Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae032
Talal Al-Yazeedi, Sally Adams, Sophie Tandonnet, Anisa Turner, Jun Kim, Junho Lee, Andre Pires-daSilva
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.
Auanema freiburgense 是一种有雄性、雌性和自交雌雄同体的线虫。当 XO 雄性与 XX 雌性交配时,它们通常会产生较低比例的 XO 后代,因为它们会消除无 X 精子。这一过程可确保大多数精子携带 X 染色体,与随机分离相比,增加了 X 染色体传递的可能性。出现这种情况的原因是精子形成过程中重要细胞器的分布不均,这可能取决于 X 染色体。精子中的某些成分被选择性地分离到 X 染色体的子细胞中,而其他成分则随着无 X 染色体的子细胞被丢弃。耐人寻味的是,两个 A. freiburgense 品系杂交后产生的杂交雄性能产生有活力的无 X 染色体精子。因此,当这些杂交雄性与雌性交配时,它们会产生高比例的雄性后代。为了揭示无精子消除和X染色体驱动的遗传基础,我们生成了弗赖堡蝇的基因组组装,并对杂交品系进行了基因分型。这项分析确定了一个定量性状基因座,该基因座跨越多个 X 染色体基因,与在弗赖堡家蚕中观察到的非孟德尔遗传模式有关。这一发现为了解雄性减数分裂过程中不对称细胞器分配的基本因素,从而了解 X 染色体的非孟德尔遗传和性别比例提供了宝贵的线索。
{"title":"The contribution of an X chromosome QTL to non-Mendelian inheritance and unequal chromosomal segregation in Auanema freiburgense.","authors":"Talal Al-Yazeedi, Sally Adams, Sophie Tandonnet, Anisa Turner, Jun Kim, Junho Lee, Andre Pires-daSilva","doi":"10.1093/genetics/iyae032","DOIUrl":"10.1093/genetics/iyae032","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075566/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae040
Patricka A Williams-Simon, Camille Oster, Jordyn A Moaton, Ronel Ghidey, Enoch Ng'oma, Kevin M Middleton, Elizabeth G King
Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants within the genes that control this trait is of high importance if we want to better comprehend thermal physiology. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource as a model system. First, we used quantitative genetics and Quantitative Trait Loci mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to (1) alter tissue-specific gene expression and (2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.
{"title":"Naturally segregating genetic variants contribute to thermal tolerance in a Drosophila melanogaster model system.","authors":"Patricka A Williams-Simon, Camille Oster, Jordyn A Moaton, Ronel Ghidey, Enoch Ng'oma, Kevin M Middleton, Elizabeth G King","doi":"10.1093/genetics/iyae040","DOIUrl":"10.1093/genetics/iyae040","url":null,"abstract":"<p><p>Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants within the genes that control this trait is of high importance if we want to better comprehend thermal physiology. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource as a model system. First, we used quantitative genetics and Quantitative Trait Loci mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to (1) alter tissue-specific gene expression and (2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075556/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140177343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae030
Dimitrios Diamantidis, Wai-Tong Louis Fan, Matthias Birkner, John Wakeley
We consider a simple diploid population-genetic model with potentially high variability of offspring numbers among individuals. Specifically, against a backdrop of Wright-Fisher reproduction and no selection, there is an additional probability that a big family occurs, meaning that a pair of individuals has a number of offspring on the order of the population size. We study how the pedigree of the population generated under this model affects the ancestral genetic process of a sample of size two at a single autosomal locus without recombination. Our population model is of the type for which multiple-merger coalescent processes have been described. We prove that the conditional distribution of the pairwise coalescence time given the random pedigree converges to a limit law as the population size tends to infinity. This limit law may or may not be the usual exponential distribution of the Kingman coalescent, depending on the frequency of big families. But because it includes the number and times of big families, it differs from the usual multiple-merger coalescent models. The usual multiple-merger coalescent models are seen as describing the ancestral process marginal to, or averaging over, the pedigree. In the limiting ancestral process conditional on the pedigree, the intervals between big families can be modeled using the Kingman coalescent but each big family causes a discrete jump in the probability of coalescence. Analogous results should hold for larger samples and other population models. We illustrate these results with simulations and additional analysis, highlighting their implications for inference and understanding of multilocus data.
{"title":"Bursts of coalescence within population pedigrees whenever big families occur.","authors":"Dimitrios Diamantidis, Wai-Tong Louis Fan, Matthias Birkner, John Wakeley","doi":"10.1093/genetics/iyae030","DOIUrl":"10.1093/genetics/iyae030","url":null,"abstract":"<p><p>We consider a simple diploid population-genetic model with potentially high variability of offspring numbers among individuals. Specifically, against a backdrop of Wright-Fisher reproduction and no selection, there is an additional probability that a big family occurs, meaning that a pair of individuals has a number of offspring on the order of the population size. We study how the pedigree of the population generated under this model affects the ancestral genetic process of a sample of size two at a single autosomal locus without recombination. Our population model is of the type for which multiple-merger coalescent processes have been described. We prove that the conditional distribution of the pairwise coalescence time given the random pedigree converges to a limit law as the population size tends to infinity. This limit law may or may not be the usual exponential distribution of the Kingman coalescent, depending on the frequency of big families. But because it includes the number and times of big families, it differs from the usual multiple-merger coalescent models. The usual multiple-merger coalescent models are seen as describing the ancestral process marginal to, or averaging over, the pedigree. In the limiting ancestral process conditional on the pedigree, the intervals between big families can be modeled using the Kingman coalescent but each big family causes a discrete jump in the probability of coalescence. Analogous results should hold for larger samples and other population models. We illustrate these results with simulations and additional analysis, highlighting their implications for inference and understanding of multilocus data.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139974078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae049
The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).
基因组资源联盟(Alliance of Genome Resources,简称 "联盟")是一个可扩展的知识库联盟,其重点是集中研究模式生物的遗传学和基因组学。联盟的组织形式为单个知识中心,与各自的研究社区和集中式软件基础设施有着紧密的联系。目前联盟中的模式生物包括芽殖酵母、优雅小鼠、果蝇、斑马鱼、青蛙、实验小鼠、实验大鼠和基因本体联盟。该项目正处于快速发展阶段,目的是协调知识、存储知识、分析知识,并通过门户网站、直接下载和应用编程接口(API)向社区展示知识。在此,我们重点介绍过去两年的发展情况。具体来说,我们添加并增强了浏览基因组(JBrowse)、下载序列、挖掘复杂数据(AllianceMine)、路径可视化、文献全文搜索(Textpresso)和序列相似性搜索(SequenceServer)等工具。我们增强了现有的交互式数据表,并添加了一个交互式旁系表,以补充我们的同源表述。为了支持单个模式生物群落,我们实施了针对特定物种的 "登陆页面",并将很快增加针对特定疾病的门户网站;此外,我们还支持使用 Discourse 软件实施的共同社区论坛。我们将介绍我们在建立中央持久数据库以支持文献整理方面取得的进展、作为协调基础的数据建模,以及在建立集成人工智能和机器学习(AI/ML)的一流文献整理系统方面取得的进展。
{"title":"Updates to the Alliance of Genome Resources central infrastructure.","authors":"","doi":"10.1093/genetics/iyae049","DOIUrl":"10.1093/genetics/iyae049","url":null,"abstract":"<p><p>The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific \"landing pages\" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075569/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140327246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vertebrate limbs start to develop as paired protrusions from the lateral plate mesoderm at specific locations of the body with forelimb buds developing anteriorly and hindlimb buds posteriorly. During the initiation process, limb progenitor cells maintain active proliferation to form protrusions and start to express Fgf10, which triggers molecular processes for outgrowth and patterning. Although both processes occur in both types of limbs, forelimbs (Tbx5), and hindlimbs (Isl1) utilize distinct transcriptional systems to trigger their development. Here, we report that Sall1 and Sall4, zinc finger transcription factor genes, regulate hindlimb initiation in mouse embryos. Compared to the 100% frequency loss of hindlimb buds in TCre; Isl1 conditional knockouts, Hoxb6Cre; Isl1 conditional knockout causes a hypomorphic phenotype with only approximately 5% of mutants lacking the hindlimb. Our previous study of SALL4 ChIP-seq showed SALL4 enrichment in an Isl1 enhancer, suggesting that SALL4 acts upstream of Isl1. Removing 1 allele of Sall4 from the hypomorphic Hoxb6Cre; Isl1 mutant background caused loss of hindlimbs, but removing both alleles caused an even higher frequency of loss of hindlimbs, suggesting a genetic interaction between Sall4 and Isl1. Furthermore, TCre-mediated conditional double knockouts of Sall1 and Sall4 displayed a loss of expression of hindlimb progenitor markers (Isl1, Pitx1, Tbx4) and failed to develop hindlimbs, demonstrating functional redundancy between Sall1 and Sall4. Our data provides genetic evidence that Sall1 and Sall4 act as master regulators of hindlimb initiation.
{"title":"Sall genes regulate hindlimb initiation in mouse embryos.","authors":"Katherine Q Chen, Hiroko Kawakami, Aaron Anderson, Dylan Corcoran, Aditi Soni, Ryuichi Nishinakamura, Yasuhiko Kawakami","doi":"10.1093/genetics/iyae029","DOIUrl":"10.1093/genetics/iyae029","url":null,"abstract":"<p><p>Vertebrate limbs start to develop as paired protrusions from the lateral plate mesoderm at specific locations of the body with forelimb buds developing anteriorly and hindlimb buds posteriorly. During the initiation process, limb progenitor cells maintain active proliferation to form protrusions and start to express Fgf10, which triggers molecular processes for outgrowth and patterning. Although both processes occur in both types of limbs, forelimbs (Tbx5), and hindlimbs (Isl1) utilize distinct transcriptional systems to trigger their development. Here, we report that Sall1 and Sall4, zinc finger transcription factor genes, regulate hindlimb initiation in mouse embryos. Compared to the 100% frequency loss of hindlimb buds in TCre; Isl1 conditional knockouts, Hoxb6Cre; Isl1 conditional knockout causes a hypomorphic phenotype with only approximately 5% of mutants lacking the hindlimb. Our previous study of SALL4 ChIP-seq showed SALL4 enrichment in an Isl1 enhancer, suggesting that SALL4 acts upstream of Isl1. Removing 1 allele of Sall4 from the hypomorphic Hoxb6Cre; Isl1 mutant background caused loss of hindlimbs, but removing both alleles caused an even higher frequency of loss of hindlimbs, suggesting a genetic interaction between Sall4 and Isl1. Furthermore, TCre-mediated conditional double knockouts of Sall1 and Sall4 displayed a loss of expression of hindlimb progenitor markers (Isl1, Pitx1, Tbx4) and failed to develop hindlimbs, demonstrating functional redundancy between Sall1 and Sall4. Our data provides genetic evidence that Sall1 and Sall4 act as master regulators of hindlimb initiation.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075541/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139933744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae044
Myra Paz David Masinas, Athanasios Litsios, Anastasia Razdaibiedina, Matej Usaj, Charles Boone, Brenda J Andrews
We previously constructed TheCellVision.org, a central repository for visualizing and mining data from yeast high-content imaging projects. At its inception, TheCellVision.org housed two high-content screening (HCS) projects providing genome-scale protein abundance and localization information for the budding yeast Saccharomyces cerevisiae, as well as a comprehensive analysis of the morphology of its endocytic compartments upon systematic genetic perturbation of each yeast gene. Here, we report on the expansion of TheCellVision.org by the addition of two new HCS projects and the incorporation of new global functionalities. Specifically, TheCellVision.org now hosts images from the Cell Cycle Omics project, which describes genome-scale cell cycle-resolved dynamics in protein localization, protein concentration, gene expression, and translational efficiency in budding yeast. Moreover, it hosts PIFiA, a computational tool for image-based predictions of protein functional annotations. Across all its projects, TheCellVision.org now houses >800,000 microscopy images along with computational tools for exploring both the images and their associated datasets. Together with the newly added global functionalities, which include the ability to query genes in any of the hosted projects using either yeast or human gene names, TheCellVision.org provides an expanding resource for single-cell eukaryotic biology.
{"title":"Expanding TheCellVision.org: a central repository for visualizing and mining high-content cell imaging projects.","authors":"Myra Paz David Masinas, Athanasios Litsios, Anastasia Razdaibiedina, Matej Usaj, Charles Boone, Brenda J Andrews","doi":"10.1093/genetics/iyae044","DOIUrl":"10.1093/genetics/iyae044","url":null,"abstract":"<p><p>We previously constructed TheCellVision.org, a central repository for visualizing and mining data from yeast high-content imaging projects. At its inception, TheCellVision.org housed two high-content screening (HCS) projects providing genome-scale protein abundance and localization information for the budding yeast Saccharomyces cerevisiae, as well as a comprehensive analysis of the morphology of its endocytic compartments upon systematic genetic perturbation of each yeast gene. Here, we report on the expansion of TheCellVision.org by the addition of two new HCS projects and the incorporation of new global functionalities. Specifically, TheCellVision.org now hosts images from the Cell Cycle Omics project, which describes genome-scale cell cycle-resolved dynamics in protein localization, protein concentration, gene expression, and translational efficiency in budding yeast. Moreover, it hosts PIFiA, a computational tool for image-based predictions of protein functional annotations. Across all its projects, TheCellVision.org now houses >800,000 microscopy images along with computational tools for exploring both the images and their associated datasets. Together with the newly added global functionalities, which include the ability to query genes in any of the hosted projects using either yeast or human gene names, TheCellVision.org provides an expanding resource for single-cell eukaryotic biology.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075560/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140190260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae037
Nicolas Morales, Mahlet T Anche, Nicholas S Kaczmar, Nicholas Lepak, Pengzun Ni, Maria Cinta Romay, Nicholas Santantonio, Edward S Buckler, Michael A Gore, Lukas A Mueller, Kelly R Robbins
Design randomizations and spatial corrections have increased understanding of genotypic, spatial, and residual effects in field experiments, but precisely measuring spatial heterogeneity in the field remains a challenge. To this end, our study evaluated approaches to improve spatial modeling using high-throughput phenotypes (HTP) via unoccupied aerial vehicle (UAV) imagery. The normalized difference vegetation index was measured by a multispectral MicaSense camera and processed using ImageBreed. Contrasting to baseline agronomic trait spatial correction and a baseline multitrait model, a two-stage approach was proposed. Using longitudinal normalized difference vegetation index data, plot level permanent environment effects estimated spatial patterns in the field throughout the growing season. Normalized difference vegetation index permanent environment were separated from additive genetic effects using 2D spline, separable autoregressive models, or random regression models. The Permanent environment were leveraged within agronomic trait genomic best linear unbiased prediction either modeling an empirical covariance for random effects, or by modeling fixed effects as an average of permanent environment across time or split among three growth phases. Modeling approaches were tested using simulation data and Genomes-to-Fields hybrid maize (Zea mays L.) field experiments in 2015, 2017, 2019, and 2020 for grain yield, grain moisture, and ear height. The two-stage approach improved heritability, model fit, and genotypic effect estimation compared to baseline models. Electrical conductance and elevation from a 2019 soil survey significantly improved model fit, while 2D spline permanent environment were most strongly correlated with the soil parameters. Simulation of field effects demonstrated improved specificity for random regression models. In summary, the use of longitudinal normalized difference vegetation index measurements increased experimental accuracy and understanding of field spatio-temporal heterogeneity.
{"title":"Spatio-temporal modeling of high-throughput multispectral aerial images improves agronomic trait genomic prediction in hybrid maize.","authors":"Nicolas Morales, Mahlet T Anche, Nicholas S Kaczmar, Nicholas Lepak, Pengzun Ni, Maria Cinta Romay, Nicholas Santantonio, Edward S Buckler, Michael A Gore, Lukas A Mueller, Kelly R Robbins","doi":"10.1093/genetics/iyae037","DOIUrl":"10.1093/genetics/iyae037","url":null,"abstract":"<p><p>Design randomizations and spatial corrections have increased understanding of genotypic, spatial, and residual effects in field experiments, but precisely measuring spatial heterogeneity in the field remains a challenge. To this end, our study evaluated approaches to improve spatial modeling using high-throughput phenotypes (HTP) via unoccupied aerial vehicle (UAV) imagery. The normalized difference vegetation index was measured by a multispectral MicaSense camera and processed using ImageBreed. Contrasting to baseline agronomic trait spatial correction and a baseline multitrait model, a two-stage approach was proposed. Using longitudinal normalized difference vegetation index data, plot level permanent environment effects estimated spatial patterns in the field throughout the growing season. Normalized difference vegetation index permanent environment were separated from additive genetic effects using 2D spline, separable autoregressive models, or random regression models. The Permanent environment were leveraged within agronomic trait genomic best linear unbiased prediction either modeling an empirical covariance for random effects, or by modeling fixed effects as an average of permanent environment across time or split among three growth phases. Modeling approaches were tested using simulation data and Genomes-to-Fields hybrid maize (Zea mays L.) field experiments in 2015, 2017, 2019, and 2020 for grain yield, grain moisture, and ear height. The two-stage approach improved heritability, model fit, and genotypic effect estimation compared to baseline models. Electrical conductance and elevation from a 2019 soil survey significantly improved model fit, while 2D spline permanent environment were most strongly correlated with the soil parameters. Simulation of field effects demonstrated improved specificity for random regression models. In summary, the use of longitudinal normalized difference vegetation index measurements increased experimental accuracy and understanding of field spatio-temporal heterogeneity.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140102686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae035
Evelina Y Basenko, Achchuthan Shanmugasundram, Ulrike Böhme, David Starns, Paul A Wilkinson, Helen R Davison, Kathryn Crouch, Gareth Maslen, Omar S Harb, Beatrice Amos, Mary Ann McDowell, Jessica C Kissinger, David S Roos, Andrew Jones
FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species.
{"title":"What is new in FungiDB: a web-based bioinformatics platform for omics-scale data analysis for fungal and oomycete species.","authors":"Evelina Y Basenko, Achchuthan Shanmugasundram, Ulrike Böhme, David Starns, Paul A Wilkinson, Helen R Davison, Kathryn Crouch, Gareth Maslen, Omar S Harb, Beatrice Amos, Mary Ann McDowell, Jessica C Kissinger, David S Roos, Andrew Jones","doi":"10.1093/genetics/iyae035","DOIUrl":"10.1093/genetics/iyae035","url":null,"abstract":"<p><p>FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075537/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140289363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae007
Kim M Rutherford, Manuel Lera-Ramírez, Valerie Wood
PomBase (https://www.pombase.org), the model organism database (MOD) for fission yeast, was recently awarded Global Core Biodata Resource (GCBR) status by the Global Biodata Coalition (GBC; https://globalbiodata.org/) after a rigorous selection process. In this MOD review, we present PomBase's continuing growth and improvement over the last 2 years. We describe these improvements in the context of the qualitative GCBR indicators related to scientific quality, comprehensivity, accelerating science, user stories, and collaborations with other biodata resources. This review also showcases the depth of existing connections both within the biocuration ecosystem and between PomBase and its user community.
{"title":"PomBase: a Global Core Biodata Resource-growth, collaboration, and sustainability.","authors":"Kim M Rutherford, Manuel Lera-Ramírez, Valerie Wood","doi":"10.1093/genetics/iyae007","DOIUrl":"10.1093/genetics/iyae007","url":null,"abstract":"<p><p>PomBase (https://www.pombase.org), the model organism database (MOD) for fission yeast, was recently awarded Global Core Biodata Resource (GCBR) status by the Global Biodata Coalition (GBC; https://globalbiodata.org/) after a rigorous selection process. In this MOD review, we present PomBase's continuing growth and improvement over the last 2 years. We describe these improvements in the context of the qualitative GCBR indicators related to scientific quality, comprehensivity, accelerating science, user stories, and collaborations with other biodata resources. This review also showcases the depth of existing connections both within the biocuration ecosystem and between PomBase and its user community.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075564/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139906737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-07DOI: 10.1093/genetics/iyae042
Nikolaos Minadakis, Lars Kaderli, Robert Horvath, Yann Bourgeois, Wenbo Xu, Michael Thieme, Daniel P Woods, Anne C Roulin
Synchronizing the timing of reproduction with the environment is crucial in the wild. Among the multiple mechanisms, annual plants evolved to sense their environment, the requirement of cold-mediated vernalization is a major process that prevents individuals from flowering during winter. In many annual plants including crops, both a long and short vernalization requirement can be observed within species, resulting in so-called early-(spring) and late-(winter) flowering genotypes. Here, using the grass model Brachypodium distachyon, we explored the link between flowering-time-related traits (vernalization requirement and flowering time), environmental variation, and diversity at flowering-time genes by combining measurements under greenhouse and outdoor conditions. These experiments confirmed that B. distachyon natural accessions display large differences regarding vernalization requirements and ultimately flowering time. We underline significant, albeit quantitative effects of current environmental conditions on flowering-time-related traits. While disentangling the confounding effects of population structure on flowering-time-related traits remains challenging, population genomics analyses indicate that well-characterized flowering-time genes may contribute significantly to flowering-time variation and display signs of polygenic selection. Flowering-time genes, however, do not colocalize with genome-wide association peaks obtained with outdoor measurements, suggesting that additional genetic factors contribute to flowering-time variation in the wild. Altogether, our study fosters our understanding of the polygenic architecture of flowering time in a natural grass system and opens new avenues of research to investigate the gene-by-environment interaction at play for this trait.
{"title":"Polygenic architecture of flowering time and its relationship with local environments in the grass Brachypodium distachyon.","authors":"Nikolaos Minadakis, Lars Kaderli, Robert Horvath, Yann Bourgeois, Wenbo Xu, Michael Thieme, Daniel P Woods, Anne C Roulin","doi":"10.1093/genetics/iyae042","DOIUrl":"10.1093/genetics/iyae042","url":null,"abstract":"<p><p>Synchronizing the timing of reproduction with the environment is crucial in the wild. Among the multiple mechanisms, annual plants evolved to sense their environment, the requirement of cold-mediated vernalization is a major process that prevents individuals from flowering during winter. In many annual plants including crops, both a long and short vernalization requirement can be observed within species, resulting in so-called early-(spring) and late-(winter) flowering genotypes. Here, using the grass model Brachypodium distachyon, we explored the link between flowering-time-related traits (vernalization requirement and flowering time), environmental variation, and diversity at flowering-time genes by combining measurements under greenhouse and outdoor conditions. These experiments confirmed that B. distachyon natural accessions display large differences regarding vernalization requirements and ultimately flowering time. We underline significant, albeit quantitative effects of current environmental conditions on flowering-time-related traits. While disentangling the confounding effects of population structure on flowering-time-related traits remains challenging, population genomics analyses indicate that well-characterized flowering-time genes may contribute significantly to flowering-time variation and display signs of polygenic selection. Flowering-time genes, however, do not colocalize with genome-wide association peaks obtained with outdoor measurements, suggesting that additional genetic factors contribute to flowering-time variation in the wild. Altogether, our study fosters our understanding of the polygenic architecture of flowering time in a natural grass system and opens new avenues of research to investigate the gene-by-environment interaction at play for this trait.</p>","PeriodicalId":48925,"journal":{"name":"Genetics","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11075549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140177344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}