CRYGC Human

What is the CRYGC gene and its primary function in humans?

CRYGC encodes the gamma C crystallin protein, which belongs to the crystallin family of proteins found predominantly in the eye lens. Crystallins maintain lens transparency and proper refractive index, which are critical for normal vision. Gamma-crystallins, including CRYGC, are highly symmetrical, monomeric proteins typically lacking connecting peptides and terminal extensions . These proteins are differentially regulated after early development and remain extremely stable throughout life because lens central fiber cells lose their nuclei during development, making crystallins some of the most long-lived proteins in the human body .

CRYGC is part of a cluster of gamma-crystallin genes (gamma-A through gamma-D) and pseudogenes (gamma-E, gamma-F, gamma-G) organized in a genomic segment. The protein plays a crucial role in maintaining the structural integrity and transparency of the lens, with mutations frequently associated with various forms of congenital cataracts .

What methodologies are commonly employed for CRYGC gene variant analysis?

Several complementary methodologies are routinely used for comprehensive CRYGC variant analysis:

• DNA Sequencing Techniques:

  • PCR amplification of coding regions and intron/exon boundaries, followed by direct Sanger sequencing

  • Whole-exome sequencing (WES), particularly trio-based WES for detection of de novo variants

  • Next-generation sequencing panels focused on crystallin and other cataract-associated genes

• Variant Screening Methods:

  • Restriction enzyme digestion (e.g., MslI for CRYGC) to screen control populations

  • High-resolution melting analysis to detect sequence variations

  • Multiplex ligation-dependent probe amplification (MLPA) for larger deletions or duplications

• In Silico Analysis Tools:

  • Prediction of functional impact using computational algorithms:

    • SIFT (Sorting Intolerant from Tolerant amino acid substitutions)

    • PolyPhen (Polymorphism Phenotyping)

    • Align-GVGD (Grantham score difference)

  • Conservation analysis across species to assess evolutionary importance of affected residues

What is the relationship between CRYGC mutations and congenital cataracts?

CRYGC mutations have been strongly associated with the development of congenital cataracts. These cataracts are visible at birth or during the first decade of life and represent one of the most common causes of childhood blindness, with an estimated prevalence of 1-6 cases per 10,000 live births .

Approximately 8.3-25% of congenital cataract cases exhibit Mendelian inheritance patterns, with autosomal dominant inheritance being most common, though autosomal recessive and X-linked patterns have also been reported . CRYGC mutations specifically disrupt the proper folding or stability of the gamma C crystallin protein, leading to protein aggregation within lens fiber cells and subsequent opacification of the lens.

Various types of mutations in CRYGC have been identified, including missense mutations, nonsense mutations, and small deletions or insertions. For example, a novel 1-bp deletion (c.394delG, p.V132Sfs*15) was recently detected in a Chinese congenital cataract patient through trio-based whole-exome sequencing . This frameshift mutation creates a premature termination codon, likely resulting in a truncated protein or triggering nonsense-mediated mRNA decay.

How do different experimental models contribute to understanding CRYGC function and pathogenicity?

Different experimental models offer complementary insights into CRYGC function and the pathogenic mechanisms associated with its mutations:

Cell-Based Models:

• Lens epithelial cell (LEC) cultures provide a platform for studying:

  • Protein aggregation dynamics using fluorescently tagged CRYGC variants

  • Protein-protein interactions through co-immunoprecipitation and FRET analysis

  • Subcellular localization of wild-type versus mutant proteins

  • Effects on cell viability, stress response pathways, and protein degradation machinery

Animal Models:

• Mouse models with targeted CRYGC mutations allow for:

  • In vivo analysis of lens development and cataract progression

  • Evaluation of age-dependent changes in lens transparency

  • Assessment of potential therapeutic interventions

  • Study of interactions with other crystallin family members

In Vitro Protein Studies:

• Recombinant protein expression and purification facilitate:

  • Structural studies using X-ray crystallography and NMR

  • Stability analyses through thermal denaturation and chemical unfolding experiments

  • Aggregation propensity measurements using light scattering and thioflavin T binding

  • Interactions with chaperones and other lens proteins

Computational Approaches:

• Molecular dynamics simulations provide insights into:

  • Conformational changes induced by specific mutations

  • Effects on protein solubility and stability

  • Prediction of pathogenicity for novel variants

  • Potential sites for therapeutic targeting

What are the most significant CRYGC variants associated with human pathology, and what methodological approaches have revealed their functional impact?

