Identification of rare variants in PTCH2 associated with non-syndromic orofacial clefts.

Orofacial clefts (OFCs) represent the most prevalent congenital craniofacial anomalies, significantly impacting patients' appearance, oral function, and psychological well-being. Among these, non-syndromic OFCs (NSOFCs) are the most predominant type, with the etiology attributed to a combination of genetic and environmental factors. Rare variants of key genes involved in craniofacial development-related signaling pathway are crucial in the occurrence of NSOFCs, and our recent studies have identified PTCH1, a receptor-coding gene in the Hedgehog signaling pathway, as a causative gene for NSOFCs. However, the role of PTCH2, the paralog of PTCH1, in pathogenesis of NSOFCs remains unclear. Here, we perform whole-exome sequencing to explore the genetic basis of 144 sporadic NSOFC patients. We identify five heterozygous variants of PTCH2 in four patients: p.L104P, p.A131G, p.R557H, p.I927S, and p.V978D, with the latter two co-occurring in a single patient. These variants, all proven to be rare through multiple genomic databases, with p.I927S and p.V978D being novel variants and previously unreported. Sequence alignment suggests that these affected amino acids are evolutionarily conserved across vertebrates. Utilizing predictive structural modeling tools such as AlphaFold and SWISS-MODEL, we propose that these variants may disrupt the protein's structure and function. In summary, our findings suggest that PTCH2 may be a novel candidate gene predicted to be associated with NSOFCs, thereby broadening the spectrum of causative genes implicated in the craniofacial anomalies.

Influence of presurgical nasoalveolar molding (PNAM) treatment in maxillary dental arch width and nasolabial symmetry in patients with unilateral complete cleft lip and palate.

Unilateral complete cleft lip and palate (UCCLP) is one of the most severe clinical subphenotypes among nonsyndromic cleft lip and/or palate (NSCL/P), that complicates surgical repair operations. Presurgical nasoalveolar molding (PNAM) is a technique used to reshape the nose, lip and alveolar bone of infants with UCCLP before surgery (the modified Mohler rotation advancement cheiloplasty and two flap palatoplasty), with the potential to facilitate surgical repair. However, the effectiveness of PNAM treatment is still a matter of debate. In this paper, the 3Shape scanning system and 3dMD stereophotography were used to assess the short-term and long-term effects of PNAM treatment on the dental arch morphology and nasolabial features of patients with UCCLP, respectively. The findings indicated that PNAM treatment negatively affects both short-term and long-term dental arch shape compared to the treatment without PNAM, particularly in terms of limiting the transverse width of the maxillary canine-to-midline. Regarding the nasal and labial symmetry, PNAM improves the symmetry of the nasal alae in patients over 7 years old and the symmetry of the lip in patients under 7 years old. Moreover, UCCLP patients who received PNAM treatment exhibited a shorter and wider shape of the nostril on the cleft side compared to those without PNAM treatment. In clinical practice, the multidisciplinary team should carefully consider the advantages and disadvantages of the outcomes of PNAM treatment when treating infants with cleft lip and palate.

Establishment of a novel classification system for alveolar morphology in infants with unilateral complete cleft lip and palate.

OBJECTIVES: Unilateral complete cleft lip and palate (UCCLP) is one of the most severe clinical subtypes among cleft lip and palate (CLP), making repair surgery and subsequent orthodontic treatment particularly challenging. Presurgical nasoalveolar molding (PNAM) has shown conflicting and heterogeneous results in the treatment of UCCLP patients, raising questions about whether the diversity in alveolar anatomical morphology among these patients plays a role in the effectiveness of PNAM treatment. MATERIALS AND METHODS: We collected 90 digital maxillary models of infants with UCCLP and performed mathematical clustering analysis, including principal component analysis (PCA), decision tree modeling, and area under the ROC Curve (AUC) analysis, to classify alveolar morphology and identify key measurements. We also conducted clinical evaluations to assess the association between the alveolar morphology and CLP treatment outcomes. RESULTS: Using mathematical clustering analysis, we classified the alveolar morphology into three distinct types: average form, horizontal form, and longitudinal form. The decision tree model, AUC analysis, and comparison analysis revealed that four measurements (Trans ACG-ACL, ML length, MG length and Inc length) were essential for clustering the alveolar morphology of infants with UCCLP. Furthermore, the blinded clinical evaluation indicated that UCCLP patients with alveolar segments of horizontal form had the lowest treatment outcomes. CONCLUSION: Overall, our findings establish a novel quantitative classification system for the morphology of alveolar bone in infants with UCCLP and suggest that this classification may be associated with the outcomes of CLP treatment. CLINICAL RELEVANCE: The multidisciplinary CLP team should thoroughly evaluate and classify the specific alveolar morphology when administering PNAM to infants with UCCLP.

