Biology subjects

Abbadi, A.

Publications and source records attributed to Abbadi, A..

4 recordsLinked to original sources

bioRxiv2025

Machine learning and multi-omic analysis reveal contrasting recombination landscape of A and C subgenomes of winter oilseed rape

Meiotic recombination is essential for generating genetic diversity, driving plant evolution, and enabling crop improvement, yet its uneven distribution across genomes constrains breeding efforts. Here, we investigated the multi-omic landmarks that shape the recombination landscape in Brassica napus by integrating epigenomic, genomic and transcriptomic data with recombination maps derived from large multi-parental rapeseed populations. Predictive machine-learning accurately predicted recombination rates and hotspot location using only feature information. Recombination was generally suppressed in centromeres and other repeat-rich, methylated regions and enriched in gene-dense, transcriptionally active domains. Proxies for chromatin configuration--such as DNA methylation, transposable elements or genes-- consistently achieved the highest predictive power with the random forest algorithm. We discovered distinct recombination landscape patterns between subgenomes, with crossovers clustering near subtelomeres in the A subgenome and more evenly spread across the C subgenome. Models trained on A-subgenome data outperformed those based on the C subgenome, although combining both subgenomes improved overall accuracy.

bioinformatics↗

bioRxiv2024

Graphical pangenomics-enabled characterisation of structural variant impact on gene expression in Brassica napus

Structural variants (SVs, eg. insertions and deletions) are genomic variations > 50 bp that are known to be associated with a range of crop traits, from yield to flowering behaviour and stress responses. Recently, pangenome graphs have emerged as a powerful framework for analysing genomic data by encoding population- or species-level diversity in one data structure. Pangenome graphs have the potential to serve as unbiased references for downstream applications, including SV genotyping and pan-transcriptomic analyses. In this work, we hypothesized that extensive variation affects transcript quantification and expression quantitative trait locus (eQTL) analysis when relying on a single reference, and that using pangenome graphs can mitigate reference sequence bias. We combined long and short read whole genome sequencing data with expression profiling of Brassica napus (oilseed rape) to assess the impact of SVs on gene expression regulation and explored the utility of pangenome graphs for eQTL analysis. We demonstrate that pangenome graphs provides a superior framework for eQTL analysis by eliminating single reference bias in gene expression quantification. Combined with the graph-based genotyping of SVs, we identified 240 eQTL-SVs found in close proximity of target loci. These SVs affect expression of genes related to important traits, are often not in linkage with SNPs and represent diversity unaccounted for in classical SNP-based analyses. This study highlights the multiple advantages of graph-based approaches in population-scale studies and provides novel insight into gene expression regulation in an important crop.

plant biology↗

bioRxiv2022

Direct access to millions of mutations by Whole Genome Sequencing of an oilseed rape mutant population

Induced mutations are an essential source of genetic variation in plant breeding. EMS mutagenesis has been frequently applied, and mutants have been detected by phenotypic or genotypic screening of large populations. In this study, a rapeseed M2 population was derived from M1 parent cultivar "Express" treated with EMS. Whole genomes were sequenced from fourfold (4x) pools of 1,988 M2 plants representing 497 M2 families. Detected mutations were not evenly distributed and displayed distinct patterns across the 19 chromosomes with lower mutation rates towards the ends. Mutation frequencies ranged from 32/Mb to 48/Mb. On average, 284,442 single nucleotide polymorphisms per M2 DNA pool were found resulting from EMS mutagenesis. 55% were C[->]T and G[->]A transitions, characteristic for EMS induced ( canonical) mutations, whereas the remaining SNPs were non-canonical transitions (15%) or transversions (30%). Additionally, we detected 88,725 high confidence insertions and deletions (InDels) per pool. On average, each M2 plant carried 39,120 canonical mutations, corresponding to a frequency of one mutation per 23.6 kb. Roughly 82% of such mutations were located either 5 kb upstream or downstream (~56%) of gene coding regions or within intergenic regions (26%). The remaining 18% were located within regions coding for genes. All mutations detected by whole-genome sequencing could be verified by comparison with known mutations. Furthermore, all sequences are accessible via the online tool "EMS Brassica" (http://www.emsbrassica.plantbreeding.uni-kiel.de/), which enables direct identification of mutations in any target sequence. The sequence resource described here will further add value for functional gene studies in rapeseed breeding.

genomics↗

bioRxiv2022

Reduced glucosinolate content in oilseed rape (Brassica napus L.) by random mutagenesis of BnMYB28 and BnCYP79F1 genes

The presence of anti-nutritive compounds like glucosinolates (GSLs) in the rapeseed meal severely restricts its utilization as animal feed. Therefore, reducing the GSL content to <18 {micro}mol/g dry weight in the seeds is a major breeding target. While candidate genes involved in the biosynthesis of GSLs have been described in rapeseed, comprehensive functional analyses are missing. By knocking out the aliphatic GSL biosynthesis genes BnMYB28 and BnCYP79F1 encoding an R2R3 MYB transcription factor and a cytochrome P450 enzyme, respectively, we aimed to reduce the seed GSL content in rapeseed. After expression analyses on single paralogs, we used an ethyl methanesulfonate (EMS) treated population of the inbred winter rapeseed Express617 to detect functional mutations in the two gene families. Our results provide the first functional analysis by knock-out for the two GSL biosynthesis genes in winter rapeseed. We demonstrate that independent knock-out mutants of the two genes possessed significantly reduced seed aliphatic GSLs, primarily progoitrin. Compared to the wildtype Express617 control plants (36.3 {micro}mol/g DW), progoitrin levels were decreased by 55.3% and 32.4% in functional mutants of BnMYB28 (16.20 {micro}mol/g DW) and BnCYP79F1 (24.5 {micro}mol/g DW), respectively. Our study provides a strong basis for breeding rapeseed with improved meal quality in the future.

plant biology↗