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You X, Fang Q, Chen C, Cao J, Fu S, Zhang T, Wang S, He X, He J, Zhou Y, Wang B, Wang L, Wang Z, Sun T, Yang X, Te R, Jian J, Zhou H, Dai Y, Liu Y. A near complete genome assembly of the East Friesian sheep genome. Sci Data 2024; 11:762. [PMID: 38992134 PMCID: PMC11239650 DOI: 10.1038/s41597-024-03581-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 06/27/2024] [Indexed: 07/13/2024] Open
Abstract
Advancements in sequencing have enabled the assembly of numerous sheep genomes, significantly advancing our understanding of the link between genetic variation and phenotypic traits. However, the genome of East Friesian sheep (Ostfriesisches Milchschaf), a key high-yield milk breed, remains to be fully assembled. Here, we constructed a near-complete and gap-free East Friesian genome assembly using PacBio HiFi, ultra-long ONT and Hi-C sequencing. The resulting genome assembly spans approximately 2.96 Gb, with a contig N50 length of 104.1 Mb and only 164 unplaced sequences. Remarkably, our assembly has captured 41 telomeres and 24 centromeres. The assembled sequence is of high quality on completeness (BUSCO score: 97.1%) and correctness (QV: 69.1). In addition, a total of 24,580 protein-coding genes were predicted, of which 97.2% (23,891) carried at least one conserved functional domain. Collectively, this assembly provides not only a near T2T gap-free genome, but also provides a valuable genetic resource for comparative genome studies of sheep and will serve as an important tool for the sheep research community.
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Affiliation(s)
| | | | - Chunhai Chen
- Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, China
| | - Junwei Cao
- Inner Mongolia Agricultural University, Hohhot, China
| | | | - Teng Zhang
- Inner Mongolia University, Hohhot, China
| | - Shenyuan Wang
- Inner Mongolia Agricultural University, Hohhot, China
| | | | | | - Yang Zhou
- Inner Mongolia University, Hohhot, China
| | | | | | - Zheng Wang
- Inner Mongolia University, Hohhot, China
| | | | - Xukui Yang
- Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, China
| | | | - Jianbo Jian
- Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, China
| | - Huanmin Zhou
- Inner Mongolia University, Hohhot, China.
- Inner Mongolia Agricultural University, Hohhot, China.
| | | | - Yongbin Liu
- Inner Mongolia University, Hohhot, China.
- BGI Genomics, Shenzhen, China.
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2
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Hui X, Yang J, Sun J, Liu F, Pan W. MCSS: microbial community simulator based on structure. Front Microbiol 2024; 15:1358257. [PMID: 38516019 PMCID: PMC10956353 DOI: 10.3389/fmicb.2024.1358257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 02/20/2024] [Indexed: 03/23/2024] Open
Abstract
De novo assembly plays a pivotal role in metagenomic analysis, and the incorporation of third-generation sequencing technology can significantly improve the integrity and accuracy of assembly results. Recently, with advancements in sequencing technology (Hi-Fi, ultra-long), several long-read-based bioinformatic tools have been developed. However, the validation of the performance and reliability of these tools is a crucial concern. To address this gap, we present MCSS (microbial community simulator based on structure), which has the capability to generate simulated microbial community and sequencing datasets based on the structure attributes of real microbiome communities. The evaluation results indicate that it can generate simulated communities that exhibit both diversity and similarity to actual community structures. Additionally, MCSS generates synthetic PacBio Hi-Fi and Oxford Nanopore Technologies (ONT) long reads for the species within the simulated community. This innovative tool provides a valuable resource for benchmarking and refining metagenomic analysis methods. Code available at: https://github.com/panlab-bio/mcss.
