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Vaughn JN, Korani W, Clevenger J, Ozias-Akins P. Agile Genetics: Single gene resolution without the fuss. Bioessays 2024; 46:e2300206. [PMID: 38769697 DOI: 10.1002/bies.202300206] [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: 10/26/2023] [Revised: 03/06/2024] [Accepted: 05/08/2024] [Indexed: 05/22/2024]
Abstract
Gene discovery reveals new biology, expands the utility of marker-assisted selection, and enables targeted mutagenesis. Still, such discoveries can take over a decade. We present a general strategy, "Agile Genetics," that uses nested, structured populations to overcome common limits on gene resolution. Extensive simulation work on realistic genetic architectures shows that, at population sizes of >5000 samples, single gene-resolution can be achieved using bulk segregant pools. At this scale, read depth and technical replication become major drivers of resolution. Emerging enrichment methods to address coverage are on the horizon; we describe one possibility - iterative depth sequencing (ID-seq). In addition, graph-based pangenomics in experimental populations will continue to maximize accuracy and improve interpretation. Based on this merger of agronomic scale with molecular and bioinformatic innovation, we predict a new age of rapid gene discovery.
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Affiliation(s)
| | - Walid Korani
- Hudson-Alpha Institute of Biotechnology, Huntsville, Alabama, USA
| | - Josh Clevenger
- Hudson-Alpha Institute of Biotechnology, Huntsville, Alabama, USA
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Yin P, Fu X, Feng H, Yang Y, Xu J, Zhang X, Wang M, Ji S, Zhao B, Fang H, Du X, Li Y, Hu S, Li K, Xu S, Li Z, Liu F, Xiao Y, Wang Y, Li J, Yang X. Linkage and association mapping in multi-parental populations reveal the genetic basis of carotenoid variation in maize kernels. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:2312-2326. [PMID: 38548388 PMCID: PMC11258976 DOI: 10.1111/pbi.14346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 03/02/2024] [Accepted: 03/14/2024] [Indexed: 07/21/2024]
Abstract
Carotenoids are indispensable to plants and critical components of the human diet. The carotenoid metabolic pathway is conserved across plant species, but our understanding of the genetic basis of carotenoid variation remains limited for the seeds of most cereal crops. To address this issue, we systematically performed linkage and association mapping for eight carotenoid traits using six recombinant inbred line (RIL) populations. Single linkage mapping (SLM) and joint linkage mapping (JLM) identified 77 unique additive QTLs and 104 pairs of epistatic QTLs. Among these QTLs, we identified 22 overlapping hotspots of additive and epistatic loci, highlighting the important contributions of some QTLs to carotenoid levels through additive or epistatic mechanisms. A genome-wide association study based on all RILs detected 244 candidate genes significantly associated with carotenoid traits, 23 of which were annotated as carotenoid pathway genes. Effect comparisons suggested that a small number of loci linked to pathway genes have substantial effects on carotenoid variation in our tested populations, but many loci not associated with pathway genes also make important contributions to carotenoid variation. We identified ZmPTOX as the causal gene for a QTL hotspot (Q10/JLM10/GWAS019); this gene encodes a putative plastid terminal oxidase that produces plastoquinone-9 used by two enzymes in the carotenoid pathway. Natural variants in the promoter and second exon of ZmPTOX were found to alter carotenoid levels. This comprehensive assessment of the genetic mechanisms underlying carotenoid variation establishes a foundation for rewiring carotenoid metabolism and accumulation for efficient carotenoid biofortification.
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Affiliation(s)
- Pengfei Yin
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Xiuyi Fu
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular BreedingMaize Research InstituteBeijing Academy of Agriculture and Forestry Sciences (BAAFS)BeijingChina
| | - Haiying Feng
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Yanyan Yang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Jing Xu
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Xuan Zhang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Min Wang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Shenghui Ji
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Binghao Zhao
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Hui Fang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Xiaoxia Du
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Yaru Li
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Shuting Hu
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Kun Li
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Shutu Xu
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Zhigang Li
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
| | - Fang Liu
- Center for Crop Functional Genomics and Molecular BreedingChina Agricultural UniversityBeijingChina
| | - Yingni Xiao
- Crops Research InstituteGuangdong Academy of Agricultural Sciences/Guangdong Provincial Key Laboratory of Crop Genetic ImprovementGuangzhouGuangdongChina
| | - Yuandong Wang
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular BreedingMaize Research InstituteBeijing Academy of Agriculture and Forestry Sciences (BAAFS)BeijingChina
| | - Jiansheng Li
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
- Center for Crop Functional Genomics and Molecular BreedingChina Agricultural UniversityBeijingChina
| | - Xiaohong Yang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of ChinaChina Agricultural UniversityBeijingChina
- Center for Crop Functional Genomics and Molecular BreedingChina Agricultural UniversityBeijingChina
- Frontiers Science Center for Molecular Design BreedingChina Agricultural UniversityBeijingChina
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3
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Cheng S, Feng C, Wingen LU, Cheng H, Riche AB, Jiang M, Leverington-Waite M, Huang Z, Collier S, Orford S, Wang X, Awal R, Barker G, O'Hara T, Lister C, Siluveru A, Quiroz-Chávez J, Ramírez-González RH, Bryant R, Berry S, Bansal U, Bariana HS, Bennett MJ, Bicego B, Bilham L, Brown JKM, Burridge A, Burt C, Buurman M, Castle M, Chartrain L, Chen B, Denbel W, Elkot AF, Fenwick P, Feuerhelm D, Foulkes J, Gaju O, Gauley A, Gaurav K, Hafeez AN, Han R, Horler R, Hou J, Iqbal MS, Kerton M, Kondic-Spica A, Kowalski A, Lage J, Li X, Liu H, Liu S, Lovegrove A, Ma L, Mumford C, Parmar S, Philp C, Playford D, Przewieslik-Allen AM, Sarfraz Z, Schafer D, Shewry PR, Shi Y, Slafer GA, Song B, Song B, Steele D, Steuernagel B, Tailby P, Tyrrell S, Waheed A, Wamalwa MN, Wang X, Wei Y, Winfield M, Wu S, Wu Y, Wulff BBH, Xian W, Xu Y, Xu Y, Yuan Q, Zhang X, Edwards KJ, Dixon L, Nicholson P, Chayut N, Hawkesford MJ, Uauy C, Sanders D, Huang S, Griffiths S. Harnessing landrace diversity empowers wheat breeding. Nature 2024; 632:823-831. [PMID: 38885696 PMCID: PMC11338829 DOI: 10.1038/s41586-024-07682-9] [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] [Received: 09/18/2023] [Accepted: 06/06/2024] [Indexed: 06/20/2024]
Abstract
Harnessing genetic diversity in major staple crops through the development of new breeding capabilities is essential to ensure food security1. Here we examined the genetic and phenotypic diversity of the A. E. Watkins landrace collection2 of bread wheat (Triticum aestivum), a major global cereal, by whole-genome re-sequencing of 827 Watkins landraces and 208 modern cultivars and in-depth field evaluation spanning a decade. We found that modern cultivars are derived from two of the seven ancestral groups of wheat and maintain very long-range haplotype integrity. The remaining five groups represent untapped genetic sources, providing access to landrace-specific alleles and haplotypes for breeding. Linkage disequilibrium-based haplotypes and association genetics analyses link Watkins genomes to the thousands of identified high-resolution quantitative trait loci and significant marker-trait associations. Using these structured germplasm, genotyping and informatics resources, we revealed many Watkins-unique beneficial haplotypes that can confer superior traits in modern wheat. Furthermore, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritized quantitative trait loci in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilizing genetic diversity in crop improvement to achieve sustainable food security.
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Affiliation(s)
- Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
| | - Cong Feng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Hong Cheng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Mei Jiang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Zejian Huang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | - Xiaoming Wang
- John Innes Centre, Norwich, UK
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, China
| | | | - Gary Barker
- Functional Genomics, School of Biological Sciences, University of Bristol, Bristol, UK
| | | | | | | | | | | | | | | | - Urmil Bansal
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney Plant Breeding Institute, Cobbitty, New South Wales, Australia
| | - Harbans S Bariana
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney Plant Breeding Institute, Cobbitty, New South Wales, Australia
- Western Sydney University, Richmond, New South Wales, Australia
| | - Malcolm J Bennett
- School of Biosciences, University of Nottingham, Sutton Bonington, UK
| | - Breno Bicego
- Department of Agricultural and Forest Sciences and Engineering, University of Lleida-AGROTECNIO-CERCA Center, Lleida, Spain
| | | | | | - Amanda Burridge
- Functional Genomics, School of Biological Sciences, University of Bristol, Bristol, UK
| | | | | | | | | | - Baizhi Chen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Worku Denbel
- Debre Zeit Agricultural Research Center, Ethiopian Institute of Agricultural Research, Debre Zeit, Ethiopia
| | - Ahmed F Elkot
- Wheat Research Department, Field Crops Research Institute, Agricultural Research Center, Giza, Egypt
| | | | | | - John Foulkes
- School of Biosciences, University of Nottingham, Sutton Bonington, UK
| | - Oorbessy Gaju
- School of Biosciences, University of Nottingham, Sutton Bonington, UK
| | - Adam Gauley
- School of Biology, University of Leeds, Leeds, UK
- Agri-Food and Biosciences Institute, Belfast, UK
| | | | | | - Ruirui Han
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Qingdao Agricultural University, Qingdao, China
| | | | - Junliang Hou
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Muhammad S Iqbal
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Ankica Kondic-Spica
- Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Novi Sad, Republic of Serbia
| | | | | | - Xiaolong Li
- Key Laboratory of Quality and Safety Control for Subtropical Fruit and Vegetable, Ministry of Agriculture and Rural Affairs, College of Horticulture Science, Zhejiang A&F University, Hangzhou, China
| | - Hongbing Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Shiyan Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Lingling Ma
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | | | | | | | - Zareen Sarfraz
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | - Yan Shi
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Gustavo A Slafer
- Department of Agricultural and Forest Sciences and Engineering, University of Lleida-AGROTECNIO-CERCA Center, Lleida, Spain
- ICREA, Catalonian Institution for Research and Advanced Studies, Barcelona, Spain
| | - Baoxing Song
- National Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, China
| | - Bo Song
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | | | | | - Abdul Waheed
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Xingwei Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yanping Wei
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Mark Winfield
- Functional Genomics, School of Biological Sciences, University of Bristol, Bristol, UK
| | - Shishi Wu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yubing Wu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Huazhong Agricultural University, Wuhan, China
| | - Brande B H Wulff
- John Innes Centre, Norwich, UK
- Center for Desert Agriculture, Plant Science Program, Biological and Environmental Science and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Wenfei Xian
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Department of Molecular Biology, Max Planck Institute for Biology Tübingen, Tübingen, Germany
| | - Yawen Xu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Huazhong Agricultural University, Wuhan, China
| | - Yunfeng Xu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Quan Yuan
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xin Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Huazhong Agricultural University, Wuhan, China
| | - Keith J Edwards
- Functional Genomics, School of Biological Sciences, University of Bristol, Bristol, UK
| | - Laura Dixon
- School of Biology, University of Leeds, Leeds, UK
| | | | | | | | | | | | - Sanwen Huang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- State Key Laboratory of Tropical Crop Breeding, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
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4
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Hickey K, Şahin Y, Turner G, Nazarov T, Jitkov V, Pumphrey M, Smertenko A. Genotype-Specific Activation of Autophagy during Heat Wave in Wheat. Cells 2024; 13:1226. [PMID: 39056807 PMCID: PMC11274669 DOI: 10.3390/cells13141226] [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: 05/23/2024] [Revised: 07/04/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024] Open
Abstract
Recycling of unnecessary or dysfunctional cellular structures through autophagy plays a critical role in cellular homeostasis and environmental resilience. Therefore, the autophagy trait may have been unintentionally selected in wheat breeding programs for higher yields in arid climates. This hypothesis was tested by measuring the response of three common autophagy markers, ATG7, ATG8, and NBR1, to a heat wave under reduced soil moisture content in 16 genetically diverse spring wheat landraces originating from different geographical locations. We observed in the greenhouse trials that ATG8 and NBR1 exhibited genotype-specific responses to a 1 h, 40 °C heat wave, while ATG7 did not show a consistent response. Three genotypes from Uruguay, Mozambique, and Afghanistan showed a pattern consistent with higher autophagic activity: decreased or stable abundance of both ATG8 and NBR1 proteins, coupled with increased transcription of ATG8 and NBR1. In contrast, three genotypes from Pakistan, Ethiopia, and Egypt exhibited elevated ATG8 protein levels alongside reduced or unaltered ATG8 transcript levels, indicating a potential suppression or no change in autophagic activity. Principal component analysis demonstrated a correlation between lower abundance of ATG8 and NBR1 proteins and higher yield in the field trials. We found that (i) the combination of heat and drought activated autophagy only in several genotypes, suggesting that despite being a resilience mechanism, autophagy is a heat-sensitive process; (ii) higher autophagic activity correlates positively with greater yield; (iii) the lack of autophagic activity in some high-yielding genotypes suggests contribution of alternative stress-resilient mechanisms; and (iv) enhanced autophagic activity in response to heat and drought was independently selected by wheat breeding programs in different geographic locations.
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Affiliation(s)
- Kathleen Hickey
- Institute of Biological Chemistry, Washington State University, Pullman, WA 99163, USA (Y.Ş.); (G.T.); (T.N.)
| | - Yunus Şahin
- Institute of Biological Chemistry, Washington State University, Pullman, WA 99163, USA (Y.Ş.); (G.T.); (T.N.)
| | - Glenn Turner
- Institute of Biological Chemistry, Washington State University, Pullman, WA 99163, USA (Y.Ş.); (G.T.); (T.N.)
| | - Taras Nazarov
- Institute of Biological Chemistry, Washington State University, Pullman, WA 99163, USA (Y.Ş.); (G.T.); (T.N.)
| | - Vadim Jitkov
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99163, USA; (V.J.); (M.P.)
| | - Mike Pumphrey
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99163, USA; (V.J.); (M.P.)
| | - Andrei Smertenko
- Institute of Biological Chemistry, Washington State University, Pullman, WA 99163, USA (Y.Ş.); (G.T.); (T.N.)
