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Jin M, Liu H, Liu X, Guo T, Guo J, Yin Y, Ji Y, Li Z, Zhang J, Wang X, Qiao F, Xiao Y, Zan Y, Yan J. Complex genetic architecture underlying the plasticity of maize agronomic traits. PLANT COMMUNICATIONS 2023; 4:100473. [PMID: 36642074 DOI: 10.1016/j.xplc.2022.100473] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 08/21/2022] [Accepted: 11/07/2022] [Indexed: 05/11/2023]
Abstract
Phenotypic plasticity is the ability of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and establishing a predictive model is highly relevant to future agriculture under a changing climate. Here we report findings on the genetic basis of phenotypic plasticity for 23 complex traits using a diverse maize population planted at five sites with distinct environmental conditions. We found that latitude-related environmental factors were the main drivers of across-site variation in flowering time traits but not in plant architecture or yield traits. For the 23 traits, we detected 109 quantitative trait loci (QTLs), 29 for mean values, 66 for plasticity, and 14 for both parameters, and 80% of the QTLs interacted with latitude. The effects of several QTLs changed in magnitude or sign, driving variation in phenotypic plasticity. We experimentally validated one plastic gene, ZmTPS14.1, whose effect was likely mediated by the compensation effect of ZmSPL6 from a downstream pathway. By integrating genetic diversity, environmental variation, and their interaction into a joint model, we could provide site-specific predictions with increased accuracy by as much as 9.9%, 2.2%, and 2.6% for days to tassel, plant height, and ear weight, respectively. This study revealed a complex genetic architecture involving multiple alleles, pleiotropy, and genotype-by-environment interaction that underlies variation in the mean and plasticity of maize complex traits. It provides novel insights into the dynamic genetic architecture of agronomic traits in response to changing environments, paving a practical way toward precision agriculture.
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Affiliation(s)
- Minliang Jin
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Haijun Liu
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna BioCenter, 1030 Vienna, Austria
| | - Xiangguo Liu
- Institute of Agricultural Biotechnology, Jilin Academy of Agricultural Sciences, Changchun 130033, China
| | - Tingting Guo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Jia Guo
- Institute of Agricultural Biotechnology, Jilin Academy of Agricultural Sciences, Changchun 130033, China
| | - Yuejia Yin
- Institute of Agricultural Biotechnology, Jilin Academy of Agricultural Sciences, Changchun 130033, China
| | - Yan Ji
- Key Laboratory of Tobacco Improvement and Biotechnology, Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao 266000, China
| | - Zhenxian Li
- Institute of Agricultural Sciences of Xishuangbanna Prefecture of Yunnan Province, Jinghong 666100, China
| | - Jinhong Zhang
- Institute of Agricultural Sciences of Xishuangbanna Prefecture of Yunnan Province, Jinghong 666100, China
| | - Xiaqing Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Feng Qiao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Yingjie Xiao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Yanjun Zan
- Umeå Plant Science Center, Department of Forestry Genetics and Plant Physiology, Swedish University of Agricultural Sciences, 90736 Umeå, Sweden; Key Laboratory of Tobacco Improvement and Biotechnology, Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao 266000, China.
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China.
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2
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A comparative genomics examination of desiccation tolerance and sensitivity in two sister grass species. Proc Natl Acad Sci U S A 2022; 119:2118886119. [PMID: 35082155 PMCID: PMC8812550 DOI: 10.1073/pnas.2118886119] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/14/2021] [Indexed: 12/13/2022] Open
Abstract
This is a significant sister group contrast comparative study of the underpinning genomics and evolution of desiccation tolerance (DT), a critical trait in the evolution of land plants. Our results revealed that the DT grass Sporobolus stapfianus is transcriptionally primed to tolerate a dehydration/desiccation event and that the desiccation response in the DT S. stapfianus is distinct from the water stress response of the desiccation-sensitive Sporobolus pyramidalis. Our results also show that the desiccation response is largely unique, indicating a recent evolution of this trait within the angiosperms, and that inhibition of senescence during dehydration is likely critical in rendering a plant desiccation tolerant. Desiccation tolerance is an ancient and complex trait that spans all major lineages of life on earth. Although important in the evolution of land plants, the mechanisms that underlay this complex trait are poorly understood, especially for vegetative desiccation tolerance (VDT). The lack of suitable closely related plant models that offer a direct contrast between desiccation tolerance and sensitivity has hampered progress. We have assembled high-quality genomes for two closely related grasses, the desiccation-tolerant Sporobolus stapfianus and the desiccation-sensitive Sporobolus pyramidalis. Both species are complex polyploids; S. stapfianus is primarily tetraploid, and S. pyramidalis is primarily hexaploid. S. pyramidalis undergoes a major transcriptome remodeling event during initial exposure to dehydration, while S. stapfianus has a muted early response, with peak remodeling during the transition between 1.5 and 1.0 grams of water (gH2O) g−1 dry weight (dw). Functionally, the dehydration transcriptome of S. stapfianus is unrelated to that for S. pyramidalis. A comparative analysis of the transcriptomes of the hydrated controls for each species indicated that S. stapfianus is transcriptionally primed for desiccation. Cross-species comparative analyses indicated that VDT likely evolved from reprogramming of desiccation tolerance mechanisms that evolved in seeds and that the tolerance mechanism of S. stapfianus represents a recent evolution for VDT within the Chloridoideae. Orthogroup analyses of the significantly differentially abundant transcripts reconfirmed our present understanding of the response to dehydration, including the lack of an induction of senescence in resurrection angiosperms. The data also suggest that failure to maintain protein structure during dehydration is likely critical in rendering a plant desiccation sensitive.
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Comprehensive transcriptome characterization of Grus japonensis using PacBio SMRT and Illumina sequencing. Sci Rep 2021; 11:23927. [PMID: 34907275 PMCID: PMC8671462 DOI: 10.1038/s41598-021-03474-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 12/03/2021] [Indexed: 12/13/2022] Open
Abstract
The red-crowned crane (Grus japonensis) is an endangered species distributed across southeast Russia, northeast China, Korea, and Japan. Here, we sequenced for the first time the full-length unreferenced transcriptome of red-crowned crane mixed samples using a PacBio Sequel platform. A total of 359,136 circular consensus sequences (CCS) were obtained via clustering to remove redundancy. A total of 303,544 full-length non-chimeric sequences were identified by judging whether CCS contained 5' and 3' adapters, and the poly(A) tail. Eight samples were sequenced using Illumina, and PacBio sequencing data were corrected according to the collected Illumina data to obtain more accurate full-length transcripts. A total of 4,100 long non-coding RNAs, 13,115 simple sequences repeat loci and 29 transcription factor families were identified. The expression of lncRNAs and TFs in pancreas was lowest comparing with other tissues. Many enriched immune-related transmission pathways (MHC and IL receptors) were identified in the spleen. This study will contribute to a better understanding of the gene structure and post-transcriptional regulatory network, and provide references for future studies on red-crowned cranes.
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Hufford MB, Seetharam AS, Woodhouse MR, Chougule KM, Ou S, Liu J, Ricci WA, Guo T, Olson A, Qiu Y, Della Coletta R, Tittes S, Hudson AI, Marand AP, Wei S, Lu Z, Wang B, Tello-Ruiz MK, Piri RD, Wang N, Kim DW, Zeng Y, O'Connor CH, Li X, Gilbert AM, Baggs E, Krasileva KV, Portwood JL, Cannon EKS, Andorf CM, Manchanda N, Snodgrass SJ, Hufnagel DE, Jiang Q, Pedersen S, Syring ML, Kudrna DA, Llaca V, Fengler K, Schmitz RJ, Ross-Ibarra J, Yu J, Gent JI, Hirsch CN, Ware D, Dawe RK. De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes. Science 2021; 373:655-662. [PMID: 34353948 PMCID: PMC8733867 DOI: 10.1126/science.abg5289] [Citation(s) in RCA: 279] [Impact Index Per Article: 69.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 06/24/2021] [Indexed: 12/24/2022]
Abstract
We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The number of pan-genes in these diverse genomes exceeds 103,000, with approximately a third found across all genotypes. The results demonstrate that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres revealed additional variation in major cytological landmarks. We show that combining structural variation with single-nucleotide polymorphisms can improve the power of quantitative mapping studies. We also document variation at the level of DNA methylation and demonstrate that unmethylated regions are enriched for cis-regulatory elements that contribute to phenotypic variation.
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Affiliation(s)
- Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Arun S Seetharam
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Genome Informatics Facility, Iowa State University, Ames, IA 50011, USA
| | - Margaret R Woodhouse
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | | | - Shujun Ou
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Jianing Liu
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - William A Ricci
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Tingting Guo
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Andrew Olson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Yinjie Qiu
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Silas Tittes
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - Asher I Hudson
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | | | - Sharon Wei
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Zhenyuan Lu
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Bo Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | | | - Rebecca D Piri
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Na Wang
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Dong Won Kim
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Yibing Zeng
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - Christine H O'Connor
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN 55108, USA
| | - Xianran Li
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Amanda M Gilbert
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Erin Baggs
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - Ksenia V Krasileva
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - John L Portwood
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Ethalinda K S Cannon
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Carson M Andorf
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Nancy Manchanda
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Samantha J Snodgrass
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - David E Hufnagel
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA, 50010, USA
| | - Qiuhan Jiang
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Sarah Pedersen
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Michael L Syring
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - David A Kudrna
- Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
| | | | | | - Robert J Schmitz
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - Jeffrey Ross-Ibarra
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
- Genome Center, University of California, Davis, CA 95616, USA
| | - Jianming Yu
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Jonathan I Gent
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Doreen Ware
- USDA-ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, Ithaca, NY 14853, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - R Kelly Dawe
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA.