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Affiliation(s)
- Xingqi Hui
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (ICR, CAAS), Shenzhen, China
| | - Jinbao Yang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (ICR, CAAS), Shenzhen, China
- College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Jinhuan Sun
- Key Laboratory of Plant Molecular Physiology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Fang Liu
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences (ICR, CAAS), Anyang, China
| | - Weihua Pan
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (ICR, CAAS), Shenzhen, China
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3
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Fitz-Gibbon S, Mead A, O’Donnell S, Li ZZ, Escalona M, Beraut E, Sacco S, Marimuthu MPA, Nguyen O, Sork VL. Reference genome of California walnut, Juglans californica, and resemblance with other genomes in the order Fagales. J Hered 2023; 114:570-579. [PMID: 37335172 PMCID: PMC10445516 DOI: 10.1093/jhered/esad036] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 06/16/2023] [Indexed: 06/21/2023] Open
Abstract
Juglans californica, California walnut, is a vulnerable small tree that is locally abundant but restricted to woodland and chaparral habitats of Southern California threatened by urbanization and land use change. This species is the dominant species in a unique woodland ecosystem in California. It is one of 2 endemic California walnut species (family Juglandaceae). The other species, Northern California black walnut (J. hindsii), has been suggested controversially to be a variety of J. californica. Here, we report a new, chromosome-level assembly of J. californica as part of the California Conservation Genomics Project (CCGP). Consistent with the CCGP common methodology across ~150 genomes, we used Pacific Biosciences HiFi long reads and Omni-C chromatin-proximity sequencing technology to produce a de novo assembled genome. The assembly comprises 137 scaffolds spanning 551,065,703 bp, has a contig N50 of 30 Mb, a scaffold N50 of 37 Mb, and BUSCO complete score of 98.9%. Additionally, the mitochondrial genome has 701,569 bp. In addition, we compare this genome with other existing high-quality Juglans and Quercus genomes, which are in the same order (Fagales) and show relatively high synteny within the Juglans genomes. Future work will utilize the J. californica genome to determine its relationship with the Northern California walnut and assess the extent to which these 2 endemic trees might be at risk from fragmentation and/or climate warming.
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Affiliation(s)
- Sorel Fitz-Gibbon
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, United States
| | - Alayna Mead
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, United States
| | - Scott O’Donnell
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, United States
| | - Zhi-Zhong Li
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, United States
- Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, China
| | - Merly Escalona
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, United States
| | - Eric Beraut
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, United States
| | - Samuel Sacco
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, United States
| | - Mohan P A Marimuthu
- DNA Technologies and Expression Analysis Core Laboratory, Genome Center, University of California, Davis, CA, United States
| | - Oanh Nguyen
- DNA Technologies and Expression Analysis Core Laboratory, Genome Center, University of California, Davis, CA, United States
| | - Victoria L Sork
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, United States
- Institute of the Environment and Sustainability, University of California Los Angeles, Los Angeles, CA, United States
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4
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Ahsan MU, Liu Q, Perdomo JE, Fang L, Wang K. A survey of algorithms for the detection of genomic structural variants from long-read sequencing data. Nat Methods 2023; 20:1143-1158. [PMID: 37386186 PMCID: PMC11208083 DOI: 10.1038/s41592-023-01932-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 05/31/2023] [Indexed: 07/01/2023]
Abstract
As long-read sequencing technologies are becoming increasingly popular, a number of methods have been developed for the discovery and analysis of structural variants (SVs) from long reads. Long reads enable detection of SVs that could not be previously detected from short-read sequencing, but computational methods must adapt to the unique challenges and opportunities presented by long-read sequencing. Here, we summarize over 50 long-read-based methods for SV detection, genotyping and visualization, and discuss how new telomere-to-telomere genome assemblies and pangenome efforts can improve the accuracy and drive the development of SV callers in the future.
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Affiliation(s)
- Mian Umair Ahsan
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Qian Liu
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jonathan Elliot Perdomo
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- School of Biomedical Engineering, Drexel University, Philadelphia, PA, USA
| | - Li Fang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Ruiz JL, Reimering S, Escobar-Prieto JD, Brancucci NMB, Echeverry DF, Abdi AI, Marti M, Gómez-Díaz E, Otto TD. From contigs towards chromosomes: automatic improvement of long read assemblies (ILRA). Brief Bioinform 2023; 24:bbad248. [PMID: 37406192 PMCID: PMC10359078 DOI: 10.1093/bib/bbad248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 05/24/2023] [Accepted: 06/16/2023] [Indexed: 07/07/2023] Open
Abstract
Recent advances in long read technologies not only enable large consortia to aim to sequence all eukaryotes on Earth, but they also allow individual laboratories to sequence their species of interest with relatively low investment. Long read technologies embody the promise of overcoming scaffolding problems associated with repeats and low complexity sequences, but the number of contigs often far exceeds the number of chromosomes and they may contain many insertion and deletion errors around homopolymer tracts. To overcome these issues, we have implemented the ILRA pipeline to correct long read-based assemblies. Contigs are first reordered, renamed, merged, circularized, or filtered if erroneous or contaminated. Illumina short reads are used subsequently to correct homopolymer errors. We successfully tested our approach by improving the genome sequences of Homo sapiens, Trypanosoma brucei, and Leptosphaeria spp., and by generating four novel Plasmodium falciparum assemblies from field samples. We found that correcting homopolymer tracts reduced the number of genes incorrectly annotated as pseudogenes, but an iterative approach seems to be required to correct more sequencing errors. In summary, we describe and benchmark the performance of our new tool, which improved the quality of novel long read assemblies up to 1 Gbp. The pipeline is available at GitHub: https://github.com/ThomasDOtto/ILRA.
