1
|
Werner CR, Gemenet DC, Tolhurst DJ. FieldSimR: an R package for simulating plot data in multi-environment field trials. Front Plant Sci 2024; 15:1330574. [PMID: 38638352 PMCID: PMC11024423 DOI: 10.3389/fpls.2024.1330574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 02/01/2024] [Indexed: 04/20/2024]
Abstract
This paper presents a general framework for simulating plot data in multi-environment field trials with one or more traits. The framework is embedded within the R package FieldSimR, whose core function generates plot errors that capture global field trend, local plot variation, and extraneous variation at a user-defined ratio. FieldSimR's capacity to simulate realistic plot data makes it a flexible and powerful tool for a wide range of improvement processes in plant breeding, such as the optimisation of experimental designs and statistical analyses of multi-environment field trials. FieldSimR provides crucial functionality that is currently missing in other software for simulating plant breeding programmes and is available on CRAN. The paper includes an example simulation of field trials that evaluate 100 maize hybrids for two traits in three environments. To demonstrate FieldSimR's value as an optimisation tool, the simulated data set is then used to compare several popular spatial models for their ability to accurately predict the hybrids' genetic values and reliably estimate the variance parameters of interest. FieldSimR has broader applications to simulating data in other agricultural trials, such as glasshouse experiments.
Collapse
Affiliation(s)
- Christian R. Werner
- Accelerated Breeding Initiative (ABI), Consultative Group of International Agricultural Research (CGIAR), Texcoco, Mexico
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Dorcus C. Gemenet
- Accelerated Breeding Initiative (ABI), Consultative Group of International Agricultural Research (CGIAR), Texcoco, Mexico
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Daniel J. Tolhurst
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| |
Collapse
|
2
|
Labroo MR, Endelman JB, Gemenet DC, Werner CR, Gaynor RC, Covarrubias-Pazaran GE. Clonal diploid and autopolyploid breeding strategies to harness heterosis: insights from stochastic simulation. Theor Appl Genet 2023; 136:147. [PMID: 37291402 DOI: 10.1007/s00122-023-04377-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 05/05/2023] [Indexed: 06/10/2023]
Abstract
KEY MESSAGE Reciprocal recurrent selection sometimes increases genetic gain per unit cost in clonal diploids with heterosis due to dominance, but it typically does not benefit autopolyploids. Breeding can change the dominance as well as additive genetic value of populations, thus utilizing heterosis. A common hybrid breeding strategy is reciprocal recurrent selection (RRS), in which parents of hybrids are typically recycled within pools based on general combining ability. However, the relative performances of RRS and other breeding strategies have not been thoroughly compared. RRS can have relatively increased costs and longer cycle lengths, but these are sometimes outweighed by its ability to harness heterosis due to dominance. Here, we used stochastic simulation to compare genetic gain per unit cost of RRS, terminal crossing, recurrent selection on breeding value, and recurrent selection on cross performance considering different amounts of population heterosis due to dominance, relative cycle lengths, time horizons, estimation methods, selection intensities, and ploidy levels. In diploids with phenotypic selection at high intensity, whether RRS was the optimal breeding strategy depended on the initial population heterosis. However, in diploids with rapid-cycling genomic selection at high intensity, RRS was the optimal breeding strategy after 50 years over almost all amounts of initial population heterosis under the study assumptions. Diploid RRS required more population heterosis to outperform other strategies as its relative cycle length increased and as selection intensity and time horizon decreased. The optimal strategy depended on selection intensity, a proxy for inbreeding rate. Use of diploid fully inbred parents vs. outbred parents with RRS typically did not affect genetic gain. In autopolyploids, RRS typically did not outperform one-pool strategies regardless of the initial population heterosis.
Collapse
Affiliation(s)
- Marlee R Labroo
- Excellence in Breeding Platform, Consultative Group of International Agricultural Research, Texcoco, Mexico
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Jeffrey B Endelman
- Department of Horticulture, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Dorcus C Gemenet
- Excellence in Breeding Platform, Consultative Group of International Agricultural Research, Texcoco, Mexico
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Christian R Werner
- Excellence in Breeding Platform, Consultative Group of International Agricultural Research, Texcoco, Mexico
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | | | - Giovanny E Covarrubias-Pazaran
- Excellence in Breeding Platform, Consultative Group of International Agricultural Research, Texcoco, Mexico.
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
| |
Collapse
|
3
|
Werner CR, Gaynor RC, Sargent DJ, Lillo A, Gorjanc G, Hickey JM. Genomic selection strategies for clonally propagated crops. Theor Appl Genet 2023; 136:74. [PMID: 36952013 PMCID: PMC10036424 DOI: 10.1007/s00122-023-04300-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 01/14/2023] [Indexed: 05/27/2023]
Abstract
For genomic selection in clonally propagated crops with diploid (-like) meiotic behavior to be effective, crossing parents should be selected based on genomic predicted cross-performance unless dominance is negligible. For genomic selection (GS) in clonal breeding programs to be effective, parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Genomic prediction of cross-performance enables efficient exploitation of the additive and dominance value simultaneously. Here, we compared different GS strategies for clonally propagated crops with diploid (-like) meiotic behavior, using strawberry as an example. We used stochastic simulation to evaluate six combinations of three breeding programs and two parent selection methods. The three breeding programs included (1) a breeding program that introduced GS in the first clonal stage, and (2) two variations of a two-part breeding program with one and three crossing cycles per year, respectively. The two parent selection methods were (1) parent selection based on genomic estimated breeding values (GEBVs) and (2) parent selection based on genomic predicted cross-performance (GPCP). Selection of parents based on GPCP produced faster genetic gain than selection of parents based on GEBVs because it reduced inbreeding when the dominance degree increased. The two-part breeding programs with one and three crossing cycles per year using GPCP always produced the most genetic gain unless dominance was negligible. We conclude that (1) in clonal breeding programs with GS, parents should be selected based on GPCP, and (2) a two-part breeding program with parent selection based on GPCP to rapidly drive population improvement has great potential to improve breeding clonally propagated crops.
