Asymmetric variation in DNA methylation during domestication and de-domestication of rice.

Hundreds of plant species have been domesticated to feed human civilization, while some crops have undergone de-domestication into agricultural weeds, threatening global food security. To understand the genetic and epigenetic basis of crop domestication and de-domestication, we generated DNA methylomes from 95 accessions of wild rice (Oryza rufipogon L.), cultivated rice (Oryza sativa L.) and weedy rice (O. sativa f. spontanea). We detected a significant decrease in DNA methylation over the course of rice domestication but observed an unexpected increase in DNA methylation through de-domestication. Notably, DNA methylation changes occurred in distinct genomic regions for these 2 opposite stages. Variation in DNA methylation altered the expression of nearby and distal genes through affecting chromatin accessibility, histone modifications, transcription factor binding, and the formation of chromatin loops, which may contribute to morphological changes during domestication and de-domestication of rice. These insights into population epigenomics underlying rice domestication and de-domestication provide resources and tools for epigenetic breeding and sustainable agriculture.

Ectopic expression of OsWOX9A alters leaf anatomy and plant architecture in rice.

MAIN CONCLUSION: Ectopic expression of OsWOX9A induces narrow adaxially rolled rice leaves with larger bulliform cells and fewer large veins, probably through regulating the expression of auxin-related and expansin genes. The WUSCHEL-related homeobox (WOX) family plays a pivotal role in plant development by regulating genes involved in various aspects of growth and differentiation. OsWOX9A (DWT1) has been linked to tiller growth, uniform plant growth, and flower meristem activity. However, its impact on leaf growth and development in rice has not been studied. In this study, we investigated the biological role of OsWOX9A in rice growth and development using transgenic plants. Overexpression of OsWOX9A conferred narrow adaxially rolled rice leaves and altered plant architecture. These plants exhibited larger bulliform cells and fewer larger veins compared to wild-type plants. OsWOX9A overexpression also reduced plant height, tiller number, and seed-setting rate. Comparative transcriptome analysis revealed several differentially expressed auxin-related and expansin genes in OsWOX9A overexpressing plants, consistent with their roles in leaf and plant development. These results indicate that the ectopic expression of OsWOX9A may have multiple effects on the development and growth of rice, providing a more comprehensive picture of how the WOX9 subfamily contributes to leaf development and plant architecture.

EMLI-ICC: an ensemble machine learning-based integration algorithm for metastasis prediction and risk stratification in intrahepatic cholangiocarcinoma.

Robust strategies to identify patients at high risk for tumor metastasis, such as those frequently observed in intrahepatic cholangiocarcinoma (ICC), remain limited. While gene/protein expression profiling holds great potential as an approach to cancer diagnosis and prognosis, previously developed protocols using multiple diagnostic signatures for expression-based metastasis prediction have not been widely applied successfully because batch effects and different data types greatly decreased the predictive performance of gene/protein expression profile-based signatures in interlaboratory and data type dependent validation. To address this problem and assist in more precise diagnosis, we performed a genome-wide integrative proteome and transcriptome analysis and developed an ensemble machine learning-based integration algorithm for metastasis prediction (EMLI-Metastasis) and risk stratification (EMLI-Prognosis) in ICC. Based on massive proteome (216) and transcriptome (244) data sets, 132 feature (biomarker) genes were selected and used to train the EMLI-Metastasis algorithm. To accurately detect the metastasis of ICC patients, we developed a weighted ensemble machine learning method based on k-Top Scoring Pairs (k-TSP) method. This approach generates a metastasis classifier for each bootstrap aggregating training data set. Ten binary expression rank-based classifiers were generated for detection of metastasis separately. To further improve the accuracy of the method, the 10 binary metastasis classifiers were combined by weighted voting based on the score from the prediction results of each classifier. The prediction accuracy of the EMLI-Metastasis algorithm achieved 97.1% and 85.0% in proteome and transcriptome datasets, respectively. Among the 132 feature genes, 21 gene-pair signatures were developed to establish a metastasis-related prognosis risk-stratification model in ICC (EMLI-Prognosis). Based on EMLI-Prognosis algorithm, patients in the high-risk group had significantly dismal overall survival relative to the low-risk group in the clinical cohort (P-value < 0.05). Taken together, the EMLI-ICC algorithm provides a powerful and robust means for accurate metastasis prediction and risk stratification across proteome and transcriptome data types that is superior to currently used clinicopathological features in patients with ICC. Our developed algorithm could have profound implications not just in improved clinical care in cancer metastasis risk prediction, but also more broadly in machine-learning-based multi-cohort diagnosis method development. To make the EMLI-ICC algorithm easily accessible for clinical application, we established a web-based server for metastasis risk prediction (http://ibi.zju.edu.cn/EMLI/).

