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Short interspersed nuclear elements (SINEs) are a widespread type of small transposable element (TE). With increasing evidence for their impact on gene function and genome evolution in plants, accurate genome-scale SINE annotation becomes a fundamental step for studying the regulatory roles of SINEs and their relationship with other components in the genomes. Despite the overall promising progress made in TE annotation, SINE annotation remains a major challenge. Unlike some other TEs, SINEs are short and heterogeneous, and they usually lack well-conserved sequence or structural features. Thus, current SINE annotation tools have either low sensitivity or high false discovery rates. Given the demand and challenges, we aimed to provide a more accurate and efficient SINE annotation tool for plant genomes. The pipeline starts with maximizing the pool of SINE candidates via profile hidden Markov model-based homology search and de novo SINE search using structural features. Then, it excludes the false positives by integrating all known features of SINEs and the features of other types of TEs that can often be misannotated as SINEs. As a result, the pipeline substantially improves the tradeoff between sensitivity and accuracy, with both values close to or over 90%. We tested our tool in Arabidopsis thaliana and rice (Oryza sativa), and the results show that our tool competes favorably against existing SINE annotation tools. The simplicity and effectiveness of this tool would potentially be useful for generating more accurate SINE annotations for other plant species. The pipeline is freely available at https://github.com/yangli557/AnnoSINE.

 

Abstract The majority of sequenced genomes in the monocots are from species belonging to Poaceae, which include many commercially important crops. Here, we expand the number of sequenced genomes from the monocots to include the genomes of 4 related cyperids: Carex cristatella and Carex scoparia from Cyperaceae and Juncus effusus and Juncus inflexus from Juncaceae. The high-quality, chromosome-scale genome sequences from these 4 cyperids were assembled by combining whole-genome shotgun sequencing of Nanopore long reads, Illumina short reads, and Hi-C sequencing data. Some members of the Cyperaceae and Juncaceae are known to possess holocentric chromosomes. We examined the repeat landscapes in our sequenced genomes to search for potential repeats associated with centromeres. Several large satellite repeat families, comprising 3.2–9.5% of our sequenced genomes, showed dispersed distribution of large satellite repeat clusters across all Carex chromosomes, with few instances of these repeats clustering in the same chromosomal regions. In contrast, most large Juncus satellite repeats were clustered in a single location on each chromosome, with sporadic instances of large satellite repeats throughout the Juncus genomes. Recognizable transposable elements account for about 20% of each of the 4 genome assemblies, with the Carex genomes containing more DNA transposons than retrotransposons while the converse is true for the Juncus genomes. These genome sequences and annotations will facilitate better comparative analysis within monocots. 

Canonical CRISPR-Cas9 genome editing technique has profoundly impacted the fields of plant biology, biotechnology, and crop improvement. Since non-homologous end joining (NHEJ) is usually considered to generate random indels, its high efficiency mutation is generally not pertinent to precise editing. Homology-directed repair (HDR) can mediate precise editing with supplied donor DNA, but it suffers from extreme low efficiency in higher plants. Therefore, precision editing in plants will be facilitated by the ability to predict NHEJ repair outcome and to improve HDR efficiency. Here, we report that NHEJ-mediated single nucleotide insertion at different rice genes is predictable based on DNA sequences at the target loci. Three mutation prediction tools (inDelphi, FORECasT, and SPROUT) have been validated in the rice plant system. We also evaluated the chimeric guide RNA (cgRNA) and Cas9-Retron precISe Parallel Editing via homologY (CRISPEY) strategies to facilitate donor template supply for improving HDR efficiency in Nicotiana benthamiana and rice. However, neither cgRNA nor CRISPEY improved plant HDR editing efficiency in this study. Interestingly, our data indicate that tethering of 200–250 nucleotides long sequence to either 5′ or 3′ ends of guide RNA did not significantly affect Cas9 cleavage activity. 

Abstract Motivation The standard bootstrap method is used throughout science and engineering to perform general-purpose non-parametric resampling and re-estimation. Among the most widely cited and widely used such applications is the phylogenetic bootstrap method, which Felsenstein proposed in 1985 as a means to place statistical confidence intervals on an estimated phylogeny (or estimate ‘phylogenetic support’). A key simplifying assumption of the bootstrap method is that input data are independent and identically distributed (i.i.d.). However, the i.i.d. assumption is an over-simplification for biomolecular sequence analysis, as Felsenstein noted. Results In this study, we introduce a new sequence-aware non-parametric resampling technique, which we refer to as RAWR (‘RAndom Walk Resampling’). RAWR consists of random walks that synthesize and extend the standard bootstrap method and the ‘mirrored inputs’ idea of Landan and Graur. We apply RAWR to the task of phylogenetic support estimation. RAWR’s performance is compared to the state-of-the-art using synthetic and empirical data that span a range of dataset sizes and evolutionary divergence. We show that RAWR support estimates offer comparable or typically superior type I and type II error compared to phylogenetic bootstrap support. We also conduct a re-analysis of large-scale genomic sequence data from a recent study of Darwin’s finches. Our findings clarify phylogenetic uncertainty in a charismatic clade that serves as an important model for complex adaptive evolution. Availability and implementation Data and software are publicly available under open-source software and open data licenses at: https://gitlab.msu.edu/liulab/RAWR-study-datasets-and-scripts. 

Human life intimately depends on plants for food, biomaterials, health, energy, and a sustainable environment. Various plants have been genetically improved mostly through breeding, along with limited modification via genetic engineering, yet they are still not able to meet the ever-increasing needs, in terms of both quantity and quality, resulting from the rapid increase in world population and expected standards of living. A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches. This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems. Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes. From this perspective, we present a comprehensive roadmap of plant biosystems design covering theories, principles, and technical methods, along with potential applications in basic and applied plant biology research. We highlight current challenges, future opportunities, and research priorities, along with a framework for international collaboration, towards rapid advancement of this emerging interdisciplinary area of research. Finally, we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception, trust, and acceptance.