Dissection of the genetic basis of heterosis in an elite maize hybrid by QTL mapping in an immortalized F2 population

Abstract We introduced an experimental design that produced an “immortalized F2” population allowing for complete dissection of genetic components underlying quantitative traits. Data for yield and three component traits of the immortalized F2 were collected from replicated field trials over 2 years. Using 231 marker loci, we resolved the genetic effects into individual components and assessed relative performance of all the genotypes at both single- and two-locus levels. Single-locus analysis detected 40 QTL for the four traits. Dominance effects for about one-half of the QTL were negative, resulting in little “net” positive dominance effect. Correlation between genotype heterozygosity and trait performance was low. Large numbers of digenic interactions, including AA, AD, and DD, were detected for all the traits, with AA as the most prevalent interaction. Complementary two-locus homozygotes frequently performed the best among the nine genotypes of many two-locus combinations. While cumulative small advantages over two-locus combinations may partly explain the genetic basis of heterosis of the hybrid as double heterozygotes frequently demonstrated marginal advantages, double heterozygotes were never the best genotypes in any of the two-locus combinations. It was concluded that heterozygotes were not necessarily advantageous for trait performance even among genotypes derived from such a highly heterotic hybrid.

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Analysis of the genetic basis of plant height-related traits in response to ethylene by QTL mapping in maize (Zea mays L.)

PLoS ONE ◽

10.1371/journal.pone.0193072 ◽

2018 ◽

Vol 13 (2) ◽

pp. e0193072

Author(s):

Weiqiang Zhang ◽

Zhi Li ◽

Hui Fang ◽

Mingcai Zhang ◽

Liusheng Duan

Keyword(s):

Zea Mays ◽

Qtl Mapping ◽

Plant Height ◽

Genetic Basis ◽

Zea Mays L

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Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr x Holstein F2 population

Genetics and Molecular Biology ◽

10.1590/s1415-47572011005000049 ◽

2011 ◽

Vol 34 (4) ◽

pp. 575-582 ◽

Cited By ~ 6

Author(s):

Fabyano Fonseca Silva ◽

Karen P. Tunin ◽

Guilherme J.M. Rosa ◽

Marcos V.B. da Silva ◽

Ana Luisa Souza Azevedo ◽

...

Keyword(s):

Qtl Mapping ◽

Poisson Regression ◽

Regression Models ◽

F2 Population ◽

Tick Resistance

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QTL mapping and the genetic basis of adaptation: recent developments

Georgia Genetics Review III - Genetics of Adaptation ◽

10.1007/1-4020-3836-4_4 ◽

2005 ◽

pp. 25-37 ◽

Cited By ~ 1

Author(s):

Zhao-Bang Zeng

Keyword(s):

Qtl Mapping ◽

Genetic Basis ◽

Recent Developments

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Association mapping of leaf traits, flowering time, and phytate content in Brassica rapa

Genome ◽

10.1139/g07-078 ◽

2007 ◽

Vol 50 (10) ◽

pp. 963-973 ◽

Cited By ~ 62

Author(s):

Jianjun Zhao ◽

Maria-João Paulo ◽

Diaan Jamar ◽

Ping Lou ◽

Fred van Eeuwijk ◽

...

Keyword(s):

Population Structure ◽

Qtl Mapping ◽

Association Mapping ◽

Brassica Rapa ◽

Morphological Traits ◽

Genetic Basis ◽

Leaf Traits ◽

Structure Association ◽

Phytate Content ◽

Trait Associations

Association mapping was used to investigate the genetic basis of variation within Brassica rapa , which is an important vegetable and oil crop. We analyzed the variation of phytate and phosphate levels in seeds and leaves and additional developmental and morphological traits in a set of diverse B. rapa accessions and tested association of these traits with AFLP markers. The analysis of population structure revealed four subgroups in the population. Trait values differed between these subgroups, thus defining associations between population structure and trait values, even for traits such as phytate and phosphate levels. Marker–trait associations were investigated both with and without taking population structure into account. One hundred and seventy markers were found to be associated with the observed traits without correction for population structure. Association analysis with correction for population structure led to the identification of 27 markers, 6 of which had known map positions; 3 of these were confirmed in additional QTL mapping studies.

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QTL Mapping of a Brazilian Bioethanol Strain Unravels the Cell Wall Protein-Encoding Gene GAS1 as a Major Contributor to Low Ph Tolerance in S. Cerevisiae

10.21203/rs.3.rs-827768/v1 ◽

2021 ◽

Author(s):

Alessandro L V Coradini ◽

Fellipe da Silveira Bezerra de Mello ◽

Monique Furlan ◽

Carla Maneira ◽

Marcello Falsarella Carazzolle ◽

...

