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Chen G, Shi G, Dai Y, Zhao R, Wu Q. Graph-Based Pan-Genome Reveals the Pattern of Deleterious Mutations during the Domestication of Saccharomyces cerevisiae. J Fungi (Basel) 2024; 10:575. [PMID: 39194902 DOI: 10.3390/jof10080575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 08/08/2024] [Accepted: 08/10/2024] [Indexed: 08/29/2024] Open
Abstract
The "cost of domestication" hypothesis suggests that the domestication of wild species increases the number, frequency, and/or proportion of deleterious genetic variants, potentially reducing their fitness in the wild. While extensively studied in domesticated species, this phenomenon remains understudied in fungi. Here, we used Saccharomyces cerevisiae, the world's oldest domesticated fungus, as a model to investigate the genomic characteristics of deleterious variants arising from fungal domestication. Employing a graph-based pan-genome approach, we identified 1,297,761 single nucleotide polymorphisms (SNPs), 278,147 insertion/deletion events (indels; <30 bp), and 19,967 non-redundant structural variants (SVs; ≥30 bp) across 687 S. cerevisiae isolates. Comparing these variants with synonymous SNPs (sSNPs) as neutral controls, we found that the majority of the derived nonsynonymous SNPs (nSNPs), indels, and SVs were deleterious. Heterozygosity was positively correlated with the impact of deleterious SNPs, suggesting a role of genetic diversity in mitigating their effects. The domesticated isolates exhibited a higher additive burden of deleterious SNPs (dSNPs) than the wild isolates, but a lower burden of indels and SVs. Moreover, the domesticated S. cerevisiae showed reduced rates of adaptive evolution relative to the wild S. cerevisiae. In summary, deleterious variants tend to be heterozygous, which may mitigate their harmful effects, but they also constrain breeding potential. Addressing deleterious alleles and minimizing the genetic load are crucial considerations for future S. cerevisiae breeding efforts.
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Affiliation(s)
- Guotao Chen
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Guohui Shi
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yi Dai
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Ruilin Zhao
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qi Wu
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
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2
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L Rocha J, Lou RN, Sudmant PH. Structural variation in humans and our primate kin in the era of telomere-to-telomere genomes and pangenomics. Curr Opin Genet Dev 2024; 87:102233. [PMID: 39042999 DOI: 10.1016/j.gde.2024.102233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 07/02/2024] [Accepted: 07/05/2024] [Indexed: 07/25/2024]
Abstract
Structural variants (SVs) account for the majority of base pair differences both within and between primate species. However, our understanding of inter- and intra-species SV has been historically hampered by the quality of draft primate genomes and the absence of genome resources for key taxa. Recently, advances in long-read sequencing and genome assembly have begun to radically reshape our understanding of SVs. Two landmark achievements include the publication of a human telomere-to-telomere (T2T) genome as well as the development of the first human pangenome reference. In this review, we first look back to the major works laying the foundation for these projects. We then examine the ways in which T2T genome assemblies and pangenomes are transforming our understanding of and approach to primate SV. Finally, we discuss what the future of primate SV research may look like in the era of T2T genomes and pangenomics.
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Affiliation(s)
- Joana L Rocha
- Department of Integrative Biology, University of California, Berkeley, Berkeley, USA. https://twitter.com/@joanocha
| | - Runyang N Lou
- Department of Integrative Biology, University of California, Berkeley, Berkeley, USA. https://twitter.com/@NicolasLou10
| | - Peter H Sudmant
- Department of Integrative Biology, University of California, Berkeley, Berkeley, USA; Center for Computational Biology, University of California, Berkeley, Berkeley, USA.
