Task-Specific Compressive Optical System Design through Genetic Algorithms.
Abstract not provided.
Galiardi, Meghan↗
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Results for “Genetic”
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GeneLab: Conducting Genetic Research in Space: Using NASAs GeneLab genetic data to advance medical research
GeneLab overview with description of one type of analysis that GeneLab can be used to generate novel hypothesis.
Afshin Beheshti↗
Disentangling genetic structure for genetic monitoring of complex populations
Explore the source record for details and available documents.
Brook G. Milligan↗
Genomic Diversity Evaluation of Populus trichocarpa Germplasm for Rare Variant Genetic Association Studies
Genome-wide association studies are powerful tools to elucidate the genome-to-phenome relationship. In order to explain most of the observed heritability of a phenotypic trait, a sufficient number of individuals and a large set of genetic variants must be examined. The development of high-throughput technologies and cost-efficient resequencing of complete genomes have enabled the genome-wide identification of genetic variation at large scale. As such, almost all existing genetic variation becomes available, and it is now possible to identify rare genetic variants in a population sample. Rare genetic variants that were usually filtered out in most genetic association studies are the most numerous genetic variations across genomes and hold great potential to explain a significant part of the missing heritability observed in association studies. Rare genetic variants must be identified with high confidence, as they can easily be confounded with sequencing errors. In this study, we used a pre-filtered data set of 1,014 pure Populus trichocarpa entire genomes to identify rare and common small genetic variants across individual genomes. We compared variant calls between Platypus and HaplotypeCaller pipelines, and we further applied strict quality filters for improved genetic variant identification. Finally, we only retained genetic variants that were identified by both variant callers increasing calling confidence. Based on these shared variants and after stringent quality filtering, we found high genomic diversity in P. trichocarpa germplasm, with 7.4 million small genetic variants. Importantly, 377k non-synonymous variants (5% of the total) were uncovered. We highlight the importance of genomic diversity and the potential of rare defective genetic variants in explaining a significant portion of P. trichocarpa's phenotypic variability in association genetics. The ultimate goal is to associate both rare and common alleles with poplar's wood quality traits to support selective breeding for an improved bioenergy feedstock.
Genetics & Heredity↗
Genetic compensation of triacylglycerol biosynthesis in the green microalga Chlamydomonas reinhardtii
Genetic compensation has been proposed to explain phenotypic differences between gene knockouts and knockdowns in several metazoan and plant model systems. With the rapid development of reverse genetic tools such as CRISPR/Cas9 and RNAi in microalgae, it is increasingly important to assess whether genetic compensation affects the phenotype of engineered algal mutants. While exploring triacylglycerol (TAG) biosynthesis pathways in the model alga Chlamydomonas reinhardtii, it was discovered that knockout of certain genes catalyzing rate-limiting steps of TAG biosynthesis, type-2 diacylglycerol acyltransferase genes (DGTTs), triggered genetic compensation under abiotic stress conditions. Genetic compensation of a DGTT1 null mutation by a related PDAT gene was observed regardless of the strain background or mutagenesis approach, for example, CRISPR/Cas 9 or insertional mutagenesis. However, no compensation was found in the PDAT knockout mutant. The effect of PDAT knockout was evaluated in a Δvtc1 mutant, in which PDAT was upregulated under stress, resulting in a 90% increase in TAG content. Knockout of PDAT in the Δvtc1 background induced a 12.8-fold upregulation of DGTT1 and a 272.3% increase in TAG content in Δvtc1/pdat1 cells, while remaining viable. These data suggest that genetic compensation contributes to the genetic robustness of microalgal TAG biosynthetic pathways, maintaining lipid and redox homeostasis in the knockout mutants under abiotic stress. This work demonstrates examples of genetic compensation in microalgae, implies the physiological relevance of genetic compensation in TAG biosynthesis under stress, and provides guidance for future genetic engineering and mutant characterization efforts.
09 BIOMASS FUELS↗
A swapped genetic code prevents viral infections and gene transfer
Engineering the genetic code of an organism has been proposed to provide a firewall from natural ecosystems by preventing viral infections and gene transfer. However, numerous viruses and mobile genetic elements encode parts of the translational apparatus, potentially rendering a genetic-code-based firewall ineffective. Here we show that such mobile transfer RNAs (tRNAs) enable gene transfer and allow viral replication in Escherichia coli despite the genome-wide removal of 3 of the 64 codons and the previously essential cognate tRNA and release factor genes. We then establish a genetic firewall by discovering viral tRNAs that provide exceptionally efficient codon reassignment allowing us to develop cells bearing an amino acid-swapped genetic code that reassigns two of the six serine codons to leucine during translation. This amino acid-swapped genetic code renders cells resistant to viral infections by mistranslating viral proteomes and prevents the escape of synthetic genetic information by engineered reliance on serine codons to produce leucine-requiring proteins. As these cells may have a selective advantage over wild organisms due to virus resistance, we also repurpose a third codon to biocontain this virus-resistant host through dependence on an amino acid not found in nature. Furthermore, our results may provide the basis for a general strategy to make any organism safely resistant to all natural viruses and prevent genetic information flow into and out of genetically modified organisms.
