Journal articles on the topic 'Phenotypes'
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Catalán, Pablo, Andreas Wagner, Susanna Manrubia, and José A. Cuesta. "Adding levels of complexity enhances robustness and evolvability in a multilevel genotype–phenotype map." Journal of The Royal Society Interface 15, no. 138 (January 2018): 20170516. http://dx.doi.org/10.1098/rsif.2017.0516.
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Robustness and evolvability are the main properties that account for the stability and accessibility of phenotypes. They have been studied in a number of computational genotype–phenotype maps. In this paper, we study a metabolic genotype–phenotype map defined in toyLIFE , a multilevel computational model that represents a simplified cellular biology. toyLIFE includes several levels of phenotypic expression, from proteins to regulatory networks to metabolism. Our results show that toyLIFE shares many similarities with other seemingly unrelated computational genotype–phenotype maps. Thus, toyLIFE shows a high degeneracy in the mapping from genotypes to phenotypes, as well as a highly skewed distribution of phenotypic abundances. The neutral networks associated with abundant phenotypes are highly navigable, and common phenotypes are close to each other in genotype space. All of these properties are remarkable, as toyLIFE is built on a version of the HP protein-folding model that is neither robust nor evolvable: phenotypes cannot be mutually accessed through point mutations. In addition, both robustness and evolvability increase with the number of genes in a genotype. Therefore, our results suggest that adding levels of complexity to the mapping of genotypes to phenotypes and increasing genome size enhances both these properties.
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von Both, Ulrich, Anna Buerckstuemmer, Kirsten Fluegge, and Reinhard Berner. "Heterogeneity of Genotype-Phenotype Correlation among Macrolide-Resistant Streptococcus agalactiae Isolates." Antimicrobial Agents and Chemotherapy 49, no. 7 (July 2005): 3080–82. http://dx.doi.org/10.1128/aac.49.7.3080-3082.2005.
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ABSTRACT Seventy-four erythromycin-resistant group B Streptococcus isolates were analyzed regarding their phenotype-genotype and phenotype-serotype correlation. Four different phenotypes were assessed, one of them for the first time. ermB and ermTR were the most frequent genotypes (80%). The most prevalent serotype III showed great phenotypic variability while serotype V was strongly associated only with two different phenotypes.
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Volkova, G. V., O. A. Kudinova, and O. F. Vaganova. "Diversity of virulence phenotypes of Puccinia triticinain different agroclimatic zones of the North Caucasus." Rossiiskaia selskokhoziaistvennaia nauka, no. 6 (December 15, 2019): 23–26. http://dx.doi.org/10.31857/s2500-26272019623-26.
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The phenotypic composition of the North Caucasian population of wheat leaf rust pathogen (Puccinia triticina Erikks.) in various agro-climatic zones of the region in 2016-2018 is analyzed. 233 single pustule isolates were studied, of which 212 virulence phenotypes were identified. In all the years of research, a high level of population diversity was established (the Shannon index (Sh) was 0.92-0.99). The dominant phenotype in 2016 was the PHRS phenotype, which was identified in the southern foothill, western Azov and eastern steppe agro-climatic zones. In the population of 2016, phenotypes with a high and medium number of virulence genes prevailed. In 2017, the most represented are the phenotypes of DCRL, LBLL (Western Azov zone) and PCQB (Northern zone). Avirulent phenotype BBBB was common for populations of 20162018. In 2016, a phenotype with virulence to Lr9 (TLGS) was first detected. In 2017 and 2018, phenotypes virulent to the Lr24 gene (PKTT, SFGQ, CFPQ, TKTS, MKTT, LKSR) were detected in the populations of the fungus. A high level of population differences in phenotypic composition between the years of research was established (Rogers index (R) was 0.96 -0.99).
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Zhang, Tracy D., Scott C. Kolbe, Leah C. Beauchamp, Ella K. Woodbridge, David I. Finkelstein, and Emma L. Burrows. "How Well Do Rodent Models of Parkinson’s Disease Recapitulate Early Non-Motor Phenotypes? A Systematic Review." Biomedicines 10, no. 12 (November 24, 2022): 3026. http://dx.doi.org/10.3390/biomedicines10123026.
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The prodromal phase of Parkinson’s disease (PD) is characterised by many non-motor symptoms, and these have recently been posited to be predictive of later diagnosis. Genetic rodent models can develop non-motor phenotypes, providing tools to identify mechanisms underlying the early development of PD. However, it is not yet clear how reproducible non-motor phenotypes are amongst genetic PD rodent models, whether phenotypes are age-dependent, and the translatability of these phenotypes has yet to be explored. A systematic literature search was conducted on studies using genetic PD rodent models to investigate non-motor phenotypes; cognition, anxiety/depressive-like behaviour, gastrointestinal (GI) function, olfaction, circadian rhythm, cardiovascular and urinary function. In total, 51 genetic models of PD across 150 studies were identified. We found outcomes of most phenotypes were inconclusive due to inadequate studies, assessment at different ages, or variation in experimental and environmental factors. GI dysfunction was the most reproducible phenotype across all genetic rodent models. The mouse model harbouring mutant A53T, and the wild-type hα-syn overexpression (OE) model recapitulated the majority of phenotypes, albeit did not reliably produce concurrent motor deficits and nigral cell loss. Furthermore, animal models displayed different phenotypic profiles, reflecting the distinct genetic risk factors and heterogeneity of disease mechanisms. Currently, the inconsistent phenotypes within rodent models pose a challenge in the translatability and usefulness for further biomechanistic investigations. This review highlights opportunities to improve phenotype reproducibility with an emphasis on phenotypic assay choice and robust experimental design.
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Angelone, Steven, Iván Piña-Torres, Israel Padilla-Guerrero, and Michael Bidochka. "“Sleepers” and “Creepers”: A Theoretical Study of Colony Polymorphisms in the Fungus Metarhizium Related to Insect Pathogenicity and Plant Rhizosphere Colonization." Insects 9, no. 3 (August 17, 2018): 104. http://dx.doi.org/10.3390/insects9030104.
