1
|
van Wijk KJ, Leppert T, Sun Z, Guzchenko I, Debley E, Sauermann G, Routray P, Mendoza L, Sun Q, Deutsch EW. The Zea mays PeptideAtlas: A New Maize Community Resource. J Proteome Res 2024. [PMID: 39101213 DOI: 10.1021/acs.jproteome.4c00320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2024]
Abstract
This study presents the Maize PeptideAtlas resource (www.peptideatlas.org/builds/maize) to help solve questions about the maize proteome. Publicly available raw tandem mass spectrometry (MS/MS) data for maize collected from ProteomeXchange were reanalyzed through a uniform processing and metadata annotation pipeline. These data are from a wide range of genetic backgrounds and many sample types and experimental conditions. The protein search space included different maize genome annotations for the B73 inbred line from MaizeGDB, UniProtKB, NCBI RefSeq, and for the W22 inbred line. 445 million MS/MS spectra were searched, of which 120 million were matched to 0.37 million distinct peptides. Peptides were matched to 66.2% of proteins in the most recent B73 nuclear genome annotation. Furthermore, most conserved plastid- and mitochondrial-encoded proteins (NCBI RefSeq annotations) were identified. Peptides and proteins identified in the other B73 genome annotations will improve maize genome annotation. We also illustrate the high-confidence detection of unique W22 proteins. N-terminal acetylation, phosphorylation, ubiquitination, and three lysine acylations (K-acetyl, K-malonyl, and K-hydroxyisobutyryl) were identified and can be inspected through a PTM viewer in PeptideAtlas. All matched MS/MS-derived peptide data are linked to spectral, technical, and biological metadata. This new PeptideAtlas is integrated in MaizeGDB with a peptide track in JBrowse.
Collapse
Affiliation(s)
- Klaas J van Wijk
- Section of Plant Biology, School of Integrative Plant Sciences (SIPS), Cornell University, Ithaca, New York 14853, United States
| | - Tami Leppert
- Institute for Systems Biology (ISB), Seattle, Washington 98109, United States
| | - Zhi Sun
- Institute for Systems Biology (ISB), Seattle, Washington 98109, United States
| | - Isabell Guzchenko
- Section of Plant Biology, School of Integrative Plant Sciences (SIPS), Cornell University, Ithaca, New York 14853, United States
| | - Erica Debley
- Section of Plant Biology, School of Integrative Plant Sciences (SIPS), Cornell University, Ithaca, New York 14853, United States
| | - Georgia Sauermann
- Section of Plant Biology, School of Integrative Plant Sciences (SIPS), Cornell University, Ithaca, New York 14853, United States
| | - Pratyush Routray
- Section of Plant Biology, School of Integrative Plant Sciences (SIPS), Cornell University, Ithaca, New York 14853, United States
| | - Luis Mendoza
- Institute for Systems Biology (ISB), Seattle, Washington 98109, United States
| | - Qi Sun
- Computational Biology Service Unit, Cornell University, Ithaca, New York 14853, United States
| | - Eric W Deutsch
- Institute for Systems Biology (ISB), Seattle, Washington 98109, United States
| |
Collapse
|
2
|
Jamil S, Ahmad S, Shahzad R, Umer N, Kanwal S, Rehman HM, Rana IA, Atif RM. Leveraging Multiomics Insights and Exploiting Wild Relatives' Potential for Drought and Heat Tolerance in Maize. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:16048-16075. [PMID: 38980762 DOI: 10.1021/acs.jafc.4c01375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
Climate change, particularly drought and heat stress, may slash agricultural productivity by 25.7% by 2080, with maize being the hardest hit. Therefore, unraveling the molecular nature of plant responses to these stressors is vital for the development of climate-smart maize. This manuscript's primary objective was to examine how maize plants respond to these stresses, both individually and in combination. Additionally, the paper delved into harnessing the potential of maize wild relatives as a valuable genetic resource and leveraging AI-based technologies to boost maize resilience. The role of multiomics approaches particularly genomics and transcriptomics in dissecting the genetic basis of stress tolerance was also highlighted. The way forward was proposed to utilize a bunch of information obtained through omics technologies by an interdisciplinary state-of-the-art forward-looking big-data, cyberagriculture system, and AI-based approach to orchestrate the development of climate resilient maize genotypes.
Collapse
Affiliation(s)
- Shakra Jamil
- Agricultural Biotechnology Research Institute, Ayub Agricultural Research Institute, Faisalabad 38000, Pakistan
| | - Shakeel Ahmad
- Seed Centre and Plant Genetic Resources Bank Ministry of Environment, Water and Agriculture, Riyadh 14712, Saudi Arabia
| | - Rahil Shahzad
- Agricultural Biotechnology Research Institute, Ayub Agricultural Research Institute, Faisalabad 38000, Pakistan
| | - Noroza Umer
- Dr. Ikram ul Haq - Institute of Industrial Biotechnology, Government College University, Lahore 54590, Pakistan
| | - Shamsa Kanwal
- Agricultural Biotechnology Research Institute, Ayub Agricultural Research Institute, Faisalabad 38000, Pakistan
| | - Hafiz Mamoon Rehman
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad 38000, Pakistan
| | - Iqrar Ahmad Rana
- Centre for Advanced Studies in Agriculture and Food Security, University of Agriculture, Faisalabad 38000, Pakistan
| | - Rana Muhammad Atif
- Department of Plant Sciences, University of California Davis, California 95616, United States
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad 38000, Pakistan
- Precision Agriculture and Analytics Lab, Centre for Advanced Studies in Agriculture and Food Security, National Centre in Big Data and Cloud Computing, University of Agriculture, Faisalabad 38000, Pakistan
| |
Collapse
|
3
|
Naumann TA, Dowling NV, Price NPJ, Rose DR. In vitro functional analysis and in silico structural modelling of pathogen-secreted polyglycine hydrolases. Biochem Biophys Res Commun 2024; 706:149746. [PMID: 38461646 DOI: 10.1016/j.bbrc.2024.149746] [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: 11/29/2023] [Revised: 02/16/2024] [Accepted: 03/01/2024] [Indexed: 03/12/2024]
Abstract
Polyglycine hydrolases are fungal effectors composed of an N-domain with unique sequence and structure and a C-domain that resembles β-lactamases, with serine protease activity. These secreted fungal proteins cleave Gly-Gly bonds within a polyglycine sequence in corn ChitA chitinase. The polyglycine hydrolase N-domain (PND) function is unknown. In this manuscript we provide evidence that the PND does not directly participate in ChitA cleavage. In vitro analysis of site-directed mutants in conserved residues of the PND of polyglycine hydrolase Es-cmp did not specifically impair protease activity. Furthermore, in silico structural models of three ChitA-bound polyglycine hydrolases created by High Ambiguity Driven protein-protein DOCKing (HADDOCK) did not predict significant interactions between the PND and ChitA. Together these results suggest that the PND has another function. To determine what types of PND-containing proteins exist in nature we performed a computational analysis of Foldseek-identified PND-containing proteins. The analysis showed that proteins with PNDs are present throughout biology as either single domain proteins or fused to accessory domains that are diverse but are usually proteases or kinases.
Collapse
Affiliation(s)
- Todd A Naumann
- USDA, Agricultural Research Service, National Center for Agricultural Utilization Research, Mycotoxin Prevention and Applied Microbiology Research Unit, 1815 N. University, Peoria, IL, 61604, USA.
| | - Nicole V Dowling
- Department of Biology, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Neil P J Price
- USDA, Agricultural Research Service, National Center for Agricultural Utilization Research, Renewable Product Technologies Research Unit, 1815 N. University, Peoria, IL, 61604, USA
| | - David R Rose
- Department of Biology, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| |
Collapse
|
4
|
Tsai H, Kippes N, Firl A, Lieberman M, Comai L, Henry IM. Efficient construction of a linkage map and haplotypes for Mentha suaveolens using sequence capture. G3-GENES GENOMES GENETICS 2021; 11:6321234. [PMID: 34544134 PMCID: PMC8496254 DOI: 10.1093/g3journal/jkab232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 06/25/2021] [Indexed: 11/12/2022]
Abstract
The sustainability of many crops is hindered by the lack of genomic resources and a poor understanding of natural genetic diversity. Particularly, application of modern breeding requires high-density linkage maps that are integrated into a highly contiguous reference genome. Here, we present a rapid method for deriving haplotypes and developing linkage maps, and its application to Mentha suaveolens, one of the diploid progenitors of cultivated mints. Using sequence-capture via DNA hybridization to target single nucleotide polymorphisms (SNPs), we successfully genotyped ∼5000 SNPs within the genome of >400 individuals derived from a self cross. After stringent quality control, and identification of nonredundant SNPs, 1919 informative SNPs were retained for linkage map construction. The resulting linkage map defined a total genetic space of 942.17 cM divided among 12 linkage groups, ranging from 56.32 to 122.61 cM in length. The linkage map is in good agreement with pseudomolecules from our preliminary genome assembly, proving this resource effective for the correction and validation of the reference genome. We discuss the advantages of this method for the rapid creation of linkage maps.
Collapse
Affiliation(s)
- Helen Tsai
- Department of Plant Biology and Genome Center, University of California, Davis, Davis, CA 95616, USA
| | - Nestor Kippes
- Department of Plant Biology and Genome Center, University of California, Davis, Davis, CA 95616, USA
| | - Alana Firl
- Department of Plant Biology and Genome Center, University of California, Davis, Davis, CA 95616, USA
| | - Meric Lieberman
- Department of Plant Biology and Genome Center, University of California, Davis, Davis, CA 95616, USA
| | - Luca Comai
- Department of Plant Biology and Genome Center, University of California, Davis, Davis, CA 95616, USA
| | - Isabelle M Henry
- Department of Plant Biology and Genome Center, University of California, Davis, Davis, CA 95616, USA
| |
Collapse
|
5
|
Fan K, Yuan S, Chen J, Chen Y, Li Z, Lin W, Zhang Y, Liu J, Lin W. Molecular evolution and lineage-specific expansion of the PP2C family in Zea mays. PLANTA 2019; 250:1521-1538. [PMID: 31346803 DOI: 10.1007/s00425-019-03243-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 07/16/2019] [Indexed: 05/19/2023]
Abstract
97 ZmPP2Cs were clustered into 10 subfamilies with biased subfamily evolution and lineage-specific expansion. Segmental duplication after the divergence of maize and sorghum might have led to primary expansion of ZmPP2Cs. The protein phosphatase 2C (PP2C) enzymes control many stress responses and developmental processes in plants. In Zea mays, a comprehensive understanding of the evolution and expansion of the PP2C family is still lacking. In the current study, 97 ZmPP2Cs were identified and clustered into 10 subfamilies. Through the analysis of the PP2C family in monocots, the ZmPP2C subfamilies displayed biased subfamily molecular evolution and lineage-specific expansion, as evidenced by their differing numbers of member genes, expansion and evolutionary rates, conserved subdomains, chromosomal distributions, expression levels, responsive-regulatory elements and regulatory networks. Moreover, while segmental duplication events have caused the primary expansion of the ZmPP2Cs, the majority of their diversification occurred following the additional whole-genome duplication that took place after the divergence of maize and sorghum (Sorghum bicolor). After this event, the PP2C subfamilies showed asymmetric evolutionary rates, with the D, F2 and H subfamily likely the most closely to resemble its ancestral subfamily's genes. These findings could provide novel insights into the molecular evolution and expansion of the PP2C family in maize, and lay the foundation for the functional analysis of these enzymes in maize and related monocots.
Collapse
Affiliation(s)
- Kai Fan
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, College of Crop Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 35002, China
| | - Shuna Yuan
- Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences/Danzhou Investigation and Experiment Station of Tropical Crops, Ministry of Agriculture, Danzhou, 571737, China
| | - Jie Chen
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, College of Crop Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 35002, China
| | - Yunrui Chen
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, College of Crop Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 35002, China
| | - Zhaowei Li
- Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 35002, China
| | - Weiwei Lin
- Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 35002, China
| | - Yongqiang Zhang
- Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 35002, China
| | - Jianping Liu
- Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
- Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 35002, China
| | - Wenxiong Lin
- Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, College of Crop Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
- Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
- Key Laboratory of Crop Ecology and Molecular Physiology (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou, 35002, China.
| |
Collapse
|
6
|
Washburn JD, Mejia-Guerra MK, Ramstein G, Kremling KA, Valluru R, Buckler ES, Wang H. Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence. Proc Natl Acad Sci U S A 2019; 116:5542-5549. [PMID: 30842277 PMCID: PMC6431157 DOI: 10.1073/pnas.1814551116] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Deep learning methodologies have revolutionized prediction in many fields and show potential to do the same in molecular biology and genetics. However, applying these methods in their current forms ignores evolutionary dependencies within biological systems and can result in false positives and spurious conclusions. We developed two approaches that account for evolutionary relatedness in machine learning models: (i) gene-family-guided splitting and (ii) ortholog contrasts. The first approach accounts for evolution by constraining model training and testing sets to include different gene families. The second approach uses evolutionarily informed comparisons between orthologous genes to both control for and leverage evolutionary divergence during the training process. The two approaches were explored and validated within the context of mRNA expression level prediction and have the area under the ROC curve (auROC) values ranging from 0.75 to 0.94. Model weight inspections showed biologically interpretable patterns, resulting in the hypothesis that the 3' UTR is more important for fine-tuning mRNA abundance levels while the 5' UTR is more important for large-scale changes.
