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All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Constraints in Genetic Programming

Genetic programming refers to a class of genetic algorithms utilizing generic representation in the form of program trees. For a particular application, one needs to provide the set of functions, whose compositions determine the space of program structures being evolved, and the set of terminals, which determine the space of specific instances of those programs. The algorithm searches the space for the best program for a given problem, applying evolutionary mechanisms borrowed from nature. Genetic algorithms have shown great capabilities in approximately solving optimization problems which could not be approximated or solved with other methods. Genetic programming extends their capabilities to deal with a broader variety of problems. However, it also extends the size of the search space, which often becomes too large to be effectively searched even by evolutionary methods. Therefore, our objective is to utilize problem constraints, if such can be identified, to restrict this space. In this publication, we propose a generic constraint specification language, powerful enough for a broad class of problem constraints. This language has two elements -- one reduces only the number of program instances, the other reduces both the space of program structures as well as their instances. With this language, we define the minimal set of complete constraints, and a set of operators guaranteeing offspring validity from valid parents. We also show that these operators are not less efficient than the standard genetic programming operators if one preprocesses the constraints - the necessary mechanisms are identified.

Janikow, Cezary Z.↗
NASA NTRS2000

JavaGenes and Condor: Cycle-Scavenging Genetic Algorithms

A genetic algorithm code, JavaGenes, was written in Java and used to evolve pharmaceutical drug molecules and digital circuits. JavaGenes was run under the Condor cycle-scavenging batch system managing 100-170 desktop SGI workstations. Genetic algorithms mimic biological evolution by evolving solutions to problems using crossover and mutation. While most genetic algorithms evolve strings or trees, JavaGenes evolves graphs representing (currently) molecules and circuits. Java was chosen as the implementation language because the genetic algorithm requires random splitting and recombining of graphs, a complex data structure manipulation with ample opportunities for memory leaks, loose pointers, out-of-bound indices, and other hard to find bugs. Java garbage-collection memory management, lack of pointer arithmetic, and array-bounds index checking prevents these bugs from occurring, substantially reducing development time. While a run-time performance penalty must be paid, the only unacceptable performance we encountered was using standard Java serialization to checkpoint and restart the code. This was fixed by a two-day implementation of custom checkpointing. JavaGenes is minimally integrated with Condor; in other words, JavaGenes must do its own checkpointing and I/O redirection. A prototype Java-aware version of Condor was developed using standard Java serialization for checkpointing. For the prototype to be useful, standard Java serialization must be significantly optimized. JavaGenes is approximately 8700 lines of code and a few thousand JavaGenes jobs have been run. Most jobs ran for a few days. Results include proof that genetic algorithms can evolve directed and undirected graphs, development of a novel crossover operator for graphs, a paper in the journal Nanotechnology, and another paper in preparation.

Globus, Al↗
NASA NTRS2002

Combinatorial Multiobjective Optimization Using Genetic Algorithms

The research proposed in this document investigated multiobjective optimization approaches based upon the Genetic Algorithm (GA). Several versions of the GA have been adopted for multiobjective design, but, prior to this research, there had not been significant comparisons of the most popular strategies. The research effort first generalized the two-branch tournament genetic algorithm in to an N-branch genetic algorithm, then the N-branch GA was compared with a version of the popular Multi-Objective Genetic Algorithm (MOGA). Because the genetic algorithm is well suited to combinatorial (mixed discrete / continuous) optimization problems, the GA can be used in the conceptual phase of design to combine selection (discrete variable) and sizing (continuous variable) tasks. Using a multiobjective formulation for the design of a 50-passenger aircraft to meet the competing objectives of minimizing takeoff gross weight and minimizing trip time, the GA generated a range of tradeoff designs that illustrate which aircraft features change from a low-weight, slow trip-time aircraft design to a heavy-weight, short trip-time aircraft design. Given the objective formulation and analysis methods used, the results of this study identify where turboprop-powered aircraft and turbofan-powered aircraft become more desirable for the 50 seat passenger application. This aircraft design application also begins to suggest how a combinatorial multiobjective optimization technique could be used to assist in the design of morphing aircraft.