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Different strains of Metarhizium exhibit a range of polymorphisms in colony phenotypes. These phenotypes range from highly conidiating colonies to colonies that produce relatively more mycelia and few conidia. These different phenotypes are exhibited in infected insects in the soil. In this paper, we provide a theoretical consideration of colony polymorphisms and suggest that these phenotypes represent a range of strategies in the soil that Metarhizium exhibits. We call these different strategies “sleepers” and “creepers”. The “sleeper” phenotype produces relatively greater amounts of conidia. We use the term “sleeper” to identify this phenotype since this strategy is to remain in the soil as conidia in a relatively metabolically inactive state until a host insect or plant encounter these conidia. The “creeper” phenotype is predominantly a mycelial phenotype. In this strategy, hyphae move through the soil until a host insect or plant is encountered. We theoretically model the costs and benefits of these phenotypic polymorphisms and suggest how evolution could possibly select for these different strategies.
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Adams, Dean C., and Michael L. Collyer. "Phylogenetic Comparative Methods and the Evolution of Multivariate Phenotypes." Annual Review of Ecology, Evolution, and Systematics 50, no. 1 (November 2, 2019): 405–25. http://dx.doi.org/10.1146/annurev-ecolsys-110218-024555.
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Evolutionary biology is multivariate, and advances in phylogenetic comparative methods for multivariate phenotypes have surged to accommodate this fact. Evolutionary trends in multivariate phenotypes are derived from distances and directions between species in a multivariate phenotype space. For these patterns to be interpretable, phenotypes should be characterized by traits in commensurate units and scale. Visualizing such trends, as is achieved with phylomorphospaces, should continue to play a prominent role in macroevolutionary analyses. Evaluating phylogenetic generalized least squares (PGLS) models (e.g., phylogenetic analysis of variance and regression) is valuable, but using parametric procedures is limited to only a few phenotypic variables. In contrast, nonparametric, permutation-based PGLS methods provide a flexible alternative and are thus preferred for high-dimensional multivariate phenotypes. Permutation-based methods for evaluating covariation within multivariate phenotypes are also well established and can test evolutionary trends in phenotypic integration. However, comparing evolutionary rates and modes in multivariate phenotypes remains an important area of future development.
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Iwasaki, Takeshi, Hiroshi Doi, Hideaki Tsuji, Yuya Tabuchi, Motomu Hashimoto, Koji Kitagori, Shuji Akizuki, et al. "Phenotypic landscape of systemic lupus erythematosus: An analysis of the Kyoto Lupus Cohort." Modern Rheumatology 32, no. 3 (August 12, 2021): 571–76. http://dx.doi.org/10.1093/mr/roab020.
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ABSTRACT Objectives The present study aimed to clarify comprehensive relationships among the clinical variables of systemic lupus erythematosus (SLE). Methods We retrospectively surveyed 32 clinical variables in 581 patients and conducted comprehensive association studies among SLE clinical phenotypes. A univariate analysis of all possible combinations was performed, and the results of phenotypic correlations were reduced into two dimensions. We also created a regression formula using L1 regularisation (LASSO) to calculate the probability of exhibiting each phenotype. Results The univariate analysis identified 26 correlations, including multiple phenotypes with low complement. Some unpredicted correlations were identified, including fever and the anti-Sm antibody (odds ratio; OR = 2.3, p = 1.6 × 10–5) or thrombocytopenia and psychosis (OR = 3.7, p = 3.2 × 10–5). The multivariate analysis accurately estimated the probability of exhibiting each phenotype (area under the curve > 0.7) in 10 out of 20 phenotypes. Conclusions The present results show the phenotypic architecture of SLE and represent a model for estimating the probability of exhibiting each phenotype. They also offer insights into the pathology of SLE and estimating the probability of the onset of new phenotypes in clinical practice.
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Ju, Meizhi, Andrea D. Short, Paul Thompson, Nawar Diar Bakerly, Georgios V. Gkoutos, Loukia Tsaprouni, and Sophia Ananiadou. "Annotating and detecting phenotypic information for chronic obstructive pulmonary disease." JAMIA Open 2, no. 2 (April 26, 2019): 261–71. http://dx.doi.org/10.1093/jamiaopen/ooz009.
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Abstract Objectives Chronic obstructive pulmonary disease (COPD) phenotypes cover a range of lung abnormalities. To allow text mining methods to identify pertinent and potentially complex information about these phenotypes from textual data, we have developed a novel annotated corpus, which we use to train a neural network-based named entity recognizer to detect fine-grained COPD phenotypic information. Materials and methods Since COPD phenotype descriptions often mention other concepts within them (proteins, treatments, etc.), our corpus annotations include both outermost phenotype descriptions and concepts nested within them. Our neural layered bidirectional long short-term memory conditional random field (BiLSTM-CRF) network firstly recognizes nested mentions, which are fed into subsequent BiLSTM-CRF layers, to help to recognize enclosing phenotype mentions. Results Our corpus of 30 full papers (available at: http://www.nactem.ac.uk/COPD) is annotated by experts with 27 030 phenotype-related concept mentions, most of which are automatically linked to UMLS Metathesaurus concepts. When trained using the corpus, our BiLSTM-CRF network outperforms other popular approaches in recognizing detailed phenotypic information. Discussion Information extracted by our method can facilitate efficient location and exploration of detailed information about phenotypes, for example, those specifically concerning reactions to treatments. Conclusion The importance of our corpus for developing methods to extract fine-grained information about COPD phenotypes is demonstrated through its successful use to train a layered BiLSTM-CRF network to extract phenotypic information at various levels of granularity. The minimal human intervention needed for training should permit ready adaption to extracting phenotypic information about other diseases.
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Monés, Jordi, and Marc Biarnés. "Geographic atrophy phenotype identification by cluster analysis." British Journal of Ophthalmology 102, no. 3 (July 20, 2017): 388–92. http://dx.doi.org/10.1136/bjophthalmol-2017-310268.
