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Journal articles on the topic 'Genetics, Experimental'

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Published: 4 June 2021

Last updated: 1 February 2022

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1

Teotónio, Henrique, Suzanne Estes, Patrick C. Phillips, and Charles F. Baer. "Experimental Evolution withCaenorhabditisNematodes." Genetics 206, no. 2 (June 2017): 691–716. http://dx.doi.org/10.1534/genetics.115.186288.

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2

Dominiczak, Anna F., James S. Clark, Baxter Jeffs, Niall H. Anderson, Cervantes D. Negrin, Wai K. Lee, and M. Julia Brosnan. "Genetics of experimental hypertension." Journal of Hypertension 16, Supplement (December 1998): 1859–69. http://dx.doi.org/10.1097/00004872-199816121-00003.

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3

Nilsson, Annika I., Elisabeth Kugelberg, Otto G. Berg, and Dan I. Andersson. "Experimental Adaptation ofSalmonella typhimuriumto Mice." Genetics 168, no. 3 (November 2004): 1119–30. http://dx.doi.org/10.1534/genetics.104.030304.

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4

McClosky, B., and S. D. Tanksley. "Optimizing Experimental Design in Genetics." Journal of Optimization Theory and Applications 157, no. 2 (September 18, 2012): 520–32. http://dx.doi.org/10.1007/s10957-012-0172-9.

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5

Silverman, Sanford J. "Experimental techniques in bacterial genetics." Analytical Biochemistry 192, no. 1 (January 1991): 254. http://dx.doi.org/10.1016/0003-2697(91)90219-j.

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6

Crow, James F., and Seymour Abrahamson. "Seventy Years Ago: Mutation Becomes Experimental." Genetics 147, no. 4 (December 1, 1997): 1491–96. http://dx.doi.org/10.1093/genetics/147.4.1491.

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7

Dykhuizen, Daniel E., and Antony M. Dean. "Evolution of Specialists in an Experimental Microcosm." Genetics 167, no. 4 (August 2004): 2015–26. http://dx.doi.org/10.1534/genetics.103.025205.

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8

Colegrave, N., and S. Collins. "Experimental evolution: experimental evolution and evolvability." Heredity 100, no. 5 (January 23, 2008): 464–70. http://dx.doi.org/10.1038/sj.hdy.6801095.

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9

Cesarini, David, Christopher T. Dawes, Magnus Johannesson, Paul Lichtenstein, and Björn Wallace. "Experimental Game Theory and Behavior Genetics." Annals of the New York Academy of Sciences 1167, no. 1 (June 2009): 66–75. http://dx.doi.org/10.1111/j.1749-6632.2009.04505.x.

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10

Johnston, Mark, and Oliver Hobert. "Extending Our Experimental Reach: Toolbox Reviews in GENETICS." Genetics 192, no. 1 (September 2012): 1. http://dx.doi.org/10.1534/genetics.112.143578.

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11

Botstein, David, and Gerald R. Fink. "Yeast: An Experimental Organism for 21st Century Biology." Genetics 189, no. 3 (November 2011): 695–704. http://dx.doi.org/10.1534/genetics.111.130765.

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12

Werren, John H., and Johannes van den Assem. "EXPERIMENTAL ANALYSIS OF A PATERNALLY INHERITED EXTRACHROMOSOMAL FACTOR." Genetics 114, no. 1 (September 1, 1986): 217–33. http://dx.doi.org/10.1093/genetics/114.1.217.

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ABSTRACT Virtually all known cases of extrachromosomal inheritance involve cytoplasmic inheritance through the maternal line. Recently, a paternally transmitted factor that causes the production of all-male families has been discovered in a parasitic wasp. The wasp has haplodiploid sex determination: male offspring are haploid and usually develop from unfertilized eggs, whereas females are diploid and usually develop from fertilized eggs. It has been postulated that this paternal sex-ratio factor (psr) is either (1) an infectious agent (a venereal disease) that is transmitted to the female reproductive tract during copulation with an infected male and, subsequently, causes all-male families or (2) a male cytoplasmic factor that is transmitted by sperm to eggs upon egg fertilization and, somehow, causes loss of the paternal set of chromosomes.—Experimental evidence is presented which shows that the factor requires egg fertilization for transmission to the next generation; therefore, it is likely to be a cytoplasmic factor. Significant potential intragenomic conflict results from the presence of this factor and two other sex-ratio distorters in this wasp species.

