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Li J, Li Y, Agyenim-Boateng KG, Shaibu AS, Liu Y, Feng Y, Qi J, Li B, Zhang S, Sun J. Natural variation of domestication-related genes contributed to latitudinal expansion and adaptation in soybean. BMC PLANT BIOLOGY 2024; 24:651. [PMID: 38977969 PMCID: PMC11232268 DOI: 10.1186/s12870-024-05382-0] [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: 05/17/2024] [Accepted: 07/05/2024] [Indexed: 07/10/2024]
Abstract
Soybean is a major source of protein and edible oil worldwide. Originating from the Huang-Huai-Hai region, which has a temperate climate, soybean has adapted to a wide latitudinal gradient across China. However, the genetic mechanisms responsible for the widespread latitudinal adaptation in soybean, as well as the genetic basis, adaptive differentiation, and evolutionary implications of theses natural alleles, are currently lacking in comprehensive understanding. In this study, we examined the genetic variations of fourteen major gene loci controlling flowering and maturity in 103 wild species, 1048 landraces, and 1747 cultivated species. We found that E1, E3, FT2a, J, Tof11, Tof16, and Tof18 were favoured during soybean improvement and selection, which explained 75.5% of the flowering time phenotypic variation. These genetic variation was significantly associated with differences in latitude via the LFMM algorithm. Haplotype network and geographic distribution analysis suggested that gene combinations were associated with flowering time diversity contributed to the expansion of soybean, with more HapA clustering together when soybean moved to latitudes beyond 35°N. The geographical evolution model was developed to accurately predict the suitable planting zone for soybean varieties. Collectively, by integrating knowledge from genomics and haplotype classification, it was revealed that distinct gene combinations improve the adaptation of cultivated soybeans to different latitudes. This study provides insight into the genetic basis underlying the environmental adaptation of soybean accessions, which could contribute to a better understanding of the domestication history of soybean and facilitate soybean climate-smart molecular breeding for various environments.
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Affiliation(s)
- Jing Li
- The State Key Laboratory of Crop Gene Resources and Breeding, National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yecheng Li
- The State Key Laboratory of Crop Gene Resources and Breeding, National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | | | | | - Yitian Liu
- The State Key Laboratory of Crop Gene Resources and Breeding, National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yue Feng
- The State Key Laboratory of Crop Gene Resources and Breeding, National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Jie Qi
- The State Key Laboratory of Crop Gene Resources and Breeding, National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Bin Li
- The State Key Laboratory of Crop Gene Resources and Breeding, National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Shengrui Zhang
- The State Key Laboratory of Crop Gene Resources and Breeding, National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Junming Sun
- The State Key Laboratory of Crop Gene Resources and Breeding, National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China.
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Agha HI, Endelman JB, Chitwood-Brown J, Clough M, Coombs J, De Jong WS, Douches DS, Higgins CR, Holm DG, Novy R, Resende MFR, Sathuvalli V, Thompson AL, Yencho GC, Zotarelli L, Shannon LM. Genotype-by-environment interactions and local adaptation shape selection in the US National Chip Processing Trial. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:99. [PMID: 38598016 PMCID: PMC11006776 DOI: 10.1007/s00122-024-04610-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 03/25/2024] [Indexed: 04/11/2024]
Abstract
KEY MESSAGE We find evidence of selection for local adaptation and extensive genotype-by-environment interaction in the potato National Chip Processing Trial (NCPT). We present a novel method for dissecting the interplay between selection, local adaptation and environmental response in plant breeding schemes. Balancing local adaptation and the desire for widely adapted cultivars is challenging for plant breeders and makes genotype-by-environment interactions (GxE) an important target of selection. Selecting for GxE requires plant breeders to evaluate plants across multiple environments. One way breeders have accomplished this is to test advanced materials across many locations. Public potato breeders test advanced breeding material in the National Chip Processing Trial (NCPT), a public-private partnership where breeders from ten institutions submit advanced chip lines to be evaluated in up to ten locations across the country. These clones are genotyped and phenotyped for important agronomic traits. We used these data to interrogate the NCPT for GxE. Further, because breeders submitting clones to the NCPT select in a relatively small geographic range for the first 3 years of selection, we examined these data for evidence of incidental selection for local adaptation, and the alleles underlying it, using an environmental genome-wide association study (envGWAS). We found genomic regions associated with continuous environmental variables and discrete breeding programs, as well as regions of the genome potentially underlying GxE for yield.
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Affiliation(s)
- Husain I Agha
- Department of Horticultural Science, University of Minnesota, Saint Paul, MN, USA
| | - Jeffrey B Endelman
- Department of Plant & Agroecosystem Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Jessica Chitwood-Brown
- Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO, USA
| | - Mark Clough
- Department of Horticultural Science, North Carolina State University, Raleigh, NC, USA
| | - Joseph Coombs
- Department of Plant Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA
| | - Walter S De Jong
- School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - David S Douches
- Department of Plant Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA
| | | | - David G Holm
- Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO, USA
| | - Richard Novy
- Small Grains and Potato Germplasm Research, USDA-ARS, Aberdeen, ID, USA
| | - Marcio F R Resende
- Horticultural Sciences Department, University of Florida, Gainesville, FL, USA
| | - Vidyasagar Sathuvalli
- Hermiston Agricultural Research and Extension Center, Oregon State University, Hermiston, OR, USA
| | - Asunta L Thompson
- Department of Plant Sciences, North Dakota State University, Fargo, ND, USA
| | - G Craig Yencho
- Department of Horticultural Science, North Carolina State University, Raleigh, NC, USA
| | - Lincoln Zotarelli
- Horticultural Sciences Department, University of Florida, Gainesville, FL, USA
| | - Laura M Shannon
- Department of Horticultural Science, University of Minnesota, Saint Paul, MN, USA.
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Chen T, Xu J, Wang L, Wang H, You E, Deng C, Bian H, Shen Y. Landscape genomics reveals adaptive genetic differentiation driven by multiple environmental variables in naked barley on the Qinghai-Tibetan Plateau. Heredity (Edinb) 2023; 131:316-326. [PMID: 37935814 PMCID: PMC10673939 DOI: 10.1038/s41437-023-00647-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 08/21/2023] [Accepted: 08/23/2023] [Indexed: 11/09/2023] Open
Abstract
Understanding the local adaptation of crops has long been a concern of evolutionary biologists and molecular ecologists. Identifying the adaptive genetic variability in the genome is crucial not only to provide insights into the genetic mechanism of local adaptation but also to explore the adaptation potential of crops. This study aimed to identify the climatic drivers of naked barley landraces and putative adaptive loci driving local adaptation on the Qinghai-Tibetan Plateau (QTP). To this end, a total of 157 diverse naked barley accessions were genotyped using the genotyping-by-sequencing approach, which yielded 3123 high-quality SNPs for population structure analysis and partial redundancy analysis, and 37,636 SNPs for outlier analysis. The population structure analysis indicated that naked barley landraces could be divided into four groups. We found that the genomic diversity of naked barley landraces could be partly traced back to the geographical and environmental diversity of the landscape. In total, 136 signatures associated with temperature, precipitation, and ultraviolet radiation were identified, of which 13 had pleiotropic effects. We mapped 447 genes, including a known gene HvSs1. Some genes involved in cold stress and regulation of flowering time were detected near eight signatures. Taken together, these results highlight the existence of putative adaptive loci in naked barley on QTP and thus improve our current understanding of the genetic basis of local adaptation.