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Boyle JA, Frederickson ME, Stinchcombe JR. Genetic architecture of heritable leaf microbes. Microbiol Spectr 2024; 12:e0061024. [PMID: 38842309 PMCID: PMC11218475 DOI: 10.1128/spectrum.00610-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 05/02/2024] [Indexed: 06/07/2024] Open
Abstract
Host-associated microbiomes are shaped by both their environment and host genetics, and often impact host performance. The scale of host genetic variation important to microbes is largely unknown yet fundamental to the community assembly of host-associated microbiomes, with implications for the eco-evolutionary dynamics of microbes and hosts. Using Ipomoea hederacea, ivyleaf morning glory, we generated matrilines differing in quantitative genetic variation and leaf shape, which is controlled by a single Mendelian locus. We then investigated the relative roles of Mendelian and quantitative genetic variation in structuring the leaf microbiome and how these two sources of genetic variation contributed to microbe heritability. We found that despite large effects of the environment, both Mendelian and quantitative genetic host variation contribute to microbe heritability and that the cumulative small effect genomic differences due to matriline explained as much or more microbial variation than a single large effect Mendelian locus. Furthermore, our results are the first to suggest that leaf shape itself contributes to variation in the abundances of some phyllosphere microbes.IMPORTANCEWe investigated how host genetic variation affects the assembly of Ipomoea hederacea's natural microbiome. We found that the genetic architecture of leaf-associated microbiomes involves both quantitative genetic variation and Mendelian traits, with similar contributions to microbe heritability. The existence of Mendelian and quantitative genetic variation for host-associated microbes means that plant evolution at the leaf shape locus or other quantitative genetic loci has the potential to shape microbial abundance and community composition.
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Affiliation(s)
- Julia A Boyle
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
| | - Megan E Frederickson
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
| | - John R Stinchcombe
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
- Swedish Collegium for Advanced Study, Uppsala, Sweden
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Chen J, Zhang Y, Wei J, Hu X, Yin H, Liu W, Li D, Tian W, Hao Y, He Z, Fernie AR, Chen W. Beyond pathways: Accelerated flavonoids candidate identification and novel exploration of enzymatic properties using combined mapping populations of wheat. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:2033-2050. [PMID: 38408119 PMCID: PMC11182594 DOI: 10.1111/pbi.14323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 02/06/2024] [Accepted: 02/12/2024] [Indexed: 02/28/2024]
Abstract
Although forward-genetics-metabolomics methods such as mGWAS and mQTL have proven effective in providing myriad loci affecting metabolite contents, they are somehow constrained by their respective constitutional flaws such as the hidden population structure for GWAS and insufficient recombinant rate for QTL. Here, the combination of mGWAS and mQTL was performed, conveying an improved statistical power to investigate the flavonoid pathways in common wheat. A total of 941 and 289 loci were, respectively, generated from mGWAS and mQTL, within which 13 of them were co-mapped using both approaches. Subsequently, the mGWAS or mQTL outputs alone and their combination were, respectively, utilized to delineate the metabolic routes. Using this approach, we identified two MYB transcription factor encoding genes and five structural genes, and the flavonoid pathway in wheat was accordingly updated. Moreover, we have discovered some rare-activity-exhibiting flavonoid glycosyl- and methyl-transferases, which may possess unique biological significance, and harnessing these novel catalytic capabilities provides potentially new breeding directions. Collectively, we propose our survey illustrates that the forward-genetics-metabolomics approaches including multiple populations with high density markers could be more frequently applied for delineating metabolic pathways in common wheat, which will ultimately contribute to metabolomics-assisted wheat crop improvement.
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Affiliation(s)
- Jie Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
- Yazhouwan National LaboratorySanyaChina
| | - Yueqi Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
| | - Jiaqi Wei
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
- Wuhan Academy of Agricultural SciencesWuhanChina
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
| | - Huanran Yin
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
| | - Wei Liu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
| | - Dongqin Li
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
| | - Wenfei Tian
- National Wheat Improvement Center, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yuanfeng Hao
- National Wheat Improvement Center, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Zhonghu He
- National Wheat Improvement Center, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | | | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
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7
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Davis RF, Harris-Shultz K, Knoll JE, Krakowsky M, Scully B. A Quantitative Trait Locus on Maize Chromosome 5 Is Associated with Root-Knot Nematode Resistance. PHYTOPATHOLOGY 2024; 114:1657-1663. [PMID: 38427606 DOI: 10.1094/phyto-08-23-0286-r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
Abstract
This study provides the first report of a quantitative trait locus (QTL) in maize (Zea mays) for resistance to the southern root-knot nematode (SRKN) (Meloidogyne incognita). The SRKN can feed on the roots of maize in the U.S. Southern Coastal Plain region and can cause yield losses of 30% or more in heavily infested fields. Increases in SRKN density in the soil may reduce the yield for subsequently planted susceptible crops. The use of maize hybrids with resistance to SRKN could prevent an increase in SRKN density, yet no genetic regions have been identified that confer host resistance. In this study, a B73 (susceptible) × Ky21 (resistant) S5 recombinant inbred line (RIL) population was phenotyped for total number of eggs (TE) and root weight. This population had been genotyped using single-nucleotide polymorphisms (SNPs). By utilizing the SNP data with the phenotype data, a single QTL was identified on chromosome 5 that explained 15% of the phenotypic variation (PV) for the number of eggs and 11% of the PV for the number of eggs per gram of root (EGR). Plants that were homozygous for the Ky21 allele for the most associated marker PZA03172.3 had fewer eggs and fewer EGR than the plants that were homozygous or heterozygous for the B73 allele. Thus, the first QTL for SRKN resistance in maize has been identified and could be incorporated into maize hybrids.
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Affiliation(s)
- Richard F Davis
- U.S. Department of Agriculture-Agricultural Research Service, Crop Genetics and Breeding Research Unit, Tifton, GA
| | - Karen Harris-Shultz
- U.S. Department of Agriculture-Agricultural Research Service, Crop Genetics and Breeding Research Unit, Tifton, GA
| | - Joseph E Knoll
- U.S. Department of Agriculture-Agricultural Research Service, Crop Genetics and Breeding Research Unit, Tifton, GA
| | - Matthew Krakowsky
- U.S. Department of Agriculture-Agricultural Research Service, Plant Science Research Unit, Raleigh, NC
| | - Brian Scully
- U.S. Department of Agriculture-Agricultural Research Service, U.S. Horticultural Research Laboratory, Fort Pierce, FL (retired)
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8
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Jiang C, Zhao G, Wang H, Zheng W, Zhang R, Wang L, Zheng Z. Comparative genomics analysis and transposon mutagenesis provides new insights into high menaquinone-7 biosynthetic potential of Bacillus subtilis natto. Gene 2024; 907:148264. [PMID: 38346457 DOI: 10.1016/j.gene.2024.148264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 02/15/2024]
Abstract
This research combined Whole-Genome sequencing, intraspecific comparative genomics and transposon mutagenesis to investigate the menaquinone-7 (MK-7) synthesis potential in Bacillus subtilis natto. First, Whole-Genome sequencing showed that Bacillus subtilis natto BN-P15-11-1 contains one single circular chromosome in size of 3,982,436 bp with a GC content of 43.85 %, harboring 4,053 predicted coding genes. Next, the comparative genomics analysis among strain BN-P15-11-1 with model Bacillus subtilis 168 and four typical Bacillus subtilis natto strains proves that the closer evolutionary relationship Bacillus subtilis natto BN-P15-11-1 and Bacillus subtilis 168 both exhibit strong biosynthetic potential. To further dig for MK-7 biosynthesis latent capacity of BN-P15-11-1, we constructed a mutant library using transposons and a high throughput screening method using microplates. We obtained a YqgQ deficient high MK-7 yield strain F4 with a yield 3.02 times that of the parent strain. Experiments also showed that the high yield mutants had defects in different transcription and translation regulatory factor genes, indicating that regulatory factor defects may affect the biosynthesis and accumulation of MK-7 by altering the overall metabolic level. The findings of this study will provide more novel insights on the precise identification and rational utilization of the Bacillus subtilis subspecies for biosynthesis latent capacity.
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Affiliation(s)
- Chunxu Jiang
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China; University of Science and Technology of China, Hefei, Anhui, PR China
| | - Genhai Zhao
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China
| | - Han Wang
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China
| | - Wenqian Zheng
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China; University of Science and Technology of China, Hefei, Anhui, PR China
| | - Rui Zhang
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China
| | - Li Wang
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China.
| | - Zhiming Zheng
- Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, PR China.
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9
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Yin B, Jia J, Sun X, Hu X, Ao M, Liu W, Tian Z, Liu H, Li D, Tian W, Hao Y, Xia X, Sade N, Brotman Y, Fernie AR, Chen J, He Z, Chen W. Dynamic metabolite QTL analyses provide novel biochemical insights into kernel development and nutritional quality improvement in common wheat. PLANT COMMUNICATIONS 2024; 5:100792. [PMID: 38173227 PMCID: PMC11121174 DOI: 10.1016/j.xplc.2024.100792] [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: 08/20/2023] [Revised: 12/20/2023] [Accepted: 01/01/2024] [Indexed: 01/05/2024]
Abstract
Despite recent advances in crop metabolomics, the genetic control and molecular basis of the wheat kernel metabolome at different developmental stages remain largely unknown. Here, we performed widely targeted metabolite profiling of kernels from three developmental stages (grain-filling kernels [FKs], mature kernels [MKs], and germinating kernels [GKs]) using a population of 159 recombinant inbred lines. We detected 625 annotated metabolites and mapped 3173, 3143, and 2644 metabolite quantitative trait loci (mQTLs) in FKs, MKs, and GKs, respectively. Only 52 mQTLs were mapped at all three stages, indicating the high stage specificity of the wheat kernel metabolome. Four candidate genes were functionally validated by in vitro enzymatic reactions and/or transgenic approaches in wheat, three of which mediated the tricin metabolic pathway. Metabolite flux efficiencies within the tricin pathway were evaluated, and superior candidate haplotypes were identified, comprehensively delineating the tricin metabolism pathway in wheat. Finally, additional wheat metabolic pathways were re-constructed by updating them to incorporate the 177 candidate genes identified in this study. Our work provides new information on variations in the wheat kernel metabolome and important molecular resources for improvement of wheat nutritional quality.
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Affiliation(s)
- Bo Yin
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Jingqi Jia
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Xu Sun
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Min Ao
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Wei Liu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Zhitao Tian
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Hongbo Liu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Dongqin Li
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wenfei Tian
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuanfeng Hao
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xianchun Xia
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Nir Sade
- School of Plant Sciences and Food Security, The Institute for Cereal Crops Improvement, Tel Aviv University, Tel Aviv 69978, Israel
| | - Yariv Brotman
- School of Plant Sciences and Food Security, The Institute for Cereal Crops Improvement, Tel Aviv University, Tel Aviv 69978, Israel
| | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Jie Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China; Yazhouwan National Laboratory, Sanya 572025, China.
| | - Zhonghu He
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
| | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China.
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10
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Cannon EK, Portwood JL, Hayford RK, Haley OC, Gardiner JM, Andorf CM, Woodhouse MR. Enhanced pan-genomic resources at the maize genetics and genomics database. Genetics 2024; 227:iyae036. [PMID: 38577974 DOI: 10.1093/genetics/iyae036] [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: 11/13/2023] [Accepted: 01/13/2024] [Indexed: 04/06/2024] Open
Abstract
Pan-genomes, encompassing the entirety of genetic sequences found in a collection of genomes within a clade, are more useful than single reference genomes for studying species diversity. This is especially true for a species like Zea mays, which has a particularly diverse and complex genome. Presenting pan-genome data, analyses, and visualization is challenging, especially for a diverse species, but more so when pan-genomic data is linked to extensive gene model and gene data, including classical gene information, markers, insertions, expression and proteomic data, and protein structures as is the case at MaizeGDB. Here, we describe MaizeGDB's expansion to include the genic subset of the Zea pan-genome in a pan-gene data center featuring the maize genomes hosted at MaizeGDB, and the outgroup teosinte Zea genomes from the Pan-Andropoganeae project. The new data center offers a variety of browsing and visualization tools, including sequence alignment visualization, gene trees and other tools, to explore pan-genes in Zea that were calculated by the pipeline Pandagma. Combined, these data will help maize researchers study the complexity and diversity of Zea, and to use the comparative functions to validate pan-gene relationships for a selected gene model.
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Affiliation(s)
- Ethalinda K Cannon
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, USA
| | - John L Portwood
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, USA
| | - Rita K Hayford
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, USA
| | - Olivia C Haley
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, USA
| | - Jack M Gardiner
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
| | - Carson M Andorf
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, USA
- Department of Computer Science, Iowa State University, Ames, IA 50011, USA
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11
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Paterson AH, Queitsch C. Genome organization and botanical diversity. THE PLANT CELL 2024; 36:1186-1204. [PMID: 38382084 PMCID: PMC11062460 DOI: 10.1093/plcell/koae045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 02/07/2024] [Accepted: 02/07/2024] [Indexed: 02/23/2024]
Abstract
The rich diversity of angiosperms, both the planet's dominant flora and the cornerstone of agriculture, is integrally intertwined with a distinctive evolutionary history. Here, we explore the interplay between angiosperm genome organization and botanical diversity, empowered by genomic approaches ranging from genetic linkage mapping to analysis of gene regulation. Commonality in the genetic hardware of plants has enabled robust comparative genomics that has provided a broad picture of angiosperm evolution and implicated both general processes and specific elements in contributing to botanical diversity. We argue that the hardware of plant genomes-both in content and in dynamics-has been shaped by selection for rather substantial differences in gene regulation between plants and animals such as maize and human, organisms of comparable genome size and gene number. Their distinctive genome content and dynamics may reflect in part the indeterminate development of plants that puts strikingly different demands on gene regulation than in animals. Repeated polyploidization of plant genomes and multiplication of individual genes together with extensive rearrangement and differential retention provide rich raw material for selection of morphological and/or physiological variations conferring fitness in specific niches, whether natural or artificial. These findings exemplify the burgeoning information available to employ in increasing knowledge of plant biology and in modifying selected plants to better meet human needs.
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Affiliation(s)
- Andrew H Paterson
- Plant Genome Mapping Laboratory, University of Georgia, Athens, GA, USA
| | - Christine Queitsch
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
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12
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Garin V, Diallo C, Tékété ML, Théra K, Guitton B, Dagno K, Diallo AG, Kouressy M, Leiser W, Rattunde F, Sissoko I, Touré A, Nébié B, Samaké M, Kholovà J, Berger A, Frouin J, Pot D, Vaksmann M, Weltzien E, Témé N, Rami JF. Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping. Genetics 2024; 226:iyae003. [PMID: 38381593 PMCID: PMC10990433 DOI: 10.1093/genetics/iyae003] [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: 10/19/2023] [Accepted: 12/20/2023] [Indexed: 02/23/2024] Open
Abstract
Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.