Crossley, William A.↗
NASA NTRS2017

Genetic Correlation with the DNA Repair Assay in Mice Exposed to High-LET

We hypothesize that DNA damage induced by high local energy deposition, occurring when cells are traversed by high-LET (Linear Energy Transfer) particles, can be experimentally modeled by exposing cells to high doses of low-LET. In this work, we validate such hypothesis by characterizing and correlating the time dependence of 53BP1 radiation-induced foci (RIF) for various doses and LET across 72 primary skin fibroblast from mice. This genetically diverse population allows us to understand how genetic may modulate the dose and LET relationship. The cohort was made on average from 3 males and 3 females belonging to 15 different strains of mice with various genetic backgrounds, including the collaborative cross (CC) genetic model (10 strains) and 5 reference mice strains. Cells were exposed to two fluences of three HZE (High Atomic Energy) particles (Si 350 megaelectronvolts per nucleon, Ar 350 megaelectronvolts per nucleon and Fe 600 megaelectronvolts per nucleon) and to 0.1, 1 and 4 grays from a 160 kilovolt X-ray. Individual radiation sensitivity was investigated by high throughput measurements of DNA repair kinetics for different doses of each radiation type. The 53BP1 RIF dose response to high-LET particles showed a linear dependency that matched the expected number of tracks per cell, clearly illustrating the fact that close-by DNA double strand breaks along tracks cluster within one single RIF. By comparing the slope of the high-LET dose curve to the expected number of tracks per cell we computed the number of remaining unrepaired tracks as a function of time post-irradiation. Results show that the percentage of unrepaired track over a 48 hours follow-up is higher as the LET increases across all strains. We also observe a strong correlation between the high dose repair kinetics following exposure to 160 kilovolts X-ray and the repair kinetics of high-LET tracks, with higher correlation with higher LET. At the in-vivo level for the 10-CC strains, we observe that drops in the number of T-cells and B-cells found in the blood of mice 24 hours after exposure to 0.1 gray of 320 kilovolts X-ray correlate well with slower DNA repair kinetics in skin cells exposed to X-ray. Overall, our results suggest that repair kinetics found in skin is a surrogate marker for in-vivo radiation sensitivity in other tissue, such as blood cells, and that such response is modulated by genetic variability.

cosmic radiation↗
DOE OSTI2013

Molecular Genetic Analysis of Activation-tagged Transcription Factors Thought to be Involved in Photomorphogenesis

Plants utilize light as a source of information via families of photoreceptors such as the red/far-red absorbing phytochromes (PHY) and the blue/UVA absorbing cryptochromes (CRY). The main goal of the Neff lab is to use molecular-genetic mutant screens to elucidate signaling components downstream of these photoreceptors. Activation-tagging mutagenesis led to the identification of two putative transcription factors that may be involved in both photomorphogenesis and hormone signaling pathways. sob1-D (suppressor of phyB-dominant) mutant phenotypes are caused by the over-expression of a Dof transcription factor previously named OBP3. Our previous studies indicate that OBP3 is a negative regulator of light-mediated cotyledon expansion and may be involved in modulating responsiveness to the growth-regulating hormone auxin. The sob2-D mutant uncovers a role for LEP, a putative AP2/EREBP-like transcription factor, in seed germination, hypocotyl elongation and responsiveness to the hormone abscisic acid. Based on photobiological and genetic analysis of OBP3-knockdown and LEP-null mutations, we hypothesize that these transcription factors are involved in both light-mediated seedling development and hormone signaling. To examine the role that these genes play in photomorphogenesis we will: 1) Further explore the genetic role of OBP3 in cotyledon/leaf expansion and other photomorphogenic processes as well as examine potential physical interactions between OBP3 and CRY1 or other signaling components that genetically interact with this transcription factor 2) Test the hypothesis that OBP3 is genetically involved in auxin signaling and root development as well as examine the affects of this hormone and light on OBP3 protein accumulation. 3) Test the hypothesis that LEP is involved in seed germination, seedling photomorphogenesis and hormone signaling. Together these experiments will lead to a greater understanding of the complexity of interactions between photoreceptors and DNA-interacting proteins during photomorphogenesis. These studies also address the roles OBP3 and LEP may play as points of intersection between hormone signaling and photomorphogenesis. In the future, phenotypes caused by altered expression of these genes may generate useful traits for improving crop yield.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

The New World of Human Genetics: A dialogue between Practitioners & the General Public on Ethical, Legal & Social Implications of the Human Genome Project

The history and reasons for launching the Human Genome project and the current uses of genetic human material; Identifying and discussing the major issues stemming directly from genetic research and therapy-including genetic discrimination, medical/ person privacy, allocation of government resources and individual finances, and the effect on the way in which we perceive the value of human life; Discussing the sometimes hidden ethical, social and legislative implications of genetic research and therapy such as informed consent, screening and preservation of genetic materials, efficacy of medical procedures, the role of the government, and equal access to medical coverage.