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5
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Sequence of the supernumerary B chromosome of maize provides insight into its drive mechanism and evolution. Proc Natl Acad Sci U S A 2021; 118:2104254118. [PMID: 34088847 PMCID: PMC8201846 DOI: 10.1073/pnas.2104254118] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
B chromosomes are enigmatic elements in thousands of plant and animal genomes that persist in populations despite being nonessential. They circumvent the laws of Mendelian inheritance but the molecular mechanisms underlying this behavior remain unknown. Here we present the sequence, annotation, and analysis of the maize B chromosome providing insight into its drive mechanism. The sequence assembly reveals detailed locations of the elements involved with the cis and trans functions of its drive mechanism, consisting of nondisjunction at the second pollen mitosis and preferential fertilization of the egg by the B-containing sperm. We identified 758 protein-coding genes in 125.9 Mb of B chromosome sequence, of which at least 88 are expressed. Our results demonstrate that transposable elements in the B chromosome are shared with the standard A chromosome set but multiple lines of evidence fail to detect a syntenic genic region in the A chromosomes, suggesting a distant origin. The current gene content is a result of continuous transfer from the A chromosomal complement over an extended evolutionary time with subsequent degradation but with selection for maintenance of this nonvital chromosome.
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6
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Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn. Nat Commun 2021; 12:1227. [PMID: 33623026 PMCID: PMC7902669 DOI: 10.1038/s41467-021-21380-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 01/26/2021] [Indexed: 01/31/2023] Open
Abstract
Sweet corn is one of the most important vegetables in the United States and Canada. Here, we present a de novo assembly of a sweet corn inbred line Ia453 with the mutated shrunken2-reference allele (Ia453-sh2). This mutation accumulates more sugar and is present in most commercial hybrids developed for the processing and fresh markets. The ten pseudochromosomes cover 92% of the total assembly and 99% of the estimated genome size, with a scaffold N50 of 222.2 Mb. This reference genome completely assembles the large structural variation that created the mutant sh2-R allele. Furthermore, comparative genomics analysis with six field corn genomes highlights differences in single-nucleotide polymorphisms, structural variations, and transposon composition. Phylogenetic analysis of 5,381 diverse maize and teosinte accessions reveals genetic relationships between sweet corn and other types of maize. Our results show evidence for a common origin in northern Mexico for modern sweet corn in the U.S. Finally, population genomic analysis identifies regions of the genome under selection and candidate genes associated with sweet corn traits, such as early flowering, endosperm composition, plant and tassel architecture, and kernel row number. Our study provides a high-quality reference-genome sequence to facilitate comparative genomics, functional studies, and genomic-assisted breeding for sweet corn.
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7
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Yan Z, Shen Z, Li Z, Chao Q, Kong L, Gao ZF, Li QW, Zheng HY, Zhao CF, Lu CM, Wang YW, Wang BC. Genome-wide transcriptome and proteome profiles indicate an active role of alternative splicing during de-etiolation of maize seedlings. PLANTA 2020; 252:60. [PMID: 32964359 DOI: 10.1007/s00425-020-03464-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 09/12/2020] [Indexed: 06/11/2023]
Abstract
AS events affect genes encoding protein domain composition and make the single gene produce more proteins with a certain number of genes to satisfy the establishment of photosynthesis during de-etiolation. The drastic switch from skotomorphogenic to photomorphogenic development is an excellent system to elucidate rapid developmental responses to environmental stimuli in plants. To decipher the effects of different light wavelengths on de-etiolation, we illuminated etiolated maize seedlings with blue, red, blue-red mixed and white light, respectively. We found that blue light alone has the strongest effect on photomorphogenesis and that this effect can be attributed to the higher number and expression levels of photosynthesis and chlorosynthesis proteins. Deep sequencing-based transcriptome analysis revealed gene expression changes under different light treatments and a genome-wide alteration in alternative splicing (AS) profiles. We discovered 41,188 novel transcript isoforms for annotated genes, which increases the percentage of multi-exon genes with AS to 63% in maize. We provide peptide support for all defined types of AS, especially retained introns. Further in silico prediction revealed that 58.2% of retained introns have changes in domains compared with their most similar annotated protein isoform. This suggests that AS acts as a protein function switch allowing rapid light response through the addition or removal of functional domains. The richness of novel transcripts and protein isoforms also demonstrates the potential and importance of integrating proteomics into genome annotation in maize.
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Affiliation(s)
- Zhen Yan
- Photosynthesis Research Center, Key Laboratory of Photobiology, Institute of Botany, Chinese Academy of Sciences, No. 20 Nanxincun, Xiangshan, Beijing, 100093, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Zhuo Shen
- Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangdong Key Laboratory for New Technology Research of Vegetables, Guangzhou, 510640, China
| | - Zhe Li
- Precision Scientific (Beijing) Co., Ltd., Beijing, 100085, China
| | - Qing Chao
- Photosynthesis Research Center, Key Laboratory of Photobiology, Institute of Botany, Chinese Academy of Sciences, No. 20 Nanxincun, Xiangshan, Beijing, 100093, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
- The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100039, China
| | - Lei Kong
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, College of Life Sciences, Peking University, Beijing, 100871, China
| | - Zhi-Fang Gao
- Photosynthesis Research Center, Key Laboratory of Photobiology, Institute of Botany, Chinese Academy of Sciences, No. 20 Nanxincun, Xiangshan, Beijing, 100093, China
| | - Qing-Wei Li
- Beijing Botanical Garden, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Hai-Yan Zheng
- Center for Advanced Biotechnology and Medicine, Biological Mass Spectrometry Facility, Rutgers University, Piscataway, NJ, 08855, USA
| | - Cai-Feng Zhao
- Center for Advanced Biotechnology and Medicine, Biological Mass Spectrometry Facility, Rutgers University, Piscataway, NJ, 08855, USA
| | - Cong-Ming Lu
- State Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Taian, 271018, Shandong, China
| | - Ying-Wei Wang
- Beijing Botanical Garden, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
| | - Bai-Chen Wang
- Photosynthesis Research Center, Key Laboratory of Photobiology, Institute of Botany, Chinese Academy of Sciences, No. 20 Nanxincun, Xiangshan, Beijing, 100093, China.
- University of Chinese Academy of Sciences, 100049, Beijing, China.
- The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100039, China.
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Morales L, Repka AC, Swarts KL, Stafstrom WC, He Y, Sermons SM, Yang Q, Lopez-Zuniga LO, Rucker E, Thomason WE, Nelson RJ, Balint-Kurti PJ. Genotypic and phenotypic characterization of a large, diverse population of maize near-isogenic lines. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 103:1246-1255. [PMID: 32349163 DOI: 10.1111/tpj.14787] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 04/13/2020] [Accepted: 04/22/2020] [Indexed: 06/11/2023]
Abstract
Genome-wide association (GWA) studies can identify quantitative trait loci (QTL) putatively underlying traits of interest, and nested association mapping (NAM) can further assess allelic series. Near-isogenic lines (NILs) can be used to characterize, dissect and validate QTL, but the development of NILs is costly. Previous studies have utilized limited numbers of NILs and introgression donors. We characterized a panel of 1270 maize NILs derived from crosses between 18 diverse inbred lines and the recurrent inbred parent B73, referred to as the nested NILs (nNILs). The nNILs were phenotyped for flowering time, height and resistance to three foliar diseases, and genotyped with genotyping-by-sequencing. Across traits, broad-sense heritability (0.4-0.8) was relatively high. The 896 genotyped nNILs contain 2638 introgressions, which span the entire genome with substantial overlap within and among allele donors. GWA with the whole panel identified 29 QTL for height and disease resistance with allelic variation across donors. To date, this is the largest and most diverse publicly available panel of maize NILs to be phenotypically and genotypically characterized. The nNILs are a valuable resource for the maize community, providing an extensive collection of introgressions from the founders of the maize NAM population in a B73 background combined with data on six agronomically important traits and from genotyping-by-sequencing. We demonstrate that the nNILs can be used for QTL mapping and allelic testing. The majority of nNILs had four or fewer introgressions, and could readily be used for future fine mapping studies.
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Affiliation(s)
- Laura Morales
- School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - A C Repka
- School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - Kelly L Swarts
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna BioCenter, 1030, Vienna, Austria
- Max Perutz Labs, University of Vienna, Vienna BioCenter, 1030, Vienna, Austria
| | - William C Stafstrom
- School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - Yijian He
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695, USA
| | - Shannon M Sermons
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695, USA
| | - Qin Yang
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695, USA
| | - Luis O Lopez-Zuniga
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695, USA
| | - Elizabeth Rucker
- School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA, 24061, USA
| | - Wade E Thomason
- School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA, 24061, USA
| | - Rebecca J Nelson
- School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - Peter J Balint-Kurti
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, 27695, USA
- Plant Science Research Unit, United States Department of Agriculture-Agricultural Research Service, Raleigh, NC, 27695, USA
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9
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de Oliveira AA, Resende MFR, Ferrão LFV, Amadeu RR, Guimarães LJM, Guimarães CT, Pastina MM, Margarido GRA. Genomic prediction applied to multiple traits and environments in second season maize hybrids. Heredity (Edinb) 2020; 125:60-72. [PMID: 32472060 DOI: 10.1038/s41437-020-0321-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 05/05/2020] [Accepted: 05/08/2020] [Indexed: 02/06/2023] Open
Abstract
Genomic selection has become a reality in plant breeding programs with the reduction in genotyping costs. Especially in maize breeding programs, it emerges as a promising tool for predicting hybrid performance. The dynamics of a commercial breeding program involve the evaluation of several traits simultaneously in a large set of target environments. Therefore, multi-trait multi-environment (MTME) genomic prediction models can leverage these datasets by exploring the correlation between traits and Genotype-by-Environment (G×E) interaction. Herein, we assess predictive abilities of univariate and multivariate genomic prediction models in a maize breeding program. To this end, we used data from 415 maize hybrids evaluated in 4 years of second season field trials for the traits grain yield, number of ears, and grain moisture. Genotypes of these hybrids were inferred in silico based on their parental inbred lines using single nucleotide polymorphisms (SNPs) markers obtained via genotyping-by-sequencing (GBS). Because genotypic information was available for only 257 hybrids, we used the genomic and pedigree relationship matrices to obtain the H matrix for all 415 hybrids. Our results demonstrated that in the single-environment context the use of multi-trait models was always superior in comparison to their univariate counterparts. Besides that, although MTME models were not particularly successful in predicting hybrid performance in untested years, they improved the ability to predict the performance of hybrids that had not been evaluated in any environment. However, the computational requirements of this kind of model could represent a limitation to its practical implementation and further investigation is necessary.
