Recombinant Human Uncharacterized protein C6orf10 (C6orf10)

What is the chromosomal location and genetic structure of C6orf10?

C6orf10 is located on chromosome 6p21.32 within the major histocompatibility complex (MHC) region, which also contains the HLA-DRB1 gene. The C6orf10 structure comprises several transcripts, including three isoforms of validated long non-coding RNA (NR_136244.1, NR_136245.1, and NR_136246.1) and a pseudogene hnRNP (HNRNPA1P2). The full transcript ENST00000533191.5 spans approximately 80 Kb .

The gene contains multiple exons with a complex 3' region. Analysis of the ENST00000533191.5 transcript reveals that some variants can affect the C-terminal portion of several uncharacterized proteins that are expressed in both brain and B cells, which are tissues of particular interest in multiple sclerosis research .

How is recombinant C6orf10 different from native C6orf10?

Native C6orf10 is the protein as it exists naturally in biological systems, while recombinant C6orf10 is produced through laboratory methods involving expression systems. When working with recombinant proteins, researchers should be aware that post-translational modifications may differ from the native form, potentially affecting protein function and interaction studies.

For detection purposes, some assays like ELISA kits are specifically designed for native C6orf10 rather than recombinant forms. These assays are optimized to detect the protein in biological samples such as undiluted body fluids and/or tissue homogenates and secretions .

What is the association between C6orf10 variants and Multiple Sclerosis?

Studies have identified significant associations between C6orf10 variants and Multiple Sclerosis (MS). In a cohort of 120 Italian unrelated MS patients, the C6orf10 rs16870005 variant showed significantly higher allelic frequencies compared to control databases (p = 9.89 × 10-7 when compared with gnomAD controls). Importantly, this association does not appear to depend on linkage disequilibrium with the HLA-DRB1 locus, despite C6orf10's location in the MHC region .

Sequencing of the C6orf10 3′ region revealed 14 rare mutations in MS patients, with 10 not previously reported. Four of these variants were null mutations (causing premature termination or translational frameshift), and their frequency was significantly higher than in control databases (p = 0.0254 compared to Control gnomAD, p = 0.0184 compared to ExAC) .

How is C6orf10 implicated in gene-gene interactions related to lung cancer susceptibility?

Genome-wide gene-gene interaction studies have identified significant interactions involving C6orf10 in relation to lung cancer susceptibility. In European populations, a significant interaction between rs521828 (C6orf10) and rs204999 (PRRT1) was identified with an interaction odds ratio of 1.17 (p = 6.57 × 10-13). Notably, this interaction remained significant when validated in an Asian population (interaction odds ratio = 1.13), despite considerable genetic heterogeneity across ethnicities .

These findings suggest that C6orf10 may participate in complex genetic interactions that contribute to lung cancer risk, potentially through mechanisms involving the MHC region where C6orf10 is located .

What are the recommended methods for detecting native C6orf10 in biological samples?

For detecting native C6orf10 in biological samples, enzyme-linked immunosorbent assay (ELISA) is a commonly used technique. ELISA kits for C6orf10 are designed based on C6orf10 antibody-C6orf10 antigen interactions (immunosorbency) with an HRP colorimetric detection system .

When selecting samples for C6orf10 detection, appropriate types may include undiluted body fluids, tissue homogenates, and secretions. It's important to note that most commercially available detection kits are optimized for native, not recombinant, C6orf10 .

What sequencing approaches are recommended for studying C6orf10 variants?

For comprehensive detection of C6orf10 variants, a combination of whole exome sequencing (WES) and targeted Sanger sequencing is recommended. In previous studies, WES was used to identify exonic low-frequency SNPs, followed by targeted Sanger sequencing of specific regions like the 3′ exon of C6orf10 (chr6:32261295-32260757) .

When analyzing sequencing data, it's important to consider all potential transcripts of C6orf10, as variants may have different effects depending on the specific isoform. For example, the transcript ENST0000442822.6 undergoes splicing and encodes a different 3′ sequence compared to other transcripts, which affects the interpretation of null mutations .

How should researchers evaluate the functional impact of C6orf10 variants?

When evaluating the functional impact of C6orf10 variants, researchers should consider:

• Location of the variant within the gene structure

• Type of mutation (missense, nonsense, frameshift)

• Effect on different transcripts

• Potential linkage disequilibrium with other loci

• Prediction algorithms for functional effects

For missense variants, multiple prediction algorithms should be employed as they may yield discordant results. For example, in previous studies of C6orf10 variants in MS patients, algorithms predicted discordant effects for most missense changes, with only certain variants like Gly477Val (rs7751028) consistently predicted as damaging .

