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TAG. Theoretical and Applied Genetics.... Jan 2022Rising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress.... (Review)
Review
Rising temperatures and changing precipitation patterns will affect agricultural production substantially, exposing crops to extended and more intense periods of stress. Therefore, breeding of varieties adapted to the constantly changing conditions is pivotal to enable a quantitatively and qualitatively adequate crop production despite the negative effects of climate change. As it is not yet possible to select for adaptation to future climate scenarios in the field, simulations of future conditions in controlled-environment (CE) phenotyping facilities contribute to the understanding of the plant response to special stress conditions and help breeders to select ideal genotypes which cope with future conditions. CE phenotyping facilities enable the collection of traits that are not easy to measure under field conditions and the assessment of a plant's phenotype under repeatable, clearly defined environmental conditions using automated, non-invasive, high-throughput methods. However, extrapolation and translation of results obtained under controlled environments to field environments is ambiguous. This review outlines the opportunities and challenges of phenotyping approaches under controlled environments complementary to conventional field trials. It gives an overview on general principles and introduces existing phenotyping facilities that take up the challenge of obtaining reliable and robust phenotypic data on climate response traits to support breeding of climate-adapted crops.
Topics: Adaptation, Physiological; Climate Change; Droughts; Environment, Controlled; Phenotype; Plant Breeding; Plant Transpiration; Salt Stress
PubMed: 34302493
DOI: 10.1007/s00122-021-03892-1 -
Trends in Plant Science Jun 2022Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential...
Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential applications for genetic and physiological analysis of plant anatomical phenotypes.
Topics: Phenotype; Plants
PubMed: 35307268
DOI: 10.1016/j.tplants.2022.02.009 -
American Journal of Human Genetics Dec 2021Whole-genome sequencing studies applied to large populations or biobanks with extensive phenotyping raise new analytic challenges. The need to consider many variants at... (Comparative Study)
Comparative Study
Whole-genome sequencing studies applied to large populations or biobanks with extensive phenotyping raise new analytic challenges. The need to consider many variants at a locus or group of genes simultaneously and the potential to study many correlated phenotypes with shared genetic architecture provide opportunities for discovery not addressed by the traditional one variant, one phenotype association study. Here, we introduce a Bayesian model comparison approach called MRP (multiple rare variants and phenotypes) for rare-variant association studies that considers correlation, scale, and direction of genetic effects across a group of genetic variants, phenotypes, and studies, requiring only summary statistic data. We apply our method to exome sequencing data (n = 184,698) across 2,019 traits from the UK Biobank, aggregating signals in genes. MRP demonstrates an ability to recover signals such as associations between PCSK9 and LDL cholesterol levels. We additionally find MRP effective in conducting meta-analyses in exome data. Non-biomarker findings include associations between MC1R and red hair color and skin color, IL17RA and monocyte count, and IQGAP2 and mean platelet volume. Finally, we apply MRP in a multi-phenotype setting; after clustering the 35 biomarker phenotypes based on genetic correlation estimates, we find that joint analysis of these phenotypes results in substantial power gains for gene-trait associations, such as in TNFRSF13B in one of the clusters containing diabetes- and lipid-related traits. Overall, we show that the MRP model comparison approach improves upon useful features from widely used meta-analysis approaches for rare-variant association analyses and prioritizes protective modifiers of disease risk.
Topics: Bayes Theorem; Female; Genetic Variation; Genome-Wide Association Study; Humans; Male; Models, Genetic; Phenotype
PubMed: 34822764
DOI: 10.1016/j.ajhg.2021.11.005 -
American Journal of Medical Genetics.... Jun 2022Technological advances in both genome sequencing and prenatal imaging are increasing our ability to accurately recognize and diagnose Mendelian conditions prenatally....