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3
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Gao Z, Lu Y, Chong Y, Li M, Hong J, Wu J, Wu D, Xi D, Deng W. Beef Cattle Genome Project: Advances in Genome Sequencing, Assembly, and Functional Genes Discovery. Int J Mol Sci 2024; 25:7147. [PMID: 39000250 PMCID: PMC11240973 DOI: 10.3390/ijms25137147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 06/23/2024] [Accepted: 06/26/2024] [Indexed: 07/16/2024] Open
Abstract
Beef is a major global source of protein, playing an essential role in the human diet. The worldwide production and consumption of beef continue to rise, reflecting a significant trend. However, despite the critical importance of beef cattle resources in agriculture, the diversity of cattle breeds faces severe challenges, with many breeds at risk of extinction. The initiation of the Beef Cattle Genome Project is crucial. By constructing a high-precision functional annotation map of their genome, it becomes possible to analyze the genetic mechanisms underlying important traits in beef cattle, laying a solid foundation for breeding more efficient and productive cattle breeds. This review details advances in genome sequencing and assembly technologies, iterative upgrades of the beef cattle reference genome, and its application in pan-genome research. Additionally, it summarizes relevant studies on the discovery of functional genes associated with key traits in beef cattle, such as growth, meat quality, reproduction, polled traits, disease resistance, and environmental adaptability. Finally, the review explores the potential of telomere-to-telomere (T2T) genome assembly, structural variations (SVs), and multi-omics techniques in future beef cattle genetic breeding. These advancements collectively offer promising avenues for enhancing beef cattle breeding and improving genetic traits.
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Affiliation(s)
- Zhendong Gao
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Ying Lu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Yuqing Chong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Mengfei Li
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Jieyun Hong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Jiao Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dongwang Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dongmei Xi
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Weidong Deng
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, Kunming 650201, China
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4
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Kalleberg J, Rissman J, Schnabel RD. Overcoming Limitations to Deep Learning in Domesticated Animals with TrioTrain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.15.589602. [PMID: 38659907 PMCID: PMC11042298 DOI: 10.1101/2024.04.15.589602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Variant calling across diverse species remains challenging as most bioinformatics tools default to assumptions based on human genomes. DeepVariant (DV) excels without joint genotyping while offering fewer implementation barriers. However, the growing appeal of a "universal" algorithm has magnified the unknown impacts when used with non-human genomes. Here, we use bovine genomes to assess the limits of human-genome-trained models in other species. We introduce the first multi-species DV model that achieves a lower Mendelian Inheritance Error (MIE) rate during single-sample genotyping. Our novel approach, TrioTrain, automates extending DV for species without Genome In A Bottle (GIAB) resources and uses region shuffling to mitigate barriers for SLURM-based clusters. To offset imperfect truth labels for animal genomes, we remove Mendelian discordant variants before training, where models are tuned to genotype the offspring correctly. With TrioTrain, we use cattle, yak, and bison trios to build 30 model iterations across five phases. We observe remarkable performance across phases when testing the GIAB human trios with a mean SNP F1 score >0.990. In HG002, our phase 4 bovine model identifies more variants at a lower MIE rate than DeepTrio. In bovine F1-hybrid genomes, our model substantially reduces inheritance errors with a mean MIE rate of 0.03 percent. Although constrained by imperfect labels, we find that multi-species, trio-based training produces a robust variant calling model. Our research demonstrates that exclusively training with human genomes restricts the application of deep-learning approaches for comparative genomics.
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Affiliation(s)
- Jenna Kalleberg
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
| | - Jacob Rissman
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
| | - Robert D Schnabel
- University of Missouri, Division of Animal Sciences, Columbia, MO, 65201 USA
- University of Missouri, Genetics Area Program, Columbia, MO, 65201 USA
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5
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Leonard AS, Mapel XM, Pausch H. Pangenome-genotyped structural variation improves molecular phenotype mapping in cattle. Genome Res 2024; 34:300-309. [PMID: 38355307 PMCID: PMC10984387 DOI: 10.1101/gr.278267.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024]
Abstract
Expression and splicing quantitative trait loci (e/sQTL) are large contributors to phenotypic variability. Achieving sufficient statistical power for e/sQTL mapping requires large cohorts with both genotypes and molecular phenotypes, and so, the genomic variation is often called from short-read alignments, which are unable to comprehensively resolve structural variation. Here we build a pangenome from 16 HiFi haplotype-resolved cattle assemblies to identify small and structural variation and genotype them with PanGenie in 307 short-read samples. We find high (>90%) concordance of PanGenie-genotyped and DeepVariant-called small variation and confidently genotype close to 21 million small and 43,000 structural variants in the larger population. We validate 85% of these structural variants (with MAF > 0.1) directly with a subset of 25 short-read samples that also have medium coverage HiFi reads. We then conduct e/sQTL mapping with this comprehensive variant set in a subset of 117 cattle that have testis transcriptome data, and find 92 structural variants as causal candidates for eQTL and 73 for sQTL. We find that roughly half of the top associated structural variants affecting expression or splicing are transposable elements, such as SV-eQTL for STN1 and MYH7 and SV-sQTL for CEP89 and ASAH2 Extensive linkage disequilibrium between small and structural variation results in only 28 additional eQTL and 17 sQTL discovered when including SVs, although many top associated SVs are compelling candidates.
