The experimental evolution of laboratory populations of microbes provides an opportunity to observe the evolutionary dynamics of adaptation in real time. Until very recently, however, such studies have been limited by our inability to systematically find mutations in evolved organisms. We overcome this limitation by using a variety of DNA microarray-based techniques to characterize genetic changes—including point mutations, structural changes, and insertion variation—that resulted from the experimental adaptation of 24 haploid and diploid cultures of Saccharomyces cerevisiae to growth in either glucose, sulfate, or phosphate-limited chemostats for ∼200 generations. We identified frequent genomic amplifications and rearrangements as well as novel retrotransposition events associated with adaptation. Global nucleotide variation detection in ten clonal isolates identified 32 point mutations. On the basis of mutation frequencies, we infer that these mutations and the subsequent dynamics of adaptation are determined by the batch phase of growth prior to initiation of the continuous phase in the chemostat. We relate these genotypic changes to phenotypic outcomes, namely global patterns of gene expression, and to increases in fitness by 5–50%. We found that the spectrum of available mutations in glucose- or phosphate-limited environments combined with the batch phase population dynamics early in our experiments allowed several distinct genotypic and phenotypic evolutionary pathways in response to these nutrient limitations. By contrast, sulfate-limited populations were much more constrained in both genotypic and phenotypic outcomes. Thus, the reproducibility of evolution varies with specific selective pressures, reflecting the constraints inherent in the system-level organization of metabolic processes in the cell. We were able to relate some of the observed adaptive mutations (e.g., transporter gene amplifications) to known features of the relevant metabolic pathways, but many of the mutations pointed to genes not previously associated with the relevant physiology. Thus, in addition to answering basic mechanistic questions about evolutionary mechanisms, our work suggests that experimental evolution can also shed light on the function and regulation of individual metabolic pathways.

Hybridization is often considered maladaptive, but sometimes hybrids can invade new ecological niches and adapt to novel or stressful environments better than their parents. The genomic changes that occur following hybridization that facilitate genome resolution and/or adaptation are not well understood. Here, we examine hybrid genome evolution using experimental evolution of de novo interspecific hybrid yeast Saccharomyces cerevisiae × Saccharomyces uvarum and their parentals. We evolved these strains in nutrient-limited conditions for hundreds of generations and sequenced the resulting cultures identifying numerous point mutations, copy number changes, and loss of heterozygosity (LOH) events, including species-biased amplification of nutrient transporters. We focused on a particularly interesting example, in which we saw repeated LOH at the high-affinity phosphate transporter gene PHO84 in both intra- and interspecific hybrids. Using allele replacement methods, we tested the fitness of different alleles in hybrid and S. cerevisiae strain backgrounds and found that the LOH is indeed the result of selection on one allele over the other in both S. cerevisiae and the hybrids. This is an example where hybrid genome resolution is driven by positive selection on existing heterozygosity and demonstrates that even infrequent outcrossing may have lasting impacts on adaptation.

Novel therapeutics are required for improving the management of chronic inflammatory diseases. Aptamers are single-stranded RNA or DNA molecules that have recently shown utility in a clinical setting, as they can specifically neutralize biomedically relevant proteins, particularly cell surface and extracellular proteins. The nuclear chromatin protein DEK is a secreted chemoattractant that is abundant in the synovia of patients with juvenile idiopathic arthritis (JIA). Here, we show that DEK is crucial to the development of arthritis in mouse models, thus making it an appropriate target for aptamer-based therapy. Genetic depletion of DEK or treatment with DEK-targeted aptamers significantly reduces joint inflammation in vivo and greatly impairs the ability of neutrophils to form neutrophil extracellular traps (NETs). DEK is detected in spontaneously forming NETs from JIA patient synovial neutrophils, and DEK-targeted aptamers reduce NET formation. DEK is thus key to joint inflammation, and anti-DEK aptamers hold promise for the treatment of JIA and other types of arthritis.

We demonstrate a new method, microarray-assisted bulk segregant analysis, for mapping traits in yeast by genotyping pooled segregants. We apply a probabilistic model to the progeny of a single cross and as little as two microarray hybridizations to reliably map an auxotrophic marker, a Mendelian trait, and a major-effect quantitative trait locus. M APPING the genes responsible for traits remains one of the most basic goals of genetics. There are several techniques available for reaching this goal, especially in model organisms such as the yeast Saccharomyces cerevisiae. The dense and well-characterized genetic map of S. cerevisiae supports traditional tetrad analysis, which is still widely used in spite of its requirements for time-and labor-intensive crosses and dissections. More recently developed genomics techniques take advantage of parallel genotyping of single feature polymorphisms (SFPs) and other small differences between two strain backgrounds (Winzeler et al. 1998(Winzeler et al. , 1999(Winzeler et al. , 2003Brem et al. 2002;Steinmetz et al. 2002;Deutschbauer and Davis 2005). Other approaches use the strains created by the yeast deletion project as a dense collection of genetic markers that can be crossed in parallel to a query strain ( Jorgensen et al. 2002). Finally, a new approach looks for mutations directly by hybridizing DNA from a strain of interest to a reference sequence microarray (Gresham et al. 2006).All of these approaches have limitations that reduce their value as routinely applied methods for mapping suppressors or other mutations. Most highly parallel methods are still resource intensive, requiring 10 or more array-typed segregants. Mapping strategies that use the yeast deletion collection are appropriate only for limited classes of phenotypes and are tedious and timeconsuming without substantial robotic automation. Methods that find DNA sequence changes directly are unable to link these changes to particular phenotypes without extensive follow-up work.Here we describe a microarray-based methodmicroarray-assisted bulk segregant analysis-that applies a highly parallel genotyping strategy to mapping genes in pooled populations of yeast. Bulk segregant analysis measures the variation present in pools of segregants that have been sorted according to phenotype and uses the correlation between these measurements and the pool phenotype to assign a likely map location. This is an improvement over methods that require individual genotyping, as it simultaneously measures the average genotype of progeny with a given phenotype. The approach of bulk segregant analysis was first developed (Michelmore et al. 1991) and adapted for microarraybased genotyping (Borevitz et al. 2003;Hazen et al. 2005) in plants. We have adapted the method for use in yeast and have also developed an analytical model that takes advantage of the linkage that is expected to occur between loci at similar map locations. Incorporating this cosegregation into the mapping model greatly improves the accuracy of the method a...

