Stochastic loss and gain of symmetric divisions in the C. elegans epidermis perturbs robustness of stem cell number

Biological systems are subject to inherent stochasticity. Nevertheless, development is remarkably robust, ensuring the consistency of key phenotypic traits such as correct cell numbers in a certain tissue. It is currently unclear which genes modulate phenotypic variability, what their relationship is to core components of developmental gene networks, and what is the developmental basis of variable phenotypes. Here, we start addressing these questions using the robust number of Caenorhabditis elegans epidermal stem cells, known as seam cells, as a readout. We employ genetics, cell lineage tracing, and single molecule imaging to show that mutations in lin-22, a Hes-related basic helix-loop-helix (bHLH) transcription factor, increase seam cell number variability. We show that the increase in phenotypic variability is due to stochastic conversion of normally symmetric cell divisions to asymmetric and vice versa during development, which affect the terminal seam cell number in opposing directions. We demonstrate that LIN-22 acts within the epidermal gene network to antagonise the Wnt signalling pathway. However, lin-22 mutants exhibit cell-to-cell variability in Wnt pathway activation, which correlates with and may drive phenotypic variability. Our study demonstrates the feasibility to study phenotypic trait variance in tractable model organisms using unbiased mutagenesis screens

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Bi-allelic Variants in TKFC Encoding Triokinase/FMN Cyclase Are Associated with Cataracts and Multisystem Disease

International audienceWe report an inborn error of metabolism caused by TKFC deficiency in two unrelated families. Rapid trio genome sequencing in family 1 and exome sequencing in family 2 excluded known genetic etiologies, and further variant analysis identified rare homozygous variants in TKFC. TKFC encodes a bifunctional enzyme involved in fructose metabolism through its glyceraldehyde kinase activity and in the generation of riboflavin cyclic 4',5'-phosphate (cyclic FMN) through an FMN lyase domain. The TKFC homozygous variants reported here are located within the FMN lyase domain. Functional assays in yeast support the deleterious effect of these variants on protein function. Shared phenotypes between affected individuals with TKFC deficiency include cataracts and developmental delay, associated with cerebellar hypoplasia in one case. Further complications observed in two affected individuals included liver dysfunction and microcytic anemia, while one had fatal cardiomyopathy with lactic acidosis following a febrile illness. We postulate that deficiency of TKFC causes disruption of endogenous fructose metabolism leading to generation of by-products that can cause cataract. In line with this, an affected individual had mildly elevated urinary galactitol, which has been linked to cataract development in the galactosemias. Further, in light of a previously reported role of TKFC in regulating innate antiviral immunity through suppression of MDA5, we speculate that deficiency of TKFC leads to impaired innate immunity in response to viral illness, which may explain the fatal illness observed in the most severely affected individual

Quantification of <i>lin-22</i> expression in the seam.

<p>(A) Transgenic animals carrying transcriptional reporters consisting of various fragments of upstream of <i>lin-22</i> sequences fused to GFP. From top to bottom: full <i>lin-22</i> endogenous promoter, distal <i>lin-22</i> promoter region that is deleted in <i>lin-22(icb38)</i>, proximal <i>lin-22</i> promoter present in <i>lin-22(icb38)</i>, distal <i>lin-22</i> promoter with deleted CR1, and CR1 only driving expression of GFP. White arrows indicate expression in the seam cells; white arrowheads expression in the hypodermis and green arrowheads expression in intestinal cells. (B) Quantification of expression pattern for each transcriptional reporter (<i>n</i> ≥ 35 animals). (C) Representative smFISH images showing <i>lin-22</i> expression (black spots correspond to mRNAs and seam cells are labelled in green due to <i>scm</i>∷<i>GFP</i> expression) in wild-type V cells after the symmetric L2 division (top), the L2 asymmetric division (middle), and late after the L2 asymmetric division (bottom). (D) Quantification of <i>lin-22</i> spots per seam cell in wild-type and <i>lin-22(icb38)</i> animals at the late L1 stage (<i>n</i> ≥ 10 cells per genotype). (E) Quantification of <i>lin-22</i> spots in wild-type, <i>lin-22(ot267)</i>, <i>lin-22(ot269)</i>, and <i>lin-22(icb49)</i> mutants in pools of H cells and V cells at the late L1 stage (<i>n</i> ≥ 41). (F-G) Comparison of number of <i>lin-22</i> spots between wild-type and the <i>elt-1(ku491)</i> mutant (F) or the <i>egl-18(ok290)</i> mutant, (G) both at the late L1 stage in pools of H and V cells (<i>n</i> ≥ 49). Black stars show statistically significant changes in the mean with a <i>t</i> test or one-way ANOVA as follows: * <i>P</i> < 0.05, ** <i>P</i> < 0.01, *** <i>P</i> < 0.001, **** <i>P</i> < 0.0001. Reference samples for comparisons in E, F, G are the control samples depicted in black. Scale bars in A and C are 100 μm and 10 μm, respectively. Error bars show mean ± SEM (D, F, G) or mean ± SD (E). Numerical data used for Fig 3B, D, E, F, G can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002429#pbio.2002429.s003" target="_blank">S2 Data</a>. CR1, conserved region 1; GFP, green fluorescent protein; L1, first larval stage; L2, second larval stage; smFISH, single molecule fluorescent in situ hybridization.</p