Collapse
Affiliation(s)
- Jacob D Washburn
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853
| | | | | | - Karl A Kremling
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853
| | - Ravi Valluru
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853;
- Agricultural Research Service, United States Department of Agriculture, Ithaca, NY 14850
| | - Hai Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, 100081 Beijing, China
- Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853
| |
Collapse
|
7
|
Andorf C, Beavis WD, Hufford M, Smith S, Suza WP, Wang K, Woodhouse M, Yu J, Lübberstedt T. Technological advances in maize breeding: past, present and future. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:817-849. [PMID: 30798332 DOI: 10.1007/s00122-019-03306-3] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Accepted: 02/05/2019] [Indexed: 05/18/2023]
Abstract
Maize has for many decades been both one of the most important crops worldwide and one of the primary genetic model organisms. More recently, maize breeding has been impacted by rapid technological advances in sequencing and genotyping technology, transformation including genome editing, doubled haploid technology, parallelled by progress in data sciences and the development of novel breeding approaches utilizing genomic information. Herein, we report on past, current and future developments relevant for maize breeding with regard to (1) genome analysis, (2) germplasm diversity characterization and utilization, (3) manipulation of genetic diversity by transformation and genome editing, (4) inbred line development and hybrid seed production, (5) understanding and prediction of hybrid performance, (6) breeding methodology and (7) synthesis of opportunities and challenges for future maize breeding.
Collapse
Affiliation(s)
| | - William D Beavis
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | - Matthew Hufford
- Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA, 50011-1010, USA
| | - Stephen Smith
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | - Walter P Suza
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | - Kan Wang
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | | | - Jianming Yu
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | - Thomas Lübberstedt
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA.
| |
Collapse
|
8
|
Okagaki RJ, Dukowic-Schulze S, Eggleston WB, Muehlbauer GJ. A Critical Assessment of 60 Years of Maize Intragenic Recombination. FRONTIERS IN PLANT SCIENCE 2018; 9:1560. [PMID: 30420864 PMCID: PMC6215864 DOI: 10.3389/fpls.2018.01560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Accepted: 10/04/2018] [Indexed: 06/09/2023]
Abstract
Until the mid-1950s, it was believed that genetic crossovers did not occur within genes. Crossovers occurred between genes, the "beads on a string" model. Then in 1956, Seymour Benzer published his classic paper describing crossing over within a gene, intragenic recombination. This result from a bacteriophage gene prompted Oliver Nelson to study intragenic recombination in the maize Waxy locus. His studies along with subsequent work by others working with maize and other organisms described the outcomes of intragenic recombination and provided some of the earliest evidence that genes, not intergenic regions, were recombination hotspots. High-throughput genotyping approaches have since replaced single gene intragenic studies for characterizing the outcomes of recombination. These large-scale studies confirm that genes, or more generally genic regions, are the most active recombinogenic regions, and suggested a pattern of crossovers similar to the budding yeast Saccharomyces cerevisiae. In S. cerevisiae recombination is initiated by double-strand breaks (DSBs) near transcription start sites (TSSs) of genes producing a polarity gradient where crossovers preferentially resolve at the 5' end of genes. Intragenic studies in maize yielded less evidence for either polarity or for DSBs near TSSs initiating recombination and in certain respects resembled Schizosaccharomyces pombe or mouse. These different perspectives highlight the need to draw upon the strengths of different approaches and caution against relying on a single model system or approach for understanding recombination.
Collapse
Affiliation(s)
- Ron J. Okagaki
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, United States
| | | | - William B. Eggleston
- Department of Biology, Virginia Commonwealth University, St. Paul, MN, United States
| | - Gary J. Muehlbauer
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, United States
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, MN, United States
| |
Collapse
|
9
|
Gao Y, Zhang L, Zhao S, Yan Y. Comparative analysis of the male inflorescence transcriptome profiles of an ms22 mutant of maize. PLoS One 2018; 13:e0199437. [PMID: 30005064 PMCID: PMC6044530 DOI: 10.1371/journal.pone.0199437] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 06/07/2018] [Indexed: 11/18/2022] Open
Abstract
In modern agricultural production, maize is the most successful crop utilizing heterosis. 712C-ms22 is an important male sterile material in maize. In this study, we performed transcriptome sequencing analysis of the V10 stage of male inflorescence. Through this analysis, 27.63 million raw reads were obtained, and trimming of the raw data revealed 26.63 million clean reads, with an average match rate of 94.64%. Using Tophat software, we matched these clean reads to the maize reference genome. The abundance of 39,622 genes was measured, and 35,399 genes remained after filtering out the non-expressed genes across all the samples. These genes were classified into 19 categories by clusters of orthologous groups of protein annotation. Transcriptome sequencing analysis of the male sterile and fertile 712C-ms22 maize revealed some key DEGs that may be related to metabolic pathways. qRT-PCR analysis validated the gene expression patterns identified by RNA-seq. This analysis revealed some of the essential genes responsible for pollen development and for pollen tube elongation. Our findings provide useful markers of male sterility and new insights into the global mechanisms mediating male sterility in maize.
Collapse
Affiliation(s)
- Yonggang Gao
- Nanjing Agricultural University, Nanjing, Jiangsu, China
- * E-mail: (YG); (YY)
| | - LiJuan Zhang
- Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - ShengChao Zhao
- Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - Yuanxin Yan
- Nanjing Agricultural University, Nanjing, Jiangsu, China
- * E-mail: (YG); (YY)
| |
Collapse
|
10
|
Chang PK, Zhang Q, Scharfenstein L, Mack B, Yoshimi A, Miyazawa K, Abe K. Aspergillus flavus GPI-anchored protein-encoding ecm33 has a role in growth, development, aflatoxin biosynthesis, and maize infection. Appl Microbiol Biotechnol 2018; 102:5209-5220. [DOI: 10.1007/s00253-018-9012-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 04/09/2018] [Accepted: 04/10/2018] [Indexed: 12/21/2022]
|
11
|
Underwood CJ, Choi K, Lambing C, Zhao X, Serra H, Borges F, Simorowski J, Ernst E, Jacob Y, Henderson IR, Martienssen RA. Epigenetic activation of meiotic recombination near Arabidopsis thaliana centromeres via loss of H3K9me2 and non-CG DNA methylation. Genome Res 2018; 28:519-531. [PMID: 29530927 PMCID: PMC5880242 DOI: 10.1101/gr.227116.117] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 01/15/2018] [Indexed: 02/02/2023]
Abstract
Eukaryotic centromeres contain the kinetochore, which connects chromosomes to the spindle allowing segregation. During meiosis, centromeres are suppressed for inter-homolog crossover, as recombination in these regions can cause chromosome missegregation and aneuploidy. Plant centromeres are surrounded by transposon-dense pericentromeric heterochromatin that is epigenetically silenced by histone 3 lysine 9 dimethylation (H3K9me2), and DNA methylation in CG and non-CG sequence contexts. However, the role of these chromatin modifications in control of meiotic recombination in the pericentromeres is not fully understood. Here, we show that disruption of Arabidopsis thaliana H3K9me2 and non-CG DNA methylation pathways, for example, via mutation of the H3K9 methyltransferase genes KYP/SUVH4 SUVH5 SUVH6, or the CHG DNA methyltransferase gene CMT3, increases meiotic recombination in proximity to the centromeres. Using immunocytological detection of MLH1 foci and genotyping by sequencing of recombinant plants, we observe that H3K9me2 and non-CG DNA methylation pathway mutants show increased pericentromeric crossovers. Increased pericentromeric recombination in H3K9me2/non-CG mutants occurs in hybrid and inbred backgrounds and likely involves contributions from both the interfering and noninterfering crossover repair pathways. We also show that meiotic DNA double-strand breaks (DSBs) increase in H3K9me2/non-CG mutants within the pericentromeres, via purification and sequencing of SPO11-1-oligonucleotides. Therefore, H3K9me2 and non-CG DNA methylation exert a repressive effect on both meiotic DSB and crossover formation in plant pericentromeric heterochromatin. Our results may account for selection of enhancer trap Dissociation (Ds) transposons into the CMT3 gene by recombination with proximal transposon launch-pads.
Collapse
Affiliation(s)
- Charles J. Underwood
- Howard Hughes Medical Institute, Watson School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA;,Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom
| | - Kyuha Choi
- Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom
| | - Christophe Lambing
- Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom
| | - Xiaohui Zhao
- Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom
| | - Heïdi Serra
- Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom
| | - Filipe Borges
- Howard Hughes Medical Institute, Watson School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Joe Simorowski
- Howard Hughes Medical Institute, Watson School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Evan Ernst
- Howard Hughes Medical Institute, Watson School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Yannick Jacob
- Howard Hughes Medical Institute, Watson School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Ian R. Henderson
- Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, United Kingdom
| | - Robert A. Martienssen
- Howard Hughes Medical Institute, Watson School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| |
Collapse
|
12
|
Yurkevich OY, Kirov IV, Bolsheva NL, Rachinskaya OA, Grushetskaya ZE, Zoschuk SA, Samatadze TE, Bogdanova MV, Lemesh VA, Amosova AV, Muravenko OV. Integration of Physical, Genetic, and Cytogenetic Mapping Data for Cellulose Synthase ( CesA) Genes in Flax ( Linum usitatissimum L.). FRONTIERS IN PLANT SCIENCE 2017; 8:1467. [PMID: 28878799 PMCID: PMC5572355 DOI: 10.3389/fpls.2017.01467] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2017] [Accepted: 08/07/2017] [Indexed: 05/07/2023]
Abstract
Flax, Linum usitatissimum L., is a valuable multi-purpose plant, and currently, its genome is being extensively investigated. Nevertheless, mapping of genes in flax genome is still remaining a challenging task. The cellulose synthase (CesA) multigene family involving in the process of cellulose synthesis is especially important for metabolism of this fiber crop. For the first time, fluorescent in situ hybridization (FISH)-based chromosomal localization of the CesA conserved fragment (KF011584.1), 5S, and 26S rRNA genes was performed in landrace, oilseed, and fiber varieties of L. usitatissimum. Intraspecific polymorphism in chromosomal distribution of KF011584.1 and 5S DNA loci was revealed, and the generalized chromosome ideogram was constructed. Using BLAST analysis, available data on physical/genetic mapping and also whole-genome sequencing of flax, localization of KF011584.1, 45S, and 5S rRNA sequences on genomic scaffolds, and their anchoring to the genetic map were conducted. The alignment of the results of FISH and BLAST analyses indicated that KF011584.1 fragment revealed on chromosome 3 could be anchored to linkage group (LG) 11. The common LG for 45S and 5S rDNA was not found probably due to the polymorphic localization of 5S rDNA on chromosome 1. Our findings indicate the complexity of integration of physical, genetic, and cytogenetic mapping data for multicopy gene families in plants. Nevertheless, the obtained results can be useful for future progress in constructing of integrated physical/genetic/cytological maps in L. usitatissimum which are essential for flax breeding.