Technological advances in both genome sequencing and prenatal imaging are increasing our ability to accurately recognize and diagnose Mendelian conditions prenatally. Phenotype-driven early genetic diagnosis of fetal genetic disease can help to strategize treatment options and clinical preventive measures during the perinatal period, to plan in utero therapies, and to inform parental decision-making. Fetal phenotypes of genetic diseases are often unique and at present are not well understood; more comprehensive knowledge about prenatal phenotypes and computational resources have an enormous potential to improve diagnostics and translational research. The Human Phenotype Ontology (HPO) has been widely used to support diagnostics and translational research in human genetics. To better support prenatal usage, the HPO consortium conducted a series of workshops with a group of domain experts in a variety of medical specialties, diagnostic techniques, as well as diseases and phenotypes related to prenatal medicine, including perinatal pathology, musculoskeletal anomalies, neurology, medical genetics, hydrops fetalis, craniofacial malformations, cardiology, neonatal-perinatal medicine, fetal medicine, placental pathology, prenatal imaging, and bioinformatics. We expanded the representation of prenatal phenotypes in HPO by adding 95 new phenotype terms under the Abnormality of prenatal development or birth (HP:0001197) grouping term, and revised definitions, synonyms, and disease annotations for most of the 152 terms that existed before the beginning of this effort. The expansion of prenatal phenotypes in HPO will support phenotype-driven prenatal exome and genome sequencing for precision genetic diagnostics of rare diseases to support prenatal care.
Topics: Infant, Newborn; Humans; Female; Pregnancy; Placenta; Computational Biology; Phenotype; Rare Diseases; Exome Sequencing
PubMed: 35872606
DOI: 10.1002/ajmg.c.31989 -
AMIA ... Annual Symposium Proceedings.... 2020Phenotyping algorithms are essential tools for conducting clinical research on observational data. Manually devel- oped phenotyping algorithms, such as those curated...
Phenotyping algorithms are essential tools for conducting clinical research on observational data. Manually devel- oped phenotyping algorithms, such as those curated within the eMERGE (electronic Medical Records and Genomics) Network, represent the gold standard but are time consuming to create. In this work, we propose a framework for learning from the structure of eMERGE phenotype concept sets to assist construction of novel phenotype definitions. We use eMERGE phenotypes as a source of reference concept sets and engineer rich features characterizing the con- cept pairs within each set. We treat these pairwise relationships as edges in a concept graph, train models to perform edge prediction, and identify candidate phenotype concept sets as highly connected subgraphs. Candidate concept sets may then be interrogated and composed to construct novel phenotype definitions.
Topics: Algorithms; Electronic Health Records; Genomics; Humans; Phenotype; Probability
PubMed: 33936484
DOI: No ID Found -
PLoS Neglected Tropical Diseases Nov 2022Advances in high-throughput and high-content imaging technologies require concomitant development of analytical software capable of handling large datasets and...
Advances in high-throughput and high-content imaging technologies require concomitant development of analytical software capable of handling large datasets and generating relevant phenotypic measurements. Several tools have been developed to analyze drug response phenotypes in parasitic and free-living worms, but these are siloed and often limited to specific instrumentation, worm species, and single phenotypes. No unified tool exists to analyze diverse high-content phenotypic imaging data of worms and provide a platform for future extensibility. We have developed wrmXpress, a unified framework for analyzing a variety of phenotypes matched to high-content experimental assays of free-living and parasitic nematodes and flatworms. We demonstrate its utility for analyzing a suite of phenotypes, including motility, development/size, fecundity, and feeding, and establish the package as a platform upon which to build future custom phenotypic modules. We show that wrmXpress can serve as an analytical workhorse for anthelmintic screening efforts across schistosomes, filarial nematodes, and free-living model nematodes and holds promise for enabling collaboration among investigators with diverse interests.
Topics: Humans; Research Personnel; Biological Assay; Culture; Fertility; Phenotype
PubMed: 36399491
DOI: 10.1371/journal.pntd.0010937 -
Genetics in Medicine : Official Journal... Sep 2023Congenital hypopituitarism (CH) disorders are phenotypically variable. Variants in multiple genes are associated with these disorders, with variable penetrance and...
PURPOSE
Congenital hypopituitarism (CH) disorders are phenotypically variable. Variants in multiple genes are associated with these disorders, with variable penetrance and inheritance.
