RNAirport: a deep neural network-based database characterizing representative gene models in plants.

A 5'-leader, known initially as the 5'-untranslated region, contains multiple isoforms due to alternative splicing (aS) and alternative transcription start site (aTSS). Therefore, a representative 5'-leader is demanded to examine the embedded RNA regulatory elements in controlling translation efficiency. Here, we develop a ranking algorithm and a deep-learning model to annotate representative 5'-leaders for five plant species. We rank the intra-sample and inter-sample frequency of aS-mediated transcript isoforms using the Kruskal-Wallis test-based algorithm and identify the representative aS-5'-leader. To further assign a representative 5'-end, we train the deep-learning model 5'leaderP to learn aTSS-mediated 5'-end distribution patterns from cap-analysis gene expression data. The model accurately predicts the 5'-end, confirmed experimentally in Arabidopsis and rice. The representative 5'-leader-contained gene models and 5'leaderP can be accessed at RNAirport (http://www.rnairport.com/leader5P/). This stage 1 5'-leader annotation records 5'-leader diversity and will pave the way to Ribo-Seq open-reading frame annotation, identical to the project recently initiated by human GENCODE.

Plant HEM1 specifies a condensation domain to control immune gene translation.

Translational reprogramming is a fundamental layer of immune regulation, but how such a global regulatory mechanism operates remains largely unknown. Here we perform a genetic screen and identify Arabidopsis HEM1 as a global translational regulator of plant immunity. The loss of HEM1 causes exaggerated cell death to restrict bacterial growth during effector-triggered immunity (ETI). By improving ribosome footprinting, we reveal that the hem1 mutant increases the translation efficiency of pro-death immune genes. We show that HEM1 contains a plant-specific low-complexity domain (LCD) absent from animal homologues. This LCD endows HEM1 with the capability of phase separation in vitro and in vivo. During ETI, HEM1 interacts and condensates with the translation machinery; this activity is promoted by the LCD. CRISPR removal of this LCD causes more ETI cell death. Our results suggest that HEM1 condensation constitutes a brake mechanism of immune activation by controlling the tissue health and disease resistance trade-off during ETI.

Carbonation Curing on Magnetically Separated Steel Slag for the Preparation of Artificial Reefs.

Magnetic separation is an effective method to recover iron from steel slag. However, the ultra-fine tailings generated from steel slag become a new issue for utilization. The dry separation processes generates steel slag powder, which has hydration activity and can be used as cement filler. However, wet separation processes produce steel slag mud, which has lost its hydration activity and is no longer suitable to be used as a cement filler. This study investigates the potential of magnetically separated steel slag for carbonation curing and the potential use of the carbonated products as an artificial reef. Steel slag powder and steel slag mud were moulded, carbonation-cured and seawater-cured. Various testing methods were used to characterize the macro and micro properties of the materials. The results obtained show that carbonation and hydration collaborated during the carbonation curing process of steel slag powder, while only carbonation happened during the carbonation curing process of steel slag mud. The seawater-curing process of carbonated steel slag powder compact had three stages: C-S-H gel formation, C-S-H gel decomposition and equilibrium, which were in correspondence to the compressive strength of compact increasing, decreasing and unchanged. However, the seawater-curing process of carbonated steel slag mud compact suffered three stages: C-S-H gel decomposition, calcite transfer to vaterite and equilibrium, which made the compressive strength of compact decreased, increased and unchanged. Carbonated steel slags tailings after magnetic separation underwent their lowest compressive strength when seawater-cured for 7 days. The amount of CaO in the carbonation active minerals in the steel slag determined the carbonation consolidation ability of steel slag and durability of the carbonated steel slag compacts. This paper provides a reference for preparation of artificial reefs and marine coagulation materials by the carbonation curing of steel slag.

Small RNA sequencing revealed various microRNAs involved in ethylene-triggered flowering process in Aechmea fasciata.

