Additional file 1 of Genome-wide screening reveals the genetic basis of mammalian embryonic eye development
Bibliographic record
Abstract
Additional file 1: Table S1. Knockout mice exhibiting phenotypic embryonic eye defects. The embryonic eye defects were divided into four categories: Abnormal eyelid fusion, abnormal optic vesicle formation, microphthalmia, and anophthalmia. If a knockout strain of the gene has already been created, a PMID is listed, along with a description of the ocular defect, age, and zygosity of the mice upon diagnosis if pertinent. If there is an ocular defect present within humans (Human Eye PMID), or if there is a weak, potential correlation between the gene and an ocular defect in any species besides mice and humans (Associated Phenotypes), the PMID is listed as well. Any systemic co-phenotypes (numerical code listed below) associated with either homozygous or heterozygous mice are listed, along with the description of the heterozygous eye phenotype. From the IMPC database, if a photo of ocular defects was present in heterozygous adult mice, the type of photo taken was described in the spreadsheet. Additionally, from the same database, the phenotypic embryonic eye defects were labelled for each knockout strain, along with the age the mice were diagnosed with the defect (E9.5, E12.5, E15.5, E18.5), their homozygous viability, the zygosity of the mice with the phenotypic eye defect, and a ratio of mutant KO to normal KO mice by sex. In conclusion, the IMPC yielded 74 genes that created knockout strains with an embryonic eye defect, 27 of which had already had previously published mouse knockouts, but only15 of these knockouts exhibiting an eye abnormality. There are a total of 59 genes that are associated with embryonic eye defects in mice of which 19 genes had a previously reported human eye phenotype. Therefore, there are a total of 40 genes not previously associated with eye defects; these are bolded and highlighted in red in the first column of the table. 1 = Endocrine/exocrine 11 = Respiratory 2 = Taste/olfaction 12 = Cardiovascular 3 = Ear, hearing, vestibular 13 = Behavior, Neurologic 4 = Craniofacial 14 = Metabolism/homeostasis 5 = Muscle phenotype 15 = Growth and Body Size 6 = Immune/Hematopoietic 16 = Reproductive System 7 = Skeletal Phenotype 17 = Embryonic 8 = Limbs, digits, tail 18 = Mortality, aging 9 = Integumentary/Pigmentation 19 = Eyes 10 = Digestive 20 = Urinary. Table S2. The Gold standard list of 114 genes was created from a list of previously published genes that contribute to MAC spectrum disorders in humans. The 74 IMPC list of genes is listed beside it, and the genes present on both the gold standard list and IMPC list are highlighted in yellow. References from which the gold standard list was curated from are listed on the column to the furthest right (PMID or DOI). Fig. S1. Pie graphs demonstrating and comparing the molecular pathways of both the 74 IMPC genes and the 114 gold standard genes, using the Panther function on Gene Ontology. Pathways with the red box are only implicated from the mouse data from our genes. The genes implicated within the pathways with the red box are labeled next to the pathway. Fig. S2. Serine-Glycine biosynthesis pathway derived from the KEGG pathway on DAVID, based on pathways and gene interactions predicted by gene ontology and STRING analysis. IMPC genes with MAC phenotypes (blue) are highlighted. Fig. S3. Interrelationships between pathways involved in stem cell maintenance and proliferation derived from the KEGG pathway on DAVID. Established MAC genes (pink) and IMPC genes with MAC phenotypes (blue) are highlighted. Red indicates a gene in both groups, and SOX2 is highlighted (pink) as an established critical MAC spectrum disease gene. Fig. S4. Analysis of protein-protein interactions between the IMPC genes and the Gold Standard genes within a merged network. Cytoscape was the software platform used to merge the two networks together, and the protein interactions between the two groups of genes were analyzed using the STRING biological database software program. The arrows point towards genes that are initially not incorporated into STRING clusters until merged together within the Cytoscape platform. Fig. S5. Analysis of protein-protein interactions in the 74 IMPC genes (left) and the 114 Gold Standard genes (pink, right) using STRING biological database software. Among the IMPC genes, strongly significant (P<0.0001, green) and conventionally significant (P<0.05, yellow) genes are shown. Red genes are those that also appear on the list of gold standard MAC genes. Genes with stars (n=6) are members of signaling pathways regulating pluripotency of stem cells. Clusters encircled represent the serine-glycine pathway (red box) and Cplane1 complex (blue box). Table S3. Genes implicated in ciliopathies from both the IMPC and Gold Standard list of genes. The genes on column A represent IMPC genes that are implicated in ciliopathies, while the genes in column F represent Gold Standard genes that are implicated in ciliopathies.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.731 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".