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1. Multiple genetic loci affect place learning and memory performance in Drosophila melanogaster

   https://doi.org/10.1111/gbb.12581  

   Williams‐Simon, Patricka A.; Posey, Christopher; Mitchell, Samuel; Ng'oma, Enoch; Mrkvicka, James A.; Zars, Troy; King, Elizabeth G. (May 2019, Genes, Brain and Behavior)

   Abstract Learning and memory are critical functions for all animals, giving individuals the ability to respond to changes in their environment. Within populations, individuals vary, however the mechanisms underlying this variation in performance are largely unknown. Thus, it remains to be determined what genetic factors cause an individual to have high learning ability and what factors determine how well an individual will remember what they have learned. To genetically dissect learning and memory performance, we used theDrosophilasynthetic population resource (DSPR), a multiparent mapping resource in the model systemDrosophila melanogaster, consisting of a large set of recombinant inbred lines (RILs) that naturally vary in these and other traits. Fruit flies can be trained in a “heat box” to learn to remain on one side of a chamber (place learning) and can remember this (place memory) over short timescales. Using this paradigm, we measured place learning and memory for ~49 000 individual flies from over 700 DSPR RILs. We identified 16 different loci across the genome that significantly affect place learning and/or memory performance, with 5 of these loci affecting both traits. To identify transcriptomic differences associated with performance, we performed RNA‐Seq on pooled samples of seven high performing and seven low performing RILs for both learning and memory and identified hundreds of genes with differences in expression in the two sets. Integrating our transcriptomic results with the mapping results allowed us to identify nine promising candidate genes, advancing our understanding of the genetic basis underlying natural variation in learning and memory performance. 

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2. Greenscreen: A simple method to remove artifactual signals and enrich for true peaks in genomic datasets including ChIP-seq data

   https://doi.org/10.1093/plcell/koac282  

   Klasfeld, Samantha; Roulé, Thomas; Wagner, Doris (September 2022, The Plant Cell)

   Abstract Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to identify factor binding to genomic DNA and chromatin modifications. ChIP-seq data analysis is affected by genomic regions that generate ultra-high artifactual signals. To remove these signals from ChIP-seq data, the Encyclopedia of DNA Elements (ENCODE) project developed comprehensive sets of regions defined by low mappability and ultra-high signals called blacklists for human, mouse (Mus musculus), nematode (Caenorhabditis elegans), and fruit fly (Drosophila melanogaster). However, blacklists are not currently available for many model and nonmodel species. Here, we describe an alternative approach for removing false-positive peaks called greenscreen. Greenscreen is easy to implement, requires few input samples, and uses analysis tools frequently employed for ChIP-seq. Greenscreen removes artifactual signals as effectively as blacklists in Arabidopsis thaliana and human ChIP-seq dataset while covering less of the genome and dramatically improves ChIP-seq peak calling and downstream analyses. Greenscreen filtering reveals true factor binding overlap and occupancy changes in different genetic backgrounds or tissues. Because it is effective with as few as two inputs, greenscreen is readily adaptable for use in any species or genome build. Although developed for ChIP-seq, greenscreen also identifies artifactual signals from other genomic datasets including Cleavage Under Targets and Release Using Nuclease. We present an improved ChIP-seq pipeline incorporating greenscreen that detects more true peaks than other methods. 

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3. Nebulous without white : annotated long-read genome assembly and CRISPR/Cas9 genome engineering in Drosophila nebulosa

   https://doi.org/10.1093/g3journal/jkac231  

   Sottolano, Christopher J.; Revaitis, Nicole T.; Geneva, Anthony J.; Yakoby, Nir; Arbeitman, ed., M. (September 2022, G3 Genes|Genomes|Genetics)

   Abstract The diversity among Drosophila species presents an opportunity to study the molecular mechanisms underlying the evolution of biological phenomena. A challenge to investigating these species is that, unlike the plethora of molecular and genetics tools available for D. melanogaster research, many other species do not have sequenced genomes; a requirement for employing these tools. Selecting transgenic flies through white (w) complementation has been commonly practiced in numerous Drosophila species. While tolerated, the disruption of w is associated with impaired vision, among other effects in D. melanogaster. The D. nebulosa fly has a unique mating behavior which requires vision, and is thus unable to successfully mate in dark conditions. Here, we hypothesized that the disruption of w will impede mating success. As a first step, using PacBio long-read sequencing, we assembled a high-quality annotated genome of D. nebulosa. Using these data, we employed CRISPR/Cas9 to successfully disrupt the w gene. As expected, D. nebulosa males null for w did not court females, unlike several other mutant strains of Drosophila species whose w gene has been disrupted. In the absence of mating, no females became homozygous null for w. We conclude that gene disruption via CRISPR/Cas9 genome engineering is a successful tool in D. nebulosa, and that the w gene is necessary for mating. Thus, an alternative selectable marker unrelated to vision is desirable. 

