In plants, transgenerational inheritance of some epialleles has been demonstrated but it remains controversial whether epigenetic variation is subject to selection and contributes to adaptation. Simulating selection in a rapidly changing environment, we compare phenotypic traits and epigenetic variation between Arabidopsis thaliana populations grown for five generations under selection and their genetically nearly identical ancestors. Selected populations of two distinct genotypes show significant differences in flowering time and plant architecture, which are maintained for at least 2–3 generations in the absence of selection. While we cannot detect consistent genetic changes, we observe a reduction of epigenetic diversity and changes in the methylation state of about 50,000 cytosines, some of which are associated with phenotypic changes. Thus, we propose that epigenetic variation is subject to selection and can contribute to rapid adaptive responses, although the extent to which epigenetics plays a role in adaptation is still unclear.
Finger millet (Eleusine coracana (L.) Gaertn) is an important crop for food security because of its tolerance to drought, which is expected to be exacerbated by global climate changes. Nevertheless, it is often classified as an orphan/underutilized crop because of the paucity of scientific attention. Among several small millets, finger millet is considered as an excellent source of essential nutrient elements, such as iron and zinc; hence, it has potential as an alternate coarse cereal. However, high-quality genome sequence data of finger millet are currently not available. One of the major problems encountered in the genome assembly of this species was its polyploidy, which hampers genome assembly compared with a diploid genome. To overcome this problem, we sequenced its genome using diverse technologies with sufficient coverage and assembled it via a novel multiple hybrid assembly workflow that combines next-generation with single-molecule sequencing, followed by whole-genome optical mapping using the Bionano Irys® system. The total number of scaffolds was 1,897 with an N50 length >2.6 Mb and detection of 96% of the universal single-copy orthologs. The majority of the homeologs were assembled separately. This indicates that the proposed workflow is applicable to the assembly of other allotetraploid genomes.
Joint pain causes significant morbidity in osteoarthritis (OA). The aetiology of joint pain in OA is not well understood. The synovial membrane as an innervated joint structure represents a potential source of peripheral pain in OA. Here we analyse, using a hypothesis-free next generation RNA sequencing, the differences in protein-coding and non-coding transcriptomes in knee synovial tissues from OA patients with high knee pain (n = 5) compared with OA patients with low knee pain (n = 5), as evaluated by visual analogue scale (VAS). We conduct Gene Ontology and pathway analyses on differentially expressed mRNA genes. We identify new protein-coding, long non-coding RNA and microRNA candidates that can be associated with OA joint pain. Top enriched genes in painful OA knees encode neuronal proteins that are known to promote neuronal survival under cellular stress or participate in calcium-dependent synaptic exocytosis and modulation of GABA(γ-aminobutyric acid)ergic activity. Our study uncovers transcriptome changes associated with pain in synovial microenvironment of OA knees. This sets a firm ground for future mechanistic studies and drug discovery to alleviate joint pain in OA.
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