Meiotic recombination is the most important source of genetic variation in higher eukaryotes. It is initiated by formation of double-strand breaks (DSBs) in chromosomal DNA in early meiotic prophase. The DSBs are subsequently repaired, resulting in crossovers (COs) and noncrossovers (NCOs). Recombination events are not distributed evenly along chromosomes but cluster at recombination hotspots. How specific sites become hotspots is poorly understood. Studies in yeast and mammals linked initiation of meiotic recombination to active chromatin features present upstream from genes, such as absence of nucleosomes and presence of trimethylation of lysine 4 in histone H3 (H3K4me3). Core recombination components are conserved among eukaryotes, but it is unclear whether this conservation results in universal characteristics of recombination landscapes shared by a wide range of species. To address this question, we mapped meiotic DSBs in maize, a higher eukaryote with a large genome that is rich in repetitive DNA. We found DSBs in maize to be frequent in all chromosome regions, including sites lacking COs, such as centromeres and pericentromeric regions. Furthermore, most DSBs are formed in repetitive DNA, predominantly retrotransposons, and only one-quarter of DSB hotspots are near genes. Genic and nongenic hotspots differ in several characteristics, and only genic DSBs contribute to crossover formation. Maize hotspots overlap regions of low nucleosome occupancy but show only limited association with H3K4me3 sites. Overall, maize DSB hotspots exhibit distribution patterns and characteristics not reported previously in other species. Understanding recombination patterns in maize will shed light on mechanisms affecting dynamics of the plant genome.

With the recent advances in genomics and sequencing technologies, databases of transcriptomes representing many cellular processes have been assembled. Meiotic transcriptomes in plants have been studied in Arabidopsis thaliana, rice (Oryza sativa), wheat (Triticum aestivum), petunia (Petunia hybrida), sunflower (Helianthus annuus), and maize (Zea mays). Studies in all organisms, but particularly in plants, indicate that a very large number of genes are expressed during meiosis, though relatively few of them seem to be required for the completion of meiosis. In this review, we focus on gene expression at the RNA level and analyze the meiotic transcriptome datasets and explore expression patterns of known meiotic genes to elucidate how gene expression could be regulated during meiosis. We also discuss mechanisms, such as chromatin organization and non-coding RNAs that might be involved in the regulation of meiotic transcription patterns.

Distribution of meiotic recombination events in plants has been associated with local chromatin and DNA characteristics, chromosome landmark proximity, and other features. However, relative importance of these characteristics is unclear and it is unknown if they are sufficient to unambiguously determine recombination landscape. Here, we analyzed over 40 DNA sequence, chromatin, and chromosome location features of maize and Arabidopsis recombination sites using machine learning. We discovered that a combination of just three features, CG methylation, CHG methylation, and nucleosome occupancy, enabled identification of exact crossover site with 90% accuracy. These results imply redundancy of most recombination site characteristics. Recombination takes place in a small fraction of the genome with chromatin features distinct from those of genome at large. Surprisingly, crossover sites show elevated heterochromatin histone marks despite low DNA methylation. Crossover site features show broad evolutionary conservation, which will enable creating genetic maps in species where conventional mapping is unfeasible.

Plant breeding relies on crossing-over to create novel combinations of alleles needed to confer increased productivity and other desired traits in new varieties. However, crossover (CO) events are rare, as usually only one or two of them occur per chromosome in each generation. In addition, COs are not distributed evenly along chromosomes. In plants with large genomes, which includes most crops, COs are predominantly formed close to chromosome ends, and there are few COs in the large chromosome swaths around centromeres. This situation has created interest in engineering CO landscape to improve breeding efficiency. Methods have been developed to boost COs globally by altering expression of anti-recombination genes and increase CO rates in certain chromosome parts by changing DNA methylation patterns. In addition, progress is being made to devise methods to target COs to specific chromosome sites. We review these approaches and examine using simulations whether they indeed have the capacity to improve efficiency of breeding programs. We found that the current methods to alter CO landscape can produce enough benefits for breeding programs to be attractive. They can increase genetic gain in recurrent selection and significantly decrease linkage drag around donor loci in schemes to introgress a trait from unimproved germplasm to an elite line. Methods to target COs to specific genome sites were also found to provide advantage when introgressing a chromosome segment harboring a desirable quantitative trait loci. We recommend avenues for future research to facilitate implementation of these methods in breeding programs.

AmbIGeM is a technological solution to prevent in-patient falls in patients aged >65. It has been evaluated in a 100-week stepped wedge pragmatic design in two geriatric evaluation and management (GEM) wards and a general medical ward in two Australian hospitals (Visvanathan, Ranasinghe, Wilson et al., Injury Prevention, 2017,0:1). Evaluation of acceptability of the AmbIGeM system from the perspectives of patients and staff who experienced it is reported here. 30 patients completed a 24-item survey, 27 patients were interviewed, 22 staff participated in 3 focus groups and 51 staff completed a 39-item survey. Survey data were descriptively analysed, and focus group and interview data were thematically analysed. In patient surveys, patients were overall strongly positive, with means 8+ (on 11-point scale) on most items. In patient interviews, the AmbIGeM system was considered a good idea to prevent falls. Most patients thought the singlets comfortable and had no concerns for their privacy nor impact on normal activity. Patients and families felt reassured, although sometimes they misunderstood the purpose of AmbIGeM. In staff focus groups, staff perceived AmbIGeM beneficial in that it can detect and alert movement in patients who require supervision. In both GEM wards, AmbIGeM was considered particularly beneficial,practical and valuable to use on night shift. Factors such as perceived technical limitations (false and delayed alerts) and felt staff burden impacted on acceptability. In staff surveys, 56% agreed/strongly agreed that AmbIGeM has the capability to prevent falls while 16% disagreed/strongly disagreed, 62% thought AmbIGeM would be more user friendly if it was consistently accurate and 76% believed that AmbIGeM takes a moderate/lot of extra work. Conclusion AmbIGeM is largely acceptable to patients and requires further refinement for staff. Feedback is valuable to further refine the system.