Comparative analysis of miniature inverted-repeat transposable elements (MITEs) and long terminal repeat (LTR) retrotransposons in six Citrus species.

BACKGROUND: Miniature inverted-repeat transposable elements (MITEs) and long terminal repeat (LTR) retrotransposons are ubiquitous in plants genomes, and highly important in their evolution and diversity. However, their mechanisms of insertion/amplification and roles in Citrus genome's evolution/diversity are still poorly understood. RESULTS: To address this knowledge gap, we developed different computational pipelines to analyze, annotate and classify MITEs and LTR retrotransposons in six different sequenced Citrus species. We identified 62,010 full-length MITEs from 110 distinguished families. We observed MITEs tend to insert in gene related regions and enriched in promoters. We found that DTM63 is possibly an active Mutator-like MITE family in the traceable past and may still be active in Citrus. The insertion of MITEs resulted in massive polymorphisms and played an important role in Citrus genome diversity and gene structure variations. In addition, 6630 complete LTR retrotransposons and 13,371 solo-LTRs were identified. Among them, 12 LTR lineages separated before the differentiation of mono- and dicotyledonous plants. We observed insertion and deletion of LTR retrotransposons was accomplished with a dynamic balance, and their half-life in Citrus was ~ 1.8 million years. CONCLUSIONS: These findings provide insights into MITEs and LTR retrotransposons and their roles in genome diversity in different Citrus genomes.

Two haplotype-resolved genome assemblies for AAB allotriploid bananas provide insights into banana subgenome asymmetric evolution and Fusarium wilt control.

Bananas (Musa spp.) are one of the world's most important fruit crops and play a vital role in food security for many developing countries. Most banana cultivars are triploids derived from inter- and intraspecific hybridizations between the wild diploid ancestor species Musa acuminate (AA) and M. balbisiana (BB). We report two haplotype-resolved genome assemblies of the representative AAB-cultivated types, Plantain and Silk, and precisely characterize ancestral contributions by examining ancestry mosaics across the genome. Widespread asymmetric evolution is observed in their subgenomes, which can be linked to frequent homologous exchange events. We reveal the genetic makeup of triploid banana cultivars and verify that subgenome B is a rich source of disease resistance genes. Only 58.5% and 59.4% of Plantain and Silk genes, respectively, are present in all three haplotypes, with >50% of genes being differentially expressed alleles in different subgenomes. We observed that the number of upregulated genes in Plantain is significantly higher than that in Silk at one-week post-inoculation with Fusarium wilt tropical race 4 (Foc TR4), which confirms that Plantain can initiate defense responses faster than Silk. Additionally, we compared genomic and transcriptomic differences among the genes related to carotenoid synthesis and starch metabolism between Plantain and Silk. Our study provides resources for better understanding the genomic architecture of cultivated bananas and has important implications for Musa genetics and breeding.

Ribosome profiling reveals the translational landscape and allele-specific translational efficiency in rice.

Translational regulation is a critical step in the process of gene expression and governs the synthesis of proteins from mRNAs. Many studies have revealed translational regulation in plants in response to various environmental stimuli. However, there have been no studies documenting the comprehensive landscape of translational regulation and allele-specific translational efficiency in multiple plant tissues, especially those of rice, a main staple crop that feeds nearly half of the world's population. Here we used RNA sequencing and ribosome profiling data to analyze the transcriptome and translatome of an elite hybrid rice, Shanyou 63 (SY63), and its parental varieties Zhenshan 97 and Minghui 63. The results revealed that gene expression patterns varied more among tissues than among varieties at the transcriptional and translational levels. We identified 3392 upstream open reading frames (uORFs), and the uORF-containing genes were enriched in transcription factors. Only 668 of 13 492 long non-coding RNAs could be translated into peptides. Finally, we discovered numerous genes with allele-specific translational efficiency in SY63 and demonstrated that some cis-regulatory elements may contribute to allelic divergence in translational efficiency. Overall, these findings may improve our understanding of translational regulation in rice and provide information for molecular breeding research.