The <i>icb38</i> mutation represents a loss of function mutation in <i>lin-22</i>.

<p>(A) Illustration of the <i>lin-22(icb38)</i> mutation, which is a 3,329 bp deletion removing part of the distal <i>lin-22</i> promoter (2,371 bp upstream of the <i>lin-22</i> ATG). The deletion also removes part of the third exon and 3′ UTR of the upstream gene Y54G2A.3. The deleted part is replaced by a 1,733 bp insertion consisting of exon 7 and parts of introns 6 and 7 of the downstream gene <i>mca-3</i>. The position of other <i>lin-22</i> alleles described in the manuscript is shown on the wild-type sequence. (B) Quantification of the number of PDE neurons (<i>dat-1</i>∷<i>GFP</i> foci) in the EMS-derived <i>lin-22(icb-38)</i> mutant and CRISPR-derived <i>lin-22</i> mutants (<i>n</i> ≥ 30). Reference sample is <i>egIs1</i> containing only the marker. (C) Quantification of seam cell number in <i>lin-22(icb38)</i> and other CRISPR-derived <i>lin-22</i> mutants (<i>n</i> ≥ 30). Note an increase in seam cell number variance in <i>lin-22</i> mutants depicted with red stars. Black stars show statistically significant changes in the mean with one-way ANOVA followed by the Dunnett test, and red stars depict changes in variance with a Levene’s median test (in both cases, **** corresponds to <i>P</i> value < 0.0001). Error bars show mean ± SEM (B) or mean ± SD (C). Numerical data used for Fig 2B, C can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002429#pbio.2002429.s003" target="_blank">S2 Data</a>. CRISPR, Clustered Regularly Interspaced Short Palindromic Repeats; EMS, ethyl methanesulfonate; GFP, green fluorescent protein; PDE, post-deirid; scm, seam cell marker; UTR, untranslated region.</p

Rapid Paediatric Sequencing (RaPS): Comprehensive real-life workflow for rapid diagnosis of critically ill children

Background Rare genetic conditions are frequent risk factors for, or direct causes of, paediatric intensive care unit (PICU) admission. Such conditions are frequently suspected but unidentified at PICU admission. Compassionate and effective care is greatly assisted by definitive diagnostic information. There is therefore a need to provide a rapid genetic diagnosis to inform clinical management. To date, whole genome sequencing (WGS) approaches have proved successful in diagnosing a proportion of children with rare diseases, but results may take months to report. Our aim was to develop an end-to-end workflow for the use of rapid WGS for diagnosis in critically ill children in a UK National Health Service (NHS) diagnostic setting. Methods We sought to establish a multidisciplinary Rapid Paediatric Sequencing team for case selection, trio WGS, rapid bioinformatics sequence analysis and a phased analysis and reporting system to prioritise genes with a high likelihood of being causal. Results Trio WGS in 24 critically ill children led to a molecular diagnosis in 10 (42%) through the identification of causative genetic variants. In 3 of these 10 individuals (30%), the diagnostic result had an immediate impact on the individual’s clinical management. For the last 14 trios, the shortest time taken to reach a provisional diagnosis was 4 days (median 8.5 days). Conclusion Rapid WGS can be used to diagnose and inform management of critically ill children within the constraints of an NHS clinical diagnostic setting. We provide a robust workflow that will inform and facilitate the rollout of rapid genome sequencing in the NHS and other healthcare systems globally. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made

Gene expression changes associated with loss and gain of daughter cell fate symmetry in <i>lin-22</i> mutants.