Collapse
Affiliation(s)
- Olga Y. Yurkevich
- Engelhardt Institute of Molecular Biology, Russian Academy of SciencesMoscow, Russia
| | - Ilya V. Kirov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of SciencesMoscow, Russia
| | - Nadezhda L. Bolsheva
- Engelhardt Institute of Molecular Biology, Russian Academy of SciencesMoscow, Russia
| | - Olga A. Rachinskaya
- Engelhardt Institute of Molecular Biology, Russian Academy of SciencesMoscow, Russia
| | - Zoya E. Grushetskaya
- Institute of Genetics and Cytology, National Academy of Sciences of BelarusMinsk, Belarus
| | - Svyatoslav A. Zoschuk
- Engelhardt Institute of Molecular Biology, Russian Academy of SciencesMoscow, Russia
| | - Tatiana E. Samatadze
- Engelhardt Institute of Molecular Biology, Russian Academy of SciencesMoscow, Russia
| | - Marina V. Bogdanova
- Institute of Genetics and Cytology, National Academy of Sciences of BelarusMinsk, Belarus
| | - Valentina A. Lemesh
- Institute of Genetics and Cytology, National Academy of Sciences of BelarusMinsk, Belarus
| | - Alexandra V. Amosova
- Engelhardt Institute of Molecular Biology, Russian Academy of SciencesMoscow, Russia
| | - Olga V. Muravenko
- Engelhardt Institute of Molecular Biology, Russian Academy of SciencesMoscow, Russia
| |
Collapse
|
13
|
Jiao Y, Peluso P, Shi J, Liang T, Stitzer MC, Wang B, Campbell MS, Stein JC, Wei X, Chin CS, Guill K, Regulski M, Kumari S, Olson A, Gent J, Schneider KL, Wolfgruber TK, May MR, Springer NM, Antoniou E, McCombie WR, Presting GG, McMullen M, Ross-Ibarra J, Dawe RK, Hastie A, Rank DR, Ware D. Improved maize reference genome with single-molecule technologies. Nature 2017; 546:524-527. [PMID: 28605751 DOI: 10.1101/079004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Accepted: 05/14/2017] [Indexed: 05/21/2023]
Abstract
Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation. These resources facilitate the determination of biological processes and support translation of research findings into improved and sustainable agricultural technologies. Many reference genomes for crop plants have been generated over the past decade, but these genomes are often fragmented and missing complex repeat regions. Here we report the assembly and annotation of a reference genome of maize, a genetic and agricultural model species, using single-molecule real-time sequencing and high-resolution optical mapping. Relative to the previous reference genome, our assembly features a 52-fold increase in contig length and notable improvements in the assembly of intergenic spaces and centromeres. Characterization of the repetitive portion of the genome revealed more than 130,000 intact transposable elements, allowing us to identify transposable element lineage expansions that are unique to maize. Gene annotations were updated using 111,000 full-length transcripts obtained by single-molecule real-time sequencing. In addition, comparative optical mapping of two other inbred maize lines revealed a prevalence of deletions in regions of low gene density and maize lineage-specific genes.
Collapse
Affiliation(s)
- Yinping Jiao
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Paul Peluso
- Pacific Biosciences, Menlo Park, California 94025, USA
| | - Jinghua Shi
- BioNano Genomics, San Diego, California 92121, USA
| | | | - Michelle C Stitzer
- Department of Plant Sciences and Center for Population Biology, University of California, Davis, Davis, California 95616, USA
| | - Bo Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | | | - Joshua C Stein
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Xuehong Wei
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | | | - Katherine Guill
- USDA-ARS, Plant Genetics Research Unit, Columbia, Missouri 65211, USA
| | - Michael Regulski
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Sunita Kumari
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Andrew Olson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | | | - Kevin L Schneider
- Department of Molecular Biosciences and Bioengineering, University of Hawaii, Honolulu, Hawaii 96822, USA
| | - Thomas K Wolfgruber
- Department of Molecular Biosciences and Bioengineering, University of Hawaii, Honolulu, Hawaii 96822, USA
| | - Michael R May
- Department of Evolution and Ecology, University of California, Davis, California 95616, USA
| | - Nathan M Springer
- Department of Plant Biology, University of Minnesota, St Paul, Minnesota 55108, USA
| | - Eric Antoniou
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | | | - Gernot G Presting
- Department of Molecular Biosciences and Bioengineering, University of Hawaii, Honolulu, Hawaii 96822, USA
| | - Michael McMullen
- USDA-ARS, Plant Genetics Research Unit, Columbia, Missouri 65211, USA
| | - Jeffrey Ross-Ibarra
- Department of Plant Sciences, Center for Population Biology, and Genome Center, University of California, Davis, California 95616, USA
| | - R Kelly Dawe
- University of Georgia, Athens, Georgia 30602, USA
| | - Alex Hastie
- BioNano Genomics, San Diego, California 92121, USA
| | - David R Rank
- Pacific Biosciences, Menlo Park, California 94025, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
- USDA-ARS, NEA Robert W. Holley Center for Agriculture and Health, Cornell University, Ithaca, New York 14853, USA
| |
Collapse
|
14
|
Improved maize reference genome with single-molecule technologies. Nature 2017; 546:524-527. [PMID: 28605751 PMCID: PMC7052699 DOI: 10.1038/nature22971] [Citation(s) in RCA: 693] [Impact Index Per Article: 99.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Accepted: 05/14/2017] [Indexed: 01/01/2023]
Abstract
An improved reference genome for maize, using single-molecule sequencing and high-resolution optical mapping, enables characterization of structural variation and repetitive regions, and identifies lineage expansions of transposable elements that are unique to maize. The maize genome was initially reported in 2009 but with some accuracy limitations. Doreen Ware and colleagues report a new reference genome for maize using single-molecule sequencing and high-resolution optical mapping. The technique shows improvements in the gene space including resolution of gaps and misassemblies and correction of order and orientation of genes. The authors characterize structural variation and repetitive regions, and identify transposable element lineage expansions unique to maize. Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation1. These resources facilitate the determination of biological processes and support translation of research findings into improved and sustainable agricultural technologies. Many reference genomes for crop plants have been generated over the past decade, but these genomes are often fragmented and missing complex repeat regions2. Here we report the assembly and annotation of a reference genome of maize, a genetic and agricultural model species, using single-molecule real-time sequencing and high-resolution optical mapping. Relative to the previous reference genome3, our assembly features a 52-fold increase in contig length and notable improvements in the assembly of intergenic spaces and centromeres. Characterization of the repetitive portion of the genome revealed more than 130,000 intact transposable elements, allowing us to identify transposable element lineage expansions that are unique to maize. Gene annotations were updated using 111,000 full-length transcripts obtained by single-molecule real-time sequencing4. In addition, comparative optical mapping of two other inbred maize lines revealed a prevalence of deletions in regions of low gene density and maize lineage-specific genes.
Collapse
|
15
|
Coates BS, Abel CA, Perera OP. Estimation of long terminal repeat element content in the Helicoverpa zea genome from high-throughput sequencing of bacterial artificial chromosome pools. Genome 2016; 60:310-324. [PMID: 28177843 DOI: 10.1139/gen-2016-0067] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The lepidopteran pest insect Helicoverpa zea feeds on cultivated corn and cotton across the Americas where control remains challenging owing to the evolution of resistance to chemical and transgenic insecticidal toxins, yet genomic resources remain scarce for this species. A bacterial artificial chromosome (BAC) library having a mean genomic insert size of 145 ± 20 kbp was created from a laboratory strain of H. zea, which provides ∼12.9-fold coverage of a 362.8 ± 8.8 Mbp (0.37 ± 0.09 pg) flow cytometry estimated haploid genome size. Assembly of Illumina HiSeq 2000 reads generated from 14 pools that encompassed all BAC clones resulted in 165 485 genomic contigs (N50 = 3262 bp; 324.6 Mbp total). Long terminal repeat (LTR) protein coding regions annotated from 181 contigs included 30 Ty1/copia, 78 Ty3/gypsy, and 73 BEL/Pao elements, of which 60 (33.1%) encoded all five functional polyprotein (pol) domains. Approximately 14% of LTR elements are distributed non-randomly across pools of BAC clones.
Collapse
Affiliation(s)
- Brad S Coates
- a USDA-ARS, Corn Insects & Crop Genetics Research Unit, Genetics Laboratory, Iowa State University, Ames, IA 50011, USA.,b Department of Entomology, Iowa State University, Ames, IA 50011, USA
| | - Craig A Abel
- a USDA-ARS, Corn Insects & Crop Genetics Research Unit, Genetics Laboratory, Iowa State University, Ames, IA 50011, USA
| | - Omaththage P Perera
- c USDA-ARS, Southern Insect Management Research Unit, 141 Experiment Station Road, P.O. Box 346, Stoneville, MS 38776, USA
| |
Collapse
|
16
|
Handrick V, Robert CAM, Ahern KR, Zhou S, Machado RAR, Maag D, Glauser G, Fernandez-Penny FE, Chandran JN, Rodgers-Melnik E, Schneider B, Buckler ES, Boland W, Gershenzon J, Jander G, Erb M, Köllner TG. Biosynthesis of 8-O-Methylated Benzoxazinoid Defense Compounds in Maize. THE PLANT CELL 2016; 28:1682-700. [PMID: 27317675 PMCID: PMC4981128 DOI: 10.1105/tpc.16.00065] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Accepted: 06/14/2016] [Indexed: 05/04/2023]
Abstract
Benzoxazinoids are important defense compounds in grasses. Here, we investigated the biosynthesis and biological roles of the 8-O-methylated benzoxazinoids, DIM2BOA-Glc and HDM2BOA-Glc. Using quantitative trait locus mapping and heterologous expression, we identified a 2-oxoglutarate-dependent dioxygenase (BX13) that catalyzes the conversion of DIMBOA-Glc into a new benzoxazinoid intermediate (TRIMBOA-Glc) by an uncommon reaction involving a hydroxylation and a likely ortho-rearrangement of a methoxy group. TRIMBOA-Glc is then converted to DIM2BOA-Glc by a previously described O-methyltransferase BX7. Furthermore, we identified an O-methyltransferase (BX14) that converts DIM2BOA-Glc to HDM2BOA-Glc. The role of these enzymes in vivo was demonstrated by characterizing recombinant inbred lines, including Oh43, which has a point mutation in the start codon of Bx13 and lacks both DIM2BOA-Glc and HDM2BOA-Glc, and Il14H, which has an inactive Bx14 allele and lacks HDM2BOA-Glc in leaves. Experiments with near-isogenic maize lines derived from crosses between B73 and Oh43 revealed that the absence of DIM2BOA-Glc and HDM2BOA-Glc does not alter the constitutive accumulation or deglucosylation of other benzoxazinoids. The growth of various chewing herbivores was not significantly affected by the absence of BX13-dependent metabolites, while aphid performance increased, suggesting that DIM2BOA-Glc and/or HDM2BOA-Glc provide specific protection against phloem feeding insects.
Collapse
Affiliation(s)
| | | | - Kevin R Ahern
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853
| | - Shaoqun Zhou
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853
| | | | - Daniel Maag
- Institute of Biology, University of Neuchatel, 2009 Neuchatel, Switzerland
| | - Gaetan Glauser
- Institute of Biology, University of Neuchatel, 2009 Neuchatel, Switzerland
| | | | - Jima N Chandran
- Max Planck Institute for Chemical Ecology, 07745 Jena, Germany
| | - Eli Rodgers-Melnik
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853
| | - Bernd Schneider
- Max Planck Institute for Chemical Ecology, 07745 Jena, Germany
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853
| | - Wilhelm Boland
- Max Planck Institute for Chemical Ecology, 07745 Jena, Germany
| | | | - Georg Jander
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853
| | - Matthias Erb
- Institute of Plant Sciences, University of Bern, 3013 Bern, Switzerland
| | | |
Collapse
|
17
|
Wang B, Tseng E, Regulski M, Clark TA, Hon T, Jiao Y, Lu Z, Olson A, Stein JC, Ware D. Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing. Nat Commun 2016; 7:11708. [PMID: 27339440 DOI: 10.1038/ncomms11708] [Citation(s) in RCA: 325] [Impact Index Per Article: 40.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Accepted: 04/20/2016] [Indexed: 12/31/2022] Open
Abstract
Zea mays is an important genetic model for elucidating transcriptional networks. Uncertainties about the complete structure of mRNA transcripts limit the progress of research in this system. Here, using single-molecule sequencing technology, we produce 111,151 transcripts from 6 tissues capturing ∼70% of the genes annotated in maize RefGen_v3 genome. A large proportion of transcripts (57%) represent novel, sometimes tissue-specific, isoforms of known genes and 3% correspond to novel gene loci. In other cases, the identified transcripts have improved existing gene models. Averaging across all six tissues, 90% of the splice junctions are supported by short reads from matched tissues. In addition, we identified a large number of novel long non-coding RNAs and fusion transcripts and found that DNA methylation plays an important role in generating various isoforms. Our results show that characterization of the maize B73 transcriptome is far from complete, and that maize gene expression is more complex than previously thought.
