1
|
Liu J, Zhou SZ, Liu YL, Zhao BY, Yu D, Zhong MC, Jiang XD, Cui WH, Zhao JX, Qiu J, Liu LM, Guo ZH, Li HT, Tan DY, Hu JY, Li DZ. Genomes of Meniocus linifolius and Tetracme quadricornis reveal the ancestral karyotype and genomic features of core Brassicaceae. PLANT COMMUNICATIONS 2024; 5:100878. [PMID: 38475995 PMCID: PMC11287156 DOI: 10.1016/j.xplc.2024.100878] [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: 03/20/2023] [Revised: 03/03/2024] [Accepted: 03/11/2024] [Indexed: 03/14/2024]
Abstract
Brassicaceae represents an important plant family from both a scientific and economic perspective. However, genomic features related to the early diversification of this family have not been fully characterized, especially upon the uplift of the Tibetan Plateau, which was followed by increasing aridity in the Asian interior, intensifying monsoons in Eastern Asia, and significantly fluctuating daily temperatures. Here, we reveal the genomic architecture that accompanied early Brassicaceae diversification by analyzing two high-quality chromosome-level genomes for Meniocus linifolius (Arabodae; clade D) and Tetracme quadricornis (Hesperodae; clade E), together with genomes representing all major Brassicaceae clades and the basal Aethionemeae. We reconstructed an ancestral core Brassicaceae karyotype (CBK) containing 9 pseudochromosomes with 65 conserved syntenic genomic blocks and identified 9702 conserved genes in Brassicaceae. We detected pervasive conflicting phylogenomic signals accompanied by widespread ancient hybridization events, which correlate well with the early divergence of core Brassicaceae. We identified a successive Brassicaceae-specific expansion of the class I TREHALOSE-6-PHOSPHATE SYNTHASE 1 (TPS1) gene family, which encodes enzymes with essential regulatory roles in flowering time and embryo development. The TPS1s were mainly randomly amplified, followed by expression divergence. Our results provide fresh insights into historical genomic features coupled with Brassicaceae evolution and offer a potential model for broad-scale studies of adaptive radiation under an ever-changing environment.
Collapse
Affiliation(s)
- Jie Liu
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shi-Zhao Zhou
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yun-Long Liu
- Germplasm Bank of Wild Species & Yunnan Key Laboratory for Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Bin-Yan Zhao
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Dongmei Yu
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Mi-Cai Zhong
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Xiao-Dong Jiang
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Wei-Hua Cui
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Jiu-Xia Zhao
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Juan Qiu
- College of Life Sciences, Xinjiang Agricultural University, Ürümqi 830052, China
| | - Liang-Min Liu
- Germplasm Bank of Wild Species & Yunnan Key Laboratory for Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhen-Hua Guo
- Germplasm Bank of Wild Species & Yunnan Key Laboratory for Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Hong-Tao Li
- Germplasm Bank of Wild Species & Yunnan Key Laboratory for Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Dun-Yan Tan
- College of Life Sciences, Xinjiang Agricultural University, Ürümqi 830052, China
| | - Jin-Yong Hu
- CAS Key Laboratory for Plant Diversity and Biogeography of East Asia & Yunnan Key Laboratory of Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China.
| | - De-Zhu Li
- Germplasm Bank of Wild Species & Yunnan Key Laboratory for Crop Wild Relatives Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China.
| |
Collapse
|
2
|
Cribbie EP, Doerr D, Chauve C. AGO, a Framework for the Reconstruction of Ancestral Syntenies and Gene Orders. Methods Mol Biol 2024; 2802:247-265. [PMID: 38819563 DOI: 10.1007/978-1-0716-3838-5_10] [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] [Indexed: 06/01/2024]
Abstract
Reconstructing ancestral gene orders from the genome data of extant species is an important problem in comparative and evolutionary genomics. In a phylogenomics setting that accounts for gene family evolution through gene duplication and gene loss, the reconstruction of ancestral gene orders involves several steps, including multiple sequence alignment, the inference of reconciled gene trees, and the inference of ancestral syntenies and gene adjacencies. For each of the steps of such a process, several methods can be used and implemented using a growing corpus of, often parameterized, tools; in practice, interfacing such tools into an ancestral gene order reconstruction pipeline is far from trivial. This chapter introduces AGO, a Python-based framework aimed at creating ancestral gene order reconstruction pipelines allowing to interface and parameterize different bioinformatics tools. The authors illustrate the features of AGO by reconstructing ancestral gene orders for the X chromosome of three ancestral Anopheles species using three different pipelines. AGO is freely available at https://github.com/cchauve/AGO-pipeline .
