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Record W2069478547 · doi:10.1095/biolreprod.112.101402

Rhox5 Rules in an Evolving Saga of Reproductive Diversity

2012· letter· en· W2069478547 on OpenAlexaff
Geoffrey L. Hammond

Bibliographic record

VenueBiology of Reproduction · 2012
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologyDiversity (politics)Evolutionary biologyZoologyComputational biologyAnthropology

Abstract

fetched live from OpenAlex

Homeobox (Hox) genes encode several subfamilies of nuclear proteins with structurally conserved helix-turn-helix domains that recognize specific DNA sequences [1]. As transcription factors, HOX family members control key events during early development, influencing the organization of body patterning and tissue structures in all species of the animal kingdom from invertebrates to humans [1, 2]. In fully developed organisms, Hox genes contribute to tissue damage and repair mechanisms by controlling apoptosis, receptor signaling, differentiation, motility, and angiogenesis; when expressed abnormally, these activities can have oncogenic consequences [3]. Rhox5 was first identified by Wilkinson et al. [4] as an oncofetal gene (originally called Pem because it was expressed in placenta and embryos) that influenced the progression of Tcell lymphomas to their oncogenic phenotype. During the decade following its discovery, Pem was classified as an orphan member of the Hox gene family that is selectively expressed in reproductive tissues. It therefore followed that Pem was renamed Rhox5 when it was located within a syntenically conserved cluster of other, related reproductive Hox genes on the mouse X chromosome, which was dubbed the Rhox gene family locus in a groundbreaking report in 2005 [5]. In the intervening years, MacLean, Wilkinson, and their colleagues defined the roles of Rhox genes in reproductive tissues [6]. In an elegant report published in the current issue of Biology of Reproduction, MacLean et al. [7] have integrated the power of mouse genetics with the emerging discipline of comparative genomics to gain insight into how Rhox gene expression is regulated within specific regions of the epididymis. The rodent epididymis is ideal for these studies because of its well-established segmentation into three anatomically and functionally distinct regions; the head, or caput; the main body, or corpus; and the tail, or cauda. Over the ;16M years since the Mus/Rattus evolutionary divergence, the segmented anatomical arrangement of the rodent epididymis has remained intact, but each of the segments has acquired distinct roles in terms of the maturation and storage of spermatozoa in the different species. In a clear example of this, the caput epididymidis of mice plays a key role in sperm maturation and the acquisition of forward motility, whereas this occurs in the rat cauda epididymidis, which is normally considered to be a site of sperm storage. Building on a previous finding that the sperm of Rhox5 null mice lack forward motility [5], MacLean et al. [7] embarked on a series of experiments. Their results now show that Rhox5 is a master regulator of many other members of the X-linked Rhox gene cluster in the mouse caput epididymidis and that it acts in almost the same way in the rat cauda epididymidis. This remarkable evolutionary shift in the Rhox5-dominated regionspecific expression of Rhox genes in the rodent epididymis sets the stage for additional experiments that promise to provide insight into mechanisms responsible for the functional maturation of sperm. Comparative studies of gene expression profiles of different segments of the rat and mouse epididymis have already been performed [8], and similar studies will undoubtedly follow in mice with either a functional or a disrupted Rhox5 gene. This should help define whether Rhox5 or other members of the Rhox family act directly or indirectly by controlling spatially defined networks of genes to explain why sperm from the mouse caput and corpus epididymidis are functionally much more mature than rat sperm taken from the same anatomical locations. These types of studies integrate the power of comparative genomics with a wealth of information about the functional diversity of reproductive tissues in two closely related species, and they offer huge potential for the discovery of key mechanisms that control male fertility. In this context, the report by MacLean et al. [7] is a harbinger of many other such studies that will follow in the wake of the Genome10K Project (http://www.genome10k.org), which sets out to assemble the genomic DNA sequences of 10 000 vertebrate species and to thereby cover every vertebrate genus. When overlaid on the well-documented diversity in reproductive strategies within the animal kingdom and the remarkable evolutionary divergence of reproductive anatomy and physiology that occurs in even the most closely related of species, these genomic data sets are in essence the virtual keys that may allow us to unlock many of the secrets that have long eluded reproductive biologists. This new age of comparative genomics is fast approaching, and it will have a huge impact on fields like reproductive biology, where sometimes dramatic biological adaptations have occurred in concert with rapid evolutionarily changes in the sequences of genes, like the Rhox family. It can be anticipated that these rapidly evolving genes will surface as the drivers or mediators of adaptive mechanisms that have ensured the diversity and, ultimately, the survival of species. Most important, these advances in knowledge are poised to occur quickly and can be expected to reveal new and unexpected ways of modifying the fertility of different species across the animal kingdom.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.275
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2012
Admission routes1
Has abstractyes

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