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Background/aimsTo identify ocular phenotypes in patients with geographic atrophy secondary to age-related macular degeneration (GA) using a data-driven cluster analysis.MethodsThis was a retrospective analysis of data from a prospective, natural history study of patients with GA who were followed for ≥6 months. Cluster analysis was used to identify subgroups within the population based on the presence of several phenotypic features: soft drusen, reticular pseudodrusen (RPD), primary foveal atrophy, increased fundus autofluorescence (FAF), greyish FAF appearance and subfoveal choroidal thickness (SFCT). A comparison of features between the subgroups was conducted, and a qualitative description of the new phenotypes was proposed. The atrophy growth rate between phenotypes was then compared.ResultsData were analysed from 77 eyes of 77 patients with GA. Cluster analysis identified three groups: phenotype 1 was characterised by high soft drusen load, foveal atrophy and slow growth; phenotype 3 showed high RPD load, extrafoveal and greyish FAF appearance and thin SFCT; the characteristics of phenotype 2 were midway between phenotypes 1 and 3. Phenotypes differed in all measured features (p≤0.013), with decreases in the presence of soft drusen, foveal atrophy and SFCT seen from phenotypes 1 to 3 and corresponding increases in high RPD load, high FAF and greyish FAF appearance. Atrophy growth rate differed between phenotypes 1, 2 and 3 (0.63, 1.91 and 1.73 mm2/year, respectively, p=0.0005).ConclusionCluster analysis identified three distinct phenotypes in GA. One of them showed a particularly slow growth pattern.
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Greenbury, Sam F., Iain G. Johnston, Ard A. Louis, and Sebastian E. Ahnert. "A tractable genotype–phenotype map modelling the self-assembly of protein quaternary structure." Journal of The Royal Society Interface 11, no. 95 (June 6, 2014): 20140249. http://dx.doi.org/10.1098/rsif.2014.0249.
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The mapping between biological genotypes and phenotypes is central to the study of biological evolution. Here, we introduce a rich, intuitive and biologically realistic genotype–phenotype (GP) map that serves as a model of self-assembling biological structures, such as protein complexes, and remains computationally and analytically tractable. Our GP map arises naturally from the self-assembly of polyomino structures on a two-dimensional lattice and exhibits a number of properties: redundancy (genotypes vastly outnumber phenotypes), phenotype bias (genotypic redundancy varies greatly between phenotypes), genotype component disconnectivity (phenotypes consist of disconnected mutational networks) and shape space covering (most phenotypes can be reached in a small number of mutations). We also show that the mutational robustness of phenotypes scales very roughly logarithmically with phenotype redundancy and is positively correlated with phenotypic evolvability. Although our GP map describes the assembly of disconnected objects, it shares many properties with other popular GP maps for connected units, such as models for RNA secondary structure or the hydrophobic-polar (HP) lattice model for protein tertiary structure. The remarkable fact that these important properties similarly emerge from such different models suggests the possibility that universal features underlie a much wider class of biologically realistic GP maps.
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Cerqueira, Juliana X. M., Päivi Saavalainen, Kalle Kurppa, Pilvi Laurikka, Heini Huhtala, Matti Nykter, Lotta L. E. Koskinen, et al. "Independent and cumulative coeliac disease-susceptibility loci are associated with distinct disease phenotypes." Journal of Human Genetics 66, no. 6 (January 15, 2021): 613–23. http://dx.doi.org/10.1038/s10038-020-00888-5.
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AbstractThe phenotype of coeliac disease varies considerably for incompletely understood reasons. We investigated whether established coeliac disease susceptibility variants (SNPs) are individually or cumulatively associated with distinct phenotypes. We also tested whether a polygenic risk score (PRS) based on genome-wide associated (GWA) data could explain the phenotypic variation. The phenotypic association of 39 non-HLA coeliac disease SNPs was tested in 625 thoroughly phenotyped coeliac disease patients and 1817 controls. To assess their cumulative effects a weighted genetic risk score (wGRS39) was built, and stratified by tertiles. In our PRS model in cases, we took the summary statistics from the largest GWA study in coeliac disease and tested their association at eight P value thresholds (PT) with phenotypes. Altogether ten SNPs were associated with distinct phenotypes after correction for multiple testing (PEMP2 ≤ 0.05). The TLR7/TLR8 locus was associated with disease onset before and the SH2B3/ATXN2, ITGA4/UBE2E3 and IL2/IL21 loci after 7 years of age. The latter three loci were associated with a more severe small bowel mucosal damage and SH2B3/ATXN2 with type 1 diabetes. Patients at the highest wGRS39 tertiles had OR > 1.62 for having coeliac disease-related symptoms during childhood, a more severe small bowel mucosal damage, malabsorption and anaemia. PRS was associated only with dermatitis herpetiformis (PT = 0.2, PEMP2 = 0.02). Independent coeliac disease-susceptibility loci are associated with distinct phenotypes, suggesting that genetic factors play a role in determining the disease presentation. Moreover, the increased number of coeliac disease susceptibility SNPs might predispose to a more severe disease course.
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Wang, Huiling, Mian Lv, Yonghong Huang, Xiaoming Pan, and Changyuan Wei. "Identification of Circulating Tumor Cell Phenotype in Differentiated Thyroid Carcinoma." Journal of Biomaterials and Tissue Engineering 12, no. 4 (April 1, 2022): 813–19. http://dx.doi.org/10.1166/jbt.2022.2957.
