October GENETICS Highlights
Rhythmic behavior is controlled by the SRm160 splicing factor in Drosophila melanogaster, pp. 593–607
Esteban J. Beckwith, Carlos E. Hernando, Sofía Polcowñuk, Agustina P. Bertolin, Estefania Mancini, M. Fernanda Ceriani, and Marcelo J. Yanovsky
Animals have evolved neural circuits that allow them to generate adaptive behaviors to their natural environment. Specific neuronal clusters depend on biological timekeeping systems that are collectively known as circadian clocks. These clocks rely on complex biochemical events that ensure rhythmicity and guarantee an accurate period. In this study, Beckwith et al. describe a new component of the clockwork machinery in the fruit fly, showing that this new clock component impacts the oscillation of the pacemaker clock, thus affecting its main clock outputs.
Accumulation of deleterious mutations during bacterial range expansions, pp. 669–684
Lars Bosshard, Isabelle Dupanloup, Olivier Tenaillon, Rémy Bruggmann, Martin Ackermann, Stephan Peischl, and Laurent Excoffier
Recent theoretical work suggested that deleterious mutations could accumulate during the range expansion of a species, negatively affecting its fitness. Bosshard et al. tested this prediction using an experimental evolution approach over 1650 generations. The fitness of high mutation rate lines expanding on agar decreased when measured in several environments, unlike that of low mutation rate lines expanding on agar or of well-mixed high-mutation rate lines. These results imply that successfully expanding species accumulate deleterious mutations that impact their fitness, potentially limiting their ability to adapt to new environments.
Stress-induced sleep after exposure to ultraviolet light is promoted by p53 in Caenorhabditis elegans, pp. 571–582
Hilary K. DeBardeleben, Lindsey E. Lopes, Mark P. Nessel, and David M. Raizen
The conservation of sleep among animals suggests that this behavior serves an important adaptive function; however, a unifying function for and genetic regulation of sleep behavior is still unknown. Stress-induced sleep in the model organism Caenorhabditis elegans gives new insight into function and regulation of sleep at the cellular level. Here, DeBardeleben et al. expand upon previous work by introducing a new type of stress that induces sleep, suggesting a broader function for sleep than previously thought. They also report a novel function for the highly conserved P53 family of tumor suppressors in the regulation of stress induced sleep.
Silencing of repetitive DNA is controlled by a member of an unusual Caenorhabditis elegans gene family, pp. 529–545
Eduardo Leyva-Daz, Nikolaos Stefanakis, Inés Carrera, Lori Glenwinkel, Guoqiang Wang, Monica Driscoll, and Oliver Hobert
Levya-Díaz et al. identify a Caenorhabditis elegans gene involved in transgene silencing and RNA interference. The gene is a member of a divergent gene family that specifically expanded in the C. elegans genome.
Selection constrains high rates of tandem repetitive DNA mutation in Daphnia pulex, pp. 697–710
Jullien M. Flynn, Ian Caldas, Melania E. Cristescu, and Andrew G. Clark
Tandemly repeated DNA is known to be highly abundant and highly divergent between species, but the genome-wide mutation rates in these mostly unmappable repeats have never been directly tested. Here, Flynn et al. use whole genome sequencing of Daphnia pulex mutation accumulation lines and a competitive population to estimate the mutation rates and the influence of selection on tandem repeats. They found extremely high rates of expansions and contraction in the MA lines, which was reduced in the population that experienced selection.
Incorporating gene annotation into genomic prediction of complex phenotypes, pp. 489–501
Ning Gao, Johannes W. R. Martini, Zhe Zhang, Xiaolong Yuan, Hao Zhang, Henner Simianer, and Jiaqi Li
Gao et al. propose several approaches to incorporate gene annotation into genomic prediction and evaluate these new methods on populations of mouse, Drosophila, and rice. Their results show that, for many traits under consideration, annotation-based models outperform SNP and haplotype models without gene annotation. Using gene annotation to define haploblocks leads to comparable or better predictions, and modeling gene interaction effects additionally improves prediction ability. This is the first work which incorporates gene annotation and epistatic interactions into haplotype-based prediction approaches.
Selection during maize domestication targeted a gene network controlling plant and inflorescence architecture, pp. 755–765
Anthony J. Studer, Huai Wang, and John F. Doebley
Selection during evolution, whether natural or artificial, is evidenced through the phenotype. For complex phenotypes like plant and inflorescence architecture, the underlying genetic foundation is composed of a network of interacting genes, rather than single genes that act independently. Here, Studer et al. begin to define the genetic regulatory network to which the maize domestication gene, teosinte branched1 (tb1), belongs. Multiple members of the tb1 network appear to have been the targets of selection during maize domestication. Understanding the regulatory hierarchies controlling traits is central to understanding how new morphologies evolve.
Multi-population genomic relationships for estimating current genetic variances within and genetic correlations between populations, pp. 503–515
Yvonne C. J. Wientjes, Piter Bijma, Jérémie Vandenplas, and Mario P. L. Calus
Relationships between individuals are important to estimate genetic variances within a population and covariances between populations. Here, Wientjes et al. define and validate the multipopulation genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genetic correlation between populations is an important parameter in human, animal, and plant research and helps in understanding the genetic architecture and evolution of complex traits. It also provides information about the potential to combine information across populations for genomic prediction.