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Affiliation(s)
- José Luis Ruiz
- Instituto de Parasitología y Biomedicina López-Neyra (IPBLN), Consejo Superior de Investigaciones Científicas, 18016, Granada, Spain
| | - Susanne Reimering
- Department for Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | | | - Nicolas M B Brancucci
- School of Infection & Immunity, MVLS, University of Glasgow, Glasgow, UK
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, 4123 Allschwil, Switzerland
- University of Basel, 4001 Basel, Switzerland
| | - Diego F Echeverry
- Centro Internacional de Entrenamiento e Investigaciones Médicas (CIDEIM), Cali, Colombia
- Departamento de Microbiología, Facultad de Salud, Universidad del Valle, Cali, Colombia
| | | | - Matthias Marti
- School of Infection & Immunity, MVLS, University of Glasgow, Glasgow, UK
| | - Elena Gómez-Díaz
- Instituto de Parasitología y Biomedicina López-Neyra (IPBLN), Consejo Superior de Investigaciones Científicas, 18016, Granada, Spain
| | - Thomas D Otto
- School of Infection & Immunity, MVLS, University of Glasgow, Glasgow, UK
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6
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Sichel V, Sarah G, Girollet N, Laucou V, Roux C, Roques M, Mournet P, Cunff LL, Bert P, This P, Lacombe T. Chimeras in Merlot grapevine revealed by phased assembly. BMC Genomics 2023; 24:396. [PMID: 37452318 PMCID: PMC10347889 DOI: 10.1186/s12864-023-09453-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
Chimerism is the phenomenon when several genotypes coexist in a single individual. Used to understand plant ontogenesis they also have been valorised through new cultivar breeding. Viticulture has been taking economic advantage out of chimeras when the variant induced an important modification of wine type such as berry skin colour. Crucial agronomic characters may also be impacted by chimeras that aren't identified yet. Periclinal chimera where the variant has entirely colonised a cell layer is the most stable and can be propagated through cuttings. In grapevine, leaves are derived from both meristem layers, L1 and L2. However, lateral roots are formed from the L2 cell layer only. Thus, comparing DNA sequences of roots and leaves allows chimera detection. In this study we used new generation Hifi long reads sequencing, recent bioinformatics tools and trio-binning with parental sequences to detect periclinal chimeras on 'Merlot' grapevine cultivar. Sequencing of cv. 'Magdeleine Noire des Charentes' and 'Cabernet Franc', the parents of cv. 'Merlot', allowed haplotype resolved assembly. Pseudomolecules were built with a total of 33 to 47 contigs and in few occasions a unique contig for one chromosome. This high resolution allowed haplotype comparison. Annotation was transferred from PN40024 VCost.v3 to all pseudomolecules. After strong selection of variants, 51 and 53 'Merlot' specific periclinal chimeras were found on the Merlot-haplotype-CF and Merlot-haplotype-MG respectively, 9 and 7 been located in a coding region. A subset of positions was analysed using Molecular Inversion Probes (MIPseq) and 69% were unambiguously validated, 25% are doubtful because of technological noise or weak depth and 6% invalidated. These results open new perspectives on chimera detection as an important resource to improve cultivars through clonal selection or breeding.
