Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.1
3.5
Journals
Genes
Special Issues
Selection Methods in Plant Breeding: From Visual Phenotyping to NGS
share announcement

Selection Methods in Plant Breeding: From Visual Phenotyping to NGS

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Plant Genetics and Genomics".

Deadline for manuscript submissions: closed (20 July 2020) | Viewed by 42211

Special Issue Editors

Dr. Dan Milbourne

E-Mail Website
Guest Editor
Teagasc - Irish Agriculture and Food Development Authority, Crops Research Centre, Carlow R93 XE12, Ireland
Interests: molecular genetics; genomics, breeding tools, potato breeding
Dr. Tony Slater

E-Mail
Guest Editor
AgriBio, Melbourne, Australia

Special Issue Information

Dear Colleagues

We are entering a “Golden Era” of plant breeding, where advances across a range of allied disciplines and associated technological advances are enhancing our ability to breed better varieties in a faster, more efficient, and more targeted manner. These advances are incredibly timely in the face of population expansion across valuable agricultural land, resource limitation, and climate instability. To secure food production and agricultural output against the backdrop of these challenges, the role of plant breeding has never been more important.

The sequencing of crop plant genomes is leading to a greater understanding of gene function and the underlying control of key plant processes, giving plant breeders the potential to “design” plant varieties with increased resilience to abiotic and biotic stresses, whilst increasing yield and quality characteristics. At the same time, advances in DNA sequencing and genotyping, phenotyping techniques, and predictive data analytics are being combined in approaches such as marker-assisted selection and genomic selection, radically speeding up plant breeding, which is vital if agriculture is going to feed the predicted future population. In this Special Issue of Genes, we invite you to submit papers exploring how these exciting developments are being applied to your favorite crop species.

Dr. Dan Milbourne
Dr. Tony Slater
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Phenotyping
  • Next-Generation Sequencing
  • Quantitative Trait Loci
  • Abiotic stress
  • Disease resistance
  • Yield
  • Quality
  • Breeding values
  • Marker-assisted selection
  • Genotyping
  • Genomic Selection
  • Speed Breeding

Published Papers (11 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 2293 KiB  
Article
Genetic Characterization of Russian Rapeseed Collection and Association Mapping of Novel Loci Affecting Glucosinolate Content
by Rim Gubaev, Lyudmila Gorlova, Stepan Boldyrev, Svetlana Goryunova, Denis Goryunov, Pavel Mazin, Alina Chernova, Elena Martynova, Yakov Demurin and Philipp Khaitovich
Genes 2020, 11(8), 926; https://doi.org/10.3390/genes11080926 - 12 Aug 2020
Cited by 3 | Viewed by 4473
Abstract
Rapeseed is the second most common oilseed crop worldwide. While the start of rapeseed breeding in Russia dates back to the middle of the 20th century, its widespread cultivation began only recently. In contrast to the world’s rapeseed genetic variation, the genetic composition [...] Read more.
Rapeseed is the second most common oilseed crop worldwide. While the start of rapeseed breeding in Russia dates back to the middle of the 20th century, its widespread cultivation began only recently. In contrast to the world’s rapeseed genetic variation, the genetic composition of Russian rapeseed lines remained unexplored. We have addressed this question by performing genome-wide genotyping of 90 advanced rapeseed accessions provided by the All-Russian Research Institute of Oil Crops (VNIIMK). Genome-wide genetic analysis demonstrated a clear difference between Russian rapeseed varieties and the rapeseed varieties from the rest of the world, including the European ones, indicating that rapeseed breeding in Russia proceeded in its own independent direction. Hence, genetic determinants of agronomical traits might also be different in Russian rapeseed lines. To assess it, we collected the glucosinolate content data for the same 90 genotyped accessions obtained during three years and performed an association mapping of this trait. We indeed found that the loci significantly associated with glucosinolate content variation in the Russian rapeseed collection differ from those previously reported for the non-Russian rapeseed lines. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