MicroRNAs constitute an additional layer in plant response to simultaneous bio- and abiotic stresses as exemplified by UV-B radiation and flg22-treatment on Arabidopsis thaliana.

Plants are confronted with various environmental stresses and develop sophisticated adaptive mechanisms. Our previous work demonstrated that the crosstalk of flg22 and ultraviolet (UV)-B-induced signalling cascades reprograms the expression of flavonol pathway genes (FPGs), benefiting plant defence responses. Although several transcription factors have been identified to be involved in this crosstalk, the underlying mechanism is largely unclear. Here, we analyzed microRNAs (miRNAs) and identified 126, 129 and 113 miRNAs with altered abundances compared to untreated control in flg22-, UV-B- and flg22/UV-B-treated seedlings, respectively. Two distinct modules were identified: The first consists of 10 miRNAs repressed by UV-B but up-regulated by flg22, and the second with five miRNAs repressed by flg22 but up-regulated by UV-B. In Arabidopsis, the knockdown of miR858a, a representative of module I, increased the abundance of CHS (a marker gene for FPGs), whereas its overexpression reduced CHS. Conversely, knockout of miR164b from module II decreased CHS and its overexpression increased CHS transcript levels. These data suggest a decisive role of miRNAs in the crosstalk. In the next, we described the interaction between miR858a and its target MYB111 (a positive regulator of FPGs) from module I in detail. We showed that MYB111 was profoundly post-transcriptionally regulated by miR858a during the crosstalk, whose expression was specifically but antagonistically controlled by UVR8- and FLS2-mediated signallings. Moreover, transcriptional monitoring using the GUS reporter gene demonstrates that miRNA-mediated posttranscriptional regulation is the main driving force in reprogramming the expression of FPGs and regulates plant adaptation to multiple concurrent environmental stresses.

An ABCC-type transporter endowing glyphosate resistance in plants.

Glyphosate is the most widely used herbicide in world agriculture and for general vegetation control in a wide range of situations. Global and often intensive glyphosate selection of very large weedy plant populations has resulted in widespread glyphosate resistance evolution in populations of many weed species. Here, working with a glyphosate-resistant (GR) Echinochloa colona population that evolved in a Western Australia agricultural field, we identified an ATP-binding cassette (ABC) transporter (EcABCC8) that is consistently up-regulated in GR plants. When expressed in transgenic rice, this EcABCC8 transporter endowed glyphosate resistance. Equally, rice, maize, and soybean overexpressing the EcABCC8 ortholog genes were made resistant to glyphosate. Conversely, CRISPR/Cas9-mediated knockout of the EcABCC8 ortholog gene OsABCC8 increased rice susceptibility to glyphosate. Subcellular localization analysis and quantification of glyphosate cellular levels in treated ABCC8 transgenic rice plants and isolated leaf protoplasts as well as structural modeling support that EcABCC8 is likely a plasma membrane-localized transporter extruding cytoplasmic glyphosate to the apoplast, lowering the cellular glyphosate level. This is a report of a membrane transporter effluxing glyphosate in a GR plant species, and its function is likely conserved in crop plant species.

Lateral transfers lead to the birth of momilactone biosynthetic gene clusters in grass.

