DOI: 10.5061/dryad.ttdz08m3k
title: Recombination data for the repeat-based holocentromere-harbouring genome of R. breviuscula

description: 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.
description: # 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](https://github.com/Raina-M/detectCO_by_scRNAseq).* *
 **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](https://github.com/Raina-M/detectCO_by_scRNAseq).