For null mutations (nonsense or frameshift), consider which portion of the protein is affected and in which transcripts. In C6orf10, null mutations can remove varying portions of the C-terminus depending on the specific transcript affected .

What considerations are important when analyzing C6orf10 in genome-wide gene-gene interaction studies?

When analyzing C6orf10 in genome-wide gene-gene interaction studies, researchers should consider:

• Dimensional reduction techniques: Due to computational constraints and the vast number of possible interactions, screening methods like "Screening before Testing" are recommended .

• Two-phase study design: A discovery phase followed by a validation phase helps control false positives. For example, significant interactions identified in one population (e.g., ILCCO-OncoArray and TRICL) should be confirmed in an independent cohort (e.g., UK Biobank) .

• Trans-ethnic validation: Given the genetic heterogeneity across ethnicities, validating findings across different populations (e.g., European and Asian) strengthens the evidence for true associations .

• Linkage disequilibrium: When analyzing C6orf10, consider its location in the MHC region and potential linkage disequilibrium with HLA genes. For example, C6orf10 rs16870005 shows low LD with HLA rs9271366 (r² = 0.055), suggesting independent association .

What are the challenges in interpreting combinations of C6orf10 variants?

Interpreting combinations of C6orf10 variants presents several challenges:

• Intra-locus combinations: Some patients may carry multiple variants within the C6orf10 gene itself. For example, studies have found three patients with combinations of heterozygous low-frequency variants within C6orf10 .

• Inter-locus combinations: C6orf10 variants may occur in combination with variants in other genes. Previous research has identified seven patients with combinations of C6orf10 variants and low-frequency variants in other candidate genes .

• Homozygosity effects: Homozygous null mutations may have particularly strong effects. For instance, a homozygous Ser389Xfr mutation was found in a patient with early onset MS, suggesting a potential role in disease onset .

• Statistical power limitations: Small sample sizes limit the evaluation of the possible impact of multiple variants within an integrated model. Larger cohorts are needed to assess how combinations of variants affect disease onset or clinical course .

What factors should be considered when developing recombinant C6orf10 for experimental use?

When developing recombinant C6orf10 for experimental use, researchers should consider:

• Carrier proteins: For protein stability, shelf-life enhancement, and storage at dilute concentrations, consider whether to include carrier proteins like Bovine Serum Albumin (BSA). While carrier proteins can enhance stability, carrier-free versions may be preferred for applications where BSA could interfere .

• Expression system selection: Choose an appropriate expression system based on your research needs, considering factors such as post-translational modifications, protein folding, and yield.

• Transcript selection: Given the multiple transcripts of C6orf10, carefully consider which transcript variant to express as a recombinant protein, as this will affect the structure and potentially the function of the protein.

• Validation methods: Incorporate appropriate quality control assays to assess reproducibility, including intra-assay CV (%) and inter-assay CV(%) measurements .

What are promising areas for future research involving C6orf10?

Several promising research directions for C6orf10 include:

• Functional characterization: Given that C6orf10 remains largely uncharacterized, basic research into its normal biological function is needed.

• Age of disease onset: Investigate the potential role of C6orf10 in determining the age of onset of neurodegenerative diseases. Previous research has suggested a link between C6orf10 and early onset of MS, warranting further investigation .

• Tissue-specific expression: Further explore the expression of C6orf10 in brain and B cells, tissues that are particularly relevant to MS pathophysiology .

• Gene-gene interactions: Expand studies of interactions between C6orf10 and other genes in the context of complex diseases like lung cancer and MS .

• Development of lung cancer screening models: Incorporate C6orf10 gene-gene interactions into polygenetic risk score (PRS) models for identifying high-risk subpopulations for lung cancer screening .

How might C6orf10 contribute to personalized medicine approaches?

C6orf10 variants show potential for inclusion in personalized medicine approaches through several mechanisms:

• Risk stratification: Specific C6orf10 variants or combinations of variants could be incorporated into genetic risk scores for diseases like MS and lung cancer.

• Disease onset prediction: Given the association between certain C6orf10 variants (like homozygous Ser389Xfr) and early disease onset in MS, genotyping could help predict age of onset and inform preventive strategies .

• Population-specific risk assessment: Consider the variations in C6orf10 allele frequencies across different populations when developing personalized risk models.

• Integrated genetic models: Combine C6orf10 variant data with other genetic markers for improved risk prediction. For example, incorporating gene-gene interactions into polygenetic risk scores may enhance lung cancer screening models .