Biology subjects

Rabanal, F.

Publications and source records attributed to Rabanal, F..

5 recordsLinked to original sources

bioRxiv2025

Long-read detection of transposable element mobilization in the soma of hypomethylated Arabidopsis thaliana individuals

BackgroundBecause transposable elements (TEs) can cause heritable genetic changes, past work on TE mobility in Arabidopsis thaliana has mostly focused on new TE insertions in the germline of hypomethylated plants. It is, however, well-known that TEs can also be active in the soma, although the high-confidence detection of somatic events has been challenging. Here, we leveraged the high accuracy of PacBio HiFi long reads to evaluate the somatic mobility of TEs in individuals of an A. thaliana non-reference strain lacking activity of METHYLTRANSFERASE1 (MET1), a major component of the DNA methylation maintenance machinery. Most somatically mobile families coincided with those found in germline studies of hypomethylated genotypes, although the exact TE copies differed. We also discovered mobile elements that had been missed by standard TE annotation methods. Somatic TE activity was variable among individual plants, but also within TE families. Finally, our approach pointed to the possible involvement of alternative transposition as a cause for somatic hypermutability in a region that contains two closely spaced VANDAL21 elements. We conclude that long-read sequencing can reveal widespread TE transposition in the soma of A. thaliana hypomethylated mutants. Assessing somatic instead of germline mobilization is a fast and reliable method to investigate different aspects of TE mobility at the single plant level.

genomics↗

bioRxiv2024

Towards an unbiased characterization of genetic polymorphism

Our view of genetic polymorphism is shaped by methods that provide a limited and reference-biased picture. Long-read sequencing technologies, which are starting to provide nearly complete genome sequences for population samples, should solve the problem--except that characterizing and making sense of non-SNP variation is difficult even with perfect sequence data. Here we analyze 27 genomes of Arabidopsis thaliana in an attempt to address these issues, and illustrate what can be learned by analyzing whole-genome polymorphism data in an unbiased manner. Estimated genome sizes range from 135 to 155 Mb, with differences almost entirely due to centromeric and rDNA repeats that are difficult to assemble. The completely assembled chromosome arms comprise roughly 120 Mb in all accessions, but are full of structural variants, largely due to transposable elements. Even with only 27 accessions, a pan-genome coordinate system that includes the resulting variation ends up being [~] 70% larger than the size of any one genome. Our analysis reveals an incompletely annotated mobile-ome: we not only detect several novel TE families, but also find that existing TE annotation is a poor predictor of elements that have recently been active. In contrast to this, the genic portion, or "gene-ome", is highly conserved. By annotating each genome using accession-specific transcriptome data, we find that 13% of all (non-TE) genes are segregating in our 27 accessions, but most of these are transcriptionally silenced. Finally, we show that with short-read data we previously massively underestimated genetic variation of all kinds, including SNPs--mostly in regions where short reads could not be mapped reliably, but also where reads were mapped incorrectly. We demonstrate that SNP-calling errors can be biased by the choice of reference genome, and that RNA-seq and BS-seq results can be strongly affected by mapping reads only to a reference genome rather than to the genome of the assayed individual. In conclusion, while whole-genome polymorphism data pose tremendous analytical challenges, they also have the potential to revolutionize our understanding of genome evolution.

genomics↗

bioRxiv2023

Atlas of telomeric repeat diversity in Arabidopsis thaliana

Telomeric repeat arrays at the ends of chromosomes are highly dynamic but their repetitive nature and technological limitations have made it difficult to assess the variation in genome diversity surveys. Here we present a comprehensive characterization of the sequence variation immediately adjacent to the canonical telomeric repeat arrays at the very ends of chromosomes in 49 genetically diverse Arabidopsis thaliana accessions. We reveal several types of distinct telomeric repeat units and identify evolutionary processes such as local homogenization and higher-order repeat formation that shape diversity of chromosome ends. The identification of segmental duplications and at least one recombination event suggests a plausible history of telomerase-independent maintenance generation. By comparing largely isogenic samples, we are able to determine variant telomeric repeat number variation at both the germline and somatic levels. Analysis of haplotype structure uncovers chromosome end-specific as well as genetic group-specific patterns in telomeric repeat diversity and provides evidence for linkage disequilibrium between repeat arrays and their adjacent non-coding regions. Together, our findings illustrate the fine-scale telomeric repeat spectrum in A. thaliana, expanding our knowledge of the evolution of chromosome ends.

genomics↗

bioRxiv2017

Plant genes influence microbial hubs that shape beneficial leaf communities

Although complex interactions between hosts and microbial associates are increasingly well documented, we still know little about how and why hosts shape microbial communities in nature. In addition, host genetic effects on microbial communities vary widely depending on the environment, obscuring conclusions about which microbes are impacted and which plant functions are important. We characterized the leaf microbiota of 200 A. thaliana genotypes in eight field experiments and detected consistent host effects on specific, broadly distributed microbial OTUs. Host genetics disproportionately influenced hubs within the microbial communities, with their impact then percolating through the community, as evidenced by a decline in the heritability of particular OTUs with their distance to the nearest hub. By simultaneously measuring host performance, we found that host genetics associated with microbial hubs explained over 10% of the variation in lifetime seed production among host genotypes across sites and years. We successfully cultured one of these microbial hubs and demonstrated its growth-promoting effects on plants grown in sterile conditions. Finally, genome-wide association mapping identified many putatively causal genes with small effects on the relative abundance of microbial hubs across sites and years, and these genes were enriched for those involved in the synthesis of specialized metabolites, auxins and the immune system. Using untargeted metabolomics, we corroborate the consistent association of variation in specialized metabolites and microbial hubs across field sites. Together, our results reveal that host natural variation impacts the microbial communities in consistent ways across environments and that these effects contribute to fitness variation among host genotypes.

microbiology↗

bioRxiv2017

Verification of Arabidopsis stock collections using SNPmatch - an algorithm for genotyping high-plexed samples

Large-scale studies such as the Arabidopsis thaliana 1001 Genomes Project aim to understand genetic variation in populations and link it to phenotypic variation. Such studies require routine genotyping of stocks to avoid sample contamination and mix-ups. To genotype samples efficiently and economically, sequencing must be inexpensive and data processing simple. Here we present SNPmatch, a tool which identifies the most likely strain (inbred line, or \"accession\") from a SNP database. We tested the tool by performing low-coverage sequencing of over 2000 strains. SNPmatch could readily genotype samples correctly from 1-fold coverage sequencing data, and could also identify the parents of F1 or F2 individuals. SNPmatch can be run either on the command line or through AraGeno (https://arageno.gmi.oeaw.ac.at), a web interface that permits sample genotyping from a user-uploaded VCF or BED file.\n\nAvailability and implementation: https://github.com/Gregor-Mendel-Institute/SNPmatch.git

genomics↗