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Affiliation(s)
- Vincent Garin
- Crop Physiology Laboratory, International Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502 324, India
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Chiaka Diallo
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
- Département d’Enseignement et de Recherche des Sciences et Techniques Agricoles, Institut polytechnique rural de formation et de recherche appliquée de Katibougou, Koulikoro, BP 06, Mali
| | - Mohamed Lamine Tékété
- Institut d’Economie Rurale, Bamako, BP 262, Mali
- Faculté des Sciences et Techniques, Université des Sciences des Techniques et des Technologies de Bamako, Bamako, BP E 3206, Mali
| | | | - Baptiste Guitton
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Karim Dagno
- Institut d’Economie Rurale, Bamako, BP 262, Mali
| | | | | | - Willmar Leiser
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
| | - Fred Rattunde
- Agronomy Department, University of Wisconsin, Madison, WI 53705, WI, USA
| | - Ibrahima Sissoko
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
| | - Aboubacar Touré
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
| | - Baloua Nébié
- Dryland Crops Program, International Maize and Wheat Improvement Center (CIMMYT-Senegal) U/C CERAAS, Thiès, Po Box 3320, Senegal
| | - Moussa Samaké
- Faculté des Sciences et Techniques, Université des Sciences des Techniques et des Technologies de Bamako, Bamako, BP E 3206, Mali
| | - Jana Kholovà
- Crop Physiology Laboratory, International Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502 324, India
- Department of Information Technologies, Faculty of Economics and Management, Czech University of Life Sciences, Prague, 165 00, Czech Republic
| | - Angélique Berger
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Julien Frouin
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - David Pot
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Michel Vaksmann
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
| | - Eva Weltzien
- Sorghum Program, International Crops Research Institute for the Semi-Arid Tropics, Bamako, BP 320, Mali
- Agronomy Department, University of Wisconsin, Madison, WI 53705, WI, USA
| | - Niaba Témé
- Institut d’Economie Rurale, Bamako, BP 262, Mali
| | - Jean-François Rami
- CIRAD, UMR AGAP Institut, Montpellier, F-34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France
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13
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Wright TIC, Horsnell R, Love B, Burridge AJ, Gardner KA, Jackson R, Leigh FJ, Ligeza A, Heuer S, Bentley AR, Howell P. A new winter wheat genetic resource harbors untapped diversity from synthetic hexaploid wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:73. [PMID: 38451354 PMCID: PMC10920491 DOI: 10.1007/s00122-024-04577-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 02/06/2024] [Indexed: 03/08/2024]
Abstract
KEY MESSAGE The NIAB_WW_SHW_NAM population, a large nested association mapping panel, is a useful resource for mapping QTL from synthetic hexaploid wheat that can improve modern elite wheat cultivars. The allelic richness harbored in progenitors of hexaploid bread wheat (Triticum aestivum L.) is a useful resource for addressing the genetic diversity bottleneck in modern cultivars. Synthetic hexaploid wheat (SHW) is created through resynthesis of the hybridisation events between the tetraploid (Triticum turgidum subsp. durum Desf.) and diploid (Aegilops tauschii Coss.) bread wheat progenitors. We developed a large and diverse winter wheat nested association mapping (NAM) population (termed the NIAB_WW_SHW_NAM) consisting of 3241 genotypes derived from 54 nested back-cross 1 (BC1) populations, each formed via back-crossing a different primary SHW into the UK winter wheat cultivar 'Robigus'. The primary SHW lines were created using 15 T. durum donors and 47 Ae. tauschii accessions that spanned the lineages and geographical range of the species. Primary SHW parents were typically earlier flowering, taller and showed better resistance to yellow rust infection (Yr) than 'Robigus'. The NIAB_WW_SHW_NAM population was genotyped using a single nucleotide polymorphism (SNP) array and 27 quantitative trait loci (QTLs) were detected for flowering time, plant height and Yr resistance. Across multiple field trials, a QTL for Yr resistance was found on chromosome 4D that corresponded to the Yr28 resistance gene previously reported in other SHW lines. These results demonstrate the value of the NIAB_WW_SHW_NAM population for genetic mapping and provide the first evidence of Yr28 working in current UK environments and genetic backgrounds. These examples, coupled with the evidence of commercial wheat breeders selecting promising genotypes, highlight the potential value of the NIAB_WW_SHW_NAM to variety improvement.
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Affiliation(s)
- Tally I C Wright
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK.
| | - Richard Horsnell
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Bethany Love
- 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
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Mexico
| | - Robert Jackson
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Fiona J Leigh
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Aleksander Ligeza
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
- Processors and Growers Research Organization (PGRO), The Research Station, Thornhaugh, Peterborough, PE8 6HJ, UK
| | - Sigrid Heuer
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Alison R Bentley
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
- Research School of Biology, Australian National University, Canberra, ACT, 2600, Australia
| | - Philip Howell
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
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14
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Zhao B, Li K, Wang M, Liu Z, Yin P, Wang W, Li Z, Li X, Zhang L, Han Y, Li J, Yang X. Genetic basis of maize stalk strength decoded via linkage and association mapping. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024; 117:1558-1573. [PMID: 38113320 DOI: 10.1111/tpj.16583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 11/20/2023] [Accepted: 11/26/2023] [Indexed: 12/21/2023]
Abstract
Stalk lodging is a severe problem that limits maize production worldwide, although little attention has been given to its genetic basis. Here we measured rind penetrometer resistance (RPR), an effective index for stalk lodging, in a multi-parent population of 1948 recombinant inbred lines (RILs) and an association population of 508 inbred lines (AMP508). Linkage and association mapping identified 53 and 29 single quantitative trait loci (QTLs) and 50 and 19 pairs of epistatic interactions for RPR in the multi-parent population and AMP508 population, respectively. Phenotypic variation explained by all identified epistatic QTLs (up to ~5%) was much less than that explained by all single additive QTLs (up to ~33% in the multi-parent population and ~ 60% in the AMP508 population). Among all detected QTLs, only eight single QTLs explained >10% of phenotypic variation in single RIL populations. Alleles that increased RPR were enriched in tropical/subtropical (TST) groups from the AMP508 population. Based on genome-wide association studies in both populations, we identified 137 candidate genes affecting RPR, which were assigned to multiple biological processes, such as the biosynthesis of cell wall components. Sixty-six candidate genes were cross-validated by multiple methods or populations. Most importantly, 23 candidate genes were upregulated or downregulated in high-RPR lines relative to low-RPR lines, supporting the associations between candidate genes and RPR. These findings reveal the complex nature of the genetic basis underlying RPR and provide loci or candidate genes for developing elite varieties that are resistant to stalk lodging via molecular breeding.
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Affiliation(s)
- Binghao Zhao
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Kun Li
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Min Wang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Zhiyuan Liu
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Pengfei Yin
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Weidong Wang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Zhigang Li
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Xiaowei Li
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Lili Zhang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Yingjia Han
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China
| | - Jiansheng Li
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
| | - Xiaohong Yang
- State Key Laboratory of Plant Environmental Resilience and National Maize Improvement Center of China, China Agricultural University, Beijing, 100193, China
- Frontiers Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China
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15
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Thudi M, Samineni S, Li W, Boer MP, Roorkiwal M, Yang Z, Ladejobi F, Zheng C, Chitikineni A, Nayak S, He Z, Valluri V, Bajaj P, Khan AW, Gaur PM, van Eeuwijk F, Mott R, Xin L, Varshney RK. Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea. THE PLANT GENOME 2024; 17:e20333. [PMID: 37122200 DOI: 10.1002/tpg2.20333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 02/17/2023] [Accepted: 03/09/2023] [Indexed: 06/19/2023]
Abstract
Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.
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Affiliation(s)
- Mahendar Thudi
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- Department of Agricultural Biotechnology and Molecular Biology, Dr. Rajendra Prasad Central Agricultural University (RPCAU), Pusa, India
| | - Srinivasan Samineni
- Crop Improvement Program-Asia, ICRISAT, Patancheru, India
- International Center for Biosaline Agriculture, Dubai, United Arab Emirates
| | - Wenhao Li
- Wageningen University and Research, Wageningen, The Netherlands
| | - Martin P Boer
- Wageningen University and Research, Wageningen, The Netherlands
| | - Manish Roorkiwal
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- Khalifa Center for Genetic Engineering and Biotechnology (KCGEB), United Arab Emirates University, Al Ain, United Arab Emirates
| | | | - Funmi Ladejobi
- Department of Genetics, Evolution and Environment, Genetics Institute, University College London, London, UK
| | - Chaozhi Zheng
- Wageningen University and Research, Wageningen, The Netherlands
- BGI-Shenzhen, Shenzhen, China
| | - Annapurna Chitikineni
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Sourav Nayak
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | | | - Vinod Valluri
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Prasad Bajaj
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Aamir W Khan
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
| | - Pooran M Gaur
- Department of Agricultural Biotechnology and Molecular Biology, Dr. Rajendra Prasad Central Agricultural University (RPCAU), Pusa, India
- The UWA Institute of Agriculture, University of Western Australia, Perth, Western Australia, Australia
| | | | - Richard Mott
- Department of Genetics, Evolution and Environment, Genetics Institute, University College London, London, UK
| | - Liu Xin
- BGI-Shenzhen, Shenzhen, China
| | - Rajeev K Varshney
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
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16
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Martina M, De Rosa V, Magon G, Acquadro A, Barchi L, Barcaccia G, De Paoli E, Vannozzi A, Portis E. Revitalizing agriculture: next-generation genotyping and -omics technologies enabling molecular prediction of resilient traits in the Solanaceae family. FRONTIERS IN PLANT SCIENCE 2024; 15:1278760. [PMID: 38375087 PMCID: PMC10875072 DOI: 10.3389/fpls.2024.1278760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 01/22/2024] [Indexed: 02/21/2024]
Abstract
This review highlights -omics research in Solanaceae family, with a particular focus on resilient traits. Extensive research has enriched our understanding of Solanaceae genomics and genetics, with historical varietal development mainly focusing on disease resistance and cultivar improvement but shifting the emphasis towards unveiling resilience mechanisms in genebank-preserved germplasm is nowadays crucial. Collecting such information, might help researchers and breeders developing new experimental design, providing an overview of the state of the art of the most advanced approaches for the identification of the genetic elements laying behind resilience. Building this starting point, we aim at providing a useful tool for tackling the global agricultural resilience goals in these crops.
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Affiliation(s)
- Matteo Martina
- Department of Agricultural, Forest and Food Sciences (DISAFA), Plant Genetics, University of Torino, Grugliasco, Italy
| | - Valeria De Rosa
- Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, Udine, Italy
| | - Gabriele Magon
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Laboratory of Plant Genetics and Breeding, University of Padua, Legnaro, Italy
| | - Alberto Acquadro
- Department of Agricultural, Forest and Food Sciences (DISAFA), Plant Genetics, University of Torino, Grugliasco, Italy
| | - Lorenzo Barchi
- Department of Agricultural, Forest and Food Sciences (DISAFA), Plant Genetics, University of Torino, Grugliasco, Italy
| | - Gianni Barcaccia
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Laboratory of Plant Genetics and Breeding, University of Padua, Legnaro, Italy
| | - Emanuele De Paoli
- Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, Udine, Italy
| | - Alessandro Vannozzi
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Laboratory of Plant Genetics and Breeding, University of Padua, Legnaro, Italy
| | - Ezio Portis
- Department of Agricultural, Forest and Food Sciences (DISAFA), Plant Genetics, University of Torino, Grugliasco, Italy
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17
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Mantel SJ, Sweigart AL. Postzygotic barriers persist despite ongoing introgression in hybridizing Mimulus species. Mol Ecol 2024; 33:e17261. [PMID: 38174628 PMCID: PMC10922885 DOI: 10.1111/mec.17261] [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: 09/27/2023] [Revised: 12/04/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024]
Abstract
The evolution of postzygotic isolation is thought to be a key step in maintaining species boundaries upon secondary contact, yet the dynamics and persistence of hybrid incompatibilities in naturally hybridizing species are not well understood. Here, we explore these issues using genetic mapping in three independent populations of recombinant inbred lines between naturally hybridizing monkeyflowers, Mimulus guttatus and Mimulus nasutus, from the sympatric Catherine Creek population. We discover that the three M. guttatus founders differ dramatically in admixture history, with nearly a quarter of one founder's genome introgressed from M. nasutus. Comparative genetic mapping in the three RIL populations reveals three new putative inversions, each one segregating among the M. guttatus founders, two due to admixture. We find strong, genome-wide transmission ratio distortion in all RILs, but patterns are highly variable among the three populations. At least some of this distortion appears to be explained by epistatic selection favouring parental genotypes, but tests of inter-chromosomal linkage disequilibrium also reveal multiple candidate Dobzhansky-Muller incompatibilities. We also map several genetic loci for hybrid pollen viability, including two interacting pairs that coincide with peaks of distortion. Remarkably, even with this limited sample of three M. guttatus lines, we discover abundant segregating variation for hybrid incompatibilities with M. nasutus, suggesting this population harbours diverse contributors to postzygotic isolation. Moreover, even with substantial admixture, hybrid incompatibilities between Mimulus species persist, suggesting postzygotic isolation might be a potent force in maintaining species barriers in this system.
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Affiliation(s)
- Samuel J. Mantel
- Department of Genetics, University of Georgia, Athens, GA, 30602, USA
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18
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Fattel L, Yanarella CF, Ngara B, Johnson OT, Campbell DA, Wimalanathan K, Lawrence-Dill CJ. Gene function annotations for the maize NAM founder lines. BMC Res Notes 2024; 17:9. [PMID: 38167110 PMCID: PMC10762836 DOI: 10.1186/s13104-023-06668-6] [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: 08/21/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
OBJECTIVES We annotated the latest published sequences of the 26 Zea mays Nested Association Mapping (NAM) founder lines using GOMAP, the Gene Ontology Meta Annotator for Plants. The maize NAM panel enables researchers to understand and identify the genetic basis of complex traits. Annotations of predicted functions for genes can help researchers investigate gene-phenotype associations, prioritize candidate genes for phenotypes of interest, and formulate testable hypotheses about gene function/phenotype associations. The creation and release of high-confidence, high-coverage gene function annotation sets for the NAM founder lines is critical to accelerate the generation of knowledge in maize genetics research. GOMAP is a high-throughput computational pipeline that annotates gene functions genome-wide in plant genomes using Gene Ontology functional class terms. Here we report and share GOMAP-generated functional annotations for the NAM founder lines. DATA DESCRIPTION Datasets include the protein sequences used as input, GOMAP-generated annotation files, scripts used to update obsolete terms, and GAF-formatted tab-delimited text files of gene function annotations along with README files that describe formatting, content, and how files relate to each other.
