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Vitte, C.

Publications and source records attributed to Vitte, C..

5 recordsLinked to original sources

How to be dispensable: genomic and transcriptomic determinants in maize genes

BackgroundPlant genomes harbour a substantial proportion of dispensable genes - present only in a subset of individuals - that differ from ubiquitously shared core genes in multiple genomic and expression features. While these differences have been repeatedly documented, the factors shaping gene dispensability remain poorly understood. ResultsWe assembled a pan-gene set from eight maize inbred lines from American and European germplasms, together with their transcriptomic profile across 22 tissues/conditions, revealing the genomic and transcriptomic determinants of maize gene dispensability. Multivariate analysis demonstrates that gene expression level and purifying selection - rather than gene size - are the primary factors distinguishing core from dispensable genes. Dispensable genes overlap Helitrons at 4.6 times the rate of core genes, implicating Helitron-mediated gene capture as a major mechanism of dispensable gene formation. Classifying genes into stably expressed, variably expressed, and on-off categories shows that all three classes contain dispensable genes, though in different proportions than for core genes. Contrary to previous assumptions, we show that dispensable genes can participate in basal biological functions just as core genes, and that gene duplication likely provides only a partial mechanism for functional complementation of accessory genes absence. ConclusionsOur results provide novel insights into the molecular and evolutionary factors distinguishing core from dispensable genes and into the biological mechanisms shaping gene dispensability in maize, and demonstrate that classifying genes by transcriptional patterns provides a powerful framework for understanding the biological functions and evolutionary dynamics of both core and dispensable genes.

plant biology↗

Alternative silencing states of Transposable Elements in Arabidopsis

The DNA methylation/H3K9me2 and Polycomb-group proteins (PcG)-H3K27me3 pathways have long been considered mutually exclusive and specific to TEs and genes, respectively. However, H3K27me3 can be recruited to many TEs in the absence of DNA methylation machinery and sometimes also co-occur with DNA methylation. In this study, we show that TEs can also be solely targeted by H3K27me3 in wild-type Arabidopsis plants. These H3K27me3-marked TEs not only comprise degenerate relics but also seemingly intact copies that display the epigenetic features of responsive PcG target genes as well as an active H3K27me3 regulation. We also show that H3K27me3 can be deposited on newly inserted transgenic TE sequences in a TE-specific manner indicating that silencing is determined in cis. Finally, comparison of Arabidopsis natural accessions reveals the existence of a category of TEs - which we refer to as "bifrons" - that are marked by DNA methylation or H3K27me3 depending on the ecotype. This variation can be linked to intrinsic TE features and to trans- acting factors, and reveals a change in epigenetic status across TE lifespan. Our study sheds light on an alternative mode of TE silencing associated with H3K27me3 instead of DNA methylation in flowering plants. It also suggests dynamic switching between the two epigenetic marks at the species level, a new paradigm that might extend to other multicellular eukaryotes.

molecular biology↗

Simultaneous Profiling of Chromatin Accessibility and DNA Methylation in Complete Plant Genomes Using Long-Read Sequencing

Epigenetic regulations, including chromatin accessibility, nucleosome positioning, and DNA methylation intricately shape genome function. However, current chromatin profiling techniques relying on short-read sequencing technologies fail to characterise highly repetitive genomic regions and cannot detect multiple chromatin features simultaneously. Here, we performed Simultaneous Accessibility and DNA Methylation Sequencing (SAM-seq) of purified plant nuclei. Thanks to the use of long-read nanopore sequencing, SAM-seq enables high-resolution profiling of m6A-tagged chromatin accessibility together with endogenous cytosine methylation in plants. Analysis of naked genomic DNA revealed significant sequence preference biases of m6A-MTases, controllable through a normalisation step. By applying SAM-seq to Arabidopsis and maize nuclei we obtained fine-grained accessibility and DNA methylation landscapes genome-wide. We uncovered crosstalk between chromatin accessibility and DNA methylation within nucleosomes of genes, TEs, and centromeric repeats. SAM-seq also detects DNA footprints over cis-regulatory regions. Furthermore, using the single-molecule information provided by SAM-seq we identified extensive cellular heterogeneity at chromatin domains with antagonistic chromatin marks, suggesting that bivalency reflects cell-specific regulations. SAM-seq is a powerful approach to simultaneously study multiple epigenetic features over unique and repetitive sequences, opening new opportunities for the investigation of epigenetic mechanisms.