27 pages, 4600 KiB  
Article
Genetic Analysis Using a Multi-Parent Wheat Population Identifies Novel Sources of Septoria Tritici Blotch Resistance
by Adnan Riaz, Petra KockAppelgren, James Gerard Hehir, Jie Kang, Fergus Meade, James Cockram, Dan Milbourne, John Spink, Ewen Mullins and Stephen Byrne
Genes 2020, 11(8), 887; https://doi.org/10.3390/genes11080887 - 04 Aug 2020
Cited by 15 | Viewed by 5262
Abstract
Zymoseptoria tritici is the causative fungal pathogen of septoria tritici blotch (STB) disease of wheat (Triticum aestivum L.) that continuously threatens wheat crops in Ireland and throughout Europe. Under favorable conditions, STB can cause up to 50% yield losses if left untreated. [...] Read more.
Zymoseptoria tritici is the causative fungal pathogen of septoria tritici blotch (STB) disease of wheat (Triticum aestivum L.) that continuously threatens wheat crops in Ireland and throughout Europe. Under favorable conditions, STB can cause up to 50% yield losses if left untreated. STB is commonly controlled with fungicides; however, a combination of Z. tritici populations developing fungicide resistance and increased restrictions on fungicide use in the EU has led to farmers relying on fewer active substances. Consequently, this serves to drive the emergence of Z. tritici resistance against the remaining chemistries. In response, the use of resistant wheat varieties provides a more sustainable disease management strategy. However, the number of varieties offering an adequate level of resistance against STB is limited. Therefore, new sources of resistance or improved stacking of existing resistance loci are needed to develop varieties with superior agronomic performance. Here, we identified quantitative trait loci (QTL) for STB resistance in the eight-founder “NIAB Elite MAGIC” winter wheat population. The population was screened for STB response in the field under natural infection for three seasons from 2016 to 2018. Twenty-five QTL associated with STB resistance were identified in total. QTL either co-located with previously reported QTL or represent new loci underpinning STB resistance. The genomic regions identified and the linked genetic markers serve as useful resources for STB resistance breeding, supporting rapid selection of favorable alleles for the breeding of new wheat cultivars with improved STB resistance. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

15 pages, 917 KiB  
Article
Major QTLs for Trunk Height and Correlated Agronomic Traits Provide Insights into Multiple Trait Integration in Oil Palm Breeding
by Chee-Keng Teh, Ai-Ling Ong, Sean Mayes, Festo Massawe and David Ross Appleton
Genes 2020, 11(7), 826; https://doi.org/10.3390/genes11070826 - 21 Jul 2020
Cited by 13 | Viewed by 3682
Abstract
Superior oil yield is always the top priority of the oil palm industry. Short trunk height (THT) and compactness traits have become increasingly important to improve harvesting efficiency since the industry started to suffer yield losses due to labor shortages. Breeding populations with [...] Read more.
Superior oil yield is always the top priority of the oil palm industry. Short trunk height (THT) and compactness traits have become increasingly important to improve harvesting efficiency since the industry started to suffer yield losses due to labor shortages. Breeding populations with low THT and short frond length (FL) are actually available, such as Dumpy AVROS pisifera (DAV) and Gunung Melayu dura (GM). However, multiple trait stacking still remains a challenge for oil palm breeding, which usually requires 12–20 years to complete a breeding cycle. In this study, yield and height increment in the GM × GM (GM-3341) and the GM × DAV (GM-DAV-3461) crossing programs were evaluated and palms with good yield and smaller height increment were identified. In the GM-3341 family, non-linear THT growth between THT_2008 (seven years old) and THT_2014 (13 years old) was revealed by a moderate correlation, suggesting that inter-palm competition becomes increasingly important. In total, 19 quantitative trait loci (QTLs) for THT_2008 (8), oil per palm (O/P) (7) and FL (4) were localized on the GM-3341 linkage map, with an average mapping interval of 2.01 cM. Three major QTLs for THT_2008, O/P and FL are co-located on chromosome 11 and reflect the correlation of THT_2008 with O/P and FL. Multiple trait selection for high O/P and low THT (based on the cumulative effects of positive alleles per trait) identified one palm from 100 palms, but with a large starting population of 1000–1500 seedling per cross, this low frequency could be easily compensated for during breeding selection. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

