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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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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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Xia H, Hao Z, Shen Y, Tu Z, Yang L, Zong Y, Li H. Genome-wide association study of multiyear dynamic growth traits in hybrid Liriodendron identifies robust genetic loci associated with growth trajectories. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 115:1544-1563. [PMID: 37272730 DOI: 10.1111/tpj.16337] [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: 10/31/2022] [Revised: 04/30/2023] [Accepted: 05/29/2023] [Indexed: 06/06/2023]
Abstract
The genetic factors underlying growth traits differ over time points or stages. However, most current studies of phenotypes at single time points do not capture all loci or explain the genetic differences underlying growth trajectories. Hybrid Liriodendron exhibits obvious heterosis and is widely cultivated, although its complex genetic mechanism underlying growth traits remains unknown. A genome-wide association study (GWAS) is an effective method for elucidating the genetic architecture by identifying genetic loci underlying complex quantitative traits. In the present study, using a GWAS, we identified robust loci associated with growth trajectories in hybrid Liriodendron populations. We selected 233 hybrid progenies derived from 25 crosses for resequencing, and measured their tree height (H) and diameter at breast height (DBH) for 11 consecutive years; 192 972 high-quality single nucleotide polymorphisms (SNPs) were obtained. The dynamics of the multiyear single-trait GWAS showed that year-specific SNPs predominated, and only five robust SNPs for DBH were identified in at least three different years. Multitrait GWAS analysis with model parameters as latent variables also revealed 62 SNPs for H and 52 for DBH associated with the growth trajectory, displaying different biomass accumulation patterns, among which four SNPs exerted pleiotropic effects. All identified SNPs also exhibited temporal variations in effect sizes and inheritance patterns potentially related to different growth and developmental stages. The haplotypes resulting from these significant SNPs might pyramid favorable loci, benefitting the selection of superior genotypes. The present study provides insights into the genetic architecture of dynamic growth traits and lays a basis for future molecular-assisted breeding.
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Affiliation(s)
- Hui Xia
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
| | - Ziyuan Hao
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
| | - Yufang Shen
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
| | - Zhonghua Tu
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
| | - Lichun Yang
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
| | - Yaxian Zong
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
| | - Huogen Li
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
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Wang Y, Zhang H, Zhu S, Shen T, Pan H, Xu M. Association Mapping and Expression Analysis of the Genes Involved in the Wood Formation of Poplar. Int J Mol Sci 2023; 24:12662. [PMID: 37628843 PMCID: PMC10454019 DOI: 10.3390/ijms241612662] [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: 07/06/2023] [Revised: 08/04/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023] Open
Abstract
Xylogenesis is a complex and sequential biosynthetic process controlled by polygenes. Deciphering the genetic architecture of this complex quantitative trait could provide valuable information for increasing wood biomass and improving its properties. Here, we performed genomic resequencing of 64 24-year-old trees (64 hybrids of section Aigeiros and their parents) grown in the same field and conducted full-sib family-based association analyses of two growth and six woody traits using GEMMA as a choice of association model selection. We identified 1342 significantly associated single nucleotide polymorphisms (SNPs), 673 located in the region upstream and downstream of 565 protein-encoding genes. The transcriptional regulation network of secondary cell wall (SCW) biosynthesis was further constructed based on the published data of poplar miRNA, transcriptome, and degradome. These provided a certain scientific basis for the in-depth understanding of the mechanism of poplar timber formation and the molecular-assisted breeding in the future.
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Affiliation(s)
| | | | | | | | | | - Meng Xu
- Co-Innovation Center for Sustainable Forestry in Southern China, Satae Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing 210037, China; (Y.W.); (H.Z.); (S.Z.); (T.S.); (H.P.)