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13

Bell, G. "Experimental evolution." Heredity 100, no. 5 (April 23, 2008): 441–42. http://dx.doi.org/10.1038/hdy.2008.19.

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14

Wernick, Riana I., Stephen F. Christy, Dana K. Howe, Jennifer A. Sullins, Joseph F. Ramirez, Maura Sare, McKenna J. Penley, Levi T. Morran, Dee R. Denver, and Suzanne Estes. "Sex and Mitonuclear Adaptation in Experimental Caenorhabditis elegans Populations." Genetics 211, no. 3 (January 22, 2019): 1045–58. http://dx.doi.org/10.1534/genetics.119.301935.

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To reveal phenotypic and functional genomic patterns of mitonuclear adaptation, a laboratory adaptation study with Caenorhabditis elegans nematodes was conducted in which independently evolving lines were initiated from a low-fitness mitochondrial electron transport chain (ETC) mutant, gas-1. Following 60 generations of evolution in large population sizes with competition for food resources, two distinct classes of lines representing different degrees of adaptive response emerged: a low-fitness class that exhibited minimal or no improvement compared to the gas-1 mutant ancestor, and a high-fitness class containing lines that exhibited partial recovery of wild-type fitness. Many lines that achieved higher reproductive and competitive fitness levels were also noted to evolve high frequencies of males during the experiment, consistent with adaptation in these lines having been facilitated by outcrossing. Whole-genome sequencing and analysis revealed an enrichment of mutations in loci that occur in a gas-1-centric region of the C. elegans interactome and could be classified into a small number of functional genomic categories. A highly nonrandom pattern of mitochondrial DNA mutation was observed within high-fitness gas-1 lines, with parallel fixations of nonsynonymous base substitutions within genes encoding NADH dehydrogenase subunits I and VI. These mitochondrial gene products reside within ETC complex I alongside the nuclear-encoded GAS-1 protein, suggesting that rapid adaptation of select gas-1 recovery lines was driven by fixation of compensatory mitochondrial mutations.

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15

Liu, Jingxian, Jackson Champer, Anna Maria Langmüller, Chen Liu, Joan Chung, Riona Reeves, Anisha Luthra, et al. "Maximum Likelihood Estimation of Fitness Components in Experimental Evolution." Genetics 211, no. 3 (January 24, 2019): 1005–17. http://dx.doi.org/10.1534/genetics.118.301893.

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Estimating fitness differences between allelic variants is a central goal of experimental evolution. Current methods for inferring such differences from allele frequency time series typically assume that the effects of selection can be described by a fixed selection coefficient. However, fitness is an aggregate of several components including mating success, fecundity, and viability. Distinguishing between these components could be critical in many scenarios. Here, we develop a flexible maximum likelihood framework that can disentangle different components of fitness from genotype frequency data, and estimate them individually in males and females. As a proof-of-principle, we apply our method to experimentally evolved cage populations of Drosophila melanogaster, in which we tracked the relative frequencies of a loss-of-function and wild-type allele of yellow. This X-linked gene produces a recessive yellow phenotype when disrupted and is involved in male courtship ability. We find that the fitness costs of the yellow phenotype take the form of substantially reduced mating preference of wild-type females for yellow males, together with a modest reduction in the viability of yellow males and females. Our framework should be generally applicable to situations where it is important to quantify fitness components of specific genetic variants, including quantitative characterization of the population dynamics of CRISPR gene drives.

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16

Manichaikul, Ani, and Karl W. Broman. "Binary Trait Mapping in Experimental Crosses With Selective Genotyping." Genetics 182, no. 3 (May 4, 2009): 863–74. http://dx.doi.org/10.1534/genetics.108.098913.

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17

Wahl, Lindi M., Philip J. Gerrish, and Ivan Saika-Voivod. "Evaluating the Impact of Population Bottlenecks in Experimental Evolution." Genetics 162, no. 2 (October 1, 2002): 961–71. http://dx.doi.org/10.1093/genetics/162.2.961.