Collapse
Affiliation(s)
- Evan P Cribbie
- Department of Mathematics, Simon Fraser University, Burnaby, BC, Canada
| | - Daniel Doerr
- Department for Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, German Diabetes Center (DDZ), Leibniz Institute for Diabetes Research, and Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - Cedric Chauve
- Department of Mathematics, Simon Fraser University, Burnaby, BC, Canada.
| |
Collapse
|
3
|
Xu Q, Jin L, Zheng C, Zhang X, Leebens-Mack J, Sankoff D. From comparative gene content and gene order to ancestral contigs, chromosomes and karyotypes. Sci Rep 2023; 13:6095. [PMID: 37055453 PMCID: PMC10102168 DOI: 10.1038/s41598-023-33029-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 04/06/2023] [Indexed: 04/15/2023] Open
Abstract
To reconstruct the ancestral genome of a set of phylogenetically related descendant species, we use the RACCROCHE pipeline for organizing a large number of generalized gene adjacencies into contigs and then into chromosomes. Separate reconstructions are carried out for each ancestral node of the phylogenetic tree for focal taxa. The ancestral reconstructions are monoploids; they each contain at most one member of each gene family constructed from descendants, ordered along the chromosomes. We design and implement a new computational technique for solving the problem of estimating the ancestral monoploid number of chromosomes x. This involves a "g-mer" analysis to resolve a bias due long contigs, and gap statistics to estimate x. We find that the monoploid number of all the rosid and asterid orders is [Formula: see text]. We show that this is not an artifact of our method by deriving [Formula: see text] for the metazoan ancestor.
Collapse
Affiliation(s)
- Qiaoji Xu
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada
| | - Lingling Jin
- Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, S7N 5C9, Canada
| | - Chunfang Zheng
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada
| | - Xiaomeng Zhang
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada
| | - James Leebens-Mack
- Department of Plant Biology, University of Georgia, Athens, Georgia, 30602, USA
| | - David Sankoff
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada.
| |
Collapse
|
4
|
Gao S, Yang X, Sun J, Zhao X, Wang B, Ye K. IAGS: Inferring Ancestor Genome Structure under a wide range of evolutionary scenarios. Mol Biol Evol 2022; 39:6530294. [PMID: 35176153 PMCID: PMC8896626 DOI: 10.1093/molbev/msac041] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Significant improvements in genome sequencing and assembly technology have led to increasing numbers of high-quality genomes, revealing complex evolutionary scenarios such as multiple whole-genome duplication events, which hinders ancestral genome reconstruction via the currently available computational frameworks. Here, we present the Inferring Ancestor Genome Structure (IAGS) framework, a novel block/endpoint matching optimization strategy with single-cut-or-join distance, to allow ancestral genome reconstruction under both simple (single-copy ancestor) and complex (multicopy ancestor) scenarios. We evaluated IAGS with two simulated data sets and applied it to four different real evolutionary scenarios to demonstrate its performance and general applicability. IAGS is available at https://github.com/xjtu-omics/IAGS.