59 BASIC BIOLOGICAL SCIENCES↗
Biomass yield in a genetically diverse Miscanthus sacchariflorus germplasm panel phenotyped at five locations in Asia, North America, and Europe
Abstract Miscanthus is a high‐yielding bioenergy crop that is broadly adapted to temperate and tropical environments. Commercial cultivation of Miscanthus is predominantly limited to a single sterile triploid clone of Miscanthus × giganteus , a hybrid between Miscanthus sacchariflorus and M. sinensis. To expand the genetic base of M. × giganteus , the substantial diversity within its progenitor species should be used for cultivar improvement and diversification. Here, we phenotyped a diversity panel of 605 M. sacchariflorus from six previously described genetic groups and 27 M. × giganteus genotypes for dry biomass yield and 16 yield‐component traits, in field trials grown over 3 years at one subtropical location (Zhuji, China) and four temperate locations (Foulum, Denmark; Sapporo, Japan; Urbana, Illinois; and Chuncheon, South Korea). There was considerable diversity in yield and yield‐component traits among and within genetic groups of M. sacchariflorus , and across the five locations. Biomass yield of M. sacchariflorus ranged from 0.003 to 34.0 Mg ha −1 in year 3. Variation among the genetic groups was typically greater than within, so selection of genetic group should be an important first step for breeding with M. sacchariflorus . The Yangtze 2x genetic group (=ssp. lutarioriparius ) of M. sacchariflorus had the tallest and thickest culms at all locations tested. Notably, the Yangtze 2x genetic group's exceptional culm length and yield potential were driven primarily by a large number of nodes (>29 nodes culm −1 average over all locations), which was consistent with the especially late flowering of this group. The S Japan 4x, the N China/Korea/Russia 4x, and the N China 2x genetic groups were also promising genetic resources for biomass yield, culm length, and culm thickness, especially for temperate environments. Culm length was the best indicator of yield potential in M. sacchariflorus . These results will inform breeders' selection of M. sacchariflorus genotypes for population improvement and adaptation to target production environments.
59 BASIC BIOLOGICAL SCIENCES↗
Ecological connectivity and habitat loss shape patterns of genetic diversity in a threatened salamander
Context The maintenance of genetic diversity is essential for preserving adaptive potential in populations, yet it is increasingly threatened by landscape alteration. The field of landscape genetics offers a framework for assessing how patch-level landscape conditions, modeled at multiple scales, influence genetic diversity. Objectives We sought to assess how local environmental features and connectivity influence genetic diversity across 74 four-toed salamander (Hemidactylium scutatum) breeding wetlands in the southeastern United States. Methods Using next-generation sequencing data and hierarchical Bayesian models, we examined genome-wide heterozygosity in relation to local landscape features and ecological connectivity. We also assessed the scale of effect of landscape features and tested for temporal lag effects. Results Genetic diversity was lower in wetlands with higher levels of historic deforestation and lower connectivity. An interaction between deforestation and connectivity indicated that deforestation had stronger negative effects in isolated wetlands but weaker effects in well-connected wetlands. Accounting for scale of effect and temporal lags was critical for detecting these relationships. Conclusions Our analyses highlight the importance of assessing the spatial scale (scale of effect) and temporal lag of landscape features to detect key drivers of genetic diversity. In line with population genetic theory, our results indicate that the genetic consequences of habitat loss do not affect populations uniformly and are most severe in isolated populations where gene flow cannot buffer against loss of diversity. Altogether, we highlight the importance of considering the interaction of habitat loss and connectivity in conservation genetic management.
Hemidactylium scutatum↗
A Parallel Genetic Algorithm for Automated Electronic Circuit Design
Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency issues in the GA, it is possible to have idle processors. However, as long as the load at each processing node is similar, the processors are kept busy nearly all of the time. In applying GAs to circuit design, a suitable genetic representation 'is that of a circuit-construction program. We discuss one such circuit-construction programming language and show how evolution can generate useful analog circuit designs. This language has the desirable property that virtually all sets of combinations of primitives result in valid circuit graphs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm and circuit simulation software, we present experimental results as applied to three analog filter and two amplifier design tasks. For example, a figure shows an 85 dB amplifier design evolved by our system, and another figure shows the performance of that circuit (gain and frequency response). In all tasks, our system is able to generate circuits that achieve the target specifications.