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Affiliation(s)
- Leila Fattel
- Interdepartmental Genetics and Genomics, Iowa State University, Ames, IA, USA
- Department of Agronomy, Iowa State University, Ames, IA, USA
- College of Agriculture and Life Sciences, Iowa State University, Ames, IA, USA
| | - Colleen F Yanarella
- Department of Agronomy, Iowa State University, Ames, IA, USA
- College of Agriculture and Life Sciences, Iowa State University, Ames, IA, USA
- Interdepartmental Bioinformatics and Computational Biology, Iowa State University, Ames, IA, USA
| | - Blessing Ngara
- Department of Computer Science, Iowa State University, Ames, IA, USA
- College of Liberal Arts and Sciences, Iowa State University, Ames, IA, USA
| | - Olivia T Johnson
- College of Liberal Arts and Sciences, Iowa State University, Ames, IA, USA
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA, USA
| | - Darwin A Campbell
- College of Agriculture and Life Sciences, Iowa State University, Ames, IA, USA
| | - Kokulapalan Wimalanathan
- Interdepartmental Bioinformatics and Computational Biology, Iowa State University, Ames, IA, USA
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA, USA
- Neuroscience Team, Atalanta Therapeutics, Boston, MA, USA
| | - Carolyn J Lawrence-Dill
- Interdepartmental Genetics and Genomics, Iowa State University, Ames, IA, USA.
- Department of Agronomy, Iowa State University, Ames, IA, USA.
- College of Agriculture and Life Sciences, Iowa State University, Ames, IA, USA.
- Interdepartmental Bioinformatics and Computational Biology, Iowa State University, Ames, IA, USA.
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA, USA.
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19
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Tanaka R, Wu D, Li X, Tibbs-Cortes LE, Wood JC, Magallanes-Lundback M, Bornowski N, Hamilton JP, Vaillancourt B, Li X, Deason NT, Schoenbaum GR, Buell CR, DellaPenna D, Yu J, Gore MA. Leveraging prior biological knowledge improves prediction of tocochromanols in maize grain. THE PLANT GENOME 2023; 16:e20276. [PMID: 36321716 DOI: 10.1002/tpg2.20276] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 09/21/2022] [Indexed: 06/16/2023]
Abstract
With an essential role in human health, tocochromanols are mostly obtained by consuming seed oils; however, the vitamin E content of the most abundant tocochromanols in maize (Zea mays L.) grain is low. Several large-effect genes with cis-acting variants affecting messenger RNA (mRNA) expression are mostly responsible for tocochromanol variation in maize grain, with other relevant associated quantitative trait loci (QTL) yet to be fully resolved. Leveraging existing genomic and transcriptomic information for maize inbreds could improve prediction when selecting for higher vitamin E content. Here, we first evaluated a multikernel genomic best linear unbiased prediction (MK-GBLUP) approach for modeling known QTL in the prediction of nine tocochromanol grain phenotypes (12-21 QTL per trait) within and between two panels of 1,462 and 242 maize inbred lines. On average, MK-GBLUP models improved predictive abilities by 7.0-13.6% when compared with GBLUP. In a second approach with a subset of 545 lines from the larger panel, the highest average improvement in predictive ability relative to GBLUP was achieved with a multi-trait GBLUP model (15.4%) that had a tocochromanol phenotype and transcript abundances in developing grain for a few large-effect candidate causal genes (1-3 genes per trait) as multiple response variables. Taken together, our study illustrates the enhancement of prediction models when informed by existing biological knowledge pertaining to QTL and candidate causal genes.
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Affiliation(s)
- Ryokei Tanaka
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell Univ., Ithaca, NY, 14853, USA
| | - Di Wu
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell Univ., Ithaca, NY, 14853, USA
| | - Xiaowei Li
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell Univ., Ithaca, NY, 14853, USA
| | | | - Joshua C Wood
- Institute for Plant Breeding, Genetics & Genomics, Center for Applied Genetic Technologies, Dep. of Crop & Soil Sciences, Univ. of Georgia, Athens, GA, 30602, USA
| | | | - Nolan Bornowski
- Dep. of Plant Biology, Michigan State Univ., East Lansing, MI, 48824, USA
| | - John P Hamilton
- Institute for Plant Breeding, Genetics & Genomics, Center for Applied Genetic Technologies, Dep. of Crop & Soil Sciences, Univ. of Georgia, Athens, GA, 30602, USA
| | - Brieanne Vaillancourt
- Institute for Plant Breeding, Genetics & Genomics, Center for Applied Genetic Technologies, Dep. of Crop & Soil Sciences, Univ. of Georgia, Athens, GA, 30602, USA
| | - Xianran Li
- USDA ARS, Wheat Health, Genetics, and Quality Research Unit, Pullman, WA, 99164, USA
| | - Nicholas T Deason
- Dep. of Biochemistry and Molecular Biology, Michigan State Univ., East Lansing, MI, 48824, USA
| | | | - C Robin Buell
- Institute for Plant Breeding, Genetics & Genomics, Center for Applied Genetic Technologies, Dep. of Crop & Soil Sciences, Univ. of Georgia, Athens, GA, 30602, USA
| | - Dean DellaPenna
- Dep. of Biochemistry and Molecular Biology, Michigan State Univ., East Lansing, MI, 48824, USA
| | - Jianming Yu
- Dep. of Agronomy, Iowa State Univ., Ames, IA, 50011, USA
| | - Michael A Gore
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell Univ., Ithaca, NY, 14853, USA
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20
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Minow MAA, Marand AP, Schmitz RJ. Leveraging Single-Cell Populations to Uncover the Genetic Basis of Complex Traits. Annu Rev Genet 2023; 57:297-319. [PMID: 37562412 PMCID: PMC10775913 DOI: 10.1146/annurev-genet-022123-110824] [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] [Indexed: 08/12/2023]
Abstract
The ease and throughput of single-cell genomics have steadily improved, and its current trajectory suggests that surveying single-cell populations will become routine. We discuss the merger of quantitative genetics with single-cell genomics and emphasize how this synergizes with advantages intrinsic to plants. Single-cell population genomics provides increased detection resolution when mapping variants that control molecular traits, including gene expression or chromatin accessibility. Additionally, single-cell population genomics reveals the cell types in which variants act and, when combined with organism-level phenotype measurements, unveils which cellular contexts impact higher-order traits. Emerging technologies, notably multiomics, can facilitate the measurement of both genetic changes and genomic traits in single cells, enabling single-cell genetic experiments. The implementation of single-cell genetics will advance the investigation of the genetic architecture of complex molecular traits and provide new experimental paradigms to study eukaryotic genetics.
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Affiliation(s)
- Mark A A Minow
- Department of Genetics, University of Georgia, Athens, Georgia, USA;
| | | | - Robert J Schmitz
- Department of Genetics, University of Georgia, Athens, Georgia, USA;
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21
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Ellis N, Hofer J, Sizer-Coverdale E, Lloyd D, Aubert G, Kreplak J, Burstin J, Cheema J, Bal M, Chen Y, Deng S, Wouters RHM, Steuernagel B, Chayut N, Domoney C. Recombinant inbred lines derived from wide crosses in Pisum. Sci Rep 2023; 13:20408. [PMID: 37990072 PMCID: PMC10663473 DOI: 10.1038/s41598-023-47329-9] [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: 08/02/2023] [Accepted: 11/12/2023] [Indexed: 11/23/2023] Open
Abstract
Genomic resources are becoming available for Pisum but to link these to phenotypic diversity requires well marked populations segregating for relevant traits. Here we describe two such resources. Two recombinant inbred populations, derived from wide crosses in Pisum are described. One high resolution mapping population involves cv Caméor, for which the first pea whole genome assembly was obtained, crossed to JI0281, a basally divergent P. sativum sativum landrace from Ethiopia. The other is an inter sub-specific cross between P. s. sativum and the independently domesticated P. s. abyssinicum. The corresponding genetic maps provide information on chromosome level sequence assemblies and identify structural differences between the genomes of these two Pisum subspecies. In order to visualise chromosomal translocations that distinguish the mapping parents, we created a simplified version of Threadmapper to optimise it for interactive 3-dimensional display of multiple linkage groups. The genetic mapping of traits affecting seed coat roughness and colour, plant height, axil ring pigmentation, leaflet number and leaflet indentation enabled the definition of their corresponding genomic regions. The consequence of structural rearrangement for trait analysis is illustrated by leaf serration. These analyses pave the way for identification of the underlying genes and illustrate the utility of these publicly available resources. Segregating inbred populations derived from wide crosses in Pisum, together with the associated marker data, are made publicly available for trait dissection. Genetic analysis of these populations is informative about chromosome scale assemblies, structural diversity in the pea genome and has been useful for the fine mapping of several discrete and quantitative traits.
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Affiliation(s)
- N Ellis
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK.
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK.
| | - J Hofer
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
| | - E Sizer-Coverdale
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
- Germinal Horizon, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
| | - D Lloyd
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
- Germinal Horizon, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
| | - G Aubert
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France
| | - J Kreplak
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France
| | - J Burstin
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France
| | - J Cheema
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - M Bal
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - Y Chen
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - S Deng
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - R H M Wouters
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - B Steuernagel
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - N Chayut
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - C Domoney
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
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22
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Lamkey CM, Lorenz AJ. A genomic analysis of the University of Nebraska Replicated Recurrent Selection program. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:243. [PMID: 37950832 DOI: 10.1007/s00122-023-04475-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 09/27/2023] [Indexed: 11/13/2023]
Abstract
The inbred-hybrid system of maize breeding closely resembles a reciprocal full-sib (RFS) selection program. Studying changes in genetic variation as a result of RFS selection can help illuminate long-standing questions regarding the relative roles of selection and genetic drift and help understand the nature of adaptation occurring in selection programs. The University of Nebraska-Lincoln Replicated Recurrent Selection (UNL-RpRS) program underwent eight cycles of replicated RFS and S1-progeny selection, making it a powerful system to study genomic changes accompanying selection for inter-population performance. The objectives of this study were to identify regions of the genome under selection after eight cycles of selection and evaluate the effect eight cycles of selection for inter-population full-sib performance had in expanding genome-wide and localized population structure. We address these questions with a large set of individuals sampled from the UNL-RpRS program with dense genotyping-by-sequence data. We found evidence of parallel selection signatures in the UNL-RpRS program, with a region on chromosome 7 being implicated in three of the four selection systems studied. Regions that displayed selection signatures across independently run selection programs represent regions likely to be capitalizing on standing genetic variation and support a soft sweep model of adaptation. We did not find selection to be a strong force in diverging populations undergoing RFS. This could be due to the nature of adaptation occurring in these populations, underlying gene action, or a result of unstable genetic topographies.
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Affiliation(s)
- Collin M Lamkey
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE, 68583, USA
- Corteva Agriscience, 19456 Hwy 22, Mankato, MN, 56001, USA
| | - Aaron J Lorenz
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE, 68583, USA.
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
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23
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Hao Y, Hu Y, Jaqueth J, Lin J, He C, Lin G, Zhao M, Ren J, Tamang TM, Park S, Robertson AE, White FF, Fu J, Li B, Liu S. Genetic and transcriptomic dissection of host defense to Goss's bacterial wilt and leaf blight of maize. G3 (BETHESDA, MD.) 2023; 13:jkad197. [PMID: 37652038 PMCID: PMC10627284 DOI: 10.1093/g3journal/jkad197] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 01/28/2023] [Accepted: 08/22/2023] [Indexed: 09/02/2023]
Abstract
Goss's wilt, caused by the Gram-positive actinobacterium Clavibacter nebraskensis, is an important bacterial disease of maize. The molecular and genetic mechanisms of resistance to the bacterium, or, in general, Gram-positive bacteria causing plant diseases, remain poorly understood. Here, we examined the genetic basis of Goss's wilt through differential gene expression, standard genome-wide association mapping (GWAS), extreme phenotype (XP) GWAS using highly resistant (R) and highly susceptible (S) lines, and quantitative trait locus (QTL) mapping using 3 bi-parental populations, identifying 11 disease association loci. Three loci were validated using near-isogenic lines or recombinant inbred lines. Our analysis indicates that Goss's wilt resistance is highly complex and major resistance genes are not commonly present. RNA sequencing of samples separately pooled from R and S lines with or without bacterial inoculation was performed, enabling identification of common and differential gene responses in R and S lines. Based on expression, in both R and S lines, the photosynthesis pathway was silenced upon infection, while stress-responsive pathways and phytohormone pathways, namely, abscisic acid, auxin, ethylene, jasmonate, and gibberellin, were markedly activated. In addition, 65 genes showed differential responses (up- or down-regulated) to infection in R and S lines. Combining genetic mapping and transcriptional data, individual candidate genes conferring Goss's wilt resistance were identified. Collectively, aspects of the genetic architecture of Goss's wilt resistance were revealed, providing foundational data for mechanistic studies.
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Affiliation(s)
- Yangfan Hao
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Ying Hu
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | | | - Jinguang Lin
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Cheng He
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Guifang Lin
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Mingxia Zhao
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Jie Ren
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Tej Man Tamang
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Sunghun Park
- Department of Horticulture and Natural Resources, Kansas State University, Manhattan, KS 66506, USA
| | - Alison E Robertson
- Department of Plant Pathology, Entomology and Microbiology, Iowa State University, Ames, IA 50010, USA
| | - Frank F White
- Department of Plant Pathology, University of Florida, Gainesville, FL 32611, USA
| | - Junjie Fu
- Chinese Academy of Agricultural Sciences, Institute of Crop Science, Beijing 100081, China
| | - Bailin Li
- Corteva Agriscience, Johnston, IA 50131, USA
| | - Sanzhen Liu
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
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Simpson CJC, Singh P, Sogbohossou DEO, Eric Schranz M, Hibberd JM. A rapid method to quantify vein density in C 4 plants using starch staining. PLANT, CELL & ENVIRONMENT 2023; 46:2928-2938. [PMID: 37350263 PMCID: PMC10947256 DOI: 10.1111/pce.14656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 06/05/2023] [Accepted: 06/13/2023] [Indexed: 06/24/2023]
Abstract
C4 photosynthesis has evolved multiple times in the angiosperms and typically involves alterations to the biochemistry, cell biology and development of leaves. One common modification found in C4 plants compared with the ancestral C3 state is an increase in vein density such that the leaf contains a larger proportion of bundle sheath cells. Recent findings indicate that there may be significant intraspecific variation in traits such as vein density in C4 plants but to use such natural variation for trait-mapping, rapid phenotyping would be required. Here we report a high-throughput method to quantify vein density that leverages the bundle sheath-specific accumulation of starch found in C4 species. Starch staining allowed high-contrast images to be acquired permitting image analysis with MATLAB- and Python-based programmes. The method works for dicotyledons and monocotolydons. We applied this method to Gynandropsis gynandra where significant variation in vein density was detected between natural accessions, and Zea mays where no variation was apparent in the genotypically diverse lines assessed. We anticipate this approach will be useful to map genes controlling vein density in C4 species demonstrating natural variation for this trait.