14 pages, 1069 KiB  
Article
Genomic Selection in Winter Wheat Breeding Using a Recommender Approach
by Dennis N. Lozada and Arron H. Carter
Genes 2020, 11(7), 779; https://doi.org/10.3390/genes11070779 - 11 Jul 2020
Cited by 12 | Viewed by 2862
Abstract
Achieving optimal predictive ability is key to increasing the relevance of implementing genomic selection (GS) approaches in plant breeding programs. The potential of an item-based collaborative filtering (IBCF) recommender system in the context of multi-trait, multi-environment GS has been explored. Different GS scenarios [...] Read more.
Achieving optimal predictive ability is key to increasing the relevance of implementing genomic selection (GS) approaches in plant breeding programs. The potential of an item-based collaborative filtering (IBCF) recommender system in the context of multi-trait, multi-environment GS has been explored. Different GS scenarios for IBCF were evaluated for a diverse population of winter wheat lines adapted to the Pacific Northwest region of the US. Predictions across years through cross-validations resulted in improved predictive ability when there is a high correlation between environments. Using multiple spectral traits collected from high-throughput phenotyping resulted in better GS accuracies for grain yield (GY) compared to using only single traits for predictions. Trait adjustments through various Bayesian regression models using genomic information from SNP markers was the most effective in achieving improved accuracies for GY, heading date, and plant height among the GS scenarios evaluated. Bayesian LASSO had the highest predictive ability compared to other models for phenotypic trait adjustments. IBCF gave competitive accuracies compared to a genomic best linear unbiased predictor (GBLUP) model for predicting different traits. Overall, an IBCF approach could be used as an alternative to traditional prediction models for important target traits in wheat breeding programs. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

18 pages, 1394 KiB  
Article
Detection of Novel QTLs for Late Blight Resistance Derived from the Wild Potato Species Solanum microdontum and Solanum pampasense
by Fergus Meade, Ronald Hutten, Silke Wagener, Vanessa Prigge, Emmet Dalton, Hanne Grethe Kirk, Denis Griffin and Dan Milbourne
Genes 2020, 11(7), 732; https://doi.org/10.3390/genes11070732 - 30 Jun 2020
Cited by 8 | Viewed by 2859
Abstract
Wild potato species continue to be a rich source of genes for resistance to late blight in potato breeding. Whilst many dominant resistance genes from such sources have been characterised and used in breeding, quantitative resistance also offers potential for breeding when the [...] Read more.
Wild potato species continue to be a rich source of genes for resistance to late blight in potato breeding. Whilst many dominant resistance genes from such sources have been characterised and used in breeding, quantitative resistance also offers potential for breeding when the loci underlying the resistance can be identified and tagged using molecular markers. In this study, F1 populations were created from crosses between blight susceptible parents and lines exhibiting strong partial resistance to late blight derived from the South American wild species Solanum microdontum and Solanum pampasense. Both populations exhibited continuous variation for resistance to late blight over multiple field-testing seasons. High density genetic maps were created using single nucleotide polymorphism (SNP) markers, enabling mapping of quantitative trait loci (QTLs) for late blight resistance that were consistently expressed over multiple years in both populations. In the population created with the S. microdontum source, QTLs for resistance consistently expressed over three years and explaining a large portion (21–47%) of the phenotypic variation were found on chromosomes 5 and 6, and a further resistance QTL on chromosome 10, apparently related to foliar development, was discovered in 2016 only. In the population created with the S. pampasense source, QTLs for resistance were found in over two years on chromosomes 11 and 12. For all loci detected consistently across years, the QTLs span known R gene clusters and so they likely represent novel late blight resistance genes. Simple genetic models following the effect of the presence or absence of SNPs associated with consistently effective loci in both populations demonstrated that marker assisted selection (MAS) strategies to introgress and pyramid these loci have potential in resistance breeding strategies. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