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Affiliation(s)
- Tongrui Chen
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Laboratory for Research and Utilization of Qinghai Tibetan Plateau Germplasm Resources, Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810000, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jinqing Xu
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Laboratory for Research and Utilization of Qinghai Tibetan Plateau Germplasm Resources, Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810000, China
- Innovation Academy for Seed Design, Chinese Academy of Sciences, Xining, 810000, China
| | - Lei Wang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Laboratory for Research and Utilization of Qinghai Tibetan Plateau Germplasm Resources, Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810000, China
- Innovation Academy for Seed Design, Chinese Academy of Sciences, Xining, 810000, China
| | - Handong Wang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Laboratory for Research and Utilization of Qinghai Tibetan Plateau Germplasm Resources, Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810000, China
- Innovation Academy for Seed Design, Chinese Academy of Sciences, Xining, 810000, China
| | - En You
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Laboratory for Research and Utilization of Qinghai Tibetan Plateau Germplasm Resources, Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810000, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chao Deng
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Laboratory for Research and Utilization of Qinghai Tibetan Plateau Germplasm Resources, Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810000, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Haiyan Bian
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Laboratory for Research and Utilization of Qinghai Tibetan Plateau Germplasm Resources, Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810000, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuhu Shen
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Laboratory for Research and Utilization of Qinghai Tibetan Plateau Germplasm Resources, Qinghai Provincial Key Laboratory of Crop Molecular Breeding, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810000, China.
- Innovation Academy for Seed Design, Chinese Academy of Sciences, Xining, 810000, China.
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Schmidt SB, Brown LK, Booth A, Wishart J, Hedley PE, Martin P, Husted S, George TS, Russell J. Heritage genetics for adaptation to marginal soils in barley. TRENDS IN PLANT SCIENCE 2023; 28:544-551. [PMID: 36858842 DOI: 10.1016/j.tplants.2023.01.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 01/17/2023] [Accepted: 01/23/2023] [Indexed: 05/22/2023]
Abstract
Future crops need to be sustainable in the face of climate change. Modern barley varieties have been bred for high productivity and quality; however, they have suffered considerable genetic erosion, losing crucial genetic diversity. This renders modern cultivars vulnerable to climate change and stressful environments. We highlight the potential to tailor crops to a specific environment by utilising diversity inherent in an adapted landrace population. Tapping into natural biodiversity, while incorporating information about local environmental and climatic conditions, allows targeting of key traits and genotypes, enabling crop production in marginal soils. We outline future directions for the utilisation of genetic resources maintained in landrace collections to support sustainable agriculture through germplasm development via the use of genomics technologies and big data.
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Affiliation(s)
- Sidsel Birkelund Schmidt
- The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK; Innovation Centre for Organic Farming, Agro Food Park 26, 8200 Aarhus N., Denmark
| | - Lawrie K Brown
- The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK
| | - Allan Booth
- The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK
| | - John Wishart
- Agronomy Institute, Orkney College, University of the Highlands and Islands, Orkney, UK
| | - Pete E Hedley
- The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK
| | - Peter Martin
- Agronomy Institute, Orkney College, University of the Highlands and Islands, Orkney, UK
| | - Søren Husted
- Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Thorvaldsensvej 40, 1879 Frederiksberg C., Denmark
| | | | - Joanne Russell
- The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK.
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5
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Discovering Loci for Breeding Prospective and Phenology in Wheat Mediterranean Landraces by Environmental and eigenGWAS. Int J Mol Sci 2023; 24:ijms24021700. [PMID: 36675215 PMCID: PMC9863576 DOI: 10.3390/ijms24021700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/27/2022] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
Knowledge of the genetic basis of traits controlling phenology, differentiation patterns, and environmental adaptation is essential to develop new cultivars under climate change conditions. Landrace collections are an appropriate platform to study the hidden variation caused by crop breeding. The use of genome-wide association analysis for phenology, climatic data and differentiation among Mediterranean landraces led to the identification of 651 marker-trait associations that could be grouped in 46 QTL hotspots. A candidate gene analysis using the annotation of the genome sequence of the wheat cultivar 'Chinese Spring' detected 1097 gene models within 33 selected QTL hotspots. From all the gene models, 42 were shown to be differentially expressed (upregulated) under abiotic stress conditions, and 9 were selected based on their levels of expression. Different gene families previously reported for their involvement in different stress responses were found (protein kinases, ras-like GTP binding proteins and ethylene-responsive transcription factors). Finally, the synteny analysis in the QTL hotspots regions among the genomes of wheat and other cereal species identified 23, 21 and 7 ortho-QTLs for Brachypodium, rice and maize, respectively, confirming the importance of these loci.
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Shan D, Ali M, Shahid M, Arif A, Waheed MQ, Xia X, Trethowan R, Tester M, Poland J, Ogbonnaya FC, Rasheed A, He Z, Li H. Genetic networks underlying salinity tolerance in wheat uncovered with genome-wide analyses and selective sweeps. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2925-2941. [PMID: 35915266 DOI: 10.1007/s00122-022-04153-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
A genetic framework underpinning salinity tolerance at reproductive stage was revealed by genome-wide SNP markers and major adaptability genes in synthetic-derived wheats, and trait-associated loci were used to predict phenotypes. Using wild relatives of crops to identify genes related to improved productivity and resilience to climate extremes is a prioritized area of crop genetic improvement. High salinity is a widespread crop production constraint, and development of salt-tolerant cultivars is a sustainable solution. We evaluated a panel of 294 wheat accessions comprising synthetic-derived wheat lines (SYN-DERs) and modern bread wheat advanced lines under control and high salinity conditions at two locations. The GWAS analysis revealed a quantitative genetic framework of more than 200 loci with minor effect underlying salinity tolerance at reproductive stage. The significant trait-associated SNPs were used to predict phenotypes using a GBLUP model, and the prediction accuracy (r2) ranged between 0.57 and 0.74. The r2 values for flag leaf weight, days to flowering, biomass, and number of spikes per plant were all above 0.70, validating the phenotypic effects of the loci discovered in this study. Furthermore, the germplasm sets were compared to identify selection sweeps associated with salt tolerance loci in SYN-DERs. Six loci associated with salinity tolerance were found to be differentially selected in the SYN-DERs (12.4 Mb on chromosome (chr)1B, 7.1 Mb on chr2A, 11.2 Mb on chr2D, 200 Mb on chr3D, 600 Mb on chr6B, and 700.9 Mb on chr7B). A total of 228 reported markers and genes, including 17 well-characterized genes, were uncovered using GWAS and EigenGWAS. A linkage disequilibrium (LD) block on chr5A, including the Vrn-A1 gene at 575 Mb and its homeologs on chr5D, were strongly associated with multiple yield-related traits and flowering time under salinity stress conditions. The diversity panel was screened with more than 68 kompetitive allele-specific PCR (KASP) markers of functional genes in wheat, and the pleiotropic effects of superior alleles of Rht-1, TaGASR-A1, and TaCwi-A1 were revealed under salinity stress. To effectively utilize the extensive genetic information obtained from the GWAS analysis, a genetic interaction network was constructed to reveal correlations among the investigated traits. The genetic network data combined with GWAS, selective sweeps, and the functional gene survey provided a quantitative genetic framework for identifying differentially retained loci associated with salinity tolerance in wheat.