A multi-omics integrative network map of maize.

Networks are powerful tools to uncover functional roles of genes in phenotypic variation at a system-wide scale. Here, we constructed a maize network map that contains the genomic, transcriptomic, translatomic and proteomic networks across maize development. This map comprises over 2.8 million edges in more than 1,400 functional subnetworks, demonstrating an extensive network divergence of duplicated genes. We applied this map to identify factors regulating flowering time and identified 2,651 genes enriched in eight subnetworks. We validated the functions of 20 genes, including 18 with previously unknown connections to flowering time in maize. Furthermore, we uncovered a flowering pathway involving histone modification. The multi-omics integrative network map illustrates the principles of how molecular networks connect different types of genes and potential pathways to map a genome-wide functional landscape in maize, which should be applicable in a wide range of species.

[A cross-sectional study about the effects of residential exposure to power transmission line on human nervous system symptoms and hematology].

OBJECTIVE: To investigate the possible effects on nervous system and health condition under the exposure to electromagnetic field. METHODS: Take the resident around the power transmission line as the objects and were divided into 3 groups by the distance from the power transmission line 20 m, 100 m and 500 m, respectively. Some living conditions and health conditions were recorded by face-to-face the questionnaire survey, and Hematological indices of each groups were examined including IgG, IgM, leukocyte formulae, erythrocyte, hemoglobin and platelet. RESULTS: There was no significant difference in each group, according exposure of daily life, such as drinking and smoking (P > 0.05). Compared with the each distance groups, it was presented significant difference between the distance from the power transmission line and the incidence of headache or dizziness, insomnia and easy weary and so on (P < 0.05). In hematology aspect, with the horizontal distance from the power transmission line decreasing, PLT level of residents was reductive and the difference was statistically significant (P < 0.001), whereas leukocyte formulae, erythrocyte, hemoglobin, IgG and IgM had no significant difference among each group (P < 0.05). CONCLUSION: Closely exposure to electromagnetic field may induce headache and so on and decrease the level of PLT.

Evolution Analyses of CAMTA Transcription Factor in Plants and Its Enhancing Effect on Cold-tolerance.

The calmodulin binding transcription activator (CAMTA) is a transcription factor that is widely present in eukaryotes with conserved structure. It contributes to the response to biotic and abiotic stresses and promotes the growth and development of plants. Although previous studies have investigated the number and function of CAMTAs in some species, there is still a lack of comprehensive understanding of the evolutionary process, phylogenetic relationship, expression patterns, and functions of CAMTAs in plants. Here we identified 465 CMATA genes from 112 plants and systematically studied the origin of CAMTA family, gene expansion, functional differentiation, gene structure, and conservative motif distribution. Based on these analyses, we presented the evidence that CAMTA family was originated from chlorophyta, and we speculated that CAMTA might experience obvious structure variation during its early evolution, and that the number of CAMTA genes might gradually increase in higher plants. To reveal potential functions of CAMTA genes, we analyzed the expression patterns of 12 representative species and found significant species specificity, tissue specificity, and developmental stage specificity of CAMTAs. The results also indicated that the CAMTA genes might promote the maturation and senescence. The expression levels and regulatory networks of CAMTAs revealed that CAMTAs could enhance cold tolerance of rice by regulating carbohydrate metabolism-related genes to accumulate carbohydrates or by modulating target genes together with other transcription factors. Our study provides an insight into the molecular evolution of CAMTA family and lays a foundation for further study of related biological functions.

Phasing analysis of the transcriptome and epigenome in a rice hybrid reveals the inheritance and difference in DNA methylation and allelic transcription regulation.