Collapse
Affiliation(s)
- Shenghan Gao
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiaofei Yang
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jianyong Sun
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China
| | - Xixi Zhao
- Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Bo Wang
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Kai Ye
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,Faculty of Science, Leiden University, Leiden, The Netherlands
| |
Collapse
|
5
|
Xu Q, Jin L, Zhang Y, Zhang X, Zheng C, Leebens-Mack JH, Sankoff D. Ancestral Flowering Plant Chromosomes and Gene Orders Based on Generalized Adjacencies and Chromosomal Gene Co-Occurrences. J Comput Biol 2021; 28:1156-1179. [PMID: 34783601 DOI: 10.1089/cmb.2021.0340] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Recurrent whole genome duplication and the ensuing loss of redundant genes-fractionation-complicate efforts to reconstruct the gene orders and chromosomes of the ancestors associated with the nodes of a phylogeny. Loss of genes disrupts the gene adjacencies key to current techniques. With our RACCROCHE pipeline, instead of starting with the inference of short ancestral segments, we suggest delaying the choice of gene adjacencies while we accumulate many more syntenically validated generalized (gapped) adjacencies. We obtain longer ancestral contigs using maximum weight matching (MWM). Similarly, we do not construct chromosomes by successively piecing together contigs into larger segments, but rather compile counts of pairwise contig co-occurrences on the set of extant genomes and use these to cluster the contigs. Chromosome-level contig assemblies for a monoploid genome emerge naturally at each node of the phylogeny and the contigs then can be ordered along the chromosome. Sampling alternative MWM solutions, visualizing heat maps, and applying gap statistics allow us to estimate the number of chromosomes in the reconstruction. We introduce several measures of quality: length of contigs, continuity of contig structure on successive ancestors, coverage of the extant genome by the reconstruction, and rearrangement relations among the inferred chromosomes. The reconstructed ancestors are visualized by painting the ancestral projections on the descendant genomes. We submit genomes drawn from a broad range of monocot orders to our pipeline, confirming the tetraploidization event "tau" in the stem lineage between the alismatids and the lilioids. We show additional applications to the Solanaceae and to four Brassica genomes, producing evidence about the monoploid ancestor in each case.
Collapse
Affiliation(s)
- Qiaoji Xu
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, Canada
| | - Lingling Jin
- Department of Computer Science, University of Saskatchewan, Saskatoon, Canada
| | - Yue Zhang
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, Canada
| | - Xiaomeng Zhang
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, Canada
| | - Chunfang Zheng
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, Canada
| | | | - David Sankoff
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, Canada
| |
Collapse
|
6
|
Yang X, Gao S, Guo L, Wang B, Jia Y, Zhou J, Che Y, Jia P, Lin J, Xu T, Sun J, Ye K. Three chromosome-scale Papaver genomes reveal punctuated patchwork evolution of the morphinan and noscapine biosynthesis pathway. Nat Commun 2021; 12:6030. [PMID: 34654815 PMCID: PMC8521590 DOI: 10.1038/s41467-021-26330-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 09/29/2021] [Indexed: 01/07/2023] Open
Abstract
For millions of years, plants evolve plenty of structurally diverse secondary metabolites (SM) to support their sessile lifestyles through continuous biochemical pathway innovation. While new genes commonly drive the evolution of plant SM pathway, how a full biosynthetic pathway evolves remains poorly understood. The evolution of pathway involves recruiting new genes along the reaction cascade forwardly, backwardly, or in a patchwork manner. With three chromosome-scale Papaver genome assemblies, we here reveal whole-genome duplications (WGDs) apparently accelerate chromosomal rearrangements with a nonrandom distribution towards SM optimization. A burst of structural variants involving fusions, translocations and duplications within 7.7 million years have assembled nine genes into the benzylisoquinoline alkaloids gene cluster, following a punctuated patchwork model. Biosynthetic gene copies and their total expression matter to morphinan production. Our results demonstrate how new genes have been recruited from a WGD-induced repertoire of unregulated enzymes with promiscuous reactivities to innovate efficient metabolic pathways with spatiotemporal constraint.
Collapse
Affiliation(s)
- Xiaofei Yang
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Shenghan Gao
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Li Guo
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Bo Wang
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Yanyan Jia
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jian Zhou
- College of Life Sciences, Henan Normal University, Xinxiang, Henan, China
| | - Yizhuo Che
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Peng Jia
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jiadong Lin
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,Faculty of Science, Leiden University, Leiden, The Netherlands
| | - Tun Xu
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.,School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jianyong Sun
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Kai Ye
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China. .,Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China. .,School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China. .,School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China. .,Faculty of Science, Leiden University, Leiden, The Netherlands.
| |
Collapse
|
7
|
|