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Affiliation(s)
- Danting Shan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China
- Nanfan Research Institute, CAAS, Sanya, 572024, Hainan, China
| | - Mohsin Ali
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China
- Nanfan Research Institute, CAAS, Sanya, 572024, Hainan, China
| | - Mohammed Shahid
- International Center for Biosaline Agriculture (ICBA), Al Ruwayyah 2, Academic City, Dubai, UAE
| | - Anjuman Arif
- National Institute of Agriculture and Biology (NIAB), Faisalabad, Pakistan
| | | | - Xianchun Xia
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Richard Trethowan
- Plant Breeding Institute, School of Life and Environmental Sciences, The University of Sydney, Sydney, 2006, Australia
| | - Mark Tester
- Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KASUT), Thuwal, 23955-6900, Saudi Arabia
| | - Jesse Poland
- Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KASUT), Thuwal, 23955-6900, Saudi Arabia
- Kansas State University, Manhattan, KS, USA
| | | | - Awais Rasheed
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China.
| | - Zhonghu He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China.
- Nanfan Research Institute, CAAS, Sanya, 572024, Hainan, China.
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Yang CJ, Ladejobi O, Mott R, Powell W, Mackay I. Analysis of historical selection in winter wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3005-3023. [PMID: 35864201 PMCID: PMC9482581 DOI: 10.1007/s00122-022-04163-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
KEY MESSAGE Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically important traits like yield have been well characterized and are the major force driving its production. Winter wheat is also an excellent model for analyzing historical genetic selection. As a proof of concept, we analyze two major collections of winter wheat varieties that were bred in Western Europe from 1916 to 2010, namely the Triticeae Genome (TG) and WAGTAIL panels, which include 333 and 403 varieties, respectively. We develop and apply a selection mapping approach, Regression of Alleles on Years (RALLY), in these panels, as well as in simulated populations. RALLY maps loci under sustained historical selection by using a simple logistic model to regress allele counts on years of variety release. To control for drift-induced allele frequency change, we develop a hybrid approach of genomic control and delta control. Within the TG panel, we identify 22 significant RALLY quantitative selection loci (QSLs) and estimate the local heritabilities for 12 traits across these QSLs. By correlating predicted marker effects with RALLY regression estimates, we show that alleles whose frequencies have increased over time are heavily biased toward conferring positive yield effect, but negative effects in flowering time, lodging, plant height and grain protein content. Altogether, our results (1) demonstrate the use of RALLY to identify selected genomic regions while controlling for drift, and (2) reveal key patterns in the historical selection in winter wheat and guide its future breeding.
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Affiliation(s)
- Chin Jian Yang
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
| | - Olufunmilayo Ladejobi
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Richard Mott
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Wayne Powell
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
| | - Ian Mackay
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK.
- IMplant Consultancy Ltd, Chelmsford, UK.
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Cortés AJ, López-Hernández F, Blair MW. Genome-Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives. Front Genet 2022; 13:910386. [PMID: 35991553 PMCID: PMC9389289 DOI: 10.3389/fgene.2022.910386] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 05/30/2022] [Indexed: 11/23/2022] Open
Abstract
Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome-environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat-based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change. "I shall endeavor to find out how nature's forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature" Alexander von Humboldt-Letter to Karl Freiesleben, June 1799.
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Affiliation(s)
- Andrés J. Cortés
- Corporacion Colombiana de Investigacion Agropecuaria AGROSAVIA, C.I. La Selva, Rionegro, Colombia
| | - Felipe López-Hernández
- Corporacion Colombiana de Investigacion Agropecuaria AGROSAVIA, C.I. La Selva, Rionegro, Colombia
| | - Matthew W. Blair
- Department of Agricultural & Environmental Sciences, Tennessee State University, Nashville, TN, United States
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Ali M, Danting S, Wang J, Sadiq H, Rasheed A, He Z, Li H. Genetic Diversity and Selection Signatures in Synthetic-Derived Wheats and Modern Spring Wheat. FRONTIERS IN PLANT SCIENCE 2022; 13:877496. [PMID: 35903232 PMCID: PMC9315363 DOI: 10.3389/fpls.2022.877496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
Synthetic hexaploid wheats and their derived advanced lines were subject to empirical selection in developing genetically superior cultivars. To investigate genetic diversity, patterns of nucleotide diversity, population structure, and selection signatures during wheat breeding, we tested 422 wheat accessions, including 145 synthetic-derived wheats, 128 spring wheat cultivars, and 149 advanced breeding lines from Pakistan. A total of 18,589 high-quality GBS-SNPs were identified that were distributed across the A (40%), B (49%), and D (11%) genomes. Values of population diversity parameters were estimated across chromosomes and genomes. Genome-wide average values of genetic diversity and polymorphic information content were estimated to be 0.30 and 0.25, respectively. Neighbor-joining (NJ) tree, principal component analysis (PCA), and kinship analyses revealed that synthetic-derived wheats and advanced breeding lines were genetically diverse. The 422 accessions were not separated into distinct groups by NJ analysis and confirmed using the PCA. This conclusion was validated with both relative kinship and Rogers' genetic distance analyses. EigenGWAS analysis revealed that 32 unique genome regions had undergone selection. We found that 50% of the selected regions were located in the B-genome, 29% in the D-genome, and 21% in the A-genome. Previously known functional genes or QTL were found within the selection regions associated with phenology-related traits such as vernalization, adaptability, disease resistance, and yield-related traits. The selection signatures identified in the present investigation will be useful for understanding the targets of modern wheat breeding in Pakistan.
