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      Lineage-specific amplification and epigenetic regulation of LTR-retrotransposons contribute to the structure, evolution, and function of Fabaceae species

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          Abstract

          Background

          Long terminal repeat (LTR)-retrotransposons (LTR-RTs) are ubiquitous and make up the majority of nearly all sequenced plant genomes, whereas their pivotal roles in genome evolution, gene expression regulation as well as their epigenetic regulation are still not well understood, especially in a large number of closely related species.

          Results

          Here, we analyzed the abundance and dynamic evolution of LTR-RTs in 54 species from an economically and agronomically important family, Fabaceae, and also selected two representative species for further analysis in expression of associated genes, transcriptional activity and DNA methylation patterns of LTR-RTs. Annotation results revealed highly varied proportions of LTR-RTs in these genomes (5.1%~68.4%) and their correlation with genome size was highly positive, and they were significantly contributed to the variance in genome size through species-specific unique amplifications. Almost all of the intact LTR-RTs were inserted into the genomes 4 Mya (million years ago), and more than 50% of them were inserted in the last 0.5 million years, suggesting that recent amplifications of LTR-RTs were an important force driving genome evolution. In addition, expression levels of genes with intronic, promoter, and downstream LTR-RT insertions of Glycine max and Vigna radiata, two agronomically important crops in Fabaceae, showed that the LTR-RTs located in promoter or downstream regions suppressed associated gene expression. However, the LTR-RTs within introns promoted gene expression or had no contribution to gene expression. Additionally, shorter and younger LTR-RTs maintained higher mobility and transpositional potential. Compared with the transcriptionally silent LTR-RTs, the active elements showed significantly lower DNA methylation levels in all three contexts. The distributions of transcriptionally active and silent LTR-RT methylation varied across different lineages due to the position of LTR-RTs located or potentially epigenetic regulation.

          Conclusion

          Lineage-specific amplification patterns were observed and higher methylation level may repress the activity of LTR-RTs, further influence evolution in Fabaceae species. This study offers valuable clues into the evolution, function, transcriptional activity and epigenetic regulation of LTR-RTs in Fabaceae genomes.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-023-09530-y.

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          Most cited references69

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

            Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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              IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

              Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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                Author and article information

                Contributors
                lishufen83@163.com
                gaowujun@htu.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                27 July 2023
                27 July 2023
                2023
                : 24
                : 423
                Affiliations
                GRID grid.462338.8, ISNI 0000 0004 0605 6769, College of Life Sciences, , Henan Normal University, ; Xinxiang, 453007 P. R. China
                Article
                9530
                10.1186/s12864-023-09530-y
                10373317
                36593441
                88a0fa2b-6abb-4a15-ac8f-fa0d1143bf62
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 7 April 2023
                : 22 July 2023
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 31970240
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Genetics
                fabaceae species,ltr-rts,genome evolution,ltr-rt insertion,transcriptional activity,dna methylation

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