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While prokaryotic pan-genomes have been shown to contain many more genes than any individual organism, the prevalence and functional significance of differentially present genes in eukaryotes remains poorly understood. Whole-genome de novo assembly and annotation of 54 lines of the grass Brachypodium distachyon yield a pan-genome containing nearly twice the number of genes found in any individual genome. Genes present in all lines are enriched for essential biological functions, while genes present in only some lines are enriched for conditionally beneficial functions (e.g., defense and development), display faster evolutionary rates, lie closer to transposable elements and are less likely to be syntenic with orthologous genes in other grasses. Our data suggest that differentially present genes contribute substantially to phenotypic variation within a eukaryote species, these genes have a major influence in population genetics, and transposable elements play a key role in pan-genome evolution. The role of differential gene content in the evolution and function of eukaryotic genomes remains poorly explored. Here the authors assemble and annotate the Brachypodium distachyon pan-genome consisting of 54 diverse lines and reveal the differential present genes as a major driver of phenotypic variation.

The microbial communities that inhabit the distal gut of humans and other mammals exhibit large inter-individual variation. While host genetics is a known factor that influences gut microbiota composition, the mechanisms underlying this variation remain largely unknown. Bile acids (BAs) are hormones that are produced by the host and chemically modified by gut bacteria. BAs serve as environmental cues and nutrients to microbes, but they can also have antibacterial effects. We hypothesized that host genetic variation in BA metabolism and homeostasis influence gut microbiota composition. To address this, we used the Diversity Outbred (DO) stock, a population of genetically distinct mice derived from eight founder strains. We characterized the fecal microbiota composition and plasma and cecal BA profiles from 400 DO mice maintained on a high-fat high-sucrose diet for ~22 weeks. Using quantitative trait locus (QTL) analysis, we identified several genomic regions associated with variations in both bacterial and BA profiles. Notably, we found overlapping QTL for Turicibacter sp. and plasma cholic acid, which mapped to a locus containing the gene for the ileal bile acid transporter, Slc10a2. Mediation analysis and subsequent follow-up validation experiments suggest that differences in Slc10a2 gene expression associated with the different strains influences levels of both traits and revealed novel interactions between Turicibacter and BAs. This work illustrates how systems genetics can be utilized to generate testable hypotheses and provide insight into host-microbe interactions.

Purpose Establishing links between Mendelian phenotypes and genes enables the proper interpretation of variants therein. Autozygome, a rich source of homozygous variants, has been successfully utilized for the high throughput identification of novel autosomal recessive disease genes. Here, we highlight the utility of the autozygome for the high throughput confirmation of previously published tentative links to diseases. Methods Autozygome and exome analysis of patients with suspected Mendelian phenotypes. All variants were classified according to the American College of Medical Genetics and Genomics guidelines. Results We highlight 30 published candidate genes ( ACTL6B , ADAM22 , AGTPBP1 , APC , C12orf4 , C3orf17 (NEPRO) , CENPF , CNPY3 , COL27A1 , DMBX1 , FUT8 , GOLGA2 , KIAA0556 , LENG8 , MCIDAS , MTMR9 , MYH11 , QRSL1 , RUBCN , SLC25A42 , SLC9A1 , TBXT , TFG , THUMPD1 , TRAF3IP2 , UFC1 , UFM1 , WDR81 , XRCC2 , ZAK ) in which we identified homozygous likely deleterious variants in patients with compatible phenotypes. We also identified homozygous likely deleterious variants in 18 published candidate genes ( ABCA2 , ARL6IP1 , ATP8A2 , CDK9 , CNKSR1 , DGAT1 , DMXL2 , GEMIN4 , HCN2 , HCRT , MYO9A , PARS2 , PLOD3 , PREPL , SCLT1 , STX3 , TXNRD2 , WIPI2 ) although the associated phenotypes are sufficiently different from the original reports that they represent phenotypic expansion or potentially distinct allelic disorders. Conclusions Our results should facilitate the timely relabeling of these candidate disease genes in relevant databases to improve the yield of clinical genomic sequencing.

