42
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Assessing genome assembly quality using the LTR Assembly Index (LAI)

      research-article
      1 , 2 , 3 , 1 , 2
      Nucleic Acids Research
      Oxford University Press

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Assembling a plant genome is challenging due to the abundance of repetitive sequences, yet no standard is available to evaluate the assembly of repeat space. LTR retrotransposons (LTR-RTs) are the predominant interspersed repeat that is poorly assembled in draft genomes. Here, we propose a reference-free genome metric called LTR Assembly Index (LAI) that evaluates assembly continuity using LTR-RTs. After correcting for LTR-RT amplification dynamics, we show that LAI is independent of genome size, genomic LTR-RT content, and gene space evaluation metrics (i.e., BUSCO and CEGMA). By comparing genomic sequences produced by various sequencing techniques, we reveal the significant gain of assembly continuity by using long-read-based techniques over short-read-based methods. Moreover, LAI can facilitate iterative assembly improvement with assembler selection and identify low-quality genomic regions. To apply LAI, intact LTR-RTs and total LTR-RTs should contribute at least 0.1% and 5% to the genome size, respectively. The LAI program is freely available on GitHub: https://github.com/oushujun/LTR_retriever.

          Related collections

          Most cited references23

          • Record: found
          • Abstract: found
          • Article: not found
          Is Open Access

          The zebrafish reference genome sequence and its relationship to the human genome.

          Zebrafish have become a popular organism for the study of vertebrate gene function. The virtually transparent embryos of this species, and the ability to accelerate genetic studies by gene knockdown or overexpression, have led to the widespread use of zebrafish in the detailed investigation of vertebrate gene function and increasingly, the study of human genetic disease. However, for effective modelling of human genetic disease it is important to understand the extent to which zebrafish genes and gene structures are related to orthologous human genes. To examine this, we generated a high-quality sequence assembly of the zebrafish genome, made up of an overlapping set of completely sequenced large-insert clones that were ordered and oriented using a high-resolution high-density meiotic map. Detailed automatic and manual annotation provides evidence of more than 26,000 protein-coding genes, the largest gene set of any vertebrate so far sequenced. Comparison to the human reference genome shows that approximately 70% of human genes have at least one obvious zebrafish orthologue. In addition, the high quality of this genome assembly provides a clearer understanding of key genomic features such as a unique repeat content, a scarcity of pseudogenes, an enrichment of zebrafish-specific genes on chromosome 4 and chromosomal regions that influence sex determination.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The Sorghum bicolor genome and the diversification of grasses.

            Sorghum, an African grass related to sugar cane and maize, is grown for food, feed, fibre and fuel. We present an initial analysis of the approximately 730-megabase Sorghum bicolor (L.) Moench genome, placing approximately 98% of genes in their chromosomal context using whole-genome shotgun sequence validated by genetic, physical and syntenic information. Genetic recombination is largely confined to about one-third of the sorghum genome with gene order and density similar to those of rice. Retrotransposon accumulation in recombinationally recalcitrant heterochromatin explains the approximately 75% larger genome size of sorghum compared with rice. Although gene and repetitive DNA distributions have been preserved since palaeopolyploidization approximately 70 million years ago, most duplicated gene sets lost one member before the sorghum-rice divergence. Concerted evolution makes one duplicated chromosomal segment appear to be only a few million years old. About 24% of genes are grass-specific and 7% are sorghum-specific. Recent gene and microRNA duplications may contribute to sorghum's drought tolerance.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              LTRharvest, an efficient and flexible software for de novo detection of LTR retrotransposons

              Background Transposable elements are abundant in eukaryotic genomes and it is believed that they have a significant impact on the evolution of gene and chromosome structure. While there are several completed eukaryotic genome projects, there are only few high quality genome wide annotations of transposable elements. Therefore, there is a considerable demand for computational identification of transposable elements. LTR retrotransposons, an important subclass of transposable elements, are well suited for computational identification, as they contain long terminal repeats (LTRs). Results We have developed a software tool LTRharvest for the de novo detection of full length LTR retrotransposons in large sequence sets. LTRharvest efficiently delivers high quality annotations based on known LTR transposon features like length, distance, and sequence motifs. A quality validation of LTRharvest against a gold standard annotation for Saccharomyces cerevisae and Drosophila melanogaster shows a sensitivity of up to 90% and 97% and specificity of 100% and 72%, respectively. This is comparable or slightly better than annotations for previous software tools. The main advantage of LTRharvest over previous tools is (a) its ability to efficiently handle large datasets from finished or unfinished genome projects, (b) its flexibility in incorporating known sequence features into the prediction, and (c) its availability as an open source software. Conclusion LTRharvest is an efficient software tool delivering high quality annotation of LTR retrotransposons. It can, for example, process the largest human chromosome in approx. 8 minutes on a Linux PC with 4 GB of memory. Its flexibility and small space and run-time requirements makes LTRharvest a very competitive candidate for future LTR retrotransposon annotation projects. Moreover, the structured design and implementation and the availability as open source provides an excellent base for incorporating novel concepts to further improve prediction of LTR retrotransposons.
                Bookmark

                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                30 November 2018
                10 August 2018
                10 August 2018
                : 46
                : 21
                : e126
                Affiliations
                [1 ]Department of Horticulture, Michigan State University, East Lansing, MI 48824, USA
                [2 ]Program in Ecology, Evolutionary Biology and Behavior, Michigan State University, East Lansing, MI 48824, USA
                [3 ]Department of Plant Pathology and Microbiology, University of California, Riverside, CA 92507, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 517 353 0379; Fax: +1 517 353 0890; Email: oushujun@ 123456msu.edu
                Author information
                http://orcid.org/0000-0001-5938-7180
                Article
                gky730
                10.1093/nar/gky730
                6265445
                30107434
                3483845e-13dc-423f-9f35-f67f2e6765ea
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 July 2018
                : 26 July 2018
                : 20 April 2018
                Page count
                Pages: 11
                Funding
                Funded by: National Science Foundation 10.13039/100000001
                Award ID: MCB-1121650
                Award ID: IOS-1126998
                Award ID: IOS-1740874
                Funded by: Michigan State University 10.13039/100007709
                Award ID: MICL02408
                Categories
                Methods Online

                Genetics
                Genetics

                Comments

                Comment on this article