Collapse
Affiliation(s)
- Christian R Werner
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK.
| | - R Chris Gaynor
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK
| | - Daniel J Sargent
- NIAB EMR, New Road, East Malling, Kent, ME19 6BJ, UK
- East Malling Enterprise Centre, Driscoll's Genetics Ltd, New Road, East Malling, Kent, ME19 6BJ, UK
| | - Alessandra Lillo
- East Malling Enterprise Centre, Driscoll's Genetics Ltd, New Road, East Malling, Kent, ME19 6BJ, UK
| | - Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK
| | - John M Hickey
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK
| |
Collapse
|
4
|
Gozalo-Marcilla M, Buntjer J, Johnsson M, Batista L, Diez F, Werner CR, Chen CY, Gorjanc G, Mellanby RJ, Hickey JM, Ros-Freixedes R. Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds. Genet Sel Evol 2021; 53:76. [PMID: 34551713 PMCID: PMC8459476 DOI: 10.1186/s12711-021-00671-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 09/07/2021] [Indexed: 01/23/2023] Open
Abstract
Background Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Methods Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10–6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. Results We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Conclusions Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-021-00671-w.
Collapse
Affiliation(s)
- Miguel Gozalo-Marcilla
- The Roslin Institute, The University of Edinburgh, Midlothian, UK.,The Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | - Jaap Buntjer
- The Roslin Institute, The University of Edinburgh, Midlothian, UK
| | - Martin Johnsson
- The Roslin Institute, The University of Edinburgh, Midlothian, UK.,Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Lorena Batista
- The Roslin Institute, The University of Edinburgh, Midlothian, UK
| | - Federico Diez
- The Roslin Institute, The University of Edinburgh, Midlothian, UK.,The Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | | | - Ching-Yi Chen
- The Pig Improvement Company, Genus plc, Hendersonville, TN, USA
| | - Gregor Gorjanc
- The Roslin Institute, The University of Edinburgh, Midlothian, UK
| | - Richard J Mellanby
- The Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
| | - John M Hickey
- The Roslin Institute, The University of Edinburgh, Midlothian, UK
| | - Roger Ros-Freixedes
- The Roslin Institute, The University of Edinburgh, Midlothian, UK. .,Departament de Ciència Animal, Universitat de Lleida - Agrotecnio-CERCA Center, Lleida, Spain.
| |
Collapse
|
5
|
Yao M, Guan M, Yang Q, Huang L, Xiong X, Jan HU, Voss-Fels KP, Werner CR, He X, Qian W, Snowdon RJ, Guan C, Hua W, Qian L. Regional association analysis coupled with transcriptome analyses reveal candidate genes affecting seed oil accumulation in Brassica napus. Theor Appl Genet 2021; 134:1545-1555. [PMID: 33677638 DOI: 10.1007/s00122-021-03788-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 02/03/2021] [Indexed: 06/12/2023]
Abstract
Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions in combination with co-expression analysis reveal candidate genes affecting oil accumulation in Brassica napus. One of the breeding goals in rapeseed production is to enhance the seed oil content to cater to the increased demand for vegetable oils due to a growing global population. To investigate the genetic basis of variation in seed oil content, we used 60 K Brassica Infinium SNP array along with phenotype data of 203 Chinese semi-winter rapeseed accessions to perform a genome-wide analysis of haplotype blocks associated with the oil content. Nine haplotype regions harbouring lipid synthesis/transport-, carbohydrate metabolism- and photosynthesis-related genes were identified as significantly associated with the oil content and were mapped to chromosomes A02, A04, A05, A07, C03, C04, C05, C08 and C09, respectively. Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions combined with transcriptome datasets from 13 accessions was further performed on these nine haplotype regions. This revealed natural variation in the BnTGD3-A02 and BnSSE1-A05 gene regions correlated with the phenotypic variation of the oil content within the A02 and A04 chromosome haplotype regions, respectively. Moreover, co-expression network analysis revealed that BnTGD3-A02 and BnSSE1-A05 were directly linked with fatty acid beta-oxidation-related gene BnKAT2-C04, thus forming a molecular network involved in the potential regulation of seed oil accumulation. The results of this study could be used to combine favourable haplotype alleles for further improvement of the seed oil content in rapeseed.
Collapse
Affiliation(s)
- Min Yao
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Mei Guan
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Qian Yang
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Luyao Huang
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Xinghua Xiong
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Habib U Jan
- Molecular Biology, Department of Pathology, MTI-LRH, Peshawar, 25000, Pakistan
| | - Kai P Voss-Fels
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Christian R Werner
- The Roslin Institute University of Edinburgh Easter Bush Research Centre Midlothian, Midlothian, EH25 9RG, UK
| | - Xin He
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Wei Qian
- College of Horticulture and Landscape Architecture, Southwest University, Chongqing, 400715, China
| | - Rod J Snowdon
- Department of Plant Breeding, Land Use and Nutrition, IFZ Research Centre for Biosystems, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Chunyun Guan
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Wei Hua
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China.
