Association of low‐frequency genetic variants in regulatory regions with nonsyndromic orofacial clefts

Shaffer, John R.; LeClair, Jessica; Carlson, Jenna C.; Feingold, Eleanor; Buxó, Carmen J.; Christensen, Kaare; Deleyiannis, Frederic W.‐B.; Field, L. Leigh; Hecht, Jacqueline; Moreno, Lina M.; Orioli, Iêda M.; Padilla, Carmencita D.; Vieira, Alexandre R.; Wehby, George L.; Murray, Jeffrey C.; Weinberg, Seth M.; Marazita, Mary L.; Leslie, Elizabeth J.

doi:10.1002/ajmg.a.61002

Cited by 20 publications

(20 citation statements)

References 43 publications

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“…Prescott et al used a collection of craniofacial enhancers identified and characterized by the Visel Spoke in a study of regulatory divergence of neural crest enhancers between chimpanzees and humans (Prescott et al, 2015). Shaffer et al used enhancer data generated by this Spoke to identify a significant association between cleft palate and a branchial arch enhancer at the FOXP1 locus (Shaffer et al, 2019). Finally, Carlson et al used data from this Spoke to examine the regulatory basis of phenotypic modifiers of non-syndromic cleft lip with or without cleft palate (Carlson et al, 2017).…”

Section: Facebase 2 Spoke Projectsmentioning

confidence: 99%

FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research

et al. 2020

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The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a ‘big data’ resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote integration of multidisciplinary data while remaining dedicated to the FAIR principles of data management (findability, accessibility, interoperability and reusability) and providing a faceted search infrastructure for locating desired data efficiently. Summaries of the datasets generated by the FaceBase projects from 2014 to 2019 are provided here. FaceBase 3 now welcomes contributions of data on craniofacial and dental development in humans, model organisms and cell lines. Collectively, the FaceBase Consortium, along with other NIH-supported data resources, provide a continuously growing, dynamic and current resource for the scientific community while improving data reproducibility and fulfilling data sharing requirements.

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Section: Facebase 2 Spoke Projectsmentioning

confidence: 99%

FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research

et al. 2020

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“…Interestingly, this association would have been missed if only the coding parts of the genes had been considered. Another example is the study performed by Shaffer et al (Shaffer et al 2019) where they looked for an accumulation of rare variants in enhancers in orofacial clefts phenotype using CMC (Li and Leal 2008) and SKAT (Wu et al 2011) association tests. They grouped rare variants by enhancers that were defined using different sources including the VISTA database (Visel et al 2007), results from ChIP-Seq studies and a literature search, and found an association with an enhancer near FOXP1.…”

Section: Using Functional Annotationsmentioning

confidence: 99%

Rare variant association testing in the non-coding genome

Bocher

Génin

2020

Hum Genet

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The development of next-generation sequencing technologies has opened-up some new possibilities to explore the contribution of genetic variants to human diseases and in particular that of rare variants. Statistical methods have been developed to test for association with rare variants that require the definition of testing units and, in these testing units, the selection of qualifying variants to include in the test. In the coding regions of the genome, testing units are usually the different genes and qualifying variants are selected based on their functional effects on the encoded proteins. Extending these tests to the non-coding regions of the genome is challenging. Testing units are difficult to define as the non-coding genome organisation is still rather unknown. Qualifying variants are difficult to select as the functional impact of non-coding variants on gene expression is hard to predict. These difficulties could explain why very few investigators so far have analysed the non-coding parts of their whole genome sequencing data. These non-coding parts yet represent the vast majority of the genome and some studies suggest that they could play a major role in disease susceptibility. In this review, we discuss recent experimental and statistical developments to gain knowledge on the non-coding genome and how this knowledge could be used to include rare non-coding variants in association tests. We describe the few studies that have considered variants from the non-coding genome in association tests and how they managed to define testing units and select qualifying variants. Study Type of data / Fraction analysed Trait Frequency filter Other filter Specific RV weight Testing unit RVAT Type of RVAT

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“…Significantly, Tgfbr1 and Tgfbr2 mutant mice also exhibit cleft palate, suggesting that Tgf-β signaling pathway is crucial in regulating palatogenesis (Han et al 2014; Iwata et al 2014). Recent studies on patients with nonsyndromic orofacial clefts have revealed that differential DNA methylation, epigenetic regulator mutations, and low-frequency genetic variants in noncoding regions may contribute to cleft palate (Alvizi et al 2017; Shaffer et al 2019). It is crucial to develop relevant animal models to test how epigenetic factors may control palate development.…”

Section: Molecular and Cellular Regulatory Mechanisms Of Soft Palate Developmentmentioning

confidence: 99%

Regulatory Mechanisms of Soft Palate Development and Malformations

Rodriguez

Han

et al. 2019

J Dent Res

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Orofacial clefting is the most common congenital craniofacial malformation, appearing in approximately 1 in 700 live births. Orofacial clefting includes several distinct anatomic malformations affecting the upper lip and hard and soft palate. The etiology of orofacial clefting is multifactorial, including genetic or environmental factors or their combination. A large body of work has focused on the molecular etiology of cleft lip and clefts of the hard palate, but study of the underlying etiology of soft palate clefts is an emerging field. Recent advances in the understanding of soft palate development suggest that it may be regulated by distinct pathways from those implicated in hard palate development. Soft palate clefting leads to muscle misorientation and oropharyngeal deficiency and adversely affects speech, swallowing, breathing, and hearing. Hence, there is an important need to investigate the regulatory mechanisms of soft palate development. Significantly, the anatomy, function, and development of soft palatal muscles are similar in humans and mice, rendering the mouse an excellent model for investigating molecular and cellular mechanisms of soft palate clefts. Cranial neural crest–derived cells provide important regulatory cues to guide myogenic progenitors to differentiate into muscles in the soft palate. Signals from the palatal epithelium also play key roles via tissue-tissue interactions mediated by Tgf-β, Wnt, Fgf, and Hh signaling molecules. Additionally, mutations in transcription factors, such as Dlx5, Tbx1, and Tbx22, have been associated with soft palate clefting in humans and mice, suggesting that they play important regulatory roles during soft palate development. Finally, we highlight the importance of distinguishing specific types of soft palate defects in patients and developing relevant animal models for each of these types to improve our understanding of the regulatory mechanism of soft palate development. This knowledge will provide a foundation for improving treatment for patients in the future.

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Association of low‐frequency genetic variants in regulatory regions with nonsyndromic orofacial clefts

Cited by 20 publications

References 43 publications

FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research

FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research

Rare variant association testing in the non-coding genome

Regulatory Mechanisms of Soft Palate Development and Malformations

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