<p>(A-B) Representative smFISH images and quantification of wild-type and <i>lin-22(icb38)</i> animals at the L2 symmetric division stage using an <i>elt-1</i> probe. (A) Comparable amounts of <i>elt-1</i> spots are detected in wild-type V cell daughters and more spots in the posterior H2 daughter. In <i>lin-22(icb38)</i> animals, more spots are detected in the posterior V daughters than the anterior (marked by arrowheads) and even numbers in the 2 H2.p daughters (arrow points to anterior H2.p daughter cell). (B) Quantification of <i>elt-1</i> expression in H2.p daughters (<i>n</i> > 9) and pools of V.p daughter cells (<i>n</i> > 41) of wild-type and <i>lin-22(icb38)</i> animals at the L2 symmetric division stage. (C) <i>mab-5</i> expression expands to posterior daughters of V1–V4 cells (arrowheads) in <i>lin-22(icb38)</i> animals, reminiscent of the expression in the posterior V5 cell in wild-type (arrow). (D-F) <i>egl-18</i> smFISH images and quantification of wild-type and <i>lin-22(icb38)</i> animals. (D) Quantification of <i>egl-18</i> smFISH spots in the H2.p cell daughters at the L2 stage (<i>n</i> ≥ 21). (E) Images depicting <i>egl-18</i> expression at the L3 stage. Note expression in anterior daughter cells in <i>lin-22(icb38)</i> animals (arrowheads). (F) Quantification of <i>egl-18</i> smFISH spots in V1-V4 cells (<i>n</i> ≥ 68) of wild-type and <i>lin-22(icb38)</i> animals at the L2 asymmetric division stage. (G) Representative <i>eff-1</i> smFISH images of wild-type and <i>lin-22(icb38)</i> animals at the L3 asymmetric division stage. Note absence of signal in the most anterior of the 4 daughter cells in <i>lin-22(icb38)</i> animals (arrowheads). H2 consists of 4 cells that have arisen due to symmetric division at the L2 stage. (H) Quantification of seam cell number in wild-type (<i>n</i> = 39), <i>lin-22(icb38)</i> (<i>n</i> = 29), <i>eff-1(hy21)</i> (<i>n</i> = 31), and <i>lin-22(icb38)</i>; <i>eff-1(hy21)</i> (<i>n</i> = 35) animals. Note that the <i>eff-1(hy21)</i> does not show a significant difference in seam cell numbers compared to wild-type, but the double mutant does in comparison to both parental strains. Black stars show statistically significant changes in the mean with a <i>t</i> test or one-way ANOVA /Dunnett’s test. Scale bars in A, C, E, and G are 10 μm; black spots correspond to mRNAs and green labels the seam cell nuclei. Error bars in B, D, F, H show mean ± SD. Numerical data used for Fig 5B, D, F, H can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002429#pbio.2002429.s003" target="_blank">S2 Data</a>. GFP, green fluorescent protein; L2, second larval stage; L2sym, symmetric first division at the L2 stage; L3, third larval stage; SCM, seam cell marker; smFISH, single molecule fluorescent in situ hybridization.</p

The developmental basis of variability in <i>lin-22</i> mutants.

<p>(A) The upper panel shows wild-type seam cell lineages, while the bottom panel indicates the most frequently occurring errors in <i>lin-22(icb38)</i> mutants (<i>n</i> = 14 independent complete lineages). The developmental errors are grouped for simplicity in 4 main classes and presented as a function of the developmental stage. The percentages refer to occurrence of these errors within the total number of relevant cell lineages. Note that the errors described are not independent, so they can occur within the same animal and even within the same lineage (see also <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002429#pbio.2002429.s010" target="_blank">S4 Fig</a>). (B) Heat map showing the frequency of errors per cell lineage and developmental stage (<i>n</i> = 14 lineages). Blue depicts errors leading to gain of terminal cell number due to gain of symmetric division, and red depicts errors leading to loss of symmetric division. (C-D) Quantification of seam cell number (C) and number of PDE neurons (D) in wild-type (<i>n</i> ≥ 36) and <i>lin-22(icb38)</i> animals (<i>n</i> ≥ 30) treated with control or <i>lin-28</i> RNAi. Black stars show statistically significant changes in the mean with a <i>t</i> test (<i>P</i> < 0.0001). Error bars show mean ± SD (C) or mean ± SEM in (D). Numerical data used for Fig 4B, C, D can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2002429#pbio.2002429.s003" target="_blank">S2 Data</a>. L2, second larval stage; L3, third larval stage; L4, fourth larval stage; PDE, post-deirid; RNAi, RNA interference.</p