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Affiliation(s)
- Mohsin Ali
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya, China
| | - Shan Danting
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya, China
| | - Jiankang Wang
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Hafsa Sadiq
- Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | - Awais Rasheed
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | - Zhonghu He
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Huihui Li
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya, China
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Yang J, Liang B, Zhang Y, Liu Y, Wang S, Yang Q, Geng X, Liu S, Wu Y, Zhu Y, Lin T. Genome-wide association study of eigenvectors provides genetic insights into selective breeding for tomato metabolites. BMC Biol 2022; 20:120. [PMID: 35606872 PMCID: PMC9128223 DOI: 10.1186/s12915-022-01327-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/10/2022] [Indexed: 01/05/2023] Open
Abstract
Background Long-term domestication and intensive breeding of crop plants aim to establish traits desirable for human needs, and characteristics related to yield, disease resistance, and postharvest storage have traditionally received considerable attention. These processes have led also to negative consequences, as is the case of loss of variants controlling fruit quality, for instance in tomato. Tomato fruit quality is directly associated to metabolite content profiles; however, a full understanding of the genetics affecting metabolite content during tomato domestication and improvement has not been reached due to limitations of the single detection methods previously employed. Here, we aim to reach a broad understanding of changes in metabolite content using a genome-wide association study (GWAS) with eigenvector decomposition (EigenGWAS) on tomato accessions. Results An EigenGWAS was performed on 331 tomato accessions using the first eigenvector generated from the genomic data as a “phenotype” to understand the changes in fruit metabolite content during breeding. Two independent gene sets were identified that affected fruit metabolites during domestication and improvement in consumer-preferred tomatoes. Furthermore, 57 candidate genes related to polyphenol and polyamine biosynthesis were discovered, and a major candidate gene chlorogenate: glucarate caffeoyltransferase (SlCGT) was identified, which affected the quality and diseases resistance of tomato fruit, revealing the domestication mechanism of polyphenols. Conclusions We identified gene sets that contributed to consumer liking during domestication and improvement of tomato. Our study reports novel evidence of selective sweeps and key metabolites controlled by multiple genes, increasing our understanding of the mechanisms of metabolites variation during those processes. It also supports a polygenic selection model for the application of tomato breeding. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-022-01327-x.
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Sharma R, Cockram J, Gardner KA, Russell J, Ramsay L, Thomas WTB, O'Sullivan DM, Powell W, Mackay IJ. Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:667-678. [PMID: 34778903 PMCID: PMC8866380 DOI: 10.1007/s00122-021-03991-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 11/02/2021] [Indexed: 05/26/2023]
Abstract
Variety age and population structure detect novel QTL for yield and adaptation in wheat and barley without the need to phenotype. The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However, in many cases, the alleles and genomic regions underpinning this success remain unknown. This is partly due to the difficulty of generating sufficient phenotypic data on large numbers of historical varieties to enable such analyses. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using age of a variety as a surrogate for yield. Rather than collecting phenotype data, we deployed 'environmental genome-wide association scans' (EnvGWAS) based on variety age in two of the world's most important crops, wheat and barley, and detected strong signals of selection across both genomes. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure, we used the genomic relationship matrix of the genotypic data to derive eigenvectors for analysis in EigenGWAS. This detected seven major chromosomal introgressions that contributed to adaptation in wheat. EigenGWAS and EnvGWAS based on variety age avoid costly phenotyping and facilitate the identification of genomic tracts that have been under selection during breeding. Our results demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions under selection and may help guide future plant breeding strategies to maximise the rate of genetic gain and adaptation.
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Affiliation(s)
- Rajiv Sharma
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
| | - James Cockram
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Keith A Gardner
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Joanne Russell
- The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK
| | - Luke Ramsay
- The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK
| | | | - Donal M O'Sullivan
- School of Agriculture, Policy and Development, University of Reading, Reading, RG6 6AR, UK
| | - Wayne Powell
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
| | - Ian J Mackay
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK.
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Yang Y, Xu C, Shen Z, Yan C. Crop Quality Improvement Through Genome Editing Strategy. Front Genome Ed 2022; 3:819687. [PMID: 35174353 PMCID: PMC8841430 DOI: 10.3389/fgeed.2021.819687] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 12/30/2021] [Indexed: 11/13/2022] Open
Abstract
Good quality of crops has always been the most concerning aspect for breeders and consumers. However, crop quality is a complex trait affected by both the genetic systems and environmental factors, thus, it is difficult to improve through traditional breeding strategies. Recently, the CRISPR/Cas9 genome editing system, enabling efficiently targeted modification, has revolutionized the field of quality improvement in most crops. In this review, we briefly review the various genome editing ability of the CRISPR/Cas9 system, such as gene knockout, knock-in or replacement, base editing, prime editing, and gene expression regulation. In addition, we highlight the advances in crop quality improvement applying the CRISPR/Cas9 system in four main aspects: macronutrients, micronutrients, anti-nutritional factors and others. Finally, the potential challenges and future perspectives of genome editing in crop quality improvement is also discussed.
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Affiliation(s)
- Yihao Yang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou, China
- Department of Crop Genetics and Breeding, Agricultural College of Yangzhou University, Yangzhou, China
| | - Chenda Xu
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou, China
| | - Ziyan Shen
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou, China
| | - Changjie Yan
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou, China
- Department of Crop Genetics and Breeding, Agricultural College of Yangzhou University, Yangzhou, China
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13
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Hanif U, Alipour H, Gul A, Jing L, Darvishzadeh R, Amir R, Munir F, Ilyas MK, Ghafoor A, Siddiqui SU, St Amand P, Bernado A, Bai G, Sonder K, Rasheed A, He Z, Li H. Characterization of the genetic basis of local adaptation of wheat landraces from Iran and Pakistan using genome-wide association study. THE PLANT GENOME 2021; 14:e20096. [PMID: 34275212 DOI: 10.1002/tpg2.20096] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 01/31/2021] [Indexed: 05/21/2023]
Abstract
Characterization of genomic regions underlying adaptation of landraces can reveal a quantitative genetics framework for local wheat (Triticum aestivum L.) adaptability. A collection of 512 wheat landraces from the eastern edge of the Fertile Crescent in Iran and Pakistan were genotyped using genome-wide single nucleotide polymorphism markers generated by genotyping-by-sequencing. The minor allele frequency (MAF) and the heterozygosity (H) of Pakistani wheat landraces (MAF = 0.19, H = 0.008) were slightly higher than the Iranian wheat landraces (MAF = 0.17, H = 0.005), indicating that Pakistani landraces were slightly more genetically diverse. Population structure analysis clearly separated the Pakistani landraces from Iranian landraces, which indicates two separate adaptability trajectories. The large-scale agro-climatic data of seven variables were quite dissimilar between Iran and Pakistan as revealed by the correlation coefficients. Genome-wide association study identified 91 and 58 loci using agroclimatic data, which likely underpin local adaptability of the wheat landraces from Iran and Pakistan, respectively. Selective sweep analysis identified significant hits on chromosomes 4A, 4B, 6B, 7B, 2D, and 6D, which were colocalized with the loci associated with local adaptability and with some known genes related to flowering time and grain size. This study provides insight into the genetic diversity with emphasis on the genetic architecture of loci involved in adaptation to local environments, which has breeding implications.
