Background Massive forest decline has been observed almost everywhere as a result of negative anthropogenic and climatic effects, which can interact with pests, fungi and other phytopathogens and aggravate their effects. Climatic changes can weaken trees and make fungi, such as Armillaria more destructive. Armillaria borealis (Marxm. & Korhonen) is a fungus from the Physalacriaceae family (Basidiomycota) widely distributed in Eurasia, including Siberia and the Far East. Species from this genus cause the root white rot disease that weakens and often kills woody plants. However, little is known about ecological behavior and genetics of A. borealis. According to field research data, A. borealis is less pathogenic than A. ostoyae, and its aggressive behavior is quite rare. Mainly A. borealis behaves as a secondary pathogen killing trees already weakened by other factors. However, changing environment might cause unpredictable effects in fungus behavior. Results The de novo genome assembly and annotation were performed for the A. borealis species for the first time and presented in this study. The A. borealis genome assembly contained ~ 68 Mbp and was comparable with ~ 60 and ~ 79.5 Mbp for the A. ostoyae and A. mellea genomes, respectively. The N50 for contigs equaled 50,544 bp. Functional annotation analysis revealed 21,969 protein coding genes and provided data for further comparative analysis. Repetitive sequences were also identified. The main focus for further study and comparative analysis will be on the enzymes and regulatory factors associated with pathogenicity. Conclusions Pathogenic fungi such as Armillaria are currently one of the main problems in forest conservation. A comprehensive study of these species and their pathogenicity is of great importance and needs good genomic resources. The assembled genome of A. borealis presented in this study is of sufficiently good quality for further detailed comparative study on the composition of enzymes in other Armillaria species. There is also a fundamental problem with the identification and classification of species of the Armillaria genus, where the study of repetitive sequences in the genomes of basidiomycetes and their comparative analysis will help us identify more accurately taxonomy of these species and reveal their evolutionary relationships.
Background: Repetitive elements (REs) or repeats are sequences that occur multiple times in the genome. They represent a significant part of the gigantic conifer genomes (70-80%) relative to mammals and other plants and complicate whole genome sequencing and annotation. However, REs play important roles in evolution and adaptation processes in both plants and animals. Moreover, amino acid repeats play an important role in plant immunity being a structural element of the products of some disease resistance genes. Analysis of REs in conifer genomes is an important fundamental task.Results: REs were identified de novo and partly classified in the Siberian larch (Larix sibirica Ledeb.) nuclear genome for the first time. In total, 20.9 million REs were detected with the total size of 4.8 Gbp, which comprises about 39% of the 12.3 Gbp larch genome. Resistance genes with leucine-rich repeats (LRRs) were also identified and analyzed in the transcriptome data of autumn buds obtained using RNA-seq.Conclusions: For the first time, REs were identified and classified in the Siberian larch genome and transcriptome. In addition, LRRs and resistance genes were identified and analyzed in the Siberian larch transcriptomes from autumn buds. The larch genome contains twice as less RE compared to other conifers in the same Pinaceae family (39 vs 70-80%), and it might explain why it also has almost twice as smaller genome size (12 vs 18-31 Gbp).
Reduced representation library approaches are still a valuable tool for breeding and population and ecological genomics, even with impressive increases in sequencing capacity in recent years. Unfortunately, current approaches only allow for multiplexing up to 384 samples. To take advantage of increased sequencing capacity, we present Multi-GBS, a massively multiplexable extension to Genotyping-by-Sequencing that is also optimized for large conifer genomes. In Norway Spruce, a highly repetitive 20Gbp diploid genome with high population genetic variation, we call over a million variants in 32 genotypes from three populations, two natural forest in the Alps and Bohemian Alps, and a managed population from southeastern Austria using the existing TASSEL GBSv2 pipeline. Metric MDS analysis of replicated genotypes shows that technical bias in resulting genotype calling is minimal and that populations cluster in biologically meaningful ways.
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