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Affiliation(s)
| | - Pallavi Singh
- Department of Plant SciencesUniversity of CambridgeCambridgeUK
| | | | - M. Eric Schranz
- Biosystematics GroupWageningen UniversityWageningenThe Netherlands
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25
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McFarland FL, Collier R, Walter N, Martinell B, Kaeppler SM, Kaeppler HF. A key to totipotency: Wuschel-like homeobox 2a unlocks embryogenic culture response in maize (Zea mays L.). PLANT BIOTECHNOLOGY JOURNAL 2023; 21:1860-1872. [PMID: 37357571 PMCID: PMC10440991 DOI: 10.1111/pbi.14098] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 06/19/2023] [Accepted: 05/28/2023] [Indexed: 06/27/2023]
Abstract
The ability of plant somatic cells to dedifferentiate, form somatic embryos and regenerate whole plants in vitro has been harnessed for both clonal propagation and as a key component of plant genetic engineering systems. Embryogenic culture response is significantly limited, however, by plant genotype in most species. This impedes advancements in both plant transformation-based functional genomics research and crop improvement efforts. We utilized natural variation among maize inbred lines to genetically map somatic embryo generation potential in tissue culture and identify candidate genes underlying totipotency. Using a series of maize lines derived from crosses involving the culturable parent A188 and the non-responsive parent B73, we identified a region on chromosome 3 associated with embryogenic culture response and focused on three candidate genes within the region based on genetic position and expression pattern. Two candidate genes showed no effect when ectopically expressed in B73, but the gene Wox2a was found to induce somatic embryogenesis and embryogenic callus proliferation. Transgenic B73 cells with strong constitutive expression of the B73 and A188 coding sequences of Wox2a were found to produce somatic embryos at similar frequencies, demonstrating that sufficient expression of either allele could rescue the embryogenic culture phenotype. Transgenic B73 plants were regenerated from the somatic embryos without chemical selection and no pleiotropic effects were observed in the Wox2a overexpression lines in the regenerated T0 plants or in the two independent events which produced T1 progeny. In addition to linking natural variation in tissue culture response to Wox2a, our data support the utility of Wox2a in enabling transformation of recalcitrant genotypes.
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Affiliation(s)
- Frank L. McFarland
- Department of AgronomyUniversity of WisconsinMadisonWIUSA
- Wisconsin Crop Innovation CenterUniversity of WisconsinMiddletonWIUSA
| | - Ray Collier
- Department of AgronomyUniversity of WisconsinMadisonWIUSA
| | | | | | - Shawn M. Kaeppler
- Department of AgronomyUniversity of WisconsinMadisonWIUSA
- Wisconsin Crop Innovation CenterUniversity of WisconsinMiddletonWIUSA
| | - Heidi F. Kaeppler
- Department of AgronomyUniversity of WisconsinMadisonWIUSA
- Wisconsin Crop Innovation CenterUniversity of WisconsinMiddletonWIUSA
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26
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Chawla R, Poonia A, Samantara K, Mohapatra SR, Naik SB, Ashwath MN, Djalovic IG, Prasad PVV. Green revolution to genome revolution: driving better resilient crops against environmental instability. Front Genet 2023; 14:1204585. [PMID: 37719711 PMCID: PMC10500607 DOI: 10.3389/fgene.2023.1204585] [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: 04/12/2023] [Accepted: 08/11/2023] [Indexed: 09/19/2023] Open
Abstract
Crop improvement programmes began with traditional breeding practices since the inception of agriculture. Farmers and plant breeders continue to use these strategies for crop improvement due to their broad application in modifying crop genetic compositions. Nonetheless, conventional breeding has significant downsides in regard to effort and time. Crop productivity seems to be hitting a plateau as a consequence of environmental issues and the scarcity of agricultural land. Therefore, continuous pursuit of advancement in crop improvement is essential. Recent technical innovations have resulted in a revolutionary shift in the pattern of breeding methods, leaning further towards molecular approaches. Among the promising approaches, marker-assisted selection, QTL mapping, omics-assisted breeding, genome-wide association studies and genome editing have lately gained prominence. Several governments have progressively relaxed their restrictions relating to genome editing. The present review highlights the evolutionary and revolutionary approaches that have been utilized for crop improvement in a bid to produce climate-resilient crops observing the consequence of climate change. Additionally, it will contribute to the comprehension of plant breeding succession so far. Investing in advanced sequencing technologies and bioinformatics will deepen our understanding of genetic variations and their functional implications, contributing to breakthroughs in crop improvement and biodiversity conservation.
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Affiliation(s)
- Rukoo Chawla
- Department of Genetics and Plant Breeding, Maharana Pratap University of Agriculture and Technology, Udaipur, Rajasthan, India
| | - Atman Poonia
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural University, Bawal, Haryana, India
| | - Kajal Samantara
- Institute of Technology, University of Tartu, Tartu, Estonia
| | - Sourav Ranjan Mohapatra
- Department of Forest Biology and Tree Improvement, Odisha University of Agriculture and Technology, Bhubaneswar, Odisha, India
| | - S. Balaji Naik
- Institute of Integrative Biology and Systems, University of Laval, Quebec City, QC, Canada
| | - M. N. Ashwath
- Department of Forest Biology and Tree Improvement, Kerala Agricultural University, Thrissur, Kerala, India
| | - Ivica G. Djalovic
- Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Novi Sad, Serbia
| | - P. V. Vara Prasad
- Department of Agronomy, Kansas State University, Manhattan, KS, United States
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Marla S, Felderhoff T, Hayes C, Perumal R, Wang X, Poland J, Morris GP. Genomics and phenomics enabled prebreeding improved early-season chilling tolerance in Sorghum. G3 (BETHESDA, MD.) 2023; 13:jkad116. [PMID: 37232400 PMCID: PMC10411554 DOI: 10.1093/g3journal/jkad116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 05/11/2023] [Accepted: 05/16/2023] [Indexed: 05/27/2023]
Abstract
In temperate climates, earlier planting of tropical-origin crops can provide longer growing seasons, reduce water loss, suppress weeds, and escape post-flowering drought stress. However, chilling sensitivity of sorghum, a tropical-origin cereal crop, limits early planting, and over 50 years of conventional breeding has been stymied by coinheritance of chilling tolerance (CT) loci with undesirable tannin and dwarfing alleles. In this study, phenomics and genomics-enabled approaches were used for prebreeding of sorghum early-season CT. Uncrewed aircraft systems (UAS) high-throughput phenotyping platform tested for improving scalability showed moderate correlation between manual and UAS phenotyping. UAS normalized difference vegetation index values from the chilling nested association mapping population detected CT quantitative trait locus (QTL) that colocalized with manual phenotyping CT QTL. Two of the 4 first-generation Kompetitive Allele Specific PCR (KASP) molecular markers, generated using the peak QTL single nucleotide polymorphisms (SNPs), failed to function in an independent breeding program as the CT allele was common in diverse breeding lines. Population genomic fixation index analysis identified SNP CT alleles that were globally rare but common to the CT donors. Second-generation markers, generated using population genomics, were successful in tracking the donor CT allele in diverse breeding lines from 2 independent sorghum breeding programs. Marker-assisted breeding, effective in introgressing CT allele from Chinese sorghums into chilling-sensitive US elite sorghums, improved early-planted seedling performance ratings in lines with CT alleles by up to 13-24% compared to the negative control under natural chilling stress. These findings directly demonstrate the effectiveness of high-throughput phenotyping and population genomics in molecular breeding of complex adaptive traits.
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Affiliation(s)
- Sandeep Marla
- Department of Agronomy, Kansas State University, Manhattan, KS 66506, USA
| | - Terry Felderhoff
- Department of Agronomy, Kansas State University, Manhattan, KS 66506, USA
| | - Chad Hayes
- USDA-ARS, Plant Stress & Germplasm Development Unit, Cropping Systems Research Laboratory, Lubbock, TX 79415, USA
| | - Ramasamy Perumal
- Western Kansas Agricultural Research Center, Kansas State University, Hays, KS 67601, USA
| | - Xu Wang
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
- Department of Agricultural and Biological Engineering, University of Florida, IFAS Gulf Coast Research and Education Center, Wimauma, FL 33598, USA
| | - Jesse Poland
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
- Center for Desert Agriculture, King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Geoffrey P Morris
- Department of Agronomy, Kansas State University, Manhattan, KS 66506, USA
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523, USA
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28
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Impens L, Lorenzo CD, Vandeputte W, Wytynck P, Debray K, Haeghebaert J, Herwegh D, Jacobs TB, Ruttink T, Nelissen H, Inzé D, Pauwels L. Combining multiplex gene editing and doubled haploid technology in maize. THE NEW PHYTOLOGIST 2023; 239:1521-1532. [PMID: 37306056 PMCID: PMC7614789 DOI: 10.1111/nph.19021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/09/2023] [Indexed: 06/13/2023]
Abstract
A major advantage of using CRISPR/Cas9 for gene editing is multiplexing, that is, the simultaneous targeting of many genes. However, primary transformants typically contain hetero-allelic mutations or are genetic mosaic, while genetically stable lines that are homozygous are desired for functional analysis. Currently, a dedicated and labor-intensive effort is required to obtain such higher-order mutants through several generations of genetic crosses and genotyping. We describe the design and validation of a rapid and efficient strategy to produce lines of genetically identical plants carrying various combinations of homozygous edits, suitable for replicated analysis of phenotypical differences. This approach was achieved by combining highly multiplex gene editing in Zea mays (maize) with in vivo haploid induction and efficient in vitro generation of doubled haploid plants using embryo rescue doubling. By combining three CRISPR/Cas9 constructs that target in total 36 genes potentially involved in leaf growth, we generated an array of homozygous lines with various combinations of edits within three generations. Several genotypes show a reproducible 10% increase in leaf size, including a septuple mutant combination. We anticipate that our strategy will facilitate the study of gene families via multiplex CRISPR mutagenesis and the identification of allele combinations to improve quantitative crop traits.
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Affiliation(s)
- Lennert Impens
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Christian D. Lorenzo
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Wout Vandeputte
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Pieter Wytynck
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Kevin Debray
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Jari Haeghebaert
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Denia Herwegh
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Thomas B. Jacobs
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Tom Ruttink
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), B-9820 Merelbeke, Belgium
| | - Hilde Nelissen
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Dirk Inzé
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
| | - Laurens Pauwels
- department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium
- Center for Plant Systems Biology, VIB, B-9052 Ghent, Belgium
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29
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Rio S, Charcosset A, Moreau L, Mary-Huard T. Detecting directional and non-directional epistasis in bi-parental populations using genomic data. Genetics 2023; 224:iyad089. [PMID: 37170627 DOI: 10.1093/genetics/iyad089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 01/16/2023] [Accepted: 05/01/2023] [Indexed: 05/13/2023] Open
Abstract
Epistasis, commonly defined as interaction effects between alleles of different loci, is an important genetic component of the variation of phenotypic traits in natural and breeding populations. In addition to its impact on variance, epistasis can also affect the expected performance of a population and is then referred to as directional epistasis. Before the advent of genomic data, the existence of epistasis (both directional and non-directional) was investigated based on complex and expensive mating schemes involving several generations evaluated for a trait of interest. In this study, we propose a methodology to detect the presence of epistasis based on simple inbred biparental populations, both genotyped and phenotyped, ideally along with their parents. Thanks to genomic data, parental proportions as well as shared parental proportions between inbred individuals can be estimated. They allow the evaluation of epistasis through a test of the expected performance for directional epistasis or the variance of genetic values. This methodology was applied to two large multiparental populations, i.e. the American maize and soybean nested association mapping populations, evaluated for different traits. Results showed significant epistasis, especially for the test of directional epistasis, e.g. the increase in anthesis to silking interval observed in most maize inbred progenies or the decrease in grain yield observed in several soybean inbred progenies. In general, the effects detected suggested that shuffling allelic associations of both elite parents had a detrimental effect on the performance of their progeny. This methodology is implemented in the EpiTest R-package and can be applied to any bi/multiparental inbred population evaluated for a trait of interest.
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Affiliation(s)
- Simon Rio
- CIRAD, UMR AGAP Institut, F-34398 Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, F-34398 Montpellier, France
| | - Alain Charcosset
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91190 Gif-sur-Yvette, France
| | - Laurence Moreau
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91190 Gif-sur-Yvette, France
| | - Tristan Mary-Huard
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91190 Gif-sur-Yvette, France
- Université Paris-Saclay, AgroParisTech, INRAE, UMR MIA-Paris, 91120 Palaiseau, France
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Thatcher S, Jung M, Panangipalli G, Fengler K, Sanyal A, Li B, Llaca V, Habben J. The NLRomes of Zea mays NAM founder lines and Zea luxurians display presence-absence variation, integrated domain diversity, and mobility. MOLECULAR PLANT PATHOLOGY 2023; 24:742-757. [PMID: 36929631 PMCID: PMC10257044 DOI: 10.1111/mpp.13319] [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: 05/31/2022] [Revised: 02/09/2023] [Accepted: 02/14/2023] [Indexed: 06/11/2023]
Abstract
Plant pathogens cause significant crop loss worldwide, and new resistance genes deployed to combat diseases can be overcome quickly. Understanding the existing resistance gene diversity within the germplasm of major crops, such as maize, is crucial for the development of new disease-resistant varieties. We analysed the nucleotide-binding leucine-rich repeat receptors (NLRs) of 26 recently sequenced diverse founder lines from the maize nested association mapping (NAM) population and compared them to the R gene complement present in a wild relative of maize, Zea luxurians. We found that NLRs in both species contain a large diversity of atypical integrated domains, including many domains that have not previously been found in the NLRs of other species. Additionally, the single Z. luxurians genome was found to have greater integrated atypical domain diversity than all 26 NAM founder lines combined, indicating that this species may represent a rich source of novel resistance genes. NLRs were also found to have very high sequence diversity and presence-absence variation among the NAM founder lines, with a large NLR cluster on Chr10 representing a diversity hotspot. Additionally, NLRs were shown to be mobile within maize genomes, with several putative interchromosomal translocations identified.