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Affiliation(s)
- V. Sichel
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398 France
| | - G. Sarah
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398 France
- UMT Geno-Vigne®, IFV-INRAE-Institut Agro, Montpellier, F-34398 France
| | - N. Girollet
- EGFV, Université de Bordeaux, Bordeaux-Sciences Agro, INRAe, ISVV, 210 Chemin de Leysotte, F-33882 Villenave d’Ornon, France
| | - V. Laucou
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398 France
- UMT Geno-Vigne®, IFV-INRAE-Institut Agro, Montpellier, F-34398 France
| | - C. Roux
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398 France
- UMT Geno-Vigne®, IFV-INRAE-Institut Agro, Montpellier, F-34398 France
| | - M. Roques
- Institut Français de la Vigne et du Vin, Montpellier, F-34398 France
- UMT Geno-Vigne®, IFV-INRAE-Institut Agro, Montpellier, F-34398 France
| | - P. Mournet
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398 France
- UMR AGAP Institut, CIRAD, Montpellier, F-34398 France
| | - L. Le Cunff
- Institut Français de la Vigne et du Vin, Montpellier, F-34398 France
- UMT Geno-Vigne®, IFV-INRAE-Institut Agro, Montpellier, F-34398 France
| | - P.F. Bert
- EGFV, Université de Bordeaux, Bordeaux-Sciences Agro, INRAe, ISVV, 210 Chemin de Leysotte, F-33882 Villenave d’Ornon, France
| | - P. This
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398 France
- UMT Geno-Vigne®, IFV-INRAE-Institut Agro, Montpellier, F-34398 France
| | - T. Lacombe
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398 France
- UMT Geno-Vigne®, IFV-INRAE-Institut Agro, Montpellier, F-34398 France
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Tombácz D, Torma G, Gulyás G, Fülöp Á, Dörmő Á, Prazsák I, Csabai Z, Mizik M, Hornyák Á, Zádori Z, Kakuk B, Boldogkői Z. Hybrid sequencing discloses unique aspects of the transcriptomic architecture in equid alphaherpesvirus 1. Heliyon 2023; 9:e17716. [PMID: 37449092 PMCID: PMC10336594 DOI: 10.1016/j.heliyon.2023.e17716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 06/05/2023] [Accepted: 06/26/2023] [Indexed: 07/18/2023] Open
Abstract
This study employed both short-read sequencing (SRS, Illumina) and long-read sequencing (LRS Oxford Nanopore Technologies) platforms to conduct a comprehensive analysis of the equid alphaherpesvirus 1 (EHV-1) transcriptome. The study involved the annotation of canonical mRNAs and their transcript variants, encompassing transcription start site (TSS) and transcription end site (TES) isoforms, in addition to alternative splicing forms. Furthermore, the study revealed the presence of numerous non-coding RNA (ncRNA) molecules, including intergenic and antisense transcripts, produced by EHV-1. An intriguing finding was the abundant production of chimeric transcripts, some of which potentially encode fusion polypeptides. Moreover, EHV-1 exhibited a greater incidence of transcriptional overlaps and splicing compared to related viruses. It is noteworthy that many genes have their unique TESs along with the co-terminal transcription ends, a characteristic scarcely seen in other alphaherpesviruses. The study also identified transcripts that overlap the replication origins of the virus. Moreover, a novel ncRNA, referred to as NOIR, was found to intersect with the 5'-ends of longer transcript isoform specified by the major transactivator genes ORF64 and ORF65, surrounding the OriL. These findings together imply the existence of a key regulatory mechanism that governs both transcription and replication through, among others, a process that involves interference between the DNA and RNA synthesis machineries.
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Affiliation(s)
- Dóra Tombácz
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Gábor Torma
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Gábor Gulyás
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Ádám Fülöp
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Ákos Dörmő
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - István Prazsák
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Zsolt Csabai
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Máté Mizik
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Ákos Hornyák
- Institute for Veterinary Medical Research, Centre for Agricultural Research, Budapest, Hungary
| | - Zoltán Zádori
- Institute for Veterinary Medical Research, Centre for Agricultural Research, Budapest, Hungary
| | - Balázs Kakuk
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Zsolt Boldogkői
- Department of Medical Biology, Faculty of Medicine, University of Szeged, Szeged, Hungary
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8
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Nguyen TV, Vander Jagt CJ, Wang J, Daetwyler HD, Xiang R, Goddard ME, Nguyen LT, Ross EM, Hayes BJ, Chamberlain AJ, MacLeod IM. In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants. Genet Sel Evol 2023; 55:9. [PMID: 36721111 PMCID: PMC9887926 DOI: 10.1186/s12711-023-00783-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 01/23/2023] [Indexed: 02/02/2023] Open
Abstract
Studies have demonstrated that structural variants (SV) play a substantial role in the evolution of species and have an impact on Mendelian traits in the genome. However, unlike small variants (< 50 bp), it has been challenging to accurately identify and genotype SV at the population scale using short-read sequencing. Long-read sequencing technologies are becoming competitively priced and can address several of the disadvantages of short-read sequencing for the discovery and genotyping of SV. In livestock species, analysis of SV at the population scale still faces challenges due to the lack of resources, high costs, technological barriers, and computational limitations. In this review, we summarize recent progress in the characterization of SV in the major livestock species, the obstacles that still need to be overcome, as well as the future directions in this growing field. It seems timely that research communities pool resources to build global population-scale long-read sequencing consortiums for the major livestock species for which the application of genomic tools has become cost-effective.