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Wuhan, 430062, China.
| | - Lunwen Qian
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China.
| |
Collapse
|
6
|
Knoch D, Werner CR, Meyer RC, Riewe D, Abbadi A, Lücke S, Snowdon RJ, Altmann T. Multi-omics-based prediction of hybrid performance in canola. Theor Appl Genet 2021; 134:1147-1165. [PMID: 33523261 PMCID: PMC7973648 DOI: 10.1007/s00122-020-03759-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 12/19/2020] [Indexed: 05/05/2023]
Abstract
Complementing or replacing genetic markers with transcriptomic data and use of reproducing kernel Hilbert space regression based on Gaussian kernels increases hybrid prediction accuracies for complex agronomic traits in canola. In plant breeding, hybrids gained particular importance due to heterosis, the superior performance of offspring compared to their inbred parents. Since the development of new top performing hybrids requires labour-intensive and costly breeding programmes, including testing of large numbers of experimental hybrids, the prediction of hybrid performance is of utmost interest to plant breeders. In this study, we tested the effectiveness of hybrid prediction models in spring-type oilseed rape (Brassica napus L./canola) employing different omics profiles, individually and in combination. To this end, a population of 950 F1 hybrids was evaluated for seed yield and six other agronomically relevant traits in commercial field trials at several locations throughout Europe. A subset of these hybrids was also evaluated in a climatized glasshouse regarding early biomass production. For each of the 477 parental rapeseed lines, 13,201 single nucleotide polymorphisms (SNPs), 154 primary metabolites, and 19,479 transcripts were determined and used as predictive variables. Both, SNP markers and transcripts, effectively predict hybrid performance using (genomic) best linear unbiased prediction models (gBLUP). Compared to models using pure genetic markers, models incorporating transcriptome data resulted in significantly higher prediction accuracies for five out of seven agronomic traits, indicating that transcripts carry important information beyond genomic data. Notably, reproducing kernel Hilbert space regression based on Gaussian kernels significantly exceeded the predictive abilities of gBLUP models for six of the seven agronomic traits, demonstrating its potential for implementation in future canola breeding programmes.
Collapse
Affiliation(s)
- Dominic Knoch
- Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben Germany
| | - Christian R. Werner
- The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG Scotland, UK
| | - Rhonda C. Meyer
- Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben Germany
| | - David Riewe
- Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben Germany
- Institute for Ecological Chemistry, Plant Analysis and Stored Product Protection, Julius Kühn Institute (JKI)—Federal Research Centre for Cultivated Plants, 14195 Berlin, Germany
| | - Amine Abbadi
- NPZ Innovation GmbH, Hohenlieth, 24363 Holtsee, Germany
- Norddeutsche Pflanzenzucht Hans-Georg Lembke KG, Hohenlieth, 24363 Holtsee, Germany
| | - Sophie Lücke
- Norddeutsche Pflanzenzucht Hans-Georg Lembke KG, Hohenlieth, 24363 Holtsee, Germany
| | - Rod J. Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany
| | - Thomas Altmann
- Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben Germany
| |
Collapse
|
7
|
Bančič J, Werner CR, Gaynor RC, Gorjanc G, Odeny DA, Ojulong HF, Dawson IK, Hoad SP, Hickey JM. Modeling Illustrates That Genomic Selection Provides New Opportunities for Intercrop Breeding. Front Plant Sci 2021; 12:605172. [PMID: 33633761 PMCID: PMC7902002 DOI: 10.3389/fpls.2021.605172] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 01/05/2021] [Indexed: 05/14/2023]
Abstract
Intercrop breeding programs using genomic selection can produce faster genetic gain than intercrop breeding programs using phenotypic selection. Intercropping is an agricultural practice in which two or more component crops are grown together. It can lead to enhanced soil structure and fertility, improved weed suppression, and better control of pests and diseases. Especially in subsistence agriculture, intercropping has great potential to optimize farming and increase profitability. However, breeding for intercrop varieties is complex as it requires simultaneous improvement of two or more component crops that combine well in the field. We hypothesize that genomic selection can significantly simplify and accelerate the process of breeding crops for intercropping. Therefore, we used stochastic simulation to compare four different intercrop breeding programs implementing genomic selection and an intercrop breeding program entirely based on phenotypic selection. We assumed three different levels of genetic correlation between monocrop grain yield and intercrop grain yield to investigate how the different breeding strategies are impacted by this factor. We found that all four simulated breeding programs using genomic selection produced significantly more intercrop genetic gain than the phenotypic selection program regardless of the genetic correlation with monocrop yield. We suggest a genomic selection strategy which combines monocrop and intercrop trait information to predict general intercropping ability to increase selection accuracy in the early stages of a breeding program and to minimize the generation interval.
