Abstract

Background

   Cryptorchidism is the most frequent congenital disorder in male
   children; however the genetic causes of cryptorchidism remain poorly
   investigated. Comparative integratomics combined with systems biology
   approach was employed to elucidate genetic factors and molecular
   pathways underlying testis descent.

Methods

   Literature mining was performed to collect genomic loci associated with
   cryptorchidism in seven mammalian species. Information regarding the
   collected candidate genes was stored in MySQL relational database.
   Genomic view of the loci was presented using Flash GViewer web tool
   (http://gmod.org/wiki/Flashgviewer/). DAVID Bioinformatics Resources
   6.7 was used for pathway enrichment analysis. Cytoscape plug-in PiNGO
   1.11 was employed for protein-network-based prediction of novel
   candidate genes. Relevant protein-protein interactions were confirmed
   and visualized using the STRING database (version 9.0).

Results

   The developed cryptorchidism gene atlas includes 217 candidate loci
   (genes, regions involved in chromosomal mutations, and copy number
   variations) identified at the genomic, transcriptomic, and proteomic
   level. Human orthologs of the collected candidate loci were presented
   using a genomic map viewer. The cryptorchidism gene atlas is freely
   available online: http://www.integratomics-time.com/cryptorchidism/.
   Pathway analysis suggested the presence of twelve enriched pathways
   associated with the list of 179 literature-derived candidate genes.
   Additionally, a list of 43 network-predicted novel candidate genes was
   significantly associated with four enriched pathways. Joint pathway
   analysis of the collected and predicted candidate genes revealed the
   pivotal importance of the muscle-contraction pathway in cryptorchidism
   and evidence for genomic associations with cardiomyopathy pathways in
   RASopathies.

Conclusions

   The developed gene atlas represents an important resource for the
   scientific community researching genetics of cryptorchidism. The
   collected data will further facilitate development of novel genetic
   markers and could be of interest for functional studies in animals and
   human. The proposed network-based systems biology approach elucidates
   molecular mechanisms underlying co-presence of cryptorchidism and
   cardiomyopathy in RASopathies. Such approach could also aid in
   molecular explanation of co-presence of diverse and apparently
   unrelated clinical manifestations in other syndromes.

   Keywords: Cryptorchidism, Muscle-contraction pathway, Cardiomyopathy,
   Comparative integratomics, Protein-protein interactions, Systems
   biology, Undescended testes, RASopathy

Background

   Cryptorchidism (CO) is the most frequent congenital disorder in male
   children (2-4% of full-term male births) and is defined as incomplete
   descent of one (unilateral) or both (bilateral) testes and associated
   structures. Cryptorchidism has a potential effect on health; defects in
   testes descent usually cause impaired spermatogenesis, resulting in
   reduced fertility and increased rates of testicular neoplasia, and
   testicular torsion (reviewed in [[34]1]). Cryptorchidism is common in
   human, pigs, and companion animals (2–12%) but relatively rare in
   cattle, and sheep (≤ 1%) [[35]2].

   Testicular descent is a complex series of events which requires
   concerted action of hormones, constitutive mechanisms, and the nervous
   system. In most species, including human, the complete descent of
   testes usually occurs prenatally, while in some (e.g. dogs),
   postnatally. Beside environmental factors like endocrine disruptors, CO
   is at least in part determined by genetic causes (chromosome or gene
   mutations), and is often a common feature of different syndromes. For
   example, Klinefelter syndrome and mutations in INSL3 gene have already
   been recognized as a cause of CO in some cases [[36]3].

   The comparative knowledge attained through study of animal models has
   been of great importance in understanding complex disease etiology,
   suggesting several candidate genes involved also in the pathogenesis of
   human diseases [[37]4]. Therefore, the use of comparative genomics
   approach, integrating and cross-filtering the available knowledge from
   different species seems highly justified. Different animal models for
   CO exist; for example natural mutants or transgenic mice, rat, rabbit,
   dog, pig and rhesus monkeys are used to elucidate the role of different
   factors involved in CO [[38]5]. Based on mouse knock-out models from
   Mouse Genome Informatics (MGI) database, several genes appear as
   possible candidates (AR, HOX genes, INSL3, RXFP2, and WT1).
   Additionally, the technological progress in the last years enabled the
   use of high-throughput omics-information, at coding (DNA), expression
   (RNA), and proteomic level. This technological revolution creates a
   vast amount of data, which increases the need for application of
   bioinformatics tools that are able to connect omics data with phenotype
   and enable search for overlapping pathogenetic mechanisms in different
   genetic diseases [[39]6]. However, this existing technology hasn’t been
   significantly employed in human CO research on a genome and
   transcriptome-wide scale; to date only one genome-wide expression study
   has been performed in rat [[40]7].

   Integratomics represents a novel trend in the omics-research and is
   based on the integration of diverse omics-data (genomic,
   transcriptomic, proteomic, etc.), regardless of the study approach or
   species [[41]8-[42]10]. High genetic homology between mammals and the
   availability of well annotated genomes from different species allows
   the assembled data to be presented in a form of a comparative genomic
   view, displaying candidate genes as a single species orthologs.

   Information extracted from diverse and methodologically focused studies
   are often fragmented and controversial. To overcome this problem we
   integrated the collected data, using a holistic (map-driven) approach,
   and developed freely available interactive genomic visualization tool.
   Such map-based approach allows identification and prioritization of
   candidate genes [[43]11] based on a number of literature sources
   (references), genomic position, and pathway analyses, employing all