Momilactone A, an important plant labdane-related diterpenoid, functions as a phytoalexin against pathogens and an allelochemical against neighboring plants. The genes involved in the biosynthesis of momilactone A are found in clusters, i.e., momilactone A biosynthetic gene clusters (MABGCs), in the rice and barnyardgrass genomes. In addition, we know little about the origin and evolution of MABGCs. Here, we integrated results from comprehensive phylogeny and comparative genomic analyses of the core genes of MABGC-like clusters and MABGCs in 40 monocot plant genomes, providing convincing evidence for the birth and evolution of MABGCs in grass species. The MABGCs found in the PACMAD clade of the core grass lineage (including Panicoideae and Chloridoideae) originated from a MABGC-like cluster in Triticeae (BOP clade) via lateral gene transfer (LGT) and followed by recruitment of MAS1/2 and CYP76L1 genes. The MABGCs in Oryzoideae originated from PACMAD through another LGT event and lost CYP76L1 afterwards. The Oryza MABGC and another Oryza diterpenoid cluster c2BGC are two distinct clusters, with the latter originating from gene duplication and relocation within Oryzoideae. Further comparison of the expression patterns of the MABGC genes between rice and barnyardgrass in response to pathogen infection and allelopathy provides novel insights into the functional innovation of MABGCs in plants. Our results demonstrate LGT-mediated origination of MABGCs in grass and shed lights into the evolutionary innovation and optimization of plant biosynthetic pathways.

TOD-CUP: a gene expression rank-based majority vote algorithm for tissue origin diagnosis of cancers of unknown primary.

Gene expression profiling holds great potential as a new approach to histological diagnosis and precision medicine of cancers of unknown primary (CUP). Batch effects and different data types greatly decrease the predictive performance of biomarker-based algorithms, and few methods have been widely applied to identify tissue origin of CUP up to now. To address this problem and assist in more precise diagnosis, we have developed a gene expression rank-based majority vote algorithm for tissue origin diagnosis of CUP (TOD-CUP) of most common cancer types. Based on massive tissue-specific RNA-seq data sets (10 553) found in The Cancer Genome Atlas (TCGA), 538 feature genes (biomarkers) were selected based on their gene expression ranks and used to predict tissue types. The top scoring pairs (TSPs) classifier of the tumor type was optimized by the TCGA training samples. To test the prediction accuracy of our TOD-CUP algorithm, we analyzed (1) two microarray data sets (1029 Agilent and 2277 Affymetrix/Illumina chips) and found 91% and 94% prediction accuracy, respectively, (2) RNA-seq data from five cancer types derived from 141 public metastatic cancer tumor samples and achieved 94% accuracy and (3) a total of 25 clinical cancer samples (including 14 metastatic cancer samples) were able to classify 24/25 samples correctly (96.0% accuracy). Taken together, the TOD-CUP algorithm provides a powerful and robust means to accurately identify the tissue origin of 24 cancer types across different data platforms. To make the TOD-CUP algorithm easily accessible for clinical application, we established a Web-based server for tumor tissue origin diagnosis (http://ibi. zju.edu.cn/todcup/).

Poaceae Chloroplast Genome Sequencing: Great Leap Forward in Recent Ten Years.

The first complete chloroplast genome of rice (Oryza sativa) was published in 1989, ushering in a new era of studies of chloroplast genomics in Poaceae. Progresses in Next-Generation Sequencing (NGS) and Third-Generation Sequencing (TGS) technologiesand in the development of genome assembly software, have significantly advanced chloroplast genomics research. Poaceae is one of the most targeted families in chloroplast genome research because of its agricultural, ecological, and economic importance. Over the last 30 years, 2,050 complete chloroplast genome sequences from 40 tribes and 282 genera have been generated, most (97%) of them in the recent ten years. The wealth of data provides the groundwork for studies on species evolution, phylogeny, genetic transformation, and other aspects of Poaceae chloroplast genomes. As a result, we have gained a deeper understanding of the properties of Poaceae chloroplast genomes. Here, we summarize the achievements of the studies of the Poaceae chloroplast genomes and envision the challenges for moving the area ahead.

Genomic evidence for convergent evolution of gene clusters for momilactone biosynthesis in land plants.