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Objective: Circulating tumor cells (CTCs) have been considered as the origin of tumor metastasis and recurrence, which always indicate a poor prognosis. There are three phenotypes of CTCs according on different epithelial-to-mesenchymal transition (EMT) markers, including epithelial, mesenchymal, and epithelial/mesenchymal (mixed phenotypic) CTCs. We intended to explore the relationship among CTC phenotypes and the clinicopathological characteristics of patients with differentiated thyroid carcinoma (DTC). Methods: Peripheral blood samples from 58 patients with DTC were collected, and CTCs were isolated by cell sizes. To identify phenotypes of CTCs, branched DNA signal amplification technology was adopted to capture and amplify target sequences, and then multiplex RNA-in situ hybridization (RNA-ISH) assay was used to identify CTC phenotypes depended on epithelial-mesenchymal transition (EMT) markers. Results: The positive rate of CTCs was 77.59% in 58 DTC patients. Totally, 488 CTCs with detective phenotype were found. Among them, there were 121 (24.80%) epithelial CTCs, 67 (13.72%) mesenchymal CTCs, and 300 (61.48%) mixed phenotypic CTCs. An obvious increased epithelial CTCs was observed in male patients compared with female. Notably, CTCs were more prevailing in younger male patients with ETI and bilateral focus. Conclusions: The CTCs are common in DTC patients, and mixed phenotypic is the major phenotype, indicating that EMT is prevalent in DTC even though its prognosis was better than other epithelial tumors. Detection of CTC and its phenotypes might independently predict the prognosis of DTC.
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Feldman, Marcus W., Freddy B. Christiansen, and Sarah P. Otto. "Gene-culture co-evolution: teaching, learning, and correlations between relatives." Israel Journal of Ecology and Evolution 59, no. 2 (May 18, 2013): 72–91. http://dx.doi.org/10.1080/15659801.2013.853435.
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Heritability, the fraction of phenotypic variance attributable to the action of genes, is usually derived from a linear statistical partition of variance. In this paper we study a dichotomous phenotype whose transmission from parents to offspring depends on the parents’ phenotypes and the offspring’s genotype. Each individual is then represented as a phenogenotype. We derive expressions for each component of phenotypic variance and for covariances between relatives of various degrees. The resulting heritability estimates vary with the rates of phenotypic transmission as well as with the genetic contribution to the phenotype. Assortative mating by phenotype in parents is also shown to contribute to the correlations between relatives. In addition, we show that the frequency of alleles at genes affecting the phenotypes strongly affects standard heritability measures. This is important because for most complex traits these allele frequencies cannot be ascertained.
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Minelli, Alessandro, and Giuseppe Fusco. "Developmental plasticity and the evolution of animal complex life cycles." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1540 (February 27, 2010): 631–40. http://dx.doi.org/10.1098/rstb.2009.0268.
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Metazoan life cycles can be complex in different ways. A number of diverse phenotypes and reproductive events can sequentially occur along the cycle, and at certain stages a variety of developmental and reproductive options can be available to the animal, the choice among which depends on a combination of organismal and environmental conditions. We hypothesize that a diversity of phenotypes arranged in developmental sequence throughout an animal's life cycle may have evolved by genetic assimilation of alternative phenotypes originally triggered by environmental cues. This is supported by similarities between the developmental mechanisms mediating phenotype change and alternative phenotype determination during ontogeny and the common ecological condition that favour both forms of phenotypic variation. The comparison of transcription profiles from different developmental stages throughout a complex life cycle with those from alternative phenotypes in closely related polyphenic animals is expected to offer critical evidence upon which to evaluate our hypothesis.
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Seo, Jieun, Saeam Shin, Sang-woon Kim, Su Jin Kim, Myeongseob Lee, Kyungchul Song, Junghwan Suh, et al. "The Genotype-Phenotype Correlation in Human 5α-Reductase Type 2 Deficiency: Classified and Analyzed from a SRD5A2 Structural Perspective." International Journal of Molecular Sciences 24, no. 4 (February 7, 2023): 3297. http://dx.doi.org/10.3390/ijms24043297.
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The phenotype of the 5α-reductase type 2 deficiency (5αRD2) by the SRD5A2 gene mutation varies, and although there have been many attempts, the genotype-phenotype correlation still has not yet been adequately evaluated. Recently, the crystal structure of the 5α-reductase type 2 isozyme (SRD5A2) has been determined. Therefore, the present study retrospectively evaluated the genotype-phenotype correlation from a structural perspective in 19 Korean patients with 5αRD2. Additionally, variants were classified according to structural categories, and phenotypic severity was compared with previously published data. The p.R227Q variant, which belongs to the NADPH-binding residue mutation category, exhibited a more masculine phenotype (higher external masculinization score) than other variants. Furthermore, compound heterozygous mutations with p.R227Q mitigated phenotypic severity. Similarly, other mutations in this category showed mild to moderate phenotypes. Conversely, the variants categorized as structure-destabilizing and small to bulky residue mutations showed moderate to severe phenotypes, and those categorized as catalytic site and helix-breaking mutations exhibited severe phenotypes. Therefore, the SRD5A2 structural approach suggested that a genotype-phenotype correlation does exist in 5αRD2. Furthermore, the categorization of SRD5A2 gene variants according to the SRD5A2 structure facilitates the prediction of the severity of 5αRD2 and the management and genetic counseling of patients affected by it.
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Jin, Xiaoqin, and Gang Shi. "Kernel-based gene–environment interaction tests for rare variants with multiple quantitative phenotypes." PLOS ONE 17, no. 10 (October 12, 2022): e0275929. http://dx.doi.org/10.1371/journal.pone.0275929.
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Previous studies have suggested that gene–environment interactions (GEIs) between a common variant and an environmental factor can influence multiple correlated phenotypes simultaneously, that is, GEI pleiotropy, and that analyzing multiple phenotypes jointly is more powerful than analyzing phenotypes separately by using single-phenotype GEI tests. Methods to test the GEI for rare variants with multiple phenotypes are, however, lacking. In our work, we model the correlation among the GEI effects of a variant on multiple quantitative phenotypes through four kernels and propose four multiphenotype GEI tests for rare variants, which are a test with a homogeneous kernel (Hom-GEI), a test with a heterogeneous kernel (Het-GEI), a test with a projection phenotype kernel (PPK-GEI) and a test with a linear phenotype kernel (LPK-GEI). Through numerical simulations, we show that correlation among phenotypes can enhance the statistical power except for LPK-GEI, which simply combines statistics from single-phenotype GEI tests and ignores the phenotypic correlations. Among almost all considered scenarios, Het-GEI and PPK-GEI are more powerful than Hom-GEI and LPK-GEI. We apply Het-GEI and PPK-GEI in the genome-wide GEI analysis of systolic blood pressure (SBP) and diastolic blood pressure (DBP) in the UK Biobank. We analyze 18,101 genes and find that LEUTX is associated with SBP and DBP (p = 2.20×10−6) through its interaction with hemoglobin. The single-phenotype GEI test and our multiphenotype GEI tests Het-GEI and PPK-GEI are also used to evaluate the gene–hemoglobin interactions for 22 genes that were previously reported to be associated with SBP or DBP in a meta-analysis of genetic main effects. MYO1C shows nominal significance (p < 0.05) by the Het-GEI test. NOS3 shows nominal significance in DBP and MYO1C in both SBP and DBP by the single-phenotype GEI test.