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Affiliation(s)
- Tuan V. Nguyen
- grid.452283.a0000 0004 0407 2669Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
| | - Christy J. Vander Jagt
- grid.452283.a0000 0004 0407 2669Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
| | - Jianghui Wang
- grid.452283.a0000 0004 0407 2669Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
| | - Hans D. Daetwyler
- grid.452283.a0000 0004 0407 2669Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia ,grid.1018.80000 0001 2342 0938School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083 Australia
| | - Ruidong Xiang
- grid.452283.a0000 0004 0407 2669Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia ,grid.1008.90000 0001 2179 088XFaculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, VIC 3052 Australia
| | - Michael E. Goddard
- grid.452283.a0000 0004 0407 2669Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia ,grid.1008.90000 0001 2179 088XFaculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, VIC 3052 Australia
| | - Loan T. Nguyen
- grid.1003.20000 0000 9320 7537Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD 4072 Australia
| | - Elizabeth M. Ross
- grid.1003.20000 0000 9320 7537Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD 4072 Australia
| | - Ben J. Hayes
- grid.1003.20000 0000 9320 7537Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD 4072 Australia
| | - Amanda J. Chamberlain
- grid.452283.a0000 0004 0407 2669Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia ,grid.1018.80000 0001 2342 0938School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083 Australia
| | - Iona M. MacLeod
- grid.452283.a0000 0004 0407 2669Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083 Australia
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Matoulek D, Ježek B, Vohnoutová M, Symonová R. Advances in Vertebrate (Cyto)Genomics Shed New Light on Fish Compositional Genome Evolution. Genes (Basel) 2023; 14:genes14020244. [PMID: 36833171 PMCID: PMC9956151 DOI: 10.3390/genes14020244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 01/05/2023] [Indexed: 01/19/2023] Open
Abstract
Cytogenetic and compositional studies considered fish genomes rather poor in guanine-cytosine content (GC%) because of a putative "sharp increase in genic GC% during the evolution of higher vertebrates". However, the available genomic data have not been exploited to confirm this viewpoint. In contrast, further misunderstandings in GC%, mostly of fish genomes, originated from a misapprehension of the current flood of data. Utilizing public databases, we calculated the GC% in animal genomes of three different, technically well-established fractions: DNA (entire genome), cDNA (complementary DNA), and cds (exons). Our results across chordates help set borders of GC% values that are still incorrect in literature and show: (i) fish in their immense diversity possess comparably GC-rich (or even GC-richer) genomes as higher vertebrates, and fish exons are GC-enriched among vertebrates; (ii) animal genomes generally show a GC-enrichment from the DNA, over cDNA, to the cds level (i.e., not only the higher vertebrates); (iii) fish and invertebrates show a broad(er) inter-quartile range in GC%, while avian and mammalian genomes are more constrained in their GC%. These results indicate no sharp increase in the GC% of genes during the transition to higher vertebrates, as stated and numerously repeated before. We present our results in 2D and 3D space to explore the compositional genome landscape and prepared an online platform to explore the AT/GC compositional genome evolution.