METHODS
We screened a large cohort (N = 1765) of patients with or at risk of CH using Sanger sequencing, selected according to phenotype, and conducted next-generation sequencing (NGS) in 51 families within our cohort. We report the clinical, hormonal, and neuroradiological phenotypes of patients with variants in known genes associated with CH.
RESULTS
We identified variants in 178 patients: GH1/GHRHR (51 patients of 414 screened), PROP1 (17 of 253), POU1F1 (15 of 139), SOX2 (13 of 59), GLI2 (7 of 106), LHX3/LHX4 (8 of 110), HESX1 (8 of 724), SOX3 (9 of 354), OTX2 (5 of 59), SHH (2 of 64), and TCF7L1, KAL1, FGFR1, and FGF8 (2 of 585, respectively). NGS identified 26 novel variants in 35 patients (from 24 families). Magnetic resonance imaging showed prevalent hypothalamo-pituitary abnormalities, present in all patients with PROP1, GLI2, SOX3, HESX1, OTX2, LHX3, and LHX4 variants. Normal hypothalamo-pituitary anatomy was reported in 24 of 121, predominantly those with GH1, GHRHR, POU1F1, and SOX2 variants.
CONCLUSION
We identified variants in 10% (178 of 1765) of our CH cohort. NGS has revolutionized variant identification, and careful phenotypic patient characterization has improved our understanding of CH. We have constructed a flow chart to guide genetic analysis in these patients, which will evolve upon novel gene discoveries.
Topics: Humans; Mutation; Hypopituitarism; Transcription Factors; Phenotype; Genes, Homeobox
PubMed: 37165954
DOI: 10.1016/j.gim.2023.100881 -
Plant Communications Nov 2022Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and... (Review)
Review
Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.
Topics: Phenomics; Plant Breeding; Crops, Agricultural; Remote Sensing Technology; Phenotype
PubMed: 35655429
DOI: 10.1016/j.xplc.2022.100344 -
Cell Systems Jun 2021Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from... (Review)
Review
Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.
Topics: Biological Variation, Population; Microscopy, Fluorescence; Phenotype; Single-Cell Analysis
PubMed: 34139168
DOI: 10.1016/j.cels.2021.05.010 -
Proceedings of the National Academy of... Apr 2023Controlled population development and genome-wide association studies have proven powerful in uncovering genes and alleles underlying complex traits. An underexplored...
Controlled population development and genome-wide association studies have proven powerful in uncovering genes and alleles underlying complex traits. An underexplored dimension of such studies is the phenotypic contribution of nonadditive interactions between quantitative trait loci (QTLs). Capturing of such epistasis in a genome-wide manner requires very large populations to represent replicated combinations of loci whose interactions determine phenotypic outcomes. Here, we dissect epistasis using a densely genotyped population of 1,400 backcross inbred lines (BILs) between a modern processing tomato inbred () and the Lost Accession (LA5240) of a distant, green-fruited, drought-tolerant wild species, . The homozygous BILs, each harboring an average of 11 introgressions and their hybrids with the recurrent parents, were phenotyped for tomato yield components. Population-wide mean yield of the BILs was less than 50% of that of their hybrids (BILHs). All the homozygous introgressions across the genome reduced yield relative to recurrent parent, while several QTLs of the BILHs independently improved productivity. Analysis of two QTL scans showed 61 cases of less-than-additive interactions and 19 cases of more-than-additive interactions. Strikingly, a single epistatic interaction involving QTLs on chromosomes 1 and 7, that independently did not affect yield, increased fruit yield by 20 to 50% in the double introgression hybrid grown in irrigated and dry fields over a period of 4 y. Our work demonstrates the power of large, interspecific controlled population development to uncover hidden QTL phenotypes and how rare epistatic interactions can improve crop productivity via heterosis.
Topics: Quantitative Trait Loci; Solanum lycopersicum; Chromosome Mapping; Genome-Wide Association Study; Hybrid Vigor; Quantitative Trait, Heritable; Genes, Plant; Phenotype; Epistasis, Genetic
PubMed: 36972451
DOI: 10.1073/pnas.2205787119