Collapse
Affiliation(s)
- Jon Bančič
- Royal (Dick) School of Veterinary Studies, The Roslin Institute, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
- Scotland’s Rural College (SRUC), Edinburgh, United Kingdom
| | - Christian R. Werner
- Royal (Dick) School of Veterinary Studies, The Roslin Institute, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
| | - R. Chris Gaynor
- Royal (Dick) School of Veterinary Studies, The Roslin Institute, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
| | - Gregor Gorjanc
- Royal (Dick) School of Veterinary Studies, The Roslin Institute, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
| | - Damaris A. Odeny
- International Crops Research Institute for the Semi-Arid Tropics, ICRAF House, Nairobi, Kenya
| | - Henry F. Ojulong
- International Crops Research Institute for the Semi-Arid Tropics, ICRAF House, Nairobi, Kenya
| | - Ian K. Dawson
- Scotland’s Rural College (SRUC), Edinburgh, United Kingdom
| | | | - John M. Hickey
- Royal (Dick) School of Veterinary Studies, The Roslin Institute, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
| |
Collapse
|
8
|
Werner CR, Gaynor RC, Gorjanc G, Hickey JM, Kox T, Abbadi A, Leckband G, Snowdon RJ, Stahl A. How Population Structure Impacts Genomic Selection Accuracy in Cross-Validation: Implications for Practical Breeding. Front Plant Sci 2020; 11:592977. [PMID: 33391305 PMCID: PMC7772221 DOI: 10.3389/fpls.2020.592977] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 11/24/2020] [Indexed: 05/27/2023]
Abstract
Over the last two decades, the application of genomic selection has been extensively studied in various crop species, and it has become a common practice to report prediction accuracies using cross validation. However, genomic prediction accuracies obtained from random cross validation can be strongly inflated due to population or family structure, a characteristic shared by many breeding populations. An understanding of the effect of population and family structure on prediction accuracy is essential for the successful application of genomic selection in plant breeding programs. The objective of this study was to make this effect and its implications for practical breeding programs comprehensible for breeders and scientists with a limited background in quantitative genetics and genomic selection theory. We, therefore, compared genomic prediction accuracies obtained from different random cross validation approaches and within-family prediction in three different prediction scenarios. We used a highly structured population of 940 Brassica napus hybrids coming from 46 testcross families and two subpopulations. Our demonstrations show how genomic prediction accuracies obtained from among-family predictions in random cross validation and within-family predictions capture different measures of prediction accuracy. While among-family prediction accuracy measures prediction accuracy of both the parent average component and the Mendelian sampling term, within-family prediction only measures how accurately the Mendelian sampling term can be predicted. With this paper we aim to foster a critical approach to different measures of genomic prediction accuracy and a careful analysis of values observed in genomic selection experiments and reported in literature.
Collapse
Affiliation(s)
- Christian R. Werner
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
| | - R. Chris Gaynor
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
| | - Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
| | - John M. Hickey
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Research Centre, Midlothian, United Kingdom
| | | | | | | | - Rod J. Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Giessen, Germany
| | - Andreas Stahl
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Giessen, Germany
- Julius Kuehn Institute (JKI), Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Quedlinburg, Germany
| |
Collapse
|
9
|
Yao M, Guan M, Zhang Z, Zhang Q, Cui Y, Chen H, Liu W, Jan HU, Voss-Fels KP, Werner CR, He X, Liu Z, Guan C, Snowdon RJ, Hua W, Qian L. GWAS and co-expression network combination uncovers multigenes with close linkage effects on the oleic acid content accumulation in Brassica napus. BMC Genomics 2020; 21:320. [PMID: 32326904 PMCID: PMC7181522 DOI: 10.1186/s12864-020-6711-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 03/31/2020] [Indexed: 11/19/2022] Open
Abstract
Background Strong artificial and natural selection causes the formation of highly conserved haplotypes that harbor agronomically important genes. GWAS combination with haplotype analysis has evolved as an effective method to dissect the genetic architecture of complex traits in crop species. Results We used the 60 K Brassica Infinium SNP array to perform a genome-wide analysis of haplotype blocks associated with oleic acid (C18:1) in rapeseed. Six haplotype regions were identified as significantly associated with oleic acid (C18:1) that mapped to chromosomes A02, A07, A08, C01, C02, and C03. Additionally, whole-genome sequencing of 50 rapeseed accessions revealed three genes (BnmtACP2-A02, BnABCI13-A02 and BnECI1-A02) in the A02 chromosome haplotype region and two genes (BnFAD8-C02 and BnSDP1-C02) in the C02 chromosome haplotype region that were closely linked to oleic acid content phenotypic variation. Moreover, the co-expression network analysis uncovered candidate genes from these two different haplotype regions with potential regulatory interrelationships with oleic acid content accumulation. Conclusions Our results suggest that several candidate genes are closely linked, which provides us with an opportunity to develop functional haplotype markers for the improvement of the oleic acid content in rapeseed.
Collapse
Affiliation(s)
- Min Yao
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Mei Guan
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Zhenqian Zhang
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Qiuping Zhang
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Yixin Cui
- College of Horticulture and Landscape Architecture, Southwest University, Chongqing, 400715, China
| | - Hao Chen
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Wei Liu
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Habib U Jan
- Precision Medicine Lab, Rehman Medical Institute (RMI), Phase 5, Hayatabad, Peshawar, 25000, Pakistan
| | - Kai P Voss-Fels
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Christian R Werner
- The Roslin Institute University of Edinburgh Easter Bush Research Centre Midlothian, Edinburgh, EH25 9RG, UK
| | - Xin He
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Zhongsong Liu
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Chunyun Guan
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Rod J Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Wei Hua
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China. .,Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, 430062, China.
| | - Lunwen Qian
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China.
| |
Collapse
|
10
|
Knoch D, Abbadi A, Grandke F, Meyer RC, Samans B, Werner CR, Snowdon RJ, Altmann T. Strong temporal dynamics of QTL action on plant growth progression revealed through high-throughput phenotyping in canola. Plant Biotechnol J 2020; 18:68-82. [PMID: 31125482 PMCID: PMC6920335 DOI: 10.1111/pbi.13171] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 05/13/2019] [Accepted: 05/15/2019] [Indexed: 05/08/2023]
Abstract
A major challenge of plant biology is to unravel the genetic basis of complex traits. We took advantage of recent technical advances in high-throughput phenotyping in conjunction with genome-wide association studies to elucidate genotype-phenotype relationships at high temporal resolution. A diverse Brassica napus population from a commercial breeding programme was analysed by automated non-invasive phenotyping. Time-resolved data for early growth-related traits, including estimated biovolume, projected leaf area, early plant height and colour uniformity, were established and complemented by fresh and dry weight biomass. Genome-wide SNP array data provided the framework for genome-wide association analyses. Using time point data and relative growth rates, multiple robust main effect marker-trait associations for biomass and related traits were detected. Candidate genes involved in meristem development, cell wall modification and transcriptional regulation were detected. Our results demonstrate that early plant growth is a highly complex trait governed by several medium and many small effect loci, most of which act only during short phases. These observations highlight the importance of taking the temporal patterns of QTL/allele actions into account and emphasize the need for detailed time-resolved analyses to effectively unravel the complex and stage-specific contributions of genes affecting growth processes that operate at different developmental phases.