Collapse
Affiliation(s)
- Bo Wang
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Elizabeth Tseng
- Pacific Biosciences, 1380 Willow Road, Menlo Park, California 94025, USA
| | - Michael Regulski
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Tyson A Clark
- Pacific Biosciences, 1380 Willow Road, Menlo Park, California 94025, USA
| | - Ting Hon
- Pacific Biosciences, 1380 Willow Road, Menlo Park, California 94025, USA
| | - Yinping Jiao
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Zhenyuan Lu
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Andrew Olson
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Joshua C Stein
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, New York 11724, USA.,USDA ARS NEA Robert W. Holley Center for Agriculture and Health Cornell University, Ithaca, New York 14853, USA
| |
Collapse
|
18
|
Zhang J, Kudrna D, Mu T, Li W, Copetti D, Yu Y, Goicoechea JL, Lei Y, Wing RA. Genome puzzle master (GPM): an integrated pipeline for building and editing pseudomolecules from fragmented sequences. Bioinformatics 2016; 32:3058-3064. [PMID: 27318200 PMCID: PMC5048067 DOI: 10.1093/bioinformatics/btw370] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 06/06/2016] [Indexed: 12/16/2022] Open
Abstract
Motivation: Next generation sequencing technologies have revolutionized our ability to rapidly and affordably generate vast quantities of sequence data. Once generated, raw sequences are assembled into contigs or scaffolds. However, these assemblies are mostly fragmented and inaccurate at the whole genome scale, largely due to the inability to integrate additional informative datasets (e.g. physical, optical and genetic maps). To address this problem, we developed a semi-automated software tool—Genome Puzzle Master (GPM)—that enables the integration of additional genomic signposts to edit and build ‘new-gen-assemblies’ that result in high-quality ‘annotation-ready’ pseudomolecules. Results: With GPM, loaded datasets can be connected to each other via their logical relationships which accomplishes tasks to ‘group,’ ‘merge,’ ‘order and orient’ sequences in a draft assembly. Manual editing can also be performed with a user-friendly graphical interface. Final pseudomolecules reflect a user’s total data package and are available for long-term project management. GPM is a web-based pipeline and an important part of a Laboratory Information Management System (LIMS) which can be easily deployed on local servers for any genome research laboratory. Availability and Implementation: The GPM (with LIMS) package is available at https://github.com/Jianwei-Zhang/LIMS Contacts:jzhang@mail.hzau.edu.cn or rwing@mail.arizona.edu Supplementary information:Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Jianwei Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
| | - Dave Kudrna
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
| | - Ting Mu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Weiming Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Dario Copetti
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA International Rice Research Institute, Genetic Resource Center, Los Baños, Laguna, Philippines
| | - Yeisoo Yu
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
| | - Jose Luis Goicoechea
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
| | - Yang Lei
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Rod A Wing
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA International Rice Research Institute, Genetic Resource Center, Los Baños, Laguna, Philippines
| |
Collapse
|
19
|
Casas MI, Falcone-Ferreyra ML, Jiang N, Mejía-Guerra MK, Rodríguez E, Wilson T, Engelmeier J, Casati P, Grotewold E. Identification and Characterization of Maize salmon silks Genes Involved in Insecticidal Maysin Biosynthesis. THE PLANT CELL 2016; 28:1297-309. [PMID: 27221383 PMCID: PMC4944406 DOI: 10.1105/tpc.16.00003] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Accepted: 05/23/2016] [Indexed: 05/02/2023]
Abstract
The century-old maize (Zea mays) salmon silks mutation has been linked to the absence of maysin. Maysin is a C-glycosyl flavone that, when present in silks, confers natural resistance to the maize earworm (Helicoverpa zea), which is one of the most damaging pests of maize in America. Previous genetic analyses predicted Pericarp Color1 (P1; R2R3-MYB transcription factor) to be epistatic to the sm mutation. Subsequent studies identified two loci as being capable of conferring salmon silks phenotypes, salmon silks1 (sm1) and sm2 Benefitting from available sm1 and sm2 mapping information and from knowledge of the genes regulated by P1, we describe here the molecular identification of the Sm1 and Sm2 gene products. Sm2 encodes a rhamnosyl transferase (UGT91L1) that uses isoorientin and UDP-rhamnose as substrates and converts them to rhamnosylisoorientin. Sm1 encodes a multidomain UDP-rhamnose synthase (RHS1) that converts UDP-glucose into UDP-l-rhamnose. Here, we demonstrate that RHS1 shows unexpected substrate plasticity in converting the glucose moiety in rhamnosylisoorientin to 4-keto-6-deoxy glucose, resulting in maysin. Both Sm1 and Sm2 are direct targets of P1, as demonstrated by chromatin immunoprecipitation experiments. The molecular characterization of Sm1 and Sm2 described here completes the maysin biosynthetic pathway, providing powerful tools for engineering tolerance to maize earworm in maize and other plants.
Collapse
Affiliation(s)
- María Isabel Casas
- Molecular, Cellular, and Developmental Biology Program, The Ohio State University, Columbus, Ohio 43210 Center for Applied Plant Sciences, The Ohio State University, Columbus, Ohio 43210
| | | | - Nan Jiang
- Center for Applied Plant Sciences, The Ohio State University, Columbus, Ohio 43210
| | - María Katherine Mejía-Guerra
- Molecular, Cellular, and Developmental Biology Program, The Ohio State University, Columbus, Ohio 43210 Center for Applied Plant Sciences, The Ohio State University, Columbus, Ohio 43210
| | - Eduardo Rodríguez
- Instituto de Biología Molecular y Celular de Rosario, Rosario, Santa Fe S2002LRK, Argentina
| | - Tyler Wilson
- Center for Applied Plant Sciences, The Ohio State University, Columbus, Ohio 43210
| | - Jacob Engelmeier
- Center for Applied Plant Sciences, The Ohio State University, Columbus, Ohio 43210
| | - Paula Casati
- Centro de Estudios Fotosintéticos y Bioquímicos, Universidad Nacional de Rosario, Santa Fe S2002LRK, Argentina
| | - Erich Grotewold
- Center for Applied Plant Sciences, The Ohio State University, Columbus, Ohio 43210 Department of Molecular Genetics, The Ohio State University, Columbus, Ohio 43210
| |
Collapse
|
20
|
Yelina NE, Lambing C, Hardcastle TJ, Zhao X, Santos B, Henderson IR. DNA methylation epigenetically silences crossover hot spots and controls chromosomal domains of meiotic recombination in Arabidopsis. Genes Dev 2016; 29:2183-202. [PMID: 26494791 PMCID: PMC4617981 DOI: 10.1101/gad.270876.115] [Citation(s) in RCA: 126] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Yelina et al. show that RNA-directed DNA methylation is sufficient to locally silence Arabidopsis euchromatic crossover hot spots and is associated with increased nucleosome density and H3K9me2. This work demonstrates that DNA methylation plays a key role in establishing domains of meiotic recombination along chromosomes. During meiosis, homologous chromosomes undergo crossover recombination, which is typically concentrated in narrow hot spots that are controlled by genetic and epigenetic information. Arabidopsis chromosomes are highly DNA methylated in the repetitive centromeres, which are also crossover-suppressed. Here we demonstrate that RNA-directed DNA methylation is sufficient to locally silence Arabidopsis euchromatic crossover hot spots and is associated with increased nucleosome density and H3K9me2. However, loss of CG DNA methylation maintenance in met1 triggers epigenetic crossover remodeling at the chromosome scale, with pericentromeric decreases and euchromatic increases in recombination. We used recombination mutants that alter interfering and noninterfering crossover repair pathways (fancm and zip4) to demonstrate that remodeling primarily involves redistribution of interfering crossovers. Using whole-genome bisulfite sequencing, we show that crossover remodeling is driven by loss of CG methylation within the centromeric regions. Using cytogenetics, we profiled meiotic DNA double-strand break (DSB) foci in met1 and found them unchanged relative to wild type. We propose that met1 chromosome structure is altered, causing centromere-proximal DSBs to be inhibited from maturation into interfering crossovers. These data demonstrate that DNA methylation is sufficient to silence crossover hot spots and plays a key role in establishing domains of meiotic recombination along chromosomes.
Collapse
Affiliation(s)
- Nataliya E Yelina
- Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom
| | - Christophe Lambing
- Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom
| | - Thomas J Hardcastle
- Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom
| | - Xiaohui Zhao
- Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom
| | - Bruno Santos
- Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom
| | - Ian R Henderson
- Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom
| |
Collapse
|
21
|
Wolfgruber TK, Nakashima MM, Schneider KL, Sharma A, Xie Z, Albert PS, Xu R, Bilinski P, Dawe RK, Ross-Ibarra J, Birchler JA, Presting GG. High Quality Maize Centromere 10 Sequence Reveals Evidence of Frequent Recombination Events. FRONTIERS IN PLANT SCIENCE 2016; 7:308. [PMID: 27047500 PMCID: PMC4806543 DOI: 10.3389/fpls.2016.00308] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2015] [Accepted: 02/27/2016] [Indexed: 05/02/2023]
Abstract
The ancestral centromeres of maize contain long stretches of the tandemly arranged CentC repeat. The abundance of tandem DNA repeats and centromeric retrotransposons (CR) has presented a significant challenge to completely assembling centromeres using traditional sequencing methods. Here, we report a nearly complete assembly of the 1.85 Mb maize centromere 10 from inbred B73 using PacBio technology and BACs from the reference genome project. The error rates estimated from overlapping BAC sequences are 7 × 10(-6) and 5 × 10(-5) for mismatches and indels, respectively. The number of gaps in the region covered by the reassembly was reduced from 140 in the reference genome to three. Three expressed genes are located between 92 and 477 kb from the inferred ancestral CentC cluster, which lies within the region of highest centromeric repeat density. The improved assembly increased the count of full-length CR from 5 to 55 and revealed a 22.7 kb segmental duplication that occurred approximately 121,000 years ago. Our analysis provides evidence of frequent recombination events in the form of partial retrotransposons, deletions within retrotransposons, chimeric retrotransposons, segmental duplications including higher order CentC repeats, a deleted CentC monomer, centromere-proximal inversions, and insertion of mitochondrial sequences. Double-strand DNA break (DSB) repair is the most plausible mechanism for these events and may be the major driver of centromere repeat evolution and diversity. In many cases examined here, DSB repair appears to be mediated by microhomology, suggesting that tandem repeats may have evolved to efficiently repair frequent DSBs in centromeres.
Collapse
Affiliation(s)
- Thomas K. Wolfgruber
- Department of Molecular Biosciences and Bioengineering, University of Hawaíi at MānoaHonolulu, HI, USA
| | - Megan M. Nakashima
- Department of Molecular Biosciences and Bioengineering, University of Hawaíi at MānoaHonolulu, HI, USA
| | - Kevin L. Schneider
- Department of Molecular Biosciences and Bioengineering, University of Hawaíi at MānoaHonolulu, HI, USA
| | - Anupma Sharma
- Department of Molecular Biosciences and Bioengineering, University of Hawaíi at MānoaHonolulu, HI, USA
| | - Zidian Xie
- Department of Molecular Biosciences and Bioengineering, University of Hawaíi at MānoaHonolulu, HI, USA
| | - Patrice S. Albert
- Division of Biological Sciences, University of MissouriColumbia, MO, USA
| | - Ronghui Xu
- Department of Molecular Biosciences and Bioengineering, University of Hawaíi at MānoaHonolulu, HI, USA
| | - Paul Bilinski
- Department of Plant Sciences, University of California DavisDavis, CA, USA
| | - R. Kelly Dawe
- Department of Plant Biology, University of GeorgiaAthens, GA, USA
| | | | - James A. Birchler
- Division of Biological Sciences, University of MissouriColumbia, MO, USA
| | - Gernot G. Presting
- Department of Molecular Biosciences and Bioengineering, University of Hawaíi at MānoaHonolulu, HI, USA
- *Correspondence: Gernot G. Presting
| |
Collapse
|
22
|
Mendelowitz LM, Schwartz DC, Pop M. Maligner: a fast ordered restriction map aligner. Bioinformatics 2015; 32:1016-22. [PMID: 26637292 DOI: 10.1093/bioinformatics/btv711] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Accepted: 12/01/2015] [Indexed: 12/28/2022] Open
Abstract
MOTIVATION The Optical Mapping System discovers structural variants and potentiates sequence assembly of genomes via scaffolding and comparisons that globally validate or correct sequence assemblies. Despite its utility, there are few publicly available tools for aligning optical mapping datasets. RESULTS Here we present software, named 'Maligner', for the alignment of both single molecule restriction maps (Rmaps) and in silico restriction maps of sequence contigs to a reference. Maligner provides two modes of alignment: an efficient, sensitive dynamic programming implementation that scales to large eukaryotic genomes, and a faster indexed based implementation for finding alignments with unmatched sites in the reference but not the query. We compare our software to other publicly available tools on Rmap datasets and show that Maligner finds more correct alignments in comparable runtime. Lastly, we introduce the M-Score statistic for normalizing alignment scores across restriction maps and demonstrate its utility for selecting high quality alignments. AVAILABILITY AND IMPLEMENTATION The Maligner software is written in C ++ and is available at https://github.com/LeeMendelowitz/maligner under the GNU General Public License. CONTACT mpop@umiacs.umd.edu.