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Affiliation(s)
- Dominik Matoulek
- Department of Physics, Faculty of Science, University of Hradec Králové, 500 03 Hradec Králové, Czech Republic
| | - Bruno Ježek
- Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, 500 02 Hradec Králové, Czech Republic
| | - Marta Vohnoutová
- Department of Computer Science, Faculty of Science, University of South Bohemia, Branišovská 1760, 370 05 České Budějovice, Czech Republic
| | - Radka Symonová
- Department of Computer Science, Faculty of Science, University of South Bohemia, Branišovská 1760, 370 05 České Budějovice, Czech Republic
- Department of Bioinformatics, Wissenschaftszentrum Weihenstephan, Technische Universität München, 85354 Freising, Germany
- Institute of Hydrobiology, Biology Centre of the Czech Academy of Sciences, 370 05 České Budějovice, Czech Republic
- Correspondence:
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Wang S, Wang H, Jiang F, Wang A, Liu H, Zhao H, Yang B, Xu D, Zhang Y, Fan W. EndHiC: assemble large contigs into chromosome-level scaffolds using the Hi-C links from contig ends. BMC Bioinformatics 2022; 23:528. [PMID: 36482318 PMCID: PMC9730666 DOI: 10.1186/s12859-022-05087-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 11/28/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The application of PacBio HiFi and ultra-long ONT reads have enabled huge progress in the contig-level assembly, but it is still challenging to assemble large contigs into chromosomes with available Hi-C scaffolding tools, which count Hi-C links between contigs using the whole or a large part of contig regions. As the Hi-C links of two adjacent contigs concentrate only at the neighbor ends of the contigs, larger contig size will reduce the power to differentiate adjacent (signal) and non-adjacent (noise) contig linkages, leading to a higher rate of mis-assembly. RESULTS We design and develop a novel Hi-C based scaffolding tool EndHiC, which is suitable to assemble large contigs into chromosomal-level scaffolds. The core idea behind EndHiC, which distinguishes it from other Hi-C scaffolding tools, is using Hi-C links only from the most effective regions of contig ends. By this way, the signal neighbor contig linkages and noise non-neighbor contig linkages are separated more clearly. Benefiting from the increased signal to noise ratio, the reciprocal best requirement, as well as the robustness evaluation, EndHiC achieves higher accuracy for scaffolding large contigs compared to existing tools. EndHiC has been successfully applied in the Hi-C scaffolding of simulated data from human, rice and Arabidopsis, and real data from human, great burdock, water spinach, chicory, endive, yacon, and Ipomoea cairica, suggesting that EndHiC can be applied to a broad range of plant and animal genomes. CONCLUSIONS EndHiC is a novel Hi-C scaffolding tool, which is suitable for scaffolding of contig assemblies with contig N50 size near or over 10 Mb and N90 size near or over 1 Mb. EndHiC is efficient both in time and memory, and it is interface-friendly to the users. As more genome projects have been launched and the contig continuity constantly improved, we believe EndHiC has the potential to make a great contribution to the genomics field and liberate the scientists from labor-intensive manual curation works.
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Affiliation(s)
- Sen Wang
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Hengchao Wang
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Fan Jiang
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Anqi Wang
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Hangwei Liu
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Hanbo Zhao
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Boyuan Yang
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Dong Xu
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Yan Zhang
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
| | - Wei Fan
- grid.410727.70000 0001 0526 1937Guangdong Laboratory for Lingnan Modern Agriculture (Shenzhen Branch), Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 Guangdong China
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Liu L, Yang Y, Deng Y, Zhang T. Nanopore long-read-only metagenomics enables complete and high-quality genome reconstruction from mock and complex metagenomes. MICROBIOME 2022; 10:209. [PMID: 36457010 PMCID: PMC9716684 DOI: 10.1186/s40168-022-01415-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 11/07/2022] [Indexed: 05/31/2023]
Abstract
BACKGROUND The accurate and comprehensive analyses of genome-resolved metagenomics largely depend on the reconstruction of reference-quality (complete and high-quality) genomes from diverse microbiomes. Closing gaps in draft genomes have been approaching with the inclusion of Nanopore long reads; however, genome quality improvement requires extensive and time-consuming high-accuracy short-read polishing. RESULTS Here, we introduce NanoPhase, an open-source tool to reconstruct reference-quality genomes from complex metagenomes using only Nanopore long reads. Using Kit 9 and Q20+ chemistries, we first evaluated the feasibility of NanoPhase using a ZymoBIOMICS gut microbiome standard (including 21 strains), then sequenced the complex activated sludge microbiome and reconstructed 275 MAGs with median completeness of ~ 90%. As a result, NanoPhase improved the MAG contiguity (median MAG N50: 735 Kb, 44-86X compared to conventional short-read-based methods) while maintaining high accuracy, allowing for a full and accurate investigation of target microbiomes. Additionally, leveraging these high-contiguity reference-quality genomes, we identified 165 prophages within 111 MAGs, with 5 as active prophages, indicating the prophage was a neglected source of genetic diversity within microbial populations and influencer in shaping microbial composition in the activated sludge microbiome. CONCLUSIONS Our results demonstrated that NanoPhase enables reference-quality genome reconstruction from complex metagenomes directly using only Nanopore long reads. Furthermore, besides the 16S rRNA genes and biosynthetic gene clusters, the generated high-accuracy and high-contiguity MAGs improved the host identification of critical mobile genetic elements, e.g., prophage, serving as a genomic blueprint to investigate the microbial potential and ecology in the activated sludge ecosystem. Video Abstract.