Ethylene-triggered flowering is a common phenomenon in plants of the family Bromeliaceae, but its molecular mechanism remains unclear. As a classical group of small RNAs, microRNAs play an essential role in the regulation of flowering. In this study, we found that various miRNAs participate in the ethylene-triggered flowering process in Aechmea fasciata via small RNA sequencing using juvenile and adult plants treated with ethylene for 24 hours. Finally, 63 known miRNAs, 52 novel miRNAs and 1721 target genes were identified or predicted. Expression changes of specific miRNAs were validated by qRT-PCR and northern blotting. Some predicted targets, including SPL, GAMYB and ARF, were verified in RLM-RACE experiments. Gene Ontology (GO) and KEGG analysis showed that numerous developmental and RNA-related processes were enriched. Integrated analysis of the transcriptomic data with small RNA sequencing revealed that numerous miRNAs and targets involved in ethylene-triggered flowering in A. fasciata. Our study is helpful for illuminating the molecular basis of the ethylene-triggered flowering phenomenon in Bromeliaceae.

The Chromosome-Based Rubber Tree Genome Provides New Insights into Spurge Genome Evolution and Rubber Biosynthesis.

The rubber tree, Hevea brasiliensis, produces natural rubber that serves as an essential industrial raw material. Here, we present a high-quality reference genome for a rubber tree cultivar GT1 using single-molecule real-time sequencing (SMRT) and Hi-C technologies to anchor the ∼1.47-Gb genome assembly into 18 pseudochromosomes. The chromosome-based genome analysis enabled us to establish a model of spurge chromosome evolution, since the common paleopolyploid event occurred before the split of Hevea and Manihot. We show recent and rapid bursts of the three Hevea-specific LTR-retrotransposon families during the last 10 million years, leading to the massive expansion by ∼65.88% (∼970 Mbp) of the whole rubber tree genome since the divergence from Manihot. We identify large-scale expansion of genes associated with whole rubber biosynthesis processes, such as basal metabolic processes, ethylene biosynthesis, and the activation of polysaccharide and glycoprotein lectin, which are important properties for latex production. A map of genomic variation between the cultivated and wild rubber trees was obtained, which contains ∼15.7 million high-quality single-nucleotide polymorphisms. We identified hundreds of candidate domestication genes with drastically lowered genomic diversity in the cultivated but not wild rubber trees despite a relatively short domestication history of rubber tree, some of which are involved in rubber biosynthesis. This genome assembly represents key resources for future rubber tree research and breeding, providing novel targets for improving plant biotic and abiotic tolerance and rubber production.

Identification of 12 cancer types through genome deep learning.

Cancer is a major cause of death worldwide, and an early diagnosis is required for a favorable prognosis. Histological examination is the gold standard for cancer identification; however, large amount of inter-observer variability exists in histological diagnosis. Numerous studies have shown cancer genesis is accompanied by an accumulation of harmful mutations, potentiating the identification of cancer based on genomic information. We have proposed a method, GDL (genome deep learning), to study the relationship between genomic variations and traits based on deep neural networks. We analyzed 6,083 samples' WES (Whole Exon Sequencing) mutations files from 12 cancer types obtained from the TCGA (The Cancer Genome Atlas) and 1,991 healthy samples' WES data from the 1000 Genomes project. We constructed 12 specific models to distinguish between certain type of cancer and healthy tissues, a total-specific model that can identify healthy and cancer tissues, and a mixture model to distinguish between all 12 types of cancer based on GDL. We demonstrate that the accuracy of specific, mixture and total specific model are 97.47%, 70.08% and 94.70% for cancer identification. We developed an efficient method for the identification of cancer based on genomic information that offers a new direction for disease diagnosis.

Transcriptomic repertoires depict the initiation of lint and fuzz fibres in cotton (Gossypium hirsutum L.).