22 pages, 1845 KiB  
Article
Identification of QTNs and Their Candidate Genes for 100-Seed Weight in Soybean (Glycine max L.) Using Multi-Locus Genome-Wide Association Studies
by Muhammad Ikram, Xu Han, Jian-Fang Zuo, Jian Song, Chun-Yu Han, Ya-Wen Zhang and Yuan-Ming Zhang
Genes 2020, 11(7), 714; https://doi.org/10.3390/genes11070714 - 27 Jun 2020
Cited by 18 | Viewed by 3819
Abstract
100-seed weight (100-SW) in soybeans is a yield component trait and controlled by multiple genes with different effects, but limited information is available for its quantitative trait nucleotides (QTNs) and candidate genes. To better understand the genetic architecture underlying the trait and improve [...] Read more.
100-seed weight (100-SW) in soybeans is a yield component trait and controlled by multiple genes with different effects, but limited information is available for its quantitative trait nucleotides (QTNs) and candidate genes. To better understand the genetic architecture underlying the trait and improve the precision of marker-assisted selection, a total of 43,834 single nucleotide polymorphisms (SNPs) in 250 soybean accessions were used to identify significant QTNs for 100-SW in four environments and their BLUP values using six multi-locus and one single-locus genome-wide association study methods. As a result, a total of 218 significant QTNs were detected using multi-locus methods, whereas eight QTNs were identified by a single-locus method. Among 43 QTNs or QTN clusters identified repeatedly across various environments and/or approaches, all of them exhibited significant trait differences between their corresponding alleles, 33 were found in the genomic region of previously reported QTLs, 10 were identified as new QTNs, and three (qHSW-4-1, qcHSW-7-3, and qcHSW-10-4) were detected in all the four environments. The number of seed weight (SW) increasing alleles for each accession ranged from 8 (18.6%) to 36 (83.72%), and three accessions (Yixingwuhuangdou, Nannong 95C-5, and Yafanzaodou) had more than 35 SW increasing alleles. Among 36 homologous seed-weight genes in Arabidopsis underlying the above 43 stable QTNs, more importantly, Glyma05g34120, GmCRY1, and GmCPK11 had known seed-size/weight-related genes in soybean, and Glyma07g07850, Glyma10g03440, and Glyma10g36070 were candidate genes identified in this study. These results provide useful information for genetic foundation, marker-assisted selection, genomic prediction, and functional genomics of 100-SW. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

10 pages, 3675 KiB  
Article
Identification of Genetic Locus Underlying Easy Dehulling in Rice-Tartary for Easy Postharvest Processing of Tartary Buckwheat
by Lijun Zhang, Mingchuan Ma and Longlong Liu
Genes 2020, 11(4), 459; https://doi.org/10.3390/genes11040459 - 23 Apr 2020
Cited by 11 | Viewed by 2543
Abstract
As a highly nutritious crop, Tartary buckwheat (Fagopyrum tartaricum) strongly adapts and grows in adverse environments and is widely grown in Asia. However, its flour contains a large proportion of the hull that adheres to the testa layer of the groats and [...] Read more.
As a highly nutritious crop, Tartary buckwheat (Fagopyrum tartaricum) strongly adapts and grows in adverse environments and is widely grown in Asia. However, its flour contains a large proportion of the hull that adheres to the testa layer of the groats and is difficult to be removed in industrial processing. Fortunately, rice-Tartary, with the loose and non-adhering hull, provides potentiality of improving Tartary buckwheat that can dehull easily. Here, we performed high-throughput sequencing for two parents (Tartary buckwheat and rice-Tartary) and two pools (samples from the F2 population) and obtained 101 Gb raw sequencing data for further analysis. Sequencing reads were mapped to the reference genome of Tartary buckwheat, and a total of 633,256 unique SNPs and 270,181 unique indels were found in these four samples. Then, based on the Bulked Segregant Analysis (BSA), we identified a candidate genetic region, containing 45 impact SNPs/indels and 36 genes, that might underly non-adhering hull of rice-Tartary and should have value for breeding easy dehulling Tartary buckwheat. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

