Selection Mapping of Loci for Quantitative Disease Resistance in a Diverse Maize Population

Wisser, Randall J.; Murray, Seth C.; Kolkman, Judith M.; Ceballos, Hernán; Nelson, Rebecca

doi:10.1534/genetics.108.090118

Cited by 40 publications

(45 citation statements)

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“…Methods for identifying selection in these artificially selected populations may include any of the methods utilized for natural populations, but a benefit of these types of studies is that samples of the progenitor population are frequently available, which allows for direct measurement of allele frequency changes. Separation of selection vs. genetic drift effects has been performed by comparing allele frequencies to simulations of drift (Wisser et al 2008) and by developing significance tests based on replicated or control populations (Parts et al 2011;Turner et al 2011).…”

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confidence: 99%

“…Often, plant species have the advantage that remnant seeds representing a population before selection began often remain available for years or decades following the selection process itself (e.g., Odhiambo and Compton 1987). This characteristic was utilized by Wisser et al (2008), who compared marker data gathered from samples before and after several generations of selection to identify loci affecting northern leaf blight resistance in closed populations of maize that had undergone selection.…”

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confidence: 99%

“…Modern research and breeding investments have provided numerous examples of existing maize populations that have been selected for a particular trait over time spans ranging from only a few cycles to .100 generations (e.g., Odhiambo and Compton 1987;Coors and Mardones 1989;Ross et al 2006;Dudley 2007;Wisser et al 2008). One such example involves the Golden Glow maize selection project (Coors and Mardones 1989), which has undergone selection for a specific yield component, prolificacy, defined as the number of ears per plant.…”

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A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number

et al. 2014

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A genome-wide scan to detect evidence of selection was conducted in the Golden Glow maize long-term selection population. The population had been subjected to selection for increased number of ears per plant for 30 generations, with an empirically estimated effective population size ranging from 384 to 667 individuals and an increase of more than threefold in the number of ears per plant. Allele frequencies at .1.2 million single-nucleotide polymorphism loci were estimated from pooled wholegenome resequencing data, and F ST values across sliding windows were employed to assess divergence between the population preselection and the population postselection. Twenty-eight highly divergent regions were identified, with half of these regions providing gene-level resolution on potentially selected variants. Approximately 93% of the divergent regions do not demonstrate a significant decrease in heterozygosity, which suggests that they are not approaching fixation. Also, most regions display a pattern consistent with a soft-sweep model as opposed to a hard-sweep model, suggesting that selection mostly operated on standing genetic variation. For at least 25% of the regions, results suggest that selection operated on variants located outside of currently annotated coding regions. These results provide insights into the underlying genetic effects of long-term artificial selection and identification of putative genetic elements underlying number of ears per plant in maize.

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A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number

et al. 2014

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“…Therefore, the assessment of allele frequency change is a useful technique for identifying genomic regions that were targeted by selection (Lewontin 1962). Specific methods vary depending on the populations under study and the genotyping methods employed (Wright 1951;Akey et al 2002;Sabeti et al 2002;Oleksyk et al 2008;Wisser et al 2008;Turner et al 2011). For example, in natural populations, statistics that measure population divergence such as F ST (Wright 1951) can be calculated and loci displaying extreme values above an empirically determined genome-wide threshold are implicated as potentially associated with selection (Akey et al 2002;Oleksyk et al 2008).…”

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Insights into the Effects of Long-Term Artificial Selection on Seed Size in Maize

et al. 2014

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Grain produced from cereal crops is a primary source of human food and animal feed worldwide. To understand the genetic basis of seed-size variation, a grain yield component, we conducted a genome-wide scan to detect evidence of selection in the maize Krug Yellow Dent long-term divergent seed-size selection experiment. Previous studies have documented significant phenotypic divergence between the populations. Allele frequency estimates for 3 million single nucleotide polymorphisms (SNPs) in the base population and selected populations were estimated from pooled whole-genome resequencing of 48 individuals per population. Using F ST values across sliding windows, 94 divergent regions with a median of six genes per region were identified. Additionally, 2729 SNPs that reached fixation in both selected populations with opposing fixed alleles were identified, many of which clustered in two regions of the genome. Copy-number variation was highly prevalent between the selected populations, with 532 total regions identified on the basis of read-depth variation and comparative genome hybridization. Regions important for seed weight in natural variation were identified in the maize nested association mapping population. However, the number of regions that overlapped with the long-term selection experiment did not exceed that expected by chance, possibly indicating unique sources of variation between the two populations. The results of this study provide insights into the genetic elements underlying seed-size variation in maize and could also have applications for other cereal crops.G RAIN produced by cereal crops is a staple food source in many regions of the world in terms of direct human consumption and as an animal feed source. Understanding the molecular mechanisms underlying cereal grain yield and exploiting that knowledge through improved cultivars is essential to providing a stable food source to an ever-growing human population. Yield-component traits are of particular interest, as they generally have a higher heritability than grain yield per se (Austin and Lee 1998). For example, increasing seed size has been hypothesized as one method for increasing grain yield in cereal crops (Odhiambo and Compton 1987;Kesavan et al. 2013), and positive correlations between seed size and grain yield have been shown in maize (Peng et al. 2011) as well as other cereals such as Sorghum bicolor (L.) Moench (Yang et al. 2010). Maize is a prime species with which to explore natural and artificial variation related to grain-yield and yield-component traits in the cereals, as it is the most widely grown cereal crop worldwide and has vast genetic resources for probing the genetic basis of seed traits. The maize seed is composed of the embryo and endosperm that develop from double fertilization, the aleurone, which is an epidermal layer that covers the endosperm, and the maternal pericarp tissue. The endosperm, the primary storage component of the seed in maize, consists primarily of starch, while the embryo is high in oil conte...

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“…For many of these factors, appropriate tests for selection have been developed and are in wide use. For instance, in cases of directed evolution with experimental populations, especially for those with biological replication, changes in allele frequency may be directly measured to identify single-locus selection (Wisser et al, 2008;Turner et al, 2011;Parts et al, 2011;Hirsch et al, 2014). In a related test, which is particularly useful if samples from pre-selection populations are not available, patterns of nucleotide variability between vs within populations may be leveraged to identify selection at a single locus (Lewontin and Krakauer, 1973;Akey et al, 2002;Beissinger et al, 2013).…”

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Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens

et al. 2015

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A whole-genome scan for identifying selection acting on pairs of linked loci is proposed and implemented. The scan is based on Dʹ 2 IS , one of Ohta's 1982 measures of between-population linkage disequilibrium (LD). An approximate empirical null distribution for the statistic is suggested. Although the partitioning of LD into between-population components was originally used to investigate epistatic selection, we demonstrate that values of Dʹ 2 IS may also be influenced by single-locus selective sweeps with linkage but no epistasis. The proposed scan is implemented in a diverse panel of chickens including 72 distinct breeds genotyped at 538 298 single-nucleotide polymorphisms. In all, 1723 locus pairs are identified as putatively corresponding to a selective sweep or epistatic selection. These pairs of loci generally cluster to form overlapping or neighboring signals of selection. Known variants that were expected to have been under selection in the panel are identified, as well as an assortment of novel regions that have putatively been under selection in chickens. Notably, a promising pair of genes located 8 MB apart on chromosome 9 are identified based on Dʹ 2 IS as demonstrating strong evidence of dispersive epistatic selection between populations.

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Selection Mapping of Loci for Quantitative Disease Resistance in a Diverse Maize Population

Cited by 40 publications

References 46 publications

A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number

A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number

Insights into the Effects of Long-Term Artificial Selection on Seed Size in Maize

Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens

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