Characterizing the Expression Pattern and Requirement of <i>Sf3b4</i> During Mouse Embryonic Development
Bibliographic record
Abstract
Nager Syndrome (NS) is a rare disorder that affects the face as well as the limb including both hands and feet. Patients with NS typically have malar and mandibular hypoplasia, cleft palate, as well as hearing problems. Limb defects include radial hypoplasia as well as thumb abnormalities. Using exome sequencing, NS was attributed to haploinsufficiency of the SF3B4 gene, an important component of the U2 subunit of the spliceosome complex. We hypothesized that Sf3b4 will show tissue‐specific expression during development and that mice with heterozygous mutation in this gene will model NS. To create heterozygous Sf3b4 mutant mice, we used CRISPR/Cas9 to target loxP sequences in intronic regions flanking exon 2 and 3 of the Sf3b4 gene. We will breed loxP founders with Wnt‐1 Cre transgenic mice, and report the resulting phenotypes. Additionally, whole mount in situ hybridization was used to examine expression of Sf3b4 during embryonic development of wild type mouse. We found that Sf3b4 shows ubiquitous expression at early stages of development. In midgestation embryos, although still globally expressed, Sf3b4 expression becomes stronger in the maxillomandibular region, limbs and tail bud. Our research will elucidate the expression of Sf3b4 in embryonic tissues affected in NS patients and generate a mouse model that will be used to further characterize the molecular basis of this syndrome. As there are currently no mouse models or therapy available for NS our work will help to identify some of the targets of Sf3b4 and pave the path for the creation of new therapies for spliceosomal disorders. Support or Funding Information Canadian Institutes of Health Research This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".