Size of the Ovulatory Follicle Dictates Spatial Differences in the Oviductal Transcriptome in Cattle

In cattle, molecular control of oviduct receptivity to the embryo is poorly understood. Here, we used a bovine model for receptivity based on size of the pre-ovulatory follicle to compare oviductal global and candidate gene transcript abundance on day 4 of the estrous cycle. Growth of the pre-ovulatory follicle (POF) of Nelore (Bos indicus) cows was manipulated to produce two groups: large POF large corpus luteum (CL) group (LF-LCL; greater receptivity) and small POF-small CL group (SF-SCL). Oviductal samples were collected four days after GnRH-induced ovulation. Ampulla and isthmus transcriptome was obtained by RNA-seq, regional gene expression was assessed by qPCR, and PGR and ERa protein distribution was evaluated by immunohistochemistry. There was a greater abundance of PGR and ERa in the oviduct of LF-LCL animals thus indicating a greater availability of receptors and possibly sex steroids stimulated signaling in both regions. Transcriptomic profiles indicated a series of genes associated with functional characteristics of the oviduct that are regulated by the periovulatory sex steroid milieu and that potentially affect oviductal receptivity and early embryo development. They include tissue morphology changes (extra cellular matrix remodeling), cellular changes (proliferation), and secretion changes (growth factors, ions and metal transporters), and were enriched for the genes with increased expression in the LF-LCL group. In conclusion, differences in the periovulatory sex steroid milieu lead to different oviductal gene expression profiles that could modify the oviductal environment to affect embryo survival and development

Oviductal transcriptional profiling of a bovine fertility model by next-generation sequencing

In cattle, the oviduct plays a fundamental role in the reproductive process. Oviductal functions are controlled by the ovarian sex steroids: estradiol and progesterone. Here, we tested the hypothesis that the exposure to contrasting sex steroid milieus differentially impacts the oviductal transcriptional profile. We manipulated growth of the pre-ovulatory follicle to obtain cows that ovulated a larger (LF group) or a smaller (SF group) follicle. The LF group presented greater proestrus/estrus concentrations of estradiol and metaestrus concentrations of progesterone (Gonella-Diaza et al. 2015 [1], Mesquita et al. 2014 [2]). Also, the LF group was associated with greater fertility in timed-artificial insemination programs (Pugliesi et al. 2016 [3]). Cows were slaughtered on day 4 of the estrous cycle and total RNA was extracted from ampulla and isthmus fragments and analyzed by RNAseq. The resulting reads were mapped to the bovine genome (Bos taurus UMD 3.1, NCBI). The differential expression analyses revealed that 325 and 367 genes in ampulla and 274 and 316 genes in the isthmus were up-regulated and down-regulated in LF samples, respectively. To validate the RNAseq results, transcript abundance of 23 genes was assessed by qPCR and expression patterns were consistent between the two techniques. A functional enrichment analysis was performed using Database for Annotation, Visualization and Integrated Discovery (DAVID) software. Processes enriched in the LF group included tissue morphology changes (extracellular matrix remodeling), cellular changes (proliferation), and secretion changes (growth factors, ions and metal transporters). An overview of the gene expression data was deposited in the NCBI's Gene Expression Omnibus (GEO) and is accessible through the accession number GSE65681. In conclusion, differences in the peri-ovulatory sex steroid milieu modify the oviductal gene expression profiles. Such differences may be associated with the greater fertility of the LF cows. This dataset is useful for further investigations of the oviductal biology and the impact of sex-steroid on the female reproductive tract

Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines

Abstract\ud \ud Background\ud Meat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection.\ud \ud \ud Results\ud A total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development.\ud \ud \ud Conclusions\ud In this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common genetic variants from a Brazilian broiler and a white egg layer line that can be used for genomic studies involving association analysis with phenotypes of economic interest to the poultry industry.CB received a fellowship from the program Science Without Borders - National Council for Scientific and Technological Development (CNPq, grant 370620/2013–5). GCMM and TFG received fellowships from São Paulo Research Foundation (FAPESP, grants 14/21380–9 and 15/00616–7). LLC is recipient of productivity fellowship from CNPq. This project was funded by São Paulo Research Foundation (FAPESP) - thematic project (2014/08704–0)

Gene expression profiling by high throughput sequencing to determine signatures for the bovine receptive uterus at early gestation