Long, Jason D.↗
Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England
Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don’t yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.
60 APPLIED LIFE SCIENCES↗
Predictive models of the genetic bases underlying budding yeast fitness in multiple environments
Abstract The ability of organisms to adapt and survive depends on the effects of genes and the environment on fitness. However, the multigenic nature of fitness and genotype-by-environment interactions hinder our understanding of the genetic basis of fitness. Here, we established fitness prediction models for 35 environments using machine learning and existing fitness data and different genetic variant types for a Saccharomyces cerevisiae population. Models revealed that the predictive ability of genetic variants varied across environments, with copy number variants explaining the majority of fitness variation in most cases. Model interpretation showed that different variant types identified distinct gene sets associated with predictive variants. These gene sets were significantly enriched in experimentally validated genes affecting fitness in only a subset of environments, indicating that many genes influencing fitness remain unexplored. Notably, non-experimentally validated genes were more important than validated ones for fitness predictions. Gene contributions to predictions were both isolate- and environment-dependent, pointing to gene-by-gene and gene-by-environment interactions. Furthermore, models uncovered experimentally validated and novel candidate genetic interactions for a well-characterized stress, the fungicide benomyl. These findings highlight the feasibility of identifying the genetic basis of fitness by using different genetic variant types and offer novel targets for future functional analysis.
DNA copy number variations↗
Developing a pipeline to expand the genetic code of diverse bacteria for microbial engineering
Microbial biotechnologies are key to addressing grand challenges to promote human health, reverse carbon emissions, recycle mixed plastic waste, remediate contaminated soils, and achieve sustainable economies. Synthetic biology has enabled design of diverse microbes and their proteins for useful purposes, but the narrowness of the natural genetic code limits functional diversity (e.g., biosynthesis) of engineered microbes. The natural genetic code defines the fundamental rules of translating genetic information into proteins comprised of 22 ‘canonical’ amino acids. However, using a technique called genetic code expansion (GCE), the chemical properties and therefore functions of proteins can be transformed by incorporation of one or more of ~200 chemically diverse ‘non-canonical’ amino acids. The effective application of genetic code expansion in diverse microbes has the potential to revolutionize biotechnology. However, despite over 50 years of research and its transformative potential, the application of genetic code expansion has been limited to a handful of bacterial species. In this project, we will perform three tasks to both overcome the barriers that prevent wide spread adoption of GCE as molecular tool and demonstrate its potential for biotechnological applications. Specifically, we will (1) develop a genetic engineering methodology that will enable use of GCE in a broad range of bacterial hosts, (2) use high-throughput functional genomics methods to identify physiological responses to both genetic code expansion and exposure to non-canonical amino acids in three different bacteria, and (3) demonstrate an application of GCE by selectively incorporate non-canonical amino acids into surface displayed peptides such as those used for biomining.
59 BASIC BIOLOGICAL SCIENCES↗
An analysis of the metabolic theory of the origin of the genetic code
A computer program was used to test Wong's coevolution theory of the genetic code. The codon correlations between the codons of biosynthetically related amino acids in the universal genetic code and in randomly generated genetic codes were compared. It was determined that many codon correlations are also present within random genetic codes and that among the random codes there are always several which have many more correlations than that found in the universal code. Although the number of correlations depends on the choice of biosynthetically related amino acids, the probability of choosing a random genetic code with the same or greater number of codon correlations as the universal genetic code was found to vary from 0.1% to 34% (with respect to a fairly complete listing of related amino acids). Thus, Wong's theory that the genetic code arose by coevolution with the biosynthetic pathways of amino acids, based on codon correlations between biosynthetically related amino acids, is statistical in nature.
NASA Discipline Exobiology↗
Increasing temperature weakens the positive effect of genetic diversity on population growth
Abstract Genetic diversity and temperature increases associated with global climate change are known to independently influence population growth and extinction risk. Whether increasing temperature may influence the effect of genetic diversity on population growth, however, is not known. We address this issue in the model protist system Tetrahymena thermophila . We test the hypothesis that at temperatures closer to the species’ thermal optimum (i.e., the temperature at which population growth is maximal, or T opt ), genetic diversity should have a weaker effect on population growth compared to temperatures away from the thermal optimum. To do so, we grew populations of T . thermophila with varying levels of genetic diversity at increasingly warmer temperatures and quantified their intrinsic population growth rate, r . We found that genetic diversity increases population growth at cooler temperatures, but that as temperature increases, this effect weakens. We also show that a combination of changes in the amount of expressed genetic diversity (G) in r , plastic changes in population growth across temperatures (E), and strong G × E interactions underlie this temperature effect. Our results uncover important but largely overlooked temperature effects that have implications for the management of small populations with depauperate genetic stocks in an increasingly warming world.