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Affiliation(s)
- Amanda Avelar de Oliveira
- Department of Genetics, "Luiz de Queiroz" College of Agriculture, University of Sao Paulo, Piracicaba, SP, 13418-900, Brazil.,Horticultural Sciences Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, 32611, USA
| | - Marcio F R Resende
- Horticultural Sciences Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, 32611, USA
| | - Luís Felipe Ventorim Ferrão
- Horticultural Sciences Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, 32611, USA
| | - Rodrigo Rampazo Amadeu
- Horticultural Sciences Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, 32611, USA
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10
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Zhang Y, Nyong'A TM, Shi T, Yang P. The complexity of alternative splicing and landscape of tissue-specific expression in lotus (Nelumbo nucifera) unveiled by Illumina- and single-molecule real-time-based RNA-sequencing. DNA Res 2020; 26:301-311. [PMID: 31173073 PMCID: PMC6704400 DOI: 10.1093/dnares/dsz010] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 05/03/2019] [Indexed: 12/16/2022] Open
Abstract
Alternative splicing (AS) plays a critical role in regulating different physiological and developmental processes in eukaryotes, by dramatically increasing the diversity of the transcriptome and the proteome. However, the saturation and complexity of AS remain unclear in lotus due to its limitation of rare obtainment of full-length multiple-splice isoforms. In this study, we apply a hybrid assembly strategy by combining single-molecule real-time sequencing and Illumina RNA-seq to get a comprehensive insight into the lotus transcriptomic landscape. We identified 211,802 high-quality full-length non-chimeric reads, with 192,690 non-redundant isoforms, and updated the lotus reference gene model. Moreover, our analysis identified a total of 104,288 AS events from 16,543 genes, with alternative 3ʹ splice-site being the predominant model, following by intron retention. By exploring tissue datasets, 370 tissue-specific AS events were identified among 12 tissues. Both the tissue-specific genes and isoforms might play important roles in tissue or organ development, and are suitable for ‘ABCE’ model partly in floral tissues. A large number of AS events and isoform variants identified in our study enhance the understanding of transcriptional diversity in lotus, and provide valuable resource for further functional genomic studies.
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Affiliation(s)
- Yue Zhang
- CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, CN, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Tonny Maraga Nyong'A
- CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, CN, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Tao Shi
- CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, CN, China
| | - Pingfang Yang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China
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11
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Shamimuzzaman M, Gardiner JM, Walsh AT, Triant DA, Le Tourneau JJ, Tayal A, Unni DR, Nguyen HN, Portwood JL, Cannon EKS, Andorf CM, Elsik CG. MaizeMine: A Data Mining Warehouse for the Maize Genetics and Genomics Database. FRONTIERS IN PLANT SCIENCE 2020; 11:592730. [PMID: 33193550 PMCID: PMC7642280 DOI: 10.3389/fpls.2020.592730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 10/01/2020] [Indexed: 05/11/2023]
Abstract
MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.
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Affiliation(s)
- Md Shamimuzzaman
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Jack M. Gardiner
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Amy T. Walsh
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Deborah A. Triant
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | | | - Aditi Tayal
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Deepak R. Unni
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Hung N. Nguyen
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - John L. Portwood
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA, United States
| | - Ethalinda K. S. Cannon
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA, United States
| | - Carson M. Andorf
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA, United States
| | - Christine G. Elsik
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
- Division of Plant Sciences, University of Missouri, Columbia, MO, United States
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, MO, United States
- *Correspondence: Christine G. Elsik,
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12
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Tello-Ruiz MK, Marco CF, Hsu FM, Khangura RS, Qiao P, Sapkota S, Stitzer MC, Wasikowski R, Wu H, Zhan J, Chougule K, Barone LC, Ghiban C, Muna D, Olson AC, Wang L, Ware D, Micklos DA. Double triage to identify poorly annotated genes in maize: The missing link in community curation. PLoS One 2019; 14:e0224086. [PMID: 31658277 PMCID: PMC6816542 DOI: 10.1371/journal.pone.0224086] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 10/05/2019] [Indexed: 02/02/2023] Open
Abstract
The sophistication of gene prediction algorithms and the abundance of RNA-based evidence for the maize genome may suggest that manual curation of gene models is no longer necessary. However, quality metrics generated by the MAKER-P gene annotation pipeline identified 17,225 of 130,330 (13%) protein-coding transcripts in the B73 Reference Genome V4 gene set with models of low concordance to available biological evidence. Working with eight graduate students, we used the Apollo annotation editor to curate 86 transcript models flagged by quality metrics and a complimentary method using the Gramene gene tree visualizer. All of the triaged models had significant errors-including missing or extra exons, non-canonical splice sites, and incorrect UTRs. A correct transcript model existed for about 60% of genes (or transcripts) flagged by quality metrics; we attribute this to the convention of elevating the transcript with the longest coding sequence (CDS) to the canonical, or first, position. The remaining 40% of flagged genes resulted in novel annotations and represent a manual curation space of about 10% of the maize genome (~4,000 protein-coding genes). MAKER-P metrics have a specificity of 100%, and a sensitivity of 85%; the gene tree visualizer has a specificity of 100%. Together with the Apollo graphical editor, our double triage provides an infrastructure to support the community curation of eukaryotic genomes by scientists, students, and potentially even citizen scientists.
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Affiliation(s)
- Marcela K Tello-Ruiz
- Plant Biology Program, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
- Department of Biological Sciences, State University of New York at Old Westbury, Old Westbury, New York, United States of America
| | - Cristina F Marco
- DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Fei-Man Hsu
- Graduate School of Frontier Sciences, University of Tokyo, Chiba, Japan
| | - Rajdeep S Khangura
- Department of Biochemistry, Purdue University, West Lafayette, Indiana, United States of America
| | - Pengfei Qiao
- Plant Biology Section, School of Integrative Plant Sciences, Cornell University, Ithaca, New York, United States of America
| | - Sirjan Sapkota
- Department of Plant and Environmental Sciences, Clemson University, Clemson, South Carolina, United States of America
| | - Michelle C Stitzer
- Department of Plant Sciences and Center for Population Biology, University of California Davis, Davis, California, United States of America
| | - Rachael Wasikowski
- Department of Biological Sciences, University of Toledo, Toledo, Ohio, United States of America
| | - Hao Wu
- Genetics, Development & Cell Biology Department, Iowa State University, Ames, Iowa, United States of America
| | - Junpeng Zhan
- School of Plant Sciences, University of Arizona, Tucson, Arizona, United States of America
- Donald Danforth Plant Science Center, St. Louis, Missouri, United States of America
| | - Kapeel Chougule
- Plant Biology Program, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Lindsay C Barone
- DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Cornel Ghiban
- DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Demitri Muna
- Plant Biology Program, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Andrew C Olson
- Plant Biology Program, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Liya Wang
- Plant Biology Program, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Doreen Ware
- Plant Biology Program, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
- USDA, Agricultural Research Service, Washington, D.C., United States of America
| | - David A Micklos
- DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
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13
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Evolutionary characteristics of intergenic transcribed regions indicate rare novel genes and widespread noisy transcription in the Poaceae. Sci Rep 2019; 9:12122. [PMID: 31431676 PMCID: PMC6702216 DOI: 10.1038/s41598-019-47797-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Accepted: 07/19/2019] [Indexed: 01/19/2023] Open
Abstract
Extensive transcriptional activity occurring in intergenic regions of genomes has raised the question whether intergenic transcription represents the activity of novel genes or noisy expression. To address this, we evaluated cross-species and post-duplication sequence and expression conservation of intergenic transcribed regions (ITRs) in four Poaceae species. Among 43,301 ITRs across the four species, 34,460 (80%) are species-specific. ITRs found across species tend to be more divergent in expression and have more recent duplicates compared to annotated genes. To assess if ITRs are functional (under selection), machine learning models were established in Oryza sativa (rice) that could accurately distinguish between phenotype genes and pseudogenes (area under curve-receiver operating characteristic = 0.94). Based on the models, 584 (8%) and 4391 (61%) rice ITRs are classified as likely functional and nonfunctional with high confidence, respectively. ITRs with conserved expression and ancient retained duplicates, features that were not part of the model, are frequently classified as likely-functional, suggesting these characteristics could serve as pragmatic rules of thumb for identifying candidate sequences likely to be under selection. This study also provides a framework to identify novel genes using comparative transcriptomic data to improve genome annotation that is fundamental for connecting genotype to phenotype in crop and model systems.
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14
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Colle M, Leisner CP, Wai CM, Ou S, Bird KA, Wang J, Wisecaver JH, Yocca AE, Alger EI, Tang H, Xiong Z, Callow P, Ben-Zvi G, Brodt A, Baruch K, Swale T, Shiue L, Song GQ, Childs KL, Schilmiller A, Vorsa N, Buell CR, VanBuren R, Jiang N, Edger PP. Haplotype-phased genome and evolution of phytonutrient pathways of tetraploid blueberry. Gigascience 2019; 8:giz012. [PMID: 30715294 PMCID: PMC6423372 DOI: 10.1093/gigascience/giz012] [Citation(s) in RCA: 129] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Revised: 12/18/2018] [Accepted: 01/18/2019] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Highbush blueberry (Vaccinium corymbosum) has long been consumed for its unique flavor and composition of health-promoting phytonutrients. However, breeding efforts to improve fruit quality in blueberry have been greatly hampered by the lack of adequate genomic resources and a limited understanding of the underlying genetics encoding key traits. The genome of highbush blueberry has been particularly challenging to assemble due, in large part, to its polyploid nature and genome size. FINDINGS Here, we present a chromosome-scale and haplotype-phased genome assembly of the cultivar "Draper," which has the highest antioxidant levels among a diversity panel of 71 cultivars and 13 wild Vaccinium species. We leveraged this genome, combined with gene expression and metabolite data measured across fruit development, to identify candidate genes involved in the biosynthesis of important phytonutrients among other metabolites associated with superior fruit quality. Genome-wide analyses revealed that both polyploidy and tandem gene duplications modified various pathways involved in the biosynthesis of key phytonutrients. Furthermore, gene expression analyses hint at the presence of a spatial-temporal specific dominantly expressed subgenome including during fruit development. CONCLUSIONS These findings and the reference genome will serve as a valuable resource to guide future genome-enabled breeding of important agronomic traits in highbush blueberry.