The following table summarizes key pathogenic CRYGC variants and the methodologies that revealed their functional significance:

Methodological approaches that have proven most informative for understanding these variants include:

• Structural Biology Techniques:

  • X-ray crystallography and NMR to determine how mutations affect protein folding

  • Small-angle X-ray scattering (SAXS) to analyze solution structures of wild-type and mutant proteins

  • Cryo-electron microscopy to visualize protein aggregates

• Biophysical Characterization:

  • Circular dichroism spectroscopy to assess secondary structure changes

  • Fluorescence spectroscopy to monitor tertiary structure and stability

  • Dynamic light scattering to measure aggregation kinetics

  • Differential scanning calorimetry to quantify thermal stability differences

• Functional Cell Biology:

  • CRISPR/Cas9 gene editing to introduce specific mutations in cell models

  • Live-cell imaging to track protein dynamics and aggregation in real-time

  • RNA-seq analysis to identify downstream transcriptional changes

  • Proteomics to characterize altered interaction networks

How do interactions between CRYGC and other crystallin proteins contribute to lens transparency, and what methodologies best capture these interactions?

CRYGC has been shown to interact with other crystallin proteins, including CRYBB2, CRYAA, and CRYAB . These interactions play crucial roles in maintaining lens transparency through several mechanisms:

• Solubility Maintenance:

  • Proper interactions between different crystallin classes help maintain high protein concentration without aggregation

  • The chaperone-like activity of α-crystallins (CRYAA, CRYAB) protects γ-crystallins from aggregation under stress conditions

  • Disruption of these interactions can lead to protein insolubility and cataract formation

• Structural Organization:

  • Short-range ordering of crystallin proteins creates a gradient of refractive index in the lens

  • Specific γ-crystallin interactions contribute to the unique optical properties of the lens

  • Age-related or mutation-induced changes in these interactions can affect lens clarity

Methodologies that effectively capture these interactions include:

Protein-Protein Interaction Analysis:

• Yeast two-hybrid screening to identify direct binding partners

• Protein co-immunoprecipitation followed by mass spectrometry

• Surface plasmon resonance to measure binding kinetics and affinities

• Isothermal titration calorimetry for thermodynamic characterization of interactions

• Cross-linking mass spectrometry to map interaction interfaces

Advanced Microscopy Techniques:

• Förster resonance energy transfer (FRET) microscopy to visualize protein interactions in living cells

• Proximity ligation assay to detect interactions with high sensitivity and specificity

• Super-resolution microscopy to observe nanoscale organization of crystallin complexes

• Atomic force microscopy to analyze mechanical properties of crystallin networks

Systems Biology Approaches:

• Interactome mapping using affinity purification-mass spectrometry

• Computational modeling of crystallin networks and how mutations disrupt them

• Integration of structural and functional data to build comprehensive interaction models

What are the technical challenges in analyzing CRYGC mutations in clinical settings, and how might these be addressed?

Several technical challenges complicate the analysis of CRYGC mutations in clinical settings:

• Genetic Heterogeneity:

  • Congenital cataracts can be caused by mutations in multiple genes beyond CRYGC

  • Overlapping phenotypes make it difficult to target specific genes for analysis

  • Solution: Implement comprehensive gene panels or whole-exome sequencing rather than single-gene testing

• Variant Interpretation:

  • Distinguishing pathogenic variants from benign polymorphisms can be challenging

  • Limited functional data exists for many novel variants

  • Solution: Apply ACMG guidelines with crystallin-specific refinements and develop functional screening assays applicable in diagnostic settings

• De Novo Mutations:

  • Cases without family history may be caused by de novo mutations

  • Traditional segregation analysis is not informative in such cases

  • Solution: Trio-based sequencing (proband and parents) to identify de novo variants, as demonstrated in recent research

• Technical Limitations:

  • GC-rich regions in crystallin genes can complicate PCR and sequencing

  • Standard capture-based methods may miss certain variants

  • Solution: Optimize DNA extraction and amplification protocols specifically for crystallin genes, and consider complementary methods such as long-read sequencing

• Genotype-Phenotype Correlation:

  • Variable expressivity and incomplete penetrance complicate predictions

  • The same mutation may produce different phenotypes in different individuals

  • Solution: Develop comprehensive databases linking specific mutations to detailed phenotypic information, including age of onset, progression rate, and response to interventions

How do computational prediction methods compare in assessing the functional impact of novel CRYGC variants?

