Generic Repeat Finder: A High-Sensitivity Tool for Genome-Wide De Novo Repeat Detection

CicerSpTEdb: A web-based database for high-resolution genome-wide identification of transposable elements in Cicer species

Recently, Cicer species have experienced increased research interest due to their economic importance, especially in genetics, genomics, and crop improvement. The Cicer arietinum, Cicer reticulatum, and Cicer echinospermum genomes have been sequenced and provide valuable resources for trait improvement. Since the publication of the chickpea draft genome, progress has been made in genome assembly, functional annotation, and identification of polymorphic markers. However, work is still needed to identify transposable elements (TEs) and make them available for researchers. In this paper, we present CicerSpTEdb, a comprehensive TE database for Cicer species that aims to improve our understanding of the organization and structural variations of the chickpea genome. Using structure and homology-based methods, 3942 C. echinospermum, 3579 C. reticulatum, and 2240 C. arietinum TEs were identified. Comparisons between Cicer species indicate that C. echinospermum has the highest number of LTR-RT and hAT TEs. C. reticulatum has more Mutator, PIF Harbinger, Tc1 Mariner, and CACTA TEs, while C. arietinum has the highest number of Helitron. CicerSpTEdb enables users to search and visualize TEs by location and download their results. The database will provide a powerful resource that can assist in developing TE target markers for molecular breeding and answer related biological questions. Database URL: http://cicersptedb.easyomics.org/index.php.

Assemblies of the genomes of parasitic wasps using meta-assembly and scaffolding with genetic linkage

Safe, effective biological-control introductions against invasive pests depend on narrowly host-specific natural enemies with the ability to adapt to a changing environment. As part of a project on the genetic architectures of these traits, we assembled and annotated the genomes of two aphid parasitoids, Aphelinus atriplicis and Aphelinus certus. We report here several assemblies of A. atriplicis made with Illumina and PacBio data, which we combined into a meta-assembly. We scaffolded the meta-assembly with markers from a genetic map of hybrids between A. atriplicis and A. certus. We used this genetic-linkage scaffolded (GLS) assembly of A. atriplicis to scaffold a de novo assembly of A. certus. The de novo assemblies of A. atriplicis differed in contiguity, and the meta-assembly of these assemblies was more contiguous than the best de novo assembly. Scaffolding with genetic-linkage data allowed chromosomal-level assembly of the A. atriplicis genome and scaffolding a de novo assembly of A. certus with this GLS assembly, greatly increased the contiguity of the A. certus assembly to the point where it was also at the chromosomal-level. However, completeness of the A. atriplicis assembly, as measured by percent complete, single-copy BUSCO hymenopteran genes, varied little among de novo assemblies and was not increased by meta-assembly or genetic scaffolding. Furthermore, the greater contiguity of the meta-assembly and GLS assembly had little or no effect on the numbers of genes identified, the proportions with homologs or functional annotations. Increased contiguity of the A. certus assembly provided modest improvement in assembly completeness, as measured by percent complete, single-copy BUSCO hymenopteran genes. The total genic sequence increased, and while the number of genes declined, gene length increased, which together suggest greater accuracy of gene models. More contiguous assemblies provide uses other than gene annotation, for example, identifying the genes associated with quantitative trait loci and understanding of chromosomal rearrangements associated with speciation.

Opfi: A Python package for identifying gene clusters in large genomics and metagenomics data sets

Gene clusters are sets of co-localized, often contiguous genes that together perform specific functions, many of which are relevant to biotechnology. There is a need for software tools that can extract candidate gene clusters from vast amounts of available genomic data. Therefore, we developed Opfi: a modular pipeline for identification of arbitrary gene clusters in assembled genomic or metagenomic sequences. Opfi contains functions for annotation, de-deduplication, and visualization of putative gene clusters. It utilizes a customizable rule-based filtering approach for selection of candidate systems that adhere to user-defined criteria. Opfi is implemented in Python, and is available on the Python Package Index and on Bioconda (Grüning et al., 2018).