Adverse cardiac remodeling after myocardial infarction (MI) causes structural and functional changes in the heart leading to heart failure. The initial post-MI pro-inflammatory response followed by reparative or anti-inflammatory response is essential for minimizing the myocardial damage, healing, and scar formation. Bone marrow–derived macrophages (BMDMs) are recruited to the injured myocardium and are essential for cardiac repair as they can adopt both pro-inflammatory or reparative phenotypes to modulate inflammatory and reparative responses, respectively. Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) are the key mediators of the Hippo signaling pathway and are essential for cardiac regeneration and repair. However, their functions in macrophage polarization and post-MI inflammation, remodeling, and healing are not well established. Here, we demonstrate that expression of YAP and TAZ is increased in macrophages undergoing pro-inflammatory or reparative phenotype changes. Genetic deletion of YAP/TAZ leads to impaired pro-inflammatory and enhanced reparative response. Consistently, YAP activation enhanced pro-inflammatory and impaired reparative response. We show that YAP/TAZ promote pro-inflammatory response by increasing interleukin 6 ( IL6 ) expression and impede reparative response by decreasing Arginase-I ( Arg1 ) expression through interaction with the histone deacetylase 3 (HDAC3)-nuclear receptor corepressor 1 (NCoR1) repressor complex. These changes in macrophages polarization due to YAP/TAZ deletion results in reduced fibrosis, hypertrophy, and increased angiogenesis, leading to improved cardiac function after MI. Also, YAP activation augmented MI-induced cardiac fibrosis and remodeling. In summary, we identify YAP/TAZ as important regulators of macrophage-mediated pro-inflammatory or reparative responses post-MI.

Variations in the number of nucleotides within an SSR in a coding sequence may cause a frameshift mutation that creates a premature stop codon and a truncated product (OFF) or, conversely, may restore the reading frame and production of the gene product (ON). [...]phase variation can be achieved by shuffling alleles of the same gene between an expressed locus and a distal, silent locus. Consistent with this result, phase-locked OFF mutants lacking fimbriae are attenuated in disease models of urinary tract infection [12, 13]. Some DNA methyltransferases, enzymes that methylate specific nucleotide motifs, are subject to phase variation, resulting in a population of bacteria with different methylation patterns. Because methylation can influence gene expression, methyltransferase phase variation can influence the transcription of multiple genes simultaneously.

CRISPR-Cas9 technologies have transformed genome-editing of experimental organisms and have immense therapeutic potential. Despite significant advances in our understanding of the CRISPR-Cas9 system, concerns remain over the potential for off-target effects. Recent studies have addressed these concerns using whole-genome sequencing (WGS) of gene-edited embryos or animals to search for de novo mutations (DNMs), which may represent candidate changes introduced by poor editing fidelity. Critically, these studies used strain-matched, but not pedigree-matched controls and thus were unable to reliably distinguish generational or colony-related differences from true DNMs. Here we used a trio design and whole genome sequenced 8 parents and 19 embryos, where 10 of the embryos were mutagenised with well-characterised gRNAs targeting the coat colour Tyrosinase (Tyr) locus. Detailed analyses of these whole genome data allowed us to conclude that if CRISPR mutagenesis were causing SNV or indel off-target mutations in treated embryos, then the number of these mutations is not statistically distinguishable from the background rate of DNMs occurring due to other processes.

Purpose Defects in the cohesin pathway are associated with cohesinopathies, notably Cornelia de Lange syndrome (CdLS). We aimed to delineate pathogenic variants in known and candidate cohesinopathy genes from a clinical exome perspective. Methods We retrospectively studied patients referred for clinical exome sequencing (CES, N  = 10,698). Patients with causative variants in novel or recently described cohesinopathy genes were enrolled for phenotypic characterization. Results Pathogenic or likely pathogenic single-nucleotide and insertion/deletion variants (SNVs/indels) were identified in established disease genes including NIPBL ( N  = 5), SMC1A ( N  = 14), SMC3 ( N  = 4), RAD21 ( N  = 2), and HDAC8 ( N  = 8). The phenotypes in this genetically defined cohort skew towards the mild end of CdLS spectrum as compared with phenotype-driven cohorts. Candidate or recently reported cohesinopathy genes were supported by de novo SNVs/indels in STAG1 ( N  = 3), STAG2 ( N  = 5), PDS5A ( N  = 1), and WAPL ( N  = 1), and one inherited SNV in PDS5A . We also identified copy-number deletions affecting STAG1 (two de novo, one of unknown inheritance) and STAG2 (one of unknown inheritance). Patients with STAG1 and STAG2 variants presented with overlapping features yet without characteristic facial features of CdLS. Conclusion CES effectively identified disease-causing alleles at the mild end of the cohensinopathy spectrum and enabled characterization of candidate disease genes.