Keyword(s):

Qtl Mapping ◽

Genetic Architecture ◽

Genetic Basis ◽

Acid Resistance ◽

Low Ph ◽

Susceptible Strain ◽

Yeast Cells ◽

Synonymous Mutation ◽

Major Contributor ◽

Ph Tolerance

Abstract BACKGROUNDSaccharomyces cerevisiae is largely applied in many biotechnological processes, from traditional food and beverage industries to modern biofuel and biochemicals factories. During the fermentation process, yeast cells are usually challenged in different harsh conditions, which often impact productivity. Regarding bioethanol production, cell exposure to acidic environments is related to productivity loss on both first and second generation ethanol. In this scenario, indigenous strains traditionally used in fermentation stand out as a source of complex genetic architecture, mainly due to their highly robust background - including low pH tolerance. RESULTSIn this work, we pioneer the use of QTL mapping to uncover the genetic basis that endow industrial strain Pedra-2 (PE-2) with outstanding acid resistance. First, we developed a fluorescence-based high-throughput approach to collect a large number of haploid cells using flow cytometry. Then, we were able to apply a bulk segregant analysis to solve the genetic basis of low pH resistance in PE-2, which uncovered a region in chromosome XIII as the major QTL associated with the evaluated phenotype. A reciprocal hemizygosity analysis revealed allele GAS1, encoding a β-1,3-glucanosyltransferase, as the major contributor to this phenotype. The GAS1 sequence alignment of 48 S. cerevisiae strains pointed out a non-synonymous mutation (T211A) prevalence in wild type isolates, which is absent in laboratory strains. We further showcase that GAS1 allele swap between PE-2 and a low pH-susceptible strain can improve cell viability on the latter of up to 12% after a sulfuric acid wash process.CONCLUSIONThis work revealed GAS1 as the major causative gene associated with low pH resistance in PE-2, harboring a non-synonymous mutation persistent in industrial strains. We also showcase how GAS1PE-2 can improve acid resistance of a susceptible strain, suggesting that these findings can be a powerful foundation for the development of more robust and acid-tolerant strains for the industrial production of economically-relevant goods. Our results collectively show the importance of tailored industrial isolated strains in the discovery of the genetic architecture of relevant traits and its implications over productivity.

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Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast

10.1101/2021.09.08.459513 ◽

2021 ◽

Author(s):

Alex N. Nguyen Ba ◽

Katherine R. Lawrence ◽

Artur Rego-Costa ◽

Shreyas Gopalakrishnan ◽

Daniel Temko ◽

...

Keyword(s):

Quantitative Trait Locus ◽

Qtl Mapping ◽

Quantitative Trait ◽

Complex Traits ◽

Large Scale ◽

Genetic Basis ◽

Association Studies ◽

Model Organisms ◽

Genome Wide Association Studies ◽

Trait Locus

Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits.Significance statementUnderstanding the genetic basis of important phenotypes is a central goal of genetics. However, the highly polygenic architectures of complex traits inferred by large-scale genome-wide association studies (GWAS) in humans stand in contrast to the results of quantitative trait locus (QTL) mapping studies in model organisms. Here, we use a barcoding approach to conduct QTL mapping in budding yeast at a scale two orders of magnitude larger than the previous state of the art. The resulting increase in power reveals the polygenic nature of complex traits in yeast, and offers insight into widespread patterns of pleiotropy and epistasis. Our data and analysis methods offer opportunities for future work in systems biology, and have implications for large-scale GWAS in human populations.

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Development of a core RFLP map in maize using an immortalized F2 population.

Genetics ◽

10.1093/genetics/134.3.917 ◽

1993 ◽

Vol 134 (3) ◽

pp. 917-930 ◽

Cited By ~ 4

Author(s):

J M Gardiner ◽

E H Coe ◽

S Melia-Hancock ◽

D A Hoisington ◽

S Chao

Keyword(s):

Zea Mays L ◽

Mapping Population ◽

F2 Population ◽

Rflp Map ◽

Length Polymorphisms ◽

Segregation Ratios ◽

Maize Genetic ◽

Immortalized F2 ◽

Genomic Regions ◽

Aberrant Segregation

Abstract A map derived from restriction fragment length polymorphisms (RFLPs) in maize (Zea mays L.) is presented. The map was constructed in an immortalized Tx303 x CO159 F2 mapping population that allowed for an unlimited number of markers to be mapped and pooled F3 seed to be distributed to other laboratories. A total of 215 markers consisting of 159 genomic clones, 16 isozymes and 35 cloned genes of defined function have been placed on 10 chromosomes. An examination of segregation data has revealed several genomic regions with aberrant segregation ratios favoring either parent or the heterozygote. Mapping of cloned genes and isozymes that have been previously mapped by functional criteria has provided 29 points of alignment with the classical maize genetic map. Screening of all mapped RFLP probes against a collection of U.S. Corn Belt germplasm using EcoRI, HindIII and EcoRV has resulted in a set of 97 core markers being defined. The designation of a set of core markers allows the maize genome to be subdivided into a series of bins which serve as the backbone for maize genetic information and database boundaries. The merits and applications of core markers and bins are discussed.

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