15 pages, 997 KiB  
Article
Screening for Resistance to PVY in Australian Potato Germplasm
by Anthony T. Slater, Lee Schultz, Maria Lombardi, Brendan C. Rodoni, Chris Bottcher, Noel O. I. Cogan and John W. Forster
Genes 2020, 11(4), 429; https://doi.org/10.3390/genes11040429 - 16 Apr 2020
Cited by 12 | Viewed by 3751
Abstract
Potatoes are an important human food crop, but have a number of yield limiting factors, including disease susceptibility. Potato virus Y (PVY) is found worldwide, and is one of the main virus problems for potato growers. PVY is transmitted by aphids and mechanically [...] Read more.
Potatoes are an important human food crop, but have a number of yield limiting factors, including disease susceptibility. Potato virus Y (PVY) is found worldwide, and is one of the main virus problems for potato growers. PVY is transmitted by aphids and mechanically by machinery, tools and people, and symptoms are variable across cultivars and strains, including being symptomless in some cultivars. Therefore, breeding resistant cultivars is the best way to control this virus. This study phenotypically screened 74 of the main commercial cultivars and a few other select cultivars grown in Australia, in order to identify sources of resistance to PVY. The cultivars were screened against PVYO and PVYNTN, with 23 out of 71 resistant to PVYO and 13 out of 74 resistant to PVYNTN, and all these 13 were resistant to both strains. When the phenotypic screening was compared to the results listed on the European Cultivated Potato Database, the majority of results were found to be consistent. We then evaluated three molecular markers RYSC3, M45, and STM0003 for the extreme resistance genes Ryadg and Rysto, to validate the usefulness of the markers for marker-assisted selection (MAS) on Australian germplasm. The degree of correlation between the resistance phenotypes and the RYSC3, M45, and STM0003 markers for Ryadg and Rysto conferred PVY resistance was determined. Three cultivars amplified the RYSC3 marker, while the M45 marker amplified the same 3 and an additional 9. Of the 12 cultivars, 11 phenotyped as resistant, but 1 was susceptible. The STM0003 marker was amplified from only 2 cultivars that both had resistant phenotypes. The RYSC3, M45, and STM0003 markers were therefore able to identify all the 13 cultivars that were resistant to both strains of PVY. Therefore, these markers will enable the identification of genotypes with resistance to PVY, and enable PVY resistant parents to be used for the development of superior progeny; these genetic markers can be used for MAS in the Australian potato breeding program. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

17 pages, 2683 KiB  
Article
A Genome-Wide Association Study Revealed Key SNPs/Genes Associated With Salinity Stress Tolerance In Upland Cotton
by Muhammad Yasir, Shoupu He, Gaofei Sun, Xiaoli Geng, Zhaoe Pan, Wenfang Gong, Yinhua Jia and Xiongming Du
Genes 2019, 10(10), 829; https://doi.org/10.3390/genes10100829 - 21 Oct 2019
Cited by 29 | Viewed by 3884
Abstract
Millions of hectares of land are too saline to produce economically valuable crop yields. Salt tolerance in cotton is an imperative approach for improvement in response to ever-increasing soil salinization. Little is known about the genetic basis of salt tolerance in cotton at [...] Read more.
Millions of hectares of land are too saline to produce economically valuable crop yields. Salt tolerance in cotton is an imperative approach for improvement in response to ever-increasing soil salinization. Little is known about the genetic basis of salt tolerance in cotton at the seedling stage. To address this issue, a genome-wide association study (GWAS) was conducted on a core collection of a genetically diverse population of upland cotton (Gossypium hirsutum L.) comprising of 419 accessions, representing various geographic origins, including China, USA, Pakistan, the former Soviet Union, Chad, Australia, Brazil, Mexico, Sudan, and Uganda. Phenotypic evaluation of 7 traits under control (0 mM) and treatment (150 mM) NaCl conditions depicted the presence of broad natural variation in the studied population. The association study was carried out with the efficient mixed-model association eXpedited software package. A total of 17,264 single-nucleotide polymorphisms (SNPs) associated with different salinity stress tolerance related traits were found. Twenty-three candidate SNPs related to salinity stress-related traits were selected. Final key SNPs were selected based on the r2 value with nearby SNPs in a linkage disequilibrium (LD) block. Twenty putative candidate genes surrounding SNPs, A10_95330133 and D10_61258588, associated with leaf relative water content, RWC_150, and leaf fresh weight, FW_150, were identified, respectively. We further validated the expression patterns of twelve candidate genes with qRT-PCR, which revealed different expression levels in salt-tolerant and salt-sensitive genotypes. The results of our GWAS provide useful knowledge about the genetic control of salt tolerance at the seedling stage, which could assist in elucidating the genetic and molecular mechanisms of salinity stress tolerance in cotton plants. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