Collapse
Affiliation(s)
- Lee M Mendelowitz
- Center for Bioinformatics and Computational Biology, Applied Math & Statistics, and Scientific Computation
| | - David C Schwartz
- Laboratory for Molecular and Computational Genomics, Department of Chemistry, Laboratory of Genetics, USA and the UW-Biotechnology Center, University of Wisconsin-Madison, WI 53706, USA
| | - Mihai Pop
- Center for Bioinformatics and Computational Biology, Applied Math & Statistics, and Scientific Computation, Department of Computer Science, University of Maryland, College Park, MD 20742, USA and
| |
Collapse
|
23
|
Abstract
Optical Mapping is an established single-molecule, whole-genome analysis system, which has been used to gain a comprehensive understanding of genomic structure and to study structural variation of complex genomes. A critical component of Optical Mapping system is the image processing module, which extracts single molecule restriction maps from image datasets of immobilized, restriction digested and fluorescently stained large DNA molecules. In this review, we describe robust and efficient image processing techniques to process these massive datasets and extract accurate restriction maps in the presence of noise, ambiguity and confounding artifacts. We also highlight a few applications of the Optical Mapping system.
Collapse
Affiliation(s)
- Prabu Ravindran
- Laboratory of Molecular and Computational Genomics, Department of Chemistry, Laboratory of Genetics and Biotechnology Center, University of Wisconsin, 425 Henry Mall, Madison, USA
| | - Aditya Gupta
- Laboratory of Molecular and Computational Genomics, Department of Chemistry, Laboratory of Genetics and Biotechnology Center, University of Wisconsin, 425 Henry Mall, Madison, USA
| |
Collapse
|
24
|
Muraya MM, Schmutzer T, Ulpinnis C, Scholz U, Altmann T. Targeted Sequencing Reveals Large-Scale Sequence Polymorphism in Maize Candidate Genes for Biomass Production and Composition. PLoS One 2015; 10:e0132120. [PMID: 26151830 PMCID: PMC4495061 DOI: 10.1371/journal.pone.0132120] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2015] [Accepted: 06/10/2015] [Indexed: 12/30/2022] Open
Abstract
A major goal of maize genomic research is to identify sequence polymorphisms responsible for phenotypic variation in traits of economic importance. Large-scale detection of sequence variation is critical for linking genes, or genomic regions, to phenotypes. However, due to its size and complexity, it remains expensive to generate whole genome sequences of sufficient coverage for divergent maize lines, even with access to next generation sequencing (NGS) technology. Because methods involving reduction of genome complexity, such as genotyping-by-sequencing (GBS), assess only a limited fraction of sequence variation, targeted sequencing of selected genomic loci offers an attractive alternative. We therefore designed a sequence capture assay to target 29 Mb genomic regions and surveyed a total of 4,648 genes possibly affecting biomass production in 21 diverse inbred maize lines (7 flints, 14 dents). Captured and enriched genomic DNA was sequenced using the 454 NGS platform to 19.6-fold average depth coverage, and a broad evaluation of read alignment and variant calling methods was performed to select optimal procedures for variant discovery. Sequence alignment with the B73 reference and de novo assembly identified 383,145 putative single nucleotide polymorphisms (SNPs), of which 42,685 were non-synonymous alterations and 7,139 caused frameshifts. Presence/absence variation (PAV) of genes was also detected. We found that substantial sequence variation exists among genomic regions targeted in this study, which was particularly evident within coding regions. This diversification has the potential to broaden functional diversity and generate phenotypic variation that may lead to new adaptations and the modification of important agronomic traits. Further, annotated SNPs identified here will serve as useful genetic tools and as candidates in searches for phenotype-altering DNA variation. In summary, we demonstrated that sequencing of captured DNA is a powerful approach for variant discovery in maize genes.
Collapse
Affiliation(s)
- Moses M. Muraya
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Stadt Seeland, Germany
- Department of Plant Science, Chuka University, P.O. Box, 109–60400, Chuka, Kenya
| | - Thomas Schmutzer
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Stadt Seeland, Germany
- * E-mail:
| | - Chris Ulpinnis
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Stadt Seeland, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Stadt Seeland, Germany
| | - Thomas Altmann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Stadt Seeland, Germany
| |
Collapse
|
25
|
Choi K, Henderson IR. Meiotic recombination hotspots - a comparative view. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2015; 83:52-61. [PMID: 25925869 DOI: 10.1111/tpj.12870] [Citation(s) in RCA: 81] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2015] [Revised: 04/15/2015] [Accepted: 04/17/2015] [Indexed: 05/18/2023]
Abstract
During meiosis homologous chromosomes pair and undergo reciprocal genetic exchange, termed crossover. Meiotic recombination has a profound effect on patterns of genetic variation and is an important tool during crop breeding. Crossovers initiate from programmed DNA double-stranded breaks that are processed to form single-stranded DNA, which can invade a homologous chromosome. Strand invasion events mature into double Holliday junctions that can be resolved as crossovers. Extensive variation in the frequency of meiotic recombination occurs along chromosomes and is typically focused in narrow hotspots, observed both at the level of DNA breaks and final crossovers. We review methodologies to profile hotspots at different steps of the meiotic recombination pathway that have been used in different eukaryote species. We then discuss what these studies have revealed concerning specification of hotspot locations and activity and the contributions of both genetic and epigenetic factors. Understanding hotspots is important for interpreting patterns of genetic variation in populations and how eukaryotic genomes evolve. In addition, manipulation of hotspots will allow us to accelerate crop breeding, where meiotic recombination distributions can be limiting.
Collapse
Affiliation(s)
- Kyuha Choi
- Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EA, UK
| | - Ian R Henderson
- Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EA, UK
| |
Collapse
|
26
|
Chen JJ, Wang Y. Microsatellite Development and Potential Application in Authentication, Conservation, and Genetic Improvement of Chinese Medicinal Plants. CHINESE HERBAL MEDICINES 2015. [DOI: 10.1016/s1674-6384(15)60029-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
|
27
|
Epigenetic control of meiotic recombination in plants. SCIENCE CHINA-LIFE SCIENCES 2015; 58:223-31. [PMID: 25651968 DOI: 10.1007/s11427-015-4811-x] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Accepted: 12/03/2014] [Indexed: 10/24/2022]
Abstract
Meiotic recombination is a deeply conserved process within eukaryotes that has a profound effect on patterns of natural genetic variation. During meiosis homologous chromosomes pair and undergo DNA double strand breaks generated by the Spo11 endonuclease. These breaks can be repaired as crossovers that result in reciprocal exchange between chromosomes. The frequency of recombination along chromosomes is highly variable, for example, crossovers are rarely observed in heterochromatin and the centromeric regions. Recent work in plants has shown that crossover hotspots occur in gene promoters and are associated with specific chromatin modifications, including H2A.Z. Meiotic chromosomes are also organized in loop-base arrays connected to an underlying chromosome axis, which likely interacts with chromatin to organize patterns of recombination. Therefore, epigenetic information exerts a major influence on patterns of meiotic recombination along chromosomes, genetic variation within populations and evolution of plant genomes.
Collapse
|
28
|
Law M, Childs KL, Campbell MS, Stein JC, Olson AJ, Holt C, Panchy N, Lei J, Jiao D, Andorf CM, Lawrence CJ, Ware D, Shiu SH, Sun Y, Jiang N, Yandell M. Automated update, revision, and quality control of the maize genome annotations using MAKER-P improves the B73 RefGen_v3 gene models and identifies new genes. PLANT PHYSIOLOGY 2015; 167:25-39. [PMID: 25384563 PMCID: PMC4280997 DOI: 10.1104/pp.114.245027] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Accepted: 11/02/2014] [Indexed: 05/18/2023]
Abstract
The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-P to update and revise the maize (Zea mays) B73 RefGen_v3 annotation build (5b+) in less than 3 h using the iPlant Cyberinfrastructure. MAKER-P identified and annotated 4,466 additional, well-supported protein-coding genes not present in the 5b+ annotation build, added additional untranslated regions to 1,393 5b+ gene models, identified 2,647 5b+ gene models that lack any supporting evidence (despite the use of large and diverse evidence data sets), identified 104,215 pseudogene fragments, and created an additional 2,522 noncoding gene annotations. We also describe a method for de novo training of MAKER-P for the annotation of newly sequenced grass genomes. Collectively, these results lead to the 6a maize genome annotation and demonstrate the utility of MAKER-P for rapid annotation, management, and quality control of grasses and other difficult-to-annotate plant genomes.
Collapse
Affiliation(s)
- MeiYee Law
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Kevin L Childs
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Michael S Campbell
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Joshua C Stein
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Andrew J Olson
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Carson Holt
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Nicholas Panchy
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Jikai Lei
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Dian Jiao
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Carson M Andorf
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Carolyn J Lawrence
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Doreen Ware
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Shin-Han Shiu
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Yanni Sun
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Ning Jiang
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| | - Mark Yandell
- The Jackson Laboratory, Bar Harbor, Maine 04609 (M.L.);Eccles Institute of Human Genetics (M.L., M.S.C., M.Y.), Department of Biomedical Informatics (M.L.), and USTAR Center for Genetic Discovery (C.H., M.Y.), University of Utah, Salt Lake City, Utah 84112;Genetics Program (N.P., S.-H.S., N.J.), Department of Plant Biology (K.L.C., S.-H.S.), Department of Computer Science and Engineering (J.L., Y.S.), and Department of Horticulture (N.J.), Michigan State University, East Lansing, Michigan 48824;iPlant Collaborative, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (J.C.S., A.J.O., D.W.);Ontario Institute for Cancer Research, Toronto, Ontario, Canada M5G 1L7 (C.H.);Texas Advanced Computing Center, University of Texas, Austin, Texas 78758 (D.J.);Department of Genetics, Development, and Cell Biology and Department of Agronomy (C.J.L.), and United States Department of Agriculture-Agricultural Research Service Corn Insects and Crop Genetics Research (C.M.A.), Iowa State University, Ames, Iowa 50011; andUnited States Department of Agriculture-Agricultural Research Service Northeast Area, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853 (D.W.)
| |
Collapse
|
29
|
Abstract
Maize occupies dual roles as both (a) one of the big-three grain species (along with rice and wheat) responsible for providing more than half of the calories consumed around the world, and (b) a model system for plant genetics and cytogenetics dating back to the origin of the field of genetics in the early twentieth century. The long history of genetic investigation in this species combined with modern genomic and quantitative genetic data has provided particular insight into the characteristics of genes linked to phenotypes and how these genes differ from many other sequences in plant genomes that are not easily distinguishable based on molecular data alone. These recent results suggest that the number of genes in plants that make significant contributions to phenotype may be lower than the number of genes defined by current molecular criteria, and also indicate that syntenic conservation has been underemphasized as a marker for gene function.
Collapse
Affiliation(s)
- James C Schnable
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, Nebraska 68583;
| |
Collapse
|
30
|
Istvánek J, Jaros M, Krenek A, Řepková J. Genome assembly and annotation for red clover (Trifolium pratense; Fabaceae). AMERICAN JOURNAL OF BOTANY 2014; 101:327-37. [PMID: 24500806 DOI: 10.3732/ajb.1300340] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
PREMISE OF THE STUDY Red clover (Trifolium pratense) is an important forage plant from the legume family with great importance in agronomy and livestock nourishment. Nevertheless, assembling its medium-sized genome presents a challenge, given current hardware and software possibilities. Next-generation sequencing technologies enable us to generate large amounts of sequence data at low cost. In this study, the genome assembly and red clover genome features are presented. METHODS First, assembly software was assessed using data sets from a closely related species to find the best possible combination of assembler plus error correction program to assemble the red clover genome. The newly sequenced genome was characterized by repetitive content, number of protein-coding and nonprotein-coding genes, and gene families and functions. Genome features were also compared with those of other sequenced plant species. KEY RESULTS Abyss with Echo correction was used for de novo assembly of the red clover genome. The presented assembly comprises ∼314.6 Mbp. In contrast to leguminous species with comparable genome sizes, the genome of T. pratense contains a larger repetitive portion and more abundant retrotransposons and DNA transposons. Overall, 47 398 protein-coding genes were annotated from 64 761 predicted genes. Comparative analysis revealed several gene families that are characteristic for T. pratense. Resistance genes, leghemoglobins, and nodule-specific cystein-rich peptides were identified and compared with other sequenced species. CONCLUSIONS The presented red clover genomic data constitute a resource for improvement through molecular breeding and for comparison to other sequenced plant species.