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4. P ool P arty 2: An integrated pipeline for analysing pooled or indexed low‐coverage whole‐genome sequencing data to discover the genetic basis of diversity

   https://doi.org/10.1111/1755-0998.13888  

   Willis, Stuart; Micheletti, Steven; Andrews, Kimberly R.; Narum, Shawn (November 2023, Molecular Ecology Resources)

   Abstract Whole‐genome sequencing data allow survey of variation from across the genome, reducing the constraint of balancing genome sub‐sampling with estimating recombination rates and linkage between sampled markers and target loci. As sequencing costs decrease, low‐coverage whole‐genome sequencing of pooled or indexed‐individual samples is commonly utilized to identify loci associated with phenotypes or environmental axes in non‐model organisms. There are, however, relatively few publicly available bioinformatic pipelines designed explicitly to analyse these types of data, and fewer still that process the raw sequencing data, provide useful metrics of quality control and then execute analyses. Here, we present an updated version of a bioinformatics pipeline calledPoolParty2that can effectively handle either pooled or indexed DNA samples and includes new features to improve computational efficiency. Using simulated data, we demonstrate the ability of our pipeline to recover segregating variants, estimate their allele frequencies accurately, and identify genomic regions harbouring loci under selection. Based on the simulated data set, we benchmark the efficacy of our pipeline with another bioinformatic suite,angsd, and illustrate the compatibility and complementarity of these suites usingangsdto generate genotype likelihoods as input for identifying linkage outlier regions using alignment files and variants provided byPoolParty2. Finally, we apply our updated pipeline to an empirical dataset of low‐coverage whole genomic data from population samples of Columbia River steelhead trout (Oncorhynchus mykiss), results from which demonstrate the genomic impacts of decades of artificial selection in a prominent hatchery stock. Thus, we not only demonstrate the utility ofPoolParty2for genomic studies that combine sequencing data from multiple individuals, but also illustrate how it compliments other bioinformatics resources such asangsd. 

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5. Rapid Cis–Trans Coevolution Driven by a Novel Gene Retroposed from a Eukaryotic Conserved CCR4–NOT Component in Drosophila

   https://doi.org/10.3390/genes13010057  

   Krinsky, Benjamin H.; Arthur, Robert K.; Xia, Shengqian; Sosa, Dylan; Arsala, Deanna; White, Kevin P.; Long, Manyuan (January 2022, Genes)

   Young, or newly evolved, genes arise ubiquitously across the tree of life, and they can rapidly acquire novel functions that influence a diverse array of biological processes. Previous work identified a young regulatory duplicate gene in Drosophila, Zeus that unexpectedly diverged rapidly from its parent, Caf40, an extremely conserved component in the CCR4–NOT machinery in post-transcriptional and post-translational regulation of eukaryotic cells, and took on roles in the male reproductive system. This neofunctionalization was accompanied by differential binding of the Zeus protein to loci throughout the Drosophila melanogaster genome. However, the way in which new DNA-binding proteins acquire and coevolve with their targets in the genome is not understood. Here, by comparing Zeus ChIP-Seq data from D. melanogaster and D. simulans to the ancestral Caf40 binding events from D. yakuba, a species that diverged before the duplication event, we found a dynamic pattern in which Zeus binding rapidly coevolved with a previously unknown DNA motif, which we term Caf40 and Zeus-Associated Motif (CAZAM), under the influence of positive selection. Interestingly, while both copies of Zeus acquired targets at male-biased and testis-specific genes, D. melanogaster and D. simulans proteins have specialized binding on different chromosomes, a pattern echoed in the evolution of the associated motif. Using CRISPR-Cas9-mediated gene knockout of Zeus and RNA-Seq, we found that Zeus regulated the expression of 661 differentially expressed genes (DEGs). Our results suggest that the evolution of young regulatory genes can be coupled to substantial rewiring of the transcriptional networks into which they integrate, even over short evolutionary timescales. Our results thus uncover dynamic genome-wide evolutionary processes associated with new genes. 

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