A daily-updated tree of (sequenced) life as a reference for genome research

We report a daily-updated sequenced/species Tree Of Life (sTOL) as a reference for the increasing number of cellular organisms with their genomes sequenced. The sTOL builds on a likelihood-based weight calibration algorithm to consolidate NCBI taxonomy information in concert with unbiased sampling of molecular characters from whole genomes of all sequenced organisms. Via quantifying the extent of agreement between taxonomic and molecular data, we observe there are many potential improvements that can be made to the status quo classification, particularly in the Fungi kingdom; we also see that the current state of many animal genomes is rather poor. To augment the use of sTOL in providing evolutionary contexts, we integrate an ontology infrastructure and demonstrate its utility for evolutionary understanding on: nuclear receptors, stem cells and eukaryotic genomes. The sTOL (http://supfam.org/SUPERFAMILY/ sTOL) provides a binary tree of (sequenced) life, and contributes to an analytical platform linking genome evolution, function and phenotype

Breast cancer management pathways during the COVID-19 pandemic: outcomes from the UK ‘Alert Level 4’ phase of the B-MaP-C study

Abstract: Background: The B-MaP-C study aimed to determine alterations to breast cancer (BC) management during the peak transmission period of the UK COVID-19 pandemic and the potential impact of these treatment decisions. Methods: This was a national cohort study of patients with early BC undergoing multidisciplinary team (MDT)-guided treatment recommendations during the pandemic, designated ‘standard’ or ‘COVID-altered’, in the preoperative, operative and post-operative setting. Findings: Of 3776 patients (from 64 UK units) in the study, 2246 (59%) had ‘COVID-altered’ management. ‘Bridging’ endocrine therapy was used (n = 951) where theatre capacity was reduced. There was increasing access to COVID-19 low-risk theatres during the study period (59%). In line with national guidance, immediate breast reconstruction was avoided (n = 299). Where adjuvant chemotherapy was omitted (n = 81), the median benefit was only 3% (IQR 2–9%) using ‘NHS Predict’. There was the rapid adoption of new evidence-based hypofractionated radiotherapy (n = 781, from 46 units). Only 14 patients (1%) tested positive for SARS-CoV-2 during their treatment journey. Conclusions: The majority of ‘COVID-altered’ management decisions were largely in line with pre-COVID evidence-based guidelines, implying that breast cancer survival outcomes are unlikely to be negatively impacted by the pandemic. However, in this study, the potential impact of delays to BC presentation or diagnosis remains unknown

The evolution of human cells in terms of protein innovation

Humans are composed of hundreds of cell types. As the genomic DNA of each somatic cell is identical, cell type is determined by what is expressed and when. Until recently, little has been reported about the determinants of human cell identity, particularly from the joint perspective of gene evolution and expression. Here, we chart the evolutionary past of all documented human cell types via the collective histories of proteins, the principal product of gene expression. FANTOM5 data provide cell-type-specific digital expression of human protein-coding genes and the SUPERFAMILY resource is used to provide protein domain annotation. The evolutionary epoch in which each protein was created is inferred by comparison with domain annotation of all other completely sequenced genomes. Studying the distribution across epochs of genes expressed in each cell type reveals insights into human cellular evolution in terms of protein innovation. For each cell type, its history of protein innovation is charted based on the genes it expresses. Combining the histories of all cell types enables us to create a timeline of cell evolution. This timeline identifies the possibility that our common ancestor Coelomata (cavity-forming animals) provided the innovation required for the innate immune system, whereas cells which now form the brain of human have followed a trajectory of continually accumulating novel proteins since Opisthokonta (boundary of animals and fungi). We conclude that exaptation of existing domain architectures into new contexts is the dominant source of cell-type-specific domain architectures. </p

A daily-updated tree of (sequenced) life as a reference for genome research

We report a daily-updated sequenced/species Tree Of Life (sTOL) as a reference for the increasing number of cellular organisms with their genomes sequenced. The sTOL builds on a likelihood-based weight calibration algorithm to consolidate NCBI taxonomy information in concert with unbiased sampling of molecular characters from whole genomes of all sequenced organisms. Via quantifying the extent of agreement between taxonomic and molecular data, we observe there are many potential improvements that can be made to the status quo classification, particularly in the Fungi kingdom; we also see that the current state of many animal genomes is rather poor. To augment the use of sTOL in providing evolutionary contexts, we integrate an ontology infrastructure and demonstrate its utility for evolutionary understanding on: nuclear receptors, stem cells and eukaryotic genomes. The sTOL (http://supfam.org/SUPERFAMILY/sTOL) provides a binary tree of (sequenced) life, and contributes to an analytical platform linking genome evolution, function and phenotype.</p

Hypothesis-free phenotype prediction within a genetics-first framework.

Funder: Wellcome TrustCohort-wide sequencing studies have revealed that the largest category of variants is those deemed 'rare', even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population. Associative methods give some understanding how rare genetic variants influence disease and organism-level phenotypes. But here we show that additional discoveries can be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible genetic causes for developmental disorders that have eluded other established methods and present molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied

Hypothesis-free phenotype prediction within a genetics-first framework.

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed 'rare', even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population. Associative methods give some understanding how rare genetic variants influence disease and organism-level phenotypes. But here we show that additional discoveries can be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible genetic causes for developmental disorders that have eluded other established methods and present molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied

New Oral Anticoagulants Are Not Superior to Warfarin in Secondary Prevention of Stroke or Transient Ischemic Attacks, but Lower the Risk of Intracranial Bleeding: Insights from a Meta-Analysis and Indirect Treatment Comparisons

PURPOSE: Patients with Atrial Fibrillation (AF) and prior stroke are classified as high risk in all risk stratification schemes. A systematic review and meta-analysis was performed to compare the efficacy and safety of New Oral Anticoagulants (NOACs) to warfarin in patients with AF and previous stroke or transient ischemic attack (TIA). METHODS: Three randomized controlled trials (RCTs), including total 14527 patients, comparing NOACs (apixaban, dabigatran and rivaroxaban) with warfarin were included in the analysis. Primary efficacy endpoint was ischemic stroke, and primary safety endpoint was intracranial bleeding. Random-effects models were used to pool efficacy and safety data across RCTs. RevMan and Stata software were used for direct and indirect comparisons, respectively. RESULTS: In patients with AF and previous stroke or TIA, effects of NOACs were not statistically different from that of warfarin, in reduction of stroke (Odds Ratio [OR] 0.86, 95% confidence interval [CI] 0.73- 1.01), disabling and fatal stroke (OR 0.85, 95% CI 0.71-1.04), and all-cause mortality (OR 0.90, 95% CI 0.79 -1.02). Randomization to NOACs was associated with a significantly lower risk of intracranial bleeding (OR 0.42, 95% CI 0.25-0.70). There were no major differences in efficacy between apixaban, dabigatran (110 mg BID and 150 mg BID) and rivaroxaban. Major bleeding was significantly lower with apixaban and dabigatran (110 mg BID) compared with dabigatran (150 mg BID) and rivaroxaban. CONCLUSION: NOACs may not be more effective than warfarin in the secondary prevention of ischemic stroke in patients with a prior history of cerebrovascular ischemia, but have a lower risk of intracranial bleeding