Collapse
Affiliation(s)
- Jan Istvánek
- Department of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic
| | | | | | | |
Collapse
|
31
|
Genomic resources for gene discovery, functional genome annotation, and evolutionary studies of maize and its close relatives. Genetics 2013; 195:723-37. [PMID: 24037269 DOI: 10.1534/genetics.113.157115] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Maize is one of the most important food crops and a key model for genetics and developmental biology. A genetically anchored and high-quality draft genome sequence of maize inbred B73 has been obtained to serve as a reference sequence. To facilitate evolutionary studies in maize and its close relatives, much like the Oryza Map Alignment Project (OMAP) (www.OMAP.org) bacterial artificial chromosome (BAC) resource did for the rice community, we constructed BAC libraries for maize inbred lines Zheng58, Chang7-2, and Mo17 and maize wild relatives Zea mays ssp. parviglumis and Tripsacum dactyloides. Furthermore, to extend functional genomic studies to maize and sorghum, we also constructed binary BAC (BIBAC) libraries for the maize inbred B73 and the sorghum landrace Nengsi-1. The BAC/BIBAC vectors facilitate transfer of large intact DNA inserts from BAC clones to the BIBAC vector and functional complementation of large DNA fragments. These seven Zea Map Alignment Project (ZMAP) BAC/BIBAC libraries have average insert sizes ranging from 92 to 148 kb, organellar DNA from 0.17 to 2.3%, empty vector rates between 0.35 and 5.56%, and genome equivalents of 4.7- to 8.4-fold. The usefulness of the Parviglumis and Tripsacum BAC libraries was demonstrated by mapping clones to the reference genome. Novel genes and alleles present in these ZMAP libraries can now be used for functional complementation studies and positional or homology-based cloning of genes for translational genomics.
Collapse
|
32
|
Sierro N, van Oeveren J, van Eijk MJT, Martin F, Stormo KE, Peitsch MC, Ivanov NV. Whole genome profiling physical map and ancestral annotation of tobacco Hicks Broadleaf. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2013; 75:880-9. [PMID: 23672264 PMCID: PMC3824204 DOI: 10.1111/tpj.12247] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2013] [Revised: 04/22/2013] [Accepted: 05/09/2013] [Indexed: 05/08/2023]
Abstract
Genomics-based breeding of economically important crops such as banana, coffee, cotton, potato, tobacco and wheat is often hampered by genome size, polyploidy and high repeat content. We adapted sequence-based whole-genome profiling (WGP™) technology to obtain insight into the polyploidy of the model plant Nicotiana tabacum (tobacco). N. tabacum is assumed to originate from a hybridization event between ancestors of Nicotiana sylvestris and Nicotiana tomentosiformis approximately 200,000 years ago. This resulted in tobacco having a haploid genome size of 4500 million base pairs, approximately four times larger than the related tomato (Solanum lycopersicum) and potato (Solanum tuberosum) genomes. In this study, a physical map containing 9750 contigs of bacterial artificial chromosomes (BACs) was constructed. The mean contig size was 462 kbp, and the calculated genome coverage equaled the estimated tobacco genome size. We used a method for determination of the ancestral origin of the genome by annotation of WGP sequence tags. This assignment agreed with the ancestral annotation available from the tobacco genetic map, and may be used to investigate the evolution of homoeologous genome segments after polyploidization. The map generated is an essential scaffold for the tobacco genome. We propose the combination of WGP physical mapping technology and tag profiling of ancestral lines as a generally applicable method to elucidate the ancestral origin of genome segments of polyploid species. The physical mapping of genes and their origins will enable application of biotechnology to polyploid plants aimed at accelerating and increasing the precision of breeding for abiotic and biotic stress resistance.
Collapse
Affiliation(s)
- Nicolas Sierro
- Biological System Research, Philip Morris International R&D, Philip Morris Products SA Quai Jeanrenaud 5, 2000Neuchatel, Switzerland
| | - Jan van Oeveren
- Keygene NVAgro Business Park 90, 6708 PW, Wageningen, The Netherlands
| | | | - Florian Martin
- Biological System Research, Philip Morris International R&D, Philip Morris Products SA Quai Jeanrenaud 5, 2000Neuchatel, Switzerland
| | - Keith E Stormo
- Amplicon Express Inc.2345 NE Hopkins Court, Pullman, WA, 99163, USA
| | - Manuel C Peitsch
- Biological System Research, Philip Morris International R&D, Philip Morris Products SA Quai Jeanrenaud 5, 2000Neuchatel, Switzerland
| | - Nikolai V Ivanov
- Biological System Research, Philip Morris International R&D, Philip Morris Products SA Quai Jeanrenaud 5, 2000Neuchatel, Switzerland
| |
Collapse
|
33
|
Meihls LN, Handrick V, Glauser G, Barbier H, Kaur H, Haribal MM, Lipka AE, Gershenzon J, Buckler ES, Erb M, Köllner TG, Jander G. Natural variation in maize aphid resistance is associated with 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one glucoside methyltransferase activity. THE PLANT CELL 2013; 25:2341-55. [PMID: 23898034 PMCID: PMC3723630 DOI: 10.1105/tpc.113.112409] [Citation(s) in RCA: 164] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2013] [Revised: 06/04/2013] [Accepted: 06/11/2013] [Indexed: 05/19/2023]
Abstract
Plants differ greatly in their susceptibility to insect herbivory, suggesting both local adaptation and resistance tradeoffs. We used maize (Zea mays) recombinant inbred lines to map a quantitative trait locus (QTL) for the maize leaf aphid (Rhopalosiphum maidis) susceptibility to maize Chromosome 1. Phytochemical analysis revealed that the same locus was also associated with high levels of 2-hydroxy-4,7-dimethoxy-1,4-benzoxazin-3-one glucoside (HDMBOA-Glc) and low levels of 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one glucoside (DIMBOA-Glc). In vitro enzyme assays with candidate genes from the region of the QTL identified three O-methyltransferases (Bx10a-c) that convert DIMBOA-Glc to HDMBOA-Glc. Variation in HDMBOA-Glc production was attributed to a natural CACTA family transposon insertion that inactivates Bx10c in maize lines with low HDMBOA-Glc accumulation. When tested with a population of 26 diverse maize inbred lines, R. maidis produced more progeny on those with high HDMBOA-Glc and low DIMBOA-Glc. Although HDMBOA-Glc was more toxic to R. maidis than DIMBOA-Glc in vitro, BX10c activity and the resulting decline of DIMBOA-Glc upon methylation to HDMBOA-Glc were associated with reduced callose deposition as an aphid defense response in vivo. Thus, a natural transposon insertion appears to mediate an ecologically relevant trade-off between the direct toxicity and defense-inducing properties of maize benzoxazinoids.
Collapse
Affiliation(s)
- Lisa N. Meihls
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853
| | | | - Gaetan Glauser
- Institute of Biology, University of Neuchâtel, 2009 Neuchatel, Switzerland
| | - Hugues Barbier
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853
| | - Harleen Kaur
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853
| | - Meena M. Haribal
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853
| | - Alexander E. Lipka
- U.S. Department of Agriculture–Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853
| | | | - Edward S. Buckler
- U.S. Department of Agriculture–Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853
- Department of Plant Breeding and Genetics, Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853
| | - Matthias Erb
- Max Planck Institute for Chemical Ecology, 07745 Jena, Germany
| | | | - Georg Jander
- Boyce Thompson Institute for Plant Research, Ithaca, New York 14853
- Address correspondence to
| |
Collapse
|
34
|
Tsuji H, Nakamura H, Taoka KI, Shimamoto K. Functional diversification of FD transcription factors in rice, components of florigen activation complexes. PLANT & CELL PHYSIOLOGY 2013; 54:385-97. [PMID: 23324168 PMCID: PMC3589828 DOI: 10.1093/pcp/pct005] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Florigen, a protein encoded by the FLOWERING LOCUS T (FT) in Arabidopsis and Heading date 3a (Hd3a) in rice, is the universal flowering hormone in plants. Florigen is transported from leaves to the shoot apical meristem and initiates floral evocation. In shoot apical cells, conserved cytoplasmic 14-3-3 proteins act as florigen receptors. A hexameric florigen activation complex (FAC) composed of Hd3a, 14-3-3 proteins, and OsFD1, a transcription factor, activates OsMADS15, a rice homolog of Arabidopsis APETALA1, leading to flowering. Because FD is a key component of the FAC, we characterized the FD gene family and their functions. Phylogenetic analysis of FD genes indicated that this family is divided into two groups: (i) canonical FD genes that are conserved among eudicots and non-Poaceae monocots; and (ii) Poaceae-specific FD genes that are organized into three subgroups: Poaceae FD1, FD2 and FD3. The Poaceae FD1 group shares a small sequence motif, T(A/V)LSLNS, with FDs of eudicots and non-Poaceae monocots. Overexpression of OsFD2, a member of the Poaceae FD2 group, produced smaller leaves with shorter plastochrons, suggesting that OsFD2 controls leaf development. In vivo subcellular localization of Hd3a, 14-3-3 and OsFD2 suggested that in contrast to OsFD1, OsFD2 is restricted to the cytoplasm through its interaction with the cytoplasmic 14-3-3 proteins, and interaction of Hd3a with 14-3-3 facilitates nuclear translocation of the FAC containing OsFD2. These results suggest that FD function has diverged between OsFD1 and OsFD2, but formation of a FAC is essential for their function.
Collapse
Affiliation(s)
| | | | | | - Ko Shimamoto
- *Corresponding author: E-mail: ; Fax, +81-743-72-5502
| |
Collapse
|
35
|
Delourme R, Falentin C, Fomeju BF, Boillot M, Lassalle G, André I, Duarte J, Gauthier V, Lucante N, Marty A, Pauchon M, Pichon JP, Ribière N, Trotoux G, Blanchard P, Rivière N, Martinant JP, Pauquet J. High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L. BMC Genomics 2013; 14:120. [PMID: 23432809 PMCID: PMC3600037 DOI: 10.1186/1471-2164-14-120] [Citation(s) in RCA: 150] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2012] [Accepted: 02/11/2013] [Indexed: 11/30/2022] Open
Abstract
Background High density genetic maps built with SNP markers that are polymorphic in various genetic backgrounds are very useful for studying the genetics of agronomical traits as well as genome organization and evolution. Simultaneous dense SNP genotyping of segregating populations and variety collections was applied to oilseed rape (Brassica napus L.) to obtain a high density genetic map for this species and to study the linkage disequilibrium pattern. Results We developed an integrated genetic map for oilseed rape by high throughput SNP genotyping of four segregating doubled haploid populations. A very high level of collinearity was observed between the four individual maps and a large number of markers (>59%) was common to more than two maps. The precise integrated map comprises 5764 SNP and 1603 PCR markers. With a total genetic length of 2250 cM, the integrated map contains a density of 3.27 markers (2.56 SNP) per cM. Genotyping of these mapped SNP markers in oilseed rape collections allowed polymorphism level and linkage disequilibrium (LD) to be studied across the different collections (winter vs spring, different seed quality types) and along the linkage groups. Overall, polymorphism level was higher and LD decayed faster in spring than in “00” winter oilseed rape types but this was shown to vary greatly along the linkage groups. Conclusions Our study provides a valuable resource for further genetic studies using linkage or association mapping, for marker assisted breeding and for Brassica napus sequence assembly and genome organization analyses.
Collapse
|
36
|
Hutchins AP, Liu S, Diez D, Miranda-Saavedra D. The repertoires of ubiquitinating and deubiquitinating enzymes in eukaryotic genomes. Mol Biol Evol 2013; 30:1172-87. [PMID: 23393154 PMCID: PMC3670738 DOI: 10.1093/molbev/mst022] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Reversible protein ubiquitination regulates virtually all known cellular activities. Here, we present a quantitatively evaluated and broadly applicable method to predict eukaryotic ubiquitinating enzymes (UBE) and deubiquitinating enzymes (DUB) and its application to 50 distinct genomes belonging to four of the five major phylogenetic supergroups of eukaryotes: unikonts (including metazoans, fungi, choanozoa, and amoebozoa), excavates, chromalveolates, and plants. Our method relies on a collection of profile hidden Markov models, and we demonstrate its superior performance (coverage and classification accuracy >99%) by identifying approximately 25% and approximately 35% additional UBE and DUB genes in yeast and human, which had not been reported before. In yeast, we predict 85 UBE and 24 DUB genes, for 814 UBE and 107 DUB genes in the human genome. Most UBE and DUB families are present in all eukaryotic lineages, with plants and animals harboring massively enlarged repertoires of ubiquitin ligases. Unicellular organisms, on the other hand, typically harbor less than 300 UBEs and less than 40 DUBs per genome. Ninety-one UBE/DUB genes are orthologous across all four eukaryotic supergroups, and these likely represent a primordial core of enzymes of the ubiquitination system probably dating back to the first eukaryotes approximately 2 billion years ago. Our genome-wide predictions are available through the Database of Ubiquitinating and Deubiquitinating Enzymes (www.DUDE-db.org), where users can also perform advanced sequence and phylogenetic analyses and submit their own predictions.