genomics↗

Identification of key tissue-specific, biological processes by integrating enhancer information in maize gene regulatory networks

Enhancers are important regulators of gene expression during numerous crucial processes including tissue differentiation across development. In plants, their recent molecular characterization revealed their capacity to activate the expression of several target genes through the binding of transcription factors. Nevertheless, identifying these target genes at a genome-wide level remains a challenge, in particular in species with large genomes, where enhancers and target genes can be hundreds of kilobases away. Therefore, the contribution of enhancers to regulatory network is still poorly understood in plants. In this study, we investigate the enhancer-driven regulatory network of two maize tissues at different stages: leaves at seedling stage and husks (bracts) at flowering. Using a systems biology approach, we integrate genomic, epigenomic and transcriptomic data to model the regulatory relationship between transcription factors and their potential target genes. We identify regulatory modules specific to husk and V2-IST, and show that they are involved in distinct functions related to the biology of each tissue. We evidence enhancers exhibiting binding sites for two distinct transcription factor families (DOF and AP2/ERF) that drive the tissue-specificity of gene expression in seedling immature leaf and husk. Analysis of the corresponding enhancer sequences reveals that two different transposable element families (TIR transposon Mutator and MITE Pif/Harbinger) have shaped the regulatory network in each tissue, and that MITEs have provided new transcription factor binding sites that are involved in husk tissue-specificity.Significance Enhancers play a major role in regulating tissue-specific gene expression in higher eukaryotes, including angiosperms. While molecular characterization of enhancers has improved over the past years, identifying their target genes at the genome-wide scale remains challenging. Here, we integrate genomic, epigenomic and transcriptomic data to decipher the tissue-specific gene regulatory network controlled by enhancers at two different stages of maize leaf development. Using a systems biology approach, we identify transcription factor families regulating gene tissue-specific expression in husk and seedling leaves, and characterize the enhancers likely to be involved. We show that a large part of maize enhancers is derived from transposable elements, which can provide novel transcription factor binding sites crucial to the regulation of tissue-specific biological functions.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

High throughput genotyping of structural variations in a complex plant genome using an original Affymetrix(R) Axiom(R) array

BackgroundInsertions/deletions (InDels) and more specifically presence/absence variations (PAVs) are pervasive in several species and have strong functional and phenotypic effect by removing or drastically modifying genes. Genotyping of such variants on large panels remains poorly addressed, while necessary for approaches such as association mapping or genomic selection.\n\nResultsWe have developed, as a proof of concept, a new high-throughput and affordable approach to genotype InDels. We first identified 141,000 InDels by aligning reads from the B73 line against the genome of three temperate maize inbred lines (F2, PH207, and C103) and reciprocally. Next, we designed an Affymetrix(R) Axiom(R) array to target these InDels, with a combination of probes selected at breakpoint sites (13%) or within the InDel sequence, either at polymorphic (25%) or non-polymorphic sites (63%) sites. The final array design is composed of 662,772 probes and targets 105,927 InDels, including PAVs ranging from 35bp to 129kbp. After Affymetrix(R) quality control, we successfully genotyped 86,648 polymorphic InDels (82% of all InDels interrogated by the array) on 445 maize DNA samples with 422,369 probes. Genotyping InDels using this approach produced a highly reliable dataset, with low genotyping error (~3%), high call rate (~98%), and high reproducibility (>95%). This reliability can be further increased by combining genotyping of several probes calling the same InDels (<0.1% error rate and >99.9% of call rate for 5 probes). This \"proof of concept\" tool was used to estimate the kinship matrix between 362 maize lines with 57,824 polymorphic InDels. This InDels kinship matrix was highly correlated with kinship estimated using SNPs from Illumina 50K SNP arrays.\n\nConclusionsWe efficiently genotyped thousands of small to large InDels on a sizeable number of individuals using a new Affymetrix(R) Axiom(R) array. This powerful approach opens the way to studying the contribution of InDels to trait variation and heterosis in maize. The approach is easily extendable to other species and should contribute to decipher the biological impact of InDels at a larger scale.

genomics↗