Environmental tuning of the genetic control of seed performance : a systems genetics approach

Serin, Elise A. R.

doi:10.18174/458202

Cited by 1 publication

(7 citation statements)

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“…For example, we analysed the correlation of the flowering time in a long day (FTLD) phenotype QTL of a Bay x Sha RIL population (Joosen et al 2012) with eQTLs from experiments using the same population in (Figure 4.4). We selected the top five correlated genes and found that an FLC eQTL profile on dry seed (Serin 2018) has the highest Spearman correlation coefficient (0.86) with the phenotype QTL. FLC is highly abundant in dry seeds to regulate temperature-dependent seed germination (Chiang et al 2009).…”

Section: Use Case 3: Correlation Between Phenotype and Gene Expressio...mentioning

confidence: 99%

“…Finnegan et al (2020) showed that the activation of FLC expression is started during embryo development and continues until the vegetative stage. In the transcriptome analysis of dry seed of Bay x Sha RILs (Serin 2018), FLC is expressed and shown to be regulated by two eQTLs (Figure 4.4). eQTL on chromosome 5 is collocated with the gene location, which is a likely cis-eQTL (e.g., variation in promoter leading to variation in gene expression).…”

Section: Chaptermentioning

confidence: 99%

“…We used seed germination phenotypes and gene expression data of dry seeds matured in four different maternal environments of 161 Arabidopsis RILs from Serin (2018) to test our fine-mapping approach. Seed germination phenotype QTLs (phQTLs) were mapped using the single marker method as in Hartanto et al (2020).…”

Section: Phenotype and Gene Expression Qtlsmentioning

confidence: 99%

“…Seed germination phenotype QTLs (phQTLs) were mapped using the single marker method as in Hartanto et al (2020). For gene expression QTL (eQTL) analysis, the gene expression data from RILs matured in all four different maternal environments were combined to identify the genetic main effect eQTLs, i.e., the QTL effect without interaction with the environment (Serin 2018). We identify the original location of phQTLs and eQTLs using the 1,059 bin markers found in (Serin et al 2017).…”

Section: Phenotype and Gene Expression Qtlsmentioning

confidence: 99%

“…A LOD threshold of 4.1 was used to determine significant QTLs, as in Serin (2018). QTL intervals were defined as the region between the upstream and downstream markers where a 1.5 LOD drop from the QTL peak marker was reached.…”

Section: Phenotype and Gene Expression Qtlsmentioning

confidence: 99%

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Linking genes to traits in Arabidopsis using systems genetics

Hartanto

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Pazhamala et al. 2021). Information about causal genes and their interactions could greatly help plant breeding, for example, to improve genomic prediction (Teng et al. 2020) or to provide targets for genome editing (Varshney et al. 2021). Causal gene discovery typically starts by finding an association between a trait and genetic variation in a plant population through quantitative trait locus (QTL) mapping.1.2. QTL mapping to identify the genetic component of plant traits Important target traits for plant breeding mostly show continuously distributed phenotypes. Such traits are called quantitative traits. A main characteristic of quantitative traits is that they are influenced by numerous genes (Hill 2010). For example, seed yield, the most important trait in oilseed rape (Brassica napus), was found to be associated with at least 85 distinct genomic locations (loci) (Shi et al. 2009). These trait-associated loci, individually known as quantitative trait locus (QTL), contain genes potentially controlling the trait.The most widely used method to identify QTLs is called linkage mapping, or simply QTL mapping (Bazakos et al. 2017). This method requires a population developed by crossing two or more parental plants that vary in the trait of interest, thus having different variants (alleles) of genes controlling the trait. The first filial (F1) generation is self-fertilised to generate a segregated F2 population, where the individuals have a combination of alleles from the parents. Self-fertilisation can be continued up to the F6 or even later generation to produce recombinant inbred lines with very high levels of allelic homozygosity (Loudet et al. 2002;Alonso-Blanco et al. 1998).In addition to a population, QTL mapping requires genetic markers to determine the genotypes of the parents and the offspring. Genetic markers are detectable DNA sequences located in the genome. These markers do not have to be located on the causal gene but could be in proximity so they can be inherited together (i.e., are in genetic linkage). To be informative, markers should be able to discriminate allelic variants in the mapping population (polymorphic). There are many types of genetic markers, of which the most widely used today are single nucleotide polymorphisms (SNPs), variations of a single nucleotide at a specific position in the genome (Collard and Mackill 2008;Collard et al. 2005).In general, QTL mapping analyses the correlation of the alleles of each marker with the corresponding trait values and defines QTL intervals based on markers showing significant correlation. From simple to more sophisticated, three common QTL mapping methods are single marker, simple interval, and composite interval mapping (Broman 2015). A QTL is usually presented as an interval indicating the location on the genome, together with the significance, the effect, and the most significant marker in the QTL. Plant breeders routinely use QTLs for marker-assisted selection. However, QTLs do not directly provide information about the biology of the trait. Sub...

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Section: Use Case 3: Correlation Between Phenotype and Gene Expressio...mentioning

confidence: 99%

Section: Chaptermentioning

confidence: 99%

Section: Phenotype and Gene Expression Qtlsmentioning

confidence: 99%

Section: Phenotype and Gene Expression Qtlsmentioning

confidence: 99%

Section: Phenotype and Gene Expression Qtlsmentioning

confidence: 99%

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Linking genes to traits in Arabidopsis using systems genetics

Hartanto

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Environmental tuning of the genetic control of seed performance : a systems genetics approach

Abstract: Environmental tuning of the genetic control of seed performance: a systems genetics approach, 214 pages.PhD thesis, Wageningen University, Wageningen, the Netherlands (2018) With references, with summary in English

Cited by 1 publication

References 351 publications

Linking genes to traits in Arabidopsis using systems genetics

Linking genes to traits in Arabidopsis using systems genetics

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