Collapse
Affiliation(s)
- Andrew Paul Hutchins
- Bioinformatics and Genomics Laboratory, World Premier International Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | | | | | | |
Collapse
|
37
|
Sequencing and automated whole-genome optical mapping of the genome of a domestic goat (Capra hircus). Nat Biotechnol 2012; 31:135-41. [DOI: 10.1038/nbt.2478] [Citation(s) in RCA: 369] [Impact Index Per Article: 30.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2012] [Accepted: 12/06/2012] [Indexed: 11/09/2022]
|
38
|
Cloutier S, Ragupathy R, Miranda E, Radovanovic N, Reimer E, Walichnowski A, Ward K, Rowland G, Duguid S, Banik M. Integrated consensus genetic and physical maps of flax (Linum usitatissimum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2012; 125:1783-95. [PMID: 22890805 PMCID: PMC3493668 DOI: 10.1007/s00122-012-1953-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2012] [Accepted: 07/21/2012] [Indexed: 05/06/2023]
Abstract
Three linkage maps of flax (Linum usitatissimum L.) were constructed from populations CDC Bethune/Macbeth, E1747/Viking and SP2047/UGG5-5 containing between 385 and 469 mapped markers each. The first consensus map of flax was constructed incorporating 770 markers based on 371 shared markers including 114 that were shared by all three populations and 257 shared between any two populations. The 15 linkage group map corresponds to the haploid number of chromosomes of this species. The marker order of the consensus map was largely collinear in all three individual maps but a few local inversions and marker rearrangements spanning short intervals were observed. Segregation distortion was present in all linkage groups which contained 1-52 markers displaying non-Mendelian segregation. The total length of the consensus genetic map is 1,551 cM with a mean marker density of 2.0 cM. A total of 670 markers were anchored to 204 of the 416 fingerprinted contigs of the physical map corresponding to ~274 Mb or 74 % of the estimated flax genome size of 370 Mb. This high resolution consensus map will be a resource for comparative genomics, genome organization, evolution studies and anchoring of the whole genome shotgun sequence.
Collapse
Affiliation(s)
- Sylvie Cloutier
- Cereal Research Centre, Agriculture and Agri-Food Canada, 195 Dafoe Road, Winnipeg, MB, R3T 2M9, Canada.
| | | | | | | | | | | | | | | | | | | |
Collapse
|
39
|
Wei K, Chen J, Wang Y, Chen Y, Chen S, Lin Y, Pan S, Zhong X, Xie D. Genome-wide analysis of bZIP-encoding genes in maize. DNA Res 2012; 19:463-476. [PMID: 23103471 DOI: 10.1093/dnares/dss026-] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2023] Open
Abstract
In plants, basic leucine zipper (bZIP) proteins regulate numerous biological processes such as seed maturation, flower and vascular development, stress signalling and pathogen defence. We have carried out a genome-wide identification and analysis of 125 bZIP genes that exist in the maize genome, encoding 170 distinct bZIP proteins. This family can be divided into 11 groups according to the phylogenetic relationship among the maize bZIP proteins and those in Arabidopsis and rice. Six kinds of intron patterns (a-f) within the basic and hinge regions are defined. The additional conserved motifs have been identified and present the group specificity. Detailed three-dimensional structure analysis has been done to display the sequence conservation and potential distribution of the bZIP domain. Further, we predict the DNA-binding pattern and the dimerization property on the basis of the characteristic features in the basic and hinge regions and the leucine zipper, respectively, which supports our classification greatly and helps to classify 26 distinct subfamilies. The chromosome distribution and the genetic analysis reveal that 58 ZmbZIP genes are located in the segmental duplicate regions in the maize genome, suggesting that the segment chromosomal duplications contribute greatly to the expansion of the maize bZIP family. Across the 60 different developmental stages of 11 organs, three apparent clusters formed represent three kinds of different expression patterns among the ZmbZIP gene family in maize development. A similar but slightly different expression pattern of bZIPs in two inbred lines displays that 22 detected ZmbZIP genes might be involved in drought stress. Thirteen pairs and 143 pairs of ZmbZIP genes show strongly negative and positive correlations in the four distinct fungal infections, respectively, based on the expression profile and Pearson's correlation coefficient analysis.
Collapse
Affiliation(s)
- Kaifa Wei
- Department of Biological Sciences and Biotechnology, Zhangzhou Normal University, 36 Xian Qian Zhi Street, Zhangzhou 363000 Fujian, People's Republic of China.
| | | | | | | | | | | | | | | | | |
Collapse
|
40
|
Yang L, Liu T, Li B, Sui Y, Chen J, Shi J, Wing RA, Chen M. Comparative sequence analysis of the Ghd7 orthologous regions revealed movement of Ghd7 in the grass genomes. PLoS One 2012. [PMID: 23185584 PMCID: PMC3503983 DOI: 10.1371/journal.pone.0050236] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Ghd7 is an important rice gene that has a major effect on several agronomic traits, including yield. To reveal the origin of Ghd7 and sequence evolution of this locus, we performed a comparative sequence analysis of the Ghd7 orthologous regions from ten diploid Oryza species, Brachypodium distachyon, sorghum and maize. Sequence analysis demonstrated high gene collinearity across the genus Oryza and a disruption of collinearity among non-Oryza species. In particular, Ghd7 was not present in orthologous positions except in Oryza species. The Ghd7 regions were found to have low gene densities and high contents of repetitive elements, and that the sizes of orthologous regions varied tremendously. The large transposable element contents resulted in a high frequency of pseudogenization and gene movement events surrounding the Ghd7 loci. Annotation information and cytological experiments have indicated that Ghd7 is a heterochromatic gene. Ghd7 orthologs were identified in B. distachyon, sorghum and maize by phylogenetic analysis; however, the positions of orthologous genes differed dramatically as a consequence of gene movements in grasses. Rather, we identified sequence remnants of gene movement of Ghd7 mediated by illegitimate recombination in the B. distachyon genome.
Collapse
Affiliation(s)
- Lu Yang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Science, Beijing, China
| | - Tieyan Liu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Science, Beijing, China
| | - Bo Li
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Science, Beijing, China
| | - Yi Sui
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Science, Beijing, China
| | - Jinfeng Chen
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Science, Beijing, China
| | - Jinfeng Shi
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Science, Beijing, China
| | - Rod A. Wing
- Arizona Genomics Institute, School of Plant Sciences, BIO5 Institute, University of Arizona, Tucson, Arizona, United States of America
| | - Mingsheng Chen
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Science, Beijing, China
- * E-mail:
| |
Collapse
|
41
|
Wei K, Chen J, Wang Y, Chen Y, Chen S, Lin Y, Pan S, Zhong X, Xie D. Genome-wide analysis of bZIP-encoding genes in maize. DNA Res 2012; 19:463-76. [PMID: 23103471 PMCID: PMC3514857 DOI: 10.1093/dnares/dss026] [Citation(s) in RCA: 180] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
In plants, basic leucine zipper (bZIP) proteins regulate numerous biological processes such as seed maturation, flower and vascular development, stress signalling and pathogen defence. We have carried out a genome-wide identification and analysis of 125 bZIP genes that exist in the maize genome, encoding 170 distinct bZIP proteins. This family can be divided into 11 groups according to the phylogenetic relationship among the maize bZIP proteins and those in Arabidopsis and rice. Six kinds of intron patterns (a–f) within the basic and hinge regions are defined. The additional conserved motifs have been identified and present the group specificity. Detailed three-dimensional structure analysis has been done to display the sequence conservation and potential distribution of the bZIP domain. Further, we predict the DNA-binding pattern and the dimerization property on the basis of the characteristic features in the basic and hinge regions and the leucine zipper, respectively, which supports our classification greatly and helps to classify 26 distinct subfamilies. The chromosome distribution and the genetic analysis reveal that 58 ZmbZIP genes are located in the segmental duplicate regions in the maize genome, suggesting that the segment chromosomal duplications contribute greatly to the expansion of the maize bZIP family. Across the 60 different developmental stages of 11 organs, three apparent clusters formed represent three kinds of different expression patterns among the ZmbZIP gene family in maize development. A similar but slightly different expression pattern of bZIPs in two inbred lines displays that 22 detected ZmbZIP genes might be involved in drought stress. Thirteen pairs and 143 pairs of ZmbZIP genes show strongly negative and positive correlations in the four distinct fungal infections, respectively, based on the expression profile and Pearson's correlation coefficient analysis.
Collapse
Affiliation(s)
- Kaifa Wei
- Department of Biological Sciences and Biotechnology, Zhangzhou Normal University, 36 Xian Qian Zhi Street, Zhangzhou 363000 Fujian, People's Republic of China.
| | | | | | | | | | | | | | | | | |
Collapse
|
42
|
Doležel J, Vrána J, Safář J, Bartoš J, Kubaláková M, Simková H. Chromosomes in the flow to simplify genome analysis. Funct Integr Genomics 2012; 12:397-416. [PMID: 22895700 PMCID: PMC3431466 DOI: 10.1007/s10142-012-0293-0] [Citation(s) in RCA: 71] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2012] [Accepted: 07/30/2012] [Indexed: 11/25/2022]
Abstract
Nuclear genomes of human, animals, and plants are organized into subunits called chromosomes. When isolated into aqueous suspension, mitotic chromosomes can be classified using flow cytometry according to light scatter and fluorescence parameters. Chromosomes of interest can be purified by flow sorting if they can be resolved from other chromosomes in a karyotype. The analysis and sorting are carried out at rates of 10(2)-10(4) chromosomes per second, and for complex genomes such as wheat the flow sorting technology has been ground-breaking in reducing genome complexity for genome sequencing. The high sample rate provides an attractive approach for karyotype analysis (flow karyotyping) and the purification of chromosomes in large numbers. In characterizing the chromosome complement of an organism, the high number that can be studied using flow cytometry allows for a statistically accurate analysis. Chromosome sorting plays a particularly important role in the analysis of nuclear genome structure and the analysis of particular and aberrant chromosomes. Other attractive but not well-explored features include the analysis of chromosomal proteins, chromosome ultrastructure, and high-resolution mapping using FISH. Recent results demonstrate that chromosome flow sorting can be coupled seamlessly with DNA array and next-generation sequencing technologies for high-throughput analyses. The main advantages are targeting the analysis to a genome region of interest and a significant reduction in sample complexity. As flow sorters can also sort single copies of chromosomes, shotgun sequencing DNA amplified from them enables the production of haplotype-resolved genome sequences. This review explains the principles of flow cytometric chromosome analysis and sorting (flow cytogenetics), discusses the major uses of this technology in genome analysis, and outlines future directions.