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Affiliation(s)
- Marivi Colle
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
- MSU AgBioResearch, Michigan State University, 446 West Circle Drive, East Lansing, MI, 48824, USA
| | - Courtney P Leisner
- Department of Plant Biology, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824 USA
| | - Ching Man Wai
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
| | - Shujun Ou
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
- Ecology, Evolutionary Biology and Behavior, Michigan State University, 293 Farm Lane, East Lansing, MI, 48824, USA
| | - Kevin A Bird
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
- Ecology, Evolutionary Biology and Behavior, Michigan State University, 293 Farm Lane, East Lansing, MI, 48824, USA
| | - Jie Wang
- Department of Plant Biology, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824 USA
- Center for Genomics Enabled Plant Science, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824, USA
| | - Jennifer H Wisecaver
- Department of Biochemistry, Purdue University, 175 South University Street, West Lafayette, IN, 47907, USA
- Purdue Center for Plant Biology, Purdue University, 610 Purdue Mall, West Lafayette, IN, 47907, USA
| | - Alan E Yocca
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
- Department of Plant Biology, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824 USA
| | - Elizabeth I Alger
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
| | - Haibao Tang
- Human Longevity Inc., 4570 Executive Drive, San Diego, CA 92121, USA
| | - Zhiyong Xiong
- Key Laboratory of Herbage and Endemic Crop Biotechnology, School of Life Sciences, Inner Mongolia University, 221 Aimin Road, Hohhot, 010070, China
| | - Pete Callow
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
| | - Gil Ben-Zvi
- NRGene, 5 Golda Meir Street, Ness Ziona, 7403648, Israel
| | - Avital Brodt
- NRGene, 5 Golda Meir Street, Ness Ziona, 7403648, Israel
| | - Kobi Baruch
- NRGene, 5 Golda Meir Street, Ness Ziona, 7403648, Israel
| | - Thomas Swale
- Dovetail Genomics, 100 Enterprise Way, Scotts Valley, CA, 95066, USA
| | - Lily Shiue
- Dovetail Genomics, 100 Enterprise Way, Scotts Valley, CA, 95066, USA
| | - Guo-qing Song
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
| | - Kevin L Childs
- Department of Plant Biology, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824 USA
- Center for Genomics Enabled Plant Science, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824, USA
| | - Anthony Schilmiller
- Mass Spectrometry & Metabolomics Core Facility, Michigan State University, 603 Wilson Road, East Lansing, MI, 48824, USA
| | - Nicholi Vorsa
- Department of Plant Biology, Rutgers University, 59 Dudley Road, New Brunswick, NJ, 08901, USA
- Philip E. Marucci Center for Blueberry and Cranberry Research and Extension, Rutgers University, 125A Lake Oswego Road, Chatsworth, NJ, 08019, USA
| | - C Robin Buell
- MSU AgBioResearch, Michigan State University, 446 West Circle Drive, East Lansing, MI, 48824, USA
- Department of Plant Biology, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824 USA
- Plant Resilience Institute, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824 USA
| | - Robert VanBuren
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
- Plant Resilience Institute, Michigan State University, 612 Wilson Road, East Lansing, MI, 48824 USA
| | - Ning Jiang
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
- Ecology, Evolutionary Biology and Behavior, Michigan State University, 293 Farm Lane, East Lansing, MI, 48824, USA
| | - Patrick P Edger
- Department of Horticulture, Michigan State University, 1066 Bogue Street, East Lansing, MI, 48824, USA
- MSU AgBioResearch, Michigan State University, 446 West Circle Drive, East Lansing, MI, 48824, USA
- Ecology, Evolutionary Biology and Behavior, Michigan State University, 293 Farm Lane, East Lansing, MI, 48824, USA
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15
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Rife TW, Graybosch RA, Poland JA. Genomic Analysis and Prediction within a US Public Collaborative Winter Wheat Regional Testing Nursery. THE PLANT GENOME 2018; 11:180012. [PMID: 30512033 DOI: 10.3835/plantgenome2018.02.0012] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
The development of inexpensive, whole-genome profiling enables a transition to allele-based breeding using genomic prediction models. These models consider alleles shared between lines to predict phenotypes and select new lines based on estimated breeding values. This approach can leverage highly unbalanced datasets that are common to breeding programs. The Southern Regional Performance Nursery (SRPN) is a public nursery established by the USDA-ARS in 1931 to characterize performance and quality of near-release wheat ( L.) varieties from breeding programs in the US Central Plains. New entries are submitted annually and can be re-entered only once. The trial is grown at >30 locations each year and lines are evaluated for grain yield, disease resistance, and agronomic traits. Overall genetic gain is measured across years by including common check cultivars for comparison. We have generated whole-genome profiles via genotyping-by-sequencing (GBS) for 939 SPRN entries dating back to 1992 to explore the potential use of the nursery as a genomic selection (GS) training population (TP). The GS prediction models across years (average = 0.33) outperformed year-to-year phenotypic correlation for yield ( = 0.27) for a majority of the years evaluated, suggesting that genomic selection has the potential to outperform low heritability selection on yield in these highly variable environments. We also examined the predictability of programs using both program-specific and whole-set TPs. Generally, the predictability of a program was similar with both approaches. These results suggest that wheat breeding programs can collaboratively leverage the immense datasets that are generated from regional testing networks.
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16
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Extensive intraspecific gene order and gene structural variations between Mo17 and other maize genomes. Nat Genet 2018; 50:1289-1295. [PMID: 30061735 DOI: 10.1038/s41588-018-0182-0] [Citation(s) in RCA: 237] [Impact Index Per Article: 33.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2017] [Accepted: 06/05/2018] [Indexed: 12/24/2022]
Abstract
Maize is an important crop with a high level of genome diversity and heterosis. The genome sequence of a typical female line, B73, was previously released. Here, we report a de novo genome assembly of a corresponding male representative line, Mo17. More than 96.4% of the 2,183 Mb assembled genome can be accounted for by 362 scaffolds in ten pseudochromosomes with 38,620 annotated protein-coding genes. Comparative analysis revealed large gene-order and gene structural variations: approximately 10% of the annotated genes were mutually nonsyntenic, and more than 20% of the predicted genes had either large-effect mutations or large structural variations, which might cause considerable protein divergence between the two inbred lines. Our study provides a high-quality reference-genome sequence of an important maize germplasm, and the intraspecific gene order and gene structural variations identified should have implications for heterosis and genome evolution.
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17
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The maize W22 genome provides a foundation for functional genomics and transposon biology. Nat Genet 2018; 50:1282-1288. [PMID: 30061736 DOI: 10.1038/s41588-018-0158-0] [Citation(s) in RCA: 124] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 05/17/2018] [Indexed: 11/08/2022]
Abstract
The maize W22 inbred has served as a platform for maize genetics since the mid twentieth century. To streamline maize genome analyses, we have sequenced and de novo assembled a W22 reference genome using short-read sequencing technologies. We show that significant structural heterogeneity exists in comparison to the B73 reference genome at multiple scales, from transposon composition and copy number variation to single-nucleotide polymorphisms. The generation of this reference genome enables accurate placement of thousands of Mutator (Mu) and Dissociation (Ds) transposable element insertions for reverse and forward genetics studies. Annotation of the genome has been achieved using RNA-seq analysis, differential nuclease sensitivity profiling and bisulfite sequencing to map open reading frames, open chromatin sites and DNA methylation profiles, respectively. Collectively, the resources developed here integrate W22 as a community reference genome for functional genomics and provide a foundation for the maize pan-genome.
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18
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An improved assembly and annotation of the melon (Cucumis melo L.) reference genome. Sci Rep 2018; 8:8088. [PMID: 29795526 PMCID: PMC5967340 DOI: 10.1038/s41598-018-26416-2] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Accepted: 05/09/2018] [Indexed: 12/20/2022] Open
Abstract
We report an improved assembly (v3.6.1) of the melon (Cucumis melo L.) genome and a new genome annotation (v4.0). The optical mapping approach allowed correcting the order and the orientation of 21 previous scaffolds and permitted to correctly define the gap-size extension along the 12 pseudomolecules. A new comprehensive annotation was also built in order to update the previous annotation v3.5.1, released more than six years ago. Using an integrative annotation pipeline, based on exhaustive RNA-Seq collections and ad-hoc transposable element annotation, we identified 29,980 protein-coding loci. Compared to the previous version, the v4.0 annotation improved gene models in terms of completeness of gene structure, UTR regions definition, intron-exon junctions and reduction of fragmented genes. More than 8,000 new genes were identified, one third of them being well supported by RNA-Seq data. To make all the new resources easily exploitable and completely available for the scientific community, a redesigned Melonomics genomic platform was released at http://melonomics.net. The resources produced in this work considerably increase the reliability of the melon genome assembly and resolution of the gene models paving the way for further studies in melon and related species.
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19
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Funk A, Galewski P, McGrath JM. Nucleotide-binding resistance gene signatures in sugar beet, insights from a new reference genome. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 95:659-671. [PMID: 29797366 DOI: 10.1111/tpj.13977] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 04/19/2018] [Accepted: 05/04/2018] [Indexed: 05/28/2023]
Abstract
Nucleotide-binding (NB-ARC), leucine-rich-repeat genes (NLRs) account for 60.8% of resistance (R) genes molecularly characterized from plants. NLRs exist as large gene families prone to tandem duplication and transposition, with high sequence diversity among crops and their wild relatives. This diversity can be a source of new disease resistance, but difficulty in distinguishing specific sequences from homologous gene family members hinders characterization of resistance for improving crop varieties. Current genome sequencing and assembly technologies, especially those using long-read sequencing, are improving resolution of repeat-rich genomic regions and clarifying locations of duplicated genes, such as NLRs. Using the conserved NB-ARC domain as a model, 231 tentative NB-ARC loci were identified in a highly contiguous genome assembly of sugar beet, revealing diverged and truncated NB-ARC signatures as well as full-length sequences. The NB-ARC-associated proteins contained NLR resistance gene domains, including TIR, CC and LRR, as well as other integrated domains. Phylogenetic relationships of partial and complete domains were determined, and patterns of physical clustering in the genome were evaluated. Comparison of sugar beet NB-ARC domains to validated R-genes from monocots and eudicots suggested extensive Beta vulgaris-specific subfamily expansions. The NLR landscape in the rhizomania resistance conferring Rz region of Chromosome 3 was characterized, identifying 26 NLR-like sequences spanning 20 MB. This work presents the first detailed view of NLR family composition in a member of the Caryophyllales, builds a foundation for additional disease resistance work in B. vulgaris, and demonstrates an additional nucleic-acid-based method for NLR prediction in non-model plant species.
