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Volume 226, Issue 4, April 2024
Call for Papers
Opportunities and challenges for Genomic Data Analyses in Biobanks: a call for papers
Brief Investigation
Genome Integrity and Transmission
Effects of parental age and polymer composition on short tandem repeat de novo mutation rates
Maternal mitochondrial function affects paternal mitochondrial inheritance in Drosophila
Investigation
Cellular Genetics
A missense SNP in the tumor suppressor SETD2 reduces H3K36me3 and mitotic spindle integrity in Drosophila
A novel mutation in the tumor suppressor SETD2 identified from renal cell carcinoma patients compromises epigenetic modification and mitotic fidelity when introduced in Drosophila, hinting at clinical relevance.
Premature endocycling of Drosophila follicle cells causes pleiotropic defects in oogenesis
Role of the San1 ubiquitin ligase in the heat stress-induced degradation of nonnative Nup1 in the nuclear pore complex
Experimental Technologies and Resources
High-throughput genetic manipulation of multicellular organisms using a machine-vision guided embryonic microinjection robot
Alegria et al. present a machine vision (MV) guided generalized robot that fully automates the process of microinjection in fruit fly (Drosophila melanogaster) and zebrafish (Danio rerio) embryos. The robot performs transgenesis with proficiency comparable to highly skilled human practitioners while achieving up to 4x increases in microinjection throughput in Drosophila. The automated microinjection robot was utilized to microinject pools of over 20,000 uniquely barcoded plasmids into 1,713 embryos in two days to rapidly generate more than 400 unique transgenic Drosophila lines.
Gene Expression
A fluorescent assay for cryptic transcription in Saccharomyces cerevisiae reveals novel insights into factors that stabilize chromatin structure on newly replicated DNA
Genetics of Complex Traits
Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping
Genetic architecture of trait variance in craniofacial morphology
In this work Andrade et al. study the genetic architecture of trait variance and evaluate an old hypothesis stating that heterozygotes should have lower trait variances then homozygotes. The authors observe that heterozygotes do not have lower trait variance overall. The main finding is that the different ways in which loci can interact is a better model to explain the genetic architecture of trait variance, not the level of heterozygozity.
Genome Integrity and Transmission
Histone variant H2A.Z and linker histone H1 influence chromosome condensation in Saccharomyces cerevisiae
Molecular Genetics of Development
To be or not to be: orb, the fusome and oocyte specification in Drosophila
Population and Evolutionary Genetics
Distinct genomic contexts predict gene presence–absence variation in different pathotypes of Magnaporthe oryzae
Shared evolutionary processes shape landscapes of genomic variation in the great apes
Counting the genetic ancestors from source populations in members of an admixed population
Enrichment of hard sweeps on the X chromosome compared to autosomes in six Drosophila species
Interpreting generative adversarial networks to infer natural selection from genetic data
In evolutionary biology we have used synthetic data for decades, through custom simulations from evolutionary models. In this work Riley et al. focus on a generative adversarial network (GAN) method for creating realistic simulated data, inferring demography, and identifying genomic regions under selection. The neural network is first trained with fast neutral simulations, then fine-tuned with minimal simulations of selection. The result allows the authors to predict selected regions and interpret the network based on correlation patterns with known summary statistics.
Statistical Genetics and Genomics
An expression-directed linear mixed model discovering low-effect genetic variants
Li et al. propose a new statistical method detecting low-effect genetic variants by adjusting the linear mixed models using weights learned from gene expressions.