Collapse
Affiliation(s)
- Jaroslav Doležel
- Centre of the Region Haná for Biotechnological and Agricultural Research, Institute of Experimental Botany, Sokolovská 6, Olomouc, Czech Republic.
| | | | | | | | | | | |
Collapse
|
43
|
Figueroa DM, Bass HW. Development of pachytene FISH maps for six maize chromosomes and their integration with other maize maps for insights into genome structure variation. Chromosome Res 2012; 20:363-80. [PMID: 22588802 PMCID: PMC3391363 DOI: 10.1007/s10577-012-9281-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2012] [Revised: 03/27/2012] [Accepted: 03/28/2012] [Indexed: 12/18/2022]
Abstract
Integrated cytogenetic pachytene fluorescence in situ hybridization (FISH) maps were developed for chromosomes 1, 3, 4, 5, 6, and 8 of maize using restriction fragment length polymorphism marker-selected Sorghum propinquum bacterial artificial chromosomes (BACs) for 19 core bin markers and 4 additional genetic framework loci. Using transgenomic BAC FISH mapping on maize chromosome addition lines of oats, we found that the relative locus position along the pachytene chromosome did not change as a function of total arm length, indicative of uniform axial contraction along the fibers during mid-prophase for tested loci on chromosomes 4 and 5. Additionally, we cytogenetically FISH mapped six loci from chromosome 9 onto their duplicated syntenic regions on chromosomes 1 and 6, which have varying amounts of sequence divergence, using sorghum BACs homologous to the chromosome 9 loci. We found that successful FISH mapping was possible even when the chromosome 9 selective marker had no counterpart in the syntenic block. In total, these 29 FISH-mapped loci were used to create the most extensive pachytene FISH maps to date for these six maize chromosomes. The FISH-mapped loci were then merged into one composite karyotype for direct comparative analysis with the recombination nodule-predicted cytogenetic, genetic linkage, and genomic physical maps using the relative marker positions of the loci on all the maps. Marker colinearity was observed between all pair-wise map comparisons, although marker distribution patterns varied widely in some cases. As expected, we found that the recombination nodule-based predictions most closely resembled the cytogenetic map positions overall. Cytogenetic and linkage map comparisons agreed with previous studies showing a decrease in marker spacing in the peri-centromeric heterochromatin region on the genetic linkage maps. In fact, there was a general trend with most loci mapping closer towards the telomere on the linkage maps than on the cytogenetic maps, regardless of chromosome number or maize inbred line source, with just some of the telomeric loci exempted. Finally and somewhat surprisingly, we observed considerable variation between the relative arm positions of loci when comparing our cytogenetic FISH map to the B73 genomic physical maps, even where comparisons were to a B73-derived cytogenetic map. This variation is more evident between different chromosome arms, but less so within a given arm, ruling out any type of inbred-line dependent global features of linear deoxyribonucleic acid compared with the meiotic fiber organization. This study provides a means for analyzing the maize genome structure by producing new connections for integrating the cytogenetic, linkage, and physical maps of maize.
Collapse
Affiliation(s)
- Debbie M Figueroa
- Department of Biological Science, Florida State University, Tallahassee, 32306-4295, USA.
| | | |
Collapse
|
44
|
Wei K, Chen J, Chen Y, Wu L, Xie D. Multiple-strategy analyses of ZmWRKY subgroups and functional exploration of ZmWRKY genes in pathogen responses. MOLECULAR BIOSYSTEMS 2012; 8:1940-9. [PMID: 22569521 DOI: 10.1039/c2mb05483c] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The WRKY transcription factor family plays crucial roles in biotic responses, such as fungi, bacteria, viruses and nematode infections and insect attacks. In this article, multiple-strategy analyses of the three subgroups were performed in order to gain structural and evolutionary proofs of the overall WRKY family and unravel the functions possessed by each group or subgroup. Thus we analyzed the similarity of WRKY factors between maize and Arabidopsis based on homology modelling. The gene structure and motif analyses of Group II demonstrated that specific motifs existing in the given subgroups may contribute to the functional diversification of WRKY proteins and the two types of conserved intron splice sites suggest their evolutionary conservation. The evolutionary divergence time estimation of Group III proteins indicated that the divergence of Group III occurred during the Neogene period. Further, we focused on the roles of maize WRKYs in pathogen responses based on publicly available microarray experiments. The result suggested that some ZmWRKYs are expressed specifically under the infection of certain fungus, among which some are up-regulated and some are down-regulated, indicating their positive or negative roles in pathogen response. Also, some genes remain unchanged upon fungal infection. Pearson correlation coefficient (PCC) analysis was performed using 62 fungal infection experiments to calculate the correlation between each pair of genes. A PCC value higher than 0.6 was regarded as strong correlation - in these circumstances, ninety pairs of genes showed a strong positive correlation, while fifteen pairs of genes displayed a strong negative correlation. These correlated genes form a co-regulatory network and help us investigate the existence of interactions between WRKY proteins.
Collapse
Affiliation(s)
- Kaifa Wei
- Department of Biological Sciences and Biotechnology, Zhangzhou Normal University, 36 Xian Qian Zhi Street, Zhangzhou 363000, Fujian, China.
| | | | | | | | | |
Collapse
|
45
|
Integration of the Draft Sequence and Physical Map as a Framework for Genomic Research in Soybean (Glycine max (L.) Merr.) and Wild Soybean (Glycine soja Sieb. and Zucc.). G3-GENES GENOMES GENETICS 2012; 2:321-9. [PMID: 22413085 PMCID: PMC3291501 DOI: 10.1534/g3.111.001834] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2011] [Accepted: 12/21/2011] [Indexed: 11/21/2022]
Abstract
Soybean is a model for the legume research community because of its importance as a crop, densely populated genetic maps, and the availability of a genome sequence. Even though a whole-genome shotgun sequence and bacterial artificial chromosome (BAC) libraries are available, a high-resolution, chromosome-based physical map linked to the sequence assemblies is still needed for whole-genome alignments and to facilitate map-based gene cloning. Three independent G. max BAC libraries combined with genetic and gene-based markers were used to construct a minimum tiling path (MTP) of BAC clones. A total of 107,214 clones were assembled into 1355 FPC (FingerPrinted Contigs) contigs, incorporating 4628 markers and aligned to the G. max reference genome sequence using BAC end-sequence information. Four different MTPs were made for G. max that covered from 92.6% to 95.0% of the soybean draft genome sequence (gmax1.01). Because our purpose was to pick the most reliable and complete MTP, and not the MTP with the minimal number of clones, the FPC map and draft sequence were integrated and clones with unpaired BES were added to build a high-quality physical map with the fewest gaps possible (http://soybase.org). A physical map was also constructed for the undomesticated ancestor (G. soja) of soybean to explore genome variation between G. max and G. soja. 66,028 G. soja clones were assembled into 1053 FPC contigs covering approximately 547 Mbp of the G. max genome sequence. These physical maps for G. max and its undomesticated ancestor, G. soja, will serve as a framework for ordering sequence fragments, comparative genomics, cloning genes, and evolutionary analyses of legume genomes.
Collapse
|
46
|
Advances in BAC-based physical mapping and map integration strategies in plants. J Biomed Biotechnol 2012; 2012:184854. [PMID: 22500080 PMCID: PMC3303678 DOI: 10.1155/2012/184854] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2011] [Revised: 10/26/2011] [Accepted: 11/11/2011] [Indexed: 12/29/2022] Open
Abstract
In the advent of next-generation sequencing (NGS) platforms, map-based sequencing strategy has been recently suppressed being too expensive and laborious. The detailed studies on NGS drafts alone indicated these assemblies remain far from gold standard reference quality, especially when applied on complex genomes. In this context the conventional BAC-based physical mapping has been identified as an important intermediate layer in current hybrid sequencing strategy. BAC-based physical map construction and its integration with high-density genetic maps have benefited from NGS and high-throughput array platforms. This paper addresses the current advancements of BAC-based physical mapping and high-throughput map integration strategies to obtain densely anchored well-ordered physical maps. The resulted maps are of immediate utility while providing a template to harness the maximum benefits of the current NGS platforms.
Collapse
|
47
|
Wei KF, Chen J, Chen YF, Wu LJ, Xie DX. Molecular phylogenetic and expression analysis of the complete WRKY transcription factor family in maize. DNA Res 2012; 19:153-64. [PMID: 22279089 PMCID: PMC3325079 DOI: 10.1093/dnares/dsr048] [Citation(s) in RCA: 175] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance.
Collapse
Affiliation(s)
- Kai-Fa Wei
- Department of Biological Sciences and Biotechnology, Zhangzhou Normal University, Zhangzhou, Fujian, China.
| | | | | | | | | |
Collapse
|
48
|
Cannon SB, Shoemaker RC. Evolutionary and comparative analyses of the soybean genome. BREEDING SCIENCE 2012; 61:437-44. [PMID: 23136483 PMCID: PMC3406793 DOI: 10.1270/jsbbs.61.437] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2011] [Accepted: 09/19/2011] [Indexed: 05/08/2023]
Abstract
The soybean genome assembly has been available since the end of 2008. Significant features of the genome include large, gene-poor, repeat-dense pericentromeric regions, spanning roughly 57% of the genome sequence; a relatively large genome size of ~1.15 billion bases; remnants of a genome duplication that occurred ~13 million years ago (Mya); and fainter remnants of older polyploidies that occurred ~58 Mya and >130 Mya. The genome sequence has been used to identify the genetic basis for numerous traits, including disease resistance, nutritional characteristics, and developmental features. The genome sequence has provided a scaffold for placement of many genomic feature elements, both from within soybean and from related species. These may be accessed at several websites, including http://www.phytozome.net, http://soybase.org, http://comparative-legumes.org, and http://www.legumebase.brc.miyazaki-u.ac.jp. The taxonomic position of soybean in the Phaseoleae tribe of the legumes means that there are approximately two dozen other beans and relatives that have undergone independent domestication, and which may have traits that will be useful for transfer to soybean. Methods of translating information between species in the Phaseoleae range from design of markers for marker assisted selection, to transformation with Agrobacterium or with other experimental transformation methods.
Collapse
|
49
|
Quail MA, Matthews L, Sims S, Lloyd C, Beasley H, Baxter SW. Genomic libraries: II. Subcloning, sequencing, and assembling large-insert genomic DNA clones. Methods Mol Biol 2012; 772:59-81. [PMID: 22065432 DOI: 10.1007/978-1-61779-228-1_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Sequencing large insert clones to completion is useful for characterizing specific genomic regions, identifying haplotypes, and closing gaps in whole genome sequencing projects. Despite being a standard technique in molecular laboratories, DNA sequencing using the Sanger method can be highly problematic when complex secondary structures or sequence repeats are encountered in genomic clones. Here, we describe methods to isolate DNA from a large insert clone (fosmid or BAC), subclone the sample, and sequence the region to the highest industry standard. Troubleshooting solutions for sequencing difficult templates are discussed.
Collapse
Affiliation(s)
- Mike A Quail
- Sequencing Research and Development, Wellcome Trust Sanger Institute, Cambridge, UK
| | | | | | | | | | | |
Collapse
|
50
|
Ganal MW, Durstewitz G, Polley A, Bérard A, Buckler ES, Charcosset A, Clarke JD, Graner EM, Hansen M, Joets J, Le Paslier MC, McMullen MD, Montalent P, Rose M, Schön CC, Sun Q, Walter H, Martin OC, Falque M. A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome. PLoS One 2011; 6:e28334. [PMID: 22174790 PMCID: PMC3234264 DOI: 10.1371/journal.pone.0028334] [Citation(s) in RCA: 383] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2011] [Accepted: 11/05/2011] [Indexed: 01/05/2023] Open
Abstract
SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations - IBM (B73×Mo17) and LHRF (F2×F252) - were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.
Collapse
Affiliation(s)
| | | | | | - Aurélie Bérard
- Etude du Polymorphisme des Génomes Végétaux, INRA – CEA – Institut de Génomique – Centre National de Génotypage, Evry, France
| | | | - Alain Charcosset
- UMR de Génétique Végétale, INRA – Université Paris-Sud – CNRS – AgroParisTech, Gif-sur-Yvette, France
| | - Joseph D. Clarke
- Syngenta Biotechnology Inc., Research Triangle Park, North Carolina, United States of America
| | | | - Mark Hansen
- Illumina Inc., San Diego, California, United States of America
| | - Johann Joets
- UMR de Génétique Végétale, INRA – Université Paris-Sud – CNRS – AgroParisTech, Gif-sur-Yvette, France
| | - Marie-Christine Le Paslier
- Etude du Polymorphisme des Génomes Végétaux, INRA – CEA – Institut de Génomique – Centre National de Génotypage, Evry, France
| | - Michael D. McMullen
- Plant Genetics Research Unit, USDA-Agricultural Research Service, Columbia, Missouri, United States of America
| | - Pierre Montalent
- UMR de Génétique Végétale, INRA – Université Paris-Sud – CNRS – AgroParisTech, Gif-sur-Yvette, France
| | - Mark Rose
- Syngenta Biotechnology Inc., Research Triangle Park, North Carolina, United States of America
| | - Chris-Carolin Schön
- Department of Plant Breeding, Technische Universität München, Freising, Germany
| | - Qi Sun
- Cornell University, Ithaca, New York, United States of America
| | - Hildrun Walter
- Department of Plant Breeding, Technische Universität München, Freising, Germany
| | - Olivier C. Martin
- UMR de Génétique Végétale, INRA – Université Paris-Sud – CNRS – AgroParisTech, Gif-sur-Yvette, France
| | - Matthieu Falque
- UMR de Génétique Végétale, INRA – Université Paris-Sud – CNRS – AgroParisTech, Gif-sur-Yvette, France
- * E-mail:
| |
Collapse
|