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Affiliation(s)
- Andrew Funk
- Department of Plant, Soil, and Microbial Science, Plant Breeding, Genetics, and Biotechnology Program, Michigan State University, East Lansing, MI, 48824, USA
| | - Paul Galewski
- Department of Plant, Soil, and Microbial Science, Plant Breeding, Genetics, and Biotechnology Program, Michigan State University, East Lansing, MI, 48824, USA
| | - J Mitchell McGrath
- USDA-ARS, Sugarbeet and Bean Research Unit, 1066 Bogue Street, 494 PSSB, East Lansing, MI, 48824, USA
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20
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Yao L, Wang J, Li B, Meng Y, Ma X, Si E, Ren P, Yang K, Shang X, Wang H. Transcriptome sequencing and comparative analysis of differentially-expressed isoforms in the roots of Halogeton glomeratus under salt stress. Gene 2017; 646:159-168. [PMID: 29292193 DOI: 10.1016/j.gene.2017.12.058] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 12/06/2017] [Accepted: 12/28/2017] [Indexed: 11/19/2022]
Abstract
Although Halogeton glomeratus (H. glomeratus) has been confirmed to have a unique mechanism to regulate Na+ efflux from the cytoplasm and compartmentalize Na+ into leaf vacuoles, little is known about the salt tolerance mechanisms of roots under salinity stress. In the present study, transcripts were sequenced using the BGISEQ-500 sequencing platform (BGI, Wuhan, China). After quality control, approximately 24.08 million clean reads were obtained and the average mapping ratio to the reference gene was 70.00%. When comparing salt-treated samples with the control, a total of 550, 590, 1411 and 2063 DEIs were identified at 2, 6, 24 and 72h, respectively. Numerous differentially-expressed isoforms that play important roles in response and adaptation to salt condition are related to metabolic processes, cellular processes, single-organism processes, localization, biological regulation, responses to stimulus, binding, catalytic activity and transporter activity. Fifty-eight salt-induced isoforms were common to different stages of salt stress; most of these DEIs were related to signal transduction and transporters, which maybe the core isoforms regulating Na+ uptake and transport in the roots of H. glomeratus. The expression patterns of 18 DEIs that were detected by quantitative real-time polymerase chain reaction were consistent with their respective changes in transcript abundance as identified by RNA-Seq technology. The present study thoroughly explored potential isoforms involved in salt tolerance on H. glomeratus roots at five time points. Our results may serve as an important resource for the H. glomeratus research community, improving our understanding of salt tolerance in halophyte survival under high salinity stress.
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Affiliation(s)
- Lirong Yao
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Juncheng Wang
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Baochun Li
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; Department of Botany, College of Life Sciences and Technology, Gansu Agricultural University, Lanzhou, China
| | - Yaxiong Meng
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Xiaole Ma
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Erjing Si
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Panrong Ren
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Ke Yang
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Xunwu Shang
- College of Agronomy, Gansu Agricultural University, Lanzhou, China
| | - Huajun Wang
- Gansu Provincial Key Lab of Aridland Crop Science/Gansu Key Lab of Crop Improvement and Germplasm Enhancement, Lanzhou, China; College of Agronomy, Gansu Agricultural University, Lanzhou, China.
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21
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Zhao G, Zou C, Li K, Wang K, Li T, Gao L, Zhang X, Wang H, Yang Z, Liu X, Jiang W, Mao L, Kong X, Jiao Y, Jia J. The Aegilops tauschii genome reveals multiple impacts of transposons. NATURE PLANTS 2017; 3:946-955. [PMID: 29158546 DOI: 10.1038/s41477-017-0067-8] [Citation(s) in RCA: 125] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Accepted: 10/30/2017] [Indexed: 05/19/2023]
Abstract
Wheat is an important global crop with an extremely large and complex genome that contains more transposable elements (TEs) than any other known crop species. Here, we generated a chromosome-scale, high-quality reference genome of Aegilops tauschii, the donor of the wheat D genome, in which 92.5% sequences have been anchored to chromosomes. Using this assembly, we accurately characterized genic loci, gene expression, pseudogenes, methylation, recombination ratios, microRNAs and especially TEs on chromosomes. In addition to the discovery of a wave of very recent gene duplications, we detected that TEs occurred in about half of the genes, and found that such genes are expressed at lower levels than those without TEs, presumably because of their elevated methylation levels. We mapped all wheat molecular markers and constructed a high-resolution integrated genetic map corresponding to genome sequences, thereby placing previously detected agronomically important genes/quantitative trait loci (QTLs) on the Ae. tauschii genome for the first time.
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Affiliation(s)
- Guangyao Zhao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 100081, Beijing, China
| | - Cheng Zou
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 100081, Beijing, China
| | - Kui Li
- Novogene Bioinformatics Institute, 100083, Beijing, China
| | - Kai Wang
- Novogene Bioinformatics Institute, 100083, Beijing, China
| | - Tianbao Li
- Agronomy College, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, 450002, Zhengzhou, China
| | - Lifeng Gao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 100081, Beijing, China
| | - Xiaoxia Zhang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, 100093, Beijing, China
| | - Hongjin Wang
- Center for Information in Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, 610054, Chengdu, China
| | - Zujun Yang
- Center for Information in Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, 610054, Chengdu, China
| | - Xu Liu
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 100081, Beijing, China
| | - Wenkai Jiang
- Novogene Bioinformatics Institute, 100083, Beijing, China.
| | - Long Mao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 100081, Beijing, China.
| | - Xiuying Kong
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 100081, Beijing, China.
| | - Yuannian Jiao
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, the Chinese Academy of Sciences, 100093, Beijing, China.
| | - Jizeng Jia
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 100081, Beijing, China.
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22
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Bowman MJ, Pulman JA, Liu TL, Childs KL. A modified GC-specific MAKER gene annotation method reveals improved and novel gene predictions of high and low GC content in Oryza sativa. BMC Bioinformatics 2017; 18:522. [PMID: 29178822 PMCID: PMC5702205 DOI: 10.1186/s12859-017-1942-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2017] [Accepted: 11/15/2017] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Accurate structural annotation depends on well-trained gene prediction programs. Training data for gene prediction programs are often chosen randomly from a subset of high-quality genes that ideally represent the variation found within a genome. One aspect of gene variation is GC content, which differs across species and is bimodal in grass genomes. When gene prediction programs are trained on a subset of grass genes with random GC content, they are effectively being trained on two classes of genes at once, and this can be expected to result in poor results when genes are predicted in new genome sequences. RESULTS We find that gene prediction programs trained on grass genes with random GC content do not completely predict all grass genes with extreme GC content. We show that gene prediction programs that are trained with grass genes with high or low GC content can make both better and unique gene predictions compared to gene prediction programs that are trained on genes with random GC content. By separately training gene prediction programs with genes from multiple GC ranges and using the programs within the MAKER genome annotation pipeline, we were able to improve the annotation of the Oryza sativa genome compared to using the standard MAKER annotation protocol. Gene structure was improved in over 13% of genes, and 651 novel genes were predicted by the GC-specific MAKER protocol. CONCLUSIONS We present a new GC-specific MAKER annotation protocol to predict new and improved gene models and assess the biological significance of this method in Oryza sativa. We expect that this protocol will also be beneficial for gene prediction in any organism with bimodal or other unusual gene GC content.
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Affiliation(s)
- Megan J Bowman
- Department of Plant Biology, Michigan State University, 612 Wilson Rd, Room 166, East Lansing, MI, 48824, USA.,Van Andel Research Institute, Grand Rapids, MI, 49506, USA
| | - Jane A Pulman
- Department of Plant Biology, Michigan State University, 612 Wilson Rd, Room 166, East Lansing, MI, 48824, USA.,Center for Genomics Enabled Plant Science, Michigan State University, East Lansing, MI, 48824, USA.,Centre for Genomics Research, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Tiffany L Liu
- Department of Plant Biology, Michigan State University, 612 Wilson Rd, Room 166, East Lansing, MI, 48824, USA
| | - Kevin L Childs
- Department of Plant Biology, Michigan State University, 612 Wilson Rd, Room 166, East Lansing, MI, 48824, USA. .,Center for Genomics Enabled Plant Science, Michigan State University, East Lansing, MI, 48824, USA.
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23
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Triska M, Solovyev V, Baranova A, Kel A, Tatarinova TV. Nucleotide patterns aiding in prediction of eukaryotic promoters. PLoS One 2017; 12:e0187243. [PMID: 29141011 PMCID: PMC5687710 DOI: 10.1371/journal.pone.0187243] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2017] [Accepted: 09/05/2017] [Indexed: 01/09/2023] Open
Abstract
Computational analysis of promoters is hindered by the complexity of their architecture. In less studied genomes with complex organization, false positive promoter predictions are common. Accurate identification of transcription start sites and core promoter regions remains an unsolved problem. In this paper, we present a comprehensive analysis of genomic features associated with promoters and show that probabilistic integrative algorithms-driven models allow accurate classification of DNA sequence into “promoters” and “non-promoters” even in absence of the full-length cDNA sequences. These models may be built upon the maps of the distributions of sequence polymorphisms, RNA sequencing reads on genomic DNA, methylated nucleotides, transcription factor binding sites, as well as relative frequencies of nucleotides and their combinations. Positional clustering of binding sites shows that the cells of Oryza sativa utilize three distinct classes of transcription factors: those that bind preferentially to the [-500,0] region (188 “promoter-specific” transcription factors), those that bind preferentially to the [0,500] region (282 “5′ UTR-specific” TFs), and 207 of the “promiscuous” transcription factors with little or no location preference with respect to TSS. For the most informative motifs, their positional preferences are conserved between dicots and monocots.