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Amaral, Gilda Rose S., Graciela M. Dias, Michiyo Wellington-Oguri, Luciane Chimetto, Mariana E. Campeão, Fabiano L. Thompson, and Cristiane C. Thompson. "Genotype to phenotype: identification of diagnostic vibrio phenotypes using whole genome sequences." International Journal of Systematic and Evolutionary Microbiology 64, Pt_2 (February 1, 2014): 357–65. http://dx.doi.org/10.1099/ijs.0.057927-0.
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Vibrios are ubiquitous in the aquatic environment and can be found in association with animal or plant hosts. The range of ecological relationships includes pathogenic and mutualistic associations. To gain a better understanding of the ecology of these microbes, it is important to determine their phenotypic features. However, the traditional phenotypic characterization of vibrios has been expensive, time-consuming and restricted in scope to a limited number of features. In addition, most of the commercial systems applied for phenotypic characterization cannot characterize the broad spectrum of environmental strains. A reliable and possible alternative is to obtain phenotypic information directly from whole genome sequences. The aim of the present study was to evaluate the usefulness of whole genome sequences as a source of phenotypic information. We performed a comparison of the vibrio phenotypes obtained from the literature with the phenotypes obtained from whole genome sequences. We observed a significant correlation between the previously published phenotypic data and the phenotypic data retrieved from whole genome sequences of vibrios. Analysis of 26 vibrio genomes revealed that all genes coding for the specific proteins involved in the metabolic pathways responsible for positive phenotypes of the 14 diagnostic features (Voges–Proskauer reaction, indole production, arginine dihydrolase, ornithine decarboxylase, utilization of myo-inositol, sucrose and l-leucine, and fermentation of d-mannitol, d-sorbitol, l-arabinose, trehalose, cellobiose, d-mannose and d-galactose) were found in the majority of the vibrios genomes. Vibrio species that were negative for a given phenotype revealed the absence of all or several genes involved in the respective biochemical pathways, indicating the utility of this approach to characterize the phenotypes of vibrios. The absence of the global regulation and regulatory proteins in the Vibrio parahaemolyticus genome indicated a non-vibrio phenotype. Whole genome sequences represent an important source for the phenotypic identification of vibrios.
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Wu, Bizhi, Hangxiao Zhang, Limei Lin, Huiyuan Wang, Yubang Gao, Liangzhen Zhao, Yi-Ping Phoebe Chen, Riqing Chen, and Lianfeng Gu. "A Similarity Searching System for Biological Phenotype Images Using Deep Convolutional Encoder-decoder Architecture." Current Bioinformatics 14, no. 7 (September 17, 2019): 628–39. http://dx.doi.org/10.2174/1574893614666190204150109.
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Background: The BLAST (Basic Local Alignment Search Tool) algorithm has been widely used for sequence similarity searching. Analogously, the public phenotype images must be efficiently retrieved using biological images as queries and identify the phenotype with high similarity. Due to the accumulation of genotype-phenotype-mapping data, a system of searching for similar phenotypes is not available due to the bottleneck of image processing. Objective: In this study, we focus on the identification of similar query phenotypic images by searching the biological phenotype database, including information about loss-of-function and gain-of-function. Methods: We propose a deep convolutional autoencoder architecture to segment the biological phenotypic images and develop a phenotype retrieval system to enable a better understanding of genotype–phenotype correlation. Results: This study shows how deep convolutional autoencoder architecture can be trained on images from biological phenotypes to achieve state-of-the-art performance in a phenotypic images retrieval system. Conclusion: Taken together, the phenotype analysis system can provide further information on the correlation between genotype and phenotype. Additionally, it is obvious that the neural network model of image segmentation and the phenotype retrieval system is equally suitable for any species, which has enough phenotype images to train the neural network.
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Jiménez, Alba, James Cotterell, Andreea Munteanu, and James Sharpe. "Dynamics of gene circuits shapes evolvability." Proceedings of the National Academy of Sciences 112, no. 7 (February 2, 2015): 2103–8. http://dx.doi.org/10.1073/pnas.1411065112.
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To what extent does the dynamical mechanism producing a specific biological phenotype bias the ability to evolve into novel phenotypes? We use the interpretation of a morphogen gradient into a single stripe of gene expression as a model phenotype. Although there are thousands of three-gene circuit topologies that can robustly develop a stripe of gene expression, the vast majority of these circuits use one of just six fundamentally different dynamical mechanisms. Here we explore the potential for gene circuits that use each of these six mechanisms to evolve novel phenotypes such as multiple stripes, inverted stripes, and gradients of gene expression. Through a comprehensive and systematic analysis, we find that circuits that use alternative mechanisms differ in the likelihood of reaching novel phenotypes through mutation. We characterize the phenotypic transitions and identify key ingredients of the evolutionary potential, such as sensitive interactions and phenotypic hubs. Finally, we provide an intuitive understanding on how the modular design of a particular mechanism favors the access to novel phenotypes. Our work illustrates how the dynamical mechanism by which an organism develops constrains how it can evolve. It is striking that these dynamical mechanisms and their impact on evolvability can be observed even for such an apparently simple patterning task, performed by just three-node circuits.
