Recombination data for the repeat-based holocentromere-harbouring genome of R. breviuscula
Data files
Apr 02, 2024 version files 140.83 GB
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ChIP-peaks.zip
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ChIPseq_raw_reads.tar.gz
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F1_WGS.tar.gz
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pollen_scRNA_R1.fastq.gz
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pollen_scRNA_R2.fastq.gz
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README.md
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rhyBreHap1_functAnno.gff3.gz
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rhyBreHap1.fasta.gz
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rhyBreHap2_functAnno.gff3.gz
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rhyBreHap2.fasta.gz
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Rhync_breviuscula_Methyl-seq.tar.gz
Abstract
Centromeres strongly affect (epi)genomic architecture and meiotic recombination dynamics influencing the overall distribution and frequency of crossovers. Here, we studied how recombination is regulated and distributed in the holocentric plant Rhynchospora breviuscula, a species lacking localised centromeres. Combining immunocytochemistry, chromatin analysis, and high-throughput single-pollen sequencing, we discovered that crossover frequency is distally biased, in sharp contrast with the diffused distribution of hundreds of centromeric units and (epi)genomic features. Remarkably, we found that crossovers were abolished inside centromeric units but not in their proximity indicating the absence of a canonical centromere effect. We further show that telomere-led synapsis of homologs is the feature that best explains the observed recombination landscape. Our results hint at the primary influence of mechanistic features of meiotic pairing and synapsis rather than (epi)genomic features and centromere organisation in determining the distally-biased crossover distribution in R. breviuscula. While centromeres and (epi)genetic properties only affect crossover positioning locally.
README: Recombination data for the repeat-based holocentromere-harbouring genome of R. breviuscula
This dataset provides complete raw sequencing data that is required for recombination analysis of R. breviuscula. Please refer to the following paper for more details and cite it when you use this dataset for publications:
Castellani M, Zhang M, Thangavel G, Mata-Sucre Y, Lux T, A. Campoy J. A., Marek M, Huettel B, Sun H, Mayer K. F. X., Schneeberger K & Marques A. (2023). Meiotic recombination dynamics in plants with repeat-based holocentromeres sheds light on the primary drivers of crossover patterning.
Dataset
- Phased genome assemblies of two haplotypes of *R. breviuscula*
rhyBreHap1.fasta.gz
rhyBreHap2.fasta.gz
- Annotation of phased genome assemblies
rhyBreHap1_functAnno.gff3.gz
rhyBreHap2_functAnno.gff3.gz
- Single-cell RNA sequences from pollen nuclei by 10X Genomics
a4984_merged_R1.fastq.gz
a4984_merged_R1.fastq.gz
Please note that the scRNA-seq data were sequenced from mixed R. breviuscula and R. tenuis pollen nuclei. Therefore, you need to separate the pollen of two individuals before any further analysis. To do this, you can refer to the online methods of the above paper and our github docbumentation. - Whole-genome DNA short reads of 63 selfed F1 offspring by Illumina paired-end sequencing
F1_WGS.tar.gz
WGS DNA reads of all 63 F1 individuals are in this compressed folder. Sample IDs are 5445_A, 5445_B, 5445_C, 5445_D, 5445_E, 5621_A, 5621_B, 5621_C, 5621_E, 5621_F, 5621_G, 5621_H, 5621_I, 5621_J, 5621_K, 5621_L, 5621_M, 5621_N, 5621_O, 5621_P, 5621_Q, 5621_R, 5621_S, 5621_T, 5621_U, 5621_V, 5621_W, 5621_X, 5621_Y, 5844_A, 5844_B, 5844_C, 5844_D, 5844_E, 5844_F, 5844_G, 5844_H, 5844_I, 5844_J, 5844_K, 5844_L, 5844_M, 5844_N, 5844_O, 5844_P, 5844_Q, 5844_R, 5844_S, 5844_T, 5844_U, 5844_V, 5844_W, 5844_X, 5844_Y, 5844_Z, 5844_AA, 5844_AB, 5844_AC, 5844_AD, 5844_AE, 5844_AF, 5844_AG, 5844_AH. Each sample was sequenced under one single library, so you can merge the reads with the same sample names. - ChIPseq data
ChIPseq_raw_reads.tar.gz
5165_A CENH3 rep1 rabbit 5165_B CENH3 rep2 rabbit 5165_C H3K4me3 rep1 rabbit 5165_D H4K4me3 rep2 rabbit 5165_E H3K9me2 rep1 mouse 5165_F H3K9me2 rep2 mouse 5165_G Rabbit-IgG rep1 rabbit 5165_H Rabbit-IgG input rep2 rabbit 5165_I input chromatin rep1 5165_J input chromatin rep2 5165_M Mouse-IgG rep1 mouse 5165_N Mouse-IgG rep2 mouse 5165_O H3K27me3 rep1 rabbit 5165_P H3K27me3 rep2 rabbit Each sample was sequenced under one single library, so you can merge the reads with the same sample names.ChIP_peaks.zip
- Methyl-seq data
Rhync_breviuscula_Methyl-seq.tar.gz
Each sample was sequenced under one single library, so you can merge the reads with the same sample names.
Complete CO detection pipeline by pollen scRNA-seq data can be found on this github page.