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AbstractExperimental evolution involves severe, periodic reductions in population size when fresh media are inoculated during serial transfer. These bottlenecks affect the dynamics of evolution, reducing the probability that a beneficial mutation will reach fixation. We quantify the impact of these bottlenecks on the evolutionary dynamics, for populations that grow exponentially between transfers and for populations in which growth is curbed by a resource-limited environment. We find that in both cases, mutations that survive bottlenecks are equally likely to occur, per unit time, at all times during the growth phase. We estimate the total fraction of beneficial mutations that are lost due to bottlenecks during experimental evolution protocols and derive the “optimal” dilution ratio, the ratio that maximizes the number of surviving beneficial mutations. Although more severe dilution ratios are often used in the literature, we find that a ratio of 0.1-0.2 minimizes the chances that rare beneficial mutations are lost. Finally, we provide a number of useful approximate results and illustrate our approach with applications to experimental evolution protocols in the literature.

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18

Barlow, Miriam, and Barry G. Hall. "Experimental Prediction of the Natural Evolution of Antibiotic Resistance." Genetics 163, no. 4 (April 1, 2003): 1237–41. http://dx.doi.org/10.1093/genetics/163.4.1237.

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AbstractThe TEM family of β-lactamases has evolved to confer resistance to most of the β-lactam antibiotics, but not to cefepime. To determine whether the TEM β-lactamases have the potential to evolve cefepime resistance, we evolved the ancestral TEM allele, TEM-1, in vitro and selected for cefepime resistance. After four rounds of mutagenesis and selection for increased cefepime resistance each of eight independent populations reached a level equivalent to clinical resistance. All eight evolved alleles increased the level of cefepime resistance by a factor of at least 32, and the best allele improved by a factor of 512. Sequencing showed that alleles contained from two to six amino acid substitutions, many of which were shared among alleles, and that the best allele contained only three substitutions.

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19

Manly, K. F. "Mathematica packages for simulation of experimental genetics." Bioinformatics 16, no. 4 (April 1, 2000): 408–10. http://dx.doi.org/10.1093/bioinformatics/16.4.408.

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20

Donnai, D. "Medical and Experimental Mammalian Genetics: A Perspective." Archives of Disease in Childhood 63, no. 1 (January 1, 1988): 110–11. http://dx.doi.org/10.1136/adc.63.1.110-b.

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21

Festing, Michael. "Experimental design, genetics and animal toxicity tests." Significance 4, no. 1 (March 2007): 37–40. http://dx.doi.org/10.1111/j.1740-9713.2007.00220.x.

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22

Goodfellow, P. N. "Medical and experimental mammalian genetics: A perspective." Trends in Genetics 4, no. 8 (August 1988): 240. http://dx.doi.org/10.1016/0168-9525(88)90161-8.

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23

KURTZ, T. "Genetics of experimental animal models of hypertension." American Journal of Hypertension 8, no. 4 (April 1995): 17A. http://dx.doi.org/10.1016/0895-7061(95)97438-w.

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24

Sacco, Roberto, Carla Lintas, and Antonio M. Persico. "Autism genetics: Methodological issues and experimental design." Science China Life Sciences 58, no. 10 (September 2, 2015): 946–57. http://dx.doi.org/10.1007/s11427-012-4315-x.

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25

Qian, Jiayi, Siyuan Su, and Pengda Liu. "Experimental Approaches in Delineating mTOR Signaling." Genes 11, no. 7 (July 2, 2020): 738. http://dx.doi.org/10.3390/genes11070738.

