Biology subjects

Ross-Ibarra, J.

Publications and source records attributed to Ross-Ibarra, J..

11 recordsLinked to original sources

bioRxiv2018

Adaptive phenotypic divergence in teosinte differs across biotic contexts

Climate is a powerful force shaping adaptation within species, often creating dramatic phenotypic clines. Yet adaptation to climate does not occur in a vacuum: species interactions filter the fitness consequences of both climatic and phenotypic variation. In other words, the translation of genotype to phenotype may be altered by biotic context, influencing the variation upon which climatic selection can act. We investigate the role of such interactions in changing the phenotypes on which selection acts using ten populations of an annual grass species (teosinte: Zea mays ssp. mexicana) sourced from along an elevational gradient, along with rhizosphere biota sourced from three of those populations. We grow teosinte families in a half-sibling design in separate biota treatments to first test whether the divergence we see among traits in teosinte populations exceeds what we would expect from genetic drift and then whether the source of rhizosphere biota affects the expression of divergent traits. We also assay the influence of these three rhizosphere biotas on contemporary additive genetic variation in teosinte traits across populations. We find that expression of most measured traits in teosinte is altered by rhizosphere biota, as well as the degree of variance and covariance among traits involved in root mass and flowering time. As a number of these traits are also found to underlie adaptive divergence across habitats, our data suggest that biota influence the expression of traits underlying local adaptation. Together, our results suggest that changes in trait expression and covariance elicited by interactor communities in root mass and flowering time may have played a historical role in local adaption of teosinte to environments, and that they would play a contemporary role in responses to changing selection pressures.

evolutionary biology↗

bioRxiv2018

Detecting adaptive differentiation in structured populations with genomic data and common gardens

Adaptation in quantitative traits often occurs through subtle shifts in allele frequencies at many loci, a process called polygenic adaptation. While a number of methods have been developed to detect polygenic adaptation in human populations, we lack clear strategies for doing so in many other systems. In particular, there is an opportunity to develop new methods that leverage datasets with genomic data and common garden trait measurements to systematically detect the quantitative traits important for adaptation. Here, we develop methods that do just this, using principal components of the relatedness matrix to detect excess divergence consistent with polygenic adaptation and using a conditional test to control for confounding effects due to population structure. We apply these methods to inbred maize lines from the USDA germplasm pool and maize landraces from Europe. Ultimately, these methods can be applied to additional domesticated and wild species to give us a broader picture of the specific traits that contribute to adaptation and the overall importance of polygenic adaptation in shaping quantitative trait variation.

evolutionary biology↗

bioRxiv2018

Genetic architecture and selective sweeps after polygenic adaptation to distant trait optima

Understanding the genetic basis of phenotypic adaptation to changing environments is an essential goal of population and quantitative genetics. While technological advances now allow interrogation of genome-wide genotyping data in large panels, our understanding of the process of polygenic adaptation is still limited. To address this limitation, we use extensive forward-time simulation to explore the impacts of variation in demography, trait genetics, and selection on the rate and mode of adaptation and the resulting genetic architecture. We simulate a population adapting to an optimum shift, modeling sequence variation for 20 QTL for each of 12 different demographies for 100 different traits varying in the effect size distribution of new mutations, the strength of stabilizing selection, and the contribution of the genomic background. We then use random forest regression approaches to learn the relative importance of input parameters in determining a number of aspects of the process of adaptation including the speed of adaptation, the relative frequency of hard sweeps and sweeps from standing variation, or the final genetic architecture of the trait. We find that selective sweeps occur even for traits under relatively weak selection and where the genetic background explains most of the variation. Though most sweeps occur from variation segregating in the ancestral population, new mutations can be important for traits under strong stabilizing selection that undergo a large optimum shift. We also show that population bottlenecks and expansion impact overall genetic variation as well as the relative importance of sweeps from standing variation and the speed with which adaptation can occur. We then compare our results to two traits under selection during maize domestication, showing that our simulations qualitatively recapitulate differences between them. Overall, our results underscore the complex population genetics of individual loci in even relatively simple quantitative trait models, but provide a glimpse into the factors that drive this complexity and the potential of these approaches for understanding polygenic adaptation.\n\nAuthor summaryMany traits are controlled by a large number of genes, and environmental changes can lead to shifts in trait optima. How populations adapt to these shifts depends on a number of parameters including the genetic basis of the trait as well as population demography. We simulate a number of trait architectures and population histories to study the genetics of adaptation to distant trait optima. We find that selective sweeps occur even in traits under relatively weak selection and our machine learning analyses find that demography and the effect sizes of mutations have the largest influence on genetic variation after adaptation. Maize domestication is a well suited model for trait adaptation accompanied by demographic changes. We show how two example traits under a maize specific demography adapt to a distant optimum and demonstrate that polygenic adaptation is a well suited model for crop domestication even for traits with major effect loci.

