University of Southern California researchers reveal how gene expression affects facial expressions

September 20, 2014

A person's face is the first thing that others see, and much remains unknown about how it forms -- or malforms -- during early development. Recently, Chong Pyo Choe, a senior postdoctoral fellow working in the lab of USC stem cell researcher Gage Crump, has begun to unwind these mysteries.

In a September study published in the journal Development, Choe and Crump describe how a mutation in a gene called TBX1 causes the facial and other deformities associated with DiGeorge syndrome.

During prenatal development, a series of segments form that eventually organize many features of the face. These segments, or "pouches," are composed of a type of specialized tissue called epithelium, which also forms the skin, glands and linings of organs such as the lungs, heart and intestines.

In mice and zebrafish with TBX1 mutations, these pouches never properly develop and the face is deformed, mimicking the severe facial defects typical of DiGeorge syndrome.

By using sophisticated time-lapse imaging, Crump and Choe observed how this happens in both normal and abnormal development. TBX1 works by activating additional genes, including one called Fgf8a that attracts pouch-forming cells to move to the correct locations. This enables the growing pouches to take shape.

"Whereas it has been recognized that mutations in TBX1 underlie DiGeorge syndrome in patients, our study reveals how this master control gene works to organize the complex cellular rearrangements that build the face," said Crump, associate professor and principal investigator at the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC.
Funding for this study came from a National Institute of Dental and Craniofacial Research (NIDCR) grant (R01DE022572) and a California Institute for Regenerative Medicine (CIRM) training fellowship.

University of Southern California - Health Sciences

Related Mutations Articles from Brightsurf:

SARS-CoV-2 mutations do not appear to increase transmissibility
None of the mutations currently documented in the SARS-CoV-2 virus appear to increase its transmissibility in humans, according to a study led by UCL researchers, published in Nature Communications.

Predicting the evolution of genetic mutations
CSHL quantitative biologists have designed a new machine learning technique for predicting evolutionary pathways.

SNIPRs take aim at disease-related mutations
In a new study, lead author Alex Green, a researcher at the Biodesign Center for Molecular Design and Biomimetics and his colleagues describe a new method for detecting point mutations.

Cancer mutations occur decades before diagnosis
A large-scale pan-cancer analysis of the evolutionary history of tumours reveals that cancer-causing mutations occur decades before diagnosis.

Pinpointing rare disease mutations
Scientists have compiled mouse and human cell knockout data to categorise genes based on how essential they are for survival and organism development.

Using deep learning to predict disease-associated mutations
A research team led by Professor Hongzhe Sun from the Department of Chemistry at HKU, implemented a robust deep learning approach to predict disease-associated mutations of the metal-binding sites in a protein.

Cancer: The origin of genetic mutations
In the presence of some disruptive elements, cancer cells are unable to replicate its DNA optimally.

Mutations associated with sensitivity or resistance to immunotherapy in mNSCLC
The relationship between gene alterations and response to anti-PD-L1 with and without anti-CTLA-4 are not well characterized.

Machine learning for damaging mutations prediction
Scientists from Russia and India have proposed a novel machine-learning-based method for predicting damaging mutations in the protein atomic structure.

Discovery of new mutations may lead to better treatment
In the largest study to date on developmental delay, researchers analyzed genomic data from over 31,000 parent-child trios and found more than 45,000 de novo mutations, and 40 novel genes.

Read More: Mutations News and Mutations Current Events is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to