Computational prediction methods play a crucial role in evaluating novel CRYGC variants, especially when functional studies are not immediately feasible. Research has utilized several complementary approaches :

• Sequence-Based Methods:

  • SIFT (Sorting Intolerant from Tolerant) analyzes amino acid conservation across species and predicts whether substitutions affect protein function based on sequence homology

  • PolyPhen (Polymorphism Phenotyping) combines sequence conservation with structural features to predict damaging effects

  • PROVEAN predicts functional impacts by analyzing how variants alter sequence similarity to related proteins

• Structure-Based Methods:

  • FoldX calculates changes in protein stability (ΔΔG) upon mutation

  • CUPSAT predicts changes in protein stability based on structural environment of the mutation site

  • MutPred estimates probability of pathogenicity based on structural and functional properties

• Machine Learning Approaches:

  • MutationTaster integrates multiple information sources using a naive Bayes classifier

  • CADD (Combined Annotation Dependent Depletion) integrates diverse annotations into a single pathogenicity score

  • REVEL combines multiple prediction scores specifically for rare variants

• Conservation-Based Methods:

  • Align-GVGD combines multiple sequence alignments with Grantham distances to predict pathogenicity

  • PhyloP detects sites under evolutionary constraint based on multiple alignments

Comparative analysis has shown that no single method consistently outperforms others for crystallin variants. A consensus approach using multiple prediction tools generally provides more reliable assessments. For CRYGC specifically, structure-based methods may offer advantages given the availability of crystal structures for gamma-crystallins.

When evaluating novel variants, researchers should consider:

• Consistency across different prediction methods

• Structural context of the affected residue

• Evolutionary conservation patterns specific to crystallin proteins

• Correlation with known pathogenic variants in similar regions of the protein

What protocols are most effective for functional characterization of CRYGC variants in laboratory settings?

Effective functional characterization of CRYGC variants requires a multi-faceted approach combining biochemical, biophysical, and cellular methods:

Expression System Selection:

• Bacterial expression (E. coli):

  • Advantages: High yield, cost-effective, rapid production

  • Protocol refinements: Use specialized strains (e.g., Rosetta) for optimal codon usage; express at low temperatures (16-18°C) to enhance proper folding

  • Best for: Initial biophysical characterization, structural studies

• Mammalian expression (HEK293, lens epithelial cells):

  • Advantages: Native post-translational modifications, appropriate cellular context

  • Protocol refinements: Use inducible expression systems to control expression levels

  • Best for: Subcellular localization, interaction studies, aggregation analysis

Purification and Characterization Workflow:

• Affinity chromatography (His-tag or GST-tag)

• Size-exclusion chromatography to assess oligomeric state

• Circular dichroism to analyze secondary structure

• Fluorescence spectroscopy to evaluate tertiary structure

• Differential scanning calorimetry to determine thermal stability

• Dynamic light scattering to monitor aggregation propensity

Cellular Assays:

• Transfection of wild-type and mutant CRYGC constructs into lens epithelial cells

• Immunofluorescence microscopy to assess localization patterns

• Co-immunoprecipitation to identify altered protein interactions

• Cell viability assays to measure cytotoxicity of mutant proteins

• Proteasome inhibition to evaluate degradation pathways

• Stress response analysis (heat shock, oxidative stress)

Advanced Biophysical Techniques:

• Surface plasmon resonance for quantitative interaction analysis

• Native mass spectrometry to characterize protein complexes

• Hydrogen-deuterium exchange mass spectrometry to assess conformational dynamics

• Small-angle X-ray scattering for solution structure determination

How should researchers approach discrepancies between computational predictions and experimental data for CRYGC variants?