Identification of rare loss-of-function variants in FAM3B associated with non-syndromic orofacial clefts.

Orofacial clefts (OFCs) are the most common congenital craniofacial disorders and cause serious problems with the appearance, orofacial function and mental health of the patients. The fibroblast growth factor (FGF) signaling pathway is critical for several aspects of craniofacial development and loss-of-function mutations of coding genes for multiple FGFs and FGFRs can lead to OFCs. We recently characterized FAM3B as a novel ligand of FGF signaling, which, through binding to FGFRs and activating downstream ERK, regulates craniofacial development in Xenopus. In this study, we identify two rare variants in FAM3B (p.Q61R and p.D128G) via target region sequencing of FAM3B on 144 unrelated sporadic patients with non-syndromic OFCs (NSOFCs). Bioinformatic analysis predict that these two variants are likely to be damaging and biochemical experiments show that these two variants weaken the FGF ligand activity of FAM3B by decreasing its expression and thus secretion. In summary, our results indicate that FAM3B is a novel candidate gene for NSOFCs in humans.

Hyoid bone position in subjects with different facial growth patterns of different dental ages.

OBJECTIVE: To explore the correlation between hyoid bone (HB) positions and facial growth patterns (facial patterns) in Chinese adults; to identify any significant difference in HB position among subjects with different facial patterns in various dental ages. METHODS: Lateral cephalometric radiographs of 197 Chinese subjects were divided into nine groups based on their dental ages and facial patterns. Seven measurements were used to define HB position. Regression, correlation analyses, and one-way ANOVA were carried out. RESULTS: Significant correlations were found between facial patterns and anteroposterior HB positions. The HB was more anterior in the horizontal group after mixed dentition and further away from the mandibular plane in the vertical group of adults. Vertical HB positions were insignificantly different in any stage. CONCLUSION: HB position and facial patterns were correlated. There were significantly different HB positions among people with different facial patterns in various dental ages.

Non-invasive, whole-plant imaging of chloroplast movement and chlorophyll fluorescence reveals photosynthetic phenotypes independent of chloroplast photorelocation defects in chloroplast division mutants.

Leaf chloroplast movement is thought to optimize light capture and to minimize photodamage. To better understand the impact of chloroplast movement on photosynthesis, we developed a technique based on the imaging of reflectance from leaf surfaces that enables continuous, high-sensitivity, non-invasive measurements of chloroplast movement in multiple intact plants under white actinic light. We validated the method by measuring photorelocation responses in Arabidopsis chloroplast division mutants with drastically enlarged chloroplasts, and in phototropin mutants with impaired photorelocation but normal chloroplast morphology, under different light regimes. Additionally, we expanded our platform to permit simultaneous image-based measurements of chlorophyll fluorescence and chloroplast movement. We show that chloroplast division mutants with enlarged, less-mobile chloroplasts exhibit greater photosystem II photodamage than is observed in the wild type, particularly under fluctuating high levels of light. Comparison between division mutants and the severe photorelocation mutant phot1-5 phot2-1 showed that these effects are not entirely attributable to diminished photorelocation responses, as previously hypothesized, implying that altered chloroplast morphology affects other photosynthetic processes. Our dual-imaging platform also allowed us to develop a straightforward approach to correct non-photochemical quenching (NPQ) calculations for interference from chloroplast movement. This correction method should be generally useful when fluorescence and reflectance are measured in the same experiments. The corrected data indicate that the energy-dependent (qE) and photoinhibitory (qI) components of NPQ contribute differentially to the NPQ phenotypes of the chloroplast division and photorelocation mutants. This imaging technology thus provides a platform for analyzing the contributions of chloroplast movement, chloroplast morphology and other phenotypic attributes to the overall photosynthetic performance of higher plants.