13 pages, 3167 KiB  
Article
Whole Genome Diversity, Population Structure, and Linkage Disequilibrium Analysis of Chickpea  (Cicer arietinum L.) Genotypes Using Genome-Wide DArTseq-Based SNP Markers
by Somayeh Farahani, Mojdeh Maleki, Rahim Mehrabi, Homayoun Kanouni, Armin Scheben, Jacqueline Batley and Reza Talebi
Genes 2019, 10(9), 676; https://doi.org/10.3390/genes10090676 - 04 Sep 2019
Cited by 25 | Viewed by 4716
Abstract
Characterization of genetic diversity, population structure, and linkage disequilibrium is a prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes, including advanced “Kabuli” breeding lines and Iranian landrace “Desi” chickpea [...] Read more.
Characterization of genetic diversity, population structure, and linkage disequilibrium is a prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes, including advanced “Kabuli” breeding lines and Iranian landrace “Desi” chickpea genotypes, were genotyped using DArTseq-Based single nucleotide polymorphism (SNP) markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that was covered by SNPs varied from 16,236.36 kbp (LG8) to 67,923.99 kbp (LG5), while LG4 showed a higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6, and LG8 showed higher mean PIC value than average. Unweighted neighbor joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and discriminant analysis of principal component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r2 ≥ 0.8, while 2961 pairs of markers showed complete LD (r2 = 1), and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggest the presence of a high genetic diversity among the studied chickpea genotypes. This study also demonstrates the efficiency of DArTseq-based SNP genotyping for large-scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits, such as seed yield, abiotic, and biotic stresses, and therefore can be efficiently used in breeding programs to improve chickpea. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

19 pages, 2926 KiB  
Article
Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material
by Peter S. Kristensen, Just Jensen, Jeppe R. Andersen, Carlos Guzmán, Jihad Orabi and Ahmed Jahoor
Genes 2019, 10(9), 669; https://doi.org/10.3390/genes10090669 - 31 Aug 2019
Cited by 14 | Viewed by 3471
Abstract
Use of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed [...] Read more.
Use of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed single nucleotide polymorphisms (SNPs) on chromosome 5D significantly associated with flour yield, Alveograph P (dough tenacity), and Alveograph W (dough strength). Additionally, SNPs on chromosome 1D were associated with Alveograph P and W, SNPs on chromosome 1B were associated with Alveograph P, and SNPs on chromosome 4A were associated with Alveograph L (dough extensibility). Predictive abilities based on genomic best linear unbiased prediction (GBLUP) models ranged from 0.50 for flour yield to 0.79 for Alveograph W based on a leave-one-out cross-validation strategy. Predictive abilities were negatively affected by smaller training set sizes, lower genetic relationship between lines in training and validation sets, and by genotype–environment (G×E) interactions. Bayesian Power Lasso models and genomic feature models resulted in similar or slightly improved predictions compared to GBLUP models. SNPs with the largest effects can be used for screening large numbers of lines in early generations in breeding programs to select lines that potentially have good quality traits. In later generations, genomic predictions might be used for a more accurate selection of high quality wheat lines. Full article
(This article belongs to the Special Issue Selection Methods in Plant Breeding: From Visual Phenotyping to NGS)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-11
Back to TopTop