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QTL Mapping of Seed Quality Traits in Crops

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A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Genetics, Genomics and Biotechnology".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 24058

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Prof. Dr. Abdelmajid Kassem

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Plant Genomics and Biotechnology Lab, Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA
Interests: plant genetics, genomics, and biotechnology; QTL mapping of important agronomic traits especially seed composition traits in soybean and other crops

Special Issue Information

Dear Colleagues,

Seeds of major crops contain many valuable compounds for the food and feed industry. Animal feed and human nutrition and health rely largely on seed proteins, amino acids, oils, fatty acids (palmitic, stearic, oleic, linoleic, linolenic acids, etc.), sugars (glucose, galactose, sucrose, raffinose, etc.), isoflavones (daidzein, genistein, glycitein, etc.), vitamins, minerals, secondary metabolites, and other nutrients.

Understanding the genetic basis of these beneficial compounds is very important, and many studies have been aimed at identifying and mapping QTL for these traits in the past 3 decades; however, most of these QTL regions are not well characterized, and candidate genes within these QTL regions are mostly unrevealed

This Special Issue of Plants will focus on genetic and QTL mapping of seed quality traits in crops using both traditional mapping populations (recombinant inbred lines (RILs), F2, doubled haploid, etc.) and genome-wide association studies (GWAS). Studies that also aim at identifying candidate genes within the identified QTL regions are most welcome.

Prof. Dr. Abdelmajid Kassem
Guest Editor

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Keywords

crops
QTL mapping
seed quality traits
GWAS
seed protein
oil
fatty acids
amino acids
sugars
isoflavones

Published Papers (11 papers)

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Research

15 pages, 1339 KiB

Open AccessArticle

QTLs and Candidate Genes for Seed Protein Content in Two Recombinant Inbred Line Populations of Soybean

by Hye Rang Park, Jeong Hyun Seo, Beom Kyu Kang, Jun Hoi Kim, Su Vin Heo, Man Soo Choi, Jee Yeon Ko and Choon Song Kim

Plants 2023, 12(20), 3589; https://doi.org/10.3390/plants12203589 - 16 Oct 2023

Cited by 2 | Viewed by 1193

Abstract

This study aimed to discover the quantitative trait loci (QTL) associated with a high seed protein content in soybean and unravel the potential candidate genes. We developed two recombinant inbred line populations: YS and SI, by crossing Saedanbaek (high protein) with YS2035-B-91-1-B-1 (low protein) and Saedanbaek with Ilmi (low protein), respectively, and evaluated the protein content for three consecutive years. Using single-nucleotide polymorphism (SNP)-marker-based linkage maps, four QTLs were located on chromosomes 15, 18, and 20 with high logarithm of odds values (5.9–55.0), contributing 5.5–66.0% phenotypic variance. In all three experimental years, qPSD20-1 and qPSD20-2 were stable and identified in overlapping positions in the YS and SI populations, respectively. Additionally, novel QTLs were identified on chromosomes 15 and 18. Considering the allelic sequence variation between parental lines, 28 annotated genes related to soybean seed protein—including starch, lipid, and fatty acid biosynthesis-related genes—were identified within the QTL regions. These genes could potentially affect protein accumulation during seed development, as well as sucrose and oil metabolism. Overall, this study offers insights into the genetic mechanisms underlying a high soybean protein content. The identified potential candidate genes can aid marker-assisted selection for developing soybean lines with an increased protein content. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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20 pages, 1800 KiB

Open AccessArticle

Quantitative Trait Loci and Candidate Genes That Control Seed Sugars Contents in the Soybean ‘Forrest’ by ‘Williams 82’ Recombinant Inbred Line Population

by Dounya Knizia, Nacer Bellaloui, Jiazheng Yuan, Naoufal Lakhssasi, Erdem Anil, Tri Vuong, Mohamed Embaby, Henry T. Nguyen, Alemu Mengistu, Khalid Meksem and My Abdelmajid Kassem