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Affiliation(s)
- Martin Triska
- Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA, United States of America
- Faculty of Advanced Technology, University of South Wales, Pontypridd, Wales, United Kingdom
| | | | - Ancha Baranova
- School of Systems Biology, George Mason University, Fairfax, VA, United States of America
- Research Centre for Medical Genetics, Moscow, Russia
| | - Alexander Kel
- geneXplain GmbH, Wolfenbuettel, Germany
- Institute of Chemical Biology and Fundamental Medicine, Novosibirsk, Russia
| | - Tatiana V. Tatarinova
- School of Systems Biology, George Mason University, Fairfax, VA, United States of America
- Department of Biology, Division of Natural Sciences, University of La Verne, La Verne, CA, United States of America
- Bioinformatics Center, AA Kharkevich Institute for Information Transmission Problems RAS, Moscow, Russia
- Vavilov’s Institute for General Genetics, Moscow, Russia, Moscow, Russia
- * E-mail:
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24
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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: 0.6] [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.
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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
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25
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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: 732] [Impact Index Per Article: 91.5] [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.
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26
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Daron J, Slotkin RK. EpiTEome: Simultaneous detection of transposable element insertion sites and their DNA methylation levels. Genome Biol 2017; 18:91. [PMID: 28499400 PMCID: PMC5429532 DOI: 10.1186/s13059-017-1232-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Accepted: 05/05/2017] [Indexed: 11/15/2022] Open
Abstract
The genome-wide investigation of DNA methylation levels has been limited to reference transposable element positions. The methylation analysis of non-reference and mobile transposable elements has only recently been performed, but required both genome resequencing and MethylC-seq datasets. We have created epiTEome, a program that detects both new transposable element insertion sites and their methylation states from a single MethylC-seq dataset. EpiTEome outperforms other split-read insertion site detection programs, even while functioning on bisulfite-converted reads. EpiTEome characterizes the previously discarded fraction of DNA methylation at sites of new insertions, enabling future investigation into the epigenetic regulation of non-reference and transposed elements.
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Affiliation(s)
- Josquin Daron
- Department of Molecular Genetics, The Ohio State University, Columbus, OH, USA
| | - R Keith Slotkin
- Department of Molecular Genetics, The Ohio State University, Columbus, OH, USA.
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27
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Chakraborty S, Martínez-García PJ, Dandekar AM. YeATSAM analysis of the walnut and chickpea transcriptome reveals key genes undetected by current annotation tools. F1000Res 2017; 5:2689. [PMID: 28105312 PMCID: PMC5200947 DOI: 10.12688/f1000research.10040.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/15/2016] [Indexed: 11/20/2022] Open
Abstract
Background: The transcriptome, a treasure trove of gene space information, remains severely under-used by current genome annotation methods.
Methods: Here, we present an annotation method in the YeATS suite (YeATSAM), based on information encoded by the transcriptome, that demonstrates artifacts of the assembler, which must be addressed to achieve proper annotation.
Results and Discussion: YeATSAM was applied to the transcriptome obtained from twenty walnut tissues and compared to MAKER-P annotation of the recently published walnut genome sequence (WGS). MAKER-P and YeATSAM both failed to annotate several hundred proteins found by the other. Although many of these unannotated proteins have repetitive sequences (possibly transposable elements), other crucial proteins were excluded by each method. An egg cell-secreted protein and a homer protein were undetected by YeATSAM, although these did not produce any transcripts. Importantly, MAKER-P failed to classify key photosynthesis-related proteins, which we show emanated from Trinity assembly artifacts potentially not handled by MAKER-P. Also, no proteins from the large berberine bridge enzyme (BBE) family were annotated by MAKER-P. BBE is implicated in biosynthesis of several alkaloids metabolites, like anti-microbial berberine. As further validation, YeATSAM identified ~1000 genes that are not annotated in the NCBI database by Gnomon. YeATSAM used a RNA-seq derived chickpea (
Cicer arietinum L.) transcriptome assembled using Newbler v2.3.
Conclusions: Since the current version of YeATSAM does not have an
ab initio module, we suggest a combined annotation scheme using both MAKER-P and YeATSAM to comprehensively and accurately annotate the WGS.
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28
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Lana UGDP, Prazeres de Souza IR, Noda RW, Pastina MM, Magalhaes JV, Guimaraes CT. Quantitative Trait Loci and Resistance Gene Analogs Associated with Maize White Spot Resistance. PLANT DISEASE 2017; 101:200-208. [PMID: 30682293 DOI: 10.1094/pdis-06-16-0899-re] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Maize white spot (MWS), caused by the bacterium Pantoea ananatis, is one of the most important maize foliar diseases in tropical and subtropical regions, causing significant yield losses. Despite its economic importance, genetic studies of MWS are scarce. The aim of this study was to map quantitative trait loci (QTL) associated with MWS resistance and to identify resistance gene analogs (RGA) underlying these QTL. QTL mapping was performed in a tropical maize F2:3 population, which was genotyped with simple-sequence repeat and RGA-tagged markers and phenotyped for the response to MWS in two Brazilian southeastern locations. Nine QTL explained approximately 70% of the phenotypic variance for MWS resistance at each location, with two of them consistently detected in both environments. Data mining using 112 resistance genes cloned from different plant species revealed 1,697 RGA distributed in clusters within the maize genome. The RGA Pto19, Pto20, Pto99, and Xa26.151.4 were genetically mapped within MWS resistance QTL on chromosomes 4 and 8 and were preferentially expressed in the resistant parental line at locations where their respective QTL occurred. The consistency of QTL mapping, in silico prediction, and gene expression analyses revealed RGA and genomic regions suitable for marker-assisted selection to improve MWS resistance.
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29
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van Dijk ADJ. Species-Specific Genome Sequence Databases: A Practical Review. Methods Mol Biol 2016; 1533:173-181. [PMID: 27987170 DOI: 10.1007/978-1-4939-6658-5_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/15/2023]
Abstract
This chapter presents a use case illustrating the search for homologues of a known protein in species-specific genome sequence databases. The results from different species-specific resources are compared to each other and to results obtained from a more general genome sequence database (Phytozome). Various options and settings relevant when searching these databases are discussed. For example, it is shown how the choice of reference sequence set in a given database influences the results one obtains. The provided examples illustrate some problems and pitfalls related to interpreting results obtained from species-specific genome sequence databases.
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Affiliation(s)
- A D J van Dijk
- Applied Bioinformatics, Plant Sciences Group, Wageningen University & Research Centre (WUR), Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.
- Laboratory of Bioinformatics, Plant Sciences Group, Wageningen University & Research Centre (WUR), Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.
- Biometris, Plant Sciences Group, Wageningen University & Research Centre (WUR), Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.
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30
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Hirsch CN, Hirsch CD, Brohammer AB, Bowman MJ, Soifer I, Barad O, Shem-Tov D, Baruch K, Lu F, Hernandez AG, Fields CJ, Wright CL, Koehler K, Springer NM, Buckler E, Buell CR, de Leon N, Kaeppler SM, Childs KL, Mikel MA. Draft Assembly of Elite Inbred Line PH207 Provides Insights into Genomic and Transcriptome Diversity in Maize. THE PLANT CELL 2016; 28:2700-2714. [PMID: 27803309 PMCID: PMC5155341 DOI: 10.1105/tpc.16.00353] [Citation(s) in RCA: 121] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Revised: 10/19/2016] [Accepted: 10/31/2016] [Indexed: 05/18/2023]
Abstract
Intense artificial selection over the last 100 years has produced elite maize (Zea mays) inbred lines that combine to produce high-yielding hybrids. To further our understanding of how genome and transcriptome variation contribute to the production of high-yielding hybrids, we generated a draft genome assembly of the inbred line PH207 to complement and compare with the existing B73 reference sequence. B73 is a founder of the Stiff Stalk germplasm pool, while PH207 is a founder of Iodent germplasm, both of which have contributed substantially to the production of temperate commercial maize and are combined to make heterotic hybrids. Comparison of these two assemblies revealed over 2500 genes present in only one of the two genotypes and 136 gene families that have undergone extensive expansion or contraction. Transcriptome profiling revealed extensive expression variation, with as many as 10,564 differentially expressed transcripts and 7128 transcripts expressed in only one of the two genotypes in a single tissue. Genotype-specific genes were more likely to have tissue/condition-specific expression and lower transcript abundance. The availability of a high-quality genome assembly for the elite maize inbred PH207 expands our knowledge of the breadth of natural genome and transcriptome variation in elite maize inbred lines across heterotic pools.