Oncogene amplification, a major driver of cancer pathogenicity, is often mediated through focal amplification of genomic segments. Recent results implicate extrachromosomal DNA (ecDNA) as the primary driver of focal copy number amplification (fCNA)-enabling gene amplification, rapid tumor evolution, and the rewiring of regulatory circuitry. Resolving an fCNA's structure is a first step in deciphering the mechanisms of its genesis and the fCNA's subsequent biological consequences. We introduce a computational method, AmpliconReconstructor (AR), for integrating optical mapping (OM) of long DNA fragments (>150 kb) with next-generation sequencing (NGS) to resolve fCNAs at single-nucleotide resolution. AR uses an NGS-derived breakpoint graph alongside OM scaffolds to produce high-fidelity reconstructions. After validating its performance through multiple simulation strategies, AR reconstructed fCNAs in seven cancer cell lines to reveal the complex architecture of ecDNA, a breakage-fusion-bridge and other complex rearrangements. By reconstructing the rearrangement signatures associated with an fCNA's generative mechanism, AR enables a more thorough understanding of the origins of fCNAs.

Edited by Manuel SantosKeywords: tRNA transcription tRNA processing tRNA modification Nucleolus tRNA nuclear export tRNA retrograde movement tRNA turnover a b s t r a c t This discussion focuses on the cellular dynamics of tRNA transcription, processing, and turnover. Early tRNA biosynthesis steps are shared among most tRNAs, while later ones are often individualized for specific tRNAs. In yeast, tRNA transcription and early processing occur coordinately in the nucleolus, requiring topological arrangement of 300 tRNA genes and early processing enzymes to this site; later processing events occur in the nucleoplasm or cytoplasm. tRNA nuclear export requires multiple exporters which function in parallel and the export process is coupled with other cellular events. Nuclear-cytoplasmic tRNA subcellular movement is not unidirectional as a retrograde pathway delivers mature cytoplasmic tRNAs to the nucleus. Despite the long half-lives, there are multiple pathways to turnover damaged tRNAs or normal tRNAs upon cellular stress.

Significance This study provides new insight into the requirements for observed silencing of RNA polymerase II transcription near tRNA genes. Mod5 is a conserved tRNA modification enzyme found in both the nucleus and cytoplasm, although it only modifies tRNAs in the cytoplasm. Mod5 is required for silencing near tRNA genes, and it is bound to both nuclear tRNA gene complexes and nuclear pre-tRNA transcripts. Possible mechanisms for this form of RNA-mediated transcriptional silencing are discussed.

Evolutionary outcomes depend not only on the selective forces acting upon a species, but also on the genetic background. However, large timescales and uncertain historical selection pressures can make it difficult to discern such important background differences between species. Experimental evolution is one tool to compare evolutionary potential of known genotypes in a controlled environment. Here we utilized a highly reproducible evolutionary adaptation in Saccharomyces cerevisiae to investigate whether experimental evolution of other yeast species would select for similar adaptive mutations. We evolved populations of S. cerevisiae, S. paradoxus, S. mikatae, S. uvarum, and interspecific hybrids between S. uvarum and S. cerevisiae for ~200–500 generations in sulfate-limited continuous culture. Wild-type S. cerevisiae cultures invariably amplify the high affinity sulfate transporter gene, SUL1. However, while amplification of the SUL1 locus was detected in S. paradoxus and S. mikatae populations, S. uvarum cultures instead selected for amplification of the paralog, SUL2. We measured the relative fitness of strains bearing deletions and amplifications of both SUL genes from different species, confirming that, converse to S. cerevisiae, S. uvarum SUL2 contributes more to fitness in sulfate limitation than S. uvarum SUL1. By measuring the fitness and gene expression of chimeric promoter-ORF constructs, we were able to delineate the cause of this differential fitness effect primarily to the promoter of S. uvarum SUL1. Our data show evidence of differential sub-functionalization among the sulfate transporters across Saccharomyces species through recent changes in noncoding sequence. Furthermore, these results show a clear example of how such background differences due to paralog divergence can drive changes in genome evolution.