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31
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Zhang Z, Wang L. A simulation framework for reciprocal recurrent selection-based hybrid breeding under transparent and opaque simulators. FRONTIERS IN PLANT SCIENCE 2023; 14:1174168. [PMID: 37441181 PMCID: PMC10333587 DOI: 10.3389/fpls.2023.1174168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 06/02/2023] [Indexed: 07/15/2023]
Abstract
Hybrid breeding is an established and effective process to improve offspring performance, while it is resource-intensive and time-consuming for the recurrent process in reality. To enable breeders and researchers to evaluate the effectiveness of competing decision-making strategies, we present a modular simulation framework for reciprocal recurrent selection-based hybrid breeding. Consisting of multiple modules such as heterotic separation, genomic prediction, and genomic selection, this simulation framework allows breeders to efficiently simulate the hybrid breeding process with multiple options of simulators and decision-making strategies. We also integrate the recently proposed concepts of transparent and opaque simulators into the framework in order to reflect the breeding process more realistically. Simulation results show the performance comparison among different breeding strategies under the two simulators.
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Affiliation(s)
- Zerui Zhang
- Program of Bioinformatics and Computational Biology, Iowa State University, Ames, IA, United States
- Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA, United States
- Department of Statistics, Iowa State University, Ames, IA, United States
| | - Lizhi Wang
- Program of Bioinformatics and Computational Biology, Iowa State University, Ames, IA, United States
- Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA, United States
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32
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Pandey S, Singh A, Jaiswal P, Singh MK, Meena KR, Singh SK. The potentialities of omics resources for millet improvement. Funct Integr Genomics 2023; 23:210. [PMID: 37355501 DOI: 10.1007/s10142-023-01149-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 06/16/2023] [Accepted: 06/21/2023] [Indexed: 06/26/2023]
Abstract
Millets are nutrient-rich (nutri-rich) cereals with climate resilience attributes. However, its full productive potential is not realized due to the lack of a focused yield improvement approach, as evidenced by the available literature. Also, the lack of well-characterized genomic resources significantly limits millet improvement. But the recent availability of genomic data and advancement in omics tools has shown its enormous potential to enhance the efficiency and precision faced by conventional breeding in millet improvement. The development of high throughput genotyping platforms based on next-generation sequencing (NGS) has provided a low-cost method for genomic information, specifically for neglected nutri-rich cereals with the availability of a limited number of reference genome sequences. NGS has created new avenues for millet biotechnological interventions such as mutation-based study, GWAS, GS, and other omics technologies. The simultaneous discovery of high-throughput markers and multiplexed genotyping platform has aggressively aided marker-assisted breeding for millet improvement. Therefore, omics technology offers excellent opportunities to explore and combine useful variations for targeted traits that could impart high nutritional value to high-yielding cultivars under changing climatic conditions. In millet improvement, an in-depth account of NGS, integrating genomics data with different biotechnology tools, is reviewed in this context.
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Affiliation(s)
- Saurabh Pandey
- Department of Agricultural, Guru Nanak Dev University, Amritsar, Punjab, 143005, India
| | - Ashutosh Singh
- Centre for Advanced Studies on Climate Change, RPCAU, Pusa, Samastipur, Bihar, 848125, India.
| | - Priyanka Jaiswal
- Lovely Professional University, Jalandhar - Delhi G.T. Road, Phagwara, Punjab, 144411, India
| | - Mithilesh Kumar Singh
- Department of Genetics and Plant Breeding, RPCAU, Pusa, Samastipur, Bihar, 848125, India
| | - Khem Raj Meena
- Department of Biotechnology, School of Life Sciences, Central University of Rajasthan, Kishangarh, Rajasthan, 305817, India
| | - Satish Kumar Singh
- Department of Genetics and Plant Breeding, RPCAU, Pusa, Samastipur, Bihar, 848125, India
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Jiang F, Liu L, Li Z, Bi Y, Yin X, Guo R, Wang J, Zhang Y, Shaw RK, Fan X. Identification of Candidate QTLs and Genes for Ear Diameter by Multi-Parent Population in Maize. Genes (Basel) 2023; 14:1305. [PMID: 37372485 DOI: 10.3390/genes14061305] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 06/06/2023] [Accepted: 06/17/2023] [Indexed: 06/29/2023] Open
Abstract
Ear diameter (ED) is a critical component of grain yield (GY) in maize (Zea mays L.). Studying the genetic basis of ED in maize is of great significance in enhancing maize GY. Against this backdrop, this study was framed to (1) map the ED-related quantitative trait locus (QTL) and SNPs associated with ED; and (2) identify putative functional genes that may affect ED in maize. To accomplish this, an elite maize inbred line, Ye107, which belongs to the Reid heterotic group, was used as a common parent and crossed with seven elite inbred lines from three different heterotic groups (Suwan1, Reid, and nonReid) that exhibited abundant genetic variation in ED. This led to the construction of a multi-parent population consisting of 1215 F7 recombinant inbred lines (F7RILs). A genome-wide association study (GWAS) and linkage analysis were then conducted for the multi-parent population using 264,694 high-quality SNPs generated via the genotyping-by-sequencing method. Our study identified a total of 11 SNPs that were significantly associated with ED through the GWAS, and three QTLs were revealed by the linkage analysis for ED. The major QTL on chromosome 1 was co-identified in the region by the GWAS at SNP_143985532. SNP_143985532, located upstream of the Zm00001d030559 gene, encodes a callose synthase that is expressed in various tissues, with the highest expression level in the maize ear primordium. Haplotype analysis indicated that the haplotype B (allele AA) of Zm00001d030559 was positively correlated with ED. The candidate genes and SNPs identified in this study provide crucial insights for future studies on the genetic mechanism of maize ED formation, cloning of ED-related genes, and genetic improvement of ED. These results may help develop important genetic resources for enhancing maize yield through marker-assisted breeding.
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Affiliation(s)
- Fuyan Jiang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Li Liu
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Ziwei Li
- Yunnan Dehong Dai and Jingpo Nationality Institute of Agricultural Sciences, Mangshi 678400, China
| | - Yaqi Bi
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Xingfu Yin
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Ruijia Guo
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Jing Wang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Yudong Zhang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Ranjan Kumar Shaw
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Xingming Fan
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
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Dahanayaka BA, Martin A. Multi-parental fungal mapping population study to detect genomic regions associated with Pyrenophora teres f. teres virulence. Sci Rep 2023; 13:9804. [PMID: 37328500 PMCID: PMC10275933 DOI: 10.1038/s41598-023-36963-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 06/13/2023] [Indexed: 06/18/2023] Open
Abstract
In recent years multi-parental mapping populations (MPPs) have been widely adopted in many crops to detect quantitative trait loci (QTLs) as this method can compensate for the limitations of QTL analyses using bi-parental mapping populations. Here we report the first multi-parental nested association mapping (MP-NAM) population study used to detect genomic regions associated with host-pathogenic interactions. MP-NAM QTL analyses were conducted on 399 Pyrenophora teres f. teres individuals using biallelic, cross-specific and parental QTL effect models. A bi-parental QTL mapping study was also conducted to compare the power of QTL detection between bi-parental and MP-NAM populations. Using MP-NAM with 399 individuals detected a maximum of eight QTLs with a single QTL effect model whilst only a maximum of five QTLs were detected with an individual bi-parental mapping population of 100 individuals. When reducing the number of isolates in the MP-NAM to 200 individuals the number of QTLs detected remained the same for the MP-NAM population. This study confirms that MPPs such as MP-NAM populations can be successfully used in detecting QTLs in haploid fungal pathogens and that the power of QTL detection with MPPs is greater than with bi-parental mapping populations.
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Affiliation(s)
- Buddhika A Dahanayaka
- Centre for Crop Health, University of Southern Queensland, Toowoomba, QLD, 4350, Australia
| | - Anke Martin
- Centre for Crop Health, University of Southern Queensland, Toowoomba, QLD, 4350, Australia.
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Jiao C, Hao C, Li T, Bohra A, Wang L, Hou J, Liu H, Liu H, Zhao J, Wang Y, Liu Y, Wang Z, Jing X, Wang X, Varshney RK, Fu J, Zhang X. Fast integration and accumulation of beneficial breeding alleles through an AB-NAMIC strategy in wheat. PLANT COMMUNICATIONS 2023; 4:100549. [PMID: 36642955 DOI: 10.1016/j.xplc.2023.100549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/26/2022] [Accepted: 01/11/2023] [Indexed: 05/11/2023]
Abstract
Wheat (Triticum aestivum) is among the most important staple crops for safeguarding the food security of the growing world population. To bridge the gap between genebank diversity and breeding programs, we developed an advanced backcross-nested association mapping plus inter-crossed population (AB-NAMIC) by crossing three popular wheat cultivars as recurrent founders to 20 germplasm lines from a mini core collection. Selective backcrossing combined with selection against undesirable traits and extensive crossing within and between sub-populations created new opportunities to detect unknown genes and increase the frequency of beneficial alleles in the AB-NAMIC population. We performed phenotyping of 590 AB-NAMIC lines and a natural panel of 476 cultivars for six consecutive growing seasons and genotyped these 1066 lines with a 660K SNP array. Genome-wide association studies of both panels for plant development and yield traits demonstrated improved power to detect rare alleles and loci with medium genetic effects in AB-NAMIC. Notably, genome-wide association studies in AB-NAMIC detected the candidate gene TaSWEET6-7B (TraesCS7B03G1216700), which has high homology to the rice SWEET6b gene and exerts strong effects on adaptation and yield traits. The commercial release of two derived AB-NAMIC lines attests to its direct applicability in wheat improvement. Valuable information on genome-wide association study mapping, candidate genes, and their haplotypes for breeding traits are available through WheatGAB. Our research provides an excellent framework for fast-tracking exploration and accumulation of beneficial alleles stored in genebanks.
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Affiliation(s)
- Chengzhi Jiao
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
| | - Chenyang Hao
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tian Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Abhishek Bohra
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Perth, WA 6150, Australia
| | - Lanfen Wang
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jian Hou
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hongxia Liu
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hong Liu
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jing Zhao
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yamei Wang
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yunchuan Liu
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Zhiwei Wang
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xin Jing
- Smartgenomics Technology Institute, Tianjin 301700, China
| | - Xiue Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
| | - Rajeev K Varshney
- Centre for Crop & Food Innovation, WA State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Perth, WA 6150, Australia.
| | - Junjie Fu
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Xueyong Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cytogenetics Institute, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.
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Hartwig T, Banf M, Prietsch GP, Zhu JY, Mora-Ramírez I, Schippers JHM, Snodgrass SJ, Seetharam AS, Huettel B, Kolkman JM, Yang J, Engelhorn J, Wang ZY. Hybrid allele-specific ChIP-seq analysis identifies variation in brassinosteroid-responsive transcription factor binding linked to traits in maize. Genome Biol 2023; 24:108. [PMID: 37158941 PMCID: PMC10165856 DOI: 10.1186/s13059-023-02909-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Accepted: 03/23/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND Genetic variation in regulatory sequences that alter transcription factor (TF) binding is a major cause of phenotypic diversity. Brassinosteroid is a growth hormone that has major effects on plant phenotypes. Genetic variation in brassinosteroid-responsive cis-elements likely contributes to trait variation. Pinpointing such regulatory variations and quantitative genomic analysis of the variation in TF-target binding, however, remains challenging. How variation in transcriptional targets of signaling pathways such as the brassinosteroid pathway contributes to phenotypic variation is an important question to be investigated with innovative approaches. RESULTS Here, we use a hybrid allele-specific chromatin binding sequencing (HASCh-seq) approach and identify variations in target binding of the brassinosteroid-responsive TF ZmBZR1 in maize. HASCh-seq in the B73xMo17 F1s identifies thousands of target genes of ZmBZR1. Allele-specific ZmBZR1 binding (ASB) has been observed for 18.3% of target genes and is enriched in promoter and enhancer regions. About a quarter of the ASB sites correlate with sequence variation in BZR1-binding motifs and another quarter correlate with haplotype-specific DNA methylation, suggesting that both genetic and epigenetic variations contribute to the high level of variation in ZmBZR1 occupancy. Comparison with GWAS data shows linkage of hundreds of ASB loci to important yield and disease-related traits. CONCLUSION Our study provides a robust method for analyzing genome-wide variations of TF occupancy and identifies genetic and epigenetic variations of the brassinosteroid response transcription network in maize.
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Affiliation(s)
- Thomas Hartwig
- Department of Plant Biology, Carnegie Institution for Science, 260 Panama Street, Stanford, CA, 94305, USA.
- Heinrich-Heine University, Universitätsstraße 1, Düsseldorf, NRW, 40225, Germany.
- Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, Cologne, NRW, 50829, Germany.
| | - Michael Banf
- Department of Plant Biology, Carnegie Institution for Science, 260 Panama Street, Stanford, CA, 94305, USA
| | - Gisele Passaia Prietsch
- Department of Plant Biology, Carnegie Institution for Science, 260 Panama Street, Stanford, CA, 94305, USA
| | - Jia-Ying Zhu
- Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Seeland, SA, 06466, Germany
| | - Isabel Mora-Ramírez
- Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Seeland, SA, 06466, Germany
| | - Jos H M Schippers
- Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Seeland, SA, 06466, Germany
| | - Samantha J Snodgrass
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, 339A Bessey Hall, Ames, IA, 50011, USA
| | - Arun S Seetharam
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, 339A Bessey Hall, Ames, IA, 50011, USA
| | - Bruno Huettel
- Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, Cologne, NRW, 50829, Germany
| | - Judith M Kolkman
- School of Integrative Plant Science, Plant Pathology and Plant-Microbe Biology Section, Cornell University, 413 Bradfield Hall, Ithaca, NY, 14853, USA
| | - Jinliang Yang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, 363 Keim Hall, Lincoln, NE, 68583, USA
| | - Julia Engelhorn
- Heinrich-Heine University, Universitätsstraße 1, Düsseldorf, NRW, 40225, Germany
- Max Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, Cologne, NRW, 50829, Germany
| | - Zhi-Yong Wang
- Department of Plant Biology, Carnegie Institution for Science, 260 Panama Street, Stanford, CA, 94305, USA.