Momilactones are bioactive diterpenoids that contribute to plant defense against pathogens and allelopathic interactions between plants. Both cultivated and wild grass species of Oryza and Echinochloa crus-galli (barnyard grass) produce momilactones using a biosynthetic gene cluster (BGC) in their genomes. The bryophyte Calohypnum plumiforme (formerly Hypnum plumaeforme) also produces momilactones, and the bifunctional diterpene cyclase gene CpDTC1/HpDTC1, which is responsible for the production of the diterpene framework, has been characterized. To understand the molecular architecture of the momilactone biosynthetic genes in the moss genome and their evolutionary relationships with other momilactone-producing plants, we sequenced and annotated the C. plumiforme genome. The data revealed a 150-kb genomic region that contains two cytochrome P450 genes, the CpDTC1/HpDTC1 gene and the "dehydrogenase momilactone A synthase" gene tandemly arranged and inductively transcribed following stress exposure. The predicted enzymatic functions in yeast and recombinant assay and the successful pathway reconstitution in Nicotiana benthamiana suggest that it is a functional BGC responsible for momilactone production. Furthermore, in a survey of genomic sequences of a broad range of plant species, we found that momilactone BGC is limited to the two grasses (Oryza and Echinochloa) and C. plumiforme, with no synteny among these genomes. These results indicate that while the gene cluster in C. plumiforme is functionally similar to that in rice and barnyard grass, it is likely a product of convergent evolution. To the best of our knowledge, this report of a BGC for a specialized plant defense metabolite in bryophytes is unique.

Characteristics of plant circular RNAs.

Circular RNA (circRNA) is a kind of covalently closed single-stranded RNA molecules that have been proved to play important roles in transcriptional regulation of genes in diverse species. With the rapid development of bioinformatics tools, a huge number (95143) of circRNAs have been identified from different plant species, providing an opportunity for uncovering the overall characteristics of plant circRNAs. Here, based on publicly available circRNAs, we comprehensively analyzed characteristics of plant circRNAs with the help of various bioinformatics tools as well as in-house scripts and workflows, including the percentage of coding genes generating circRNAs, the frequency of alternative splicing events of circRNAs, the non-canonical splicing signals of circRNAs and the networks involving circRNAs, miRNAs and mRNAs. All this information has been integrated into an upgraded online database, PlantcircBase 3.0 (http://ibi.zju.edu.cn/plantcircbase/). In this database, we provided browse, search and visualization tools as well as a web-based blast tool, BLASTcirc, for prediction of circRNAs from query sequences based on searching against plant genomes and transcriptomes.

scDetect: a rank-based ensemble learning algorithm for cell type identification of single-cell RNA sequencing in cancer.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) has enabled the characterization of different cell types in many tissues and tumor samples. Cell type identification is essential for single-cell RNA profiling, currently transforming the life sciences. Often, this is achieved by searching for combinations of genes that have previously been implicated as being cell-type specific, an approach that is not quantitative and does not explicitly take advantage of other scRNA-seq studies. Batch effects and different data platforms greatly decrease the predictive performance in inter-laboratory and different data type validation. RESULTS: Here, we present a new ensemble learning method named as 'scDetect' that combines gene expression rank-based analysis and a majority vote ensemble machine-learning probability-based prediction method capable of highly accurate classification of cells based on scRNA-seq data by different sequencing platforms. Because of tumor heterogeneity, in order to accurately predict tumor cells in the single-cell RNA-seq data, we have also incorporated cell copy number variation consensus clustering and epithelial score in the classification. We applied scDetect to scRNA-seq data from pancreatic tissue, mononuclear cells and tumor biopsies cells and show that scDetect classified individual cells with high accuracy and better than other publicly available tools. AVAILABILITY AND IMPLEMENTATION: scDetect is an open source software. Source code and test data is freely available from Github (https://github.com/IVDgenomicslab/scDetect/) and Zenodo (https://zenodo.org/record/4764132#.YKCOlrH5AYN). The examples and tutorial page is at https://ivdgenomicslab.github.io/scDetect-Introduction/. And scDetect will be available from Bioconductor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Recent origination of circular RNAs in plants.