Schofield, Amy↗
DOE OSTI2022

Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach

Understanding the genetic relationships between human disorders could lead to better treatment and prevention strategies, especially for individuals with multiple comorbidities. A common resource for studying genetic-disease relationships is the GWAS Catalog, a large and well curated repository of SNP-trait associations from various studies and populations. Some of these populations are contained within mega-biobanks such as the Million Veteran Program (MVP), which has enabled the genetic classification of several diseases in a large well-characterized and heterogeneous population. Here we aim to provide a network of the genetic relationships among diseases and to demonstrate the utility of quantifying the extent to which a given resource such as MVP has contributed to the discovery of such relations. We use a network-based approach to evaluate shared variants among thousands of traits in the GWAS Catalog repository. Our results indicate many more novel disease relationships that did not exist in early studies and demonstrate that the network can reveal clusters of diseases mechanistically related. Finally, we show novel disease connections that emerge when MVP data is included, highlighting methodology that can be used to indicate the contributions of a given biobank.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A common resequencing‐based genetic marker data set for global maize diversity

SUMMARY Maize ( Zea mays ssp. mays ) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole‐genome resequencing strategies, identifying millions of segregating single‐nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high‐confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering‐time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genetic identification of avian samples recovered from solar energy installations

Renewable energy production and development will drastically affect how we meet global energy demands, while simultaneously reducing the impact of climate change. Although the possible effects of renewable energy production (mainly from solar- and wind-energy facilities) on wildlife have been explored, knowledge gaps still exist, and collecting data from wildlife remains (when negative interactions occur) at energy installations can act as a first step regarding the study of species and communities interacting with facilities. In the case of avian species, samples can be collected relatively easily (as compared to other sampling methods), but may only be able to be identified when morphological characteristics are diagnostic for a species. Therefore, many samples that appear as partial remains, or “feather spots”—known to be of avian origin but not readily assignable to species via morphology—may remain unidentified, reducing the efficiency of sample collection and the accuracy of patterns observed. To obtain data from these samples and ensure their identification and inclusion in subsequent analyses, we applied, for the first time, a DNA barcoding approach that uses mitochondrial genetic data to identify unknown avian samples collected at solar facilities to species. We also verified and compared identifications obtained by our genetic method to traditional morphological identifications using a blind test, and discuss discrepancies observed. Our results suggest that this genetic tool can be used to verify, correct, and supplement identifications made in the field and can produce data that allow accurate comparisons of avian interactions across facilities, locations, or technology types. We recommend implementing this genetic approach to ensure that unknown samples collected are efficiently identified and contribute to a better understanding of wildlife impacts at renewable energy projects.

14 SOLAR ENERGY↗
DOE OSTI2017

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Chapter 2: Genetics of Unstudied Thermophiles for Industry

Thermophilic organisms hold great potential for industry due to their numerous advantages in biotechnological applications such as higher reaction rate, higher substrate loading, decreased susceptibility to reaction contamination, energy savings in industrial fermentations, and ability to express thermostable proteins that can be utilized in many important industrial processes. Bioprospecting for thermophiles will continue to reveal new enzymatic and metabolic paradigms with industrial applicability. In order to translate these paradigms to production scale, routine methods for microbial genetic engineering are needed, yet remain to be developed in many newly isolated thermophiles. Major challenges and recent developments in the establishment of reliable genetic systems in thermophiles are discussed. Here, we use a hyperthermophilic, cellulolytic bacterium, Caldicellulosiruptor bescii, as a case study to demonstrate the development of a genetic system for an industrially useful thermophile, describing in detail methods for transformation, genetic tool utilization, and chromosomal modification using targeted gene deletion and insertion techniques.

93 SC - Biological and Environmental Research (BER↗
DOE OSTI2023

Thirdhand tobacco smoke exposure increases the genetic background-dependent risk of pan-tumor development in Collaborative Cross mice