Functional approach to high-throughput plant growth analysis.

METHOD: Taking advantage of the current rapid development in imaging systems and computer vision algorithms, we present HPGA, a high-throughput phenotyping platform for plant growth modeling and functional analysis, which produces better understanding of energy distribution in regards of the balance between growth and defense. HPGA has two components, PAE (Plant Area Estimation) and GMA (Growth Modeling and Analysis). In PAE, by taking the complex leaf overlap problem into consideration, the area of every plant is measured from top-view images in four steps. Given the abundant measurements obtained with PAE, in the second module GMA, a nonlinear growth model is applied to generate growth curves, followed by functional data analysis. RESULTS: Experimental results on model plant Arabidopsis thaliana show that, compared to an existing approach, HPGA reduces the error rate of measuring plant area by half. The application of HPGA on the cfq mutant plants under fluctuating light reveals the correlation between low photosynthetic rates and small plant area (compared to wild type), which raises a hypothesis that knocking out cfq changes the sensitivity of the energy distribution under fluctuating light conditions to repress leaf growth. AVAILABILITY: HPGA is available at http://www.msu.edu/~jinchen/HPGA.

Detection and decomposition: treatment-induced cyclic gene expression disruption in high-throughput time-series datasets.

Higher organisms possess many genes which cycle under normal conditions, to allow the organism to adapt to expected environmental conditions throughout the course of a day. However, treatment-induced disruption of regular cyclic gene expression patterns presents a significant challenge in novel gene discovery experiments because these disruptions can induce strong differential regulation events for genes that are not involved in an adaptive response to the treatment. To address this cycle disruption problem, we reviewed the state-of-art periodic pattern detection algorithms and a pattern decomposition algorithm (PRIISM), which is a knowledge-based Fourier analysis algorithm designed to distinguish the cyclic patterns from the rest gene expression patterns, and discussed potential future improvements.

Frequency-based time-series gene expression recomposition using PRIISM.

BACKGROUND: Circadian rhythm pathways influence the expression patterns of as much as 31% of the Arabidopsis genome through complicated interaction pathways, and have been found to be significantly disrupted by biotic and abiotic stress treatments, complicating treatment-response gene discovery methods due to clock pattern mismatches in the fold change-based statistics. The PRIISM (Pattern Recomposition for the Isolation of Independent Signals in Microarray data) algorithm outlined in this paper is designed to separate pattern changes induced by different forces, including treatment-response pathways and circadian clock rhythm disruptions. RESULTS: Using the Fourier transform, high-resolution time-series microarray data is projected to the frequency domain. By identifying the clock frequency range from the core circadian clock genes, we separate the frequency spectrum to different sections containing treatment-frequency (representing up- or down-regulation by an adaptive treatment response), clock-frequency (representing the circadian clock-disruption response) and noise-frequency components. Then, we project the components' spectra back to the expression domain to reconstruct isolated, independent gene expression patterns representing the effects of the different influences.By applying PRIISM on a high-resolution time-series Arabidopsis microarray dataset under a cold treatment, we systematically evaluated our method using maximum fold change and principal component analyses. The results of this study showed that the ranked treatment-frequency fold change results produce fewer false positives than the original methodology, and the 26-hour timepoint in our dataset was the best statistic for distinguishing the most known cold-response genes. In addition, six novel cold-response genes were discovered. PRIISM also provides gene expression data which represents only circadian clock influences, and may be useful for circadian clock studies. CONCLUSION: PRIISM is a novel approach for overcoming the problem of circadian disruptions from stress treatments on plants. PRIISM can be integrated with any existing analysis approach on gene expression data to separate circadian-influenced changes in gene expression, and it can be extended to apply to any organism with regular oscillations in gene expression patterns across a large portion of the genome.