Plants 2023, 12(19), 3498; https://doi.org/10.3390/plants12193498 - 8 Oct 2023

Viewed by 1027

Abstract

Soybean seed sugars are among the most abundant beneficial compounds for human and animal consumption in soybean seeds. Higher seed sugars such as sucrose are desirable as they contribute to taste and flavor in soy-based food. Therefore, the objectives of this study were to use the ‘Forrest’ by ‘Williams 82’ (F × W82) recombinant inbred line (RIL) soybean population (n = 309) to identify quantitative trait loci (QTLs) and candidate genes that control seed sugar (sucrose, stachyose, and raffinose) contents in two environments (North Carolina and Illinois) over two years (2018 and 2020). A total of 26 QTLs that control seed sugar contents were identified and mapped on 16 soybean chromosomes (chrs.). Interestingly, five QTL regions were identified in both locations, Illinois and North Carolina, in this study on chrs. 2, 5, 13, 17, and 20. Amongst 57 candidate genes identified in this study, 16 were located within 10 Megabase (MB) of the identified QTLs. Amongst them, a cluster of four genes involved in the sugars’ pathway was collocated within 6 MB of two QTLs that were detected in this study on chr. 17. Further functional validation of the identified genes could be beneficial in breeding programs to produce soybean lines with high beneficial sucrose and low raffinose family oligosaccharides. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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11 pages, 672 KiB

Open AccessArticle

Identification of Novel QTLs Associated with Frost Tolerance in Winter Wheat (Triticum aestivum L.)

by Parisa Bolouri, Kamil Haliloğlu, Seyyed Abolghasem Mohammadi, Aras Türkoğlu, Emre İlhan, Gniewko Niedbała, Piotr Szulc and Mohsen Niazian

Plants 2023, 12(8), 1641; https://doi.org/10.3390/plants12081641 - 13 Apr 2023

Cited by 1 | Viewed by 1352

Abstract

Low temperature (cold) and freezing stress is a major problem during winter wheat growth. Low temperature tolerance (LT) is an important agronomic trait in winter wheat and determines the plants’ ability to cope with below-freezing temperatures; thus, the development of cold-tolerant cultivars has become a major goal of breeding in various regions of the world. In this study, we sought to identify quantitative trait loci (QTL) using molecular markers related to freezing tolerance in winter. Thirty-four polymorphic markers among 425 SSR markers were obtained for the population, including 180 inbred lines of F₁₂ generation wheat, derived from crosses (Norstar × Zagros) after testing with parents. LT₅₀ is used as an effective selection criterion for identifying frost-tolerance genotypes. The progeny of individual F₁₂ plants were used to evaluate LT50. Several QTLs related to wheat yield, including heading time period, 1000-seed weight, and number of surviving plants after overwintering, were identified. Single-marker analysis illustrated that four SSR markers with a total of 25% phenotypic variance determination were linked to LT50. Related QTLs were located on chromosomes 4A, 2B, and 3B. Common QTLs identified in two cropping seasons based on agronomical traits were two QTLs for heading time period, one QTL for 1000-seed weight, and six QTLs for number of surviving plants after overwintering. The four markers identified linked to LT₅₀ significantly affected both LT₅₀ and yield-related traits simultaneously. This is the first report to identify a major-effect QTL related to frost tolerance on chromosome 4A by the marker XGWM160. It is possible that some QTLs are closely related to pleiotropic effects that control two or more traits simultaneously, and this feature can be used as a factor to select frost-resistant lines in plant breeding programs. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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16 pages, 2597 KiB

Open AccessCommunication

Genetic Analyses of Seed Longevity in Capsicum annuum L. in Cold Storage Conditions

by Mian Abdur Rehman Arif, Pasquale Tripodi, Muhammad Qandeel Waheed, Irfan Afzal, Sibylle Pistrick, Gudrun Schütze and Andreas Börner

Plants 2023, 12(6), 1321; https://doi.org/10.3390/plants12061321 - 14 Mar 2023

Viewed by 1484

Abstract

Seed longevity is the most important trait in the genebank management system. No seed can remain infinitely viable. There are 1241 accessions of Capsicum annuum L. available at the German Federal ex situ genebank at IPK Gatersleben. C. annuum (Capsicum) is the most economically important species of the genus Capsicum. So far, there is no report that has addressed the genetic basis of seed longevity in Capsicum. Here, we convened a total of 1152 Capsicum accessions that were deposited in Gatersleben over forty years (from 1976 to 2017) and assessed their longevity by analyzing the standard germination percentage after 5–40 years of storage at −15/−18 °C. These data were used to determine the genetic causes of seed longevity, along with 23,462 single nucleotide polymorphism (SNP) markers covering all of the 12 Capsicum chromosomes. Using the association-mapping approach, we identified a total of 224 marker trait associations (MTAs) (34, 25, 31, 35, 39, 7, 21 and 32 MTAs after 5-, 10-, 15-, 20-, 25-, 30-, 35- and 40-year storage intervals) on all the Capsicum chromosomes. Several candidate genes were identified using the blast analysis of SNPs, and these candidate genes are discussed. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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21 pages, 2808 KiB

