Evidence map›Paper›PMID 36739419›Full record

ArticleJournal of ovarian research2023

Alterations in gonadotropin, apoptotic and metabolic pathways in granulosa cells warrant superior fertility of the Dummerstorf high fertility mouse line 1.

Carolin Lisa Michaela Ludwig, Simon Bohleber, Rebecca Lapp, Alexander Rebl, Eva Katrin Wirth, Martina Langhammer, Ulrich Schweizer, Joachim M Weitzel, Marten Michaelis

Open access · goldAbstract read
In one paragraph

Article in Journal of ovarian research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
7.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Carolin Lisa Michaela LudwigResearch Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
Simon BohleberInstitut für Biochemie und Molekularbiologie (IBMB), Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.
Rebecca LappResearch Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
Alexander ReblResearch Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
Eva Katrin WirthDepartment of Endocrinology and Metabolism, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
Martina LanghammerResearch Institute for Farm Animal Biology (FBN), Dummerstorf, Germany.
Ulrich SchweizerInstitut für Biochemie und Molekularbiologie (IBMB), Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.
Joachim M WeitzelResearch Institute for Farm Animal Biology (FBN), Dummerstorf, Germany. weitzel@fbn-dummerstorf.de.
Marten MichaelisResearch Institute for Farm Animal Biology (FBN), Dummerstorf, Germany. michaelis@fbn-dummerstorf.de.
Research Institute for Farm Animal Biology (FBN) · DEUniversity of Bonn · DEHumboldt-Universität zu Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development and maturation of ovarian follicles is a complex and highly regulated process, which is essential for successful ovulation. During recent decades, several mouse models provided insights into the regulation of folliculogenesis. In contrast to the commonly used transgenic or knockout mouse models, the Dummerstorf high-fertility mouse line 1 (FL1) is a worldwide unique selection experiment for increased female reproductive performance and extraordinary high fertility. Interactions of cycle-related alterations of parameters of the hypothalamic pituitary gonadal axis and molecular factors in the ovary lead to improved follicular development and therefore increased ovulation rates in FL1 mice. FL1 females almost doubled the number of ovulated oocytes compared to the unselected control mouse line. To gain insights into the cellular mechanisms leading to the high fertility phenotype we used granulosa cells isolated from antral follicles for mRNA sequencing. Based on the results of the transcriptome analysis we additionally measured hormones and growth factors associated with follicular development to complement the picture of how the signaling pathways are regulated. While IGF1 levels are decreased in FL1 mice in estrus, we found no differences in insulin, prolactin and oxytocin levels in FL1 mice compared to the control line. The results of the mRNA sequencing approach revealed that the actions of insulin, prolactin and oxytocin are restricted local to the granulosa cells, since hormonal receptor expression is differentially regulated in FL1 mice. Additionally, numerous genes, which are involved in important gonadotropin, apoptotic and metabolic signaling pathways in granulosa cells, are differentially regulated in granulosa cells of FL1 mice.We showed that an overlap of different signaling pathways reflects the crosstalk between gonadotropin and growth factor signaling pathways, follicular atresia in FL1 mice is decreased due to improved granulosa cell survival and by improving the efficiency of intracellular signaling, glucose metabolism and signal transduction, FL1 mice have several advantages in reproductive performance and therefore increased the ovulation rate. Therefore, this worldwide unique high fertility model can provide new insights into different factors leading to improved follicular development and has the potential to improve our understanding of high fertility.

Indexed as

InsulinsProlactinAnimalsFemaleFertilityFollicular AtresiaGonadotropinsGranulosa CellsMetabolic Networks and PathwaysMiceOxytocinRNA, MessengerGonadotropinsInsulinsOxytocinProlactinRNA, MessengerFollicular survivalFSH signalingGranulosa cellsHigh-fertilityOvulation rate

Identifiers

PMID36739419
PMCPMC9898973
OpenAlexW4319231359

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.