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Affiliation(s)
- Lei Liu
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Yu Yang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Yu Deng
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Tong Zhang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China
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Hu Q, Huang X, Jin Y, Zhang R, Zhao A, Wang Y, Zhou C, Liu W, Liu X, Li C, Fan G, Zhuo M, Wang X, Ling F, Luo W. Long-read assembly of major histocompatibility complex and killer cell immunoglobulin-like receptor genome regions in cynomolgus macaque. Biol Direct 2022; 17:36. [PMID: 36447238 PMCID: PMC9707422 DOI: 10.1186/s13062-022-00350-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 11/21/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The major histocompatibility complex (MHC) and the killer cell immunoglobulin-like receptors (KIR) are key regulators of immune responses. The cynomolgus macaque, an Old World monkey species, can be applied as an important preclinical model for studying human diseases, including coronavirus disease 2019 (COVID-19). Several MHC-KIR combinations have been associated with either a poor or good prognosis. Therefore, macaques with a well-characterized immunogenetic profile may improve drug evaluation and speed up vaccine development. At present, a complete overview of the MHC and KIR haplotype organizations in cynomolgus macaques is lacking, and characterization by conventional techniques is hampered by the extensive expansion of the macaque MHC-B region that complicates the discrimination between genes and alleles. METHODS We assembled complete MHC and KIR genomic regions of cynomolgus macaque using third-generation long-read sequencing approach. We identified functional Mafa-B loci at the transcriptome level using locus-specific amplification in a cohort of 33 Vietnamese cynomolgus macaques. RESULTS This is the first physical mapping of complete MHC and KIR gene regions in a Vietnamese cynomolgus macaque. Furthermore, we identified four functional Mafa-B loci (B2, B3, B5, and B6) and showed that alleles of the Mafa-I*01, -B*056, -B*034, and -B*001 functional lineages, respectively, are highly frequent in the Vietnamese cynomolgus macaque population. CONCLUSION The insights into the MHC and KIR haplotype organizations and the level of diversity may refine the selection of animals with specific genetic markers for future medical research.
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Affiliation(s)
- Qingxiu Hu
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Xiaoqi Huang
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Yabin Jin
- grid.12981.330000 0001 2360 039XThe First People’s Hospital of Foshan, Sun Yat-sen University, Foshan, 528000 China
| | - Rui Zhang
- grid.21155.320000 0001 2034 1839BGI-Qingdao, BGI-Shenzhen, Qingdao, 266555 China
| | - Aimin Zhao
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Yiping Wang
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Chenyun Zhou
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Weixin Liu
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Xunwei Liu
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Chunhua Li
- grid.21155.320000 0001 2034 1839BGI-Qingdao, BGI-Shenzhen, Qingdao, 266555 China
| | - Guangyi Fan
- grid.21155.320000 0001 2034 1839BGI-Qingdao, BGI-Shenzhen, Qingdao, 266555 China
| | - Min Zhuo
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Xiaoning Wang
- grid.414252.40000 0004 1761 8894National Clinic Center of Geriatric, The Chinese PLA General Hospital, Beijing, 100853 China
| | - Fei Ling
- grid.79703.3a0000 0004 1764 3838Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006 China
| | - Wei Luo
- grid.12981.330000 0001 2360 039XThe First People’s Hospital of Foshan, Sun Yat-sen University, Foshan, 528000 China
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Ashraf MF, Hou D, Hussain Q, Imran M, Pei J, Ali M, Shehzad A, Anwar M, Noman A, Waseem M, Lin X. Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance. Int J Mol Sci 2022; 23:651. [PMID: 35054836 PMCID: PMC8775971 DOI: 10.3390/ijms23020651] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 12/23/2021] [Accepted: 12/29/2021] [Indexed: 02/07/2023] Open
Abstract
Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.