evolutionary biology↗

bioRxiv2017

Adaptation in plant genomes: bigger isn’t better, but it’s probably different

Here we have proposed the functional space hypothesis, positing that mutational target size scales with genome size, impacting the number, source, and genomic location of beneficial mutations that contribute to adaptation. Though motivated by preliminary evidence, mostly from Arabidopsis and maize, more data are needed before any rigorous assessment of the hypothesis can be made. If correct, the functional space hypothesis suggests that we should expect plants with large genomes to exhibit more functional mutations outside of genes, more regulatory variation, and likely less signal of strong selective sweeps reducing diversity. These differences have implications for how we study the evolution and development of plant genomes, from where we should look for signals of adaptation to what patterns we expect adaptation to leave in genetic diversity or gene expression data. While flowering plant genomes vary across more than three orders of magnitude in size, most studies of both functional and evolutionary genomics have focused on species at the extreme small edge of this scale. Our hypothesis predicts that methods and results from these small genomes may not replicate well as we begin to explore large plant genomes. Finally, while we have focused here on evidence from plant genomes, we see no a priori reason why similar arguments might not hold in other taxa as well.

evolutionary biology↗

bioRxiv2017

Allele specific expression analysis identifies regulatory variation associated with stress-related genes in the Mexican highland maize landrace Palomero Toluqueno

BackgroundGene regulatory variation has been proposed to play an important role in the adaptation of plants to environmental stress. In the central highlands of Mexico, farmer selection has generated a unique group of maize landraces adapted the challenges of the highland niche. In this study, gene expression in Mexican highland maize and a reference maize breeding line were compared to identify evidence of regulatory variation in stress-related genes. It was hypothesised that local adaptation in Mexican highland maize would be associated with a transcriptional signature observable even under benign conditions.\n\nMethodsAllele specific expression analysis was performed using the seedling-leaf transcriptome of an F1 individual generated from the cross between the highland adapted Mexican landrace Palomero Toluqueno and the reference line B73, grown under benign conditions. Results were compared with a published dataset describing the transcriptional response of B73 seedlings to cold, heat, salt and UV treatments.\n\nResultsA total of 2386 genes were identified to show allele specific expression. Of these, 277 showed an expression difference between Palomero Toluqueno and B73 alleles that mirrored the response of B73 cold, heat, salt and/or UV treatments, and, as such, were considered to display a constitutive stress response. Constitutive stress response candidates included genes associated with plant hormone signaling and a number of transcription factors. Construction of a gene co-expression network revealed further signaling and stress-related genes to be among the potential targets of the transcription factors candidates.\n\nDiscussionConstitutive activation of responses may represent the best strategy when stresses are severe but predictable. Expression differences observed here between PT and B73 alleles indicate the presence of cis-acting regulatory variation linked to stress-related genes in PT. Considered alongside gene annotation and population data, allele specific expression analysis of plants grown under benign conditions provides an attractive strategy to identify functional variation potentially linked to local adaptation.

plant biology↗

bioRxiv2017

Parallel Altitudinal Clines Reveal Adaptive Evolution Of Genome Size In Zea mays

While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes.\n\nAuthor summaryGenome size in plants can vary by orders of magnitude, but this variation has long been considered to be of little to no functional consequence. Studying three independent adaptations to high altitude in Zea mays, we find that genome size experiences parallel pressures from natural selection, causing a linear reduction in genome size with increasing altitude. Though reductions in repetitive content are responsible for the genome size change, we find that only those individual loci contributing most to the variation in genome size are individually targeted by selection. To identify the phenotype influenced by genome size, we study how variation in genome size within a single teosinte population impacts leaf growth and cell division. We find that genome size variation correlates negatively with the rate of cell division, suggesting that individuals with larger genomes require longer to complete a mitotic cycle. Finally, we reanalyze data from maize inbreds to show that faster cell division is correlated with earlier flowering, connecting observed variation in genome size to an important adaptive phenotype.

evolutionary biology↗

bioRxiv2017

The interplay of demography and selection during maize domestication and expansion

The history of maize has been characterized by major demographic events including changes in population size associated with domestication and range expansion as well as gene flow with wild relatives. The interplay between demographic history and selection has shaped diversity across maize populations and genomes. Here, we investigate these processes based on high-depth resequencing data from 31 maize landraces spanning the pre-Columbian distribution of maize as well as four wild progenitor individuals (Zea mays ssp. parviglumis) from the Balsas River Valley in Mexico. Genome-wide demographic analyses reveal that maize domestication and spread resulted in pronounced declines in effective population size due to both a protracted bottleneck and serial founder effects, while, concurrently, parviglumis experienced population growth. The cost of maize domestication and spread was an increase in deleterious alleles in the domesticate relative to its wild progenitor. This cost is particularly pronounced in Andean maize, which appears to have experienced a more dramatic founder event when compared to other maize populations. Introgression from the wild teosinte Zea mays ssp. mexicana into maize in the highlands of Mexico and Guatemala is found found to decrease the prevalence of deleterious alleles, likely due to the higher long-term effective population size of wild maize. These findings underscore the strong interaction between historical demography and the efficiency of selection species- and genome-wide and suggest domesticated species with well-characterized histories may be particularly useful for understanding this interplay.

