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Monier, B.

Publications and source records attributed to Monier, B..

14 recordsLinked to original sources

Cell exit during EMT is mechanically triggered independently of E-Cadherin loss

Epithelial-to-mesenchymal transition (EMT) is a fundamental cell process with essential functions in tissue and organ formation during development but also metastasis during cancer progression. The shift between these two states is driven by evolutionary conserved transcription factors. Cell exit from the epithelium of origin is considered to be a mere consequence of progressive adhesion loss due to transcriptional repression of genes encoding molecules such as E-Cadherin or cell polarity regulators. Here we show in the Drosophila leg that, counterintuitively, adhesions (as well as cell polarity) are maintained during cell exit, while an apico-basal force is applied on E-Cadherin complexes in vivo. By combining a genetic screen, optogenetics and laser ablation experiments, we found that this pulling force originates from transient basal filopodia-like protrusions, formed as soon as cells start to exit. Finally, apical cell detachment requires -Spectrin activity, suggesting that the lateral cortex is required to efficiently transmit basal forces up to the apical cell pole. Our results indicate that, in a mature tissue, cell exit during EMT is a mechanically controlled process. Such a mechanism driving EMT without of E-Cadherin loss could fuel metastatic dissemination of collectively migrating cancer cells.

developmental biology↗

High throughput screen of NPQ in sorghum shows highly polygenic architecture of photoprotection

O_LINatural genetic variation in photosynthesis and photoprotection within crop germplasm represents an untapped resource for crop improvement. Sorghum bicolor (sorghum) is one of the worlds most widely grown crops, yet the genetic basis of photoprotection in sorghum is not well understood. C_LIO_LIThis study examined genetic variation in non-photochemical quenching traits by screening a field-grown panel of 861 genetically diverse natural sorghum accessions across two years. C_LIO_LIBroad-sense heritability ranged between 0.3 to 0.65 across different chlorophyll fluorescence parameters. A combination of genome- and transcriptome-wide (GWAS and TWAS) identification of genetic correlates with the observed trait variation uncovered a complex genetic architecture of many significant small-effect loci. An ensemble approach based on GWAS and TWAS results and the covariance between different fluorescence parameters was used to identify 110 unique candidate genes. C_LIO_LIThe resulting high-confidence candidates reveal novel genetic associations with photoprotection and offer resources for further genetic studies and crop genomic improvement efforts. C_LI

plant biology↗

Mechanical state of pre-tumoral epithelia dictates subsequent tumour aggressiveness

Tumours evolve through the acquisition of increasingly aggressive traits associated with dysplasia. This progression is accompanied by the alteration of tumour mechanical properties, especially through extracellular matrix remodelling. However, the contribution of intrinsic tumour cells mechanics to tumour aggressiveness remains unknown in vivo. Here we show that adherens junction tension in pre-tumoral tissues dictates subsequent tumour evolution. Increased cell contractility, observed in aggressive tumours before any sign of tissue overgrowth, proved sufficient to trigger dysplasia in normally hyperplastic tumours. Unexpectedly, high contractility contributes to tumour evolution through cell death induction which favours cell-cell junctions weakening. Overall, our results highlight the need to re-evaluate the roles of tumoral cell death, and identify pre-tumour cell mechanics as an unsuspected early marker and key trigger of tumour aggressiveness. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/594669v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1a677edorg.highwire.dtl.DTLVardef@b8940org.highwire.dtl.DTLVardef@15feebaorg.highwire.dtl.DTLVardef@13213ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Muller's Ratchet in Action: The Erosion of Sexual Reproduction Genes in Domesticated Cassava (Manihot esculenta)