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Affiliation(s)
| | - Xena M Mapel
- Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, 8092 Zurich, Switzerland
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Wang J, Liu J, Guo Z. Natural uORF variation in plants. TRENDS IN PLANT SCIENCE 2024; 29:290-302. [PMID: 37640640 DOI: 10.1016/j.tplants.2023.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 07/04/2023] [Accepted: 07/19/2023] [Indexed: 08/31/2023]
Abstract
Taking advantage of natural variation promotes our understanding of phenotypic diversity and trait evolution, ultimately accelerating plant breeding, in which the identification of causal variations is critical. To date, sequence variations in the coding region and transcription level polymorphisms caused by variations in the promoter have been prioritized. An upstream open reading frame (uORF) in the 5' untranslated region (5' UTR) regulates gene expression at the post-transcription or translation level. In recent years, studies have demonstrated that natural uORF variations shape phenotypic diversity. This opinion article highlights recent researches and speculates on future directions for natural uORF variation in plants.
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Affiliation(s)
- Jiangen Wang
- Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Juhong Liu
- Fuzhou Institute for Data Technology Co., Ltd., Fuzhou 350207, China
| | - Zilong Guo
- Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
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7
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Miao J, Wei X, Cao C, Sun J, Xu Y, Zhang Z, Wang Q, Pan Y, Wang Z. Pig pangenome graph reveals functional features of non-reference sequences. J Anim Sci Biotechnol 2024; 15:32. [PMID: 38389084 PMCID: PMC10882747 DOI: 10.1186/s40104-023-00984-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 12/22/2023] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND The reliance on a solitary linear reference genome has imposed a significant constraint on our comprehensive understanding of genetic variation in animals. This constraint is particularly pronounced for non-reference sequences (NRSs), which have not been extensively studied. RESULTS In this study, we constructed a pig pangenome graph using 21 pig assemblies and identified 23,831 NRSs with a total length of 105 Mb. Our findings revealed that NRSs were more prevalent in breeds exhibiting greater genetic divergence from the reference genome. Furthermore, we observed that NRSs were rarely found within coding sequences, while NRS insertions were enriched in immune-related Gene Ontology terms. Notably, our investigation also unveiled a close association between novel genes and the immune capacity of pigs. We observed substantial differences in terms of frequencies of NRSs between Eastern and Western pigs, and the heat-resistant pigs exhibited a substantial number of NRS insertions in an 11.6 Mb interval on chromosome X. Additionally, we discovered a 665 bp insertion in the fourth intron of the TNFRSF19 gene that may be associated with the ability of heat tolerance in Southern Chinese pigs. CONCLUSIONS Our findings demonstrate the potential of a graph genome approach to reveal important functional features of NRSs in pig populations.
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Affiliation(s)
- Jian Miao
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Xingyu Wei
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Caiyun Cao
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Jiabao Sun
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Yuejin Xu
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Zhe Zhang
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Qishan Wang
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
- Yazhou Bay Science and Technology City, Hainan Institute of Zhejiang University, Yazhou District, Building 11, Yongyou Industrial Park, Sanya, 572025, Hainan, China
| | - Yuchun Pan
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
- Yazhou Bay Science and Technology City, Hainan Institute of Zhejiang University, Yazhou District, Building 11, Yongyou Industrial Park, Sanya, 572025, Hainan, China.