When computational predictions conflict with experimental results for CRYGC variants, researchers should follow a systematic approach to resolve these discrepancies:

• Reassess Computational Analysis:

  • Evaluate the assumptions and limitations of the prediction algorithms used

  • Consider whether the specific structural features of crystallins are adequately represented

  • Apply multiple complementary prediction tools and assess consensus

  • Check if the variant occurs in functionally critical regions that may not be captured by general algorithms

• Review Experimental Design:

  • Evaluate whether experimental conditions appropriately mimic physiological context

  • Consider if the experimental readout directly addresses the predicted effect

  • Assess technical limitations and potential artifacts

  • Determine if sufficient controls (positive and negative) were included

• Reconciliation Strategy:

  • Perform additional experiments targeting the specific discrepancy

  • Consider orthogonal approaches that measure the same property through different methods

  • Evaluate the variant in multiple experimental systems (in vitro, cell-based, animal models)

  • Assess the effect on multiple functional parameters (stability, solubility, interactions)

• Contextual Evaluation:

  • Determine if species-specific differences might explain discrepancies

  • Consider lens-specific factors that might not be captured in general prediction models

  • Evaluate age-dependent effects that might reconcile conflicting results

  • Assess whether genetic background modifiers might explain variable findings

• Integration Framework:

  • Develop a weighted evidence approach that considers:

    • The reliability of different prediction methods for crystallin proteins specifically

    • The relevance of experimental systems to lens physiology

    • Consistency with clinical observations from patients with similar variants

    • Evolutionary conservation and structural context

What study designs are most appropriate for investigating genotype-phenotype correlations in patients with CRYGC mutations?

Optimal study designs for investigating genotype-phenotype correlations in patients with CRYGC mutations include:

Cross-Sectional Family Studies:

• Advantages: Allow observation of same mutation across multiple family members

• Design elements:

  • Comprehensive ophthalmological examination including slit-lamp biomicroscopy

  • Standardized phenotype classification (nuclear, lamellar, etc.)

  • Age-at-onset documentation

  • Associated ocular findings (microphthalmia, nystagmus)

  • Segregation analysis with full pedigree construction

• Analysis approaches: Penetrance calculation, expressivity evaluation, modifier gene identification

Longitudinal Cohort Studies:

• Advantages: Track progression and age-related changes

• Design elements:

  • Regular follow-up examinations (annually or bi-annually)

  • Standardized imaging protocols (slit-lamp photography, Scheimpflug imaging)

  • Quantitative measures of lens opacity

  • Visual function assessments

  • Pre and post-surgical outcomes where applicable

• Analysis approaches: Mixed-effects modeling, survival analysis for time-to-surgery

Systematic Multicenter Collaborations:

• Advantages: Increase sample size, reduce referral bias

• Design elements:

  • Standardized phenotyping protocols across centers

  • Centralized genetic analysis

  • Shared database with detailed clinical information

  • Common consent and data sharing agreements

• Analysis approaches: Meta-analysis, pooled data analysis, rare variant aggregation

Multi-Omics Integration:

• Advantages: Identify molecular mechanisms and modifier effects

• Design elements:

  • Whole-exome or genome sequencing beyond targeted CRYGC analysis

  • Transcriptomics where tissue is available

  • Proteomics from lens capsule or aqueous humor samples

  • Metabolomics to identify biochemical signatures

• Analysis approaches: Pathway analysis, interaction network construction, systems biology modeling

What are the recommended quality control measures for CRYGC sequencing and variant interpretation?

To ensure reliable CRYGC sequencing and variant interpretation, researchers should implement the following quality control measures:

Pre-Analytical Quality Control:

• Sample collection standardization:

  • Use appropriate anticoagulants for blood samples

  • Implement rapid processing protocols

  • Store DNA at optimal conditions (-20°C or lower)

• DNA quality assessment:

  • Measure concentration (Qubit or similar fluorometric method)

  • Evaluate purity (A260/A280 ratio ≥1.8)

  • Assess integrity (gel electrophoresis or TapeStation)

Analytical Quality Control:

• PCR and Sanger sequencing:

  • Design primers with minimal secondary structure

  • Include positive and negative controls in each run

  • Sequence in both forward and reverse directions

  • Validate unusual findings with independent primer sets

• Next-generation sequencing:

  • Achieve minimum 30× average coverage for targeted regions

  • Ensure ≥95% of target bases reach sufficient coverage

  • Include both positive (known variants) and negative controls

  • Validate novel or critical variants by Sanger sequencing

  • Monitor for batch effects across sequencing runs

Bioinformatic Quality Control:

• Alignment metrics:

  • Assess percentage of reads mapped to reference

  • Monitor for areas of systematic low coverage

  • Check for strand bias

• Variant calling:

  • Apply appropriate filtering parameters for GC-rich regions

  • Set quality score thresholds based on validation studies

  • Evaluate allelic balance for heterozygous calls

  • Check segregation in family members when available

Variant Interpretation Quality Control:

• Use multiple in silico prediction tools with documented performance for crystallin genes

• Apply ACMG/AMP guidelines systematically with documented evidence categories

• Consult multiple databases (ClinVar, LOVD, HGMD) for previous reports

• Perform periodic reanalysis as new information becomes available

• Implement dual review by independent analysts for clinical reporting

• Participate in external quality assessment programs

What novel therapeutic approaches are being investigated for CRYGC-associated cataracts, and what methodologies support their development?

Several innovative therapeutic approaches are being investigated for CRYGC-associated cataracts:

Gene Therapy Approaches:

• CRISPR/Cas9-mediated gene editing to correct specific mutations

• Antisense oligonucleotides to modulate splicing or suppress expression of mutant alleles

• AAV-mediated gene supplementation to deliver functional CRYGC copies

Methodological considerations include:

• Lens-specific promoters for targeted expression

• Delivery methods optimized for the avascular lens

• Assessment of off-target effects

• Timing of intervention (developmental window)

Pharmacological Chaperones:

• Small molecules that stabilize mutant proteins and prevent aggregation

• Compounds that enhance protein quality control mechanisms

• Antioxidants that mitigate secondary oxidative damage

Methodological support includes:

• High-throughput screening using fluorescence-based aggregation assays

• Structure-based drug design targeting specific CRYGC variants

• In vitro validation using recombinant proteins

• Lens organ culture systems for preclinical testing

Protein Disaggregation Strategies:

• Enhanced chaperone function through αA-crystallin modulation

• Targeted activation of autophagy to clear protein aggregates

• Engineered enzymes to dissolve protein aggregates

Methodologies supporting development:

• Transgenic mouse models expressing mutant CRYGC

• Ex vivo lens culture systems for intervention testing

• Advanced imaging to monitor aggregate clearance

• Electrophysiological assessment of lens transparency

Stem Cell and Regenerative Approaches:

• Lens fiber differentiation from autologous stem cells

• Bioengineered lens constructs with normal crystallin expression

• Partial lens regeneration stimulation through molecular signals

Methodological considerations include:

• Protocols for directed differentiation of stem cells to lens fiber cells

• Biomaterials compatible with lens optical properties

• Functional assessment of regenerated tissue

• Integration with existing lens structures

How do epigenetic factors influence CRYGC expression, and what methodologies best capture these regulatory mechanisms?

Epigenetic regulation of CRYGC expression represents an emerging area of research with important implications for lens development and cataract formation. Several key mechanisms and corresponding methodologies are highlighted below:

DNA Methylation:

• Regulatory regions in the CRYGC promoter and enhancers may undergo differential methylation during lens development

• Age-related changes in methylation patterns could contribute to crystallin expression alterations

Methodological approaches:

• Bisulfite sequencing for comprehensive methylation profiling

• Methylation-specific PCR for targeted analysis

• Reduced representation bisulfite sequencing (RRBS) for genome-wide screening

• DNA methyltransferase inhibitor studies to assess functional relevance

Histone Modifications:

• Activating marks (H3K4me3, H3K27ac) in lens-specific enhancers during development

• Repressive marks (H3K27me3, H3K9me3) in non-lens tissues for tissue-specific expression

• Bivalent domains during lens precursor differentiation

Methodological approaches:

• ChIP-seq for genome-wide histone modification mapping

• CUT&RUN for higher resolution profiling with less material

• ChIP-qPCR for targeted analysis of CRYGC regulatory regions

• Histone deacetylase inhibitor studies to assess functional impact

Chromatin Accessibility:

• Dynamic changes in chromatin structure during lens development

• Accessibility of CRYGC regulatory elements in different cell types

Methodological approaches:

• ATAC-seq for genome-wide accessibility profiling

• DNase-seq for hypersensitive site identification

• Chromosome conformation capture (3C, 4C, Hi-C) to map interactions between CRYGC and distal regulatory elements

Non-coding RNAs:

• lncRNAs potentially regulating CRYGC expression

• miRNAs targeting CRYGC mRNA for post-transcriptional regulation

Methodological approaches:

• RNA-seq with specialized library preparation for non-coding RNA detection

• CLIP-seq to identify RNA-protein interactions

• RNA antisense purification to identify RNA-RNA interactions

• Functional studies using locked nucleic acids (LNAs) or siRNAs

Integrative Epigenomic Analysis:

• Correlation of multiple epigenetic marks with expression data

• Identification of lens-specific regulatory elements

Methodological considerations:

• Single-cell approaches to capture heterogeneity in lens fiber cells

• Developmental time course studies to track epigenetic changes

• Comparative analysis across species to identify conserved regulatory mechanisms

• Integration with GWAS data to identify potential regulatory variants

What are the key unresolved questions in CRYGC research that would benefit from interdisciplinary approaches?

Several critical questions in CRYGC research remain unresolved and would benefit significantly from interdisciplinary approaches:

• Structure-Function Relationships:

  • How do specific domains within CRYGC contribute to its unique biophysical properties?

  • What molecular mechanisms underlie the transition from soluble to aggregated states?

  • How do interactions with other crystallins modify CRYGC stability and function?

  Interdisciplinary approach: Combine structural biology, biophysics, computational modeling, and cellular biology to create integrated models of CRYGC behavior under normal and pathological conditions.

• Developmental Regulation:

  • What controls the precise spatiotemporal expression of CRYGC during lens development?

  • How does CRYGC contribute to the refractive index gradient in the lens?

  • What mechanisms maintain CRYGC stability over decades in the aging lens?

  Interdisciplinary approach: Integrate developmental biology, epigenetics, proteomics, and advanced imaging to track CRYGC from expression to long-term maintenance.

• Genotype-Phenotype Correlations:

  • Why do similar mutations produce variable phenotypes in different individuals?

  • What modifier genes influence the expressivity of CRYGC mutations?

  • How do environmental factors interact with genetic predispositions?

  Interdisciplinary approach: Combine clinical ophthalmology, genomics, statistical genetics, and environmental health sciences to develop comprehensive models of cataract risk and progression.

• Therapeutic Development:

  • Can gene editing technologies effectively address CRYGC mutations in vivo?

  • What delivery systems can overcome the unique challenges of the lens environment?

  • How can patient-specific factors be incorporated into treatment selection?

  Interdisciplinary approach: Unite molecular biology, pharmaceutical sciences, bioengineering, and clinical medicine to develop and translate novel interventions.

• Systems Integration:

  • How does CRYGC function within the broader protein homeostasis network of the lens?

  • What compensatory mechanisms exist when CRYGC function is compromised?

  • How do age-related changes in other lens components affect CRYGC stability?

  Interdisciplinary approach: Apply systems biology, network analysis, aging research, and mathematical modeling to understand CRYGC in its full biological context.

How can researchers optimize methodological approaches to advance understanding of CRYGC biology and pathology?

To optimize methodological approaches for CRYGC research, investigators should consider these strategies:

• Standardization and Protocol Sharing:

  • Establish community-accepted protocols for CRYGC expression, purification, and functional analysis

  • Develop standardized phenotyping approaches for consistent clinical characterization

  • Create shared repositories of validated reagents (antibodies, constructs, cell lines)

  • Implement open data sharing practices to maximize research impact

• Technology Integration:

  • Combine complementary methods to address limitations of individual approaches

  • Develop multi-modal imaging pipelines that connect molecular events to macroscopic lens changes

  • Create integrated workflows that link genetic findings directly to functional validation

  • Implement automated high-throughput screening for therapeutic discovery

• Model System Advancement:

  • Develop improved in vitro systems that better recapitulate the lens environment

  • Create organoid models of lens development incorporating CRYGC mutations

  • Generate knock-in mouse models of human CRYGC variants

  • Establish patient-derived iPSC models for personalized disease modeling

• Quantitative Analysis Enhancement:

  • Apply advanced statistical methods for handling complex genotype-phenotype relationships

  • Develop computational models that predict CRYGC behavior across temporal and spatial scales

  • Implement machine learning approaches for image analysis and phenotype classification

  • Utilize systems biology frameworks to interpret multi-omics data

• Collaborative Research Structures:

  • Establish multi-disciplinary research consortia focused on crystallin biology

  • Create shared biobanks of samples from patients with CRYGC mutations

  • Develop collaborative clinical networks for natural history studies

  • Implement team science approaches that unite basic, translational, and clinical expertise