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Schupp, Jonas Christian, Sandra Freitag-Wolf, Elena Bargagli, Violeta Mihailović-Vučinić, Paola Rottoli, Aleksandar Grubanovic, Annegret Müller, et al. "Phenotypes of organ involvement in sarcoidosis." European Respiratory Journal 51, no. 1 (January 2018): 1700991. http://dx.doi.org/10.1183/13993003.00991-2017.
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Sarcoidosis is a highly variable, systemic granulomatous disease of hitherto unknown aetiology. The GenPhenReSa (Genotype–Phenotype Relationship in Sarcoidosis) project represents a European multicentre study to investigate the influence of genotype on disease phenotypes in sarcoidosis.The baseline phenotype module of GenPhenReSa comprised 2163 Caucasian patients with sarcoidosis who were phenotyped at 31 study centres according to a standardised protocol.From this module, we found that patients with acute onset were mainly female, young and of Scadding type I or II. Female patients showed a significantly higher frequency of eye and skin involvement, and complained more of fatigue. Based on multidimensional correspondence analysis and subsequent cluster analysis, patients could be clearly stratified into five distinct, yet undescribed, subgroups according to predominant organ involvement: 1) abdominal organ involvement, 2) ocular–cardiac–cutaneous–central nervous system disease involvement, 3) musculoskeletal–cutaneous involvement, 4) pulmonary and intrathoracic lymph node involvement, and 5) extrapulmonary involvement.These five new clinical phenotypes will be useful to recruit homogenous cohorts in future biomedical studies.
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Kalincik, Tomas, Katherine Buzzard, Vilija Jokubaitis, Maria Trojano, Pierre Duquette, Guillermo Izquierdo, Marc Girard, et al. "Risk of relapse phenotype recurrence in multiple sclerosis." Multiple Sclerosis Journal 20, no. 11 (April 28, 2014): 1511–22. http://dx.doi.org/10.1177/1352458514528762.
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Objectives: The aim was to analyse risk of relapse phenotype recurrence in multiple sclerosis and to characterise the effect of demographic and clinical features on this phenotype. Methods: Information about relapses was collected using MSBase, an international observational registry. Associations between relapse phenotypes and history of similar relapses or patient characteristics were tested with multivariable logistic regression models. Tendency of relapse phenotypes to recur sequentially was assessed with principal component analysis. Results: Among 14,969 eligible patients (89,949 patient-years), 49,279 phenotypically characterised relapses were recorded. Visual and brainstem relapses occurred more frequently in early disease and in younger patients. Sensory relapses were more frequent in early or non-progressive disease. Pyramidal, sphincter and cerebellar relapses were more common in older patients and in progressive disease. Women presented more often with sensory or visual symptoms. Men were more prone to pyramidal, brainstem and cerebellar relapses. Importantly, relapse phenotype was predicted by the phenotypes of previous relapses. (OR = 1.8–5, p = 10-14). Sensory, visual and brainstem relapses showed better recovery than other relapse phenotypes. Relapse severity increased and the ability to recover decreased with age or more advanced disease. Conclusion: Relapse phenotype was associated with demographic and clinical characteristics, with phenotypic recurrence significantly more common than expected by chance.
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McLean, A. H. C., J. Hrček, B. J. Parker, H. Mathé-Hubert, H. Kaech, C. Paine, and H. C. J. Godfray. "Multiple phenotypes conferred by a single insect symbiont are independent." Proceedings of the Royal Society B: Biological Sciences 287, no. 1929 (June 17, 2020): 20200562. http://dx.doi.org/10.1098/rspb.2020.0562.
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Many microbial symbionts have multiple phenotypic consequences for their animal hosts. However, the ways in which different symbiont-mediated phenotypes combine to affect fitness are not well understood. We investigated whether there are correlations between different symbiont-mediated phenotypes. We used the symbiont Spiroplasma , a striking example of a bacterial symbiont conferring diverse phenotypes on insect hosts. We took 11 strains of Spiroplasma infecting pea aphids ( Acyrthosiphon pisum ) and assessed their ability to provide protection against the fungal pathogen Pandora neoaphidis and the parasitoids Aphidius ervi and Praon volucre . We also assessed effects on male offspring production for five of the Spiroplasma strains. All but one of the Spiroplasma strains provided very strong protection against the parasitoid P. volucre . As previously reported, variable protection against P. neoaphidis and A. ervi was also present; male-killing was likewise a variable phenotype. We find no evidence of any correlation, positive or negative, between the different phenotypes, nor was there any evidence of an effect of symbiont phylogeny on protective phenotype. We conclude that multiple symbiont-mediated phenotypes can evolve independently from one another without trade-offs between them.
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Hertel, Johannes, Stefan Frenzel, Johanna König, Katharina Wittfeld, Georg Fuellen, Birte Holtfreter, Maik Pietzner, et al. "The informative error: A framework for the construction of individualized phenotypes." Statistical Methods in Medical Research 28, no. 5 (February 22, 2018): 1427–38. http://dx.doi.org/10.1177/0962280218759138.
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For the goal of individualized medicine, it is critical to have clinical phenotypes at hand which represent the individual pathophysiology. However, for most of the utilized phenotypes, two individuals with the same phenotype assignment may differ strongly in their underlying biological traits. In this paper, we propose a definition for individualization and a corresponding statistical operationalization, delivering thereby a statistical framework in which the usefulness of a variable in the meaningful differentiation of individuals with the same phenotype can be assessed. Based on this framework, we develop a statistical workflow to derive individualized phenotypes, demonstrating that under specific statistical constraints the prediction error of prediction scores contains information about hidden biological traits not represented in the modeled phenotype of interest, allowing thereby internal differentiation of individuals with the same assigned phenotypic manifestation. We applied our procedure to data of the population-based Study of Health in Pomerania to construct a refined definition of obesity, demonstrating the utility of the definition in prospective survival analyses. Summarizing, we propose a framework for the individualization of phenotypes aiding personalized medicine by shifting the focus in the assessment of prediction models from the model fit to the informational content of the prediction error.