Hybrids are always a focus of botanical research and have a high practical value in agricultural production. To better understand allele regulation and differences in DNA methylation in hybrids, we developed a phasing pipeline for hybrid rice based on two parental genomes (PP2PG), which is applicable for Iso-Seq, RNA-Seq, and Bisulfite sequencing (BS-Seq). Using PP2PG, we analyzed differences in gene transcription, alternative splicing, and DNA methylation in an allele-specific manner between parents and progeny or different progeny alleles. The phasing of Iso-Seq data provided a great advantage in separating the whole gene structure and producing a significantly higher separation ratio than RNA-Seq. The interaction of hybrid alleles was studied by constructing an allele co-expression network that revealed the dominant allele effect in the network. The expression variation between parents and the parental alleles in progeny showed tissue- or environment-specific patterns, which implied a preference for trans-acting regulation under different conditions. In addition, by comparing allele-specific DNA methylation, we found that CG methylation was more likely to be inherited than CHG and CHH methylation, and its enrichment in genic regions was connected to gene structure. In addition to an effective phasing pipeline, we also identified differentiation in OsWAK38 gene structure that may have led to the expansion of allele functions in hybrids. In summary, we developed a phasing pipeline and provided valuable insights into alternative splicing, interaction networks, trans-acting regulation, and the inheritance of DNA methylation in hybrid rice.

Analysis of Rice Transcriptome Reveals the LncRNA/CircRNA Regulation in Tissue Development.

BACKGROUND: Long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) can play important roles in many biological processes. However, no study of the influence of epigenetics factors or the 3D structure of the genome in their regulation is available in plants. RESULTS: In the current analysis, we identified a total of 15,122 lncRNAs and 7902 circRNAs in three tissues (root, leaf and panicle) in the rice varieties Minghui 63, Zhenshan 97 and their hybrid Shanyou 63. More than 73% of these lncRNAs and parental genes of circRNAs (P-circRNAs) are shared among Oryza sativa with high expression specificity. We found that, compared with protein-coding genes, the loci of these lncRNAs have higher methylation levels and the loci of circRNAs tend to locate in the middle of genes with high CG and CHG methylation. Meanwhile, the activated lncRNAs and P-circRNAs are mainly transcribed from demethylated regions containing CHH methylation. In addition, ~ 53% lncRNAs and ~ 15% P-circRNAs are associated with transposable elements (TEs), especially miniature inverted-repeat transposable elements and RC/Helitron. We didn't find correlation between the expression of lncRNAs and histone modifications; however, we found that the binding strength and interaction of RNAPII significantly affects lncRNA expression. Interestingly, P-circRNAs tend to combine active histone modifications. Finally, we found that lncRNAs and circRNAs acting as competing-endogenous RNAs have the potential to regulate the expression of genes, such as osa-156 l-5p (related to yield) and osa-miR444a-3p (related to N/P metabolism) confirmed through dual-luciferase reporter assays, with important roles in the growth and development of rice, laying a foundation for future rice breeding analyses. CONCLUSIONS: In conclusion, our study comprehensively analyzed the important regulatory roles of lncRNA/circRNA in the tissue development of Indica rice from multiple perspectives.

Two gap-free reference genomes and a global view of the centromere architecture in rice.

Rice (Oryza sativa), a major staple throughout the world and a model system for plant genomics and breeding, was the first crop genome sequenced almost two decades ago. However, reference genomes for all higher organisms to date contain gaps and missing sequences. Here, we report the assembly and analysis of gap-free reference genome sequences for two elite O. sativa xian/indica rice varieties, Zhenshan 97 and Minghui 63, which are being used as a model system for studying heterosis and yield. Gap-free reference genomes provide the opportunity for a global view of the structure and function of centromeres. We show that all rice centromeric regions share conserved centromere-specific satellite motifs with different copy numbers and structures. In addition, the similarity of CentO repeats in the same chromosome is higher than across chromosomes, supporting a model of local expansion and homogenization. Both genomes have over 395 non-TE genes located in centromere regions, of which ∼41% are actively transcribed. Two large structural variants at the end of chromosome 11 affect the copy number of resistance genes between the two genomes. The availability of the two gap-free genomes lays a solid foundation for further understanding genome structure and function in plants and breeding climate-resilient varieties.