Collapse
Affiliation(s)
- Dominic Knoch
- Molecular Genetics/HeterosisLeibniz Institute of Plant Genetics and Crop Plant Research (IPK)SeelandGermany
| | - Amine Abbadi
- Norddeutsche Pflanzenzucht Innovation GmbH (NPZi)HoltseeGermany
| | - Fabian Grandke
- Department of Plant BreedingResearch Centre for BiosystemsLand Use and Nutrition (iFZ)Justus‐Liebig‐University GiessenGiessenGermany
| | - Rhonda C. Meyer
- Molecular Genetics/HeterosisLeibniz Institute of Plant Genetics and Crop Plant Research (IPK)SeelandGermany
| | - Birgit Samans
- Department of Plant BreedingResearch Centre for BiosystemsLand Use and Nutrition (iFZ)Justus‐Liebig‐University GiessenGiessenGermany
- Present address:
Technische Hochschule Mittelhessen (THM), University of Applied SciencesFachbereich Gesundheit35390GiessenGermany
| | - Christian R. Werner
- Department of Plant BreedingResearch Centre for BiosystemsLand Use and Nutrition (iFZ)Justus‐Liebig‐University GiessenGiessenGermany
- Present address:
The Roslin InstituteUniversity of EdinburghEaster Bush CampusMidlothianEH25 9RGUK
| | - Rod J. Snowdon
- Department of Plant BreedingResearch Centre for BiosystemsLand Use and Nutrition (iFZ)Justus‐Liebig‐University GiessenGiessenGermany
| | - Thomas Altmann
- Molecular Genetics/HeterosisLeibniz Institute of Plant Genetics and Crop Plant Research (IPK)SeelandGermany
| |
Collapse
|
11
|
Voss-Fels KP, Qian L, Gabur I, Obermeier C, Hickey LT, Werner CR, Kontowski S, Frisch M, Friedt W, Snowdon RJ, Gottwald S. Genetic insights into underground responses to Fusarium graminearum infection in wheat. Sci Rep 2018; 8:13153. [PMID: 30177750 PMCID: PMC6120866 DOI: 10.1038/s41598-018-31544-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 08/19/2018] [Indexed: 11/16/2022] Open
Abstract
The ongoing global intensification of wheat production will likely be accompanied by a rising pressure of Fusarium diseases. While utmost attention was given to Fusarium head blight (FHB) belowground plant infections of the pathogen have largely been ignored. The current knowledge about the impact of soil borne Fusarium infection on plant performance and the underlying genetic mechanisms for resistance remain very limited. Here, we present the first large-scale investigation of Fusarium root rot (FRR) resistance using a diverse panel of 215 international wheat lines. We obtained data for a total of 21 resistance-related traits, including large-scale Real-time PCR experiments to quantify fungal spread. Association mapping and subsequent haplotype analyses discovered a number of highly conserved genomic regions associated with resistance, and revealed a significant effect of allele stacking on the stembase discoloration. Resistance alleles were accumulated in European winter wheat germplasm, implying indirect prior selection for improved FRR resistance in elite breeding programs. Our results give first insights into the genetic basis of FRR resistance in wheat and demonstrate how molecular parameters can successfully be explored in genomic prediction. Ongoing work will help to further improve our understanding of the complex interactions of genetic factors influencing FRR resistance.
Collapse
Affiliation(s)
- Kai P Voss-Fels
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany.
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, 4072, Australia.
| | - Lunwen Qian
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, P.R. China
| | - Iulian Gabur
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Christian Obermeier
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Lee T Hickey
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, 4072, Australia
| | - Christian R Werner
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Stefan Kontowski
- W. von Borries-Eckendorf GmbH & Co. KG, Hovedisser Str. 92, 33818, Leopoldshöhe, Germany
| | - Matthias Frisch
- Institute for Agronomy and Plant Breeding II, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Wolfgang Friedt
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Rod J Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Sven Gottwald
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| |
Collapse
|
12
|
Werner CR, Voss-Fels KP, Miller CN, Qian W, Hua W, Guan CY, Snowdon RJ, Qian L. Effective Genomic Selection in a Narrow-Genepool Crop with Low-Density Markers: Asian Rapeseed as an Example. Plant Genome 2018; 11. [PMID: 30025015 DOI: 10.3835/plantgenome2017.09.0084] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Genomic selection (GS) has revolutionized breeding for quantitative traits in plants, offering potential to optimize resource allocation in breeding programs and increase genetic gain per unit of time. Modern high-density single nucleotide polymorphism (SNP) arrays comprising up to several hundred thousand markers provide a user-friendly technology to characterize the genetic constitution of whole populations and for implementing GS in breeding programs. However, GS does not build upon detailed genotype profiling facilitated by maximum marker density. With extensive genome-wide linkage disequilibrium (LD) being a common characteristic of breeding pools, fewer representative markers from available high-density genotyping platforms could be sufficient to capture the association between a genomic region and a phenotypic trait. To examine the effects of reduced marker density on genomic prediction accuracy, we collected data on three traits across 2 yr in a panel of 203 homozygous Chinese semiwinter rapeseed ( L.) inbred lines, broadly encompassing allelic variability in the Asian genepool. We investigated two approaches to selecting subsets of markers: a trait-dependent strategy based on genome-wide association study (GWAS) significance thresholds and a trait-independent method to detect representative tag SNPs. Prediction accuracies were evaluated using cross-validation with ridge-regression best linear unbiased predictions (rrBLUP). With semiwinter rapeseed as a model species, we demonstrate that low-density marker sets comprising a few hundred to a few thousand markers enable high prediction accuracies in breeding populations with strong LD comparable to those achieved with high-density arrays. Our results are valuable for facilitating routine application of cost-efficient GS in breeding programs.