The uterus plays a central role among the reproductive tissues in the context of early embryo-maternal communication and a successful pregnancy depends on a complex series of endometrial molecular and cellular events. The factors responsible for the initial interaction between maternal and embryonic tissues, leading to the establishment of pregnancy, remain poorly understood. In this context, Illumina's next-generation sequencing technology has been used to discover the uterine transcriptome signature that is favourable for ongoing pregnancy. More specifically, the present report documents on a retrospective in vivo study in which data on pregnancy outcome were linked to uterine gene expression signatures on day 6 (bovine model). Using the RNA-Seq method, 14.654 reference genes were effectively analysed for differential expression between pregnant and non-pregnant uterine tissue. Transcriptome data revealed that 216 genes were differently expressed when comparing uterine tissue from pregnant and non-pregnant cows. All read sequences were deposited in the Sequence Read Archive (SRA) of the NCBI (http://www.ncbi.nlm.nih.gov/sra). An overview of the gene expression data has been deposited in NCBI's Gene Expression Omnibus (GEO) and is accessible through GEO Series accession number GSE65117. This allows the research community to enhance reproducibility and allows for new discoveries by comparing datasets of signatures linked to receptivity and/or pregnancy success. The resulting information can serve as tool to identify valuable and urgently needed biomarkers for scoring maternal receptivity and even for accurate detection of early pregnancy, which is a matter of cross-species interest. Beyond gene expression analysis as a marker tool, the RNA-Seq information on pregnant uterine tissue can be used to gain novel mechanistic insights, such as by identifying alternative splicing events, allele-specific expression, and rare and novel transcripts that might be involved in the onset of maternal receptivity. This concept is unique and provides a new approach towards strategies that are highly needed to improve efficiency of fertility treatments

The transcriptome signature of the receptive bovine uterus determined at early gestation.

Pregnancy success is critical to the profitability of cattle operations. However, the molecular events driving the uterine tissue towards embryo receptivity are poorly understood. This study aimed to characterize the uterine transcriptome profiles of pregnant (P) versus non-pregnant (NP) cows during early pregnancy and attempted to define a potential set of marker genes that can be valuable for predicting pregnancy outcome. Therefore, beef cows were synchronized (n=51) and artificially inseminated (n=36) at detected estrus. Six days after AI (D6), jugular blood samples and a biopsy from the uterine horn contralateral to the ovary containing the corpus luteum were collected. Based on pregnancy outcome on D30, samples were retrospectively allocated to the following groups: P (n=6) and NP (n=5). Both groups had similar plasma progesterone concentrations on D6. Uterine biopsies were submitted to RNA-Seq analysis in a Illumina platform. The 272,685,768 million filtered reads were mapped to the Bos Taurus reference genome and 14,654 genes were analyzed for differential expression between groups. Transcriptome data showed that 216 genes are differently expressed when comparing NP versus P uterine tissue (Padj ≤ 0.1). More specifically, 36 genes were up-regulated in P cows and 180 are up-regulated in NP cows. Functional enrichment and pathway analyses revealed enriched expression of genes associated with extracellular matrix remodeling in the NP cows and nucleotide binding, microsome and vesicular fraction in the P cows. From the 40 top-ranked genes, the transcript levels of nine genes were re-evaluated using qRT-PCR. In conclusion, this study characterized a unique set of genes, expressed in the uterus 6 days after insemination, that indicate a receptive state leading to pregnancy success. Furthermore, expression of such genes can be used as potential markers to efficiently predict pregnancy success

Pregnant and non-pregnant uterine differential gene expression.

<p>Heatmap and hierarchical clustering of all 11 samples based on the most differentially expressed genes (Padjusted).</p

List displaying the 20 top-annotated genes (based on Log2Fold-Change) with up-regulated expression in uterine biopsies from pregnant cows <i>Padj</i> ≤0.1.

<p>List displaying the 20 top-annotated genes (based on Log2Fold-Change) with up-regulated expression in uterine biopsies from pregnant cows <i>Padj</i> ≤0.1.</p

GO analysis and enrichment.

<p>Enriched categories for cellular component, molecular function, and biological process for the pregnant group.</p

List of primers used to validate RNA-Seq results.

<p>List of primers used to validate RNA-Seq results.</p

Plasma concentrations (mean ± SEM) of estradiol (top panel) and progesterone (bottom panel) of cows in the LF/LCL group (n = 13) and in the SF/SCL group (n = 8).

<p>Within a given Day, significantly different means (P < 0.05) were indicated by an asterisk (*). LF/LCL, large follicle-large CL; SF/SCL, small follicle-small CL.</p