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Affiliation(s)
- Uzma Hanif
- Atta-ur-Rahman School of Applied Biosciences, National Univ. of Sciences and Technology, Islamabad, Pakistan
| | - Hadi Alipour
- Dep. of Plant Production and Genetics, Faculty of Agriculture and Natural Resources, Urmia Univ., Urmia, Iran
| | - Alvina Gul
- Atta-ur-Rahman School of Applied Biosciences, National Univ. of Sciences and Technology, Islamabad, Pakistan
| | - Li Jing
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), & CIMMYT-China office, 12 Zhongguancun South St., Beijing, 100081, China
| | - Reza Darvishzadeh
- Dep. of Plant Production and Genetics, Faculty of Agriculture and Natural Resources, Urmia Univ., Urmia, Iran
| | - Rabia Amir
- Atta-ur-Rahman School of Applied Biosciences, National Univ. of Sciences and Technology, Islamabad, Pakistan
| | - Faiza Munir
- Atta-ur-Rahman School of Applied Biosciences, National Univ. of Sciences and Technology, Islamabad, Pakistan
| | - Muhammad Kashif Ilyas
- Plant Genetic Resource Program, Bioresource Conservation Institute, National Agricultural Research Center, Islamabad, 44000, Pakistan
| | - Abdul Ghafoor
- Plant Genetic Resource Program, Bioresource Conservation Institute, National Agricultural Research Center, Islamabad, 44000, Pakistan
| | - Sadar Uddin Siddiqui
- Plant Genetic Resource Program, Bioresource Conservation Institute, National Agricultural Research Center, Islamabad, 44000, Pakistan
| | - Paul St Amand
- USDA Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA
| | - Amy Bernado
- USDA Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA
| | - Guihua Bai
- USDA Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA
| | - Kai Sonder
- International Wheat and Maize Improvement Center (CIMMYT), Texcoco, Mexico
| | - Awais Rasheed
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), & CIMMYT-China office, 12 Zhongguancun South St., Beijing, 100081, China
- Dep. of Plant Sciences, Quaid-i-Azam Univ., Islamabad, 45320, Pakistan
| | - Zhonghu He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), & CIMMYT-China office, 12 Zhongguancun South St., Beijing, 100081, China
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), & CIMMYT-China office, 12 Zhongguancun South St., Beijing, 100081, China
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14
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Li H, He Z. Warming climate challenges breeding. NATURE PLANTS 2021; 7:1164-1165. [PMID: 34518668 DOI: 10.1038/s41477-021-00996-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Affiliation(s)
- Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS) & CIMMYT China Office, Beijing, China.
| | - Zhonghu He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS) & CIMMYT China Office, Beijing, China
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15
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Rowan TN, Durbin HJ, Seabury CM, Schnabel RD, Decker JE. Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattle. PLoS Genet 2021; 17:e1009652. [PMID: 34292938 PMCID: PMC8297814 DOI: 10.1371/journal.pgen.1009652] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 06/09/2021] [Indexed: 12/19/2022] Open
Abstract
Selection on complex traits can rapidly drive evolution, especially in stressful environments. This polygenic selection does not leave intense sweep signatures on the genome, rather many loci experience small allele frequency shifts, resulting in large cumulative phenotypic changes. Directional selection and local adaptation are changing populations; but, identifying loci underlying polygenic or environmental selection has been difficult. We use genomic data on tens of thousands of cattle from three populations, distributed over time and landscapes, in linear mixed models with novel dependent variables to map signatures of selection on complex traits and local adaptation. We identify 207 genomic loci associated with an animal's birth date, representing ongoing selection for monogenic and polygenic traits. Additionally, hundreds of additional loci are associated with continuous and discrete environments, providing evidence for historical local adaptation. These candidate loci highlight the nervous system's possible role in local adaptation. While advanced technologies have increased the rate of directional selection in cattle, it has likely been at the expense of historically generated local adaptation, which is especially problematic in changing climates. When applied to large, diverse cattle datasets, these selection mapping methods provide an insight into how selection on complex traits continually shapes the genome. Further, understanding the genomic loci implicated in adaptation may help us breed more adapted and efficient cattle, and begin to understand the basis for mammalian adaptation, especially in changing climates. These selection mapping approaches help clarify selective forces and loci in evolutionary, model, and agricultural contexts.
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Affiliation(s)
- Troy N. Rowan
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, United States of America
- Genetics Area Program, University of Missouri, Columbia, Missouri, United States of America
- Department of Animal Science, University of Tennessee, Knoxville, Tennessee, United States of America
- College of Veterinary Medicine, Large Animal Clinical Science, University of Tennessee, Knoxville, Tennessee, United States of America
| | - Harly J. Durbin
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, United States of America
- Genetics Area Program, University of Missouri, Columbia, Missouri, United States of America
| | - Christopher M. Seabury
- Department of Veterinary Pathobiology, Texas A&M University, College Station, Texas, United States of America
| | - Robert D. Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, United States of America
- Genetics Area Program, University of Missouri, Columbia, Missouri, United States of America
- Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri, United States of America
| | - Jared E. Decker
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, United States of America
- Genetics Area Program, University of Missouri, Columbia, Missouri, United States of America
- Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri, United States of America
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16
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Hu Y, Peng X, Wang F, Chen P, Zhao M, Shen S. Natural population re-sequencing detects the genetic basis of local adaptation to low temperature in a woody plant. PLANT MOLECULAR BIOLOGY 2021; 105:585-599. [PMID: 33651261 DOI: 10.1007/s11103-020-01111-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 12/23/2020] [Indexed: 06/12/2023]
Abstract
Total of 14 SNPs associated with overwintering-related traits and 75 selective regions were detected. Important candidate genes were identified and a possible network of cold-stress responses in woody plants was proposed. Local adaptation to low temperature is essential for woody plants to against changeable climate and safely survive the winter. To uncover the specific molecular mechanism of low temperature adaptation in woody plants, we sequenced 134 core individuals selected from 494 paper mulberry (Broussonetia papyrifera), which naturally distributed in different climate zones and latitudes. The population structure analysis, PCA analysis and neighbor-joining tree analysis indicated that the individuals were classified into three clusters, which showed forceful geographic distribution patterns because of the adaptation to local climate. Using two overwintering phenotypic data collected at high latitudes of 40°N and one bioclimatic variable, genome-phenotype and genome-environment associations, and genome-wide scans were performed. We detected 75 selective regions which possibly undergone temperature selection and identified 14 trait-associated SNPs that corresponded to 16 candidate genes (including LRR-RLK, PP2A, BCS1, etc.). Meanwhile, low temperature adaptation was also supported by other three trait-associated SNPs which exhibiting significant differences in overwintering traits between alleles within three geographic groups. To sum up, a possible network of cold signal perception and responses in woody plants were proposed, including important genes that have been confirmed in previous studies while others could be key potential candidates of woody plants. Overall, our results highlighted the specific and complex molecular mechanism of low temperature adaptation and overwintering of woody plants.
