Clinical utility of the low-density Infinium QC genotyping Array in a genomics-based diagnostics laboratory

Background

With 15,949 markers, the low-density Infinium QC Array-24 BeadChip enables linkage analysis, HLA haplotyping, fingerprinting, ethnicity determination, mitochondrial genome variations, blood groups and pharmacogenomics. It represents an attractive independent QC option for NGS-based diagnostic laboratories, and provides cost-efficient means for determining gender, ethnic ancestry, and sample kinships, that are important for data interpretation of NGS-based genetic tests.

Methods

We evaluated accuracy and reproducibility of Infinium QC genotyping calls by comparing them with genotyping data of the same samples from other genotyping platforms, whole genome/exome sequencing. Accuracy and robustness of determining gender, provenance, and kinships were assessed.

Results

Concordance of genotype calls between Infinium QC and other platforms was above 99%. Here we show that the chip’s ancestry informative markers are sufficient for ethnicity determination at continental and sometimes subcontinental levels, with assignment accuracy varying with the coverage for a particular region and ethnic groups. Mean accuracies of provenance prediction at a regional level were varied from 81% for Asia, to 89% for Americas, 86% for Africa, 97% for Oceania, 98% for Europe, and 100% for India. Mean accuracy of ethnicity assignment predictions was 63%. Pairwise concordances of AFR samples with the samples from any other super populations were the lowest (0.39–0.43), while the concordances within the same population were relatively high (0.55–0.61). For all populations except African, cross-population comparisons were similar in their concordance ranges to the range of within-population concordances (0.54–0.57). Gender determination was correct in all tested cases.

Conclusions

Our results indicate that the Infinium QC Array-24 chip is suitable for cost-efficient, independent QC assaying in the settings of an NGS-based molecular diagnostic laboratory; hence, we recommend its integration into the standard laboratory workflow. Low-density chips can provide sample-specific measures for variant call accuracy, prevent sample mix-ups, validate self-reported ethnicities, and detect consanguineous cases. Integration of low-density chips into QC procedures aids proper interpretation of candidate sequence variants. To enhance utility of this low-density chip, we recommend expansion of ADME and mitochondrial markers. Inexpensive Infinium-like low-density human chips have a potential to become a “Swiss army knife” among genotyping assays suitable for many applications requiring high-throughput assays.

     

The Chromosome‐centric Human Proteome Project at FEBS Congress

In the summer of 2013, distinguished global representatives of proteome science gathered to discuss the futuristic visions of the chromosome‐centric human proteome project (C‐HPP) (Cochairs: Y. K. Paik, G. Omenn; hosted by A. Archakov, Institute of Biomedical Chemistry, Russia) that was broadcast to the annual Federation of European Biochemical Societies Congress (St. Petersburg, Russia, July 10–11, 2013). Technology breakthroughs presented included a new ultra‐sensitive Tribrid mass‐spectrometer from Thermo and SOMAmers—Slow Off‐rate Modified Aptamers (SOMAlogic, USA), a new type of protein capture reagents. Professor Archakov's group introduced the “rectangle” concept of proteome size as a product of proteome width and depth. The discussion on proteome width culminated with the introduction of digital biomarkers—low‐copied aberrant proteins that differ from their typical forms by PTMs, alternative splicing, or single amino acid polymorphisms. The aberrant proteoforms, a complement to whole‐genome proteomic surveys, were presented as an ultimate goal for the proteomic community.     

Selection of reliable reference genes for qRT-PCR analysis in human non-cancerous gastric tissue

Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in complex diseases like obesity and gastritis. However, variations in amount of starting material, enzymatic efficiency and presence of amplification inhibitors can lead to quantification errors. Hence, the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Human gastric tissue has been the least investigated for stability of reference gene expression. In this study, three popular algorithms, GeNorm, NormFinder and BestKeeper were used to evaluate the reference gene stability. Conclusion: HPRT1 and GAPDH are the best performing pair of reference genes for qRT-PCR profiling experiments involving non-malignant gastric tissue samples.     

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