Probing the functional consequence and clinical relevance of CD320 p.E88del, a variant in the transcobalamin receptor gene.

The biological and clinical significance of the p.E88del variant in the transcobalamin receptor, CD320, is unknown. This allele is annotated in ClinVar as likely benign, pathogenic, and of uncertain significance. To determine functional consequence and clinical relevance of this allele, we employed cell culture and genetic association studies. Fibroblasts from 16 CD320 p.E88del homozygotes exhibited reduced binding and uptake of cobalamin. Complete ascertainment of newborns with transiently elevated C3 (propionylcarnitine) in New York State demonstrated that homozygosity for CD320 p.E88del was over-represented (7/348, p < 6 × 10-5 ). Using population data, we estimate that ~85% of the p.E88del homozygotes born in the same period did not have elevated C3, suggesting that cobalamin metabolism in the majority of these infants with this genotype is unaffected. Clinical follow-up of 4/9 homozygous individuals uncovered neuropsychological findings, mostly in speech and language development. None of these nine individuals exhibited perturbation of cobalamin metabolism beyond the newborn stage even during periods of acute illness. Newborns homozygous for this allele in the absence of other factors are at low risk of requiring clinical intervention, although more studies are required to clarify the natural history of various CD320 variants across patient populations.

Mutational signatures of de-differentiation in functional non-coding regions of melanoma genomes.

Much emphasis has been placed on the identification, functional characterization, and therapeutic potential of somatic variants in tumor genomes. However, the majority of somatic variants lie outside coding regions and their role in cancer progression remains to be determined. In order to establish a system to test the functional importance of non-coding somatic variants in cancer, we created a low-passage cell culture of a metastatic melanoma tumor sample. As a foundation for interpreting functional assays, we performed whole-genome sequencing and analysis of this cell culture, the metastatic tumor from which it was derived, and the patient-matched normal genomes. When comparing somatic mutations identified in the cell culture and tissue genomes, we observe concordance at the majority of single nucleotide variants, whereas copy number changes are more variable. To understand the functional impact of non-coding somatic variation, we leveraged functional data generated by the ENCODE Project Consortium. We analyzed regulatory regions derived from multiple different cell types and found that melanocyte-specific regions are among the most depleted for somatic mutation accumulation. Significant depletion in other cell types suggests the metastatic melanoma cells de-differentiated to a more basal regulatory state. Experimental identification of genome-wide regulatory sites in two different melanoma samples supports this observation. Together, these results show that mutation accumulation in metastatic melanoma is nonrandom across the genome and that a de-differentiated regulatory architecture is common among different samples. Our findings enable identification of the underlying genetic components of melanoma and define the differences between a tissue-derived tumor sample and the cell culture created from it. Such information helps establish a broader mechanistic understanding of the linkage between non-coding genomic variations and the cellular evolution of cancer.

A bioinformatics approach for determining sample identity from different lanes of high-throughput sequencing data.

The ability to generate whole genome data is rapidly becoming commoditized. For example, a mammalian sized genome (∼3Gb) can now be sequenced using approximately ten lanes on an Illumina HiSeq 2000. Since lanes from different runs are often combined, verifying that each lane in a genome's build is from the same sample is an important quality control. We sought to address this issue in a post hoc bioinformatic manner, instead of using upstream sample or "barcode" modifications. We rely on the inherent small differences between any two individuals to show that genotype concordance rates can be effectively used to test if any two lanes of HiSeq 2000 data are from the same sample. As proof of principle, we use recent data from three different human samples generated on this platform. We show that the distributions of concordance rates are non-overlapping when comparing lanes from the same sample versus lanes from different samples. Our method proves to be robust even when different numbers of reads are analyzed. Finally, we provide a straightforward method for determining the gender of any given sample. Our results suggest that examining the concordance of detected genotypes from lanes purported to be from the same sample is a relatively simple approach for confirming that combined lanes of data are of the same identity and quality.