Collapse
|
13
|
Werner CR, Qian L, Voss-Fels KP, Abbadi A, Leckband G, Frisch M, Snowdon RJ. Genome-wide regression models considering general and specific combining ability predict hybrid performance in oilseed rape with similar accuracy regardless of trait architecture. Theor Appl Genet 2018; 131:299-317. [PMID: 29080901 DOI: 10.1007/s00122-017-3002-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 10/09/2017] [Indexed: 05/02/2023]
Abstract
Genomic prediction using the Brassica 60 k genotyping array is efficient in oilseed rape hybrids. Prediction accuracy is more dependent on trait complexity than on the prediction model. In oilseed rape breeding programs, performance prediction of parental combinations is of fundamental importance. Due to the phenomenon of heterosis, per se performance is not a reliable indicator for F1-hybrid performance, and selection of well-paired parents requires the testing of large quantities of hybrid combinations in extensive field trials. However, the number of potential hybrids, in general, dramatically exceeds breeding capacity and budget. Integration of genomic selection (GS) could substantially increase the number of potential combinations that can be evaluated. GS models can be used to predict the performance of untested individuals based only on their genotypic profiles, using marker effects previously predicted in a training population. This allows for a preselection of promising genotypes, enabling a more efficient allocation of resources. In this study, we evaluated the usefulness of the Illumina Brassica 60 k SNP array for genomic prediction and compared three alternative approaches based on a homoscedastic ridge regression BLUP and three Bayesian prediction models that considered general and specific combining ability (GCA and SCA, respectively). A total of 448 hybrids were produced in a commercial breeding program from unbalanced crosses between 220 paternal doubled haploid lines and five male-sterile testers. Predictive ability was evaluated for seven agronomic traits. We demonstrate that the Brassica 60 k genotyping array is an adequate and highly valuable platform to implement genomic prediction of hybrid performance in oilseed rape. Furthermore, we present first insights into the application of established statistical models for prediction of important agronomical traits with contrasting patterns of polygenic control.
Collapse
Affiliation(s)
- Christian R Werner
- Department of Plant Breeding, Justus Liebig University, 35392, Giessen, Germany
| | - Lunwen Qian
- Department of Plant Breeding, Justus Liebig University, 35392, Giessen, Germany
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Kai P Voss-Fels
- Department of Plant Breeding, Justus Liebig University, 35392, Giessen, Germany
| | - Amine Abbadi
- NPZ Innovation GmbH, Hohenlieth, 24363, Holtsee, Germany
| | | | - Matthias Frisch
- Institute of Agronomy and Plant Breeding II, Justus Liebig University, 35392, Giessen, Germany
| | - Rod J Snowdon
- Department of Plant Breeding, Justus Liebig University, 35392, Giessen, Germany.
| |
Collapse
|
14
|
Werner CR, Qian L, Voss-Fels KP, Abbadi A, Leckband G, Frisch M, Snowdon RJ. Genome-wide regression models considering general and specific combining ability predict hybrid performance in oilseed rape with similar accuracy regardless of trait architecture. Theor Appl Genet 2017. [PMID: 29080901 DOI: 10.1007/s00122‐017‐3002‐5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
KEY MESSAGE Genomic prediction using the Brassica 60 k genotyping array is efficient in oilseed rape hybrids. Prediction accuracy is more dependent on trait complexity than on the prediction model. In oilseed rape breeding programs, performance prediction of parental combinations is of fundamental importance. Due to the phenomenon of heterosis, per se performance is not a reliable indicator for F1-hybrid performance, and selection of well-paired parents requires the testing of large quantities of hybrid combinations in extensive field trials. However, the number of potential hybrids, in general, dramatically exceeds breeding capacity and budget. Integration of genomic selection (GS) could substantially increase the number of potential combinations that can be evaluated. GS models can be used to predict the performance of untested individuals based only on their genotypic profiles, using marker effects previously predicted in a training population. This allows for a preselection of promising genotypes, enabling a more efficient allocation of resources. In this study, we evaluated the usefulness of the Illumina Brassica 60 k SNP array for genomic prediction and compared three alternative approaches based on a homoscedastic ridge regression BLUP and three Bayesian prediction models that considered general and specific combining ability (GCA and SCA, respectively). A total of 448 hybrids were produced in a commercial breeding program from unbalanced crosses between 220 paternal doubled haploid lines and five male-sterile testers. Predictive ability was evaluated for seven agronomic traits. We demonstrate that the Brassica 60 k genotyping array is an adequate and highly valuable platform to implement genomic prediction of hybrid performance in oilseed rape. Furthermore, we present first insights into the application of established statistical models for prediction of important agronomical traits with contrasting patterns of polygenic control.