| | - Zhen Wang
- College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
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8
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Groza C, Schwendinger-Schreck C, Cheung WA, Farrow EG, Thiffault I, Lake J, Rizzo WB, Evrony G, Curran T, Bourque G, Pastinen T. Pangenome graphs improve the analysis of structural variants in rare genetic diseases. Nat Commun 2024; 15:657. [PMID: 38253606 PMCID: PMC10803329 DOI: 10.1038/s41467-024-44980-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 01/10/2024] [Indexed: 01/24/2024] Open
Abstract
Rare DNA alterations that cause heritable diseases are only partially resolvable by clinical next-generation sequencing due to the difficulty of detecting structural variation (SV) in all genomic contexts. Long-read, high fidelity genome sequencing (HiFi-GS) detects SVs with increased sensitivity and enables assembling personal and graph genomes. We leverage standard reference genomes, public assemblies (n = 94) and a large collection of HiFi-GS data from a rare disease program (Genomic Answers for Kids, GA4K, n = 574 assemblies) to build a graph genome representing a unified SV callset in GA4K, identify common variation and prioritize SVs that are more likely to cause genetic disease (MAF < 0.01). Using graphs, we obtain a higher level of reproducibility than the standard reference approach. We observe over 200,000 SV alleles unique to GA4K, including nearly 1000 rare variants that impact coding sequence. With improved specificity for rare SVs, we isolate 30 candidate SVs in phenotypically prioritized genes, including known disease SVs. We isolate a novel diagnostic SV in KMT2E, demonstrating use of personal assemblies coupled with pangenome graphs for rare disease genomics. The community may interrogate our pangenome with additional assemblies to discover new SVs within the allele frequency spectrum relevant to genetic diseases.
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Affiliation(s)
- Cristian Groza
- Quantitative Life Sciences, McGill University, Montréal, QC, Canada
| | | | - Warren A Cheung
- Genomic Medicine Center, Children's Mercy Hospital and Research Institute, KC, MO, USA
| | - Emily G Farrow
- Genomic Medicine Center, Children's Mercy Hospital and Research Institute, KC, MO, USA
| | - Isabelle Thiffault
- Genomic Medicine Center, Children's Mercy Hospital and Research Institute, KC, MO, USA
| | | | - William B Rizzo
- Child Health Research Institute, Department of Pediatrics, Nebraska Medical Center, Omaha, NE, USA
| | - Gilad Evrony
- Center for Human Genetics and Genomics, Department of Pediatrics, Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Tom Curran
- Children's Mercy Research Institute, Kansas City, MO, USA
| | - Guillaume Bourque
- Canadian Center for Computational Genomics, McGill University, Montréal, QC, Canada.
- Department of Human Genetics, McGill University, Montréal, QC, Canada.
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan.
- Victor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montréal, QC, Canada.
| | - Tomi Pastinen
- Genomic Medicine Center, Children's Mercy Hospital and Research Institute, KC, MO, USA.
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Mapel XM, Kadri NK, Leonard AS, He Q, Lloret-Villas A, Bhati M, Hiltpold M, Pausch H. Molecular quantitative trait loci in reproductive tissues impact male fertility in cattle. Nat Commun 2024; 15:674. [PMID: 38253538 PMCID: PMC10803364 DOI: 10.1038/s41467-024-44935-7] [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: 07/15/2023] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
Breeding bulls are well suited to investigate inherited variation in male fertility because they are genotyped and their reproductive success is monitored through semen analyses and thousands of artificial inseminations. However, functional data from relevant tissues are lacking in cattle, which prevents fine-mapping fertility-associated genomic regions. Here, we characterize gene expression and splicing variation in testis, epididymis, and vas deferens transcriptomes of 118 mature bulls and conduct association tests between 414,667 molecular phenotypes and 21,501,032 genome-wide variants to identify 41,156 regulatory loci. We show broad consensus in tissue-specific and tissue-enriched gene expression between the three bovine tissues and their human and murine counterparts. Expression- and splicing-mediating variants are more than three times as frequent in testis than epididymis and vas deferens, highlighting the transcriptional complexity of testis. Finally, we identify genes (WDR19, SPATA16, KCTD19, ZDHHC1) and molecular phenotypes that are associated with quantitative variation in male fertility through transcriptome-wide association and colocalization analyses.
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Affiliation(s)
- Xena Marie Mapel
- Animal Genomics, ETH Zurich, Universitatstrasse 2, 8092, Zurich, Switzerland
| | - Naveen Kumar Kadri
- Animal Genomics, ETH Zurich, Universitatstrasse 2, 8092, Zurich, Switzerland
| | - Alexander S Leonard
- Animal Genomics, ETH Zurich, Universitatstrasse 2, 8092, Zurich, Switzerland
| | - Qiongyu He
- Animal Genomics, ETH Zurich, Universitatstrasse 2, 8092, Zurich, Switzerland
| | | | - Meenu Bhati
- Animal Genomics, ETH Zurich, Universitatstrasse 2, 8092, Zurich, Switzerland
- Roslin Institute, The University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Maya Hiltpold
- Animal Genomics, ETH Zurich, Universitatstrasse 2, 8092, Zurich, Switzerland
- GenPhySE, Université de Toulouse, INRAE, ENVT, 31326, Castanet Tolosan, France
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, Universitatstrasse 2, 8092, Zurich, Switzerland.