Open AccessArticle

QTL Analysis for Bread Wheat Seed Size, Shape and Color Characteristics Estimated by Digital Image Processing

by Mian Abdur Rehman Arif, Evgenii G. Komyshev, Mikhail A. Genaev, Vasily S. Koval, Nikolay A. Shmakov, Andreas Börner and Dmitry A. Afonnikov

Plants 2022, 11(16), 2105; https://doi.org/10.3390/plants11162105 - 12 Aug 2022

Cited by 5 | Viewed by 2380

Abstract

The size, shape, and color of wheat seeds are important traits that are associated with yield and flour quality (size, shape), nutritional value, and pre-harvest sprouting (coat color). These traits are under multigenic control, and to dissect their molecular and genetic basis, quantitative trait loci (QTL) analysis is used. We evaluated 114 recombinant inbred lines (RILs) in a bi-parental RIL mapping population (the International Triticeae Mapping Initiative, ITMI/MP) grown in 2014 season. We used digital image analysis for seed phenotyping and obtained data for seven traits describing seed size and shape and 48 traits of seed coat color. We identified 212 additive and 34 pairs of epistatic QTLs on all the chromosomes of wheat genome except chromosomes 1A and 5D. Many QTLs were overlapping. We demonstrated that the overlap between QTL regions was low for seed size/shape traits and high for coat color traits. Using the literature and KEGG data, we identified sets of genes in Arabidopsis and rice from the networks controlling seed size and color. Further, we identified 29 and 14 candidate genes for seed size-related loci and for loci associated with seed coat color, respectively. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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18 pages, 2388 KiB

Open AccessArticle

QTL and Candidate Genes for Seed Tocopherol Content in ‘Forrest’ by ‘Williams 82’ Recombinant Inbred Line (RIL) Population of Soybean

by Dounya Knizia, Jiazheng Yuan, Naoufal Lakhssassi, Abdelhalim El Baze, Mallory Cullen, Tri Vuong, Hamid Mazouz, Henry T. Nguyen, My Abdelmajid Kassem and Khalid Meksem

Plants 2022, 11(9), 1258; https://doi.org/10.3390/plants11091258 - 6 May 2022

Cited by 4 | Viewed by 1892

Abstract

Soybean seeds are rich in secondary metabolites which are beneficial for human health, including tocopherols. Tocopherols play an important role in human and animal nutrition thanks to their antioxidant activity. In this study, the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306) was used to map quantitative trait loci (QTL) for seed α-tocopherol, β-tocopherol, δ -tocopherol, γ-tocopherol, and total tocopherol contents in Carbondale, IL over two years. Also, the identification of the candidate genes involved in soybean tocopherols biosynthetic pathway was performed. A total of 32 QTL controlling various seed tocopherol contents have been identified and mapped on Chrs. 1, 2, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, and 20. One major and novel QTL was identified on Chr. 6 with an R² of 27.8, 9.9, and 6.9 for δ-tocopherol, α-tocopherol, and total tocopherol content, respectively. Reverse BLAST analysis of the genes that were identified in Arabidopsis allowed the identification of 37 genes involved in soybean tocopherol pathway, among which 11 were located close to the identified QTLs. The tocopherol cyclase gene (TC) Glyma.06G084100 is located close to the QTLs controlling δ-tocopherol (R² = 27.8), α-tocopherol (R² = 9.96), and total-tocopherol (R² = 6.95). The geranylgeranyl diphosphate reductase (GGDR) Glyma.05G026200 gene is located close to a QTL controlling total tocopherol content in soybean (R² = 4.42). The two methylphytylbenzoquinol methyltransferase (MPBQ-MT) candidate genes Glyma.02G002000 and Glyma.02G143700 are located close to a QTL controlling δ-tocopherol content (R² = 3.57). The two γ-tocopherol methyltransferase (γ-TMT) genes, Glyma.12G014200 and Glyma.12G014300, are located close to QTLs controlling (γ+ß) tocopherol content (R² = 8.86) and total tocopherol (R² = 5.94). The identified tocopherol seed QTLs and candidate genes will be beneficial in breeding programs to develop soybean cultivars with high tocopherol contents. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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18 pages, 2397 KiB

Open AccessArticle

Genome-Wide Association Reveals Trait Loci for Seed Glucosinolate Accumulation in Indian Mustard (Brassica juncea L.)

by Erwin Tandayu, Priyakshee Borpatragohain, Ramil Mauleon and Tobias Kretzschmar