59 BASIC BIOLOGICAL SCIENCES↗
Additive and Non-Additive Genetic Variances for Tree Growth in Several Hybrid Poplar Populations and Implications Regarding Breeding Strategy
Populus species (P. deltoides, P. maximowiczii, P. nigra) and their inter-specific hybrids were tested for growth rate over a five year period at four test locations in Minnesota, USA, to estimate genetic variance components. The breeding scheme incorporated recurrent selection of full-sib families of pure species parents, production of F 1 inter-specific hybrids from selected families, and selection of clones within the F 1 s. Improvement of yield through time using this scheme is predicated on the assumption that additive effects comprise a significant portion of the total genetic variance. The estimates of additive and non-additive variances reported are not traditional point estimates, because a fully balanced mating design was impossible due to parental incompatibilities which result in incomplete breeding matrices. Instead, bounded estimates, not previously used in tree genetics research, are derived from linear combinations of formulae of genetic expectations observed among-family, among-clone, and environmental variances. Our results suggest that combined family and mass selection would lead to increases in growth rate of 27 % and 47 % per generation in P. deltoides and P. nigra , respectively. Broad sense-based clonal selection within the F 1 could yield selection responses in excess of 90 % of the mean of such populations. Among-family variance comprised about 1/3 of total genetic variance while within-family variance was always about 2/3 of total genetic variance, regardless of pedigree. With this beind said, the results indicate that recurrent intraspecific selective breeding followed by interspecific hybridization and non-recurrent selection based on broad sense genetic variation would constitute an effective yield improvement strategy.
54 ENVIRONMENTAL SCIENCES↗
Congruence between fine-scale genetic breaks and dispersal potential in an estuarine seaweed across multiple transition zones
Abstract Genetic structure in biogeographical transition zones can be shaped by several factors including limited dispersal across barriers, admixture following secondary contact, differential selection, and mating incompatibility. A striking example is found in Northwest France and Northwest Spain, where the estuarine seaweed Fucus ceranoides L. exhibits sharp, regional genetic clustering. This pattern has been related to historical population fragmentation and divergence into distinct glacial refugia, followed by post-glacial expansion and secondary contact. The contemporary persistence of sharp ancient genetic breaks between nearby estuaries has been attributed to prior colonization effects (density barriers) but the effect of oceanographic barriers has not been tested. Here, through a combination of mesoscale sampling (15 consecutive populations) and population genetic data (mtIGS) in NW France, we define regional genetic disjunctions similar to those described in NW Iberia. Most importantly, using high resolution dispersal simulations for Brittany and Iberian populations, we provide evidence for a central role of contemporary hydrodynamics in maintaining genetic breaks across these two major biogeographic transition zones. Our findings further show the importance of a comprehensive understanding of oceanographic regimes in hydrodynamically complex coastal regions to explain the maintenance of sharp genetic breaks along continuously populated coastlines.
Nicastro, Katy R.↗
Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics
Abstract Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population‐specific and pairwise F ST ) within five metapopulations (79 populations, 4583 individuals) of steelhead trout ( Oncorhynchus mykiss ) in the Columbia River Basin, USA . Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate‐related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin‐wide to the metapopulation scale). Sensitivity analysis (leave‐one‐population‐out) revealed consistent relationships between climate variables and F ST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes ( N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.
Hand, Brian K.↗
Genetic diversity loss in the Anthropocene
Anthropogenic habitat loss and climate change are reducing species’ geographic ranges, increasing extinction risk and losses of species’ genetic diversity. Although preserving genetic diversity is key to maintaining species’ adaptability, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. We introduce a mathematical framework that bridges biodiversity theory and population genetics to understand the loss of naturally occurring DNA mutations with decreasing habitat. By analyzing genomic variation of 10,095 georeferenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a mutations-area relationship power law with geographic area, which can predict genetic diversity loss from local population extinctions. We estimate that more than 10% of genetic diversity may already be lost for many threatened and nonthreatened species, surpassing the United Nations’ post-2020 targets for genetic preservation.
Science & Technology - Other Topics↗