Show simple item record

dc.contributor.authorKikas, T
dc.contributor.authorRull, K
dc.contributor.authorBeaumont, RN
dc.contributor.authorFreathy, RM
dc.contributor.authorLaan, M
dc.date.accessioned2019-07-01T13:42:15Z
dc.date.issued2019-06-11
dc.description.abstractThe knowledge of genetic variants shaping human placental transcriptome is limited and they are not cataloged in the Genotype-Tissue Expression project. So far, only one whole genome analysis of placental expression quantitative trait loci (eQTLs) has been published by Peng et al. (2017) with no external independent validation. We report the second study on the landscape of placental eQTLs. The study aimed to generate a high-confidence list of placental cis-eQTLs and to investigate their potential functional implications. Analysis of cis-eQTLs (±100 kbp from the gene) utilized 40 placental RNA sequencing and respective whole genome genotyping datasets. The identified 199 placental cis-eSNPs represented 88 independent eQTL signals (FDR < 5%). The most significant placental eQTLs (FDR < 10-5) modulated the expression of ribosomal protein RPL9, transcription factor ZSCAN9 and aminopeptidase ERAP2. The analysis confirmed 50 eSNP-eGenes pairs reported by Peng et al. (2017) and thus, can be claimed as robust placental eQTL signals. The study identified also 13 novel placental eGenes. Among these, ZSCAN9 is modulated by several eSNPs (experimentally validated: rs1150707) that have been also shown to affect the methylation level of genes variably escaping X-chromosomal inactivation. The identified 63 placental eGenes exhibited mostly mixed or ubiquitous expression. Functional enrichment analysis highlighted 35 Gene Ontology categories with the top ranking pathways “ruffle membrane” (FDR = 1.81 × 10-2) contributing to the formation of motile cell surface and “ATPase activity, coupled” (FDR = 2.88 × 10-2), critical for the membrane transport. Placental eGenes were also significantly enriched in pathways implicated in development, signaling and immune function. However, this study was not able to confirm a significant overrepresentation of genome-wide association studies top hits among the placental eSNP and eGenes, reported by Peng et al. (2017). The identified eSNPs were further analyzed in association with newborn and pregnancy traits. In the discovery step, a suggestive association was detected between the eQTL of ALPG (rs11678251) and reduced placental, newborn’s and infant’s weight. Meta-analysis across REPROMETA, HAPPY PREGNANCY, ALSPAC cohorts (n = 6830) did not replicate these findings. In summary, the study emphasizes the role of genetic variation in driving the transcriptome profile of the human placenta and the importance to explore further its functional implications.en_GB
dc.description.sponsorshipWellcome Trusten_GB
dc.description.sponsorshipEstonian Research Councilen_GB
dc.description.sponsorshipEuropean Unionen_GB
dc.description.sponsorshipMedical Research Councilen_GB
dc.description.sponsorshipUniversity of Bristolen_GB
dc.identifier.citationPublished online 11 June 2019en_GB
dc.identifier.doi10.3389/fgene.2019.00550
dc.identifier.grantnumber104150/Z/14/Zen_GB
dc.identifier.grantnumberIUT34-12 for MLen_GB
dc.identifier.grantnumberproject HAPPY PREGNANCY, 3.2.0701.12-0047en_GB
dc.identifier.grantnumber102215/2/13/2en_GB
dc.identifier.urihttp://hdl.handle.net/10871/37774
dc.language.isoenen_GB
dc.publisherFrontiers Mediaen_GB
dc.rightsCopyright © 2019 Kikas, Rull, Beaumont, Freathy and Laan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_GB
dc.titleThe Effect of Genetic Variation on the Placental Transcriptome in Humansen_GB
dc.typeArticleen_GB
dc.date.available2019-07-01T13:42:15Z
dc.identifier.issn1664-8021
dc.descriptionThis is the author accepted manuscript. The final version is available from Frontiers Media via the DOI in this record .en_GB
dc.descriptionThe Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2019.00550/full#supplementary-materialen_GB
dc.identifier.journalFrontiers in Geneticsen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2019-05-24
exeter.funder::Wellcome Trusten_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2019-06-11
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-07-01T13:29:20Z
refterms.versionFCDAM
refterms.dateFOA2019-07-01T13:42:18Z
refterms.panelAen_GB


Files in this item

This item appears in the following Collection(s)

Show simple item record

Copyright © 2019 Kikas, Rull, Beaumont, Freathy and Laan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Except where otherwise noted, this item's licence is described as Copyright © 2019 Kikas, Rull, Beaumont, Freathy and Laan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.