Plants 2022, 11(3), 364; https://doi.org/10.3390/plants11030364 - 28 Jan 2022

Cited by 7 | Viewed by 3149

Abstract

Glucosinolates (GSLs) are sulphur- and nitrogen-containing secondary metabolites implicated in the fitness of Brassicaceae and appreciated for their pungency and health-conferring properties. In Indian mustard (Brassica juncea L.), GSL content and composition are seed-quality-determining traits affecting its economic value. Depending on the end use, i.e., condiment or oil, different GSL levels constitute breeding targets. The genetic control of GSL accumulation in Indian mustard, however, is poorly understood, and current knowledge of GSL biosynthesis and regulation is largely based on Arabidopsis thaliana. A genome-wide association study was carried out to dissect the genetic architecture of total GSL content and the content of two major GSLs, sinigrin and gluconapin, in a diverse panel of 158 Indian mustard lines, which broadly grouped into a South Asia cluster and outside-South-Asia cluster. Using 14,125 single-nucleotide polymorphisms (SNPs) as genotyping input, seven distinct significant associations were discovered for total GSL content, eight associations for sinigrin content and 19 for gluconapin. Close homologues of known GSL structural and regulatory genes were identified as candidate genes in proximity to peak SNPs. Our results provide a comprehensive map of the genetic control of GLS biosynthesis in Indian mustard, including priority targets for further investigation and molecular marker development. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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20 pages, 2347 KiB

Open AccessArticle

Portuguese Common Bean Natural Variation Helps to Clarify the Genetic Architecture of the Legume’s Nutritional Composition and Protein Quality

by Francisco A. Mendes, Susana T. Leitão, Verónica Correia, Elsa Mecha, Diego Rubiales, Maria Rosário Bronze and Maria Carlota Vaz Patto

Plants 2022, 11(1), 26; https://doi.org/10.3390/plants11010026 - 22 Dec 2021

Cited by 5 | Viewed by 2776

Abstract

Common bean is a nutritious food legume widely appreciated by consumers worldwide. It is a staple food in Latin America, and a component of the Mediterranean diet, being an affordable source of protein with high potential as a gourmet food. Breeding for nutritional quality, including both macro and micronutrients, and meeting organoleptic consumers’ preferences is a difficult task which is facilitated by uncovering the genetic basis of related traits. This study explored the diversity of 106 Portuguese common bean accessions, under two contrasting environments, to gain insight into the genetic basis of nutritional composition (ash, carbohydrates, fat, fiber, moisture, protein, and resistant starch contents) and protein quality (amino acid contents and trypsin inhibitor activity) traits through a genome-wide association study. Single-nucleotide polymorphism-trait associations were tested using linear mixed models accounting for the accessions’ genetic relatedness. Mapping resolution to the gene level was achieved in 56% of the cases, with 102 candidate genes proposed for 136 genomic regions associated with trait variation. Only one marker-trait association was stable across environments, highlighting the associations’ environment-specific nature and the importance of genotype × environment interaction for crops’ local adaptation and quality. This study provides novel information to better understand the molecular mechanisms regulating the nutritional quality in common bean and promising molecular tools to aid future breeding efforts to answer consumers’ concerns. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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10 pages, 4989 KiB

Open AccessArticle

Using Crop Databases to Explore Phenotypes: From QTL to Candidate Genes

by Anne V. Brown, David Grant and Rex T. Nelson

Plants 2021, 10(11), 2494; https://doi.org/10.3390/plants10112494 - 18 Nov 2021

Cited by 4 | Viewed by 1785

Abstract

Seeds, especially those of certain grasses and legumes, provide the majority of the protein and carbohydrates for much of the world’s population. Therefore, improvements in seed quality and yield are important drivers for the development of new crop varieties to feed a growing population. Quantitative Trait Loci (QTL) have been identified for many biologically interesting and agronomically important traits, including many seed quality traits. QTL can help explain the genetic architecture of the traits and can also be used to incorporate traits into new crop cultivars during breeding. Despite the important contributions that QTL have made to basic studies and plant breeding, knowing the exact gene(s) conditioning each QTL would greatly improve our ability to study the underlying genetics, biochemistry and regulatory networks. The data sets needed for identifying these genes are increasingly available and often housed in species- or clade-specific genetics and genomics databases. In this demonstration, we present a generalized walkthrough of how such databases can be used in these studies using SoyBase, the USDA soybean Genetics and Genomics Database, as an example. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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23 pages, 11571 KiB

Open AccessArticle

The Soybean High Density ‘Forrest’ by ‘Williams 82’ SNP-Based Genetic Linkage Map Identifies QTL and Candidate Genes for Seed Isoflavone Content

by Dounya Knizia, Jiazheng Yuan, Nacer Bellaloui, Tri Vuong, Mariola Usovsky, Qijian Song, Frances Betts, Teresa Register, Earl Williams, Naoufal Lakhssassi, Hamid Mazouz, Henry T. Nguyen, Khalid Meksem, Alemu Mengistu and My Abdelmajid Kassem