A sensitive repeat identification framework based on short and long reads

Numerous studies have shown that repetitive regions in genomes play indispensable roles in the evolution, inheritance and variation of living organisms. However, most existing methods cannot achieve satisfactory performance on identifying repeats in terms of both accuracy and size, since NGS reads are too short to identify long repeats whereas SMS (Single Molecule Sequencing) long reads are with high error rates. In this study, we present a novel identification framework, LongRepMarker, based on the global de novo assembly and k-mer based multiple sequence alignment for precisely marking long repeats in genomes. The major characteristics of LongRepMarker are as follows: (i) by introducing barcode linked reads and SMS long reads to assist the assembly of all short paired-end reads, it can identify the repeats to a greater extent; (ii) by finding the overlap sequences between assemblies or chomosomes, it locates the repeats faster and more accurately; (iii) by using the multi-alignment unique k-mers rather than the high frequency k-mers to identify repeats in overlap sequences, it can obtain the repeats more comprehensively and stably; (iv) by applying the parallel alignment model based on the multi-alignment unique k-mers, the efficiency of data processing can be greatly optimized and (v) by taking the corresponding identification strategies, structural variations that occur between repeats can be identified. Comprehensive experimental results show that LongRepMarker can achieve more satisfactory results than the existing de novo detection methods (https://github.com/BioinformaticsCSU/LongRepMarker).

Pan-genome analysis of 33 genetically diverse rice accessions reveals hidden genomic variations

Structural variations (SVs) and gene copy number variations (gCNVs) have contributed to crop evolution, domestication, and improvement. Here, we assembled 31 high-quality genomes of genetically diverse rice accessions. Coupling with two existing assemblies, we developed pan-genome-scale genomic resources including a graph-based genome, providing access to rice genomic variations. Specifically, we discovered 171,072 SVs and 25,549 gCNVs and used an Oryza glaberrima assembly to infer the derived states of SVs in the Oryza sativa population. Our analyses of SV formation mechanisms, impacts on gene expression, and distributions among subpopulations illustrate the utility of these resources for understanding how SVs and gCNVs shaped rice environmental adaptation and domestication. Our graph-based genome enabled genome-wide association study (GWAS)-based identification of phenotype-associated genetic variations undetectable when using only SNPs and a single reference assembly. Our work provides rich population-scale resources paired with easy-to-access tools to facilitate rice breeding as well as plant functional genomics and evolutionary biology research.

The transposable elements of the Drosophila serrata reference panel

Transposable elements (TEs) are an important component of the complex genomic ecosystem. Understanding the tempo and mode of TE proliferation, that is whether it is in maintained in transposition selection balance, or is induced periodically by environmental stress or other factors, is important for understanding the evolution of organismal genomes through time. Although TEs have been characterized in individuals or limited samples, a true understanding of the population genetics of TEs, and therefore the tempo and mode of transposition, is still lacking. Here, we characterize the TE landscape in an important model Drosophila, Drosophila serrata using the D. serrata reference panel, which is comprised of 102 sequenced inbred genotypes. We annotate the families of TEs in the D. serrata genome and investigate variation in TE copy number between genotypes. We find that many TEs have low copy number in the population, but this varies by family and includes a single TE making up to 50% of the genome content of TEs. We find that some TEs proliferate in particular genotypes compared with population levels. In addition, we characterize variation in each TE family allowing copy number to vary in each genotype and find that some TEs have diversified very little between individuals suggesting recent spread. TEs are important sources of spontaneous mutations in Drosophila, making up a large fraction of the total number of mutations in particular genotypes. Understanding the dynamics of TEs within populations will be an important step toward characterizing the origin of variation within and between species.

A Tutorial of EDTA: Extensive De Novo TE Annotator

Transposable elements (TEs) are important contributors to genome structure and evolution. With the growth of sequencing technologies, various computational pipelines and software programs have been developed to facilitate TE identification and annotation. These computational tools can be categorized into three types based on their underlying approach: homology-based, structural-based, and de novo methods. Each of these tools has advantages and disadvantages. In this chapter, we introduce EDTA (Extensive de novo TE Annotator), a new comprehensive pipeline composed of high-quality tools to identify and annotate all types of TEs. The development of EDTA is based on the benchmarking results of a collection of TE annotation methods. The selected programs are evaluated by their ability to identify true TEs as well as to exclude false candidates. Here, we present an overview of the EDTA pipeline and a detailed manual for its use. The source code of EDTA is available at https://github.com/oushujun/EDTA .

Sequence repetitiveness quantification and de novo repeat detection by weighted k-mer coverage

DNA repeats are abundant in eukaryotic genomes and have been proved to play a vital role in genome evolution and regulation. A large number of approaches have been proposed to identify various repeats in the genome. Some de novo repeat identification tools can efficiently generate sequence repetitive scores based on k-mer counting for repeat detection. However, we noticed that these tools can still be improved in terms of repetitive score calculation, sensitivity to segmental duplications and detection specificity. Therefore, here, we present a new computational approach named Repeat Locator (RepLoc), which is based on weighted k-mer coverage to quantify the genome sequence repetitiveness and locate the repetitive sequences. According to the repetitiveness map of the human genome generated by RepLoc, we found that there may be relationships between sequence repetitiveness and genome structures. A comprehensive benchmark shows that RepLoc is a more efficient k-mer counting based tool for de novo repeat detection. The RepLoc software is freely available at http://bis.zju.edu.cn/reploc.