Body size is a quantitative trait that is closely associated to fitness and under the control of both genetic and environmental factors. While developmental plasticity for this and other traits is heritable and under selection, little is known about the genetic basis for variation in plasticity that can provide the raw material for its evolution. We quantified genetic variation for body size plasticity in Drosophila melanogaster by measuring thorax and abdomen length of females reared at two temperatures from a panel representing naturally segregating alleles, the Drosophila Genetic Reference Panel (DGRP). We found variation between genotypes for the levels and direction of thermal plasticity in size of both body parts. We then used a Genome-Wide Association Study (GWAS) approach to unravel the genetic basis of inter-genotype variation in body size plasticity, and used different approaches to validate selected QTLs and to explore potential pleiotropic effects. We found mostly \"private QTLs\", with little overlap between the candidate loci underlying variation in plasticity for thorax versus abdomen size, for different properties of the plastic response, and for size versus size plasticity. We also found that the putative functions of plasticity QTLs were diverse and that alleles for higher plasticity were found at lower frequencies in the target population. Importantly, a number of our plasticity QTLs have been targets of selection in other populations. Our data sheds light onto the genetic basis of inter-genotype variation in size plasticity that is necessary for its evolution.

In bacteria and other microorganisms, the cells within a population often show extreme phenotypic variation. Different species use different mechanisms to determine how distinct phenotypes are allocated between individuals, including coordinated, random, and genetic determination. However, it is not clear if this diversity in mechanisms is adaptive—arising because different mechanisms are favoured in different environments—or is merely the result of non-adaptive artifacts of evolution. We use theoretical models to analyse the relative advantages of the two dominant mechanisms to divide labour between reproductives and helpers in microorganisms. We show that coordinated specialisation is more likely to evolve over random specialisation in well-mixed groups when: (i) social groups are small; (ii) helping is more “essential”; and (iii) there is a low metabolic cost to coordination. We find analogous results when we allow for spatial structure with a more detailed model of cellular filaments. More generally, this work shows how diversity in the mechanisms to produce phenotypic heterogeneity could have arisen as adaptations to different environments. In microorganisms, the cells within a population often show extreme phenotypic variation with different mechanisms used to determine how distinct phenotypes are allocated. This study uses theoretical models to examine the relative advantages of the two dominant mechanisms, coordinated and random determination, in dividing labour between reproductives and helpers in microorganisms.

Detecting genetic variants associated with the variance of complex traits, that is, variance quantitative trait loci (vQTLs), can provide crucial insights into the interplay between genes and environments and how they jointly shape human phenotypes in the population. We propose a quantile integral linear model (QUAIL) to estimate genetic effects on trait variability. Through extensive simulations and analyses of real data, we demonstrate that QUAIL provides computationally efficient and statistically powerful vQTL mapping that is robust to non-Gaussian phenotypes and confounding effects on phenotypic variability. Applied to UK Biobank (n = 375,791), QUAIL identified 11 vQTLs for body mass index (BMI) that have not been previously reported. Top vQTL findings showed substantial enrichment for interactions with physical activities and sedentary behavior. Furthermore, variance polygenic scores (vPGSs) based on QUAIL effect estimates showed superior predictive performance on both populationlevel and within-individual BMI variability compared to existing approaches. Overall, QUAIL is a unified framework to quantify genetic effects on the phenotypic variability at both single-variant and vPGS levels. It addresses critical limitations in existing approaches and may have broad applications in future gene–environment interaction studies.