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The mTOR signaling controls essential biological functions including proliferation, growth, metabolism, autophagy, ageing, and others. Hyperactivation of mTOR signaling leads to a plethora of human disorders; thus, mTOR is an attractive drug target. The discovery of mTOR signaling started from isolation of rapamycin in 1975 and cloning of TOR genes in 1993. In the past 27 years, numerous research groups have contributed significantly to advancing our understanding of mTOR signaling and mTOR biology. Notably, a variety of experimental approaches have been employed in these studies to identify key mTOR pathway members that shape up the mTOR signaling we know today. Technique development drives mTOR research, while canonical biochemical and yeast genetics lay the foundation for mTOR studies. Here in this review, we summarize major experimental approaches used in the past in delineating mTOR signaling, including biochemical immunoprecipitation approaches, genetic approaches, immunofluorescence microscopic approaches, hypothesis-driven studies, protein sequence or motif search driven approaches, and bioinformatic approaches. We hope that revisiting these distinct types of experimental approaches will provide a blueprint for major techniques driving mTOR research. More importantly, we hope that thinking and reasonings behind these experimental designs will inspire future mTOR research as well as studies of other protein kinases beyond mTOR.

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26

Rönnegård, Lars, and William Valdar. "Detecting Major Genetic Loci Controlling Phenotypic Variability in Experimental Crosses." Genetics 188, no. 2 (April 5, 2011): 435–47. http://dx.doi.org/10.1534/genetics.111.127068.

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27

Smit-McBride, Z., A. Moya, and F. J. Ayala. "Linkage disequilibrium in natural and experimental populations of Drosophila melanogaster." Genetics 120, no. 4 (December 1, 1988): 1043–51. http://dx.doi.org/10.1093/genetics/120.4.1043.

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Abstract We have studied linkage disequilibrium in Drosophila melanogaster in two samples from a wild population and in four large laboratory populations derived from the wild samples. We have assayed four polymorphic enzyme loci, fairly closely linked in the third chromosome: Sod Est-6, Pgm, and Odh. The assay method used allows us to identify the allele associations separately in each of the two homologous chromosomes from each male sampled. We have detected significant linkage disequilibrium between two loci in 16.7% of the cases in the wild samples and in 27.8% of the cases in the experimental populations, considerably more than would be expected by chance alone. We have also found three-locus disequilibria in more instances than would be expected by chance. Some disequilibria present in the wild samples disappear in the experimental populations derived from them, but new ones appear over the generations. The effective population sizes required to generate the observed disequilibria by randomness range from 40 to more than 60,000 individuals in the natural population, depending on which locus pair is considered, and from 100 to more than 60,000 in the experimental populations. These population sizes are unrealistic; the fact that different locus-pairs yield disparate estimates within the same population argues against the likelihood that the disequilibria may have arisen as a consequence of population bottlenecks. Migration, or population mixing, cannot be excluded as the process generating the disequilibria in the wild samples, but can in the experimental populations. We conclude that linkage disequilibrium in these populations is most likely due to natural selection acting on the allozymes, or on loci very tightly linked to them.

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28

Allard, R. W., Q. Zhang, M. A. Maroof, and O. M. Muona. "Evolution of multilocus genetic structure in an experimental barley population." Genetics 131, no. 4 (August 1, 1992): 957–69. http://dx.doi.org/10.1093/genetics/131.4.957.

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Abstract Data from 311 selfed families isolated from four generations (F8, F13, F23, F45) of an experimental barley population were analyzed to determine patterns of change in character expression for seven quantitative traits, and in single-locus allelic frequencies, and multilocus genetic structure, for 16 Mendelian loci that code for discretely recognizable variants. The analyses showed that large changes in single-locus allelic frequencies and major reorganizations in multilocus genetic structure occurred in each of the generation-to-generation transitions examined. Although associations among a few traits persisted over generations, dynamic dissociations and reassociations occurred among several traits in each generation-transition period. Overall, the restructuring that occurred was characterized by gradual decreases in the number of clusters of associated traits and increases in the number of traits within each cluster. The observed changes in single-locus frequencies and in multilocus genetic structure were attributed to interplay among various evolutionary factors among which natural selection acting in a temporally heterogeneous environment was the guiding force.

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29

Darvasi, A., and M. Soller. "Advanced intercross lines, an experimental population for fine genetic mapping." Genetics 141, no. 3 (November 1, 1995): 1199–207. http://dx.doi.org/10.1093/genetics/141.3.1199.