Centuries of clonal propagation in cassava (Manihot esculenta) have engaged Mullers Ratchet, leading to the accumulation of deleterious mutations due to the absence of sexual recombination. This has resulted in both inbreeding depression affecting yield and a significant decrease in reproductive performance, creating hurdles for contemporary breeding programs. Cassava is a member of the Euphorbiaceae family, including notable species such as rubber tree (Hevea brasiliensis) and poinsettia (Euphorbia pulcherrima). Expanding upon preliminary draft genomes, we annotated 7 long-read genome assemblies and aligned a total of 52 genomes, to analyze selection across the genome and the phylogeny. Through this comparative genomic approach, we identified 48 genes under relaxed selection in cassava. Notably, we discovered an overrepresentation of floral expressed genes, especially focused at six pollen-related genes. Our results indicate that domestication and a transition to clonal propagation has reduced selection pressures on sexually reproductive functions in cassava leading to an accumulation of mutations in pollen-related genes. This relaxed selection and the genome-wide deleterious mutations responsible for inbreeding depression are potential targets for improving cassava breeding, where the generation of new varieties relies on recombining favorable alleles through sexual reproduction.

evolutionary biology↗

Fishing for a reelGene: evaluating gene models with evolution and machine learning

Assembled genomes and their associated annotations have transformed our study of gene function. However, each new assembly generates new gene models. Inconsistencies between annotations likely arise from biological and technical causes, including pseudogene misclassification, transposon activity, and intron retention from sequencing of unspliced transcripts. To evaluate gene model predictions, we developed reelGene, a pipeline of machine learning models focused on (1) transcription boundaries, (2) mRNA integrity, and (3) protein structure. The first two models leverage sequence characteristics and evolutionary conservation across related taxa to learn the grammar of conserved transcription boundaries and mRNA sequences, while the third uses conserved evolutionary grammar of protein sequences to predict whether a gene can produce a protein. Evaluating 1.8 million gene models in maize, reelGene found that 28% were incorrectly annotated or nonfunctional. By leveraging a large cohort of related species and through learning the conserved grammar of proteins, reelGene provides a tool for both evaluating gene model accuracy and genome biology.

genomics↗

Elucidating the patterns of pleiotropy and its biological relevance in maize

Pleiotropy - when a single gene controls two or more seemingly unrelated traits - has been shown to impact genes with effects on flowering time, leaf architecture, and inflorescence morphology in maize. However, the genome-wide impact of true biological pleiotropy across all maize phenotypes is largely unknown. Here we investigate the extent to which biological pleiotropy impacts phenotypes within maize through GWAS summary statistics reanalyzed from previously published metabolite, field, and expression phenotypes across the Nested Association Mapping population and Goodman Association Panel. Through phenotypic saturation of 120,597 traits, we obtain over 480 million significant quantitative trait nucleotides. We estimate that only 1.56-32.3% of intervals show some degree of pleiotropy. We then assessed the relationship between pleiotropy and various biological features such as gene expression, chromatin accessibility, sequence conservation, and enrichment for gene ontology terms. We find very little relationship between pleiotropy and these variables when compared to permuted pleiotropy. We hypothesize that biological pleiotropy of common alleles is not widespread in maize and is highly impacted by nuisance terms such as population structure and linkage disequilibrium. Natural selection on large standing natural variation in maize populations may target wide- and large-effect variants, leaving the prevalence of detectable pleiotropy relatively low. Author SummaryThe genetic basis of complex traits has been thought to exhibit pleiotropy, which is the notion that a single locus can control two or more unrelated traits. Widespread reports in the human disease literature show genomic signatures of pleiotropic loci across many traits. However, little is known about the prevalence and behavior of pleiotropy in maize across a large number of phenotypes. Using association mapping of common alleles in over one hundred thousand traits, we determine how pleiotropic each region was and use these quantitative scores to functionally characterize each region of the genome. Our results show little evidence that pleiotropy is a common phenomenon in maize. We observed that maize does not exhibit the same pleiotropic characteristics as human diseases in terms of prevalence, gene expression, chromatin accessibility, or sequence conservation. Rather than pervasive pleiotropy, we hypothesize that strong selection on large and wide effect loci and the need for trait independence at the gene level keep the prevalence of pleiotropy low, thus, allowing for the adaptation of maize varieties to novel environments and conditions.

plant biology↗

The Practical Haplotype Graph, a platform for storing and using pangenomes for imputation