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Yuan G, Li Y, He D, Shi J, Yang Y, Du J, Zou C, Ma L, Pan G, Shen Y. A Combination of QTL Mapping and GradedPool-Seq to Dissect Genetic Complexity for Gibberella Ear Rot Resistance in Maize Using an IBM Syn10 DH Population. PLANT DISEASE 2023; 107:1115-1121. [PMID: 36131495 DOI: 10.1094/pdis-05-22-1183-re] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Gibberella ear rot (GER) caused by Fusarium graminearum (teleomorph Gibberella zeae) is one of the most devastating maize diseases that reduces grain yield and quality worldwide. Utilization of host genetic resistance has become one of the most suitable strategies to control GER. In this study, a set of 246 diverse inbred lines derived from the intermated B 73 × Mo 17 doubled haploid population (IBM Syn10 DH) were used to detect quantitative trait loci (QTL) associated with resistance to GER. Meanwhile, a GradedPool-Seq (GPS) approach was performed to identify genomic variations involved in GER resistance. Using artificial inoculation across multiple environments, GER severity of the population was observed with wide phenotypic variation. Based on the linkage mapping, a total of 14 resistant QTLs were detected, accounting for 5.11 to 14.87% of the phenotypic variation, respectively. In GPS analysis, five significant single nucleotide polymorphisms (SNPs) associated with GER resistance were identified. Combining QTL mapping and GPS analysis, a peak-value SNP on chromosome 4 from GPS was overlapped with the QTL qGER4.2, suggesting that the colocalized region could be the most possible target location conferring resistance to GER. Subsequently, seven candidate genes were identified within the peak SNP, linking them to GER resistance. These findings are useful for exploring the complicated genetic variations in maize GER resistance. The genomic regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the combined strategy that can be used for quantitative traits in plant species.
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Affiliation(s)
- Guangsheng Yuan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Youliang Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Dandan He
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiaxin Shi
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Yan Yang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Juan Du
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Chaoying Zou
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Langlang Ma
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Guangtang Pan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Yaou Shen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region of Ministry of Agriculture, Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
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Li G, Zhou YH, Li HF, Zhang YM. A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations. Comput Struct Biotechnol J 2023; 21:2241-2252. [PMID: 37035553 PMCID: PMC10073995 DOI: 10.1016/j.csbj.2023.03.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 03/12/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
Although multi-parent populations (MPPs) integrate the advantages of linkage and association mapping populations in the genetic dissection of complex traits and especially combine genetic analysis with crop breeding, it is difficult to detect small-effect quantitative trait loci (QTL) for complex traits in multiparent advanced generation intercross (MAGIC), nested association mapping (NAM), and random-open-parent association mapping (ROAM) populations. To address this issue, here we proposed a multi-locus linear mixed model method, namely mppQTL, to detect QTLs, especially small-effect QTLs, in these MPPs. The new method includes two steps. The first is genome-wide scanning based on a single-locus linear mixed model; the P-values are obtained from likelihood-ratio test, the peaks of negative logarithm P-value curve are selected by group-lasso, and all the selected peaks are regarded as potential QTLs. In the second step, all the potential QTLs are placed on a multi-locus linear mixed model, all the effects are estimated using expectation-maximization empirical Bayes algorithm, and all the non-zero effect vectors are further evaluated via likelihood-ratio test for significant QTLs. In Monte Carlo simulation studies, the new method has higher power in QTL detection, lower false positive rate, lower mean absolute deviation for QTL position estimate, and lower mean squared error for the estimate of QTL size (r2) than existing methods because the new method increases the power of detecting small-effect QTLs. In real dataset analysis, the new method (19) identified five more known genes than the existing three methods (14). This study provides an effective method for detecting small-effect QTLs in any MPPs.
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Diers BW, Specht JE, Graef GL, Song Q, Rainey KM, Ramasubramanian V, Liu X, Myers CL, Stupar RM, An YQC, Beavis WD. Genetic architecture of protein and oil content in soybean seed and meal. THE PLANT GENOME 2023; 16:e20308. [PMID: 36744727 DOI: 10.1002/tpg2.20308] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/09/2023] [Indexed: 05/10/2023]
Abstract
Soybean is grown primarily for the protein and oil extracted from its seed and its value is influenced by these components. The objective of this study was to map marker-trait associations (MTAs) for the concentration of seed protein, oil, and meal protein using the soybean nested association mapping (SoyNAM) population. The composition traits were evaluated on seed harvested from over 5000 inbred lines of the SoyNAM population grown in 10 field locations across 3 years. Estimated heritabilities were at least 0.85 for all three traits. The genotyping of lines with single nucleotide polymorphism markers resulted in the identification of 107 MTAs for the three traits. When MTAs for the three traits that mapped within 5 cM intervals were binned together, the MTAs were mapped to 64 intervals on 19 of the 20 soybean chromosomes. The majority of the MTA effects were small and of the 107 MTAs, 37 were for protein content, 39 for meal protein, and 31 for oil content. For cases where a protein and oil MTAs mapped to the same interval, most (94%) significant effects were opposite for the two traits, consistent with the negative correlation between these traits. A coexpression analysis identified candidate genes linked to MTAs and 18 candidate genes were identified. The large number of small effect MTAs for the composition traits suggest that genomic prediction would be more effective in improving these traits than marker-assisted selection.
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Affiliation(s)
- Brian W Diers
- Department of Crop Sciences, University of Illinois, Urbana, IL, USA
| | - James E Specht
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE, USA
| | - George L Graef
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE, USA
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, USA
| | | | | | - Xiaotong Liu
- Bioinformatics and Computational Biology Graduate Program, University of Minnesota - Twin Cities, Minneapolis, MN, USA
| | - Chad L Myers
- Department of Computer Science and Engineering, University of Minnesota - Twin Cities, Minneapolis, MN, USA
| | - Robert M Stupar
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, USA
| | - Yong-Qiang Charles An
- USDA-ARS Plant Genetic Research Unit at Donald Danforth Plant Science Center, St. Louis, MO, USA
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Takanashi H. Genetic control of morphological traits useful for improving sorghum. BREEDING SCIENCE 2023; 73:57-69. [PMID: 37168813 PMCID: PMC10165342 DOI: 10.1270/jsbbs.22069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 11/14/2022] [Indexed: 05/13/2023]
Abstract
Global climate change and global warming, coupled with the growing population, have raised concerns about sustainable food supply and bioenergy demand. Sorghum [Sorghum bicolor (L.) Moench] ranks fifth among cereals produced worldwide; it is a C4 crop with a higher stress tolerance than other major cereals and has a wide range of uses, such as grains, forage, and biomass. Therefore, sorghum has attracted attention as a promising crop for achieving sustainable development goals (SDGs). In addition, sorghum is a suitable genetic model for C4 grasses because of its high morphological diversity and relatively small genome size compared to other C4 grasses. Although sorghum breeding and genetic studies have lagged compared to other crops such as rice and maize, recent advances in research have identified several genes and many quantitative trait loci (QTLs) that control important agronomic traits in sorghum. This review outlines traits and genetic information with a focus on morphogenetic aspects that may be useful in sorghum breeding for grain and biomass utilization.
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Affiliation(s)
- Hideki Takanashi
- Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan
- Corresponding author (e-mail: )
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Fekih R, Ishimaru Y, Okada S, Maeda M, Miyagi R, Obana T, Suzuki K, Inamori M, Enoki H, Yamasaki M. High-Density Linkage Maps from Japanese Rice japonica Recombinant Inbred Lines Using Genotyping by Random Amplicon Sequencing-Direct (GRAS-Di). PLANTS (BASEL, SWITZERLAND) 2023; 12:plants12040929. [PMID: 36840276 PMCID: PMC9959243 DOI: 10.3390/plants12040929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/10/2023] [Accepted: 02/12/2023] [Indexed: 05/14/2023]
Abstract
The genetic dissection of agronomically important traits in closely related Japanese rice cultivars is still in its infancy mainly because of the narrow genetic diversity within japonica rice cultivars. In an attempt to unveil potential polymorphism between closely related Japanese rice cultivars, we used a next-generation-sequencing-based genotyping method: genotyping by random amplicon sequencing-direct (GRAS-Di) to develop genetic linkage maps. In this study, four recombinant inbred line (RIL) populations and their parents were used. A final RIL number of 190 for RIL71, 96 for RIL98, 95 for RIL16, and 94 for RIL91 derived from crosses between a common leading Japanese rice cultivar Koshihikari and Yamadanishiki, Taichung 65, Fujisaka 5, and Futaba, respectively, and the parent plants were subjected to GRAS-Di library construction and sequencing. Approximately 438.7 Mbp, 440 Mbp, 403.1 Mbp, and 392 Mbp called bases covering 97.5%, 97.3%, 98.3%, and 96.1%, respectively, of the estimated rice genome sequence at average depth of 1× were generated. Analysis of genotypic data identified 1050, 1285, 1708, and 1704 markers for each of the above RIL populations, respectively. Markers generated by GRAS-Di were organized into linkage maps and compared with those generated by GoldenGate SNP assay of the same RIL populations; the average genetic distance between markers showed a clear decrease in the four RIL populations when we integrated markers of both linkage maps. Genetic studies using these markers successfully localized five QTLs associated with heading date on chromosomes 3, 6, and 7 and which previously were identified as Hd1, Hd2, Hd6, Hd16, and Hd17. Therefore, GRAS-Di technology provided a low cost and efficient genotyping to overcome the narrow genetic diversity in closely related Japanese rice cultivars and enabled us to generate a high density linkage map in this germplasm.
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Affiliation(s)
- Rym Fekih
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, Kasai 675-2103, Japan
- Correspondence: (R.F.); (M.Y.)
| | - Yohei Ishimaru
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, Kasai 675-2103, Japan
| | - Satoshi Okada
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, Kasai 675-2103, Japan
- Bioscience and Biotechnology Center, Nagoya University, Nagoya 464-8601, Japan
| | - Michihiro Maeda
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, Kasai 675-2103, Japan
| | | | | | | | | | | | - Masanori Yamasaki
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, Kasai 675-2103, Japan
- Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
- Correspondence: (R.F.); (M.Y.)
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Singh R, Shim S, Telenko DEP, Goodwin SB. Parental Inbred Lines of the Nested Association Mapping (NAM) Population of Corn Show Sources of Resistance to Tar Spot in Northern Indiana. PLANT DISEASE 2023; 107:262-266. [PMID: 35836387 DOI: 10.1094/pdis-02-22-0314-sc] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Tar spot is a major foliar disease of corn caused by the obligate fungal pathogen Phyllachora maydis, first identified in Indiana in 2015. Under conducive weather conditions, P. maydis causes significant yield losses in the United States and other countries, constituting a major threat to corn production. Relatively little is known about resistance to tar spot other than a major quantitative gene that was identified in tropical maize lines. To test for additional sources of resistance against populations of P. maydis in North America, 26 parental inbred lines of the nested associated mapping (NAM) population were evaluated for tar spot resistance in Indiana in replicated field trials under natural infection for 3 years. Tar spot disease severity was scored visually using a 0-to-100% scale. Maximum disease severity (MDS) for tar spot scoring at reproductive growth stage ranged from 0 to 48.3%, with 0% being most resistant and 48.3% being most susceptible. Nine inbred lines were resistant to P. maydis with MDS ranging from 0 to 5.0%, six were moderately resistant (5.2 to 10.6% MDS), two were moderately susceptible (11.7 to 26.0% MDS), and the remaining eight inbred lines were rated as susceptible (30.0 to 48.3% MDS). There was some variability between years, due to higher disease pressure after 2019. Inbred B73, the common parent of the NAM populations, was rated as susceptible, with MDS of 30.0%. The nine highly resistant lines provide a potential source of new genes for genetic analysis and mapping of tar spot resistance in corn.
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Affiliation(s)
- Raksha Singh
- Crop Production and Pest Control Research Unit, United States Department of Agriculture-Agricultural Research Service, West Lafayette, IN 47907-2054
| | - Sujoung Shim
- Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907-2054
| | - Darcy E P Telenko
- Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907-2054
| | - Stephen B Goodwin
- Crop Production and Pest Control Research Unit, United States Department of Agriculture-Agricultural Research Service, West Lafayette, IN 47907-2054
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Singh J, Chhabra B, Raza A, Yang SH, Sandhu KS. Important wheat diseases in the US and their management in the 21st century. FRONTIERS IN PLANT SCIENCE 2023; 13:1010191. [PMID: 36714765 PMCID: PMC9877539 DOI: 10.3389/fpls.2022.1010191] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/28/2022] [Indexed: 05/27/2023]
Abstract
Wheat is a crop of historical significance, as it marks the turning point of human civilization 10,000 years ago with its domestication. Due to the rapid increase in population, wheat production needs to be increased by 50% by 2050 and this growth will be mainly based on yield increases, as there is strong competition for scarce productive arable land from other sectors. This increasing demand can be further achieved using sustainable approaches including integrated disease pest management, adaption to warmer climates, less use of water resources and increased frequency of abiotic stress tolerances. Out of 200 diseases of wheat, 50 cause economic losses and are widely distributed. Each year, about 20% of wheat is lost due to diseases. Some major wheat diseases are rusts, smut, tan spot, spot blotch, fusarium head blight, common root rot, septoria blotch, powdery mildew, blast, and several viral, nematode, and bacterial diseases. These diseases badly impact the yield and cause mortality of the plants. This review focuses on important diseases of the wheat present in the United States, with comprehensive information of causal organism, economic damage, symptoms and host range, favorable conditions, and disease management strategies. Furthermore, major genetic and breeding efforts to control and manage these diseases are discussed. A detailed description of all the QTLs, genes reported and cloned for these diseases are provided in this review. This study will be of utmost importance to wheat breeding programs throughout the world to breed for resistance under changing environmental conditions.