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Abstract An advanced intercrossed line (AIL) is an experimental population that can provide more accurate estimates of quantitative trait loci (QTL) map location than conventional mapping populations. An AIL is produced by randomly and sequentially intercrossing a population that initially originated from a cross between two inbred lines or some variant thereof. This provides increasing probability of recombination between any two loci. Consequently, the genetic length of the entire genome is stretched, providing increased mapping resolution. In this way, for example, with the same population size and QTL effect, a 95% confidence interval of QTL map location of 20 cM in the F2 is reduced fivefold after eight additional random mating generations (F10). Simulation results showed that to obtain the anticipated reduction in the confidence interval, breeding population size of the AIL in all generations should comprise an effective number of > or = 100 individuals. It is proposed that AILs derived from crosses between known inbred lines may be a useful resource for fine genetic mapping.

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30

Elena, Santiago F., Fernando González-Candelas, Isabel S. Novella, Elizabeth A. Duarte, David K. Clarke, Esteban Domingo, John J. Holland, and Andrés Moya. "Evolution of Fitness in Experimental Populations of Vesicular Stomatitis Virus." Genetics 142, no. 3 (March 1, 1996): 673–79. http://dx.doi.org/10.1093/genetics/142.3.673.

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Abstract The evolution of fitness in experimental clonal populations of vesicular stomatitis virus (VSV) has been compared under different genetic (fitness of initial clone) and demographic (population dynamics) regimes. In spite of the high genetic heterogeneity among replicates within experiments, there is a clear effect of population dynamics on the evolution of fitness. Those populations that went through strong periodic bottlenecks showed a decreased fitness in competition experiments with wild type. Conversely, mutant populations that were transferred under the dynamics of continuous population expansions increased their fitness when compared with the same wild type. The magnitude of the observed effect depended on the fitness of the original viral clone. Thus, high fitness clones showed a larger reduction in fitness than low fitness clones under dynamics with included periodic bottleneck. In contrast, the gain in fitness was larger the lower the initial fitness of the viral clone. The quantitative genetic analysis of the trait “fitness” in the resulting populations shows that genetic variation for the trait is positively correlated with the magnitude of the change in the same trait. The results are interpreted in terms of the operation of Muller's ratchet and genetic drift as opposed to the appearance of beneficial mutations.

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31

Versace, Elisabetta. "Experimental evolution, behavior and genetics: Associative learning as a case study." Current Zoology 61, no. 2 (April 1, 2015): 226–41. http://dx.doi.org/10.1093/czoolo/61.2.226.

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Abstract The evolutionary dynamics of behavioral traits reflect phenotypic and genetic changes. Methodological difficulties in analyzing the genetic dynamics of complex traits have left open questions on the mechanisms that have shaped complex behaviors and cognitive abilities. A strategy to investigate the change of behavior across generations is to assume that genetic constraints have a negligible role in evolution (the phenotypic gambit) and focus on the phenotype as a proxy for genetic evolution. Empirical evidence and technologic advances in genomics question the choice of neglecting the genetic underlying the dynamics of behavioral evolution. I first discuss the relevance of genetic factors – e.g. genetic variability, genetic linkage, gene interactions – in shaping evolution, showing the importance of taking genetic factors into account when dealing with evolutionary dynamics. I subsequently describe the recent advancements in genetics and genomics that make the investigation of the ongoing evolutionary process of behavioral traits finally attainable. In particular, by applying genomic resequencing to experimental evolution – a method called Evolve & Resequence – it is possible to monitor at the same time phenotypic and genomic changes in populations exposed to controlled selective pressures. Experimental evolution of associative learning, a well-known trait that promptly responds to selection, is a convenient model to illustrate this approach applied to behavior and cognition. Taking into account the recent achievements of the field, I discuss how to design and conduct an effective Evolve & Resequence study on associative learning in Drosophila. By integrating phenotypic and genomic data in the investigation of evolutionary dynamics, new insights can be gained on longstanding questions such as the modularity of mind and its evolution.

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32

Hope, Elyse A., Clara J. Amorosi, Aaron W. Miller, Kolena Dang, Caiti Smukowski Heil, and Maitreya J. Dunham. "Experimental Evolution Reveals Favored Adaptive Routes to Cell Aggregation in Yeast." Genetics 206, no. 2 (April 26, 2017): 1153–67. http://dx.doi.org/10.1534/genetics.116.198895.