Benchmarking transposable element annotation methods for creation of a streamlined, comprehensive pipeline

BACKGROUND

Sequencing technology and assembly algorithms have matured to the point that high-quality de novo assembly is possible for large, repetitive genomes. Current assemblies traverse transposable elements (TEs) and provide an opportunity for comprehensive annotation of TEs. Numerous methods exist for annotation of each class of TEs, but their relative performances have not been systematically compared. Moreover, a comprehensive pipeline is needed to produce a non-redundant library of TEs for species lacking this resource to generate whole-genome TE annotations.

RESULTS

We benchmark existing programs based on a carefully curated library of rice TEs. We evaluate the performance of methods annotating long terminal repeat (LTR) retrotransposons, terminal inverted repeat (TIR) transposons, short TIR transposons known as miniature inverted transposable elements (MITEs), and Helitrons. Performance metrics include sensitivity, specificity, accuracy, precision, FDR, and F₁. Using the most robust programs, we create a comprehensive pipeline called Extensive de-novo TE Annotator (EDTA) that produces a filtered non-redundant TE library for annotation of structurally intact and fragmented elements. EDTA also deconvolutes nested TE insertions frequently found in highly repetitive genomic regions. Using other model species with curated TE libraries (maize and Drosophila), EDTA is shown to be robust across both plant and animal species.

CONCLUSIONS

The benchmarking results and pipeline developed here will greatly facilitate TE annotation in eukaryotic genomes. These annotations will promote a much more in-depth understanding of the diversity and evolution of TEs at both intra- and inter-species levels. EDTA is open-source and freely available: https://github.com/oushujun/EDTA.

Benchmarking transposable element annotation methods for creation of a streamlined, comprehensive pipeline

BACKGROUND

Sequencing technology and assembly algorithms have matured to the point that high-quality de novo assembly is possible for large, repetitive genomes. Current assemblies traverse transposable elements (TEs) and provide an opportunity for comprehensive annotation of TEs. Numerous methods exist for annotation of each class of TEs, but their relative performances have not been systematically compared. Moreover, a comprehensive pipeline is needed to produce a non-redundant library of TEs for species lacking this resource to generate whole-genome TE annotations.

RESULTS

We benchmark existing programs based on a carefully curated library of rice TEs. We evaluate the performance of methods annotating long terminal repeat (LTR) retrotransposons, terminal inverted repeat (TIR) transposons, short TIR transposons known as miniature inverted transposable elements (MITEs), and Helitrons. Performance metrics include sensitivity, specificity, accuracy, precision, FDR, and F1. Using the most robust programs, we create a comprehensive pipeline called Extensive de-novo TE Annotator (EDTA) that produces a filtered non-redundant TE library for annotation of structurally intact and fragmented elements. EDTA also deconvolutes nested TE insertions frequently found in highly repetitive genomic regions. Using other model species with curated TE libraries (maize and Drosophila), EDTA is shown to be robust across both plant and animal species.

CONCLUSIONS

The benchmarking results and pipeline developed here will greatly facilitate TE annotation in eukaryotic genomes. These annotations will promote a much more in-depth understanding of the diversity and evolution of TEs at both intra- and inter-species levels. EDTA is open-source and freely available: https://github.com/oushujun/EDTA.

Population Genomic Approaches for Weed Science

Genomic approaches are opening avenues for understanding all aspects of biological life, especially as they begin to be applied to multiple individuals and populations. However, these approaches typically depend on the availability of a sequenced genome for the species of interest. While the number of genomes being sequenced is exploding, one group that has lagged behind are weeds. Although the power of genomic approaches for weed science has been recognized, what is needed to implement these approaches is unfamiliar to many weed scientists. In this review we attempt to address this problem by providing a primer on genome sequencing and provide examples of how genomics can help answer key questions in weed science such as: (1) Where do agricultural weeds come from; (2) what genes underlie herbicide resistance; and, more speculatively, (3) can we alter weed populations to make them easier to control? This review is intended as an introduction to orient weed scientists who are thinking about initiating genome sequencing projects to better understand weed populations, to highlight recent publications that illustrate the potential for these methods, and to provide direction to key tools and literature that will facilitate the development and execution of weed genomic projects.