Circular RNA (circRNA) is a kind of new regulatory RNA with diverse biological functions. Numerous circRNAs have been identified in many plant species; however, evolution of plant circRNAs remains largely unknown. In this study, we assembled full-length sequences of 6519 rice (Oryza sativa) circRNAs and analyzed their conservation in another 46 plant species based on comparison of sequences and expression patterns. We found that, at the genomic level, 8.7% of the 6519 circRNAs were conserved in dicotyledonous plants and 49.1% in Oryza genus. Meanwhile, 57.8% of parental protein-coding genes of the rice circRNAs originated recently after divergence of monocotyledonous plants, implying recent origin of the majority of rice circRNAs, a conclusion further supported by the results based on analysis of 4663 full-length circRNAs in Arabidopsis thaliana. Accordingly, we proposed three models to address the origination of different types of circRNAs. Taken together, the results obtained in this study provide new insights for the evolutionary dynamics of plant circRNAs and candidate circRNAs for further functional exploration.

Expansion of MIR482/2118 by a class-II transposable element in cotton.

Some plant microRNA (miRNA) families contain multiple members generating identical or highly similar mature miRNA variants. Mechanisms underlying the expansion of miRNA families remain elusive, although tandem and/or segmental duplications have been proposed. In this study of two tetraploid cottons, Gossypium hirsutum and Gossypium barbadense, and their extant diploid progenitors, Gossypium arboreum and Gossypium raimondii, we investigated the gain and loss of members of the miR482/2118 superfamily, which modulates the expression of nucleotide-binding site leucine-rich repeat (NBS-LRR) disease resistance genes. We found significant expansion of MIR482/2118d in G. barbadense, G. hirsutum and G. raimondii, but not in G. arboreum. Several newly expanded MIR482/2118d loci have mutated to produce different miR482/2118 variants with altered target-gene specificity. Based on detailed analysis of sequences flanking these MIR482/2118 loci, we found that this expansion of MIR482/2118d and its derivatives resulted from an initial capture of an MIR482/2118d by a class-II DNA transposable element (TE) in G. raimondii prior to the tetraploidization event, followed by transposition to new genomic locations in G. barbadense, G. hirsutum and G. raimondii. The 'GosTE' involved in the capture and proliferation of MIR482/2118d and its derivatives belongs to the PIF/Harbinger superfamily, generating a 3-bp target site duplication upon insertion at new locations. All orthologous MIR482/2118 loci in the two diploids were retained in the two tetraploids, but mutation(s) in miR482/2118 were observed across all four species as well as in different cultivars of both G. barbadense and G. hirsutum, suggesting a dynamic co-evolution of miR482/2118 and its NBS-LRR targets. Our results provide fresh insights into the mechanisms contributing to MIRNA proliferation and enrich our knowledge on TEs.

Effects of Sample Size on Plant Single-Cell RNA Profiling.

Single-cell RNA (scRNA) profiling or scRNA-sequencing (scRNA-seq) makes it possible to parallelly investigate diverse molecular features of multiple types of cells in a given plant tissue and discover cell developmental processes. In this study, we evaluated the effects of sample size (i.e., cell number) on the outcome of single-cell transcriptome analysis by sampling different numbers of cells from a pool of ~57,000 Arabidopsis thaliana root cells integrated from five published studies. Our results indicated that the most significant principal components could be achieved when 20,000-30,000 cells were sampled, a relatively high reliability of cell clustering could be achieved by using ~20,000 cells with little further improvement by using more cells, 96% of the differentially expressed genes could be successfully identified with no more than 20,000 cells, and a relatively stable pseudotime could be estimated in the subsample with 5000 cells. Finally, our results provide a general guide for optimizing sample size to be used in plant scRNA-seq studies.

Identification and Characterization of γ-Ray-Induced Mutations in Rice Cytoplasmic Genomes by Whole-Genome Sequencing.

Chloroplasts and mitochondria are semi-autonomous organelles and have their own genomes (cytoplasmic genomes). Physical radiations (e.g., γ-rays) have been widely used in artificial mutation induction for plant germplasm enhancement and for breeding new cultivars. However, little is known at the genomic level about which kind of cytoplasmic mutations and/or characteristics could be induced in plants. The present study aimed to investigate the type, number, and distribution of inheritable cytoplasmic mutations induced by γ-rays in rice (Oryza sativa L.). Six plants were selected from the 2nd generation (M2) populations after γ-ray (137Cs) irradiation of the rice cultivar Nipponbare, 2 each for the 3 irradiation doses (150, 250, and 350 Gy), and their genomes were sequenced on an Illumina platform. Together with the whole-genome sequencing data of 3 external Nipponbare control plants, single-base substitutions (SBSs) and insertions/deletions (InDels) in chloroplast (cp) and mitochondrial (mt) genomes were identified and analyzed in-depth using bioinformatic tools. The majority of SBSs and InDels identified were background mutations in the 6 M2 plants, and the number of induced mutations varied greatly among the plants. Most induced mutations were present in a heterogeneous state, reflecting the fact that multiple cp and mt copies existed in the progenitor cells. The induced mutations were distributed in different genomic regions in the 6 M2 plants, including exonic regions, but none of them was predicted to cause nonsynonymous mutations or frameshifts. Our study thus revealed, at the genomic level, characteristics of cytoplasmic mutations induced by γ-rays in rice.