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Moser, Lukas, Silvan Hess, Henrik Behrend, and Michael Hirschmann. "Variability of functional knee phenotypes in osteoarthritic knees shows that a more personalized approach in TKA is needed." Orthopaedic Journal of Sports Medicine 8, no. 5_suppl4 (May 1, 2020): 2325967120S0030. http://dx.doi.org/10.1177/2325967120s00300.
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Aims and Objectives: Recently, the functional knee phenotype concept was introduced as a new system to classify the coronal alignment of the lower limb. Until now, this concept has only been applied to non-osteoarthritic knees. The purpose of this study was therefore to phenotype osteoarthritic knees according to this concept and investigate the distribution of these phenotypes. Materials and Methods: Preoperative CT scans of osteoarthritic knees scheduled for TKA collected between January 2017 and December 2019 in the KneePLAN 3D database (Symbios Orthopédie S.A.) were reviewed for patients meeting the following inclusion criteria: age>50 and <90, no signs of previous fractures, osteotomies and rheumatoid arthritis. A total of 2764 patients (1438 right and 1326 left lower limbs, Male:female ratio 1096 :1668) with a mean age ± standard deviation of 70±8.5years (range 50-90 years) were included. The following coronal alignment parameters were measured using a validated software (KneePLAN 3D, Symbios Orthopédie S.A): hip-knee-ankle angle (HKA), femoral mechanical angle (FMA), and tibial mechanical angle (TMA). Based on these measurements each leg was phenotyped according to the functional knee phenotype concept and the distribution of these phenotypes assessed. A phenotype thereby consists of a phenotype specific mean value (HKA, FMA or TMA value) and covers a range of ± 1.5° from this mean (e.g. 180°± 1.5). The phenotype specific mean values represent 3° increments of the angle starting from the rounded overall mean value of the angle. Results: There were 162 different functional knee phenotypes (122 male, 138 female and 97 mutual). The most common functional knee phenotype in males was VARHKA6°VARFMA3°NEUTMA0° accounting for 8% of all males. The most common functional knee phenotype in females was VARHKA3°NEUFMA0°NEUTMA0° accounting for 9% of the population. The ten most common functional phenotypes account for 50% and 42.8% of all females and males, respectively. Overall, 134 phenotypes accounted each for less than 1% of the total population (all 134 together for 26.4%). Conclusion: The broad variability of functional knee phenotypes in osteoarthritic knees shows that a more personalized TKA realignment strategy is needed. The challenge will be to identify the optimal alignment strategy for each functional knee phenotype.
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Zheng, Neil S., QiPing Feng, V. Eric Kerchberger, Juan Zhao, Todd L. Edwards, Nancy J. Cox, C. Michael Stein, Dan M. Roden, Joshua C. Denny, and Wei-Qi Wei. "PheMap: a multi-resource knowledge base for high-throughput phenotyping within electronic health records." Journal of the American Medical Informatics Association 27, no. 11 (September 24, 2020): 1675–87. http://dx.doi.org/10.1093/jamia/ocaa104.
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Abstract Objective Developing algorithms to extract phenotypes from electronic health records (EHRs) can be challenging and time-consuming. We developed PheMap, a high-throughput phenotyping approach that leverages multiple independent, online resources to streamline the phenotyping process within EHRs. Materials and Methods PheMap is a knowledge base of medical concepts with quantified relationships to phenotypes that have been extracted by natural language processing from publicly available resources. PheMap searches EHRs for each phenotype’s quantified concepts and uses them to calculate an individual’s probability of having this phenotype. We compared PheMap to clinician-validated phenotyping algorithms from the Electronic Medical Records and Genomics (eMERGE) network for type 2 diabetes mellitus (T2DM), dementia, and hypothyroidism using 84 821 individuals from Vanderbilt Univeresity Medical Center's BioVU DNA Biobank. We implemented PheMap-based phenotypes for genome-wide association studies (GWAS) for T2DM, dementia, and hypothyroidism, and phenome-wide association studies (PheWAS) for variants in FTO, HLA-DRB1, and TCF7L2. Results In this initial iteration, the PheMap knowledge base contains quantified concepts for 841 disease phenotypes. For T2DM, dementia, and hypothyroidism, the accuracy of the PheMap phenotypes were >97% using a 50% threshold and eMERGE case-control status as a reference standard. In the GWAS analyses, PheMap-derived phenotype probabilities replicated 43 of 51 previously reported disease-associated variants for the 3 phenotypes. For 9 of the 11 top associations, PheMap provided an equivalent or more significant P value than eMERGE-based phenotypes. The PheMap-based PheWAS showed comparable or better performance to a traditional phecode-based PheWAS. PheMap is publicly available online. Conclusions PheMap significantly streamlines the process of extracting research-quality phenotype information from EHRs, with comparable or better performance to current phenotyping approaches.
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Nishiura, Naoto, and Kunihiko Kaneko. "Evolution of phenotypic fluctuation under host-parasite interactions." PLOS Computational Biology 17, no. 11 (November 9, 2021): e1008694. http://dx.doi.org/10.1371/journal.pcbi.1008694.
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Robustness and plasticity are essential features that allow biological systems to cope with complex and variable environments. In a constant environment, robustness, i.e., insensitivity of phenotypes, is expected to increase, whereas plasticity, i.e., the changeability of phenotypes, tends to diminish. Under a variable environment, existence of plasticity will be relevant. The robustness and plasticity, on the other hand, are related to phenotypic variances. As phenotypic variances decrease with the increase in robustness to perturbations, they are expected to decrease through the evolution. However, in nature, phenotypic fluctuation is preserved to a certain degree. One possible cause for this is environmental variation, where one of the most important “environmental” factors will be inter-species interactions. As a first step toward investigating phenotypic fluctuation in response to an inter-species interaction, we present the study of a simple two-species system that comprises hosts and parasites. Hosts are expected to evolve to achieve a phenotype that optimizes fitness. Then, the robustness of the corresponding phenotype will be increased by reducing phenotypic fluctuations. Conversely, plasticity tends to evolve to avoid certain phenotypes that are attacked by parasites. By using a dynamic model of gene expression for the host, we investigate the evolution of the genotype-phenotype map and of phenotypic variances. If the host–parasite interaction is weak, the fittest phenotype of the host evolves to reduce phenotypic variances. In contrast, if there exists a sufficient degree of interaction, the phenotypic variances of hosts increase to escape parasite attacks. For the latter case, we found two strategies: if the noise in the stochastic gene expression is below a certain threshold, the phenotypic variance increases via genetic diversification, whereas above this threshold, it is increased mediated by noise-induced phenotypic fluctuation. We examine how the increase in the phenotypic variances caused by parasite interactions influences the growth rate of a single host, and observed a trade-off between the two. Our results help elucidate the roles played by noise and genetic mutations in the evolution of phenotypic fluctuation and robustness in response to host–parasite interactions.
