Crossing-over in a hypervariable species preferentially occurs in regions of high local similarity.

Recombination between double-stranded DNA molecules is a key genetic process which occurs in a wide variety of organisms. Usually, crossing-over (CO) occurs during meiosis between genotypes with 98.0-99.9% sequence identity, because within-population nucleotide diversity only rarely exceeds 2%. However, some species are hypervariable and it is unclear how CO can occur between genotypes with less than 90% sequence identity. Here, we study CO in Schizophyllum commune, a hypervariable cosmopolitan basidiomycete mushroom, a frequently encountered decayer of woody substrates. We crossed two haploid individuals, from the United States and from Russia, and obtained genome sequences for their 17 offspring. The average genetic distance between the parents was 14%, making it possible to study CO at very high resolution. We found reduced levels of linkage disequilibrium between loci flanking the CO sites indicating that they are mostly confined to hotspots of recombination. Furthermore, CO events preferentially occurred in regions under stronger negative selection, in particular within exons that showed reduced levels of nucleotide diversity. Apparently, in hypervariable species CO must avoid regions of higher divergence between the recombining genomes due to limitations imposed by the mismatch repair system, with regions under strong negative selection providing the opportunity for recombination. These patterns are opposite to those observed in a number of less variable species indicating that population genomics of hypervariable species may reveal novel biological phenomena.

Comparative analysis of gene expression level by quantitative real-time PCR has limited application in objects with different morphology.

qRT-PCR is a generally acknowledged method for gene expression analysis due to its precision and reproducibility. However, it is well known that the accuracy of qRT-PCR data varies greatly depending on the experimental design and data analysis. Recently, a set of guidelines has been proposed that aims to improve the reliability of qRT-PCR. However, there are additional factors that have not been taken into consideration in these guidelines that can seriously affect the data obtained using this method. In this study, we report the influence that object morphology can have on qRT-PCR data. We have used a number of Arabidopsis thaliana mutants with altered floral morphology as models for this study. These mutants have been well characterised (including in terms of gene expression levels and patterns) by other techniques. This allows us to compare the results from the qRT-PCR with the results inferred from other methods. We demonstrate that the comparison of gene expression levels in objects that differ greatly in their morphology can lead to erroneous results.

Selection and validation of reference genes for quantitative real-time PCR in buckwheat (Fagopyrum esculentum) based on transcriptome sequence data.

Quantitative reverse transcription PCR (qRT-PCR) is one of the most precise and widely used methods of gene expression analysis. A necessary prerequisite of exact and reliable data is the accurate choice of reference genes. We studied the expression stability of potential reference genes in common buckwheat (Fagopyrum esculentum) in order to find the optimal reference for gene expression analysis in this economically important crop. Recently sequenced buckwheat floral transcriptome was used as source of sequence information. Expression stability of eight candidate reference genes was assessed in different plant structures (leaves and inflorescences at two stages of development and fruits). These genes are the orthologs of Arabidopsis genes identified as stable in a genome-wide survey gene of expression stability and a traditionally used housekeeping gene GAPDH. Three software applications--geNorm, NormFinder and BestKeeper--were used to estimate expression stability and provided congruent results. The orthologs of AT4G33380 (expressed protein of unknown function, Expressed1), AT2G28390 (SAND family protein, SAND) and AT5G46630 (clathrin adapter complex subunit family protein, CACS) are revealed as the most stable. We recommend using the combination of Expressed1, SAND and CACS for the normalization of gene expression data in studies on buckwheat using qRT-PCR. These genes are listed among five the most stably expressed in Arabidopsis that emphasizes utility of the studies on model plants as a framework for other species.