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33

Roux, Fabrice, Sandra Giancola, Stéphanie Durand, and Xavier Reboud. "Building of an Experimental Cline WithArabidopsis thalianato Estimate Herbicide Fitness Cost." Genetics 173, no. 2 (April 2, 2006): 1023–31. http://dx.doi.org/10.1534/genetics.104.036541.

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34

de Visser, J. A. G. M. Arjan, Rolf F. Hoekstra, and Herman van den Ende. "An Experimental Test for Synergistic Epistasis and Its Application in Chlamydomonas." Genetics 145, no. 3 (March 1, 1997): 815–19. http://dx.doi.org/10.1093/genetics/145.3.815.

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Theoretically, one of the most general benefits of sex is given by its function in facilitating selection against deleterious mutations. This advantage of sex may be deterministic if deleterious mumtiom affect the fitness of an individual in a synergistic way, i.e., if mutations increase each others' negative fitness effect. We present a new test for synergistic epistasis that considers the skewnessof the log fitness distribution of offspring from a cross. We applied this test to data of the unicellular alga Chlamydomonas moewussii. For this purpose, two crosses were made: one between two strains that are presumed to have accumulated slightly deleterious mutations, the other between two strains without a history of mutation accumulation. Fitness was measured by estimating the two parameters of logistic growth in batch culture, the maximum growth rate (r) and the carrying capacity (K). The finding of a negatively skewed distribution for K in the accumulation cross suggests synergism between mutations affecting the carrying capacity, while the absence of skewness for r in both crosses is consistent with independent effects of mutations affecting this parameter. The results suggest a possible alternative explanation for the general observation that sex is related to constant environments, where selection on K predominates, while asexual reproduction is found in more variable environments, where selection on r is more important.

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35

Wright, Fred A., and Augustine Kong. "Linkage Mapping in Experimental Crosses: The Robustness of Single-Gene Models." Genetics 146, no. 1 (May 1, 1997): 417–25. http://dx.doi.org/10.1093/genetics/146.1.417.

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The robustness of parametric linkage mapping against model misspecification is considered in experimental breeding designs, with a focus on localization of the gene. By examining the expected LOD across the genome, it is shown that single-gene models are quite robust, even for polygenic traits. However, when the marker map is of low resolution, linked polygenes can give rise to an apparent “ghost” gene, mapped to an incorrect interval. The results apply equally well to quantitative traits or qualitative (categorical) traits. The results are derived for backcross populations, with a discussion of extensions to intercross populations and relative-pair mapping in humans.

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36

Cuevas, José M., Santiago F. Elena, and Andrés Moya. "Molecular Basis of Adaptive Convergence in Experimental Populations of RNA Viruses." Genetics 162, no. 2 (October 1, 2002): 533–42. http://dx.doi.org/10.1093/genetics/162.2.533.

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Abstract Characterizing the molecular basis of adaptation is one of the most important goals in modern evolutionary genetics. Here, we report a full-genome sequence analysis of 21 independent populations of vesicular stomatitis ribovirus evolved on the same cell type but under different demographic regimes. Each demographic regime differed in the effective viral population size. Evolutionary convergences are widespread both at synonymous and nonsynonymous replacements as well as in an intergenic region. We also found evidence for epistasis among sites of the same and different loci. We explain convergences as the consequence of four factors: (1) environmental homogeneity that supposes an identical challenge for each population, (2) structural constraints within the genome, (3) epistatic interactions among sites that create the observed pattern of covariation, and (4) the phenomenon of clonal interference among competing genotypes carrying different beneficial mutations. Using these convergences, we have been able to estimate the fitness contribution of the identified mutations and epistatic groups. Keeping in mind statistical uncertainties, these estimates suggest that along with several beneficial mutations of major effect, many other mutations got fixed as part of a group of epistatic mutations.

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37

Cuevas, Jose M., Pilar Domingo-Calap, Marianoel Pereira-Gomez, and Rafael Sanjuan. "Experimental Evolution and Population Genetics of RNA Viruses." Open Evolution Journal 3, no. 1 (May 11, 2009): 9–16. http://dx.doi.org/10.2174/1874404400903010009.