MotivationPangenomes provide novel insights for population and quantitative genetics, genomics, and breeding not available from studying a single reference genome. Instead, a species is better represented by a pangenome or collection of genomes. Unfortunately, managing and using pangenomes for genomically diverse species is computationally and practically challenging. We developed a trellis graph representation anchored to the reference genome that represents most pangenomes well and can be used to impute complete genomes from low density sequence or variant data. ResultsThe Practical Haplotype Graph (PHG) is a pangenome pipeline, database (PostGRES & SQLite), data model (Java, Kotlin, or R), and Breeding API (BrAPI) web service. The PHG has already been able to accurately represent diversity in four major crops including maize, one of the most genomically diverse species, with up to 1000-fold data compression. Using simulated data, we show that, at even 0.1X coverage, with appropriate reads and sequence alignment, imputation results in extremely accurate haplotype reconstruction. The PHG is a platform and environment for the understanding and application of genomic diversity. AvailabilityAll resources listed here are freely available. The PHG Docker used to generate the simulation results is https://hub.docker.com/ as maizegenetics/phg:0.0.27. PHG source code is at https://bitbucket.org/bucklerlab/practicalhaplotypegraph/src/master/. The code used for the analysis of simulated data is at https://bitbucket.org/bucklerlab/phg-manuscript/src/master/. The PHG database of NAM parent haplotypes is in the CyVerse data store (https://de.cyverse.org/de/) and named /iplant/home/shared/panzea/panGenome/PHG_db_maize/phg_v5Assemblies_20200608.db. Contactpjb39@cornell.edu

bioinformatics↗

Variation in upstream open reading frames contributes to allelic diversity in protein abundance

The 5 untranslated region (UTR) sequence of eukaryotic mRNAs may contain upstream open reading frames (uORFs), which can regulate translation of the main open reading frame (mORF). The current model of translational regulation by uORFs posits that when a ribosome scans an mRNA and encounters a uORF, translation of that uORF can prevent ribosomes from reaching the mORF and cause decreased mORF translation. In this study, we first observed that rare variants in the 5 UTR dysregulate protein abundance. Upon further investigation, we found that rare variants near the start codon of uORFs can repress or derepress mORF translation, causing allelic changes in protein abundance. This finding holds for common variants as well, and common variants that modify uORF start codons also contribute disproportionately to metabolic and whole-plant phenotypes, suggesting that translational regulation by uORFs serves an adaptive function. These results provide evidence for the mechanisms by which natural sequence variation modulates gene expression, and ultimately, phenotype.

genomics↗

Machine learning enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions

Sorghum is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is also studied as a feedstock for biofuel and forage. Mechanistic modelling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping for discovery of genotype to phenotype associations remain bottlenecks in efforts to understand the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a novel machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were then the subject of genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) across 869 field-grown biomass sorghum accessions. SD was correlated with plant height and biomass production. Plasticity in SD and SLA were interrelated with each other, and productivity, across wet versus dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population supported identification of associations between DNA sequence variation, or RNA transcript abundance, and trait variation. 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose orthologs in Arabidopsis have functions related to stomatal or leaf development and leaf gas exchange. These advances in methodology and knowledge will aid efforts to improve the WUE of C4 crops.

plant biology↗

rTASSEL: an R interface to TASSEL for association mapping of complex traits

SummaryThe need for efficient tools and applications for analyzing genomic diversity is essential for any genetics research program. One such tool, TASSEL (Trait Analysis by aSSociation, Evolution and Linkage), provides many core methods for genomic analyses. Despite its efficiency, TASSEL has limited means to use scripting languages for reproducible research and interacting with other analytical tools. Here we present an R package rTASSEL, a front-end to connect to a variety of highly used TASSEL methods and analytical tools. The goal of this package is to create a unified scripting workflow that exploits the analytical prowess of TASSEL in conjunction with Rs popular data handling and parsing capabilities without ever having the user to switch between these two environments. By implementing this workflow, we can achieve performances ranging from approximately 2 to 20 times faster than other widely used R packages for various functionalities. Availability and implementationrTASSEL is implemented in R using core TASSEL methods written in Java. The source code for rTASSEL can be found at https://bitbucket.org/bucklerlab/rtassel/src/master/. The source code for TASSEL can be found at https://bitbucket.org/tasseladmin/tassel-5-source/src/master/. Supplemental informationThe rTASSEL user manual and tutorials are freely available at https://maize-genetics.github.io/rTASSEL/. Supplemental material for this manuscript regarding performance metrics can be found in the attached file.