Aldo-keto Reductase Metabolizes Glyphosate and Confers Glyphosate Resistance in Echinochloa colona.

Glyphosate, the most commonly used herbicide in the world, controls a wide range of plant species, mainly because plants have little capacity to metabolize (detoxify) glyphosate. Massive glyphosate use has led to world-wide evolution of glyphosate-resistant (GR) weed species, including the economically damaging grass weed Echinochloa colona An Australian population of E colona has evolved resistance to glyphosate with unknown mechanisms that do not involve the glyphosate target enzyme 5-enolpyruvylshikimate-3-P synthase. GR and glyphosate-susceptible (S) lines were isolated from this population and used for resistance gene discovery. RNA sequencing analysis and phenotype/genotype validation experiments revealed that one aldo-keto reductase (AKR) contig had higher expression and higher resultant AKR activity in GR than S plants. Two full-length AKR (EcAKR4-1 and EcAKR4-2) complementary DNA transcripts were cloned with identical sequences between the GR and S plants but were upregulated in the GR plants. Rice (Oryza sativa) calli and seedlings overexpressing EcAKR4-1 and displaying increased AKR activity were resistant to glyphosate. EcAKR4-1 expressed in Escherichia coli can metabolize glyphosate to produce aminomethylphosphonic acid and glyoxylate. Consistent with these results, GR E colona plants exhibited enhanced capacity for detoxifying glyphosate into aminomethylphosphonic acid and glyoxylate. Structural modeling predicted that glyphosate binds to EcAKR4-1 for oxidation, and metabolomics analysis of EcAKR4-1 transgenic rice seedlings revealed possible redox pathways involved in glyphosate metabolism. Our study provides direct experimental evidence of the evolution of a plant AKR that metabolizes glyphosate and thereby confers glyphosate resistance.

A transcriptomic profile of topping responsive non-coding RNAs in tobacco roots (Nicotiana tabacum).

BACKGROUND: Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long ncRNAs (lncRNAs) and circular RNAs (circRNAs), accomplish remarkable variety of biological functions. However, the composition of ncRNAs and their interactions with coding RNAs in modulating and controlling of cellular process in plants is largely unknown. Using a diverse group of high-throughput sequencing strategies, the mRNA, miRNA, lncRNA and circRNA compositions of tobacco (Nicotiana tabacum) roots determined and their alteration and potential biological functions in response to topping treatment analyzed. RESULTS: A total of 688 miRNAs, 7423 non-redundant lncRNAs and 12,414 circRNAs were identified, among which, some selected differentially expressed RNAs were verified by quantitative real-time PCR. Using the differentially expressed RNAs, a co-expression network was established that included all four types of RNAs. The number of circRNAs identified were higher than that of miRNAs and lncRNAs, but only two circRNAs were present in the co-expression network. LncRNAs appear to be the most active ncRNAs based on their numbers presented in the co-expression network, but none of them seems to be an eTM (endogenous Target Mimicry) of miRNAs. Integrated with analyses of sequence interaction, several mRNA-circRNA-miRNA interaction networks with a potential role in the regulation of nicotine biosynthesis were uncovered, including a QS-circQS-miR6024 interaction network. In this network miR6024 was significantly down-regulated, while the expression levels of its two targets, circQS and its host gene QS, were sharply increased following the topping treatment. CONCLUSIONS: These results illustrated the transcriptomic profiles of tobacco roots, the organ responsible for nicotine biosynthesis. mRNAs always play the most important roles, while ncRNAs are also expressed extensively for topping treatment response, especially circRNAs are the most activated in the ncRNA pool. These studies also provided insights on the coordinated regulation module of coding and non-coding RNAs in a single plant biological sample. The findings reported here indicate that ncRNAs appear to form interaction complex for the regulation of stress response forming regulation networks with transcripts involved in nicotine biosynthesis in tobacco.

