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Centriole structural integrity defects are a crucial feature of Hydrolethalus Syndrome.

ABSTRACT: Hydrolethalus Syndrome (HLS) is a lethal, autosomal recessive ciliopathy caused by the mutation of the conserved centriole protein HYLS1. However, how HYLS1 facilitates the centriole-based templating of cilia is poorly understood. Here, we show that mice harboring the HYLS1 disease mutation die shortly after birth and exhibit developmental defects that recapitulate several manifestations of the human disease. These phenotypes arise from tissue-specific defects in cilia assembly and function caused by a loss of centriole integrity. We show that HYLS1 is recruited to the centriole by CEP120 and functions to recruit centriole inner scaffold proteins that stabilize the centriolar microtubule wall. The HLS mutation disrupts the interaction of HYLS1 with CEP120 leading to HYLS1 displacement and degeneration of the centriole distal end. We propose that tissue-specific defects in centriole integrity caused by the HYLS1 mutation prevent ciliogenesis and drive HLS phenotypes.

SUBMITTER: Curinha A

PROVIDER: S-EPMC10942441 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Centriole structural integrity defects are a crucial feature of Hydrolethalus Syndrome.

Curinha Ana A Huang Zhaoyu Z Anglen Taylor T Strong Margaret A MA Gliech Colin R CR Jewett Cayla E CE Friskes Anoek A Holland Andrew J AJ

bioRxiv : the preprint server for biology 20240306

Hydrolethalus Syndrome (HLS) is a lethal, autosomal recessive ciliopathy caused by the mutation of the conserved centriole protein HYLS1. However, how HYLS1 facilitates the centriole-based templating of cilia is poorly understood. Here, we show that mice harboring the HYLS1 disease mutation die shortly after birth and exhibit developmental defects that recapitulate several manifestations of the human disease. These phenotypes arise from tissue-specific defects in cilia assembly and function caus ...[more]

PMID: 38496445

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Project description:Meckel-Gruber syndrome (MKS) is a recessive disorder resulting in multiple birth defects that are associated with mutations affecting ciliogenesis. We recovered a mouse mutant with a mutation in the Mks1 gene (Mks1(del64-323)) that caused a 260-amino-acid deletion spanning nine amino acids in the B9 domain, a protein motif with unknown function conserved in two other basal body proteins. We showed that, in wild-type cells, Mks1 was localized to the mother centriole from which the cilium was generated. However, in mutant Mks1(del64-323) cells, Mks1 was not localized to the centriole, even though it maintained a punctate distribution. Resembling MKS patients, Mks1 mutants had craniofacial defects, polydactyly, congenital heart defects, polycystic kidneys and randomized left-right patterning. These defects reflected disturbance of functions subserved by motile and non-motile cilia. In the kidney, glomerular and tubule cysts were observed along with short cilia, and cilia were reduced in number to a near-complete loss. Underlying the left-right patterning defects were fewer and shorter nodal cilia, and analysis with fluorescent beads showed no directional flow at the embryonic node. In the cochlea, the stereocilia were mal-patterned, with the kinocilia being abnormally positioned. Together, these defects suggested disruption of planar cell polarity, which is known to regulate node, kidney and cochlea development. In addition, we also showed that Shh signaling was disrupted. Thus, in the neural tube, the floor plate was not specified posteriorly even as expression of the Shh mediator Gli2 increased. By contrast, the Shh signaling domain was expanded in the anterior neural tube and anterior limb bud, consistent with reduced Gli3-repressor (Gli3R) function. The latter probably accounted for the preaxial digit duplication exhibited by the Mks1(del64-323) mutants. Overall, these findings indicate that centriole localization of Mks1 is required for ciliogenesis of motile and non-motile cilia, but not for centriole assembly. On the basis of these results, we hypothesize a role for the B9 domain in mother centriole targeting, a possibility that warrants further future investigations.

Project description:BackgroundMachine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach.ResultsThrough our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger's MyCode Community Health Initiative (on behalf of DiscovEHR collaboration).ConclusionsIn this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying any single method for feature selection via simulation studies. We were able to demonstrate the effectiveness of collective feature selection along with a comparison of many methods in our simulation analysis. We also applied our method to identify non-linear networks associated with obesity.

Dataset Information

Centriole structural integrity defects are a crucial feature of Hydrolethalus Syndrome.

Publications

Centriole structural integrity defects are a crucial feature of Hydrolethalus Syndrome.

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