Stochastic nuclear organization and host-dependent allele contribution in Rhizophagus irregularis.

BACKGROUND: Arbuscular mycorrhizal (AM) fungi are arguably the most important symbionts of plants, offering a range of benefits to their hosts. However, the provisioning of these benefits does not appear to be uniform among AM fungal individuals, with genetic variation between fungal symbionts having a substantial impact on plant performance. Interestingly, genetic variation has also been reported within fungal individuals, which contain millions of haploid nuclei sharing a common cytoplasm. In the model AM fungus, Rhizophagus irregularis, several isolates have been reported to be dikaryotes, containing two genetically distinct types of nuclei recognized based on their mating-type (MAT) locus identity. However, their extremely coenocytic nature and lack of a known single nucleus stage has raised questions on the origin, distribution and dynamics of this genetic variation. RESULTS: Here we performed DNA and RNA sequencing at the mycelial individual, single spore and single nucleus levels to gain insight into the dynamic genetic make-up of the dikaryote-like R. irregularis C3 isolate and the effect of different host plants on its genetic variation. Our analyses reveal that parallel spore and root culture batches can have widely variable ratios of two main genotypes in C3. Additionally, numerous polymorphisms were found with frequencies that deviated significantly from the general genotype ratio, indicating a diverse population of slightly different nucleotypes. Changing host plants did not show consistent host effects on nucleotype ratio's after multiple rounds of subculturing. Instead, we found a major effect of host plant-identity on allele-specific expression in C3. CONCLUSION: Our analyses indicate a highly dynamic/variable genetic organization in different isolates of R. irregularis. Seemingly random fluctuations in nucleotype ratio's upon spore formation, recombination events, high variability of non-tandemly repeated rDNA sequences and host-dependent allele expression all add levels of variation that may contribute to the evolutionary success of these widespread symbionts.

The genome sequence of Hirschfeldia incana, a new Brassicaceae model to improve photosynthetic light-use efficiency.

Photosynthesis is a key process in sustaining plant and human life. Improving the photosynthetic capacity of agricultural crops is an attractive means to increase their yields. While the core mechanisms of photosynthesis are highly conserved in C3 plants, these mechanisms are very flexible, allowing considerable diversity in photosynthetic properties. Among this diversity is the maintenance of high photosynthetic light-use efficiency at high irradiance as identified in a small number of exceptional C3 species. Hirschfeldia incana, a member of the Brassicaceae family, is such an exceptional species, and because it is easy to grow, it is an excellent model for studying the genetic and physiological basis of this trait. Here, we present a reference genome of H. incana and confirm its high photosynthetic light-use efficiency. While H. incana has the highest photosynthetic rates found so far in the Brassicaceae, the light-saturated assimilation rates of closely related Brassica rapa and Brassica nigra are also high. The H. incana genome has extensively diversified from that of B. rapa and B. nigra through large chromosomal rearrangements, species-specific transposon activity, and differential retention of duplicated genes. Duplicated genes in H. incana, B. rapa, and B. nigra that are involved in photosynthesis and/or photoprotection show a positive correlation between copy number and gene expression, providing leads into the mechanisms underlying the high photosynthetic efficiency of these species. Our work demonstrates that the H. incana genome serves as a valuable resource for studying the evolution of high photosynthetic light-use efficiency and enhancing photosynthetic rates in crop species.

Reciprocal cybrids reveal how organellar genomes affect plant phenotypes.

Assessment of the impact of variation in chloroplast and mitochondrial DNA (collectively termed the plasmotype) on plant phenotypes is challenging due to the difficulty in separating their effect from nuclear-derived variation (the nucleotype). Haploid-inducer lines can be used as efficient plasmotype donors to generate new plasmotype-nucleotype combinations (cybrids)1. We generated a panel comprising all possible cybrids of seven Arabidopsis thaliana accessions and extensively phenotyped these lines for 1,859 phenotypes under both stable and fluctuating conditions. We show that natural variation in the plasmotype results in both additive and epistatic effects across all phenotypic categories. Plasmotypes that induce more additive phenotypic changes also cause more epistatic effects, suggesting a possible common basis for both additive and epistatic effects. On average, epistatic interactions explained twice as much of the variance in phenotypes as additive plasmotype effects. The impact of plasmotypic variation was also more pronounced under fluctuating and stressful environmental conditions. Thus, the phenotypic impact of variation in plasmotypes is the outcome of multi-level nucleotype-plasmotype-environment interactions and, as such, the plasmotype is likely to serve as a reservoir of variation that is predominantly exposed under certain conditions. The production of cybrids using haploid inducers is a rapid and precise method for assessment of the phenotypic effects of natural variation in organellar genomes. It will facilitate efficient screening of unique nucleotype-plasmotype combinations to both improve our understanding of natural variation in these combinations and identify favourable combinations to enhance plant performance.

Hecaton: reliably detecting copy number variation in plant genomes using short read sequencing data.

BACKGROUND: Copy number variation (CNV) is thought to actively contribute to adaptive evolution of plant species. While many computational algorithms are available to detect copy number variation from whole genome sequencing datasets, the typical complexity of plant data likely introduces false positive calls. RESULTS: To enable reliable and comprehensive detection of CNV in plant genomes, we developed Hecaton, a novel computational workflow tailored to plants, that integrates calls from multiple state-of-the-art algorithms through a machine-learning approach. In this paper, we demonstrate that Hecaton outperforms current methods when applied to short read sequencing data of Arabidopsis thaliana, rice, maize, and tomato. Moreover, it correctly detects dispersed duplications, a type of CNV commonly found in plant species, in contrast to several state-of-the-art tools that erroneously represent this type of CNV as overlapping deletions and tandem duplications. Finally, Hecaton scales well in terms of memory usage and running time when applied to short read datasets of domesticated and wild tomato accessions. CONCLUSIONS: Hecaton provides a robust method to detect CNV in plants. We expect it to be of immediate interest to both applied and fundamental research on the relationship between genotype and phenotype in plants.