Integrative epigenomic mapping defines four main chromatin states in ArabidopsisThis first comprehensive view of the Arabidopsis epigenome reveals that it is organized into four main chromatin types based on the integrative mapping of a broad set of 11 histone marks and DNA methylation in seedlings.

In most species, crossovers (COs) are essential for the accurate segregation of homologous chromosomes at the first meiotic division. Their number and location are tightly regulated. Here, we report a detailed, genome-wide characterization of the rate and localization of COs in Arabidopsis thaliana, in male and female meiosis. We observed dramatic differences between male and female meiosis which included: (i) genetic map length; 575 cM versus 332 cM respectively; (ii) CO distribution patterns: male CO rates were very high at both ends of each chromosome, whereas female CO rates were very low; (iii) correlations between CO rates and various chromosome features: female CO rates correlated strongly and negatively with GC content and gene density but positively with transposable elements (TEs) density, whereas male CO rates correlated positively with the CpG ratio. However, except for CpG, the correlations could be explained by the unequal repartition of these sequences along the Arabidopsis chromosome. For both male and female meiosis, the number of COs per chromosome correlates with chromosome size expressed either in base pairs or as synaptonemal complex length. Finally, we show that interference modulates the CO distribution both in male and female meiosis.

The vast majority of meiotic recombination events (crossovers (COs) and non-crossovers (NCOs)) cluster in narrow hotspots surrounded by large regions devoid of recombinational activity. Here, using a new molecular approach in plants, called “pollen-typing”, we detected and characterized hundreds of CO and NCO molecules in two different hotspot regions in Arabidopsis thaliana. This analysis revealed that COs are concentrated in regions of a few kilobases where their rates reach up to 50 times the genome average. The hotspots themselves tend to cluster in regions less than 8 kilobases in size with overlapping CO distribution. Non-crossover (NCO) events also occurred in the two hotspots but at very different levels (local CO/NCO ratios of 1/1 and 30/1) and their track lengths were quite small (a few hundred base pairs). We also showed that the ZMM protein MSH4 plays a role in CO formation and somewhat unexpectedly we also found that it is involved in the generation of NCOs but with a different level of effect. Finally, factors acting in cis and in trans appear to shape the rate and distribution of COs at meiotic recombination hotspots.

BackgroundMetatranscriptomics is rapidly expanding our knowledge of gene expression patterns and pathway dynamics in natural microbial communities. However, to cope with the challenges of environmental sampling, various rRNA removal and cDNA synthesis methods have been applied in published microbial metatranscriptomic studies, making comparisons arduous. Whereas efficiency and biases introduced by rRNA removal methods have been relatively well explored, the impact of cDNA synthesis and library preparation on transcript abundance remains poorly characterized. The evaluation of potential biases introduced at this step is challenging for metatranscriptomic samples, where data analyses are complex, for example because of the lack of reference genomes.ResultsHerein, we tested four cDNA synthesis and Illumina library preparation protocols on a simplified mixture of total RNA extracted from four bacterial species. In parallel, RNA from each microbe was tested individually. cDNA synthesis was performed on rRNA depleted samples using the TruSeq Stranded Total RNA Library Preparation, the SMARTer Stranded RNA-Seq, or the Ovation RNA-Seq V2 System. A fourth experiment was made directly from total RNA using the Encore Complete Prokaryotic RNA-Seq. The obtained sequencing data were analyzed for: library complexity and reproducibility; rRNA removal efficiency and bias; the number of genes detected; coverage uniformity; and the impact of protocols on expression biases. Significant variations, especially in organism representation and gene expression patterns, were observed among the four methods. TruSeq generally performed best, but is limited by its requirement of hundreds of nanograms of total RNA. The SMARTer method appears the best solution for smaller amounts of input RNA. For very low amounts of RNA, the Ovation System provides the only option; however, the observed biases emphasized its limitations for quantitative analyses.ConclusionscDNA and library preparation methods may affect the outcome and interpretation of metatranscriptomic data. The most appropriate method should be chosen based on the available quantity of input RNA and the quantitative or non-quantitative objectives of the study. When low amounts of RNA are available, as in most metatranscriptomic studies, the SMARTer method seems to be the best compromise to obtain reliable results. This study emphasized the difficulty in comparing metatranscriptomic studies performed using different methods.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-912) contains supplementary material, which is available to authorized users.