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Affiliation(s)
- Yanmin Hu
- Key Laboratory of Plant Resources, Institute of Botany, The Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xianjun Peng
- Key Laboratory of Plant Resources, Institute of Botany, The Chinese Academy of Sciences, Beijing, 100093, China
| | - Fenfen Wang
- Key Laboratory of Plant Resources, Institute of Botany, The Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Peilin Chen
- Key Laboratory of Plant Resources, Institute of Botany, The Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Meiling Zhao
- Key Laboratory of Plant Resources, Institute of Botany, The Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shihua Shen
- Key Laboratory of Plant Resources, Institute of Botany, The Chinese Academy of Sciences, Beijing, 100093, China.
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17
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Soriano JM, Sansaloni C, Ammar K, Royo C. Labelling Selective Sweeps Used in Durum Wheat Breeding from a Diverse and Structured Panel of Landraces and Cultivars. BIOLOGY 2021; 10:biology10040258. [PMID: 33805192 PMCID: PMC8064341 DOI: 10.3390/biology10040258] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 03/17/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022]
Abstract
Simple Summary Evaluation of the genetic diversity of a crop species is a critical step for breeding. Landraces are essential to avoid genetic erosion, and Mediterranean landraces are an important group of genetic resources due to their high genetic variability, adaptation to local conditions in rainfed environments, and their resilience to pests and pathogens. This study uses a genome-wide association approach employing eigenvectors to identify selective sweeps among Mediterranean durum wheat landraces and a world panel of modern cultivars. Abstract A panel of 387 durum wheat genotypes including Mediterranean landraces and modern cultivars was characterized with 46,161 diversity arrays technology (DArTseq) markers. Analysis of population structure uncovered the existence of five subpopulations (SP) related to the pattern of migration of durum wheat from the domestication area to the west of the Mediterranean basin (SPs 1, 2, and 3) and further improved germplasm (SPs 4 and 5). The total genetic diversity (HT) was 0.40 with a genetic differentiation (GST) of 0.08 and a mean gene flow among SPs of 6.02. The lowest gene flow was detected between SP 1 (presumably the ancient genetic pool of the panel) and SPs 4 and 5. However, gene flow from SP 2 to modern cultivars was much higher. The highest gene flow was detected between SP 3 (western Mediterranean germplasm) and SP 5 (North American and European cultivars). A genome wide association study (GWAS) approach using the top ten eigenvectors as phenotypic data revealed the presence of 89 selective sweeps, represented as quantitative trait loci (QTL) hotspots, widely distributed across the durum wheat genome. A principal component analysis (PCoA) using 147 markers with −log10p > 5 identified three regions located on chromosomes 2A, 2B and 3A as the main drivers for differentiation of Mediterranean landraces. Gene flow between SPs offers clues regarding the putative use of Mediterranean old durum germplasm by the breeding programs represented in the structure analysis. EigenGWAS identified selective sweeps among landraces and modern cultivars. The analysis of the corresponding genomic regions in the ‘Zavitan’, ‘Svevo’ and ‘Chinese Spring’ genomes discovered the presence of important functional genes including Ppd, Vrn, Rht, and gene models involved in important biological processes including LRR-RLK, MADS-box, NAC, and F-box.
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Affiliation(s)
- Jose Miguel Soriano
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), 25198 Lleida, Spain;
- Correspondence:
| | - Carolina Sansaloni
- Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT), El Batán, Texcoco 56237, Mexico; (C.S.); (K.A.)
| | - Karim Ammar
- Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT), El Batán, Texcoco 56237, Mexico; (C.S.); (K.A.)
| | - Conxita Royo
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), 25198 Lleida, Spain;
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Qi GA, Zheng YT, Lin F, Huang X, Duan LW, You Y, Liu H, Wang Y, Xu HM, Chen GB. EigenGWAS: An online visualizing and interactive application for detecting genomic signatures of natural selection. Mol Ecol Resour 2021; 21:1732-1744. [PMID: 33665976 DOI: 10.1111/1755-0998.13370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 01/17/2021] [Accepted: 02/25/2021] [Indexed: 11/30/2022]
Abstract
Detecting genetic regions under selection in structured populations is of great importance in ecology, evolutionary biology and breeding programmes. We recently proposed EigenGWAS, an unsupervised genomic scanning approach that is similar to F ST but does not require grouping information of the population, for detection of genomic regions under selection. The original EigenGWAS is designed for the random mating population, and here we extend its use to inbred populations. We also show in theory and simulation that eigenvalues, the previous corrector for genetic drift in EigenGWAS, are overcorrected for genetic drift, and the genomic inflation factor is a better option for this adjustment. Applying the updated algorithm, we introduce the new EigenGWAS online platform with highly efficient core implementation. Our online computational tool accepts plink data in a standard binary format that can be easily converted from the original sequencing data, provides the users with graphical results via the R-Shiny user-friendly interface. We applied the proposed method and tool to various data sets, and biologically interpretable results as well as caveats that may lead to an unsatisfactory outcome are given. The EigenGWAS online platform is available at www.eigengwas.com, and can be localized and scaled up via R (recommended) or docker.