Increasing evidence has shown that thirdhand smoke (THS) exposure is likely to induce adverse health effects. An important knowledge gap remains in our understanding of THS exposure related to cancer risk in the human population. Population-based animal models are useful and powerful in investigating the interplay between host genetics and THS exposure on cancer risk. Here, we used the Collaborative Cross (CC) mouse population-based model system, which recapitulates the genetic and phenotypic diversity observed in the human population, to assess cancer risk after a short period of exposure, between 4 and 9 weeks of age. Eight CC strains (CC001, CC019, CC026, CC036, CC037, CC041, CC042 and CC051) were included in our study. We quantified pan-tumor incidence, tumor burden per mouse, organ tumor spectrum and tumor-free survival until 18 months of age. At the population level, we observed a significantly increased pan-tumor incidence and tumor burden per mouse in THS-treated mice as compared to the control (p = 3.04E-06). Lung and liver tissues exhibited the largest risk of undergoing tumorigenesis after THS exposure. Tumor-free survival was significantly reduced in THS-treated mice compared to control (p = 0.044). At the individual strain level, we observed a large variation in tumor incidence across the 8 CC strains. CC036 and CC041 exhibited a significant increase in pan-tumor incidence (p = 0.0084 and p = 0.000066, respectively) after THS exposure compared to control. We conclude that early-life THS exposure increases tumor development in CC mice and that host genetic background plays an important role in individual susceptibility to THS-induced tumorigenesis. Genetic background is an important factor that should be taken into account when determining human cancer risk of THS exposure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Genetic variation in metallothionein and metal-regulatory transcription factor 1 in relation to urinary cadmium, copper, and zinc

Background: Metallothionein (MT) proteins play critical roles in the physiological handling of both essential (Cu and Zn) and toxic (Cd) metals. MT expression is regulated by metal-regulatory transcription factor 1 (MTF1). Hence, genetic variation in the MT gene family and MTF1 might influence excretion of these metals. Methods: 321 women were recruited in Seattle, WA and Las Cruces, NM and provided demographic information, urine samples for measurement of metal concentrations by mass spectrometry and creatinine, and blood or saliva for extraction of DNA. Forty-one single nucleotide polymorphisms (SNPs) within the MTF1 gene region and the region of chromosome 16 encoding the MT gene family were selected for genotyping in addition to an ancestry informative marker panel. Linear regression was used to estimate the association of SNPs with urinary Cd, Cu, and Zn, adjusted for age, urinary creatinine, smoking history, study site, and ancestry. Results: Minor alleles of rs28366003 and rs10636 near the MT2A gene were associated with lower urinary Cd, Cu, and Zn. Minor alleles of rs8044719 and rs1599823, near MT1A and MT1B, were associated with lower urinary Cd and Zn, respectively. Minor alleles of rs4653329 in MTF1 were associated with lower urinary Cd. Conclusions: These results suggest that genetic variation in the MT gene region and MTF1 influences urinary Cd, Cu, and Zn excretion. - Highlights: • Genetic variation in metallothionein (MT) genes was assessed in two diverse populations. • Single nucleotide polymorphisms (SNPs) in MT genes were associated with mean urinary Cd, Cu and Zn. • Genetic variation may influence biomarkers of exposure, and associations of exposure with health.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Genetic susceptibility to toxicologic lung responses among inbred mouse strains following exposure to carbon nanotubes and profiling of underlying gene networks

The risk of human exposure to fiber nanoparticles has risen in recent years due to increases in the manufacture and utilization of carbon nanotubes (CNTs). CNTs are present as airborne particulates in occupational settings and their hazard potential has been demonstrated in experimental lung exposure studies using inbred mouse strains. However, it is not known whether different inbred strains differ in lung responses to CNTs by virtue of their genetics. In this work, common inbred strains (BALB/c, C57Bl/6, DBA/2, and C3H/He) were exposed to CNTs via oropharyngeal aspiration and lung histology and bronchoalveolar lavage (BAL) samples were evaluated over 28 days with the objective of evaluating sensitivity/resistance among strains. C57Bl/6 mice developed significantly more extensive type II pneumocyte (T2P) hyperplasia and alveolar infiltrate compared to DBA/2 mice, which were resistant. Surprisingly, DBA/2 but not C57Bl/6 mice were extremely sensitive to increases in leukocytes recovered in BAL fluid. Underlying global gene expression patterns in the two strains were compared using mRNA sequencing to investigate regulatory networks associated with the different effects. The impact of exposure on gene networks regulating various aspects of immune response and cell survival was limited in DBA/2 mice compared to C57Bl/6. Investigation of B6D2F1 (C57Bl/6 × DBA/2 hybrid) mice demonstrated inheritance of sensitivity to CNT exposures in regard to toxicologic lung pathology and BAL leukocyte accumulations. These findings demonstrate a genetic basis of susceptibility to CNT particle exposures and both inform the use of inbred mouse models and suggest the likelihood of differences in genetic susceptibility among humans. - Highlights: • Strain-specific effects followed instilled lung exposure to thin, tangled MWCNTS in mice. • Exposed C57Bl/6 exhibits more pronounced lung pathology and proinflammatory signaling. • Exposed DBA/2 responds with highly sensitive increases in leukocytes in lavage samples • Genetic background is shown to play a role in nature and severity of adverse effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Experimental validation that human microbiome phages use alternative genetic coding