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10
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Rice ES, Alberdi A, Alfieri J, Athrey G, Balacco JR, Bardou P, Blackmon H, Charles M, Cheng HH, Fedrigo O, Fiddaman SR, Formenti G, Frantz LAF, Gilbert MTP, Hearn CJ, Jarvis ED, Klopp C, Marcos S, Mason AS, Velez-Irizarry D, Xu L, Warren WC. A pangenome graph reference of 30 chicken genomes allows genotyping of large and complex structural variants. BMC Biol 2023; 21:267. [PMID: 37993882 PMCID: PMC10664547 DOI: 10.1186/s12915-023-01758-0] [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: 07/14/2023] [Accepted: 11/02/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND The red junglefowl, the wild outgroup of domestic chickens, has historically served as a reference for genomic studies of domestic chickens. These studies have provided insight into the etiology of traits of commercial importance. However, the use of a single reference genome does not capture diversity present among modern breeds, many of which have accumulated molecular changes due to drift and selection. While reference-based resequencing is well-suited to cataloging simple variants such as single-nucleotide changes and short insertions and deletions, it is mostly inadequate to discover more complex structural variation in the genome. METHODS We present a pangenome for the domestic chicken consisting of thirty assemblies of chickens from different breeds and research lines. RESULTS We demonstrate how this pangenome can be used to catalog structural variants present in modern breeds and untangle complex nested variation. We show that alignment of short reads from 100 diverse wild and domestic chickens to this pangenome reduces reference bias by 38%, which affects downstream genotyping results. This approach also allows for the accurate genotyping of a large and complex pair of structural variants at the K feathering locus using short reads, which would not be possible using a linear reference. CONCLUSIONS We expect that this new paradigm of genomic reference will allow better pinpointing of exact mutations responsible for specific phenotypes, which will in turn be necessary for breeding chickens that meet new sustainability criteria and are resilient to quickly evolving pathogen threats.
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Affiliation(s)
- Edward S Rice
- Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
- Faculty of Veterinary Medicine, Ludwig-Maximilians-Universität, Munich, Germany
| | - Antton Alberdi
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - James Alfieri
- Department of Ecology & Evolutionary Biology, Texas A&M University, College Station, TX, USA
| | - Giridhar Athrey
- Department of Poultry Science, Texas A&M University, College Station, TX, USA
| | - Jennifer R Balacco
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Philippe Bardou
- Sigenae, GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, 31326, France
| | - Heath Blackmon
- Department of Biology, Texas A&M University, College Station, TX, USA
| | - Mathieu Charles
- University Paris-Saclay, INRAE, AgroParisTech, GABI, Sigenae, Jouy-en-Josas, France
| | - Hans H Cheng
- Avian Disease and Oncology Laboratory, USDA, ARS, USNPRC, East Lansing, MI, USA
| | - Olivier Fedrigo
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | | | - Giulio Formenti
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
| | - Laurent A F Frantz
- Faculty of Veterinary Medicine, Ludwig-Maximilians-Universität, Munich, Germany
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4DQ, UK
| | - M Thomas P Gilbert
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - Cari J Hearn
- Avian Disease and Oncology Laboratory, USDA, ARS, USNPRC, East Lansing, MI, USA
| | - Erich D Jarvis
- Vertebrate Genome Laboratory, The Rockefeller University, New York, NY, USA
- The Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Christophe Klopp
- Sigenae, Genotoul Bioinfo, MIAT UR875, INRAE, Castanet Tolosan, France
| | - Sofia Marcos
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen (UCPH), Copenhagen, Denmark
- Applied Genomics and Bioinformatics, University of the Basque Country (UPV/EHU), Leioa, Bilbao, Spain
| | | | | | - Luohao Xu
- Key Laboratory of Freshwater Fish Reproduction and Development (Ministry of Education), Key Laboratory of Aquatic Science of Chongqing, School of Life Sciences, Southwest University, Chongqing, 400715, China
| | - Wesley C Warren
- Department of Animal Sciences, University of Missouri, Columbia, MO, USA.