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38

Zhao, Jean J., Thomas M. Roberts, and William C. Hahn. "Functional genetics and experimental models of human cancer." Trends in Molecular Medicine 10, no. 7 (July 2004): 344–50. http://dx.doi.org/10.1016/j.molmed.2004.05.005.

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39

Bogdanovic, N. "S-07: Dementia, Biomarker, Genetics and Experimental treatment." European Geriatric Medicine 6 (September 2015): S161—S163. http://dx.doi.org/10.1016/s1878-7649(15)30564-7.

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40

&NA;, &NA;. "Molecular genetics, immunology and experimental pathology of melanoma." Melanoma Research 4, no. 5 (October 1994): 331. http://dx.doi.org/10.1097/00008390-199410000-00012.

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41

Rose, Michael R., and Molly K. Burke. "Genomic Croesus: Experimental evolutionary genetics of Drosophila aging." Experimental Gerontology 46, no. 5 (May 2011): 397–403. http://dx.doi.org/10.1016/j.exger.2010.08.025.

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42

Delles, Christian, Martin W. McBride, Delyth Graham, Sandosh Padmanabhan, and Anna F. Dominiczak. "Genetics of hypertension: From experimental animals to humans." Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 1802, no. 12 (December 2010): 1299–308. http://dx.doi.org/10.1016/j.bbadis.2009.12.006.

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43

Kao, Chen-Hung. "Mapping Quantitative Trait Loci Using the Experimental Designs of Recombinant Inbred Populations." Genetics 174, no. 3 (November 2006): 1373–86. http://dx.doi.org/10.1534/genetics.106.056416.

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44

Knudsen, Bjarne, and Michael M. Miyamoto. "Incorporating Experimental Design and Error Into Coalescent/Mutation Models of Population History." Genetics 176, no. 4 (June 11, 2007): 2335–42. http://dx.doi.org/10.1534/genetics.106.063560.

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45

Sun, Wei, Joseph G. Ibrahim, and Fei Zou. "Genomewide Multiple-Loci Mapping in Experimental Crosses by Iterative Adaptive Penalized Regression." Genetics 185, no. 1 (February 15, 2010): 349–59. http://dx.doi.org/10.1534/genetics.110.114280.

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46

Sheng, Jian Rong, Maja Jagodic, Ingrid Dahlman, Kristina Becanovic, Rita Nohra, Monica Marta, Ellen Iacobaeus, Tomas Olsson, and Erik Wallström. "Eae19, a New Locus on Rat Chromosome 15 Regulating Experimental Autoimmune Encephalomyelitis." Genetics 170, no. 1 (February 16, 2005): 283–89. http://dx.doi.org/10.1534/genetics.104.035261.

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47

Good, A. G., G. A. Meister, H. W. Brock, T. A. Grigliatti, and D. A. Hickey. "Rapid spread of transposable p elements in experimental populations of Drosophila melanogaster." Genetics 122, no. 2 (June 1, 1989): 387–96. http://dx.doi.org/10.1093/genetics/122.2.387.

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Abstract The invasion of P elements in natural populations of Drosophila melanogaster was modeled by establishing laboratory populations with 1%, 5% and 10% P genomes and monitoring the populations for 20 generations. In one experiment, the ability of flies to either induce or suppress gonadal sterility in different generations was correlated with the amount of P element DNA. In a second experiment, the percentage of genomes that contained P elements, and the distribution of P elements among individual flies was monitored. The ability to induce gonadal dysgenesis increased rapidly each generation. However, the increase in P cytotype lagged behind by five to ten generations. The total amount of P element DNA and the frequency of flies containing P elements increased each generation. The number of P elements within individual genomes decreased initially, but then increased. Finally, the distribution of P elements within the genomes of individuals from later generations varied considerably, and this pattern differed from the parental P strain. These results suggest that the interaction between the assortment and recombination of chromosomal segments, and multiplicative transposition could result in the rapid spread of P elements in natural populations.

