Motivation: Microarrays are widely used to measure gene expression differences between sets of biological samples. Many of these differences will be due to differences in the activities of transcription factors. In principle, these differences can be detected by associating motifs in promoters with differences in gene expression levels between the groups. In practice, this is hard to do. Results: We combine correspondence analysis, between group analysis and co-inertia analysis to determine which motifs, from a database of promoter motifs, are strongly associated with differences in gene expression levels. Given a database of motifs and gene expression levels from a set of arrays, the method produces a ranked list of motifs associated with any specified split in the arrays. We give an example using the Gene Atlas compendium of gene expression levels for human tissues where we search for motifs that are associated with expression in central nervous system (CNS) or muscle tissues. Most of the motifs that we find are known from previous work to be strongly associated with expression in CNS or muscle. We give a second example using a published prostate cancer dataset where we can simply and clearly find which transcriptional pathways are associated with differences between benign and metastatic samples. Availability: The source code is freely available upon request from the authors. Contact: Ian.Jeffery@ucd.ie
Successful growth and development of the posthatching blastocyst and pregnancy establishment are a result of the interaction between a competent embryo and a receptive uterine environment. We examined the global transcriptome profiles of the Day 16 bovine conceptus and pregnant endometrium tissues using RNA-Seq to identify genes that contribute to the dialogue during the period of pregnancy recognition. Using stringent filtering criterion, a total of 16 018 and 16 262 transcripts of conceptus and pregnant endometrium origin, respectively, were identified with distinct tissue-specific expression profiles. Of these, 2261 and 2505 transcripts were conceptus and endometrium specific. Using Cytoscape software, a total of 133 conceptus ligands that interact with corresponding receptors on the endometrium and 121 endometrium ligands that interact with corresponding receptors on the conceptus were identified. While 87 ligands were commonly detected, 46 were conceptus specific and 34 endometrium specific. This study is one of the first to provide a comprehensive list of potentially secreted molecules in the conceptus that interact with receptors on the endometrium and vice versa during the critical window of maternal recognition of pregnancy. The identified tissue-specific genes may serve as candidates to study pregnancy recognition and they or downstream products may represent potential early markers of pregnancy.
Summary Objective To establish the genetic basis of L andau‐ K leffner syndrome ( LKS ) in a cohort of two discordant monozygotic ( MZ ) twin pairs and 11 isolated cases. Methods We used a multifaceted approach to identify genetic risk factors for LKS . Array comparative genomic hybridization (CGH) was performed using the A gilent 180K array. Whole genome methylation profiling was undertaken in the two discordant twin pairs, three isolated LKS cases, and 12 control samples using the I llumina 27K array. Exome sequencing was undertaken in 13 patients with LKS including two sets of discordant MZ twins. Data were analyzed with respect to novel and rare variants, overlapping genes, variants in reported epilepsy genes, and pathway enrichment. Results A variant (c G 1553 A ) was found in a single patient in the GRIN2A gene, causing an arginine to histidine change at site 518, a predicted glutamate binding site. Following copy number variation ( CNV ), methylation, and exome sequencing analysis, no single candidate gene was identified to cause LKS in the remaining cohort. However, a number of interesting additional candidate variants were identified including variants in RELN , BSN, EPHB2, and NID2 . Significance A single mutation was identified in the GRIN2A gene. This study has identified a number of additional candidate genes including RELN , BSN , EPHB2, and NID2 . A PowerPoint slide summarizing this article is available for download in the Supporting Information section here .
G-protein coupled receptors (GPCR) comprise a large protein family of transmembrane receptors that sense molecules outside the cell to activate the signal transduction pathways inside and, ultimately, the cellular responses. They have a central role in various physiological systems that places them at the forefront of many drug target programs and perturbation in their activity has been cited in many diseases, including infertility (Jean-Alphonse and Hanyaloglu 2011 Mol. Cell. Endocrinol. 331, 205–214). However, little information is available on the types of GPCR and their expression in the bovine conceptus during maternal recognition of pregnancy. The aim of this study was, therefore, to take advantage of the bovine conceptus global gene expression profiles, particularly to examine the expression of various transcripts of GPCR during the window of maternal recognition of pregnancy. Global transcriptome profiling of the bovine conceptuses at 5 key stages of pre- and peri-implantation growth (Day 7, 10, 13, 16 and 19) was carried out using in vivo-derived embryos and state-of-the-art RNA sequencing techniques, following the Illumina standard procedures for library preparation and genome analyzer sequencing (Illumina, San Diego, CA, USA). Following various quality control procedures, the transcripts were mapped to the bovine genome. ANOVA was carried out to detect the differentially regulated transcripts between any 2 developmental stages followed by self-organizing map clustering to identify genes with a similar temporal expression pattern. Those transcripts differentially regulated on Day 16 (the day of maternal recognition of pregnancy in cattle) were screened and submitted to Ingenuity pathway analysis (Ingenuity Systems Inc., Redwood City, CA). Subsequently, the expression profiles of the transcripts in the GPCR network were examined across the 5 key developmental stages. Pathway analysis detected various transcript networks, including the GPCR network, comprising a large number of transcripts (∼30). These include F2RL2, GCGR, VIPR1, LPAR6, RAC2, LPHN3, PTGFR, PTH1R, CNR2, CD97, APLNR and various other GPCR family genes. Analysis of expression profiles across the 5 development stages revealed that these receptors were significantly (P < 0.05) upregulated at Day 16, compared with other time points. The significantly higher expression pattern of these GPCR during this critical stage of pregnancy may suggest an important role during this period of maternal recognition and establishment of pregnancy that contributes to embryo-maternal crosstalk during this critical period. Supported by Science Foundation Ireland (07/SRC/B1156).
Abstract Background Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. Results We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. Conclusions GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.
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