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11
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Jang J, Jung J, Lee YH, Lee S, Baik M, Kim H. Chromosome-level genome assembly of Korean native cattle and pangenome graph of 14 Bos taurus assemblies. Sci Data 2023; 10:560. [PMID: 37612339 PMCID: PMC10447506 DOI: 10.1038/s41597-023-02453-z] [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: 03/06/2023] [Accepted: 08/08/2023] [Indexed: 08/25/2023] Open
Abstract
This study presents the first chromosome-level genome assembly of Hanwoo, an indigenous Korean breed of Bos taurus taurus. This is the first genome assembly of Asian taurus breed. Also, we constructed a pangenome graph of 14 B. taurus genome assemblies. The contig N50 was over 55 Mb, the scaffold N50 was over 89 Mb and a genome completeness of 95.8%, as estimated by BUSCO using the mammalian set, indicated a high-quality assembly. 48.7% of the genome comprised various repetitive elements, including DNAs, tandem repeats, long interspersed nuclear elements, and simple repeats. A total of 27,314 protein-coding genes were identified, including 25,302 proteins with inferred gene names and 2,012 unknown proteins. The pangenome graph of 14 B. taurus autosomes revealed 528.47 Mb non-reference regions in total and 61.87 Mb Hanwoo-specific regions. Our Hanwoo assembly and pangenome graph provide valuable resources for studying B. taurus populations.
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Affiliation(s)
- Jisung Jang
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Jaehoon Jung
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Korea
| | - Young Ho Lee
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Sanghyun Lee
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Korea
| | - Myunggi Baik
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Korea
| | - Heebal Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
- Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Korea.
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Sinha D, Maurya AK, Abdi G, Majeed M, Agarwal R, Mukherjee R, Ganguly S, Aziz R, Bhatia M, Majgaonkar A, Seal S, Das M, Banerjee S, Chowdhury S, Adeyemi SB, Chen JT. Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals. Genes (Basel) 2023; 14:1484. [PMID: 37510388 PMCID: PMC10380062 DOI: 10.3390/genes14071484] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.
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Affiliation(s)
- Dwaipayan Sinha
- Department of Botany, Government General Degree College, Mohanpur 721436, India
| | - Arun Kumar Maurya
- Department of Botany, Multanimal Modi College, Modinagar, Ghaziabad 201204, India
| | - Gholamreza Abdi
- Department of Biotechnology, Persian Gulf Research Institute, Persian Gulf University, Bushehr 75169, Iran
| | - Muhammad Majeed
- Department of Botany, University of Gujrat, Punjab 50700, Pakistan
| | - Rachna Agarwal
- Applied Genomics Section, Bhabha Atomic Research Centre, Mumbai 400085, India
| | - Rashmi Mukherjee
- Research Center for Natural and Applied Sciences, Department of Botany (UG & PG), Raja Narendralal Khan Women's College, Gope Palace, Midnapur 721102, India
| | - Sharmistha Ganguly
- Department of Dravyaguna, Institute of Post Graduate Ayurvedic Education and Research, Kolkata 700009, India
| | - Robina Aziz
- Department of Botany, Government, College Women University, Sialkot 51310, Pakistan
| | - Manika Bhatia
- TERI School of Advanced Studies, New Delhi 110070, India
| | - Aqsa Majgaonkar
- Department of Botany, St. Xavier's College (Autonomous), Mumbai 400001, India
| | - Sanchita Seal
- Department of Botany, Polba Mahavidyalaya, Polba 712148, India
| | - Moumita Das
- V. Sivaram Research Foundation, Bangalore 560040, India
| | - Swastika Banerjee
- Department of Botany, Kairali College of +3 Science, Champua, Keonjhar 758041, India
| | - Shahana Chowdhury
- Department of Biotechnology, Faculty of Engineering Sciences, German University Bangladesh, TNT Road, Telipara, Chandona Chowrasta, Gazipur 1702, Bangladesh
| | - Sherif Babatunde Adeyemi
- Ethnobotany/Phytomedicine Laboratory, Department of Plant Biology, Faculty of Life Sciences, University of Ilorin, Ilorin P.M.B 1515, Nigeria
| | - Jen-Tsung Chen
- Department of Life Sciences, National University of Kaohsiung, Kaohsiung 811, Taiwan
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