Infertility diagnosis has a significant impact on the transcriptome of developing blastocysts

STUDY QUESTION: Is the human blastocyst transcriptome associated with infertility diagnosis, specifically: polycystic ovaries (PCO), male factor (MF) and unexplained (UE)? SUMMARY ANSWER: The global blastocyst transcriptome was significantly altered in association with a PCO, MF and UE infertility diagnosis. WHAT IS KNOWN ALREADY: Infertility diagnosis has an impact on the probability for a successful outcome following an IVF cycle. Limited information is known regarding the relationship between a specific infertility diagnosis and blastocyst transcription during preimplantation development. STUDY DESIGN, SIZE, DURATION: Blastocysts created during infertility treatment from patients with specific infertility diagnoses (PCO, MF and UE) were analyzed for global transcriptome compared to fertile donor oocyte blastocysts (control). PARTICIPANTS/MATERIALS, SETTING, METHODS: Surplus cryopreserved blastocysts were donated with patient consent and institutional review board approval. Female patients were <38 years old with male patients <40 years old. Blastocysts were grouped according to infertility diagnosis: PCO (n = 50), MF (n = 50), UE (n = 50) and fertile donor oocyte controls (n = 50). Pooled blastocysts were lysed for RNA isolation followed by microarray analysis using the SurePrint G3 Human Gene Expression Microarray. Validation was performed on significant genes of interest using real-time quantitative PCR (RT-qPCR). MAIN RESULTS AND THE ROLE OF CHANCE: Transcription alterations were observed for all infertility etiologies compared to controls, resulting in differentially expressed genes: PCO = 869, MF = 348 and UE = 473 (P 2-fold). Functional annotation of biological and molecular processes revealed both similarities, as well as differences, across the infertility groups. All infertility etiologies displayed transcriptome alterations in signal transducer activity, receptor binding, reproduction, cell adhesion and response to stimulus. Blastocysts from PCO patients were also enriched for apoptotic genes while MF blastocysts displayed enrichment for genes involved in cancer processes. Blastocysts from couples with unexplained infertility displayed transcription alterations related to various disease states, which included mechanistic target of rapamycin (mTOR) and adipocytokine signaling. RT-qPCR validation confirmed differential gene expression for the following genes: BCL2 like 10 (BCL2L10), heat shock protein family A member 1A (HSPA1A), heat shock protein family A member 1B (HSPA1B), activating transcription factor 3 (ATF3), fibroblast growth factor 9 (FGF9), left-right determination factor 1 (LEFTY1), left-right determination factor 2 (LEFTY2), growth differentiation factor 15 (GDF15), inhibin beta A subunit (INHBA), adherins junctions associated protein 1 (AJAP1), cadherin 9 (CDH9) and laminin subunit alpha 4 (LAMA4) (P 2-fold)

Mapping the hinterland: Data issues in open science

© The Author(s) 2014. Open science is a practice in which the scientific process is shared completely and in real time. It offers the potential to support information flow, collaboration and dialogue among professional and non-professional participants. Using semi-structured interviews and case studies, this research investigated the relationship between open science and public engagement. This article concentrates on three particular areas of concern that emerged: first, how to effectively contextualise and narrate information to render it accessible, as opposed to simply available; second, concerns about data quantity and quality; and third, concerns about the skills required for effective contextualisation, mapping and interpretation of information

Compromised global embryonic transcriptome associated with advanced maternal age

Purpose To investigate the global transcriptome and associated embryonic molecular networks impacted with advanced maternal age (AMA). Methods Blastocysts derived from donor oocyte IVF cycles with no male factor infertility (< 30 years of age) and AMA blastocysts (≥ 42 years) with no other significant female factor infertility or male factor infertility were collected with informed patient consent. RNA sequencing libraries were prepared using the SMARTer® Ultra® Low Kit (Clontech Laboratories) and sequenced on the Illumina HiSEQ 4000. Bioinformatics included Ingenuity® Pathway Analysis (Qiagen) with ViiA™7 qPCR utilized for gene expression validation (Applied Biosystems). Results A total of 2688 significant differentially expressed transcripts were identified to distinguish the AMA blastocysts from young, donor controls. 2551 (95%) of these displayed decreased transcription in the blastocysts from older women. Pathway analysis revealed three altered molecular signaling networks known to be critical for embryo and fetal development: CREBBP, ESR1, and SP1. Validation of genes within these networks confirmed the global decreased transcription observed in AMA blastocysts (P < 0.05). Conclusions A significant, overall decreased global transcriptome was observed in blastocysts from AMA women. The ESR1/SP1/CREBBP pathway, in particular, was found to be a highly significant upstream regulator impacting biological processes that are vital during embryonic patterning and pre-implantation development. These results provide evidence that AMA embryos are compromised on a cell signaling level which can repress the embryo’s ability to proliferate and implant, contributing to a deterioration of reproductive outcomes

The impact of infertility diagnosis on embryo-endometrial dialogue

Initial stages of implantation involve bi-directional molecular crosstalk between the blastocyst and endometrium. This study investigated an association between infertility etiologies, specifically advanced maternal age (AMA) and endometriosis, on the embryo-endometrial molecular dialogue prior to implantation. Co-culture experiments were performed with endometrial epithelial cells (EEC) and cryopreserved day 5 blastocysts (n?=?41???Grade 3BB) donated from patients presenting with AMA or endometriosis, compared to fertile donor oocyte controls. Extracellular vesicles isolated from co-culture supernatant were analyzed for miRNA expression and revealed significant alterations correlating to AMA or endometriosis. Specifically, AMA resulted in 16 miRNAs with increased expression (P???0.05) and strong evidence for negative regulation toward 206 target genes. VEGFA, a known activator of cell adhesion, displayed decreased expression (P???0.05), validating negative regulation by 4 of these increased miRNAs: miR-126; 150; 29a; 29b (P???0.05). In endometriosis patients, a total of 10 significantly altered miRNAs displayed increased expression compared to controls (miR-7b; 9; 24; 34b; 106a; 191; 200b; 200c; 342-3p; 484) (P???0.05), targeting 1014 strong evidence-based genes. Three target genes of miR-106a (CDKN1A, E2F1 and RUNX1) were independently validated. Functional annotation analysis of miRNA-target genes revealed enriched pathways for both infertility etiologies, including disrupted cell cycle regulation and proliferation (P???0.05). These extracellular vesicle-bound secreted miRNAs are key transcriptional regulators in embryo-endometrial dialogue and may be prospective biomarkers of implantation success. One of the limitations of this study is that it was a stimulated, in vitro model and therefore may not accurately reflect the in-vivo environment

Mapping Public Engagement with Research in a UK University

Notwithstanding that ‘public engagement’ is conceptualised differently internationally and in different academic disciplines, higher education institutions largely accept the importance of public engagement with research. However, there is limited evidence on how researchers conceptualise engagement, their views on what constitutes engagement and the communities they would (or would not) like to engage with. This paper presents the results of a survey of researchers in the Open University that sought to gather data to fill these gaps. This research was part of an action research project designed to embed engagement in the routine practices of researchers at all levels. The findings indicate that researchers have a relatively narrow view of public engagement with research and the communities with which they interact. It also identified that very few strategically evaluate their public engagement activities. We conclude by discussing some of the interventions we have introduced with the aim of broadening and deepening future researcher engagement

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

BACKGROUND: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data was donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups