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Background The ganglionic eminences (GE) are fetal-specific structures that give rise to gamma-aminobutyric acid (GABA)- and acetylcholine-releasing neurons of the forebrain. Given the evidence for GABAergic, cholinergic, and neurodevelopmental disturbances in schizophrenia, we tested the potential involvement of GE neuron development in mediating genetic risk for the condition. Study Design We combined data from a recent large-scale genome-wide association study of schizophrenia with single-cell RNA sequencing data from the human GE to test the enrichment of schizophrenia risk variation in genes with high expression specificity for developing GE cell populations. We additionally performed the single nuclei Assay for Transposase-Accessible Chromatin with Sequencing (snATAC-Seq) to map potential regulatory genomic regions operating in individual cell populations of the human GE, using these to test for enrichment of schizophrenia common genetic variant liability and to functionally annotate non-coding variants-associated with the disorder. Study Results Schizophrenia common variant liability was enriched in genes with high expression specificity for developing neuron populations that are predicted to form dopamine D1 and D2 receptor-expressing GABAergic medium spiny neurons of the striatum, cortical somatostatin-positive GABAergic interneurons, calretinin-positive GABAergic neurons, and cholinergic neurons. Consistent with these findings, schizophrenia genetic risk was concentrated in predicted regulatory genomic sequence mapped in developing neuronal populations of the GE. Conclusions Our study implicates prenatal development of specific populations of GABAergic and cholinergic neurons in later susceptibility to schizophrenia, and provides a map of predicted regulatory genomic elements operating in cells of the GE. [ABSTRACT FROM AUTHOR]

Background and Hypothesis Schizophrenia (SCZ) and anorexia nervosa (AN) are 2 severe and highly heterogeneous disorders showing substantial familial co-aggregation. Genetic factors play a significant role in both disorders, but the shared genetic etiology between them is yet to be investigated. Study Design Using summary statistics from recent large genome-wide association studies on SCZ (N cases = 53 386) and AN (N cases = 16 992), a 2-sample Mendelian randomization analysis was conducted to explore the causal relationship between SCZ and AN. MiXeR was employed to quantify their polygenic overlap. A conditional/conjunctional false discovery rate (condFDR/conjFDR) framework was adopted to identify loci jointly associated with both disorders. Functional annotation and enrichment analyses were performed on the shared loci. Study Results We observed a cross-trait genetic enrichment, a suggestive bidirectional causal relationship, and a considerable polygenic overlap (Dice coefficient = 62.2%) between SCZ and AN. The proportion of variants with concordant effect directions among all shared variants was 69.9%. Leveraging overlapping genetic associations, we identified 6 novel loci for AN and 33 novel loci for SCZ at condFDR <0.01. At conjFDR <0.05, we identified 10 loci jointly associated with both disorders, implicating multiple genes highly expressed in the cerebellum and pituitary and involved in synapse organization. Particularly, high expression of the shared genes was observed in the hippocampus in adolescence and orbitofrontal cortex during infancy. Conclusions This study provides novel insights into the relationship between SCZ and AN by revealing a shared genetic component and offers a window into their complex etiology. [ABSTRACT FROM AUTHOR]

Motivation Spaln is the earliest practical tool for self-sufficient genome mapping and spliced alignment of protein query sequences onto a mammalian-sized eukaryotic genomic sequence. However, its computational speed has become inadequate for the analysis of rapidly growing genomic and transcript sequence data. Results The dynamic programming calculation of Spaln has been sped up in two ways: (i) the introduction of the multi-intermediate unidirectional Hirschberg method and (ii) SIMD-based vectorization. The new version, Spaln3, is ∼7 times faster than the latest Spaln version 2, and its gene prediction accuracy is consistently higher than that of Miniprot. Availability and implementation https://github.com/ogotoh/spaln. [ABSTRACT FROM AUTHOR]

Increasing SNP density by incorporating sequence information only marginally increases prediction accuracies of breeding values in livestock. To find out why, we used statistical models and simulations to investigate the shape of distribution of estimated SNP effects (a profile) around quantitative trait nucleotides (QTNs) in populations with a small effective population size (Ne). A QTN profile created by averaging SNP effects around each QTN was similar to the shape of expected pairwise linkage disequilibrium (PLD) based on Ne and genetic distance between SNP, with a distinct peak for the QTN. Populations with smaller Ne showed lower but wider QTN profiles. However, adding more genotyped individuals with phenotypes dragged the profile closer to the QTN. The QTN profile was higher and narrower for populations with larger compared to smaller Ne. Assuming the PLD curve for the QTN profile, 80% of the additive genetic variance explained by each QTN was contained in ± 1/Ne Morgan interval around the QTN, corresponding to 2 Mb in cattle and 5 Mb in pigs and chickens. With such large intervals, identifying QTN is difficult even if all of them are in the data and the assumed genetic architecture is simplistic. Additional complexity in QTN detection arises from confounding of QTN profiles with signals due to relationships, overlapping profiles with closely spaced QTN, and spurious signals. However, small Ne allows for accurate predictions with large data even without QTN identification because QTNs are accounted for by QTN profiles if SNP density is sufficient to saturate the segments. [ABSTRACT FROM AUTHOR]

Objectives Distinguishing between sporadic and germline/mosaic NF2- related schwannomatosis is important to ensure that patients have appropriate long-term care. With this report, we describe a unique case of a patient with 4 ipsilateral schwannomas and identify a combination of sequencing modalities that can accurately diagnose mosaic NF2- related schwannomatosis. Methods We present a 32-year-old woman with a familial history of vestibular schwannoma in her father and right-sided schwannomas involving the apical and basal turns of cochlea, lateral semicircular canal, and internal auditory canal (IAC). Genetic analysis of blood and frozen tissue from 2 tumors (intralabyrinthine and IAC tumors) was performed using next-generation sequencing (NGS), multiplex ligation-dependent probe amplification (MLPA), and optical genome mapping (OGM). Results Germline testing for NF2, LZTR1, and SMARCB1 was negative. Tumor genetic testing revealed a shared NF2 pathogenic variant between the 2 tumors ("first hit") but distinct "second hit" NF2 variants, including mosaic loss of chromosome 22 in the IAC tumor seen only with OGM, consistent with mosaic NF2- related schwannomatosis. Conclusions Multimodality sequencing, including NGS, MLPA, and OGM, was required to ensure appropriate diagnosis of mosaic NF2- related schwannomatosis in this patient. A similar approach can be used for other patients with multiple ipsilateral tumors and suspected tumor predisposition. [ABSTRACT FROM AUTHOR]

Summary Mitochondrial DNA sequences are used extensively in phylogeographic and phylogenetic studies for a wide range of organisms. With the advent of low-cost, high-throughput "next generation" DNA sequencing, and user-friendly bioinformatics pipelines for generating and annotating whole mitochondrial genome assemblies, the analysis of whole mitochondrial genomes has become an important component of phylogenomic studies for taxa with high species diversity but limited coverage for other genomic resources. An important step in characterizing de novo mitochondrial genome assemblies is to evaluate and describe structural rearrangements relative to reference taxa. Accessible tools are needed to help visualize gene and non-coding feature complement, their order, and strand orientation. However, there are few dedicated applications that generate high-quality genome diagrams. Here we present circularMT and circularMT-console that allow users to create highly customizable, publication-quality images, of linear and circular mitochondrial genome maps, either individually or integrated into an analysis pipeline. Availability and implementation Both applications are implemented in C#, with binaries, source code, and user guides available on GitHub (https://github.com/msjimc/circularMT). An archive of the published version is available on Zenodo (https://zenodo.org/records/10912319). [ABSTRACT FROM AUTHOR]

Motivation Hi-C is gaining prominence as a method for mapping genome organization. With declining sequencing costs and a growing demand for higher-resolution data, efficient tools for processing Hi-C datasets at different resolutions are crucial. Over the past decade, the.hic and Cooler file formats have become the de-facto standard to store interaction matrices produced by Hi-C experiments in binary format. Interoperability issues make it unnecessarily difficult to convert between the two formats and to develop applications that can process each format natively. Results We developed hictk, a toolkit that can transparently operate on.hic and.cool files with excellent performance. The toolkit is written in C++ and consists of a C++ library with Python and R bindings as well as CLI tools to perform common operations directly from the shell, including converting between.hic and.mcool formats. We benchmark the performance of hictk and compare it with other popular tools and libraries. We conclude that hictk significantly outperforms existing tools while providing the flexibility of natively working with both file formats without code duplication. Availability and implementation The hictk library, Python bindings and CLI tools are released under the MIT license as a multi-platform application available at github.com/paulsengroup/hictk. Pre-built binaries for Linux and macOS are available on bioconda. Python bindings for hictk are available on GitHub at github.com/paulsengroup/hictkpy , while R bindings are available on GitHub at github.com/paulsengroup/hictkR. [ABSTRACT FROM AUTHOR]

UV light is a potent mutagen that induces bulky DNA damage in the form of cyclobutane pyrimidine dimers (CPDs). Photodamage and other bulky lesions occurring in nuclear genomes can be repaired through nucleotide excision repair (NER), where incisions on both sides of a damaged site precede the removal of a single-stranded oligonucleotide containing the damage. Mitochondrial genomes (mtDNAs) are also susceptible to damage from UV light, but current evidence suggests that the only way to eliminate bulky mtDNA damage is through mtDNA degradation. Damage-containing oligonucleotides excised during NER can be captured with antidamage antibodies and sequenced (XR-seq) to produce high-resolution maps of active repair locations following UV exposure. We analyzed previously published datasets from Arabidopsis thaliana, Saccharomyces cerevisiae , and Drosophila melanogaster to identify reads originating from the mtDNA (and plastid genome in A. thaliana). In A. thaliana and S. cerevisiae , the mtDNA-mapping reads have unique length distributions compared to the nuclear-mapping reads. The dominant fragment size was 26 nt in S. cerevisiae and 28 nt in A. thaliana with distinct secondary peaks occurring in regular intervals. These reads also show a nonrandom distribution of di-pyrimidines (the substrate for CPD formation) with TT enrichment at positions 7–8 of the reads. Therefore, UV damage to mtDNA appears to result in production of DNA fragments of characteristic lengths and positions relative to the damaged location. The mechanisms producing these fragments are unclear, but we hypothesize that they result from a previously uncharacterized DNA degradation pathway or repair mechanism in mitochondria. [ABSTRACT FROM AUTHOR]

Ploidy is relevant to numerous biological phenomena, including development, metabolism, and tissue regeneration. Single-cell RNA-seq and other omics studies are revolutionizing our understanding of biology, yet they have largely overlooked ploidy. This is likely due to the additional assay step required for ploidy measurement. Here, we developed a statistical method to infer ploidy from single-cell ATAC-seq data, addressing this gap. When applied to data from human and mouse cell atlases, our method enabled systematic detection of polyploidy across diverse cell types. This method allows for the integration of ploidy analysis into single-cell studies. Additionally, this method can be adapted to detect the proliferating stage in the cell cycle and copy number variations in cancer cells. The software is implemented as the scPloidy package of the R software and is freely available from CRAN. [ABSTRACT FROM AUTHOR]

Auanema freiburgense is a nematode with males, females, and selfing hermaphrodites. When XO males mate with XX females, they typically produce a low proportion of XO offspring because they eliminate nullo-X spermatids. This process ensures that most sperm carry an X chromosome, increasing the likelihood of X chromosome transmission compared to random segregation. This occurs because of an unequal distribution of essential cellular organelles during sperm formation, likely dependent on the X chromosome. Some sperm components are selectively segregated into the X chromosome's daughter cell, while others are discarded with the nullo-X daughter cell. Intriguingly, the interbreeding of 2 A. freiburgense strains results in hybrid males capable of producing viable nullo-X sperm. Consequently, when these hybrid males mate with females, they yield a high percentage of male offspring. To uncover the genetic basis of nullo-spermatid elimination and X chromosome drive, we generated a genome assembly for A. freiburgense and genotyped the intercrossed lines. This analysis identified a quantitative trait locus spanning several X chromosome genes linked to the non-Mendelian inheritance patterns observed in A. freiburgense. This finding provides valuable clues to the underlying factors involved in asymmetric organelle partitioning during male meiotic division and thus non-Mendelian transmission of the X chromosome and sex ratios. [ABSTRACT FROM AUTHOR]

DDX11/Chl1R is a conserved DNA helicase with roles in genome maintenance, DNA replication, and chromatid cohesion. Loss of DDX11 in humans leads to the rare cohesinopathy Warsaw breakage syndrome. DDX11 has also been implicated in human cancer where it has been proposed to have an oncogenic role and possibly to constitute a therapeutic target. Given the multiple roles of DDX11 in genome stability and its potential as an anticancer target, we set out to define a complete genetic interaction profile of DDX11 loss in human cell lines. Screening the human genome with clustered regularly interspaced short palindromic repeats (CRISPR) guide RNA drop out screens in DDX11-wildtype (WT) or DDX11-deficient cells revealed a strong enrichment of genes with functions related to sister chromatid cohesion. We confirm synthetic lethal relationships between DDX11 and the tumor suppressor cohesin subunit STAG2 , which is frequently mutated in several cancer types and the kinase HASPIN. This screen highlights the importance of cohesion in cells lacking DDX11 and suggests DDX11 may be a therapeutic target for tumors with mutations in STAG2. [ABSTRACT FROM AUTHOR]

Motivation The interpretation of genomic data is crucial to understand the molecular mechanisms of biological processes. Protein structures play a vital role in facilitating this interpretation by providing functional context to genetic coding variants. However, mapping genes to proteins is a tedious and error-prone task due to inconsistencies in data formats. Over the past two decades, numerous tools and databases have been developed to automatically map annotated positions and variants to protein structures. However, most of these tools are web-based and not well-suited for large-scale genomic data analysis. Results To address this issue, we introduce 3Dmapper, a stand-alone command-line tool developed in Python and R. It systematically maps annotated protein positions and variants to protein structures, providing a solution that is both efficient and reliable. Availability and implementation https://github.com/vicruiser/3Dmapper [ABSTRACT FROM AUTHOR]

Motivation Currently there is a lack of efficient computational pipelines/tools for conducting simultaneous genome mapping of pathogen-derived and host reads from single cell RNA sequencing (scRNAseq) output from pathogen-infected cells. Contemporary options include processes involving multiple steps and/or running multiple computational tools, increasing user operations time. Results To address the need for new tools to directly map and quantify pathogen and host sequence reads from within an infected cell from scRNAseq datasets in a single operation, we have built a python package, called scPathoQuant. scPathoQuant extracts sequences that were not aligned to the primary host genome, maps them to a pathogen genome of interest (here as demonstrated for viral pathogens), quantifies total reads mapping to the entire pathogen, quantifies reads mapping to individual pathogen genes, and finally integrates pathogen sequence counts into matrix files that are used by standard single cell pipelines for downstream analyses with only one command. We demonstrate that scPathoQuant provides a scRNAseq viral and host genome-wide sequence read abundance analysis that can differentiate and define multiple viruses in a single sample scRNAseq output. Availability and implementation The SPQ package is available software accessible at https://github.com/galelab/scPathoQuant (DOI 10.5281/zenodo.10463670) with test codes and datasets available https://github.com/galelab/Whitmore%5fscPathoQuant%5ftestSets (DOI 10.5281/zenodo.10463677) to serve as a resource for the community. [ABSTRACT FROM AUTHOR]

Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties. [ABSTRACT FROM AUTHOR]

In species with large and complex genomes such as conifers, dense linkage maps are a useful resource for supporting genome assembly and laying the genomic groundwork at the structural, populational, and functional levels. However, most of the 600+ extant conifer species still lack extensive genotyping resources, which hampers the development of high-density linkage maps. In this study, we developed a linkage map relying on 21,570 single nucleotide polymorphism (SNP) markers in Sitka spruce (Picea sitchensis [Bong.] Carr.), a long-lived conifer from western North America that is widely planted for productive forestry in the British Isles. We used a single-step mapping approach to efficiently combine RAD-seq and genotyping array SNP data for 528 individuals from 2 full-sib families. As expected for spruce taxa, the saturated map contained 12 linkages groups with a total length of 2,142 cM. The positioning of 5,414 unique gene coding sequences allowed us to compare our map with that of other Pinaceae species, which provided evidence for high levels of synteny and gene order conservation in this family. We then developed an integrated map for P. sitchensis and Picea glauca based on 27,052 markers and 11,609 gene sequences. Altogether, these 2 linkage maps, the accompanying catalog of 286,159 SNPs and the genotyping chip developed, herein, open new perspectives for a variety of fundamental and more applied research objectives, such as for the improvement of spruce genome assemblies, or for marker-assisted sustainable management of genetic resources in Sitka spruce and related species. [ABSTRACT FROM AUTHOR]

Meiotic control of crossover (CO) number and position is critical for homologous chromosome segregation and organismal fertility, recombination of parental genotypes, and the generation of novel genetic combinations. We here characterize the recombination rate landscape of a rec-1 loss of function modifier of CO position in Caenorhabditis elegans , one of the first ever modifiers discovered. By averaging CO position across hermaphrodite and male meioses and by genotyping 203 single-nucleotide variants covering about 95% of the genome, we find that the characteristic chromosomal arm-center recombination rate domain structure is lost in the loss of function rec-1 mutant. The rec-1 loss of function mutant smooths the recombination rate landscape but is insufficient to eliminate the nonuniform position of CO. Lower recombination rates in the rec-1 mutant are particularly found in the autosomal arm domains containing the pairing centers. We further find that the rec-1 mutant is of little consequence for organismal fertility and egg viability and thus for rates of autosomal nondisjunction. It nonetheless increases X chromosome nondisjunction rates and thus male appearance. Our findings question the maintenance of recombination rate heritability and genetic diversity among C. elegans natural populations, and they further suggest that manipulating genetic modifiers of CO position will help find quantitative trait loci located in low-recombining genomic regions normally refractory to discovery. [ABSTRACT FROM AUTHOR]

Comparative sequence analysis permits unraveling the molecular processes underlying gene evolution. Many statistical methods generate candidate positions within genes, such as fast or slowly evolving sites, coevolving groups of residues, sites undergoing positive selection, or changes in evolutionary rates. Understanding the functional causes of these evolutionary patterns requires combining the results of these analyses and mapping them onto molecular structures, a complex task involving distinct coordinate referential systems. To ease this task, we introduce the site/group extended data format, a simple text format to store (groups of) site annotations. We developed a toolset, the SgedTools, which permits site/group extended data file manipulation, creating them from various software outputs and translating coordinates between individual sequences, alignments, and three-dimensional structures. The package also includes a Monte-Carlo procedure to generate random site samples, possibly conditioning on site-specific features. This eases the statistical testing of evolutionary hypotheses, accounting for the structural properties of the encoded molecules. [ABSTRACT FROM AUTHOR]

The ancestral recombination graph (ARG) is a structure that represents the history of coalescent and recombination events connecting a set of sequences (Hudson RR. In: Futuyma D, Antonovics J, editors. Gene genealogies and the coalescent process. In: Oxford Surveys in Evolutionary Biology; 1991. p. 1 to 44.). The full ARG can be represented as a set of genealogical trees at every locus in the genome, annotated with recombination events that change the topology of the trees between adjacent loci and the mutations that occurred along the branches of those trees (Griffiths RC, Marjoram P. An ancestral recombination graph. In: Donnelly P, Tavare S, editors. Progress in population genetics and human evolution. Springer; 1997. p. 257 to 270.). Valuable insights can be gained into past evolutionary processes, such as demographic events or the influence of natural selection, by studying the ARG. It is regarded as the "holy grail" of population genetics (Hubisz M, Siepel A. Inference of ancestral recombination graphs using ARGweaver. In: Dutheil JY, editors. Statistical population genomics. New York, NY: Springer US; 2020. p. 231–266.) since it encodes the processes that generate all patterns of allelic and haplotypic variation from which all commonly used summary statistics in population genetic research (e.g. heterozygosity and linkage disequilibrium) can be derived. Many previous evolutionary inferences relied on summary statistics extracted from the genotype matrix. Evolutionary inferences using the ARG represent a significant advancement as the ARG is a representation of the evolutionary history of a sample that shows the past history of recombination, coalescence, and mutation events across a particular sequence. This representation in theory contains as much information, if not more, than the combination of all independent summary statistics that could be derived from the genotype matrix. Consistent with this idea, some of the first ARG-based analyses have proven to be more powerful than summary statistic-based analyses (Speidel L, Forest M, Shi S, Myers SR. A method for genome-wide genealogy estimation for thousands of samples. Nat Genet. 2019:51(9):1321 to 1329.; Stern AJ, Wilton PR, Nielsen R. An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data. PLoS Genet. 2019:15(9):e1008384.; Hubisz MJ, Williams AL, Siepel A. Mapping gene flow between ancient hominins through demography-aware inference of the ancestral recombination graph. PLoS Genet. 2020:16(8):e1008895.; Fan C, Mancuso N, Chiang CWK. A genealogical estimate of genetic relationships. Am J Hum Genet. 2022:109(5):812–824.; Fan C, Cahoon JL, Dinh BL, Ortega-Del Vecchyo D, Huber C, Edge MD, Mancuso N, Chiang CWK. A likelihood-based framework for demographic inference from genealogical trees. bioRxiv. 2023.10.10.561787. 2023.; Hejase HA, Mo Z, Campagna L, Siepel A. A deep-learning approach for inference of selective sweeps from the ancestral recombination graph. Mol Biol Evol. 2022:39(1):msab332.; Link V, Schraiber JG, Fan C, Dinh B, Mancuso N, Chiang CWK, Edge MD. Tree-based QTL mapping with expected local genetic relatedness matrices. bioRxiv. 2023.04.07.536093. 2023.; Zhang BC, Biddanda A, Gunnarsson ÁF, Cooper F, Palamara PF. Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits. Nat Genet. 2023:55(5):768–776.). As such, there has been significant interest in the field to investigate 2 main problems related to the ARG: (i) How can we estimate the ARG based on genomic data, and (ii) how can we extract information of past evolutionary processes from the ARG? In this perspective, we highlight 3 topics that pertain to these main issues: The development of computational innovations that enable the estimation of the ARG; remaining challenges in estimating the ARG; and methodological advances for deducing evolutionary forces and mechanisms using the ARG. This perspective serves to introduce the readers to the types of questions that can be explored using the ARG and to highlight some of the most pressing issues that must be addressed in order to make ARG-based inference an indispensable tool for evolutionary research. [ABSTRACT FROM AUTHOR]

Summary Sensory receptor gene families have undergone extensive expansion and loss across vertebrate evolution, leading to significant variation in receptor counts between species. However, due to their species-specific nature, conventional reference-based annotation tools often underestimate the true number of sensory receptors in a given species. While there has been an exponential increase in the taxonomic diversity of publicly available genome assemblies in recent years, only ∼30% of vertebrate species on the NCBI database are currently annotated. To overcome these limitations, we developed 'Sensommatic', an automated and accessible sensory receptor annotation pipeline. Sensommatic implements BLAST and AUGUSTUS to mine and predict sensory receptor genes from whole genome assemblies, adopting a one-to-many gene mapping approach. While designed for vertebrates, Sensommatic can be extended to run on non-vertebrate species by generating customized reference files, making it a scalable and generalizable tool. Availability and implementation Source code and associated files are available at: https://github.com/GMHughes/Sensommatic [ABSTRACT FROM AUTHOR]

Genome sequencing and genetic mapping of molecular markers have demonstrated nearly complete Y-linkage across much of the guppy (Poecilia reticulata) XY chromosome pair. Predominant Y-linkage of factors controlling visible male-specific coloration traits also suggested that these polymorphisms are sexually antagonistic (SA). However, occasional exchanges with the X are detected, and recombination patterns also appear to differ between natural guppy populations, suggesting ongoing evolution of recombination suppression under selection created by partially sex-linked SA polymorphisms. We used molecular markers to directly estimate genetic maps in sires from 4 guppy populations. The maps are very similar, suggesting that their crossover patterns have not recently changed. Our maps are consistent with population genomic results showing that variants within the terminal 5 Mb of the 26.5 Mb sex chromosome, chromosome 12, are most clearly associated with the maleness factor, albeit incompletely. We also confirmed occasional crossovers proximal to the male-determining region, defining a second, rarely recombining, pseudo-autosomal region, PAR2. This fish species may therefore have no completely male-specific region (MSY) more extensive than the male-determining factor. The positions of the few crossover events suggest a location for the male-determining factor within a physically small repetitive region. A sex-reversed XX male had few crossovers in PAR2, suggesting that this region's low crossover rate depends on the phenotypic, not the genetic, sex. Thus, rare individuals whose phenotypic and genetic sexes differ, and/or occasional PAR2 crossovers in males can explain the failure to detect fully Y-linked variants. [ABSTRACT FROM AUTHOR]

The balanced segregation of homologous chromosomes during meiosis is essential for fertility and is mediated by crossovers (COs). A strong reduction of CO number leads to the unpairing of homologous chromosomes after the withdrawal of the synaptonemal complex. This results in the random segregation of univalents during meiosis I and ultimately to the production of unbalanced and sterile gametes. However, if CO shortage is combined with another meiotic alteration that restitutes the first meiotic division, then uniform and balanced unreduced male gametes, essentially composed of nonrecombinant homologs, are produced. This mitosis-like division is of interest to breeders because it transmits most of the parental heterozygosity to the gametes. In potato, CO shortage, a recessive trait previously referred to as desynapsis, was tentatively mapped to chromosome 8. In this article, we have fine-mapped the position of the CO shortage locus and identified StMSH4 , an essential component of the class I CO pathway, as the most likely candidate gene. A 7 base-pair insertion in the second exon of StMSH4 was found to be associated with CO shortage in our mapping population. We also identified a second allele with a 3,820 base-pair insertion and confirmed that both alleles cannot complement each other. Such nonfunctional alleles appear to be common in potato cultivars. More than half of the varieties we tested are carriers of mutational load at the StMSH4 locus. With this new information, breeders can choose to remove alleles associated with CO shortage from their germplasm to improve fertility or to use them to produce highly uniform unreduced male gametes in alternative breeding schemes. [ABSTRACT FROM AUTHOR]

The floras on chemically and physically challenging soils, such as gypsum, shale, and serpentine, are characterized by narrowly endemic species. The evolution of edaphic endemics may be facilitated or constrained by genetic correlations among traits contributing to adaptation and reproductive isolation across soil boundaries. The yellow monkeyflowers in the Mimulus guttatus species complex are an ideal system in which to examine these evolutionary patterns. To determine the genetic basis of adaptive and prezygotic isolating traits, we performed genetic mapping experiments with F2 hybrids derived from a cross between a serpentine endemic, M. nudatus , and its close relative M. guttatus. Few large effect and many small effect QTL contribute to interspecific divergence in life history, floral, and leaf traits, and a history of directional selection contributed to trait divergence. Loci contributing to adaptive traits and prezygotic reproductive isolation overlap, and their allelic effects are largely in the direction of species divergence. These loci contain promising candidate genes regulating flowering time and plant organ size. Together, our results suggest that genetic correlations among traits can facilitate the evolution of adaptation and speciation and may be a common feature of the genetic architecture of divergence between edaphic endemics and their widespread relatives. [ABSTRACT FROM AUTHOR]

The US standard for maize commercially grown for grain specifies that yellow corn can contain at maximum 5% corn of other colors. Inbred parents of commercial hybrids typically have clear pericarp, but transgressive segregants in breeding populations can display variation in pericarp pigmentation. We identified 10 doubled haploid biparental populations segregating for pigmented pericarp and evaluated qualitative genetic models using chi-square tests of observed and expected frequencies. Pigmentation ranged from light to dark brown color, and pigmentation intensity was quantitatively measured across 1,327 inbred lines using hue calculated from RGB pixel values. Genetic mapping was used to identify loci associated with pigmentation intensity. For 9 populations, pigmentation inheritance best fit a hypothesis of a 2- or 3-gene epistatic model. Significant differences in pigment intensity were observed across populations. W606S-derived inbred lines with the darkest pericarp often had clear glumes, suggesting the presence of a novel P1-rw allele, a hypothesis supported by a significant quantitative trait locus peak at P1. A separate quantitative trait locus region on chromosome 2 between 221.64 and 226.66 Mbp was identified in LH82-derived populations, and the peak near p1 was absent. A genome-wide association study using 416 inbred lines from the Wisconsin Diversity panel with full genome resequencing revealed 4 significant associations including the region near P1. This study supports that pericarp pigmentation among dent maize inbreds can arise by transgressive segregation when pigmentation in the parental generation is absent and is partially explained by functional allelic variation at the P1 locus. [ABSTRACT FROM AUTHOR]

Rice hoja blanca (RHB) is one of the most serious diseases in rice-growing areas in tropical Americas. Its causal agent is RHB virus (RHBV), transmitted by the planthopper Tagosodes orizicolus Müir. Genetic resistance is the most effective and environment-friendly way of controlling the disease. So far, only 1 major quantitative trait locus (QTL) of Oryza sativa ssp. japonica origin, qHBV4.1, that alters the incidence of the virus symptoms in 2 Colombian cultivars has been reported. This resistance has already started to be broken, stressing the urgent need for diversifying the resistance sources. In the present study, we performed a search for new QTLs of O. sativa indica origin associated with RHB resistance. We used 4 F2:3-segregating populations derived from indica-resistant varieties crossed with a highly susceptible japonica pivot parent. Besides the standard method for measuring disease incidence, we developed a new method based on computer-assisted image processing to determine the affected leaf area (ALA) as a measure of symptom severity. Based on the disease severity and incidence scores in the F3 families under greenhouse conditions and SNP genotyping of the F2 individuals, we identified 4 new indica QTLs for RHB resistance on rice chromosomes 4, 6, and 11, namely, qHBV4.2WAS208, qHBV6.1PTB25, qHBV11.1, and qHBV11.2, respectively. We also confirmed the wide-range action of qHBV4.1. Among the 5 QTLs, qHBV4.1 and qHBV11.1 had the largest effects on incidence and severity, respectively. These results provide a more complete understanding of the genetic bases of RHBV resistance in the cultivated rice gene pool and can be used to develop marker-aided breeding strategies to improve RHB resistance. The power of joint- and meta-analyses allowed precise mapping and candidate gene identification, providing the basis for positional cloning of the 2 major QTLs qHBV4.1 and qHBV11.1. [ABSTRACT FROM AUTHOR]

Osmotic stress is a ubiquitous and potent stress for all living organisms, but few studies have investigated the genetic basis of salt tolerance in filamentous fungi. The main aim of this study was to identify regions of the genome associated with tolerance to potassium chloride (KCl) in the wheat pathogen Zymoseptoria tritici. A secondary aim was to identify candidate genes affecting salt tolerance within the most promising chromosomal regions. We achieved these aims with a quantitative trait locus (QTL) mapping study using offspring from 2 crosses grown in vitro in the presence or absence of osmotic stress imposed by 0.75 M KCl. We identified significant QTL for most of the traits in both crosses. Several QTLs overlapped with QTL identified in earlier studies for other traits, and some QTL explained trait variation in both the control and salt stress environments. A significant QTL on chromosome 3 explained variation in colony radius at 8-day postinoculation (dpi) in the KCl environment as well as colony radius KCl tolerance at 8 dpi. The QTL peak had a high logarithm of the odds ratio (LOD) and encompassed an interval containing only 36 genes. Six of these genes present promising candidates for functional analyses. A gene ontology (GO) enrichment analysis of QTL unique to the KCl environment found evidence for the enrichment of functions involved in osmotic stress responses. [ABSTRACT FROM AUTHOR]

A planet embedded in a protoplanetary disk produces a gap by disk–planet interaction. It also generates velocity perturbation of gas, which can also be observed as deviations from the Keplerian rotation in the channel map of molecular line emission, called kinematic planetary features. These observed signatures provide clues to determine the mass of the planet. We investigated the features induced by a planet with an inclined orbit through three-dimensional hydrodynamic simulations. We found that a smaller planet, with an inclination of ∼10○–20○, can produce kinematic features as prominent as those induced by a massive coplanar planet. Despite the kinematic features being similar, the gap is shallower and narrower compared with the case in which the kinematic features are formed by a coplanar planet. We also found that the kinematic features induced by an inclined planet were fainter for rarer CO isotopologues because the velocity perturbation is weaker at the position closer to the midplane, which was different in the case with a coplanar massive planet. This dependence on the isotopologues is distinguished if the planet has an inclined orbit. We discussed two observed kinematic features in the disk of HD 163296. We concluded that the kink observed at 220 au can be induced by an inclined planet, while the kink at 67 au is consistent to that induced by a coplanar planet. [ABSTRACT FROM AUTHOR]

Metabolic diseases are a host of complex conditions, including obesity, diabetes mellitus, and metabolic syndrome. Endocrine control systems (eg, adrenals, thyroid, gonads) are causally linked to metabolic health outcomes. N/NIH Heterogeneous Stock (HS) rats are a genetically heterogeneous outbred population developed for genetic studies of complex traits. Genetic mapping studies in adult HS rats identified loci associated with cardiometabolic risks, such as glucose intolerance, insulin resistance, and increased body mass index. This study determined underappreciated metabolic health traits and the associated endocrine glands within available substrains of the HS rat founders. We hypothesize that the genetic diversity of the HS rat founder strains causes a range of endocrine health conditions contributing to the diversity of cardiometabolic disease risks. ACI/EurMcwi, BN/NHsdMcwi, BUF/MnaMcwi, F344/StmMcwi, M520/NRrrcMcwi, and WKY/NCrl rats of both sexes were studied from birth until 13 weeks of age. Birth weight was recorded, body weight was measured weekly, metabolic characteristics were assessed, and blood and tissues were collected. Our data show wide variation in endocrine traits and metabolic health states in ACI, BN, BUF, F344, M520, and WKY rat strains. This is the first report to compare birth weight, resting metabolic rate, endocrine gland weight, hypothalamic–pituitary–thyroid axis hormones, and brown adipose tissue weight in these rat strains. Importantly, this work unveils new potential for the HS rat population to model early life adversity and adrenal and thyroid pathophysiology. The HS population likely inherited risk alleles for these strain-specific traits, making the HS rat a powerful model to investigate interventions on endocrine and metabolic health. [ABSTRACT FROM AUTHOR]

We analyse synthetic 12CO, 13CO, and [C  ii ] emission maps of molecular cloud (MC) simulations from the SILCC-Zoom project. We present radiation, magnetohydrodynamic zoom-in simulations of individual clouds, both with and without radiative stellar feedback, forming in a turbulent multiphase interstellar medium following on-the-fly the evolution of e.g. H2, CO, and C+. We introduce a novel post-processing routine based on cloudy which accounts for higher ionization states of carbon due to stellar radiation in H  ii regions. Synthetic emission maps of [C  ii ] in and around feedback bubbles show that the bubbles are largely devoid of [C  ii ], as recently found in observations, which we attribute to the further ionization of C+ into C2+. For both 12CO and 13CO, the cloud-averaged luminosity ratio, |$L_\rm {CO}/L_\rm {[C\, \small {II}]}$|⁠ , can neither be used as a reliable measure of the H2 mass fraction nor of the evolutionary stage of the clouds. We note a relation between the |$I_\rm {CO}/I_\rm {[C\, \small {II}]}$| intensity ratio and the H2 mass fraction for individual pixels of our synthetic maps. The scatter, however, is too large to reliably infer the H2 mass fraction. Finally, the assumption of chemical equilibrium overestimates H2 and CO masses by up to 150 and 50 per cent, respectively, and |$L_\rm {CO}$| by up to 60 per cent. The masses of H and C+ would be underestimated by 65 and 30 per cent, respectively, and |$L_\rm {[C\, \small {II}]}$| by up to 35 per cent. Hence, the assumption of chemical equilibrium in MC simulations introduces intrinsic errors of a factor of 2 in chemical abundances, luminosities, and luminosity ratios. [ABSTRACT FROM AUTHOR]

Goss's wilt, caused by the Gram-positive actinobacterium Clavibacter nebraskensis, is an important bacterial disease of maize. The molecular and genetic mechanisms of resistance to the bacterium, or, in general, Gram-positive bacteria causing plant diseases, remain poorly understood. Here, we examined the genetic basis of Goss's wilt through differential gene expression, standard genome-wide association mapping (GWAS), extreme phenotype (XP) GWAS using highly resistant (R) and highly susceptible (S) lines, and quantitative trait locus (QTL) mapping using 3 bi-parental populations, identifying 11 disease association loci. Three loci were validated using nearisogenic lines or recombinant inbred lines. Our analysis indicates that Goss's wilt resistance is highly complex and major resistance genes are not commonly present. RNA sequencing of samples separately pooled from R and S lines with or without bacterial inoculation was performed, enabling identification of common and differential gene responses in R and S lines. Based on expression, in both R and S lines, the photosynthesis pathway was silenced upon infection, while stress-responsive pathways and phytohormone pathways, namely, abscisic acid, auxin, ethylene, jasmonate, and gibberellin, were markedly activated. In addition, 65 genes showed differential responses (up- or down-regulated) to infection in R and S lines. Combining genetic mapping and transcriptional data, individual candidate genes conferring Goss's wilt resistance were identified. Collectively, aspects of the genetic architecture of Goss's wilt resistance were revealed, providing foundational data for mechanistic studies. [ABSTRACT FROM AUTHOR]

Motivation Optical genome mapping (OGM) is a technique that extracts partial genomic information from optically imaged and linearized DNA fragments containing fluorescently labeled short sequence patterns. This information can be used for various genomic analyses and applications, such as the detection of structural variations and copy-number variations, epigenomic profiling, and microbial species identification. Currently, the choice of labeled patterns is based on the available biochemical methods and is not necessarily optimized for the application. Results In this work, we develop a model of OGM based on information theory, which enables the design of optimal labeling patterns for specific applications and target organism genomes. We validated the model through experimental OGM on human DNA and simulations on bacterial DNA. Our model predicts up to 10-fold improved accuracy by optimal choice of labeling patterns, which may guide future development of OGM biochemical labeling methods and significantly improve its accuracy and yield for applications such as epigenomic profiling and cultivation-free pathogen identification in clinical samples. Availability and implementation https://github.com/yevgenin/PatternCode [ABSTRACT FROM AUTHOR]

Height is a critical component of plant architecture, significantly affecting crop yield. The genetic basis of this trait in soybean remains unclear. In this study, we report the characterization of the Compact mutant of soybean, which has short internodes. The candidate gene was mapped to chromosome 17, and the interval containing the causative mutation was further delineated using biparental mapping. Whole-genome sequencing of the mutant revealed an 8.7 kb deletion in the promoter of the Glyma.17g145200 gene, which encodes a member of the class III gibberellin (GA) 2-oxidases. The mutation has a dominant effect, likely via increased expression of the GA 2-oxidase transcript observed in green tissue, as a result of the deletion in the promoter of Glyma.17g145200. We further demonstrate that levels of GA precursors are altered in the Compact mutant, supporting a role in GA metabolism, and that the mutant phenotype can be rescued with exogenous GA3. We also determined that overexpression of Glyma.17g145200 in Arabidopsis results in dwarfed plants. Thus, gain of promoter activity in the Compact mutant leads to a short internode phenotype in soybean through altered metabolism of gibberellin precursors. These results provide an example of how structural variation can control an important crop trait and a role for Glyma.17g145200 in soybean architecture, with potential implications for increasing crop yield. [ABSTRACT FROM AUTHOR]

A primary function of the skeleton is to resist the loads imparted by body weight. Genetic analyses have identified genomic regions that contribute to differences in skeletal load resistance between laboratory strains of mice, but these studies are usually restricted to 1 or 2 bones and leave open the question of how load resistance evolves in natural populations. To address these challenges, we examined the genetics of bone structure using the largest wild house mice on record, which live on Gough Island (GI). We measured structural traits connected to load resistance in the femur, tibia, scapula, humerus, radius, ulna, and mandible of GI mice, a smaller-bodied reference strain from the mainland, and 760 of their F2s. GI mice have bone geometries indicative of greater load resistance abilities but show no increase in bone mineral density compared to the mainland strain. Across traits and bones, we identified a total of 153 quantitative trait loci (QTL) that span all but one of the autosomes. The breadth of QTL detection ranges from a single bone to all 7 bones. Additive effects of QTL are modest. QTL for bone structure show limited overlap with QTL for bone length and width and QTL for body weight mapped in the same cross, suggesting a distinct genetic architecture for load resistance. Our findings provide a rare genetic portrait of the evolution of load resistance in a natural population with extreme body size. [ABSTRACT FROM AUTHOR]

Objectives Shiga toxin-producing Escherichia coli (STEC) O157:H7 are zoonotic pathogens and transmission to humans occurs via contaminated food or contact with infected animals. The aim of this study was to describe the frequency, and distribution across the phylogeny, of antimicrobial resistance (AMR) determinants in STEC O157:H7 isolated from human cases in England. Methods Short-read whole-genome sequencing data from 1473 isolates of STEC O157:H7 from all seven sub-lineages (Ia-Ic, IIa-IIc and I/II) were mapped to genes known to confer phenotypic resistance to 10 different classes of antibiotic. Long-read sequencing was used to determine the location and genomic architecture of the AMR determinants within phylogenetic clusters exhibiting multidrug resistance. Results Overall, 216/1473 (14.7%) isolates had at least one AMR determinant, although the proportion of isolates exhibiting AMR varied by sub-lineage. The highest proportion of AMR determinants were detected in sub-lineages Ib (28/64, 43.7%), I/II (18/51, 35.3%) and IIc (122/440, 27.7%). In all sub-lineages, the most commonly detected AMR determinants conferred resistance to the aminoglycosides, tetracyclines and sulphonamides, while AMR determinants conferring resistance to fluroquinolones, macrolides and third-generation cephalosporins were rarely detected. Long-read sequencing analysis showed that the AMR determinants were co-located on the chromosome in sub-lineages Ib and lineage I/II, whereas those associated with sub-lineage IIc were encoded on the chromosome and/or large plasmids. Conclusions AMR genes were unevenly distributed across the different sub-lineages of STEC O157:H7 and between different clades within the same sub-lineage. Long-read sequencing facilitates tracking the transmission of AMR at the pathogen and mobile genetic element level. [ABSTRACT FROM AUTHOR]

Summary Genome-wide association studies (GWAS) excels at harnessing dense genomic variant datasets to identify candidate regions responsible for producing a given phenotype. However, GWAS and traditional fine-mapping methods do not provide insight into the complex local landscape of linkage that contains and has been shaped by the causal variant(s). Here, we present crosshap , an R package that performs robust density-based clustering of variants based on their linkage profiles to capture haplotype structures in a local genomic region of interest. Following this, crosshap is equipped with visualization tools for choosing optimal clustering parameters (ɛ) before producing an intuitive figure that provides an overview of the complex relationships between linked variants, haplotype combinations, phenotype, and metadata traits. Availability and implementation The crosshap package is freely available under the MIT license and can be downloaded directly from CRAN with R >4.0.0. The development version is available on GitHub alongside issue support (https://github.com/jacobimarsh/crosshap). Tutorial vignettes and documentation are available (https://jacobimarsh.github.io/crosshap/). [ABSTRACT FROM AUTHOR]

Summary Here, we present an expanded utility of the R package qgg for genetic analyses of complex traits and diseases. One of the major updates of the package is, that it now includes Bayesian linear regression modeling procedures, which provide a unified framework for mapping of genetic variants, estimation of heritability and genomic prediction from either individual level data or from genome-wide association study summary data. With this release, the qgg package now provides a wealth of the commonly used methods in analysis of complex traits and diseases, without the need to switch between software and data formats. Availability and implementation The methodologies are implemented in the publicly available R software package, qgg, using fast and memory efficient algorithms in C++ and is available on CRAN or as a developer version at our GitHub page (https://github.com/psoerensen/qgg). Notes on the implemented statistical genetic models, tutorials and example scripts are available at our GitHub page https://psoerensen.github.io/qgg/. [ABSTRACT FROM AUTHOR]

This scientific commentary discusses the role of the huntingtin protein (HTT) in neurodevelopment and neurodegeneration in Huntington's disease. The authors explore the relationship between genetic topography, cortical cell loss, and disease progression using brain mapping techniques and gene expression data. They find a positive correlation between cortical cell loss and the expression of developmental genes, suggesting a complex interaction between HTT and neurodevelopment. The authors also discuss the implications of these findings for drug development strategies and propose that therapies aimed at protecting vulnerable neurons may be more effective than reducing mHTT levels. Further research is needed to fully understand the role of HTT in neurodevelopment. [Extracted from the article]

Grain chalkiness is an important index of rice appearance quality and is negatively associated with rice processing and eating quality. However, the genetic mechanism underlying chalkiness formation is largely unknown. To identify the genetic basis of chalkiness, 410 recombinant inbred lines (RILs) derived from two representative indica rice varieties, Shuhui498 (R498) and Yihui3551 (R3551), were used to discover quantitative trait loci (QTLs). The two parental lines and RILs were grown in three locations in China under three controlled fertilizer application levels. Analyses indicated that chalkiness was significantly affected by genotype, the environment, and the interaction between the two, and that heritability was high. Several QTLs were isolated, including the two stable QTLs qCGP6 and qCGP8. Fine mapping and candidate gene verification of qCGP6 showed that Wx may play a key role in chalkiness formation. Chromosomal segment substitution lines (CSSLs) and near-isogenic lines (NILs) carrying the Wx a or Wx in allele produced more chalky grain than the R498 parent. A similar result was also observed in the 3611 background. Notably, the effect of the Wx genotype on rice chalkiness was shown to be dependent on environmental conditions, and Wx alleles exhibited different sensitivities to shading treatment. Using clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9), the Wx a promoter region was successfully edited; down-regulating Wx alleviates chalkiness formation in NILR498- Wx a . This study developed a new strategy for synergistic improvement of eating and appearance qualities in rice, and created a novel Wx allele with great potential in breeding applications. [ABSTRACT FROM AUTHOR]

Summary Mapping genetic interactions and essentiality networks in human cell lines has been used to identify vulnerabilities of cells carrying specific genetic alterations and to associate novel functions to genes, respectively. In vitro and in vivo genetic screens to decipher these networks are resource-intensive, limiting the throughput of samples that can be analyzed. In this application note, we provide an R package we call Genetic inteRaction and EssenTiality neTwork mApper (GRETTA). GRETTA is an accessible tool for in silico genetic interaction screens and essentiality network analyses using publicly available data, requiring only basic R programming knowledge. Availability and implementation The R package, GRETTA, is licensed under GNU General Public License v3.0 and freely available at https://github.com/ytakemon/GRETTA and https://doi.org/10.5281/zenodo.6940757 , with documentation and tutorial. A Singularity container is also available at https://cloud.sylabs.io/library/ytakemon/gretta/gretta. [ABSTRACT FROM AUTHOR]

Chromosome rearrangements are often implicated with genomic divergence and are proposed to be associated with species evolution. Rearrangements alter the genomic structure and interfere with homologous recombination by isolating a portion of the genome. Integration of multiplatform next-generation DNA sequencing technologies has enabled putative identification of chromosome rearrangements in many taxa; however, integrating these data sets with cytogenetics is still uncommon beyond model genetic organisms. Therefore, to achieve the ultimate goal for the genomic classification of eukaryotic organisms, physical chromosome mapping remains critical. The ridge-tailed goannas (Varanus acanthurus BOULENGER) are a group of dwarf monitor lizards comprised of several species found throughout northern Australia. These lizards exhibit extreme divergence at both the genic and chromosomal levels. The chromosome polymorphisms are widespread extending across much of their distribution, raising the question if these polymorphisms are homologous within the V. acanthurus complex. We used a combined genomic and cytogenetic approach to test for homology across divergent populations with morphologically similar chromosome rearrangements. We showed that more than one chromosome pair was involved with the widespread rearrangements. This finding provides evidence to support de novo chromosome rearrangements have occurred within populations. These chromosome rearrangements are characterized by fixed allele differences originating in the vicinity of the centromeric region. We then compared this region with several other assembled genomes of reptiles, chicken, and the platypus. We demonstrated that the synteny of genes in Reptilia remains conserved despite centromere repositioning across these taxa. [ABSTRACT FROM AUTHOR]

Motivation A pangenome represents many diverse genome sequences of the same species. In order to cope with small variations as well as structural variations, recent research focused on the development of graph-based models of pangenomes. Mapping is the process of finding the original location of a DNA read in a reference sequence, typically a genome. Using a pangenome instead of a (linear) reference genome can, e.g. reduce mapping bias, the tendency to incorrectly map sequences that differ from the reference genome. Mapping reads to a graph, however, is more complex and needs more resources than mapping to a reference genome. Reducing the complexity of the graph by encoding simple variations like SNPs in a simple way can accelerate read mapping and reduce the memory requirements at the same time. Results We introduce graphs based on elastic-degenerate strings (ED strings, EDS) and the linearized form of these EDS graphs as a new representation for pangenomes. In this representation, small variations are encoded directly in the sequence. Structural variations are encoded in a graph structure. This reduces the size of the representation in comparison to sequence graphs. In the linearized form, mapping techniques that are known from ordinary strings can be applied with appropriate adjustments. Since most variations are expressed directly in the sequence, the mapping process rarely has to take edges of the EDS graph into account. We developed a prototypical software tool GED-MAP that uses this representation together with a minimizer index to map short reads to the pangenome. Our experiments show that the new method works on a whole human genome scale, taking structural variants properly into account. The advantage of GED-MAP, compared with other pangenomic short read mappers, is that the new representation allows for a simple indexing method. This makes GED-MAP fast and memory efficient. Availability and implementation Sources are available at: https://github.com/thomas-buechler-ulm/gedmap. [ABSTRACT FROM AUTHOR]

Mediation analysis is used in genetic mapping studies to identify candidate gene mediators of quantitative trait loci (QTL). We consider genetic mediation analysis of triplets--sets of three variables consisting of a target trait, the genotype at a QTL for the target trait, and a candidate mediator that is the abundance of a transcript or protein whose coding gene co-locates with the QTL. We show that, in the presence of measurement error, mediation analysis can infer partial mediation even in the absence of a causal relationship between the candidate mediator and the target. We describe a measurement error model and a corresponding latent variable model with estimable parameters that are combinations of the causal effects and measurement errors across all three variables. The relative magnitudes of the latent variable correlations determine whether or not mediation analysis will tend to infer the correct causal relationship in large samples. We examine case studies that illustrate the common failure modes of genetic mediation analysis and demonstrate how to evaluate the effects of measurement error. While genetic mediation analysis is a powerful tool for identifying candidate genes, we recommend caution when interpreting mediation analysis findings. [ABSTRACT FROM AUTHOR]

The spiral gingers (Costus L.) are a pantropical genus of herbaceous perennial monocots; the Neotropical clade of Costus radiated rapidly in the past few million years into over 60 species. The Neotropical spiral gingers have a rich history of evolutionary and ecological research that can motivate and inform modern genetic investigations. Here, we present the first 2 chromosome-level genome assemblies in the genus, for C. pulverulentus and C. lasius , and briefly compare their synteny. We assembled the C. pulverulentus genome from a combination of short-read data, Chicago and Dovetail Hi-C chromatin-proximity sequencing, and alignment with a linkage map. We annotated the genome by mapping a C. pulverulentus transcriptome and querying mapped transcripts against a protein database. We assembled the C. lasius genome with Pacific Biosciences HiFi long reads and alignment to the C. pulverulentus genome. These 2 assemblies are the first published genomes for non-cultivated tropical plants. These genomes solidify the spiral gingers as a model system and will facilitate research on the poorly understood genetic basis of tropical plant diversification. [ABSTRACT FROM AUTHOR]

The silkworm (Bombyx mori) is an important lepidopteran model insect and an industrial domestic animal traditionally used for silk production. Here, we report the genome assembly of an improved Japanese strain Nichi01, in which the cocoon yield is comparable to that of commercial silkworm strains. The integration of PacBio Sequel II long-read and ddRAD-seq-based high-density genetic linkage map achieved the highest quality genome assembly of silkworms to date; 22 of the 28 pseudomolecules contained telomeric repeats at both ends, and only four gaps were present in the assembly. A total of 452 Mbp of the assembly with an N50 of 16.614 Mbp covered 99.3% of the complete orthologs of the lepidopteran core genes. Although the genome sequence of Nichi01 and that of the previously reported low-yielding tropical strain p50T assured their accuracy in most regions, we corrected several regions, misassembled in p50T, in our assembly. A total of 18,397 proteins were predicted using over 95 Gb of mRNA-seq derived from 10 different organs, covering 96.9% of the complete orthologs of the lepidopteran core genes. The final assembly and annotation files are available in KAIKObase (https://kaikobase.dna.affrc.go.jp/index.html) along with a genome browser and BLAST searching service, which would facilitate further studies and the breeding of silkworms and other insects. [ABSTRACT FROM AUTHOR]

Motivation Efficient tapping into genomic information from a single microscopic image of an intact DNA molecule is an outstanding challenge and its solution will open new frontiers in molecular diagnostics. Here, a new computational method for optical genome mapping utilizing deep learning is presented, termed DeepOM. Utilization of a convolutional neural network, trained on simulated images of labeled DNA molecules, improves the success rate in the alignment of DNA images to genomic references. Results The method is evaluated on acquired images of human DNA molecules stretched in nano-channels. The accuracy of the method is benchmarked against state-of-the-art commercial software Bionano Solve. The results show a significant advantage in alignment success rate for molecules shorter than 50 kb. DeepOM improves the yield, sensitivity, and throughput of optical genome mapping experiments in applications of human genomics and microbiology. Availability and implementation The source code for the presented method is publicly available at https://github.com/yevgenin/DeepOM. [ABSTRACT FROM AUTHOR]

Taxonomically restricted genes (TRGs) are unique for a defined group of organisms and may act as potential genetic determinants of lineage-specific, biological properties. Here, we explore the TRGs of highly diverse and economically important Bacillus bacteria by examining commonly used TRG identification parameters and data sources. We show the significant effects of sequence similarity thresholds, composition, and the size of the reference database in the identification process. Subsequently, we applied stringent TRG search parameters and expanded the identification procedure by incorporating an analysis of noncoding and non-syntenic regions of non- Bacillus genomes. A multiplex annotation procedure minimized the number of false-positive TRG predictions and showed nearly one-third of the alleged TRGs could be mapped to genes missed in genome annotations. We traced the putative origin of TRGs by identifying homologous, noncoding genomic regions in non- Bacillus species and detected sequence changes that could transform these regions into protein-coding genes. In addition, our analysis indicated that Bacillus TRGs represent a specific group of genes mostly showing intermediate sequence properties between genes that are conserved across multiple taxa and nonannotated peptides encoded by open reading frames. [ABSTRACT FROM AUTHOR]

Objectives Polymyxins, including colistin, are the drugs of last resort to treat MDR bacterial infections in humans. In-depth understanding of the molecular basis and regulation of polymyxin resistance would provide new therapeutic opportunities to combat increasing polymyxin resistance. Here we aimed to identify novel targets that are crucial for polymyxin resistance using Escherichia coli BL21(DE3), a unique colistin-resistant model strain. Methods BL21(DE3) was subjected to random transposon mutagenesis for screening colistin-susceptible mutants. The insertion sites of desired mutants were mapped; the key genes of interest were also inactivated in different strains to examine functional conservation. Specific genes in the known PmrAB and PhoPQ regulatory network were inactivated to examine crosstalk among different pathways. Lipid A species and membrane phospholipids were analysed by normal phase LC/MS. Results Among eight mutants with increased susceptibility to colistin, five mutants contained different mutations in three genes (rseP , degS and surA) that belong to the RpoE stress response pathway. Inactivation of rpoE , pmrB , eptA or pmrD led to significantly increased susceptibility to colistin; however, inactivation of phoQ or eptB did not change colistin MIC. RpoE mutation in different E. coli and Salmonella resistant strains all led to significant reduction in colistin MIC (16–32-fold). Inactivation of rpoE did not change the lipid A profile but significantly altered the phospholipid profile. Conclusions Inactivation of the important members of the RpoE regulon in polymyxin-resistant strains led to a drastic reduction in polymyxin MIC and an increase of lysophospholipids with no change in lipid A modifications. [ABSTRACT FROM AUTHOR]

We used long-read DNA sequencing to assemble the genome of a Southern Han Chinese male. We organized the sequence into chromosomes and filled in gaps using the recently completed T2T-CHM13 genome as a guide, yielding a gap-free genome, Han1, containing 3,099,707,698 bases. Using the T2T-CHM13 annotation as a reference, we mapped all genes onto the Han1 genome and identified additional gene copies, generating a total of 60,708 putative genes, of which 20,003 are protein-coding. A comprehensive comparison between the genes revealed that 235 protein-coding genes were substantially different between the individuals, with frameshifts or truncations affecting the protein-coding sequence. Most of these were heterozygous variants in which one gene copy was unaffected. This represents the first gene-level comparison between two finished, annotated individual human genomes. [ABSTRACT FROM AUTHOR]

Argonaute 1 (AGO1), the principal protein component of microRNA-mediated regulation, plays a key role in plant growth and development. AGO1 physically interacts with the chaperone HSP90, which buffers cryptic genetic variation in plants and animals. We sought to determine whether genetic perturbation of AGO1 in Arabidopsis thaliana would also reveal cryptic genetic variation, and if so, whether AGO1-dependent loci overlap with those dependent on HSP90. To address these questions, we introgressed a hypomorphic mutant allele of AGO1 into a set of mapping lines derived from the commonly used Arabidopsis strains Col-0 and Ler. Although we identified several cases in which AGO1 buffered genetic variation, none of the AGO1-dependent loci overlapped with those buffered by HSP90 for the traits assayed. We focused on 1 buffered locus where AGO1 perturbation uncoupled the traits days to flowering and rosette leaf number, which are otherwise closely correlated. Using a bulk segregant approach, we identified a nonfunctional Ler hua2 mutant allele as the causal AGO1-buffered polymorphism. Introduction of a nonfunctional hua2 allele into a Col-0 ago1 mutant background recapitulated the Lerdependent ago1 phenotype, implying that coupling of these traits involves different molecular players in these closely related strains. Taken together, our findings demonstrate that even though AGO1 and HSP90 buffer genetic variation in the same traits, these robustness regulators interact epistatically with different genetic loci, suggesting that higher-order epistasis is uncommon. [ABSTRACT FROM AUTHOR]

The domestication history of the avocado (Persea americana) remains unclear. We created a reference genome from the Gwen varietal, which is closely related to the economically dominant Hass varietal. Our genome assembly had an N50 of 3.37 megabases, a BUSCO score of 91%, and was scaffolded with a genetic map, producing 12 pseudo-chromosomes with 49,450 genes. We used the Gwen genome as a reference to investigate population genomics, based on a sample of 34 resequenced accessions that represented the 3 botanical groups of P. americana. Our analyses were consistent with 3 separate domestication events; we estimated that the Mexican group diverged from the Lowland (formerly known as "West Indian") and Guatemalan groups >1 million years ago. We also identified putative targets of selective sweeps in domestication events; within the Guatemalan group, putative candidate genes were enriched for fruit development and ripening. We also investigated divergence between heterodichogamous flowering types, providing preliminary evidence for potential candidate genes involved in pollination and floral development. [ABSTRACT FROM AUTHOR]

Expression quantitative trait locus detection has become increasingly important for understanding how noncoding variants contribute to disease susceptibility and complex traits. The major challenges in expression quantitative trait locus fine-mapping and causal variant discovery relate to the impact of linkage disequilibrium on signals due to one or multiple functional variants that lie within a credible set. We perform expression quantitative trait locus fine-mapping using the all-but-one approach, conditioning each signal on all others detected in an interval, on the Consortium for the Architecture of Gene Expression cohorts of microarray-based peripheral blood gene expression in 2,138 European-ancestry human adults. We contrast these results with traditional forward stepwise conditional analysis and a Bayesian localization method. All-but-one conditioning significantly modifies effect-size estimates for 51% of 2,351 expression quantitative trait locus peaks, but only modestly affects credible set size and location. On the other hand, both conditioning approaches result in unexpectedly low overlap with Bayesian credible sets, with just 57% peak concordance and between 50% and 70% SNP sharing, leading us to caution against the assumption that any one localization method is superior to another. We also cross reference our results with ATAC-seq data, cell-type-specific expression quantitative trait locus, and activity-by-contact-enhancers, leading to the proposal of a 5-tier approach to further reduce credible set sizes and prioritize likely causal variants for all known inflammatory bowel disease risk loci active in immune cells. [ABSTRACT FROM AUTHOR]