Collapse
Affiliation(s)
- Christian R Werner
- Department of Plant Breeding, Justus Liebig University, 35392, Giessen, Germany
| | - Lunwen Qian
- Department of Plant Breeding, Justus Liebig University, 35392, Giessen, Germany.,Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Kai P Voss-Fels
- Department of Plant Breeding, Justus Liebig University, 35392, Giessen, Germany
| | - Amine Abbadi
- NPZ Innovation GmbH, Hohenlieth, 24363, Holtsee, Germany
| | | | - Matthias Frisch
- Institute of Agronomy and Plant Breeding II, Justus Liebig University, 35392, Giessen, Germany
| | - Rod J Snowdon
- Department of Plant Breeding, Justus Liebig University, 35392, Giessen, Germany.
| |
Collapse
|
15
|
Qian L, Hickey LT, Stahl A, Werner CR, Hayes B, Snowdon RJ, Voss-Fels KP. Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops. Front Plant Sci 2017; 8:1534. [PMID: 28928764 PMCID: PMC5591830 DOI: 10.3389/fpls.2017.01534] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Accepted: 08/22/2017] [Indexed: 05/19/2023]
Abstract
In order to meet future food, feed, fiber, and bioenergy demands, global yields of all major crops need to be increased significantly. At the same time, the increasing frequency of extreme weather events such as heat and drought necessitates improvements in the environmental resilience of modern crop cultivars. Achieving sustainably increase yields implies rapid improvement of quantitative traits with a very complex genetic architecture and strong environmental interaction. Latest advances in genome analysis technologies today provide molecular information at an ultrahigh resolution, revolutionizing crop genomic research, and paving the way for advanced quantitative genetic approaches. These include highly detailed assessment of population structure and genotypic diversity, facilitating the identification of selective sweeps and signatures of directional selection, dissection of genetic variants that underlie important agronomic traits, and genomic selection (GS) strategies that not only consider major-effect genes. Single-nucleotide polymorphism (SNP) markers today represent the genotyping system of choice for crop genetic studies because they occur abundantly in plant genomes and are easy to detect. SNPs are typically biallelic, however, hence their information content compared to multiallelic markers is low, limiting the resolution at which SNP-trait relationships can be delineated. An efficient way to overcome this limitation is to construct haplotypes based on linkage disequilibrium, one of the most important features influencing genetic analyses of crop genomes. Here, we give an overview of the latest advances in genomics-based haplotype analyses in crops, highlighting their importance in the context of polyploidy and genome evolution, linkage drag, and co-selection. We provide examples of how haplotype analyses can complement well-established quantitative genetics frameworks, such as quantitative trait analysis and GS, ultimately providing an effective tool to equip modern crops with environment-tailored characteristics.
Collapse
Affiliation(s)
- Lunwen Qian
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural UniversityChangsha, China
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University GiessenGiessen, Germany
| | - Lee T. Hickey
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St LuciaQLD, Australia
| | - Andreas Stahl
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University GiessenGiessen, Germany
| | - Christian R. Werner
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University GiessenGiessen, Germany
| | - Ben Hayes
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St LuciaQLD, Australia
| | - Rod J. Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University GiessenGiessen, Germany
| | - Kai P. Voss-Fels
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University GiessenGiessen, Germany
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St LuciaQLD, Australia
| |
Collapse
|
16
|
Saman S, Henes JC, Niepel D, Bosmüller H, Werner CR, Lauer UM, Malek NP, Xenitidis T. [Varicella gastritis under immunosuppression : Case report of a woman after lung transplantation due to granulomatosis with polyangiitis]. Internist (Berl) 2017; 58:855-858. [PMID: 28405696 DOI: 10.1007/s00108-017-0231-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
A 35-year-old woman who had previously undergone a lung transplantation presented with severe abdominal pain and vomiting. The gastroscopy showed diffuse ulcerative gastric lesions. Tests for varicella zoster virus and Epstein-Barr virus via polymerase chain reactions (PCR) on endoscopically obtained gastric biopsies were found to be positive and confirmed varicella gastritis. Intravenous antiviral therapy with acyclovir was administered resulting in a normalization of all clinical symptoms, especially of abdominal pain and inflammation parameters.
Collapse
Affiliation(s)
- S Saman
- Abteilung Innere Medizin I (Hepatologie, Gastroenterologie, Infektiologie), Universitätsklinikum Tübingen, Otfried-Müller-Str. 10, 72076, Tübingen, Deutschland.