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Affiliation(s)
- Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108
| | - Cory D Hirsch
- Department of Plant Pathology, University of Minnesota, St. Paul, Minnesota 55108
| | - Alex B Brohammer
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108
| | - Megan J Bowman
- Department of Plant Biology, Michigan State University, East Lansing, Michigan 48824
| | - Ilya Soifer
- Calico Labs, San Francisco, California 94080
| | | | | | | | - Fei Lu
- Instiute for Genome Diversity, Cornell University, Ithaca, New York 14850
| | - Alvaro G Hernandez
- Roy J. Carver Biotechnology Center, University of Illinois, Urbana, Illinois 61801
| | - Christopher J Fields
- Roy J. Carver Biotechnology Center, University of Illinois, Urbana, Illinois 61801
| | - Chris L Wright
- Roy J. Carver Biotechnology Center, University of Illinois, Urbana, Illinois 61801
| | | | - Nathan M Springer
- Department of Plant Biology, University of Minnesota, St. Paul, Minnesota 55108
| | - Edward Buckler
- Instiute for Genome Diversity, Cornell University, Ithaca, New York 14850
- U.S. Department of Agriculture/Agricultural Research Services, Ithaca, New York 14850
| | - C Robin Buell
- Department of Plant Biology, Michigan State University, East Lansing, Michigan 48824
- DOE Great Lakes Bioenergy Research Center, East Lansing, Michigan 48824
| | - Natalia de Leon
- Department of Agronomy, University of Wisconsin-Madison, Madison, Wisconsin 53706
- DOE Great Lakes Bioenergy Research Center, Madison, Wisconsin 53706
| | - Shawn M Kaeppler
- Department of Agronomy, University of Wisconsin-Madison, Madison, Wisconsin 53706
- DOE Great Lakes Bioenergy Research Center, Madison, Wisconsin 53706
| | - Kevin L Childs
- Department of Plant Biology, Michigan State University, East Lansing, Michigan 48824
- Center for Genomics-Enabled Plant Sciences, Michigan State University, East Lansing, Michigan 48824
| | - Mark A Mikel
- Roy J. Carver Biotechnology Center, University of Illinois, Urbana, Illinois 61801
- Department of Crop Sciences, University of Illinois, Urbana, Illinois 61801
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31
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Panchy N, Lehti-Shiu M, Shiu SH. Evolution of Gene Duplication in Plants. PLANT PHYSIOLOGY 2016; 171:2294-316. [PMID: 27288366 PMCID: PMC4972278 DOI: 10.1104/pp.16.00523] [Citation(s) in RCA: 845] [Impact Index Per Article: 93.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2016] [Accepted: 05/17/2016] [Indexed: 05/18/2023]
Abstract
Ancient duplication events and a high rate of retention of extant pairs of duplicate genes have contributed to an abundance of duplicate genes in plant genomes. These duplicates have contributed to the evolution of novel functions, such as the production of floral structures, induction of disease resistance, and adaptation to stress. Additionally, recent whole-genome duplications that have occurred in the lineages of several domesticated crop species, including wheat (Triticum aestivum), cotton (Gossypium hirsutum), and soybean (Glycine max), have contributed to important agronomic traits, such as grain quality, fruit shape, and flowering time. Therefore, understanding the mechanisms and impacts of gene duplication will be important to future studies of plants in general and of agronomically important crops in particular. In this review, we survey the current knowledge about gene duplication, including gene duplication mechanisms, the potential fates of duplicate genes, models explaining duplicate gene retention, the properties that distinguish duplicate from singleton genes, and the evolutionary impact of gene duplication.
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Affiliation(s)
- Nicholas Panchy
- Genetics Program (N.P., S.-H.S.) and Department of Plant Biology (M.L.-S., S.-H.S.), Michigan State University, East Lansing, Michigan 48824
| | - Melissa Lehti-Shiu
- Genetics Program (N.P., S.-H.S.) and Department of Plant Biology (M.L.-S., S.-H.S.), Michigan State University, East Lansing, Michigan 48824
| | - Shin-Han Shiu
- Genetics Program (N.P., S.-H.S.) and Department of Plant Biology (M.L.-S., S.-H.S.), Michigan State University, East Lansing, Michigan 48824
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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: 36.1] [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.
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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
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Haberer G, Mayer KF, Spannagl M. The big five of the monocot genomes. CURRENT OPINION IN PLANT BIOLOGY 2016; 30:33-40. [PMID: 26866569 DOI: 10.1016/j.pbi.2016.01.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 01/14/2016] [Accepted: 01/21/2016] [Indexed: 06/05/2023]
Abstract
Monocots represent a monophyletic clade of the angiosperms that - based on fossil and molecular records - originated at around the Early Cretaceous from aquatic and wetland ancestors. Among their members are important crops including maize, wheat, rice, sorghum and barley, accounting for the major source for the daily calorie uptake by humans. Reflecting this importance, the partly large and complex genomes of these plants were major targets for ambitious and innovative sequencing projects, which will be discussed in this review article.
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Affiliation(s)
- Georg Haberer
- Plant Genome and Systems Biology/PGSB, Helmholtz Center Munich - German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Klaus Fx Mayer
- Plant Genome and Systems Biology/PGSB, Helmholtz Center Munich - German Research Center for Environmental Health, 85764 Neuherberg, Germany.
| | - Manuel Spannagl
- Plant Genome and Systems Biology/PGSB, Helmholtz Center Munich - German Research Center for Environmental Health, 85764 Neuherberg, Germany
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Wang R, Yang X, Wang N, Liu X, Nelson RS, Li W, Fan Z, Zhou T. An efficient virus-induced gene silencing vector for maize functional genomics research. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2016; 86:102-15. [PMID: 26921244 DOI: 10.1111/tpj.13142] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 02/01/2016] [Accepted: 02/08/2016] [Indexed: 05/02/2023]
Abstract
Maize is a major crop whose rich genetic diversity provides an advanced resource for genetic research. However, a tool for rapid transient gene function analysis in maize that may be utilized in most maize cultivars has been lacking, resulting in reliance on time-consuming stable transformation and mutation studies to obtain answers. We developed an efficient virus-induced gene silencing (VIGS) vector for maize based on a naturally maize-infecting cucumber mosaic virus (CMV) strain, ZMBJ-CMV. An infectious clone of ZMBJ-CMV was constructed, and a vascular puncture inoculation method utilizing Agrobacterium was optimized to improve its utility for CMV infection of maize. ZMBJ-CMV was then modified to function as a VIGS vector. The ZMBJ-CMV vector induced mild to moderate symptoms in many maize lines, making it useful for gene function studies in critically important maize cultivars, such as the sequenced reference inbred line B73. Using this CMV VIGS system, expression of two endogenous genes, ZmPDS and ZmIspH, was found to be decreased by 75% and 78%, respectively, compared with non-silenced tissue. Inserts with lengths of 100-300 bp produced the most complete transcriptional and visual silencing phenotypes. Moreover, genes related to autophagy, ZmATG3 and ZmATG8a, were also silenced, and it was found that they function in leaf starch degradation. These results indicate that our ZMBJ-CMV VIGS vector provides a tool for rapid and efficient gene function studies in maize.
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Affiliation(s)
- Rong Wang
- State Key Laboratory for Agro-Biotechnology and Department of Plant Pathology, China Agricultural University, Beijing, 100193, China
| | - Xinxin Yang
- State Key Laboratory for Agro-Biotechnology and Department of Plant Pathology, China Agricultural University, Beijing, 100193, China
| | - Nian Wang
- State Key Laboratory for Agro-Biotechnology and Department of Plant Pathology, China Agricultural University, Beijing, 100193, China
| | - Xuedong Liu
- State Key Laboratory for Agro-Biotechnology and Department of Plant Pathology, China Agricultural University, Beijing, 100193, China
| | - Richard S Nelson
- Plant Biology Division, The Samuel Roberts Noble Foundation Inc., 2510 Sam Noble Parkway, Ardmore, OK 73401, USA
| | - Weimin Li
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, 12 South Zhongguancun Street, Beijing, 100081, China
| | - Zaifeng Fan
- State Key Laboratory for Agro-Biotechnology and Department of Plant Pathology, China Agricultural University, Beijing, 100193, China
| | - Tao Zhou
- State Key Laboratory for Agro-Biotechnology and Department of Plant Pathology, China Agricultural University, Beijing, 100193, China
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Abstract
Maize has a long history of genetic and genomic tool development and is considered one of the most accessible higher plant systems. With a fully sequenced genome, a suite of cytogenetic tools, methods for both forward and reverse genetics, and characterized phenotype markers, maize is amenable to studying questions beyond plant biology. Major discoveries in the areas of transposons, imprinting, and chromosome biology came from work in maize. Moving forward in the post-genomic era, this classic model system will continue to be at the forefront of basic biological study. In this review, we outline the basics of working with maize and describe its rich genetic toolbox.
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Tang H, Bomhoff MD, Briones E, Zhang L, Schnable JC, Lyons E. SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand. Genome Biol Evol 2015; 7:3286-98. [PMID: 26560340 PMCID: PMC4700967 DOI: 10.1093/gbe/evv219] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The identification of conserved syntenic regions enables discovery of predicted
locations for orthologous and homeologous genes, even when no such gene is present.
This capability means that synteny-based methods are far more effective than sequence
similarity-based methods in identifying true-negatives, a necessity for studying gene
loss and gene transposition. However, the identification of syntenic regions requires
complex analyses which must be repeated for pairwise comparisons between any two
species. Therefore, as the number of published genomes increases, there is a growing
demand for scalable, simple-to-use applications to perform comparative genomic
analyses that cater to both gene family studies and genome-scale studies. We
implemented SynFind, a web-based tool that addresses this need. Given one query
genome, SynFind is capable of identifying conserved syntenic regions in any set of
target genomes. SynFind is capable of reporting per-gene information, useful for
researchers studying specific gene families, as well as genome-wide data sets of
syntenic gene and predicted gene locations, critical for researchers focused on
large-scale genomic analyses. Inference of syntenic homologs provides the basis for
correlation of functional changes around genes of interests between related
organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic
data from over 15,000 organisms from all domains of life as well as supporting
multiple releases of the same organism. SynFind makes use of a powerful job execution
framework that promises scalability and reproducibility. SynFind can be accessed at
http://genomevolution.org/CoGe/SynFind.pl. A video tutorial of SynFind
using Phytophthrora as an example is available at http://www.youtube.com/watch?v=2Agczny9Nyc.