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Affiliation(s)
- Guo-An Qi
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Yuan-Ting Zheng
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Feng Lin
- Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Xin Huang
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Li-Wen Duan
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Yue You
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Hailan Liu
- Maize Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Ying Wang
- Phase I Clinical Research Center, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Hai-Ming Xu
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Guo-Bo Chen
- Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China.,Key Laboratory of Endocrine Gland Diseases of Zhejiang Province, People's Hospital of Hangzhou Medical College, Hangzhou, China
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19
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Li J, Li D, Espinosa CZ, Pastor VT, Rasheed A, Rojas NP, Wang J, Varela AS, Carolina de Almeida Silva N, Schnable PS, Costich DE, Li H. Genome-wide analyses reveal footprints of divergent selection and popping-related traits in CIMMYT's maize inbred lines. JOURNAL OF EXPERIMENTAL BOTANY 2021; 72:1307-1320. [PMID: 33070191 PMCID: PMC7904155 DOI: 10.1093/jxb/eraa480] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 10/13/2020] [Indexed: 05/16/2023]
Abstract
Popcorn (Zea mays L. var. Everta) is the most ancient type of cultivated maize. However, there is little known about the genetics of popping-related traits based on genotyping-by-sequencing (GBS) technology. Here, we characterized the phenotypic variation for seven popping-related traits in maize kernels among 526 CIMMYT inbred lines (CMLs). In total, 155 083 high-quality single nucleotide polymorphism (SNP) markers were identified by a GBS approach. Several trait-associated loci were detected by genome-wide association study for color, popping expansion volume, shape, pericarp, flotation index, floury/vitreous, and protein content, explaining a majority of the observed phenotypic variance, and these were validated by a diverse panel comprising 764 tropical landrace accessions. Sixty two of the identified loci were recognized to have undergone selection. On average, there was a 55.27% frequency for alleles that promote popping in CMLs. Our work not only pinpoints previously unknown loci for popping-related traits, but also reveals that many of these loci have undergone selection. Beyond establishing a new benchmark for the genetics of popcorn, our study provides a foundation for gene discovery and breeding. It also presents evidence to investigate the role of a gradual loss of popping ability as a by-product of diversification of culinary uses throughout the evolution of teosinte-to-modern maize.
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Affiliation(s)
- Jing Li
- Institute of Crop Sciences, The National Key Facility for Crop Gene Resources and Genetic Improvement and CIMMYT China office, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Delin Li
- Institute of Crop Sciences, The National Key Facility for Crop Gene Resources and Genetic Improvement and CIMMYT China office, Chinese Academy of Agricultural Sciences, Beijing, China
- Data Biotech (Beijing) Co., Ltd., Beijing, China
- Department of Plant Genetics and Breeding, China Agricultural University, Beijing, China
| | | | | | - Awais Rasheed
- Institute of Crop Sciences, The National Key Facility for Crop Gene Resources and Genetic Improvement and CIMMYT China office, Chinese Academy of Agricultural Sciences, Beijing, China
- Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | | | - Jiankang Wang
- Institute of Crop Sciences, The National Key Facility for Crop Gene Resources and Genetic Improvement and CIMMYT China office, Chinese Academy of Agricultural Sciences, Beijing, China
| | | | | | - Patrick S Schnable
- Data Biotech (Beijing) Co., Ltd., Beijing, China
- Department of Plant Genetics and Breeding, China Agricultural University, Beijing, China
- Data2Bio LLC, Ames, USA
- Department of Agronomy, Iowa State University, Ames, IA, USA
| | - Denise E Costich
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Huihui Li
- Institute of Crop Sciences, The National Key Facility for Crop Gene Resources and Genetic Improvement and CIMMYT China office, Chinese Academy of Agricultural Sciences, Beijing, China
- Correspondence: or
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20
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Dai P, Sun G, Jia Y, Pan Z, Tian Y, Peng Z, Li H, He S, Du X. Extensive haplotypes are associated with population differentiation and environmental adaptability in Upland cotton (Gossypium hirsutum). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:3273-3285. [PMID: 32844253 DOI: 10.1007/s00122-020-03668-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 08/08/2020] [Indexed: 05/06/2023]
Abstract
Three extensive eco-haplotypes associated with population differentiation and environmental adaptability in Upland cotton were identified, with A06_85658585, A08_43734499 and A06_113104285 considered the eco-loci for environmental adaptability. Population divergence is suggested to be the primary force driving the evolution of environmental adaptability in various species. Chromosome inversion increases reproductive isolation between subspecies and accelerates population divergence to adapt to new environments. Although modern cultivated Upland cotton (Gossypium hirsutum L.) has spread worldwide, the noticeable phenotypic differences still existed among cultivars grown in different areas. In recent years, the long-distance migration of cotton cultivation areas throughout China has demanded that breeders better understand the genetic basis of environmental adaptability in Upland cotton. Here, we integrated the genotypes of 419 diverse accessions, long-term environment-associated variables (EAVs) and environment-associated traits (EATs) to evaluate subgroup differentiation and identify adaptive loci in Upland cotton. Two highly divergent genomic regions were found on chromosomes A06 and A08, which likely caused by extensive chromosome inversions. The subgroups could be geographically classified based on distinct haplotypes in the divergent regions. A genome-wide association study (GWAS) also confirmed that loci located in these regions were significantly associated with environmental adaptability in Upland cotton. Our study first revealed the cause of population divergence in Upland cotton, as well as the consequences of variation in its environmental adaptability. These findings provide new insights into the genetic basis of environmental adaptability in Upland cotton, which could accelerate the development of molecular markers for adaptation to climate change in future cotton breeding.
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Affiliation(s)
- Panhong Dai
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Agricultural College, Yangtze University, Jingzhou, 434000, China
| | - Gaofei Sun
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- School of Computer Science & Information Engineering, Anyang Institute of Technology, Anyang, 455000, China
| | - Yinhua Jia
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Zhaoe Pan
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
| | - Yingbing Tian
- Agricultural College, Yangtze University, Jingzhou, 434000, China
| | - Zhen Peng
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China
| | - Hongge Li
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China
| | - Shoupu He
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China.
| | - Xiongming Du
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, China.
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, 450001, China.
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21
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López-Cortés XA, Matamala F, Maldonado C, Mora-Poblete F, Scapim CA. A Deep Learning Approach to Population Structure Inference in Inbred Lines of Maize. Front Genet 2020; 11:543459. [PMID: 33329691 PMCID: PMC7732446 DOI: 10.3389/fgene.2020.543459] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 10/19/2020] [Indexed: 11/16/2022] Open
Abstract
Analysis of population genetic variation and structure is a common practice for genome-wide studies, including association mapping, ecology, and evolution studies in several crop species. In this study, machine learning (ML) clustering methods, K-means (KM), and hierarchical clustering (HC), in combination with non-linear and linear dimensionality reduction techniques, deep autoencoder (DeepAE) and principal component analysis (PCA), were used to infer population structure and individual assignment of maize inbred lines, i.e., dent field corn (n = 97) and popcorn (n = 86). The results revealed that the HC method in combination with DeepAE-based data preprocessing (DeepAE-HC) was the most effective method to assign individuals to clusters (with 96% of correct individual assignments), whereas DeepAE-KM, PCA-HC, and PCA-KM were assigned correctly 92, 89, and 81% of the lines, respectively. These findings were consistent with both Silhouette Coefficient (SC) and Davies-Bouldin validation indexes. Notably, DeepAE-HC also had better accuracy than the Bayesian clustering method implemented in InStruct. The results of this study showed that deep learning (DL)-based dimensional reduction combined with ML clustering methods is a useful tool to determine genetically differentiated groups and to assign individuals into subpopulations in genome-wide studies without having to consider previous genetic assumptions.