| | - J-C Henes
- Abteilung Innere Medizin II (Onkologie, Hämatologie, Rheumatologie, Immunologie, Pulmonologie), Universitätsklinikum Tübingen, Otfried-Müller-Str. 10, 72076, Tübingen, Deutschland
| | - D Niepel
- Abteilung Innere Medizin I (Hepatologie, Gastroenterologie, Infektiologie), Universitätsklinikum Tübingen, Otfried-Müller-Str. 10, 72076, Tübingen, Deutschland
| | - H Bosmüller
- Abteilung Allgemeine Pathologie, Institut für Pathologie und Neuropathologie, Liebermeisterstr. 8, 72076, Tübingen, Deutschland
| | - C R Werner
- Abteilung Innere Medizin I (Hepatologie, Gastroenterologie, Infektiologie), Universitätsklinikum Tübingen, Otfried-Müller-Str. 10, 72076, Tübingen, Deutschland
| | - U M Lauer
- Abteilung Innere Medizin I (Hepatologie, Gastroenterologie, Infektiologie), Universitätsklinikum Tübingen, Otfried-Müller-Str. 10, 72076, Tübingen, Deutschland
| | - N P Malek
- Abteilung Innere Medizin I (Hepatologie, Gastroenterologie, Infektiologie), Universitätsklinikum Tübingen, Otfried-Müller-Str. 10, 72076, Tübingen, Deutschland
| | - T Xenitidis
- Abteilung Innere Medizin II (Onkologie, Hämatologie, Rheumatologie, Immunologie, Pulmonologie), Universitätsklinikum Tübingen, Otfried-Müller-Str. 10, 72076, Tübingen, Deutschland
| |
Collapse
|
17
|
Werner CR, Franz C, Egetemeyr DP, Janke-Maier P, Malek NP, Lauer UM, Berg CP. Efficacy and safety of telaprevir (TVR) triple therapy in a 'real-life' cohort of 102 patients with HCV genotype 1: interim analysis after 24 weeks of treatment. J Viral Hepat 2014; 21:333-40. [PMID: 24716636 DOI: 10.1111/jvh.12145] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2013] [Accepted: 06/13/2013] [Indexed: 12/16/2022]
Abstract
Since 2011, telaprevir (TVR)-based triple therapy is the new treatment standard for hepatitis C genotype 1 virus infection. The aim of our retrospective interim analysis encompassing the first 24 weeks on TVR-based triple therapy was to assess 'real-life' antiviral efficacy and side effects in a large single-centre cohort, both in comparison with the data obtained in large prospective clinical trials. In total, we treated 102 patients: 24 treatment-naïve patients, 58 patients pretreated with PEG-IFN/RBV (thereof: 28 with nonresponse, 25 with relapse, five unknown) and 20 patients who previously had received nonpegylated interferon. 74 of 102 patients were assigned with HCV genotype 1b; 34 of 102 patients were treated in the context of liver cirrhosis. 72 of 102 patients have reached treatment week 24 (mean treatment duration 31 weeks). In the ITT analysis, overall response rates were at: week 4: 66%; week 12: 85%; and week 24: 78%. So far, 24 patients discontinued treatment prematurely, of those, 10 patients were due to virological failure. Haematological side effects were frequent (40% anaemia), as were 'flu-like' symptoms (94%), rash (65%) and pruritus (79%). According to our interim ITT analysis encompassing up to 24 weeks of TVR-based triple therapy, our 'real-life' antiviral effects are comparable to the results of large multicentric clinical trials. However, TVR-based triple therapy exhibited a high frequency of side effects requiring multiple therapeutic interventions. Notably, in our 'real-life' cohort, no lethal case was observed so far.
Collapse
Affiliation(s)
- C R Werner
- Department of Gastroenterology, Hepatology, and Infectiology, University Hospital Tuebingen, Tuebingen, Germany
| | | | | | | | | | | | | |
Collapse
|
18
|
Werner CR, Graepler F, Glatzle J, Stüker D, Kratt T, Schmehl J, Bitzer M, Königsrainer A, Malek NP, Goetz M. Proximal duodenal obstruction--Bouveret's syndrome revisited. Endoscopy 2014; 45 Suppl 2 UCTN:E231-2. [PMID: 23945924 DOI: 10.1055/s-0033-1344324] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- C R Werner
- Department of Gastroenterology, University Hospital Tübingen, Medical Clinic, Tübingen, Germany.
| | | | | | | | | | | | | | | | | | | |
Collapse
|
19
|
Werner CR, Egetemeyr DP, Nadalin S, Königsrainer A, Malek NP, Lauer UM, Berg CP. Treatment of recurrent genotype 1 hepatitis C post-liver transplantation: single center experience with telaprevir-based triple therapy. Z Gastroenterol 2014; 52:27-34. [PMID: 24420796 DOI: 10.1055/s-0033-1356345] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Recurrent HCV infection post-liver transplantation (post-LT) is still a major challenge in the treatment of hepatitis C virus (HCV) infection. In this retrospective analysis we gathered data about treatment response and safety of all 14 post-LT patients who were treated between 2011 and 2013 at our centre with a telaprevir (TVR)-based triple therapy. Seven out of 14 patients completed the full treatment course of 48 weeks. Five patients achieved a SVR 24, while 3 additional HCV RNA-negative patients are still in follow-up (end of treatment, SVR 12 and 22). Four patients discontinued treatment prematurely due to side effects. A virological non-response at TW 4 was seen in 1 patient. Virological breakthrough was observed in 2 patients at TW 16 and 28, respectively; 1 patient displayed a virological relapse after the end of treatment (EOT). Patients with a complicated course post-LT accumulated most of the severe side effects, largely infections. One patient with cholestatic hepatitis died 11 weeks after discontinuation of treatment due to progressive graft failure. In conclusion, TVR-based triple therapy in post-LT patients reveals an acceptable antiviral efficacy. Unfortunately, severe side effects are frequent and often require therapeutic interventions. Therefore, with the approval of less straining DAA like sofosbuvir in sight, TVR-based triple therapy in post-LT patients should be, if possible avoided.
Collapse
Affiliation(s)
- C R Werner
- University Hospital Tübingen, Medical Clinic, Department of Gastroenterology, Hepatology, and Infectiology, Tübingen, Germany
| | - D P Egetemeyr
- University Hospital Tübingen, Medical Clinic, Department of Gastroenterology, Hepatology, and Infectiology, Tübingen, Germany
| | - S Nadalin
- University Hospital Tübingen, Department of General, Visceral and Transplant Surgery, Tübingen, Germany
| | - A Königsrainer
- University Hospital Tübingen, Department of General, Visceral and Transplant Surgery, Tübingen, Germany
| | - N P Malek
- University Hospital Tübingen, Medical Clinic, Department of Gastroenterology, Hepatology, and Infectiology, Tübingen, Germany
| | - U M Lauer
- University Hospital Tübingen, Medical Clinic, Department of Gastroenterology, Hepatology, and Infectiology, Tübingen, Germany
| | - C P Berg
- University Hospital Tübingen, Medical Clinic, Department of Gastroenterology, Hepatology, and Infectiology, Tübingen, Germany
| |
Collapse
|