Plants 2021, 10(10), 2029; https://doi.org/10.3390/plants10102029 - 27 Sep 2021

Cited by 10 | Viewed by 2773

Abstract

Isoflavones are secondary metabolites that are abundant in soybean and other legume seeds providing health and nutrition benefits for both humans and animals. The objectives of this study were to construct a single nucleotide polymorphism (SNP)-based genetic linkage map using the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306); map quantitative trait loci (QTL) for seed daidzein, genistein, glycitein, and total isoflavone contents in two environments over two years (NC-2018 and IL-2020); identify candidate genes for seed isoflavone. The FXW82 SNP-based map was composed of 2075 SNPs and covered 4029.9 cM. A total of 27 QTL that control various seed isoflavone traits have been identified and mapped on chromosomes (Chrs.) 2, 4, 5, 6, 10, 12, 15, 19, and 20 in both NC-2018 (13 QTL) and IL-2020 (14 QTL). The six QTL regions on Chrs. 2, 4, 5, 12, 15, and 19 are novel regions while the other 21 QTL have been identified by other studies using different biparental mapping populations or genome-wide association studies (GWAS). A total of 130 candidate genes involved in isoflavone biosynthetic pathways have been identified on all 20 Chrs. And among them 16 have been identified and located within or close to the QTL identified in this study. Moreover, transcripts from four genes (Glyma.10G058200, Glyma.06G143000, Glyma.06G137100, and Glyma.06G137300) were highly abundant in Forrest and Williams 82 seeds. The identified QTL and four candidate genes will be useful in breeding programs to develop soybean cultivars with high beneficial isoflavone contents. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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21 pages, 1748 KiB

Open AccessArticle

Utilization of a Wheat50K SNP Microarray-Derived High-Density Genetic Map for QTL Mapping of Plant Height and Grain Traits in Wheat

by Dongyun Lv, Chuanliang Zhang, Rui Yv, Jianxin Yao, Jianhui Wu, Xiaopeng Song, Juntao Jian, Pengbo Song, Zeyuan Zhang, Dejun Han and Daojie Sun

Plants 2021, 10(6), 1167; https://doi.org/10.3390/plants10061167 - 8 Jun 2021

Cited by 14 | Viewed by 2407

Abstract

Plant height is significantly correlated with grain traits, which is a component of wheat yield. The purpose of this study is to investigate the main quantitative trait loci (QTLs) that control plant height and grain-related traits in multiple environments. In this study, we constructed a high-density genetic linkage map using the Wheat50K SNP Array to map QTLs for these traits in 198 recombinant inbred lines (RILs). The two ends of the chromosome were identified as recombination-rich areas in all chromosomes except chromosome 1B. Both the genetic map and the physical map showed a significant correlation, with a correlation coefficient between 0.63 and 0.99. However, there was almost no recombination between 1RS and 1BS. In terms of plant height, 1RS contributed to the reduction of plant height by 3.43 cm. In terms of grain length, 1RS contributed to the elongation of grain by 0.11 mm. A total of 43 QTLs were identified, including eight QTLs for plant height (PH), 11 QTLs for thousand grain weight (TGW), 15 QTLs for grain length (GL), and nine QTLs for grain width (GW), which explained 1.36–33.08% of the phenotypic variation. Seven were environment-stable QTLs, including two loci (Qph.nwafu-4B and Qph.nwafu-4D) that determined plant height. The explanation rates of phenotypic variation were 7.39–12.26% and 20.11–27.08%, respectively. One QTL, Qtgw.nwafu-4B, which influenced TGW, showed an explanation rate of 3.43–6.85% for phenotypic variation. Two co-segregating KASP markers were developed, and the physical locations corresponding to KASP_AX-109316968 and KASP_AX-109519968 were 25.888344 MB and 25.847691 MB, respectively. Qph.nwafu-4B, controlling plant height, and Qtgw.nwafu-4B, controlling TGW, had an obvious linkage relationship, with a distance of 7–8 cM. Breeding is based on molecular markers that control plant height and thousand-grain weight by selecting strains with low plant height and large grain weight. Another QTL, Qgw.nwafu-4D, which determined grain width, had an explanation rate of 3.43–6.85%. Three loci that affected grain length were Qgl.nwafu-5A, Qgl.nwafu-5D.2, and Qgl.nwafu-6B, illustrating the explanation rates of phenotypic variation as 6.72–9.59%, 5.62–7.75%, and 6.68–10.73%, respectively. Two QTL clusters were identified on chromosomes 4B and 4D. Full article

(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)

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