Root system architecture (RSA) has a direct influence on the efficiency of nutrient uptake and plant growth, but the genetics of RSA are often studied only at the seedling stage. To get an insight into the genetic blueprint of a more mature RSA, we exploited natural variation and performed a detailed in vitro study of 241 Arabidopsis thaliana accessions using large petri dishes. A comprehensive analysis of 17 RSA traits showed high variability among the different accessions, unveiling correlations between traits and conditions of the natural habitat of the plants. A sub-selection of these accessions was grown in water-limiting conditions in a rhizotron set-up, which revealed that especially the spatial distribution showed a high consistency between in vitro and ex vitro conditions, while in particular, a large root area in the lower zone favored drought tolerance. The collected RSA phenotype data were used to perform genome-wide association studies (GWAS), which stands out from the previous studies by its exhaustive measurements of RSA traits on more mature Arabidopsis accessions used for GWAS. As a result, we found not only several genes involved in the lateral root (LR) development or auxin signaling pathways to be associated with RSA traits but also new candidate genes that are potentially involved in the adaptation to the natural habitats.

The leaf-colonizing bacterial microbiota was studied in a long-term warming experiment on a permanent grassland, which had been continuously exposed to increased surface temperature (+2°C) for more than six years. Two abundant plant species, Arrhenatherum elatius and Galium album, were studied. Surface warming reduced stomata opening and changed leaf metabolite profiles. Leaf surface colonization and the concentration of leaf-associated bacterial cells were not affected. However, bacterial 16S ribosomal RNA (rRNA) gene amplicon Illumina sequencing showed significant temperature effects on the plant species-specific phyllosphere microbiota. Warming partially affected the concentrations of cultured bacteria and had a significant effect on the composition of most abundant cultured plant species-specific bacteria. The abundance of Sphingomonas was significantly reduced. Sphingomonas isolates from warmed plots represented different phylotypes, had different physiological traits and were better adapted to higher temperatures. Among Methylobacterium isolates, a novel phylotype with a specific mxaFtype was cultured from plants of warmed plots while the most abundant phylotype cultured from control plots was strongly reduced. This study clearly showed a correlation of long-term surface warming with changes in the plant physiology and the development of a physiologically and genetically adapted phyllosphere microbiota.

Lolium perenne (perennial ryegrass) is the most widely cultivated forage and amenity grass species in temperate areas worldwide and there is a need to understand the genetic architectures of key agricultural traits and crop characteristics that deliver wider environmental services. Our aim was to identify genomic regions associated with agriculturally important traits by integrating a bacterial artificial chromosome (BAC)-based physical map with a genome-wide association study (GWAS).
BAC-based physical maps for L. perenne were constructed from ~212 000 high-information-content fingerprints using Fingerprint Contig and Linear Topology Contig software. BAC clones were associated with both BAC-end sequences and a partial minimum tiling path sequence. A panel of 716 L. perenne diploid genotypes from 90 European accessions was assessed in the field over 2 years, and genotyped using a Lolium Infinium SNP array. The GWAS was carried out using a linear mixed model implemented in TASSEL, and extended genomic regions associated with significant markers were identified through integration with the physical map.
Between ~3600 and 7500 physical map contigs were derived, depending on the software and probability thresholds used, and integrated with ~35 k sequenced BAC clones to develop a resource predicted to span the majority of the L. perenne genome. From the GWAS, eight different loci were significantly associated with heading date, plant width, plant biomass and water-soluble carbohydrate accumulation, seven of which could be associated with physical map contigs. This allowed the identification of a number of candidate genes.
Combining the physical mapping resource with the GWAS has allowed us to extend the search for candidate genes across larger regions of the L. perenne genome and identified a number of interesting gene model annotations. These physical maps will aid in validating future sequence-based assemblies of the L. perenne genome.

Oligotyping is a computational method used to increase the resolution of marker gene microbiome studies. Although oligotyping can distinguish highly similar sequence variants, the resulting units are not necessarily phylogenetically and ecologically informative due to limitations of the selected marker gene. In this perspective, we examine how oligotyping data is interpreted in recent literature, and we illustrate some of the method\'s constraints with a case study of the harmful bloom-forming cyanobacterium Microcystis. We identified three Microcystis oligotypes from a western Lake Erie bacterial community 16S rRNA gene (V4 region) survey that had previously clustered into one OTU. We found the same three oligotypes and two additional sequence variants in 46 Microcystis cultures isolated from Michigan inland lakes spanning a trophic gradient. In Lake Erie, shifts in Microcystis oligotypes corresponded to spatial nutrient gradients and temporal transitions in bloom toxicity. In the cultures, Microcystis oligotypes showed preferential distributions for different trophic states, but genomic data revealed that the oligotypes identified in Lake Erie did not correspond to toxin gene presence. Thus, oligotypes could not be used for inferring toxic ecotypes. Most strikingly, Microcystis oligotypes were not monophyletic. Our study supports the utility of oligotyping for distinguishing sequence types along certain ecological features, while it stresses that 16S rRNA gene sequence types may not reflect ecologically or phylogenetically cohesive populations. Therefore, we recommend that studies employing oligotyping or related tools consider these caveats during data interpretation.

OBJECTIVE: The current study was the first of its kind taken upon indigenous ecotypes of the Karnataka in order to unravel the diversity details at 20 chicken microsatellite regions.
METHODS: 210 indigenous chicken belonging to six districts of Bangalore and Mysore division formed the target sample for the present study. The genomic deoxyribonucleic acid was isolated by phenol chloroform isoamyl alcohol method. A panel of 20 microsatellite regions, including 14 recommended by FAO and six identified from published scientific literature became the targeted chicken genomic region. 27-33 samples were successfully genotyped in each of the six ecotypes through simplex or multiplex polymerase chain reactions, polyacrylamide gel electrophoresis and silver staining for the selected microsatellite panel.
RESULTS: The chickens of Ramanagara and Chamrajnagara were most distant with a Nei\'s genetic distance value of 0.22. The chickens of Bangalore rural and Mysore were least distant with a value of 0.056. The Ramanagara and Chamrajnagara pair had Nei\'s genetic identity value of 0.802, which is least among all pairs of ecotypes. There were five main nodes from which the six ecotypes evolved on the basis 20 microsatellite markers used in this study. This study indicates that the four ecotypes Ramnagara, Bangalore Rural, Chickaballapura and Mysore are genetically identical due to their common ancestral evolution while, Mandya and Chamrajnagara ecotypes formed a relatively different cluster due to a separate common ancestral chicken population and less number of generations since drifting from bifurcation node.
CONCLUSIONS: Twenty microsatellite markers based genetic diversity study on six indigenous ecotypes indicated lower genetic distances as well as lower FST values compared to the distinguished breeds reported. There were two main clusters, which differentiated into six ecotypes. They may differentiate into more distinct varieties if bred in isolation for a longer number of generations.