Mutation rates vary within genomes, but the causes of this remain unclear. As many prior inferences rely on methods that assume an absence of selection, potentially leading to artefactual results, we call mutation events directly using a parent-offspring sequencing strategy focusing on Arabidopsis and using rice and honey bee for replication. Here we show that mutation rates are higher in heterozygotes and in proximity to crossover events. A correlation between recombination rate and intraspecific diversity is in part owing to a higher mutation rate in domains of high recombination/diversity. Implicating diversity per se as a cause, we find an ∼3.5-fold higher mutation rate in heterozygotes than in homozygotes, with mutations occurring in closer proximity to heterozygous sites than expected by chance. In a genome that is a patchwork of heterozygous and homozygous domains, mutations occur disproportionately more often in the heterozygous domains. If segregating mutations predispose to a higher local mutation rate, clusters of genes dominantly under purifying selection (more commonly homozygous) and under balancing selection (more commonly heterozygous), might have low and high mutation rates, respectively. Our results are consistent with this, there being a ten times higher mutation rate in pathogen resistance genes, expected to be under positive or balancing selection. Consequently, we do not necessarily need to evoke extremely weak selection on the mutation rate to explain why mutational hot and cold spots might correspond to regions under positive/balancing and purifying selection, respectively.

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The evolutionary importance of meiosis may not solely be associated with allelic shuffling caused by crossing-over but also have to do with its more immediate effects such as gene conversion. Although estimates of the crossing-over rate are often well resolved, the gene conversion rate is much less clear. In Arabidopsis, for example, nextgeneration sequencing approaches suggest that the two rates are about the same, which contrasts with indirect measures, these suggesting an excess of gene conversion. Here, we provide analysis of this problem by sequencing 40 F 2 Arabidopsis plants and their parents. Small gene conversion tracts, with biased gene conversion content, represent over 90% (probably nearer 99%) of all recombination events. The rate of alteration of protein sequence caused by gene conversion is over 600 times that caused by mutation. Finally, our analysis reveals recombination hot spots and unexpectedly high recombination rates near centromeres. This may be responsible for the previously unexplained pattern of high genetic diversity near Arabidopsis centromeres.W hen considering the population genetic impact of recombination, classical theories predominantly concentrate on the impact of allelic shuffling, mediated by crossing-over, and the effect this has on linkage disequilibrium and, in turn, the effect the fate of one allele has on its genomic neighbors (1). However, when programmed double-strand breaks (DSBs) are introduced into chromosomes to initiate meiotic recombination, both crossover (CO) and noncrossover (non-CO) recombination events can occur.

Summary Numerous studies have argued that environmental variations may contribute to evolution through the generation of novel heritable variations via meiotic recombination, which plays a crucial role in crop domestication and improvement. Rice is one of the most important staple crops, but no direct estimate of recombination events has yet been made at a fine scale. Here, we address this limitation by sequencing 41 rice individuals with high sequencing coverage and c. 900 000 accurate markers. An average of 33.9 crossover (c. 4.53 cM Mb−1) and 2.47 non‐crossover events were detected per F2 plant, which is similar to the values in Arabidopsis. Although not all samples in the stress treatment group showed an increased number of crossover events, environmental stress increased the recombination rate in c. 28.5% of samples. Interestingly, the crossovers showed a highly uneven distribution among and along chromosomes, with c. 13.9% of the entire genome devoid of crossovers, including 11 of the 12 centromere regions, and c. 0.72% of the genome containing large numbers of crossovers (> 50 cM Mb−1). The gene ontology (GO) categories showed that genes clustered within the recombination hot spot regions primarily tended to be involved in responses to environmental stimuli, suggesting that recombination plays an important role for adaptive evolution in rapidly changing environments.

A retrospective case-control study of 118 (male : female, 68 : 50) Chinese type 2 diabetic patients with foot ulcers (Wagner's grade 3-5) was conducted to determine the prevalence and risk factors for meticillin-resistant Staphylococcus aureus (MRSA) infection in relation to the original community or hospital parameters. Ulcer specimens were processed for Gram staining, aerobic culture and antimicrobial susceptibility testing. Staphylococcus species were tested for meticillin resistance using oxacillin. S. aureus was the most frequent pathogen (25.6 %) in diabetic patient specimens (160 isolates), and a high proportion of S. aureus isolates were MRSA (63.4 %). A high percentage of S. aureus isolates (65.4 %) satisfied the definition for hospitalassociated MRSA (HA-MRSA) infection. The size of ulcers [adjusted odds ratio (OR) 1.61; 95 % confidence interval (CI) 1.22-2.12] and osteomyelitis (adjusted OR 18.51, 95 % CI 2.50-137.21) were independent predictors of MRSA infection. The HA-MRSA group had a significantly different distribution from the community-associated MRSA group with respect to age, history of diabetes and length of hospital stay (all P,0.001). Neuropathy, vascular disease (all P50.049) and osteomyelitis (P50.026) were the most common underlying conditions observed in the HA-MRSA group. This study contributes to the establishment of precautions against the emergence of MRSA including MRSA acquired from different sources among the Chinese population with diabetic foot ulcers based on their original or clinical parameters.

Cross-talk between competitive endogenous RNAs (ceRNAs) may play a critical role in revealing potential mechanisms of tumor development and physiology. Glioblastoma is the most common type of malignant primary brain tumor, and the mechanisms of tumor genesis and development in glioblastoma are unclear. Here, to investigate the role of non-coding RNAs and the ceRNA network in glioblastoma, we performed paired-end RNA sequencing and microarray analyses to obtain the expression profiles of mRNAs, lncRNAs, circRNAs and miRNAs. We identified that the expression of 501 lncRNAs, 1999 mRNAs, 2038 circRNAs and 143 miRNAs were often altered between glioblastoma and matched normal brain tissue. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed on these differentially expressed mRNAs and miRNA-mediated target genes of lncRNAs and circRNAs. Furthermore, we used a multi-step computational framework and several bioinformatics methods to construct a ceRNA network combining mRNAs, miRNAs, lncRNAs and circRNA, based on co-expression analysis between the differentially expressed RNAs. We identified that plenty of lncRNAs, CircRNAs and their downstream target genes in the ceRNA network are related to glutamatergic synapse, suggesting that glutamate metabolism is involved in glioma biological functions. Our results will accelerate the understanding of tumorigenesis, cancer progression and even therapeutic targeting in glioblastoma.