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      Genomic analyses provide insights into the polyploidization‐driven herbicide adaptation in Leptochloa weeds

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          Summary

          Polyploidy confers a selective advantage under stress conditions; however, whether polyploidization mediates enhanced herbicide adaptation remains largely unknown. Tetraploid Leptochloa chinensis is a notorious weed in the rice ecosystem, causing severe yield loss in rice. In China, L. chinensis has only one sister species, the diploid L. panicea, whose damage is rarely reported. To gain insights into the effects of polyploidization on herbicide adaptation, we first assembled a high‐quality genome of L. panicea and identified genome structure variations with L. chinensis. Moreover, we identified herbicide‐resistance genes specifically expanded in L. chinensis, which may confer a greater herbicide adaptability in L. chinensis. Analysis of gene retention and loss showed that five herbicide target‐site genes and several herbicide nontarget‐site resistance gene families were retained during polyploidization. Notably, we identified three pairs of polyploidization‐retained genes including LcABCC8, LcCYP76C1 and LcCYP76C4 that may enhance herbicide resistance. More importantly, we found that both copies of LcCYP76C4 were under herbicide selection during the spread of L. chinensis in China. Furthermore, we identified another gene potentially involved in herbicide resistance, LcCYP709B2, which is also retained during polyploidization and under selection. This study provides insights into the genomic basis of the enhanced herbicide adaptability of Leptochloa weeds during polyploidization and provides guidance for the precise and efficient control of polyploidy weeds.

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          Fast and accurate short read alignment with Burrows–Wheeler transform

          Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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            fastp: an ultra-fast all-in-one FASTQ preprocessor

            Abstract Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.
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              Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

              Rapid advances in next-generation sequencing technologies have dramatically changed our ability to perform genome-scale analyses. The human reference genome used for most genomic analyses represents only a small number of individuals, limiting its usefulness for genotyping. We designed a novel method, HISAT2, for representing and searching an expanded model of the human reference genome, in which a large catalogue of known genomic variants and haplotypes is incorporated into the data structure used for searching and alignment. This strategy for representing a population of genomes, along with a fast and memory-efficient search algorithm, enables more detailed and accurate variant analyses than previous methods. We demonstrate two initial applications of HISAT2: HLA typing, a critical need in human organ transplantation, and DNA fingerprinting, widely used in forensics. These applications are part of HISAT-genotype, with performance not only surpassing earlier computational methods, but matching or exceeding the accuracy of laboratory-based assays.
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                Author and article information

                Contributors
                lybai@hunaas.cn
                ifwang@hunaas.cn
                Journal
                Plant Biotechnol J
                Plant Biotechnol J
                10.1111/(ISSN)1467-7652
                PBI
                Plant Biotechnology Journal
                John Wiley and Sons Inc. (Hoboken )
                1467-7644
                1467-7652
                08 May 2023
                August 2023
                : 21
                : 8 ( doiID: 10.1111/pbi.v21.8 )
                : 1642-1658
                Affiliations
                [ 1 ] State Key Laboratory of Hybrid Rice Hunan Academy of Agricultural Sciences Changsha China
                [ 2 ] Key Laboratory of Indica Rice Genetics and Breeding in the Middle and Lower Reaches of Yangtze River Valley, Ministry of Agriculture and Rural Affairs, Hunan Rice Research Institute Hunan Academy of Agricultural Sciences Changsha China
                [ 3 ] Huangpu Research Institute of Longping Agricultural Science and Technology Guangzhou China
                [ 4 ] Longping Branch, College of Biology Hunan University Changsha China
                [ 5 ] Hunan Weed Science Key Laboratory, Hunan Agricultural Biotechnology Research Institute Hunan Academy of Agricultural Sciences Changsha China
                [ 6 ] Qingdao Kingagroot Compounds Co. Ltd Qingdao China
                [ 7 ] State Key Laboratory of Agrobiotechnology, Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, College of Horticulture China Agricultural University Beijing China
                Author notes
                [*] [* ] Correspondence (Tel +86 13908478453; Fax 0731‐84691624; email lybai@ 123456hunaas.cn (LB) and Tel +86 13574848933; Fax 0731‐84691284; email ifwang@ 123456hunaas.cn (LW))
                [ † ]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-8427-4345
                https://orcid.org/0000-0002-4318-030X
                https://orcid.org/0000-0002-1074-0534
                Article
                PBI14065 PBI-00196-2023
                10.1111/pbi.14065
                10363762
                37154437
                3484561d-b58a-4382-bdd9-810527c8d146
                © 2023 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 21 February 2023
                : 17 December 2022
                : 14 April 2023
                Page count
                Figures: 6, Tables: 1, Pages: 1658, Words: 15407
                Funding
                Funded by: China Agriculture Research System of MOF and MARA
                Award ID: CARS‐16‐E19
                Funded by: National Key R&D Program of China
                Award ID: 2021YFD1700101
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 32272564
                Funded by: Science and Technology Innovation Program of Hunan Province
                Award ID: 2020WK2014
                Award ID: 2020WK2023
                Funded by: Training Program for Excellent Young Innovators of Changsha , doi 10.13039/501100018579;
                Award ID: kq2106079
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                August 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.2 mode:remove_FC converted:24.07.2023

                Biotechnology
                leptochloa weeds,comparative genomics,genome polyploidization,genome evolution,herbicide resistance

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