Cotton fibre is an important natural fibre for the textile industry. The number of fibre initials determines the lint percentage, which is an important factor for cotton fibre yield. Although fibre development has been described by transcriptomic analysis, the mechanism by which the long noncoding RNA manipulates the initiation of lint and fuzz fibres remains unknown. In this study, three lines with different lint percentages were developed by crossing Xu142 with its fibreless mutant Xu142 fl. We collected the epidermal cells from the ovules with attached fibres at 0 and 5 days post anthesis (DPA) from Xu142, the fibreless mutant Xu142 fl and the three lint percent diversified lines for deep transcriptome sequencing. A total of 2641 novel genes, 35 802 long noncoding RNAs (lncRNAs) and 2262 circular RNAs (circRNAs) were identified, of which 645 lncRNAs were preferentially expressed in the fibreless mutant Xu142 fl and 651 lncRNAs were preferentially expressed in the fibre-attached lines. We demonstrated the functional roles of the three lncRNAs in fibre development via a virus-induced gene silencing (VIGS) system. Our results showed that silencing XLOC_545639 and XLOC_039050 in Xu142 fl increased the number of fibre initials on the ovules, but silencing XLOC_079089 in Xu142 resulted in a short fibre phenotype. This study established the transcriptomic repertoires in cotton fibre initiation and provided evidence for the potential functions of lncRNAs in fibre development.

GhJAZ2 negatively regulates cotton fiber initiation by interacting with the R2R3-MYB transcription factor GhMYB25-like.

Jasmonic acid (JA) signaling has been well studied in Arabidopsis. Most reports focus on the role of JA in biological pathways, such as stress resistance, trichome initiation and anthocyanin accumulation. The JASMONATE ZIM-DOMAIN (JAZ) protein is one of the important repressors in the JA signaling pathway. Previous studies showed that JA functions in fiber initiation and elongation, but little is known about how JAZ genes function in fiber development. In this study, a cotton JAZ protein (GhJAZ2) containing a highly conserved TIFY motif and a C-terminal Jas domain was identified, and its function during cotton fiber development was analysed. Gene expression analysis showed that GhJAZ2 was preferentially expressed in the root, hypocotyl, flower and ovule 1 day before anthesis. Overexpression of GhJAZ2 inhibited both lint and fuzz fiber initiation, and reduced the fiber length. Yeast two-hybrid assays showed that GhJAZ2 interacted with the R2R3-MYB transcription factors GhMYB25-like and GhGL1, the bHLH transcription factor GhMYC2, the WD repeat protein GhWD40 and the unknown protein GhJI1. Among these transcription factors, previous studies showed that downregulation of GhMYB25-like leads to a fiberless phenotype in cotton seeds. Molecular and genetic evidence showed that the GhJAZ2 protein suppresses fiber initiation in the overexpressing lines by interacting with GhMYB25-like and suppressing GhMYB25-like activity. Our results suggested that GhJAZ2 functions as a primary transcription repressor during lint and fuzz fiber initiation by interacting with GhMYB25-like, GhGL1, GhMYC2, GhWD40 and GhJI1 to regulate the JA signaling pathway.

Multi-omics maps of cotton fibre reveal epigenetic basis for staged single-cell differentiation.

Epigenetic modifications are highlighted for their great importance in regulating plant development, but their function associated with single-cell differentiation remains undetermined. Here, we used the cotton fibre, which is the epidermal hair on the cotton ovule, as a model to investigate the regulatory role of DNA methylation in cell differentiation. The level of CHH (H = A, T, or C) DNA methylation level was found to increase during fibre development, accompanied by a decrease in RNA-directed DNA methylation (RdDM). Examination of nucleosome positioning revealed a gradual transition from euchromatin to heterochromatin for chromatin dynamics in developing fibres, which could shape the DNA methylation landscape. The observed increase in DNA methylation in fibres, compared with other ovule tissue, was demonstrated to be mediated predominantly by an active H3K9me2-dependent pathway rather than the RdDM pathway, which was inactive. Furthermore, integrated multi-omics analyses revealed that dynamic DNA methylation played a role in the regulation of lipid biosynthesis and spatio-temporal modulation of reactive oxygen species during fibre differentiation. Our study illustrates two divergent pathways mediating a continuous increase of DNA methylation and also sheds further light on the epigenetic basis for single-cell differentiation in plants. These data and analyses are made available to the wider research community through a comprehensive web portal.