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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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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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Li W, Boer MP, van Rossum BJ, Zheng C, Joosen RVL, van Eeuwijk FA. statgenMPP: an R package implementing an IBD-based mixed model approach for QTL mapping in a wide range of multi-parent populations. Bioinformatics 2022; 38:5134-5136. [PMID: 36193999 PMCID: PMC9665859 DOI: 10.1093/bioinformatics/btac662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 08/23/2022] [Accepted: 10/03/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Multi-parent populations (MPPs) are popular for QTL mapping because they combine wide genetic diversity in parents with easy control of population structure, but a limited number of software tools for QTL mapping are specifically developed for general MPP designs. RESULTS We developed an R package called statgenMPP, adopting a unified identity-by-descent (IBD)-based mixed model approach for QTL analysis in MPPs. The package offers easy-to-use functionalities of IBD calculations, mixed model solutions and visualizations for QTL mapping in a wide range of MPP designs, including diallele, nested-association mapping populations, multi-parent advanced genetic inter-cross populations and other complicated MPPs with known crossing schemes. AVAILABILITY AND IMPLEMENTATION The R package statgenMPP is open-source and freely available on CRAN at https://CRAN.R-project.org/package=statgenMPP. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Wenhao Li
- Biometris, Wageningen University and Research Center, Wageningen, 6700 AC, The Netherlands
| | | | - Bart-Jan van Rossum
- Biometris, Wageningen University and Research Center, Wageningen, 6700 AC, The Netherlands
| | - Chaozhi Zheng
- Biometris, Wageningen University and Research Center, Wageningen, 6700 AC, The Netherlands
| | | | - Fred A van Eeuwijk
- Biometris, Wageningen University and Research Center, Wageningen, 6700 AC, The Netherlands
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Paccapelo MV, Kelly AM, Christopher JT, Verbyla AP. WGNAM: whole-genome nested association mapping. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2213-2232. [PMID: 35597886 PMCID: PMC9271119 DOI: 10.1007/s00122-022-04107-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 04/13/2022] [Indexed: 06/15/2023]
Abstract
A powerful QTL analysis method for nested association mapping populations is presented. Based on a one-stage multi-locus model, it provides accurate predictions of founder specific QTL effects. Nested association mapping (NAM) populations have been created to enable the identification of quantitative trait loci (QTL) in different genetic backgrounds. A whole-genome nested association mapping (WGNAM) method is presented to perform QTL analysis in NAM populations. The WGNAM method is an adaptation of the multi-parent whole genome average interval mapping approach where the crossing design is incorporated through the probability of inheriting founder alleles for every marker across the genome. Based on a linear mixed model, this method provides a one-stage analysis of raw phenotypic data, molecular markers, and crossing design. It simultaneously scans the whole-genome through an iterative process leading to a model with all the identified QTL while keeping the false positive rate low. The WGNAM approach was assessed through a simulation study, confirming to be a powerful and accurate method for QTL analysis for a NAM population. This novel method can also accommodate a multi-reference NAM (MR-NAM) population where donor parents are crossed with multiple reference parents to increase genetic diversity. Therefore, a demonstration is presented using a MR-NAM population for wheat (Triticum aestivum L.) to perform a QTL analysis for plant height. The strength and size of the putative QTL were summarized enhancing the understanding of the QTL effects depending on the parental origin. Compared to other methods, the proposed methodology based on a one-stage analysis provides greater power to detect QTL and increased accuracy in the estimation of their effects. The WGNAM method establishes the basis for accurate QTL mapping studies for NAM and MR-NAM populations.
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Affiliation(s)
- M Valeria Paccapelo
- Department of Agriculture and Fisheries, Leslie Research Facility, Toowoomba, QLD, 4350, Australia.
| | - Alison M Kelly
- Department of Agriculture and Fisheries, Leslie Research Facility, Toowoomba, QLD, 4350, Australia
| | - Jack T Christopher
- Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Leslie Research Facility, Toowoomba, QLD, 4350, Australia
| | - Arūnas P Verbyla
- AV Data Analytics, Pilton, QLD, 4361, Australia
- Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, St. Lucia, Brisbane, QLD, 4067, Australia
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