Previous bioinformatic analyses of metagenomic data have indicated that bacteriophages can use genetic codes different from those of their host bacteria. In particular, reassignment of stop codon TAG to glutamine (a variation known as ‘genetic code 15’) has been predicted. Here, we use LC-MS/MS-based metaproteomics of human fecal samples to provide experimental evidence of the use of genetic code 15 in two crAss-like phages. Furthermore, the proteomic data from several phage structural proteins supports the reassignment of the TAG stop codon to glutamine late in the phage infection cycle. Thus, our work experimentally validates the expression of genetic code 15 in human microbiome phages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Simulation of sugar kelp ( Saccharina latissima ) breeding guided by practices to accelerate genetic gains

Abstract Though Saccharina japonica cultivation has been established for many decades in East Asian countries, the domestication process of sugar kelp (Saccharina latissima) in the Northeast United States is still at its infancy. In this study, by using data from our breeding experience, we will demonstrate how obstacles for accelerated genetic gain can be assessed using simulation approaches that inform resource allocation decisions. Thus far, we have used 140 wild sporophytes that were sampled in 2018 from the northern Gulf of Maine to southern New England. From these sporophytes, we sampled gametophytes and made and evaluated over 600 progeny sporophytes from crosses among the gametophytes in 2019 and 2020. The biphasic life cycle of kelp gives a great advantage in selective breeding as we can potentially select both on the sporophytes and gametophytes. However, several obstacles exist, such as the amount of time it takes to complete a breeding cycle, the number of gametophytes that can be maintained in the laboratory, and whether positive selection can be conducted on farm-tested sporophytes. Using the Gulf of Maine population characteristics for heritability and effective population size, we simulated a founder population of 1,000 individuals and evaluated the impact of overcoming these obstacles on rate of genetic gain. Our results showed that key factors to improve current genetic gain rely mainly on our ability to induce reproduction of the best farm-tested sporophytes, and to accelerate the clonal vegetative growth of released gametophytes so that enough gametophyte biomass is ready for making crosses by the next growing season. Overcoming these challenges could improve rates of genetic gain more than 2-fold. Future research should focus on conditions favorable for inducing spring reproduction, and on increasing the amount of gametophyte tissue available in time to make fall crosses in the same year.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Predictive Models of Genetic Redundancy in Arabidopsis thaliana

Abstract Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features derived from accumulating omics and mutant phenotype data is yet to be established. In addition, the relative importance of these features for genetic redundancy remains largely unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plant Arabidopsis thaliana based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including posttranslational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used significantly affected model performance based on holdout, testing phenotype data. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. We also explored the potential reasons underlying mispredictions and limitations of our studies. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Ecological and genetic barriers differentiate natural populations of Saccharomyces cerevisiae

How populations that inhabit the same geographical area become genetically differentiated is not clear. To investigate this, we characterized phenotypic and genetic differences between two populations of Saccharomyces cerevisiae that in some cases inhabit the same environment but show relatively little gene flow. We profiled stress sensitivity in a group of vineyard isolates and a group of oak-soil strains and found several niche-related phenotypes that distinguish the populations. We performed bulk-segregant mapping on two of the distinguishing traits: The vineyard-specific ability to grow in grape juice and oak-specific tolerance to the cell wall damaging drug Congo red. To implicate causal genes, we also performed a chemical genomic screen in the lab-strain deletion collection and identified many important genes that fell under quantitative trait loci peaks. One gene important for growth in grape juice and identified by both the mapping and the screen was SSU1 , a sulfite-nitrite pump implicated in wine fermentations. The beneficial allele is generated by a known translocation that we reasoned may also serve as a genetic barrier. We found that the translocation is prevalent in vineyard strains, but absent in oak strains, and presents a postzygotic barrier to spore viability. Furthermore, the translocation was associated with a fitness cost to the rapid growth rate seen in oak-soil strains. Lastly, our results reveal the translocation as a dual-function locus that enforces ecological differentiation while producing a genetic barrier to gene flow in these sympatric populations.

59 BASIC BIOLOGICAL SCIENCES↗