Influenza infection elicits an expansion of gut population of endogenous Bifidobacterium animalis which protects mice against infection.

BACKGROUND: Influenza is a severe respiratory illness that continually threatens global health. It has been widely known that gut microbiota modulates the host response to protect against influenza infection, but mechanistic details remain largely unknown. Here, we took advantage of the phenomenon of lethal dose 50 (LD50) and metagenomic sequencing analysis to identify specific anti-influenza gut microbes and analyze the underlying mechanism. RESULTS: Transferring fecal microbes from mice that survive virulent influenza H7N9 infection into antibiotic-treated mice confers resistance to infection. Some gut microbes exhibit differential features to lethal influenza infection depending on the infection outcome. Bifidobacterium pseudolongum and Bifidobacterium animalis levels are significantly elevated in surviving mice when compared to dead or mock-infected mice. Oral administration of B. animalis alone or the combination of both significantly reduces the severity of H7N9 infection in both antibiotic-treated and germ-free mice. Functional metagenomic analysis suggests that B. animalis mediates the anti-influenza effect via several specific metabolic molecules. In vivo tests confirm valine and coenzyme A produce an anti-influenza effect. CONCLUSIONS: These findings show that the severity of influenza infection is closely related to the heterogeneous responses of the gut microbiota. We demonstrate the anti-influenza effect of B. animalis, and also find that the gut population of endogenous B. animalis can expand to enhance host influenza resistance when lethal influenza infection occurs, representing a novel interaction between host and gut microbiota. Further, our data suggest the potential utility of Bifidobacterium in the prevention and as a prognostic predictor of influenza.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

A coherent framework for multiresolution analysis of biological networks with "memory": Ras pathway, cell cycle, and immune system.

Various biological processes exhibit characteristics that vary dramatically in response to different input conditions or changes in the history of the process itself. One of the examples studied here, the Ras-PKC-mitogen-activated protein kinase (MAPK) bistable pathway, follows two distinct dynamics (modes) depending on duration and strength of EGF stimulus. Similar examples are found in the behavior of the cell cycle and the immune system. A classification methodology, based on time-frequency analysis, was developed and tested on these systems to understand global behavior of biological processes. Contrary to most traditionally used statistical and spectral methods, our approach captures complex functional relations between parts of the systems in a simple way. The resulting algorithms are capable of analyzing and classifying sets of time-series data obtained from in vivo or in vitro experiments, or in silico simulation of biological processes. The method was found to be considerably stable under stochastic noise perturbation and, therefore, suitable for the analysis of real experimental data.

Shrinkage-based similarity metric for cluster analysis of microarray data.

The current standard correlation coefficient used in the analysis of microarray data was introduced by M. B. Eisen, P. T. Spellman, P. O. Brown, and D. Botstein [(1998) Proc. Natl. Acad. Sci. USA 95, 14863-14868]. Its formulation is rather arbitrary. We give a mathematically rigorous correlation coefficient of two data vectors based on James-Stein shrinkage estimators. We use the assumptions described by Eisen et al., also using the fact that the data can be treated as transformed into normal distributions. While Eisen et al. use zero as an estimator for the expression vector mean mu, we start with the assumption that for each gene, mu is itself a zero-mean normal random variable [with a priori distribution N(0,tau 2)], and use Bayesian analysis to obtain a posteriori distribution of mu in terms of the data. The shrunk estimator for mu differs from the mean of the data vectors and ultimately leads to a statistically robust estimator for correlation coefficients. To evaluate the effectiveness of shrinkage, we conducted in silico experiments and also compared similarity metrics on a biological example by using the data set from Eisen et al. For the latter, we classified genes involved in the regulation of yeast cell-cycle functions by computing clusters based on various definitions of correlation coefficients and contrasting them against clusters based on the activators known in the literature. The estimated false positives and false negatives from this study indicate that using the shrinkage metric improves the accuracy of the analysis.