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      Telomere-to-telomere and gap-free reference genome assembly of the kiwifruit Actinidia chinensis

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          Abstract

          Kiwifruit is an economically and nutritionally important fruit crop with extremely high contents of vitamin C. However, the previously released versions of kiwifruit genomes all have a mass of unanchored or missing regions. Here, we report a highly continuous and completely gap-free reference genome of Actinidia chinensis cv. ‘Hongyang’, named Hongyang v4.0, which is the first to achieve two de novo haploid-resolved haplotypes, HY4P and HY4A. HY4P and HY4A have a total length of 606.1 and 599.6 Mb, respectively, with almost the entire telomeres and centromeres assembled in each haplotype. In comparison with Hongyang v3.0, the integrity and contiguity of Hongyang v4.0 is markedly improved by filling all unclosed gaps and correcting some misoriented regions, resulting in ~38.6–39.5 Mb extra sequences, which might affect 4263 and 4244 protein-coding genes in HY4P and HY4A, respectively. Furthermore, our gap-free genome assembly provides the first clue for inspecting the structure and function of centromeres. Globally, centromeric regions are characterized by higher-order repeats that mainly consist of a 153-bp conserved centromere-specific monomer ( Ach-CEN153) with different copy numbers among chromosomes. Functional enrichment analysis of the genes located within centromeric regions demonstrates that chromosome centromeres may not only play physical roles for linking a pair of sister chromatids, but also have genetic features for participation in the regulation of cell division. The availability of the telomere-to-telomere and gap-free Hongyang v4.0 reference genome lays a solid foundation not only for illustrating genome structure and functional genomics studies but also for facilitating kiwifruit breeding and improvement.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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              HISAT: a fast spliced aligner with low memory requirements.

              HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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                Author and article information

                Contributors
                Journal
                Hortic Res
                Hortic Res
                hr
                Horticulture Research
                Oxford University Press
                2662-6810
                2052-7276
                February 2023
                02 December 2022
                02 December 2022
                : 10
                : 2
                : uhac264
                Affiliations
                School of Horticulture, Anhui Agricultural University , Hefei, Anhui 230036, China
                Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences , Shenzhen, Guangdong 518124, China
                School of Horticulture, Anhui Agricultural University , Hefei, Anhui 230036, China
                School of Horticulture, Anhui Agricultural University , Hefei, Anhui 230036, China
                Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences , Wuhan, Hubei 430064, China
                School of Information and Computer, Anhui Agricultural University , Hefei, Anhui 230036, China
                Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences , Shenzhen, Guangdong 518124, China
                Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences , Shenzhen, Guangdong 518124, China
                Ministry of Education Key Laboratory for Bio-resource and Eco-environment, College of Life Science, State Key Laboratory of Hydraulic and Mountain River Engineering, Sichuan University , Chengdu, Sichuan 610064, China
                Department of Bioinformatics, Anhui Double Helix Gene Technology Corporation , Hefei, Anhui 230022, China
                Comprehensive Testing Ground , Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang 830012, China
                Institute of Special Animal and Plant Sciences , Chinese Academy of Agricultural Sciences, Changchun, Jilin 130112, China
                Institute of Special Animal and Plant Sciences , Chinese Academy of Agricultural Sciences, Changchun, Jilin 130112, China
                School of Horticulture, Anhui Agricultural University , Hefei, Anhui 230036, China
                School of Horticulture, Anhui Agricultural University , Hefei, Anhui 230036, China
                School of Horticulture, Anhui Agricultural University , Hefei, Anhui 230036, China
                School of Information and Computer, Anhui Agricultural University , Hefei, Anhui 230036, China
                School of Horticulture, Anhui Agricultural University , Hefei, Anhui 230036, China
                Ministry of Education Key Laboratory for Bio-resource and Eco-environment, College of Life Science, State Key Laboratory of Hydraulic and Mountain River Engineering, Sichuan University , Chengdu, Sichuan 610064, China
                Author notes

                Equal contribution.

                Author information
                https://orcid.org/0000-0002-5299-0160
                Article
                uhac264
                10.1093/hr/uhac264
                9909506
                36778189
                61aa68d3-80e3-4f9d-b9e7-bb13fa7f51b6
                © The Author(s) 2023. Published by Oxford University Press on behalf of Nanjing Agricultural University.

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

                History
                : 21 August 2022
                : 21 November 2022
                : 01 February 2023
                Page count
                Pages: 13
                Categories
                AcademicSubjects/SCI01210
                AcademicSubjects/SCI01140
                Article

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