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García-Martínez, José, José Aurelio Castro, Misericordia Ramón, Amparo Latorre, and Andrés Moya. "Mitochondrial DNA Haplotype Frequencies in Natural and Experimental Populations of Drosophila subobscura." Genetics 149, no. 3 (July 1, 1998): 1377–82. http://dx.doi.org/10.1093/genetics/149.3.1377.

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Abstract The evolution of Drosophila subobscura mitochondrial DNA has been studied in experimental populations, founded with flies from a natural population from Esporles (Majorca, Balearic Islands, Spain). This population, like other European ones, is characterized by the presence of two very common (>96%) mitochondrial haplotypes (called I and II) and rare and endemic haplotypes that appear at very low frequencies. There is no statistical evidence of positive Darwinian selection acting on the mitochondrial DNA variants according to Tajima's neutrality test. Two experimental populations, with one replicate each, were established with flies having a heterogeneous nuclear genetic background, which was representative of the composition of the natural population. Both populations were started with the two most frequent mitochondrial haplotypes, but at different initial frequencies. After 13 to 16 generations, haplotype II reached fixation in three cages and its frequency was 0.89 by generation 25 in the fourth cage. Random drift can be rejected as the force responsible for the observed changes in haplotype frequencies. There is not only statistical evidence of a linear trend favoring a mtDNA (haploid) fitness effect, but also of a significant nonlinear deviation that could be due to a nuclear component.

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Wahl, Lindi M., and David C. Krakauer. "Models of Experimental Evolution: The Role of Genetic Chance and Selective Necessity." Genetics 156, no. 3 (November 1, 2000): 1437–48. http://dx.doi.org/10.1093/genetics/156.3.1437.

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Abstract We present a theoretical framework within which to analyze the results of experimental evolution. Rapidly evolving organisms such as viruses, bacteria, and protozoa can be induced to adapt to laboratory conditions on very short human time scales. Artificial adaptive radiation is characterized by a list of common observations; we offer a framework in which many of these repeated questions and patterns can be characterized analytically. We allow for stochasticity by including rare mutations and bottleneck effects, demonstrating how these increase variability in the evolutionary trajectory. When the product Np, the population size times the per locus error rate, is small, the rate of evolution is limited by the chance occurrence of beneficial mutations; when Np is large and selective pressure is strong, the rate-limiting step is the waiting time while existing beneficial mutations sweep through the population. We derive the rate of divergence (substitution rate) and rate of fitness increase for the case when Np is large and illustrate our approach with an application to an experimental data set. A minimal assumption of independent additive fitness contributions provides a good fit to the experimental evolution of the bacteriophage φX174.

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Notley-McRobb, Lucinda, and Thomas Ferenci. "Experimental Analysis of Molecular Events During Mutational Periodic Selections in Bacterial Evolution." Genetics 156, no. 4 (December 1, 2000): 1493–501. http://dx.doi.org/10.1093/genetics/156.4.1493.

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Abstract A fundamental feature of bacterial evolution is a succession of adaptive mutational sweeps when fitter mutants take over a population. To understand the processes involved in mutational successions, Escherichia coli continuous cultures were analyzed for changes at two loci where mutations provide strong transport advantages to fitness under steady-state glucose limitation. Three separate sweeps, observed as classic periodic selection events causing a change in the frequency of neutral mutations (in fhuA causing phage T5 resistance), were identified with changes at particular loci. Two of the sweeps were associated with a reduction in the frequency of neutral mutations and the concurrent appearance of at least 13 alleles at the mgl or mlc loci, respectively. These mgl and mlc polymorphisms were of many mutational types, so were not the result of a mutator or directed mutation event. The third sweep observed was altogether distinct and involved hitchhiking between T5 resistance and advantageous mgl mutations. Moreover, the hitchhiking event coincided with an increase in mutation rates, due to the transient appearance of a strong mutator in the population. The spectrum of mgl mutations among mutator isolates was distinct and due to mutS. The mutator-associated periodic selection also resulted in mgl and fhuA polymorphism in the sweeping population. These examples of periodic selections maintained significant genotypic diversity even in a rapidly evolving culture, with no individual “winner clone” or genotype purging the population.

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