Full confocal projection of a larval central nervous system showing the expression of Gcm (GFP-green) and Diuretic Hormone 31 (DH31) (red). DAPI labels nuclei (blue). See Cattenoz et al. Image courtesy of Giuseppe Aiello, Pierre Cattenoz, and Angela Giangrande.

Check out the the February issue of GENETICS by looking at the highlights or the full table of contents!


This Month’s Centennial Articles

Salvador Luria and Max Delbruck on random mutation and fluctuation tests, pp. 367—368

Andrew Murray

Associate Editor Andrew W. Murray introduces Luria and Delbruck’s 1943 GENETICS Classic Mutations of bacteria from virus sensitivity to virus resistance. Their elegant statistical analysis established that mutations occur randomly over time, regardless of their effect on a cell’s survival and reproduction.

Hermann Muller on measuring mutation rates, pp. 369—370

Cristy Gelling

Assistant Editor Cristy Gelling introduces Hermann Muller’s 1928 GENETICS Classic, The measurement of gene mutation rate in Drosophila, its high variability, and its dependence upon temperature. This was the first demonstration that mutation rates could be altered by an external influence. Muller’s methods helped uncover crucial clues about the nature of mutation and was part of his Nobel prize-winning work that showed that X-rays increase mutation rates.

Pick your poisson: an educational primer for Luria and Delbruck’s Classic paper, pp. 371—375

Philip M. Meneely

In this Educational Primer Philip M. Meneely introduces the background and unpacks the arguments in Luria and Delbruck’s 1943 GENETICS Classic demonstrating that mutations occur at random with respect to selective pressure. The Primer also includes study questions for use in the classroom.

Human complex trait genetics in the 21st century, pp. 377—379

Peter M. Visscher

Peter M. Visscher “sticks his neck out” to make some predictions about human complex trait genetics in GENETICS’ second century. He argues that the relentless pace of technological innovation will cause a change in how science is conducted. Instead of the model-based hypothesis-testing science that dominated the last century, the next will be hypothesis-generating-discovery science that is driven by data.

RAD capture (Rapture): flexible and efficient sequence-based genotyping, pp. 389—400

Omar A. Ali, Sean M. O’Rourke, Stephen J. Amish, Mariah H. Meek, Gordon Luikart, Carson Jeffres, and Michael R. Miller

Massively parallel sequencing (MPS) has revolutionized genetics but sequencing large amounts of DNA across many individuals is often cost-prohibitive or unnecessary. This study presents a rapid and flexible method for distributing MPS data across individuals and genomic loci called Rapture (RAD Capture). This method combines the benefits of RAD sequencing and sequence capture. Rapture can process many individuals with minimal library preparation and sequencing costs, which makes genetic analysis more efficient for many applications.

Exploiting linkage disequilibrium for ultrahigh-dimensional genomewide data with an integrated statistical approach, pp. 411—426

Michelle Carlsen, Guifang Fu, Shaun Bushman, and Christopher Corcoran

Carlsen et al. present improved methods for analysis of genome-wide association studies. Currently, up to a million single-nucleotide polymorphisms (SNPs) can be feasibly generated within any given population, but there are often correlations among SNPs that cause truly causative loci to be confounded by correlated neighbors. Additionally, complex traits are often jointly affected by multiple genetic variants with small or moderate individual effects. The authors propose a novel statistical approach, DCRR, to detecting significant associations between large numbers of SNPs and phenotypes.

Differential masking of natural genetic variation by miR-9a in Drosophila, pp. 675—687

Justin J. Cassidy, Alexander J. Straughan, and Richard W. Carthew

Genetic variantion is rarely determinative for phenotypic traits, but instead has mainly probabilistic effects on outcome. The reasons are largely unknown but it has been suspected that active mechanisms may buffer the impact of genetic variation. Using artificial selection in Drosophila, Cassidy et al. find that the non-coding microRNA miR-9a is part of such a mechanism. Their results suggest that miR-9a molds genetic variation into a landscape in which variants’ impact is masked by miR-9a for some but not all traits.

A delicate balance between repair and replication factors regulates recombination between divergent DNA sequences in Saccharomyces cerevisiae, pp. 525—540

Ujani Chakraborty, Carolyn M. George, Amy M. Lyndaker, and Eric Alani

Homologous recombination between divergent, non-allelic DNA sequences can lead to deleterious genome rearrangements. To suppress single-strand annealing between divergent sequences, the Msh DNA mismatch recognition complex and Sgsl helicase bind to mismatches in heteroduplex DNA intermediates and trigger an unwinding mechanism known as heteroduplex rejection. Chaktraborty et al. show that Top3-Rmi1, a topoisomerase complex that interacts with Sgsl, is required for heteroduplex rejection. Msh6 overexpression significantly increased heteroduplex rejection due to a compromise in Msh2-Msh3 function required for 3′ tail clipping during single-strand annealing, This indicates that tail clipping is a critical regulatory step in the rejection vs. repair decision.

Genetic architectures of quantitative variation in RNA editing pathways, pp. 787—798

Tongjun Gu, Daniel M. Gatti, Anuj Srivastava, Elizabeth M. Snyder, Narayanan Raghupathy, Petr Simecek, Karen L. Svenson, Ivan Dotu, Jeffrey H. Chuang, Mark P Keller, Alan D. Attie, Robert E. Braun, and Gary A. Churchill

RNA editing involves post-transcriptional modification of mRNA nucleotide sequences. Gu et al. investigated the degree to which RNA editing is influenced by genetic variation in a genetically diverse mouse population. They found that variation in Apobecl influences global levels of C-to-U editing and that most A-to-I editing is influenced by local genetic variants that may alter the secondary structure of the RNA and hence alter the editing efficiency.

The role of recombination in evolutionary rescue, pp. 721—732

Hildegard Uecker and Joachim Hermisson

How likely is it that a population escapes extinction through adaptive evolution? The answer is of great relevance in conservation biology, and in the management of pesticide or drug resistance. By reshuffling the genome, recombination has two antagonistic effects on the probability of evolutionary rescue: while it generates favorable gene combinations, it also breaks them up. Analysis of a mathematical model reveals a complex dependence of rescue on recombination. Counterintuitively, rapid eradication of the wildtype can promote rescue in the presence of recombination.

An equation to predict the accuracy of genomic values by combining data from multiple traits, populations, or environments, pp. 799—823

Yvonne C. J. Wientjes, Piter Bijma, Roel F. Veerkamp, and Mario P L. Calus

Combining individuals from different populations is currently an important area of research for increasing the accuracy of genomic prediction, both for selecting the best animals and plants as well as for predicting the genetic risk of human diseases. In this paper, a deterministic equation is derived to predict the accuracy of genomic values when different populations are combined in the training population, for example from different breeds, lines, environments or genetic backgrounds, or populations measured for different traits. The equation can accurately predict the genomic prediction accuracy for these different scenarios.

Nucleosomes are essential for proper regulation of a multigated promoter in Saccharomyces cerevisiae, pp. 551—563

Robert M. Yarrington, Jenna M. Goodrum, and David J. Stillman

How does chromatin repress transcription in a complex promoter? The authors have shown that the yeast HO promoter contains multiple gates that must be opened in sequence for activation. The promoter carries SBF binding sites embedded within nucleosomes so that SBF binding requires help from an upstream promoter element. Here, Yarrington et al. modify the HO promoter so that the SBF sites are in a nucleosome free region, and showed that nucleosomes are required for a multigated promoter and its complex regulatory properties.

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