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Affiliation(s)
- Haibao Tang
- Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China School of Plant Sciences, iPlant Collaborative, University of Arizona
| | - Matthew D Bomhoff
- School of Plant Sciences, iPlant Collaborative, University of Arizona
| | - Evan Briones
- School of Plant Sciences, iPlant Collaborative, University of Arizona
| | - Liangsheng Zhang
- Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China
| | - James C Schnable
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln
| | - Eric Lyons
- School of Plant Sciences, iPlant Collaborative, University of Arizona
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Tello-Ruiz MK, Stein J, Wei S, Preece J, Olson A, Naithani S, Amarasinghe V, Dharmawardhana P, Jiao Y, Mulvaney J, Kumari S, Chougule K, Elser J, Wang B, Thomason J, Bolser DM, Kerhornou A, Walts B, Fonseca NA, Huerta L, Keays M, Tang YA, Parkinson H, Fabregat A, McKay S, Weiser J, D'Eustachio P, Stein L, Petryszak R, Kersey PJ, Jaiswal P, Ware D. Gramene 2016: comparative plant genomics and pathway resources. Nucleic Acids Res 2015; 44:D1133-40. [PMID: 26553803 PMCID: PMC4702844 DOI: 10.1093/nar/gkv1179] [Citation(s) in RCA: 108] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Accepted: 10/13/2015] [Indexed: 12/21/2022] Open
Abstract
Gramene (http://www.gramene.org) is an online resource for comparative functional genomics in crops and model plant species. Its two main frameworks are genomes (collaboration with Ensembl Plants) and pathways (The Plant Reactome and archival BioCyc databases). Since our last NAR update, the database website adopted a new Drupal management platform. The genomes section features 39 fully assembled reference genomes that are integrated using ontology-based annotation and comparative analyses, and accessed through both visual and programmatic interfaces. Additional community data, such as genetic variation, expression and methylation, are also mapped for a subset of genomes. The Plant Reactome pathway portal (http://plantreactome.gramene.org) provides a reference resource for analyzing plant metabolic and regulatory pathways. In addition to ∼ 200 curated rice reference pathways, the portal hosts gene homology-based pathway projections for 33 plant species. Both the genome and pathway browsers interface with the EMBL-EBI's Expression Atlas to enable the projection of baseline and differential expression data from curated expression studies in plants. Gramene's archive website (http://archive.gramene.org) continues to provide previously reported resources on comparative maps, markers and QTL. To further aid our users, we have also introduced a live monthly educational webinar series and a Gramene YouTube channel carrying video tutorials.
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Affiliation(s)
| | - Joshua Stein
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sharon Wei
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Justin Preece
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Andrew Olson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Vindhya Amarasinghe
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Palitha Dharmawardhana
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Yinping Jiao
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Joseph Mulvaney
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sunita Kumari
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Kapeel Chougule
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Justin Elser
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Bo Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - James Thomason
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Daniel M Bolser
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Arnaud Kerhornou
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Brandon Walts
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Nuno A Fonseca
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Laura Huerta
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Maria Keays
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Y Amy Tang
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Helen Parkinson
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Antonio Fabregat
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Sheldon McKay
- Informatics and Bio-computing Program, Ontario Institute of Cancer Research, Toronto, M5G 1L7, Canada
| | - Joel Weiser
- Informatics and Bio-computing Program, Ontario Institute of Cancer Research, Toronto, M5G 1L7, Canada
| | - Peter D'Eustachio
- Department of Biochemistry & Molecular Pharmacology, NYU School of Medicine, New York, NY 10016, USA
| | - Lincoln Stein
- Informatics and Bio-computing Program, Ontario Institute of Cancer Research, Toronto, M5G 1L7, Canada
| | - Robert Petryszak
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Paul J Kersey
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA USDA ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, Ithaca, NY 14853, USA
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Andorf CM, Cannon EK, Portwood JL, Gardiner JM, Harper LC, Schaeffer ML, Braun BL, Campbell DA, Vinnakota AG, Sribalusu VV, Huerta M, Cho KT, Wimalanathan K, Richter JD, Mauch ED, Rao BS, Birkett SM, Sen TZ, Lawrence-Dill CJ. MaizeGDB update: new tools, data and interface for the maize model organism database. Nucleic Acids Res 2015; 44:D1195-201. [PMID: 26432828 PMCID: PMC4702771 DOI: 10.1093/nar/gkv1007] [Citation(s) in RCA: 123] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Accepted: 09/24/2015] [Indexed: 11/24/2022] Open
Abstract
MaizeGDB is a highly curated, community-oriented database and informatics service to researchers focused on the crop plant and model organism Zea mays ssp. mays. Although some form of the maize community database has existed over the last 25 years, there have only been two major releases. In 1991, the original maize genetics database MaizeDB was created. In 2003, the combined contents of MaizeDB and the sequence data from ZmDB were made accessible as a single resource named MaizeGDB. Over the next decade, MaizeGDB became more sequence driven while still maintaining traditional maize genetics datasets. This enabled the project to meet the continued growing and evolving needs of the maize research community, yet the interface and underlying infrastructure remained unchanged. In 2015, the MaizeGDB team completed a multi-year effort to update the MaizeGDB resource by reorganizing existing data, upgrading hardware and infrastructure, creating new tools, incorporating new data types (including diversity data, expression data, gene models, and metabolic pathways), and developing and deploying a modern interface. In addition to coordinating a data resource, the MaizeGDB team coordinates activities and provides technical support to the maize research community. MaizeGDB is accessible online at http://www.maizegdb.org.
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Affiliation(s)
- Carson M Andorf
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA Department of Computer Science, Iowa State University, Ames, IA 50011, USA
| | - Ethalinda K Cannon
- Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA
| | - John L Portwood
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Jack M Gardiner
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
| | - Lisa C Harper
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Mary L Schaeffer
- USDA-ARS Plant Genetics Research Unit, University of Missouri, Columbia, MO 65211, USA Division of Plant Sciences, Department of Agronomy, University of Missouri, Columbia, MO 65211, USA
| | - Bremen L Braun
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Darwin A Campbell
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | | | | | - Miranda Huerta
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Kyoung Tak Cho
- Department of Computer Science, Iowa State University, Ames, IA 50011, USA
| | - Kokulapalan Wimalanathan
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA Bioinformatics and Computational Biology, Iowa State University, Ames, IA 50011, USA
| | - Jacqueline D Richter
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | - Emily D Mauch
- Interdepartmental Genetics and Genomics, Iowa State University, Ames, IA 50011, USA
| | - Bhavani S Rao
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | - Scott M Birkett
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | - Taner Z Sen
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | - Carolyn J Lawrence-Dill
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA Department of Agronomy, Iowa State University, Ames, IA 50011, USA
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Warren RL, Keeling CI, Yuen MMS, Raymond A, Taylor GA, Vandervalk BP, Mohamadi H, Paulino D, Chiu R, Jackman SD, Robertson G, Yang C, Boyle B, Hoffmann M, Weigel D, Nelson DR, Ritland C, Isabel N, Jaquish B, Yanchuk A, Bousquet J, Jones SJM, MacKay J, Birol I, Bohlmann J. Improved white spruce (Picea glauca) genome assemblies and annotation of large gene families of conifer terpenoid and phenolic defense metabolism. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2015; 83:189-212. [PMID: 26017574 DOI: 10.1111/tpj.12886] [Citation(s) in RCA: 125] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2015] [Accepted: 05/15/2015] [Indexed: 05/21/2023]
Abstract
White spruce (Picea glauca), a gymnosperm tree, has been established as one of the models for conifer genomics. We describe the draft genome assemblies of two white spruce genotypes, PG29 and WS77111, innovative tools for the assembly of very large genomes, and the conifer genomics resources developed in this process. The two white spruce genotypes originate from distant geographic regions of western (PG29) and eastern (WS77111) North America, and represent elite trees in two Canadian tree-breeding programs. We present an update (V3 and V4) for a previously reported PG29 V2 draft genome assembly and introduce a second white spruce genome assembly for genotype WS77111. Assemblies of the PG29 and WS77111 genomes confirm the reconstructed white spruce genome size in the 20 Gbp range, and show broad synteny. Using the PG29 V3 assembly and additional white spruce genomics and transcriptomics resources, we performed MAKER-P annotation and meticulous expert annotation of very large gene families of conifer defense metabolism, the terpene synthases and cytochrome P450s. We also comprehensively annotated the white spruce mevalonate, methylerythritol phosphate and phenylpropanoid pathways. These analyses highlighted the large extent of gene and pseudogene duplications in a conifer genome, in particular for genes of secondary (i.e. specialized) metabolism, and the potential for gain and loss of function for defense and adaptation.
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Affiliation(s)
- René L Warren
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Christopher I Keeling
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Macaire Man Saint Yuen
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Anthony Raymond
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Greg A Taylor
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Benjamin P Vandervalk
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Hamid Mohamadi
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Daniel Paulino
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Readman Chiu
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Shaun D Jackman
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Gordon Robertson
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Chen Yang
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
| | - Brian Boyle
- Department of Wood and Forest Sciences, Université Laval, Québec, QC, G1V 0A6, Canada
| | - Margarete Hoffmann
- Max Planck Institute for Developmental Biology, Spemannstrasse 35, 72076, Tübingen, Germany
| | - Detlef Weigel
- Max Planck Institute for Developmental Biology, Spemannstrasse 35, 72076, Tübingen, Germany
| | - David R Nelson
- Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - Carol Ritland
- Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Nathalie Isabel
- Natural Resources Canada, Laurentian Forestry Centre, Québec, QC, G1V 4C7, Canada
| | - Barry Jaquish
- British Columbia Ministry of Forests, Lands, and Natural Resource Operations, Victoria, BC, V8W 9C2, Canada
| | - Alvin Yanchuk
- British Columbia Ministry of Forests, Lands, and Natural Resource Operations, Victoria, BC, V8W 9C2, Canada
| | - Jean Bousquet
- Department of Wood and Forest Sciences, Université Laval, Québec, QC, G1V 0A6, Canada
| | - Steven J M Jones
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
- School of Computing Science, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada
| | - John MacKay
- Department of Wood and Forest Sciences, Université Laval, Québec, QC, G1V 0A6, Canada
- Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
| | - Inanc Birol
- Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6H 3N1, Canada
- School of Computing Science, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada
| | - Joerg Bohlmann
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
- Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
- Department of Botany, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
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Campbell MS, Holt C, Moore B, Yandell M. Genome Annotation and Curation Using MAKER and MAKER-P. ACTA ACUST UNITED AC 2014; 48:4.11.1-4.11.39. [PMID: 25501943 DOI: 10.1002/0471250953.bi0411s48] [Citation(s) in RCA: 447] [Impact Index Per Article: 40.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
This unit describes how to use the genome annotation and curation tools MAKER and MAKER-P to annotate protein-coding and noncoding RNA genes in newly assembled genomes, update/combine legacy annotations in light of new evidence, add quality metrics to annotations from other pipelines, and map existing annotations to a new assembly. MAKER and MAKER-P can rapidly annotate genomes of any size, and scale to match available computational resources.
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Affiliation(s)
- Michael S Campbell
- Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah
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