Skip to main content
Premium Trial:

Request an Annual Quote

Nature Studies Report NHS Sequencing Enabled Rare Disease Diagnoses, Third Phylum Within Green Plants, More

Applying whole-genome sequencing to populations in the UK's National Health Service (NHS) enabled the genetic diagnosis of rare diseases in thousands of patients, while providing information on the etiological variants and causative genes for many of the disorders, according to a paper appearing in Nature this week. In the study, a University of Cambridge-led team generated WGS data for 13,037 individuals enrolled in 57 NHS hospitals in the UK and 26 hospitals in other countries. The researchers were able to provide a genetic diagnosis to 1,138 of 7,065 rare disease patients with detailed phenotypic data and identified 95 Mendelian associations between genes and rare diseases. The investigators also used WGS data from the UK Biobank to uncover rare alleles involved in red blood cell-associated pathologies in certain people typically excluded from genome-wide association studies. "Our study demonstrates a synergy by using WGS for diagnosis and etiological discovery in routine healthcare," the authors write. GenomeWeb has more on this here.

A genomic analysis of the pico-eukaryotic marine green alga Prasinoderma coloniale, presented in Nature Ecology & Evolution this week, reveals the existence of a new, third phylum within green plants (Viridiplantae). The P. colonialegenome — representing the first nuclear genome sequence of a unicellular member of Palmophyllophyceae — enabled a team led by scientists from BGI-Shenzhen to uncover the phylum Prasinodermophyta, which diverged before the split of Viridiplantae into Chlorophyta and Streptophyta. The researchers find adaptations of P. coloniale to its deep-water environment involved the expansion of light-harvesting proteins and a distinct type of C4 photosynthesis.

A pair of papers appearing in this week's Nature Medicine demonstrate the clinical utility of a technique for analyzing cell-free DNA (cfDNA) methylomes for detecting two different cancers. In the first study, researchers from Toronto's University Health Network and collaborators apply an approach they developed for recovering and profiling methylated DNA fragments to intracranial tumors. The team shows that the method — which combines cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) — reveals "highly specific signatures to detect and accurately discriminate common primary intracranial tumors that share cell-of-origin lineages and can be challenging to distinguish using standard-of-care imaging." In the second study, a Harvard Medical School-led research group uses cfMeDIP-seq to accurately classify renal cell carcinoma patients across all stages of the disease. Further, they show that cfMeDIP-seq can be used with cfDNA in urine samples to identify RCC patients. "After training on larger datasets and performing prospective validation, this method could ultimately reduce morbidity and mortality through early and accurate detection of RCC and other cancers," the investigators write.