In most organisms that have been studied, crossovers formed during meiosis exhibit interference: nearby crossovers are rare. Here we provide an in-depth study of crossover interference in Arabidopsis thaliana, examining crossovers genome-wide in .1500 backcrosses for both male and female meiosis. This unique data set allows us to take a two-pathway modeling approach based on superposing a fraction p of noninterfering crossovers and a fraction (1 2 p) of interfering crossovers generated using the gamma model characterized by its interference strength nu. Within this framework, we fit the two-pathway model to the data and compare crossover interference strength between chromosomes and then along chromosomes. We find that the interfering pathway has markedly higher interference strength nu in female than in male meiosis and also that male meiosis has a higher proportion p of noninterfering crossovers. Furthermore, we test for possible intrachromosomal variations of nu and p. Our conclusion is that there are clear differences between left and right arms as well as between central and peripheral regions. Finally, statistical tests unveil a genome-wide picture of small-scale heterogeneities, pointing to the existence of hot regions in the genome where crossovers form preferentially without interference. SEXUALLY reproducing organisms undergo meiosis, thereby producing gametes having a level of ploidy equal to half that of the parental cells. This reduction in ploidy emerges from a complex and tightly controlled sequence of events. In most organisms, prophase I of meiosis begins by the active formation of double-strand breaks (DSBs) mediated by Spo11, a topoisomerase-like transesterase (Keeney et al. 1997). Then homologous chromosomes align and pair as the DSBs are repaired, typically using a homolog as template. Such DSB repairs can lead to either a crossover (CO), a reciprocal exchange of large chromosomal fragments between homologs), or to a noncrossover (NCO), a nonreciprocal exchange of small chromosomal segments between homologs, detected through associated gene conversions (Bishop and Zickler 2004)). COs mediate intrachromosomal rearrangement of parental alleles, giving rise to novel haplotypes in the gametes and thus driving genetic diversity. They also provide a physical connection between the homologs, holding them in a stable pair (bivalent) and allowing their correct segregation during anaphase I (Page and Hawley 2004;Jones and Franklin 2006). Studies in several plants and animals have shown that the average number of COs in meiosis may vary between male and female meiosis (see review by Lenormand and Dutheil 2005), but there is no general rule that governs the direction or degree of CO number variation. Similarly, the distribution of COs along chromosomes can also differ when comparing male and female meiosis (Drouaud et al. 2007). Such distributions are generally nonuniform: some portions of the physical chromosome seem more likely to recombine while others hardly ever do (e.g., close to the cent...

Meiotic recombination is essential for proper segregation of homologous chromosomes and thus for formation of viable gametes. Recombination generates either crossovers (COs), which are reciprocal exchanges between chromosome segments, or gene conversion not associated with crossovers (NCOs). Both kinds of events occur in narrow regions (less than 10 kb) called hotspots, which are distributed along chromosomes. While NCOs may represent a large fraction of meiotic recombination events in plants, as in many other higher eukaryotes, they have been poorly characterized due to the technical difficulty of detecting them. Here, we present a powerful approach, based on allele-specific PCR amplification of single molecules from pollen genomic DNA, allowing detection, quantification and characterization of NCO events arising at low frequencies at recombination hotspots.

A Correction to this paper has been published: https://doi.org/10.1038/s42003-021-01894-9

Accurate decoding of nucleic acid variation is critical to understand the complexity and regulation of genome function. Here we use a single-molecule magnetic tweezer (MT) platform to identify sequence variation and map a range of important epigenetic base modifications with high sensitivity, specificity, and precision in the same single molecules of DNA or RNA. We have also developed a highly specific amplification-free CRISPR-Cas enrichment strategy to isolate genomic regions from native DNA. We demonstrate enrichment of DNA from both E. coli and the FMR1 5’UTR coming from cells derived from a Fragile X carrier. From these kilobase-length enriched molecules we could characterize the differential levels of adenine and cytosine base modifications on E. coli, and the repeat expansion length and methylation status of FMR1. Together these results demonstrate that our platform can detect a variety of genetic, epigenetic, and base modification changes concomitantly within the same single molecules.