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Results for “quantitative genetics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The quantitative genetics of gene expression in Mimulus guttatus

Gene expression can be influenced by genetic variants that are closely linked to the expressed gene (cis eQTLs) and variants in other parts of the genome (trans eQTLs). We created a multiparental mapping population by sampling genotypes from a single natural population of Mimulus guttatus and scored gene expression in the leaves of 1,588 plants. We find that nearly every measured gene exhibits cis regulatory variation (91% have FDR < 0.05). cis eQTLs are usually allelic series with three or more functionally distinct alleles. The cis locus explains about two thirds of the standing genetic variance (on average) but varies among genes and tends to be greatest when there is high indel variation in the upstream regulatory region and high nucleotide diversity in the coding sequence. Despite mapping over 10,000 trans eQTL / affected gene pairs, most of the genetic variance generated by trans acting loci remains unexplained. This implies a large reservoir of trans acting genes with subtle or diffuse effects. Mapped trans eQTLs show lower allelic diversity but much higher genetic dominance than cis eQTLs. Several analyses also indicate that trans eQTLs make a substantial contribution to the genetic correlations in expression among different genes. They may thus be essential determinants of “gene expression modules,” which has important implications for the evolution of gene expression and how it is studied by geneticists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Quantitative genetic-by-soil microbiome interactions in a perennial grass affect functional traits

Plants interact with diverse microbiomes that can impact plant growth and performance. Recent studies highlight the potential beneficial aspects of plant microbiomes, including the possibility that microbes facilitate the process of local adaptation in their host plants. Microbially mediated local adaptation in plants occurs when local host genotypes have higher fitness than foreign genotypes because of their affiliation with locally beneficial microbes. Here, plant adaptation results from genetic interactions of the host with locally beneficial microbes (e.g. host genotype-by-microbiome interactions). We used a recombinant inbred line (RIL) mapping population derived from upland and lowland ecotypes of the diploid C4 perennial bunch grass Panicum hallii to explore quantitative genetic responses to soil microbiomes focusing on functional root and shoot traits involved in ecotypic divergence. We show that the growth and development of ecotypes and their trait divergence depends on soil microbiomes. Moreover, we find that the genetic architecture is modified by soil microbiomes, revealing important plant genotype-by-microbiome interactions for quantitative traits. We detected a number of quantitative trait loci (QTL) that interact with the soil microbiome. Our results highlight the importance of microbial interactions in ecotypic divergence and trait genetic architecture in C4 perennial grasses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Constitutive and inducible oleoresin defenses share genetic architectures and mechanisms in Pinus taeda

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

genome-wide association study↗
DOE OSTI2022

Association mapping across a multitude of traits collected in diverse environments in maize

Abstract Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

TGCM: (T)rait, (G)ene, and (C)rop Growth (M)odel Directed Targeted Gene Characterization in Sorghum (Final Technical Report)

Understanding which genes control important crop traits could help scientists develop better bioenergy and food crops more efficiently. However, plant genomes contain tens of thousands of genes, and testing each one individually is expensive and time-consuming. This project developed computational tools to predict which genes are most likely to matter, allowing researchers to focus their efforts where they will have the greatest impact. This project developed and validated integrated approaches combining machine learning, quantitative genetics, and crop growth modeling to improve the efficiency of functional gene characterization in sorghum (Sorghum bicolor), a critical bioenergy and food security crop. The research addressed a fundamental challenge in plant biology: the majority of genes in plant genomes lack experimentally validated functions, making it difficult to prioritize which genes to study using resource-intensive reverse genetics approaches.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Divergence in heritable life history traits suggests potential for local adaptation and trade‐offs associated with a coal ash disposal site

Abstract Globally, human activities have resulted in rapid environmental changes that present unique challenges for wildlife. However, investigations of local adaptation in response to simultaneous exposure to multiple anthropogenic selection pressures are rare and often generate conflicting results. We used an in situ reciprocal transplant design within a quantitative genetic framework to examine how adaptive evolution and phenotypic plasticity contribute to the persistence of an amphibian population inhabiting an environment characterized by high levels of multiple toxic trace elements. We found evidence of phenotypic divergence that is largely consistent with local adaptation to an environment contaminated with multiple chemical stressors, tied to potential trade‐offs in the absence of contaminants. Specifically, the population derived from the contaminated environment had a reduced risk of mortality and greater larval growth and in the contaminated environment, relative to offspring from the naïve population. Further, while survival in the uncontaminated environment was not compromised in offspring from the contaminant‐exposed population, they did show delayed development and reduced growth rates over larval development, relative to the naïve population. We found no evidence of reduced additive genetic variation in the contaminant‐exposed population, suggesting long‐term selection in a novel environment has not reduced the evolutionary potential of that population. We also saw little evidence that past selection in the ASH environment had reduced trait plasticity in the resident population. Maternal effects were prominent in early development, but we did not detect any trends suggesting these effects were associated with the maternal transfer of toxic trace elements. Our results demonstrate the potential for adaptation to multiple contaminants in a wild amphibian population, which may have facilitated long‐term persistence in a heavily impacted environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Quantitative and Predictive Genetic Parts for Plant Synthetic Biology

Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Microbiome breeding: conceptual and practical issues

Microbiome breeding is a new artificial selection technique that seeks to change the genetic composition of microbiomes in order to benefit plant or animal hosts. Recent experimental and theoretical analyses have shown that microbiome breeding is possible whenever microbiome-encoded genetic factors affect host traits (e.g., health) and microbiomes are transmissible between hosts with sufficient fidelity, such as during natural microbiome transmission between individuals of social animals, or during experimental microbiome transplanting between plants. Further, to address misunderstandings that stymie microbiome-breeding programs, we (i) clarify and visualize the corresponding elements of microbiome selection and standard selection; (ii) elucidate the eco-evolutionary processes underlying microbiome selection within a quantitative genetic framework to summarize practical guidelines that optimize microbiome breeding; and (iii) characterize the kinds of host species most amenable to microbiome breeding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A generalist–specialist trade-off between switchgrass cytotypes impacts climate adaptation and geographic range

Polyploidy results from whole-genome duplication and is a unique form of heritable variation with pronounced evolutionary implications. Different ploidy levels, or cytotypes, can exist within a single species, and such systems provide an opportunity to assess how ploidy variation alters phenotypic novelty, adaptability, and fitness, which can, in turn, drive the development of unique ecological niches that promote the coexistence of multiple cytotypes. Switchgrass, Panicum virgatum, is a widespread, perennial C4 grass in North America with multiple naturally occurring cytotypes, primarily tetraploids (4×) and octoploids (8×). Using a combination of genomic, quantitative genetic, landscape, and niche modeling approaches, we detect divergent levels of genetic admixture, evidence of niche differentiation, and differential environmental sensitivity between switchgrass cytotypes. Taken together, these findings support a generalist (8×)–specialist (4×) trade-off. Our results indicate that the 8× represent a unique combination of genetic variation that has allowed the expansion of switchgrass’ ecological niche and thus putatively represents a valuable breeding resource.

09 BIOMASS FUELS↗
DOE OSTI2023

The first two chromosome‐scale genome assemblies of American hazelnut enable comparative genomic analysis of the genus Corylus

Summary The native, perennial shrub American hazelnut ( Corylus americana ) is cultivated in the Midwestern United States for its significant ecological benefits, as well as its high‐value nut crop. Implementation of modern breeding methods and quantitative genetic analyses of C. americana requires high‐quality reference genomes, a resource that is currently lacking. We therefore developed the first chromosome‐scale assemblies for this species using the accessions ‘Rush’ and ‘Winkler’. Genomes were assembled using HiFi PacBio reads and Arima Hi‐C data, and Oxford Nanopore reads and a high‐density genetic map were used to perform error correction. N50 scores are 31.9 Mb and 35.3 Mb, with 90.2% and 97.1% of the total genome assembled into the 11 pseudomolecules, for ‘Rush’ and ‘Winkler’, respectively. Gene prediction was performed using custom RNAseq libraries and protein homology data. ‘Rush’ has a BUSCO score of 99.0 for its assembly and 99.0 for its annotation, while ‘Winkler’ had corresponding scores of 96.9 and 96.5, indicating high‐quality assemblies. These two independent assemblies enable unbiased assessment of structural variation within C. americana , as well as patterns of syntenic relationships across the Corylus genus. Furthermore, we identified high‐density SNP marker sets from genotyping‐by‐sequencing data using 1343 C. americana , C. avellana and C. americana × C. avellana hybrids, in order to assess population structure in natural and breeding populations. Finally, the transcriptomes of these assemblies, as well as several other recently published Corylus genomes, were utilized to perform phylogenetic analysis of sporophytic self‐incompatibility (SSI) in hazelnut, providing evidence of unique molecular pathways governing self‐incompatibility in Corylus .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Assembly and Repair of the Photosystem II Reaction Center