bioinformatics↗

Mechanical control of morphogenesis robustness

Epithelial sheets undergo highly reproducible remodeling to shape organs. This stereotyped morphogenesis depends on a well-defined sequence of events leading to the regionalized expression of developmental patterning genes that finally triggers downstream mechanical forces to drive tissue remodeling at a pre-defined position. However, how tissue mechanics controls morphogenetic robustness when challenged by intrinsic perturbations in close proximity has never been addressed. Here, we show that a bias in force propagation ensures stereotyped morphogenesis despite the presence of mechanical noise in the environment. We found that knockdown of the Arp2/3 complex member Arpc5 specifically affects fold directionality without altering neither the developmental nor the force generation patterns. By combining in silico modeling, biophysical and ad hoc genetic tools, our data reveal that junctional Myosin II planar polarity favors long-range force channeling and ensures folding robustness, avoiding force scattering and thus isolating the fold domain from surrounding mechanical perturbations.

developmental biology↗

Physical and functional cell-matrix uncoupling in a developing tissue under tension

Tissue mechanics play a crucial role in organ development. It relies on cells and extracellular matrix (ECM) mechanical properties, but also on their reciprocal interaction. The relative physical contribution of cells and ECM to morphogenesis is poorly understood. Here, we dissected the mechanics of the envelope of the Drosophila developing leg, an epithelium submitted to a number of mechanical stresses: first stretched, it is then torn apart and withdrawn to free the leg. During stretching, we found that mechanical tension is entirely borne by the ECM at first, then by the cellular monolayer as soon as they detach themselves from one another. Then, each envelope layer is removed by an independent mechanism: while ECM withdraws following local proteolysis, cellular monolayer withdrawal is independent of ECM degradation and driven by an autonomous myosin-II-dependent contraction. These results reveal a physical and functional cell-matrix uncoupling that could timely control tissue dynamics during development.

cell biology↗

IRIS-DGE: An integrated RNA-seq data analysis and interpretation system for differential gene expression

MotivationNext-Generation Sequencing has made available much more large-scale genomic and transcriptomic data. Studies with RNA-sequencing (RNA-seq) data typically involve generation of gene expression profiles that can be further analyzed, many times involving differential gene expression (DGE). This process enables comparison across samples of two or more factor levels. A recurring issue with DGE analyses is the complicated nature of the comparisons to be made, in which a variety of factor combinations, pairwise comparisons, and main or blocked main effects need to be tested.\n\nResultsHere we present a tool called IRIS-DGE, which is a server-based DGE analysis tool developed using Shiny. It provides a straightforward, user-friendly platform for performing comprehensive DGE analysis, and crucial analyses that help design hypotheses and to determine key genomic features. IRIS-DGE integrates the three most commonly used R-based DGE tools to determine differentially expressed genes (DEGs) and includes numerous methods for performing preliminary analysis on user-provided gene expression information. Additionally, this tool integrates a variety of visualizations, in a highly interactive manner, for improved interpretation of preliminary and DGE analyses.\n\nAvailabilityIRIS-DGE is freely available at http://bmbl.sdstate.edu/IRIS/.\n\nContactqin.ma@sdstate.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

ViDGER: An R package for integrative interpretation of differential gene expression results of RNA-seq data

Differential gene expression (DGE) is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes (DEGs) across two or more conditions. Interpretation of the DGE results can be non-intuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we present an R package, ViDGER (Visualization of Differential Gene Expression Results using R), which contains nine functions that generate information-rich visualizations for the interpretation of DGE results from three widely-used tools, Cuffdiff, DESeq2, and edgeR.

bioinformatics↗