evolutionary biology↗

bioRxiv2017

The Potential Role of Genetic Assimilation during Maize Domestication

Domestication research has largely focused on identification of morphological and genetic differences between extant populations of crops and their wild relatives. Little attention has been paid to the potential effects of environment despite substantial known changes in climate from the time of domestication to modern day. Recent research, in which maize and teosinte (i.e., wild maize) were exposed to environments similar to the time of domestication, resulted in a plastic induction of domesticated phenotypes in teosinte and little response to environment in maize. These results suggest that early agriculturalists may have selected for genetic mechanisms that cemented domestication phenotypes initially induced by a plastic response of teosinte to environment, a process known as genetic assimilation. To better understand this phenomenon and the potential role of environment in maize domestication, we examined differential gene expression in maize (Zea mays ssp. mays) and teosinte (Zea mays ssp. parviglumis) between past and present conditions. We identified a gene set of over 2000 loci showing a change in expression across environmental conditions in teosinte and invariance in maize. In fact, overall we observed both greater plasticity in gene expression and more substantial re-wiring of expression networks in teosinte across environments when compared to maize. While these results suggest genetic assimilation played at least some role in domestication, genes showing expression patterns consistent with assimilation are not significantly enriched for previously identified domestication candidates, indicating assimilation did not have a genome-wide effect.

genomics↗

bioRxiv2016

Gene fractionation and function in the ancient subgenomes of maize

The maize genome experienced an ancient whole genome duplication approximately 10 million years ago and the duplicate subgenomes have since experienced reciprocal gene loss (fractionation) such that many genes have returned to single-copy status. This process has not affected the subgenomes equally; reduced gene expression in one of the subgenomes mitigates the consequences of mutations and gene deletions and is thought to drive higher rates of fractionation. Here we take advantage of published genome-wide SNP and phenotype association data to show that, in accordance with predictions of this model, paralogs with greater expression contribute more to phenotypic variation compared to their lowly expressed counterparts. Furthermore, paralogous genes in the least-fractionated subgenome account for a greater degree of phenotypic diversity than those resident on the more-fractionated subgenome. We also show that the two subgenomes of maize are distinct in epigenetic characteristics. Intriguingly, analysis of singleton genes reveals that these differences persist even after fractionation is complete.

genomics↗

bioRxiv2016

The complex sequence landscape of maize revealed by single molecule technologies

Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation. These resources facilitate elucidation of biological processes and support translation of research findings into improved and sustainable agricultural technologies. Many reference genomes for crop plants have been generated over the past decade, but these genomes are often fragmented and missing complex repeat regions. Here, we report the assembly and annotation of maize, a genetic and agricultural model species, using Single Molecule Real-Time (SMRT) sequencing and high-resolution optical mapping. Relative to the previous reference genome, our assembly features a 52-fold increase in contig length and significant improvements in the assembly of intergenic spaces and centromeres. Characterization of the repetitive portion of the genome revealed over 130,000 intact transposable elements (TEs), allowing us to identify TE lineage expansions unique to maize. Gene annotations were updated using 111,000 full-length transcripts obtained by SMRT sequencing. In addition, comparative optical mapping of two other inbreds revealed a prevalence of deletions in the low gene density region and maize lineage-specific genes.

genomics↗

bioRxiv2016

Incomplete dominance of deleterious alleles contribute substantially to trait variation and heterosis in maize

AbstractDeleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring by crossing two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS) models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD) analysis and perform genomic prediction analyses in which we weigh blocks on the basis of segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding.\n\nAuthor SummaryA key long-term goal of biology is understanding the genetic basis of phenotypic variation. Although most new mutations are likely disadvantageous, their prevalence and importance in explaining patterns of phenotypic variation is controversial and not well understood. In this study we combine whole genome-sequencing and field evaluation of a maize mapping population to investigate the contribution of deleterious mutations to phenotype. We show that a priori prediction of deleterious alleles correlates well with effect sizes for grain yield and that variants predicted to be more damaging are on average more recessive. We develop a simple model allowing for variation in the heterozygous effects of deleterious mutations and demonstrate its improved ability to predict both phenotypes and hybrid vigor. Our results help reconcile alternative explanations for hybrid vigor and highlight the use of leveraging evolutionary history to facilitate breeding for crop improvement.

genetics↗