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.

Activation of butterfly eyespots by Distal-less is consistent with a reaction-diffusion process.

Eyespots on the wings of nymphalid butterflies represent colorful examples of pattern formation, yet the developmental origins and mechanisms underlying eyespot center differentiation are still poorly understood. Using CRISPR-Cas9 we re-examine the function of Distal-less (Dll) as an activator or repressor of eyespots, a topic that remains controversial. We show that the phenotypic outcome of CRISPR mutations depends upon which specific exon is targeted. In Bicyclus anynana, exon 2 mutations are associated with both missing and ectopic eyespots, and also exon skipping. Exon 3 mutations, which do not lead to exon skipping, produce only null phenotypes, including missing eyespots, lighter wing coloration and loss of scales. Reaction-diffusion modeling of Dll function, using Wnt and Dpp as candidate morphogens, accurately replicates these complex crispant phenotypes. These results provide new insight into the function of Dll as a potential activator of eyespot development, scale growth and melanization, and suggest that the tuning of Dll expression levels can generate a diversity of eyespot phenotypes, including their appearance on the wing.This article has an associated 'The people behind the papers' interview.

Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels.

Metabolic homeostasis is sustained by complex biological networks that respond to nutrient availability. Genetic and environmental factors may disrupt this equilibrium, leading to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we performed quantitative genetic analysis using a population of 199 recombinant inbred lines (RILs) in the nematode Caenorhabditis elegans We focused on the genomic regions that control metabolite levels by measuring fatty acid (FA) and amino acid (AA) composition in the RILs using targeted metabolomics. The genetically diverse RILs showed a large variation in their FA and AA levels with a heritability ranging from 32% to 82%. We detected strongly co-correlated metabolite clusters and 36 significant metabolite quantitative trait loci (mQTL). We focused on mQTL displaying highly significant linkage and heritability, including an mQTL for the FA C14:1 on Chromosome I, and another mQTL for the FA C18:2 on Chromosome IV. Using introgression lines (ILs), we were able to narrow down both mQTL to a 1.4-Mbp and a 3.6-Mbp region, respectively. RNAi-based screening focusing on the Chromosome I mQTL identified several candidate genes for the C14:1 mQTL, including lagr-1, Y87G2A.2, nhr-265, nhr-276, and nhr-81 Overall, this systems approach provides us with a powerful platform to study the genetic basis of C. elegans metabolism. Furthermore, it allows us to investigate interventions such as nutrients and stresses that maintain or disturb the regulatory network controlling metabolic homeostasis, and identify gene-by-environment interactions.