Selection for female traits of high fertility affects male reproductive performance and alters the testicular transcriptional profile

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Abstract

Background

Many genes important for reproductive performance are shared by both sexes. However, fecundity indices are primarily based on female parameters such as litter size. We examined a fertility mouse line (FL2), which has a considerably increased number of offspring and a total litter weight of 180% compared to a randomly bred control line (Ctrl) after more than 170 generations of breeding. In the present study, we investigated whether there might be a parallel evolution in males after more than 40 years of breeding in this outbred mouse model.

Results

Males of the fertility mouse line FL2 showed reduced sperm motility performance in a 5 h thermal stress experiment and reduced birth rate in the outbred mouse line. Transcriptional analysis of the FL2 testis showed the differential expression of genes associated with steroid metabolic processes (Cyp1b1, Cyp19a1, Hsd3b6, and Cyp21a1) and female fecundity (Gdf9), accompanied by 150% elevated serum progesterone levels in the FL2 males. Cluster analysis revealed the downregulation of genes of the kallikrein-related peptidases (KLK) cluster located on chromosome 7 in addition to alterations in gene expression with serine peptidase activity, e.g., angiotensinogen (Agt), of the renin-angiotensin system essential for ovulation. Although a majority of functional annotations map to female reproduction and ovulation, these genes are differentially expressed in FL2 testis.

Conclusions

These data indicate that selection for primary female traits of increased litter size not only affects sperm characteristics but also manifests as transcriptional alterations of the male side likely with direct long-term consequences for the reproductive performance of the mouse line.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4288-z) contains supplementary material, which is available to authorized users.

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Most cited references 65

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The PANTHER database of protein families, subfamilies, functions and pathways

Huaiyu Mi, Betty Lazareva-Ulitsky, Rozina Loo … (2004)

PANTHER is a large collection of protein families that have been subdivided into functionally related subfamilies, using human expertise. These subfamilies model the divergence of specific functions within protein families, allowing more accurate association with function (ontology terms and pathways), as well as inference of amino acids important for functional specificity. Hidden Markov models (HMMs) are built for each family and subfamily for classifying additional protein sequences. The latest version, 5.0, contains 6683 protein families, divided into 31 705 subfamilies, covering ∼90% of mammalian protein-coding genes. PANTHER 5.0 includes a number of significant improvements over previous versions, most notably (i) representation of pathways (primarily signaling pathways) and association with subfamilies and individual protein sequences; (ii) an improved methodology for defining the PANTHER families and subfamilies, and for building the HMMs; (iii) resources for scoring sequences against PANTHER HMMs both over the web and locally; and (iv) a number of new web resources to facilitate analysis of large gene lists, including data generated from high-throughput expression experiments. Efforts are underway to add PANTHER to the InterPro suite of databases, and to make PANTHER consistent with the PIRSF database. PANTHER is now publicly available without restriction at http://panther.appliedbiosystems.com.

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The evolutionary dynamics of eukaryotic gene order.

Laurence D. Hurst, Csaba Pál, Martin J Lercher (2004)

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Clustering of housekeeping genes provides a unified model of gene order in the human genome.

Martin J Lercher, Araxi O Urrutia, Laurence D. Hurst … (2002)

It is often supposed that, except for tandem duplicates, genes are randomly distributed throughout the human genome. However, recent analyses suggest that when all the genes expressed in a given tissue (notably placenta and skeletal muscle) are examined, these genes do not map to random locations but instead resolve to clusters. We have asked three questions: (i) is this clustering true for most tissues, or are these the exceptions; (ii) is any clustering simply the result of the expression of tandem duplicates and (iii) how, if at all, does this relate to the observed clustering of genes with high expression rates? We provide a unified model of gene clustering that explains the previous observations. We examined Serial Analysis of Gene Expression (SAGE) data for 14 tissues and found significant clustering, in each tissue, that persists even after the removal of tandem duplicates. We confirmed clustering by analysis of independent expressed-sequence tag (EST) data. We then tested the possibility that the human genome is organized into subregions, each specializing in genes needed in a given tissue. By comparing genes expressed in different tissues, we show that this is not the case: those genes that seem to be tissue-specific in their expression do not, as a rule, cluster. We report that genes that are expressed in most tissues (housekeeping genes) show strong clustering. In addition, we show that the apparent clustering of genes with high expression rates is a consequence of the clustering of housekeeping genes.

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Author and article information

Contributors

Marten Michaelis: +49-38208-68788 , michaelis@fbn-dummerstorf.de

Alexander Sobczak: alexander.sobczak@gmx.net

Dirk Koczan: dirk.koczan@med.uni-rostock.de

Martina Langhammer: martina.langhammer@fbn-dummerstorf.de

Norbert Reinsch: reinsch@fbn-dummerstorf.de

Jennifer Schoen: schoen.jennifer@fbn-dummerstorf.de

Joachim M. Weitzel: +49-38208-68788 , weitzel@fbn-dummerstorf.de

Journal

Journal ID (nlm-ta): BMC Genomics

Journal ID (iso-abbrev): BMC Genomics

Title: BMC Genomics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2164

Publication date (Electronic): 21 November 2017

Publication date PMC-release: 21 November 2017

Publication date Collection: 2017

Volume: 18

Electronic Location Identifier: 889

Affiliations

[1 ]ISNI 0000000121858338, GRID grid.10493.3f, Institute of Reproductive Biology, , University of Rostock, ; Rostock, Germany

[2 ]ISNI 0000 0000 9049 5051, GRID grid.418188.c, Institute of Genetics and Biometry, , Leibniz Institute for Farm Animal Biology (FBN), ; Dummerstorf, Germany

[3 ]Institute of Immunology, University of Rostock, Rostock, Germany

[4 ]ISNI 0000 0000 9049 5051, GRID grid.418188.c, Leibniz Institute for Farm Animal Biology (FBN), Institute of Reproductive Biology, , FBN Dummerstorf, ; Wilhelm-Stahl-Allee 2, 18196, Dummerstorf, Germany

Article

Publisher ID: 4288

DOI: 10.1186/s12864-017-4288-z

PMC ID: 5697431

PubMed ID: 29157197

SO-VID: 51d5f595-f290-4a28-998d-5cb81ab02d73

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 17 October 2016

Date accepted : 8 November 2017

Funding

Funded by: Research Committee for Ataxic Disease, the Ministry of Health, Labour and Welfare (JP)

Funded by: Research Committee of CNS Degenerative Disease, the Ministry of Health, Labour and Welfare (JP)

Funded by: Translational Research Network Program, Japan Agency for Medical Research and Development

Funded by: Mitsubishi Tanabe Pharma Corporation

Funded by: Practical Research Project for Rare/Intractable Diseases, Japan Agency for Medical Research and Development

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: long-term selection mouse lines,outbred mouse model,high-fertility,fecundity,testis,reproductive fitness,sperm motility,casa

Data availability:

ScienceOpen disciplines: Genetics

Keywords: long-term selection mouse lines, outbred mouse model, high-fertility, fecundity, testis, reproductive fitness, sperm motility, casa

Selection for female traits of high fertility affects male reproductive performance and alters the testicular transcriptional profile

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Abstract

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Conclusions

Electronic supplementary material

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Genes & Diseases

Most cited references 65

The PANTHER database of protein families, subfamilies, functions and pathways

The evolutionary dynamics of eukaryotic gene order.

Clustering of housekeeping genes provides a unified model of gene order in the human genome.

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