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Affiliation(s)
| | - Felipe Matamala
- Department of Computer Sciences and Industries, Catholic University of the Maule, Talca, Chile
| | - Carlos Maldonado
- Instituto de Ciencias Agroalimentarias, Animales y Ambientales, Universidad de O’Higgins, San Fernando, Chile
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22
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Li Z, Lhundrup N, Guo G, Dol K, Chen P, Gao L, Chemi W, Zhang J, Wang J, Nyema T, Dawa D, Li H. Characterization of Genetic Diversity and Genome-Wide Association Mapping of Three Agronomic Traits in Qingke Barley ( Hordeum Vulgare L.) in the Qinghai-Tibet Plateau. Front Genet 2020; 11:638. [PMID: 32719715 PMCID: PMC7351530 DOI: 10.3389/fgene.2020.00638] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 05/26/2020] [Indexed: 12/18/2022] Open
Abstract
Barley (Hordeum vulgare L.) is one of the most important cereal crops worldwide. In the Qinghai-Tibet Plateau, six-rowed hulless (or naked) barley, called “qingke” in Chinese or “nas” in Tibetan, is produced mainly in Tibet. The complexity of the environment in the Qinghai-Tibet Plateau has provided unique opportunities for research on the breeding and adaptability of qingke barley. However, the genetic architecture of many important agronomic traits for qingke barley remains elusive. Heading date (HD), plant height (PH), and spike length (SL) are three prominent agronomic traits in barley. Here, we used genome-wide association (GWAS) mapping and GWAS with eigenvector decomposition (EigenGWAS) to detect quantitative trait loci (QTL) and selective signatures for HD, PH, and SL in a collection of 308 qingke barley accessions. The accessions were genotyped using a newly-developed, proprietary genotyping-by-sequencing (tGBS) technology, that yielded 14,970 high quality single nucleotide polymorphisms (SNPs). We found that the number of SNPs was higher in the varieties than in the landraces, which suggested that Tibetan varieties and varieties in the Tibetan area may have originated from different landraces in different areas. We have identified 62 QTLs associated with three important traits, and the observed phenotypic variation is well-explained by the identified QTLs. We mapped 114 known genes that include, but are not limited to, vernalization, and photoperiod genes. We found that 83.87% of the identified QTLs are located in the non-coding regulatory regions of annotated barley genes. Forty-eight of the QTLs are first reported here, 28 QTLs have pleotropic effects, and three QTL are located in the regions of the well-characterized genes HvVRN1, HvVRN3, and PpD-H2. EigenGWAS analysis revealed that multiple heading-date-related loci bear signatures of selection. Our results confirm that the barley panel used in this study is highly diverse, and showed a great promise for identifying the genetic basis of adaptive traits. This study should increase our understanding of complex traits in qingke barley, and should facilitate genome-assisted breeding for qingke barley improvement.
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Affiliation(s)
- Zhiyong Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Namgyal Lhundrup
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Tibet Academy of Agriculture and Animal Sciences, Lhasa, China
| | - Ganggang Guo
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Kar Dol
- Tibet Agricultural and Animal Husbandry College, Nyingchi, China
| | - Panpan Chen
- Tibet Agricultural and Animal Husbandry College, Nyingchi, China
| | - Liyun Gao
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Tibet Academy of Agriculture and Animal Sciences, Lhasa, China
| | - Wangmo Chemi
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Tibet Academy of Agriculture and Animal Sciences, Lhasa, China
| | - Jing Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jiankang Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tashi Nyema
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Tibet Academy of Agriculture and Animal Sciences, Lhasa, China
| | - Dondrup Dawa
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, Tibet Academy of Agriculture and Animal Sciences, Lhasa, China
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
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23
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Jarquin D, Howard R, Liang Z, Gupta SK, Schnable JC, Crossa J. Enhancing Hybrid Prediction in Pearl Millet Using Genomic and/or Multi-Environment Phenotypic Information of Inbreds. Front Genet 2020; 10:1294. [PMID: 32038702 PMCID: PMC6993057 DOI: 10.3389/fgene.2019.01294] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 11/25/2019] [Indexed: 11/30/2022] Open
Abstract
Genomic selection (GS) is an emerging methodology that helps select superior lines among experimental cultivars in plant breeding programs. It offers the opportunity to increase the productivity of cultivars by delivering increased genetic gains and reducing the breeding cycles. This methodology requires inexpensive and sufficiently dense marker information to be successful, and with whole genome sequencing, it has become an important tool in many crops. The recent assembly of the pearl millet genome has made it possible to employ GS models to improve the selection procedure in pearl millet breeding programs. Here, three GS models were implemented and compared using grain yield and dense molecular marker information of pearl millet obtained from two different genotyping platforms (C [conventional GBS RAD-seq] and T [tunable GBS tGBS]). The models were evaluated using three different cross-validation (CV) schemes mimicking real situations that breeders face in breeding programs: CV2 resembles an incomplete field trial, CV1 predicts the performance of untested hybrids, and CV0 predicts the performance of hybrids in unobserved environments. We found that (i) adding phenotypic information of parental inbreds to the calibration sets improved predictive ability, (ii) accounting for genotype-by-environment interaction also increased the performance of the models, and (iii) superior strategies should consider the use of the molecular markers derived from the T platform (tGBS).
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Affiliation(s)
- Diego Jarquin
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Reka Howard
- Department of Statistics, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Zhikai Liang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Shashi K Gupta
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - James C Schnable
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Jose Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Ciudad de Mexico, Mexico
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24
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Li J, Chen GB, Rasheed A, Li D, Sonder K, Zavala Espinosa C, Wang J, Costich DE, Schnable PS, Hearne SJ, Li H. Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS. Mol Ecol 2019; 28:3544-3560. [PMID: 31287919 PMCID: PMC6851670 DOI: 10.1111/mec.15169] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Accepted: 06/20/2019] [Indexed: 02/01/2023]
Abstract
Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding.
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Affiliation(s)
- Jing Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Guo-Bo Chen
- Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Awais Rasheed
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | - Delin Li
- Data Biotech (Beijing) Co., Ltd, Beijing, China.,College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Kai Sonder
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | | | - Jiankang Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Denise E Costich
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Patrick S Schnable
- Data Biotech (Beijing) Co., Ltd, Beijing, China.,College of Agronomy and Biotechnology, China Agricultural University, Beijing, China.,Data2Bio LLC, Ames, IA, USA.,Department of Agronomy, Iowa State University, Ames, IA, USA
| | - Sarah J Hearne
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
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