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Affiliation(s)
- Jagdeep Singh
- Department of Crop, Soil & Environmental Sciences, Auburn University, Auburn, AL, United States
| | - Bhavit Chhabra
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, United States
| | - Ali Raza
- College of Agriculture, Oil Crops Research Institute, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Seung Hwan Yang
- Department of Integrative Biotechnology, Chonnam National University, Yeosu, Republic of Korea
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Liang M, An B, Deng T, Du L, Li K, Cao S, Du Y, Xu L, Zhang L, Gao X, Cao Y, Zhao Y, Li J, Gao H. Incorporating genome-wide and transcriptome-wide association studies to identify genetic elements of longissimus dorsi muscle in Huaxi cattle. Front Genet 2023; 13:982433. [PMID: 36685878 PMCID: PMC9852892 DOI: 10.3389/fgene.2022.982433] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 12/07/2022] [Indexed: 01/07/2023] Open
Abstract
Locating the genetic variation of important livestock and poultry economic traits is essential for genetic improvement in breeding programs. Identifying the candidate genes for the productive ability of Huaxi cattle was one crucial element for practical breeding. Based on the genotype and phenotype data of 1,478 individuals and the RNA-seq data of 120 individuals contained in 1,478 individuals, we implemented genome-wide association studies (GWAS), transcriptome-wide association studies (TWAS), and Fisher's combined test (FCT) to identify the candidate genes for the carcass trait, the weight of longissimus dorsi muscle (LDM). The results indicated that GWAS, TWAS, and FCT identified seven candidate genes for LDM altogether: PENK was located by GWAS and FCT, PPAT was located by TWAS and FCT, and XKR4, MTMR3, FGFRL1, DHRS4, and LAP3 were only located by one of the methods. After functional analysis of these candidate genes and referring to the reported studies, we found that they were mainly functional in the progress of the development of the body and the growth of muscle cells. Combining advanced breeding techniques such as gene editing with our study will significantly accelerate the genetic improvement for the future breeding of Huaxi cattle.
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Affiliation(s)
- Mang Liang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bingxing An
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianyu Deng
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lili Du
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Keanning Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Sheng Cao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yueying Du
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xue Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yang Cao
- Jilin Academy of Agricultural Sciences, Changchun, China
| | - Yuming Zhao
- Jilin Academy of Agricultural Sciences, Changchun, China
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China,*Correspondence: Huijiang Gao,
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45
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Cooper M, Messina CD. Breeding crops for drought-affected environments and improved climate resilience. THE PLANT CELL 2023; 35:162-186. [PMID: 36370076 PMCID: PMC9806606 DOI: 10.1093/plcell/koac321] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/01/2022] [Indexed: 05/12/2023]
Abstract
Breeding climate-resilient crops with improved levels of abiotic and biotic stress resistance as a response to climate change presents both opportunities and challenges. Applying the framework of the "breeder's equation," which is used to predict the response to selection for a breeding program cycle, we review methodologies and strategies that have been used to successfully breed crops with improved levels of drought resistance, where the target population of environments (TPEs) is a spatially and temporally heterogeneous mixture of drought-affected and favorable (water-sufficient) environments. Long-term improvement of temperate maize for the US corn belt is used as a case study and compared with progress for other crops and geographies. Integration of trait information across scales, from genomes to ecosystems, is needed to accurately predict yield outcomes for genotypes within the current and future TPEs. This will require transdisciplinary teams to explore, identify, and exploit novel opportunities to accelerate breeding program outcomes; both improved germplasm resources and improved products (cultivars, hybrids, clones, and populations) that outperform and replace the products in use by farmers, in combination with modified agronomic management strategies suited to their local environments.
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Affiliation(s)
| | - Carlos D Messina
- Horticultural Sciences Department, University of Florida, Gainesville, Florida 32611, USA
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Cagirici HB, Andorf CM, Sen TZ. Co-expression pan-network reveals genes involved in complex traits within maize pan-genome. BMC PLANT BIOLOGY 2022; 22:595. [PMID: 36529716 PMCID: PMC9762053 DOI: 10.1186/s12870-022-03985-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 12/07/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND With the advances in the high throughput next generation sequencing technologies, genome-wide association studies (GWAS) have identified a large set of variants associated with complex phenotypic traits at a very fine scale. Despite the progress in GWAS, identification of genotype-phenotype relationship remains challenging in maize due to its nature with dozens of variants controlling the same trait. As the causal variations results in the change in expression, gene expression analyses carry a pivotal role in unraveling the transcriptional regulatory mechanisms behind the phenotypes. RESULTS To address these challenges, we incorporated the gene expression and GWAS-driven traits to extend the knowledge of genotype-phenotype relationships and transcriptional regulatory mechanisms behind the phenotypes. We constructed a large collection of gene co-expression networks and identified more than 2 million co-expressing gene pairs in the GWAS-driven pan-network which contains all the gene-pairs in individual genomes of the nested association mapping (NAM) population. We defined four sub-categories for the pan-network: (1) core-network contains the highest represented ~ 1% of the gene-pairs, (2) near-core network contains the next highest represented 1-5% of the gene-pairs, (3) private-network contains ~ 50% of the gene pairs that are unique to individual genomes, and (4) the dispensable-network contains the remaining 50-95% of the gene-pairs in the maize pan-genome. Strikingly, the private-network contained almost all the genes in the pan-network but lacked half of the interactions. We performed gene ontology (GO) enrichment analysis for the pan-, core-, and private- networks and compared the contributions of variants overlapping with genes and promoters to the GWAS-driven pan-network. CONCLUSIONS Gene co-expression networks revealed meaningful information about groups of co-regulated genes that play a central role in regulatory processes. Pan-network approach enabled us to visualize the global view of the gene regulatory network for the studied system that could not be well inferred by the core-network alone.
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Affiliation(s)
- H Busra Cagirici
- US Department of Agriculture - Agricultural Research Service, Crop Improvement Genetics Research Unit, Western Regional Research Center, 800 Buchanan St, Albany, CA, 94710, USA
| | - Carson M Andorf
- US Department of Agriculture - Agricultural Research Service, 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.
| | - Taner Z Sen
- US Department of Agriculture - Agricultural Research Service, Crop Improvement Genetics Research Unit, Western Regional Research Center, 800 Buchanan St, Albany, CA, 94710, USA.
- Department of Bioengineering, University of California, Berkeley, CA, 94720, USA.
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Identification of Drought-Tolerance Genes in the Germination Stage of Soybean. BIOLOGY 2022; 11:biology11121812. [PMID: 36552318 PMCID: PMC9775293 DOI: 10.3390/biology11121812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 11/10/2022] [Accepted: 12/08/2022] [Indexed: 12/15/2022]
Abstract
Drought stress influences the vigor of plant seeds and inhibits seed germination, making it one of the primary environmental factors adversely affecting food security. The seed germination stage is critical to ensuring the growth and productivity of soybeans in soils prone to drought conditions. We here examined the genetic diversity and drought-tolerance phenotypes of 410 accessions of a germplasm diversity panel for soybean and conducted quantitative genetics analyses to identify loci associated with drought tolerance of seed germination. We uncovered significant differences among the diverse genotypes for four growth indices and five drought-tolerance indices, which revealed abundant variation among genotypes, upon drought stress, and for genotype × treatment effects. We also used 158,327 SNP markers and performed GWAS for the drought-related traits. Our data met the conditions (PCA + K) for using a mixed linear model in TASSEL, and we thus identified 26 SNPs associated with drought tolerance indices for germination stage distributed across 10 chromosomes. Nine SNP sites, including, for example, Gm20_34956219 and Gm20_36902659, were associated with two or more phenotypic indices, and there were nine SNP markers located in or adjacent to (within 500 kb) previously reported drought tolerance QTLs. These SNPs led to our identification of 41 candidate genes related to drought tolerance in the germination stage. The results of our study contribute to a deeper understanding of the genetic mechanisms underlying drought tolerance in soybeans at the germination stage, thereby providing a molecular basis for identifying useful soybean germplasm for breeding new drought-tolerant varieties.
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Shrestha A, Cosenza F, van Inghelandt D, Wu PY, Li J, Casale FA, Weisweiler M, Stich B. The double round-robin population unravels the genetic architecture of grain size in barley. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:7344-7361. [PMID: 36094852 PMCID: PMC9730814 DOI: 10.1093/jxb/erac369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 09/08/2022] [Indexed: 06/15/2023]
Abstract
Grain number, size and weight primarily determine the yield of barley. Although the genes regulating grain number are well studied in barley, the genetic loci and the causal gene for sink capacity are poorly understood. Therefore, the primary objective of our work was to dissect the genetic architecture of grain size and weight in barley. We used a multi-parent population developed from a genetic cross between 23 diverse barley inbreds in a double round-robin design. Seed size-related parameters such as grain length, grain width, grain area and thousand-grain weight were evaluated in the HvDRR population comprising 45 recombinant inbred line sub-populations. We found significant genotypic variation for all seed size characteristics, and observed 84% or higher heritability across four environments. The quantitative trait locus (QTL) detection results indicate that the genetic architecture of grain size is more complex than previously reported. In addition, both cultivars and landraces contributed positive alleles at grain size QTLs. Candidate genes identified using genome-wide variant calling data for all parental inbred lines indicated overlapping and potential novel regulators of grain size in cereals. Furthermore, our results indicated that sink capacity was the primary determinant of grain weight in barley.
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Affiliation(s)
- Asis Shrestha
- Institute for Quantitative Genetics and Genomics of Plants, Biology Department, Heinrich Heine University, Dusseldorf, Germany
| | - Francesco Cosenza
- Institute for Quantitative Genetics and Genomics of Plants, Biology Department, Heinrich Heine University, Dusseldorf, Germany
| | - Delphine van Inghelandt
- Institute for Quantitative Genetics and Genomics of Plants, Biology Department, Heinrich Heine University, Dusseldorf, Germany
| | - Po-Ya Wu
- Institute for Quantitative Genetics and Genomics of Plants, Biology Department, Heinrich Heine University, Dusseldorf, Germany
| | - Jinquan Li
- Max Planck Institute for Plant Breeding Research, Cologne, Germany
| | - Federico A Casale
- Institute for Quantitative Genetics and Genomics of Plants, Biology Department, Heinrich Heine University, Dusseldorf, Germany
| | - Marius Weisweiler
- Institute for Quantitative Genetics and Genomics of Plants, Biology Department, Heinrich Heine University, Dusseldorf, Germany
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Chidzanga C, Mullan D, Roy S, Baumann U, Garcia M. Nested association mapping-based GWAS for grain yield and related traits in wheat grown under diverse Australian environments. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:4437-4456. [PMID: 36205736 PMCID: PMC9734238 DOI: 10.1007/s00122-022-04230-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
Utilising a nested association mapping (NAM) population-based GWAS, 98 stable marker-trait associations with 127 alleles unique to the exotic parents were detected for grain yield and related traits in wheat. Grain yield, thousand-grain weight, screenings and hectolitre weight are important wheat yield traits. An understanding of their genetic basis is crucial for improving grain yield in breeding programmes. Nested association mapping (NAM) populations are useful resources for the dissection of the genetic basis of complex traits such as grain yield and related traits in wheat. Coupled with phenotypic data collected from multiple environments, NAM populations have the power to detect quantitative trait loci and their multiple alleles, providing germplasm that can be incorporated into breeding programmes. In this study, we evaluated a large-scale wheat NAM population with two recurrent parents in unbalanced trials in nine diverse Australian field environments over three years. By applying a single-stage factor analytical linear mixed model (FALMM) to the NAM multi-environment trials (MET) data and conducting a genome-wide association study (GWAS), we detected 98 stable marker-trait associations (MTAs) with their multiple alleles. 74 MTAs had 127 alleles that were derived from the exotic parents and were absent in either of the two recurrent parents. The exotic alleles had favourable effects on 46 MTAs of the 74 MTAs, for grain yield, thousand-grain weight, screenings and hectolitre weight. Two NAM RILs with consistently high yield in multiple environments were also identified, highlighting the potential of the NAM population in supporting plant breeding through provision of germplasm that can be readily incorporated into breeding programmes. The identified beneficial exotic alleles introgressed into the NAM population provide potential target alleles for the genetic improvement of wheat and further studies aimed at pinpointing the underlying genes.
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Affiliation(s)
- Charity Chidzanga
- School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, PMB 1 Glen Osmond, Adelaide, SA, 5064, Australia
- ARC Industrial Transformation Research Hub for Wheat in a Hot and Dry Climate, Waite Research Institute, The University of Adelaide, Glen Osmond, SA, 5064, Australia
| | - Daniel Mullan
- ARC Industrial Transformation Research Hub for Wheat in a Hot and Dry Climate, Waite Research Institute, The University of Adelaide, Glen Osmond, SA, 5064, Australia
- InterGrain Pty Ltd, 19 Ambitious Link, Bibra Lake, WA, 6163, Australia
| | - Stuart Roy
- School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, PMB 1 Glen Osmond, Adelaide, SA, 5064, Australia
- ARC Industrial Transformation Research Hub for Wheat in a Hot and Dry Climate, Waite Research Institute, The University of Adelaide, Glen Osmond, SA, 5064, Australia
| | - Ute Baumann
- School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, PMB 1 Glen Osmond, Adelaide, SA, 5064, Australia.
- ARC Industrial Transformation Research Hub for Wheat in a Hot and Dry Climate, Waite Research Institute, The University of Adelaide, Glen Osmond, SA, 5064, Australia.
| | - Melissa Garcia
- School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, PMB 1 Glen Osmond, Adelaide, SA, 5064, Australia
- ARC Industrial Transformation Research Hub for Wheat in a Hot and Dry Climate, Waite Research Institute, The University of Adelaide, Glen Osmond, SA, 5064, Australia
- Inari Agriculture, One Kendall Square, Building 600/700, Suite 7-501, Cambridge, MA, 02139, USA
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McMillen MS, Mahama AA, Sibiya J, Lübberstedt T, Suza WP. Improving drought tolerance in maize: Tools and techniques. Front Genet 2022; 13:1001001. [PMID: 36386797 PMCID: PMC9651916 DOI: 10.3389/fgene.2022.1001001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/14/2022] [Indexed: 05/01/2024] Open
Abstract
Drought is an important constraint to agricultural productivity worldwide and is expected to worsen with climate change. To assist farmers, especially in sub-Saharan Africa (SSA), to adapt to climate change, continuous generation of stress-tolerant and farmer-preferred crop varieties, and their adoption by farmers, is critical to curb food insecurity. Maize is the most widely grown staple crop in SSA and plays a significant role in food security. The aim of this review is to present an overview of a broad range of tools and techniques used to improve drought tolerance in maize. We also present a summary of progress in breeding for maize drought tolerance, while incorporating research findings from disciplines such as physiology, molecular biology, and systems modeling. The review is expected to complement existing knowledge about breeding maize for climate resilience. Collaborative maize drought tolerance breeding projects in SSA emphasize the value of public-private partnerships in increasing access to genomic techniques and useful transgenes. To sustain the impact of maize drought tolerance projects in SSA, there must be complementary efforts to train the next generation of plant breeders and crop scientists.
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Affiliation(s)
| | - Anthony A. Mahama
- Department of Agronomy, Iowa State University, Ames, IA, United States
| | - Julia Sibiya
- School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | | | - Walter P. Suza
- Department of Agronomy, Iowa State University, Ames, IA, United States
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