Using Paleogenomics to Study the Evolution of Gene Families: Origin and Duplication History of the Relaxin Family Hormones and Their Receptors
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Bibliographic record
Abstract
Recent progress in the analysis of whole genome sequencing data has resulted in the emergence of paleogenomics, a field devoted to the reconstruction of ancestral genomes. Ancestral karyotype reconstructions have been used primarily to illustrate the dynamic nature of genome evolution. In this paper, we demonstrate how they can also be used to study individual gene families by examining the evolutionary history of relaxin hormones (RLN/INSL) and relaxin family peptide receptors (RXFP). Relaxin family hormones are members of the insulin superfamily, and are implicated in the regulation of a variety of primarily reproductive and neuroendocrine processes. Their receptors are G-protein coupled receptors (GPCR's) and include members of two distinct evolutionary groups, an unusual characteristic. Although several studies have tried to elucidate the origins of the relaxin peptide family, the evolutionary origin of their receptors and the mechanisms driving the diversification of the RLN/INSL-RXFP signaling systems in non-placental vertebrates has remained elusive. Here we show that the numerous vertebrate RLN/INSL and RXFP genes are products of an ancestral receptor-ligand system that originally consisted of three genes, two of which apparently trace their origins to invertebrates. Subsequently, diversification of the system was driven primarily by whole genome duplications (WGD, 2R and 3R) followed by almost complete retention of the ligand duplicates in most vertebrates but massive loss of receptor genes in tetrapods. Interestingly, the majority of 3R duplicates retained in teleosts are potentially involved in neuroendocrine regulation. Furthermore, we infer that the ancestral AncRxfp3/4 receptor may have been syntenically linked to the AncRln-like ligand in the pre-2R genome, and show that syntenic linkages among ligands and receptors have changed dynamically in different lineages. This study ultimately shows the broad utility, with some caveats, of incorporating paleogenomics data into understanding the evolution of gene families.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it