Genetics of parallel response to selection for flowering time in maize
Date
2021
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Publisher
University of Delaware
Abstract
Genetic diversity is key to climate adaptation and breeding for crop improvement, but across crops, modern cultivars tend to draw on a limited fraction of a species' diversity. In global maize there is extensive standing variation, but an adaptational barrier driven by differences in flowering time (FT) across latitude separates the diversity of tropical and temperate germplasm pools. Moreover, founder effects, intensive selection and varietal recycling have substantially restricted the genetic base of maize in breeding programs. This is somewhat of a unidirectional problem, where extremely late flowering of tropical germplasm in temperate environments makes crossing difficult or impossible, so breeders in temperate environments are reluctant to work with tropical varieties. As the demands for agriculture are being challenged by population growth and climate change, a better understanding about FT adaptation (herein referred to as "pre-adaptation'') in maize across latitude could open new avenues for breeders to capitalize on a broader array of diversity. ☐ Pre-adaptation of tropical varieties by conventional breeding can take a decade of selection in a temperate environment. Therefore, novel methods for rapidly pre-adapting maize are under development such as genomic selection and gene editing. However, optimization and deployment of these strategies requires an in-depth understanding of how the genetic architecture of a trait interacts with environmental variation and selection to drive phenotypic change. In this dissertation, a new genome-sequencing methodology (chapter 2) and genetic simulation tool (chapter 3) were developed in order to dissect the genomic basis of an experimentally evolved population of maize that was independently selected for early FT across latitude (chapter 4). The populations used for this study were developed previously, not as part of this dissertation. Using a common base population derived by systematically intermating tropical lines, experimental evolution was coordinated in a tightly controlled parallel selection experiment spanning 28-degrees latitude in the USA. Using an extreme sampling strategy, among 10,000 individuals grown at eight locations in each of two generations of selection, 384 of the earliest and 384 of the latest FT individuals were used to genetically dissect phenotypic evolution in the parallel selected populations. ☐ First, overcoming limitations of contemporary sequence-based genotyping protocols and bioinformatic tools, LocHap-GBS was developed as a new method to resolve local haplotypes in large-scale studies of heterozygous samples. LocHap-GBS was customized for accurate genotyping (>99.4%), which allowed high-confidence, genome-wide fingerprints (~15,000 markers) to be produced for a total of 12,000 individuals sampled across the experimentally evolved populations. The large sample size empowered this investigation into the genetics of FT adaptation. ☐ As a further development, SPEARS, a species-agnostic software pipeline was designed to assess methods for reconstructing descendent haplotype blocks along homologous chromosomes, for diverse population designs. Determining the haplotype blocks inherited from specific parents, instead of genotypes, benefits several applications in genetics. In the present study, this allowed the contribution of each parental line to the selection response to be examined at any specific position in the genome. SPEARS uses a genome simulator to generate ground-truth data for validation of haplotype reconstruction which is assessed by four metrics, including: (i) ancestral assignment accuracy; (ii) genotype assignment accuracy; (iii) phase assignment accuracy; and (iv) correlation between crossover counts. When tested on the experimentally evolved populations used for this dissertation, SPEARS demonstrated accuracies exceeding 97% for all metrics, providing high confidence in the haplotype maps for downstream analysis. ☐ Prior studies have demonstrated phenotypic convergence in the response to selection for early FT, where a population selected in one environment shows a similar response in another environment. With the enhanced datasets produced here, this dissertation dissected the genetic architecture to examine parallelism at the genomic level underlying phenotypic responses to selection across latitude. Among 144,000 markers, extreme mapping identified a total of 11,417 FT-marker associations across all locations and generations of selection. A striking result was the extent of genomic parallelism resembling an oligogenic architecture in the initial generation of selection for populations selected at high latitudes. Fewer and more dispersed FT-associations across the genome occurred at lower latitudes and in the second generation of selection. However, at other scales of genomic resolution (loci and haplotypes) more extensive overlap in the genetic architecture occurred across locations and generations. Clustering of allele effects across latitude revealed strong evidence for locally adaptive alleles for FT, with limited instances of opposing allele effects in different environments. These results are congruent with co-selection of environment dependent and independent components of FT regulation leading to translational but nonetheless differentiable phenotypic responses across environments. The presence of environment-dependent drivers of variation in FT that lack negative trade-offs may enable genomics-led approaches for pre-adapting tropical populations to a wide range of temperate environments. Furthermore, adaptation across the tree of life has been a long-standing area of research in evolutionary biology, with focus recently shifting to genomic studies of polygenic adaptation. The dissection of parallelism in the genetic architecture underlying selection for FT, a finite polygenic trait, offers new insights into evolutionary processes underlying the adaptability of maize.
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Keywords
Adaptation, Breeding, Flowering, Genetics, Genomic Parallelism, Maize