Characterization and evolution of gene clusters for terpenoid phytoalexin biosynthesis in tobacco.

MAIN CONCLUSION: The study performed genome-wide identification, characterization and evolution analysis of gene clusters for phytoalexin terpenoid biosynthesis in tobacco, and specifically illustrated ones for capsidiol, an efficient defensive specialized metabolite. Terpenoid phytoalexins play an important role in plant self-defense against pest and pathogen attack. Terpenoid biosynthesis involves terpene synthase and cytochrome P450, which always locate and function as cluster(s). In this study, we performed genome-wide investigation of metabolic gene clusters involved in terpenoid production in tobacco (Nicotiana tabacum). Due to the complexity of the tobacco genome, we modified a published prediction pipeline to reduce the influence of the large number of repeats and to improve the annotation of tobacco genes with respect to their metabolic functions. We identified 1181 metabolic gene clusters with 34 of them potentially being involved in terpenoid biosynthesis. Through integration with transcriptome and metabolic pathway annotation analyses, 3 of the 34 terpenoid biosynthesis-related gene clusters were determined to be high-confidence ones, with 2 involved in biosynthesis of capsidiol, a terpenoid recognized as 1 of the effective resistance compounds in the Nicotiana species. The capsidiol-related gene cluster was conserved in N. sylvestris, N. tomentosiformis and N. attenuate. Our findings demonstrate that phytoalexins in tobacco can arise from operon-like gene clusters, a genomic pattern characterized as being beneficial for rapid stress response, gene co-regulation, co-function and co-heredity.

Genome-wide selection footprints and deleterious variations in young Asian allotetraploid rapeseed.

Brassica napus (AACC, 2n = 38) is an important oilseed crop grown worldwide. However, little is known about the population evolution of this species, the genomic difference between its major genetic groups, such as European and Asian rapeseed, and the impacts of historical large-scale introgression events on this young tetraploid. In this study, we reported the de novo assembly of the genome sequences of an Asian rapeseed (B. napus), Ningyou 7, and its four progenitors and compared these genomes with other available genomic data from diverse European and Asian cultivars. Our results showed that Asian rapeseed originally derived from European rapeseed but subsequently significantly diverged, with rapid genome differentiation after hybridization and intensive local selective breeding. The first historical introgression of B. rapa dramatically broadened the allelic pool but decreased the deleterious variations of Asian rapeseed. The second historical introgression of the double-low traits of European rapeseed (canola) has reshaped Asian rapeseed into two groups (double-low and double-high), accompanied by an increase in genetic load in the double-low group. This study demonstrates distinctive genomic footprints and deleterious SNP (single nucleotide polymorphism) variants for local adaptation by recent intra- and interspecies introgression events and provides novel insights for understanding the rapid genome evolution of a young allopolyploid crop.

The red bayberry genome and genetic basis of sex determination.

Morella rubra, red bayberry, is an economically important fruit tree in south China. Here, we assembled the first high-quality genome for both a female and a male individual of red bayberry. The genome size was 313-Mb, and 90% sequences were assembled into eight pseudo chromosome molecules, with 32 493 predicted genes. By whole-genome comparison between the female and male and association analysis with sequences of bulked and individual DNA samples from female and male, a 59-Kb region determining female was identified and located on distal end of pseudochromosome 8, which contains abundant transposable element and seven putative genes, four of them are related to sex floral development. This 59-Kb female-specific region was likely to be derived from duplication and rearrangement of paralogous genes and retained non-recombinant in the female-specific region. Sex-specific molecular markers developed from candidate genes co-segregated with sex in a genetically diverse female and male germplasm. We propose sex determination follow the ZW model of female heterogamety. The genome sequence of red bayberry provides a valuable resource for plant sex chromosome evolution and also provides important insights for molecular biology, genetics and modern breeding in Myricaceae family.