The regulatory role of miRNA in gene expression is an emerging hot new topic in the control of hypometabolism. Sea cucumber aestivation is a complicated physiological process that includes obvious hypometabolism as evidenced by a decrease in the rates of oxygen consumption and ammonia nitrogen excretion, as well as a serious degeneration of the intestine into a very tiny filament. To determine whether miRNAs play regulatory roles in this process, the present study analyzed profiles of miRNA expression in the intestine of the sea cucumber (Apostichopus japonicus), using Solexa deep sequencing technology. We identified 308 sea cucumber miRNAs, including 18 novel miRNAs specific to sea cucumber. Animals sampled during deep aestivation (DA) after at least 15 days of continuous torpor, were compared with animals from a non-aestivation (NA) state (animals that had passed through aestivation and returned to the active state). We identified 42 differentially expressed miRNAs [RPM (reads per million) >10, |FC| (|fold change|) ≥1, FDR (false discovery rate) <0.01] during aestivation, which were validated by two other miRNA profiling methods: miRNA microarray and real-time PCR. Among the most prominent miRNA species, miR-200-3p, miR-2004, miR-2010, miR-22, miR-252a, miR-252a-3p and miR-92 were significantly over-expressed during deep aestivation compared with non-aestivation animals. Preliminary analyses of their putative target genes and GO analysis suggest that these miRNAs could play important roles in global transcriptional depression and cell differentiation during aestivation. High-throughput sequencing data and microarray data have been submitted to GEO database.

Background Yellowhorn ( Xanthoceras sorbifolium Bunge), a deciduous shrub or small tree native to north China, is of great economic value. Seeds of yellowhorn are rich in oil containing unsaturated long-chain fatty acids that have been used for producing edible oil and nervonic acid capsules. However, the lack of a high-quality genome sequence hampers the understanding of its evolution and gene functions. Findings In this study, a whole genome of yellowhorn was sequenced and assembled by integration of Illumina sequencing, Pacific Biosciences single-molecule real-time sequencing, 10X Genomics linked reads, Bionano optical maps, and Hi-C. The yellowhorn genome assembly was 439.97 Mb, which comprised 15 pseudo-chromosomes covering 95.42% (419.84 Mb) of the assembled genome. The repetitive fractions accounted for 56.39% of the yellowhorn genome. The genome contained 21,059 protein-coding genes. Of them, 18,503 (87.86%) genes were found to be functionally annotated with ≥1 "annotation" term by searching against other databases. Transcriptomic analysis showed that 341, 135, 125, 113, and 100 genes were specifically expressed in hermaphrodite flower, staminate flower, young fruit, leaf, and shoot, respectively. Phylogenetic analysis suggested that yellowhorn and Dimocarpus longan diverged from their most recent common ancestor ∼46 million years ago. Conclusions The availability and subsequent annotation of the yellowhorn genome, as well as the identification of tissue-specific functional genes, provides a valuable reference for plant comparative genomics, evolutionary studies, and molecular design breeding.

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Long non-coding RNAs (lncRNAs) are involved in various regulatory processes although they do not encode protein. Presently, there is little information regarding the identification of lncRNAs in peanut (Arachis hypogaea Linn.). In this study, 50,873 lncRNAs of peanut were identified from large-scale published RNA sequencing data that belonged to 124 samples involving 15 different tissues. The average lengths of lncRNA and mRNA were 4335 bp and 954 bp, respectively. Compared to the mRNAs, the lncRNAs were shorter, with fewer exons and lower expression levels. The 4713 co-expression lncRNAs (expressed in all samples) were used to construct co-expression networks by using the weighted correlation network analysis (WGCNA). LncRNAs correlating with the growth and development of different peanut tissues were obtained, and target genes for 386 hub lncRNAs of all lncRNAs co-expressions were predicted. Taken together, these findings can provide a comprehensive identification of lncRNAs in peanut.

Lipoprotein(a) [Lp(a)] has been postulated to inhibit fibrinolysis due to its structural homology to plasminogen. Indeed, it has been reported that Lp(a) competitively inhibits the promotion by fibrin of tissue plasminogen activator (t-PA)-catalyzed plasminogen activation. However, it has also been reported that this inhibition is uncompetitive. No studies have been published, to our knowledge, of the effect of Lp(a) on prourokinase (pro-UK)-catalyzed plasminogen activation. Plasminogen activation by pro-UK or a plasmin-resistant mutant pro-UK was previously shown to be promoted by fibrin fragment E2, whereas that by t-PA is promoted by fragment D. Therefore, the influence of Lp(a) on the kinetics of these two reactions was examined. When Lp(a) was added (90-600 nM), no change in the rate of plasmin generation by Ala158-pro-UK was observed. Consistent with this, immobilized Lp(a) also failed to bind to fragment E2, whereas it did bind to D dimer. When t-PA-catalyzed plasminogen activation in the presence of D dimer was measured, uncompetitive inhibition by Lp(a) was found, but only at low concentrations of D dimer (< 0.5 microM) or t-PA (0.05 nM). At higher concentrations of D dimer and t-PA, instead of inhibition, Lp(a) induced a 2.4-fold promotion of plasminogen activation. Similarly, Lp(a) enhanced (up to 2.5-fold) plasminogen binding to immobilized fibrin in both buffer and plasma milieus at the physiological concentration of plasminogen (2.0 microM). In conclusion, Lp(a) had no effect on plasminogen activation by pro-UK and induced only limited inhibition of activation by t-PA.(ABSTRACT TRUNCATED AT 250 WORDS)