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Affiliation(s)
- Muhammad Furqan Ashraf
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, 666 Wusu Street, Lin’An, Hangzhou 311300, China; (M.F.A.); (D.H.); (Q.H.); (J.P.)
| | - Dan Hou
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, 666 Wusu Street, Lin’An, Hangzhou 311300, China; (M.F.A.); (D.H.); (Q.H.); (J.P.)
| | - Quaid Hussain
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, 666 Wusu Street, Lin’An, Hangzhou 311300, China; (M.F.A.); (D.H.); (Q.H.); (J.P.)
| | - Muhammad Imran
- Colleges of Agriculture and Horticulture, South China Agricultural University, Guangzhou 510642, China; (M.I.); (M.W.)
| | - Jialong Pei
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, 666 Wusu Street, Lin’An, Hangzhou 311300, China; (M.F.A.); (D.H.); (Q.H.); (J.P.)
| | - Mohsin Ali
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China;
| | - Aamar Shehzad
- Maize Research Station, AARI, Faisalabad 38000, Pakistan;
| | - Muhammad Anwar
- Guangdong Technology Research Center for Marine Algal Bioengineering, Guangdong Key Laboratory of Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518055, China;
| | - Ali Noman
- Department of Botany, Government College University, Faisalabad 38000, Pakistan;
| | - Muhammad Waseem
- Colleges of Agriculture and Horticulture, South China Agricultural University, Guangzhou 510642, China; (M.I.); (M.W.)
| | - Xinchun Lin
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, 666 Wusu Street, Lin’An, Hangzhou 311300, China; (M.F.A.); (D.H.); (Q.H.); (J.P.)
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Liu L, Wang Y, Yang Y, Wang D, Cheng SH, Zheng C, Zhang T. Charting the complexity of the activated sludge microbiome through a hybrid sequencing strategy. MICROBIOME 2021; 9:205. [PMID: 34649602 PMCID: PMC8518188 DOI: 10.1186/s40168-021-01155-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 09/01/2021] [Indexed: 06/01/2023]
Abstract
BACKGROUND Long-read sequencing has shown its tremendous potential to address genome assembly challenges, e.g., achieving the first telomere-to-telomere assembly of a gapless human chromosome. However, many issues remain unresolved when leveraging error-prone long reads to characterize high-complexity metagenomes, for instance, complete/high-quality genome reconstruction from highly complex systems. RESULTS Here, we developed an iterative haplotype-resolved hierarchical clustering-based hybrid assembly (HCBHA) approach that capitalizes on a hybrid (error-prone long reads and high-accuracy short reads) sequencing strategy to reconstruct (near-) complete genomes from highly complex metagenomes. Using the HCBHA approach, we first phase short and long reads from the highly complex metagenomic dataset into different candidate bacterial haplotypes, then perform hybrid assembly of each bacterial genome individually. We reconstructed 557 metagenome-assembled genomes (MAGs) with an average N50 of 574 Kb from a deeply sequenced, highly complex activated sludge (AS) metagenome. These high-contiguity MAGs contained 14 closed genomes and 111 high-quality (HQ) MAGs including full-length rRNA operons, which accounted for 61.1% of the microbial community. Leveraging the near-complete genomes, we also profiled the metabolic potential of the AS microbiome and identified 2153 biosynthetic gene clusters (BGCs) encoded within the recovered AS MAGs. CONCLUSION Our results established the feasibility of an iterative haplotype-resolved HCBHA approach to reconstruct (near-) complete genomes from highly complex ecosystems, providing new insights into "complete metagenomics". The retrieved high-contiguity MAGs illustrated that various biosynthetic gene clusters (BGCs) were harbored in the AS microbiome. The high diversity of BGCs highlights the potential to discover new natural products biosynthesized by the AS microbial community, aside from the traditional function (e.g., organic carbon and nitrogen removal) in wastewater treatment. Video Abstract.
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Affiliation(s)
- Lei Liu
- Environmental Microbiome Engineering and Biotechnology Laboratory, The University of Hong Kong, Hong Kong SAR, China
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yulin Wang
- Environmental Microbiome Engineering and Biotechnology Laboratory, The University of Hong Kong, Hong Kong SAR, China
| | - Yu Yang
- Environmental Microbiome Engineering and Biotechnology Laboratory, The University of Hong Kong, Hong Kong SAR, China
| | - Depeng Wang
- Nextomics Biosciences Institute, Wuhan, China
| | - Suk Hang Cheng
- Department of Chemical Pathology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Chunmiao Zheng
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Tong Zhang
- Environmental Microbiome Engineering and Biotechnology Laboratory, The University of Hong Kong, Hong Kong SAR, China
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
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