This project investigated the biochemical and biophysical mechanisms governing assembly and repair of Photosystem II (PSII), the membrane protein complex responsible for solar-driven water oxidation in oxygenic photosynthesis. The work focused on three integrated areas: (1) protein–protein interactions that facilitate PSII assembly in cyanobacterial biogenesis centers, (2) the chemical mechanism of photo-assembly of the Mn 4 CaO 5 oxygen-evolving complex (OEC), and (3) mechanisms that target PSII reaction centers for degradation and repair in photosynthetic organisms. Using electron paramagnetic resonance spectroscopy, protein biochemistry, molecular genetics, quantitative mass spectrometry, and computational modeling, the project demonstrated that proton release events limit early steps of OEC assembly and that chloride and calcium ions facilitate Mn oxidation and intermediate stabilization. Complementary studies identified chaperone recruitment mechanisms in cyanobacterial PSII biogenesis centers and translation and protease factors involved in PSII turnover in Chlamydomonas. Together, these results establish proton management and coordinated protein quality control as central design principles in PSII assembly and repair and provide mechanistic insight relevant to biological and artificial photosynthetic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

APPL Hyperspectral_Imaging_Dataset_for_Heritability_Analysis_in_Populus_trichocarpa

This dataset contains hyperspectral imaging data collected at the Advanced Plant Phenotyping Laboratory (APPL) at Oak Ridge National Laboratory. Natural variants of Populus trichocarpa were imaged using a high-throughput hyperspectral phenotyping pipeline to quantify spectral reflectance traits for downstream quantitative genetics analyses. The dataset includes hyperspectral image files and derived reflectance data products suitable for extracting spectral features across the measured wavelength range (e.g., VNIR and/or SWIR, depending on instrument configuration), along with associated sample metadata (e.g., genotype identifiers, experimental design factors, and imaging run identifiers). These data were generated to support analyses of broad-sense heritability of hyperspectral traits and their relationships with biochemical phenotypes (including lignin traits from Py-MBMS).

APPL↗
DOE OSTI2026

Ornamental origins and genomic frontiers: a review of big-bracted dogwood research

The big-bracted (Benthamidia) dogwood clade consists of small- to medium-sized deciduous trees within the genus Cornus, known for their showy spring-time floral bract display. Cornus is within the family Cornaceae and order Cornales, and as Cornales is one of the earliest diverging asterids, these taxa have been important for phylogenetic research. Three species within the big-bracted clade, flowering (Cornus florida), kousa (C. kousa), and Pacific (C. nuttallii) dogwoods, are popular ornamental landscape plants in North America, with more than 130 cultivars released. Despite their commercial popularity, numerous research gaps have limited the expansion of fundamental research and dogwood breeding programs. In this present review, we aim to provide a thorough overview of our current understanding of 1) the phylogenetic and biogeographic context, 2) plant biology and major pests and pathogens impacting commercialization, 3) historical commercialization and propagation methods, and 4) genetic and genomic resources and how they have been implemented to understand these species. Research gaps and future directions to advance basic research and breeding of big-bracted ornamental dogwoods are discussed throughout.

Cornus florida↗
DOE OSTI2020

Inference of Chromosome-Length Haplotypes Using Genomic Data of Three or a Few More Single Gametes

Compared with genomic data of individual markers, haplotype data provide higher resolution for DNA variants, advancing our knowledge in genetics and evolution. Although many computational and experimental phasing methods have been developed for analyzing diploid genomes, it remains challenging to reconstruct chromosome-scale haplotypes at low cost, which constrains the utility of this valuable genetic resource. Gamete cells, the natural packaging of haploid complements, are ideal materials for phasing entire chromosomes because the majority of the haplotypic allele combinations has been preserved. Therefore, compared with the current diploid-based phasing methods, using haploid genomic data of single gametes may substantially reduce the complexity in inferring the donor’s chromosomal haplotypes. In this study, we developed the first easy-to-use R package, Hapi, for inferring chromosome-length haplotypes of individual diploid genomes with only a few gametes. Hapi outperformed other phasing methods when analyzing both simulated and real single gamete cell sequencing data sets. The results also suggested that chromosome-scale haplotypes may be inferred by using as few as three gametes, which has pushed the boundary to its possible limit. The single gamete cell sequencing technology allied with the cost-effective Hapi method will make large-scale haplotype-based genetic studies feasible and affordable, promoting the use of haplotype data in a wide range of research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Meta-analysis identifies pleiotropic loci controlling phenotypic trade-offs in sorghum

Abstract Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here, we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome-wide association studies (GWAS) conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35–43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.

59 BASIC BIOLOGICAL SCIENCES↗