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Tomar, A., and R. Teperino. "Genetic control of non-genetic inheritance in mammals: state-of-the-art and perspectives." Mammalian Genome 31, no. 5-6 (June 2020): 146–56. http://dx.doi.org/10.1007/s00335-020-09841-5.
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Abstract Thought to be directly and uniquely dependent from genotypes, the ontogeny of individual phenotypes is much more complicated. Individual genetics, environmental exposures, and their interaction are the three main determinants of individual’s phenotype. This picture has been further complicated a decade ago when the Lamarckian theory of acquired inheritance has been rekindled with the discovery of epigenetic inheritance, according to which acquired phenotypes can be transmitted through fertilization and affect phenotypes across generations. The results of Genome-Wide Association Studies have also highlighted a big degree of missing heritability in genetics and have provided hints that not only acquired phenotypes, but also individual’s genotypes affect phenotypes intergenerationally through indirect genetic effects. Here, we review available examples of indirect genetic effects in mammals, what is known of the underlying molecular mechanisms and their potential impact for our understanding of missing heritability, phenotypic variation. and individual disease risk.
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Dadachanji, Roshan, Anushree Patil, Beena Joshi, and Srabani Mukherjee. "Elucidating the impact of obesity on hormonal and metabolic perturbations in polycystic ovary syndrome phenotypes in Indian women." PLOS ONE 16, no. 2 (February 26, 2021): e0246862. http://dx.doi.org/10.1371/journal.pone.0246862.
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Polycystic ovary syndrome is a complex endocrinopathy with heterogeneous presentation and multifactorial etiology. We have undertaken this case-control study to compare metabolic and endocrine characteristics in different phenotypic subgroups of women with PCOS and the impact of obesity on them. Women with PCOS (n = 489) were classified into 4 phenotypes according to Rotterdam criteria. Comparisons of clinical, biochemical and hormonal parameters were performed across all phenotypic groups of PCOS and with controls (n = 270) by Welch’s ANOVA with subsequent Games-Howell post-hoc test. We found maximum prevalence of normoandrogenic phenotype D, which is milder form of PCOS in terms of insulin resistance, gonadotropin levels and dyslipidemia, followed by phenotype A, in our total study population. After classification of the study group into lean and obese groups, only few insulin and lipid-related traits showed marked differences between phenotypes. Further, we noted that obese women showed adverse metabolic but not androgenic traits compared to lean counterparts in the same phenotype. Metabolic syndrome frequency is increased in hyperandrogenic phenotypes with HDL-C and waist circumference being most predominant contributing factors in total, lean and obese groups. We demonstrate that in our study population there is greater occurrence of phenotype D of PCOS. Our study highlights the importance of clinicians concurrently employing Rotterdam criteria along with obesity status for ascertaining accurate PCOS status and formulating suitable therapeutic intervention.
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Roemer, F., J. Collins, T. Neogi, M. Crema, and A. Guermazi. "FRI0421 RATES OF PROGRESSION DIFFER BETWEEN STRUCTURAL PHENOTYPES OF KNEE OSTEOARTHRITIS: A SECONDARY ANALYSIS FROM THE FNIH COHORT." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 808.1–809. http://dx.doi.org/10.1136/annrheumdis-2020-eular.1802.
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Background:Imaging plays an important role in determining structural disease severity and potential suitability of patients recruited to disease-modifying osteoarthritis drug (DMOAD) trials. It has been suggested that there may be three main structural phenotypes in OA, i.e., inflammation, meniscus/cartilage and subchondral bone. These may progress differently and may represent distinct tissue targets for DMOAD approaches.Objectives:To stratify the Foundation for National Institutes of Health Osteoarthritis Biomarkers Consortium (FNIH) cohort, a well-defined subsample of the larger Osteoarthritis Initiative (OAI) study, into distinct structural phenotypes based on semiquantitative MRI assessment and to determine their risk for progression over 48 months.Methods:The FNIH was designed as a case-control study with knees showing either 1) radiographic and pain progression (i.e., “composite” cases), 2) radiographic progression only (“JSL”), 3) pain progression only, and 4) neither radiographic nor pain progression. MRI of both knees was performed on 3 T systems at the four OAI clinical sites. Two musculoskeletal radiologists read the baseline MRIs according to the MOAKS scoring system. Knees were stratified into subchondral bone, meniscus/cartilage and inflammatory phenotypes1. A secondary, less stringent definition for inflammatory and meniscus/cartilage phenotype was used for sensitivity analyses. The relation of each phenotype to risk of being in the JSL or composite case group compared to those not having that phenotype was determined using conditional logistic regression. Only KL2 and 3 and those without root tears were included.Results:485 knees were included. 362 (75%) did not have any phenotype, while 95 (20%) had the bone phenotype, 22 (5%) the cartilage/meniscus phenotype and 19 (4%) the inflammatory phenotype. The bone phenotype was associated with a higher risk of the JSL and composite outcome (OR 1.81;[95%CI 1.14,2.85] and 1.65; 95%CI [1.04,2.61]) while the inflammatory (OR 0.96 [95%CI 0.38,2.42] and 1.25; 95%CI [0.48,3.25]) and the meniscus/cartilage phenotypes were not (OR 1.30 95%CI [0.55,3.07] and 0.99; 95%CI [0.40,2,49]).In sensitivity analyses, the bone phenotype and having two phenotypes (vs. none) were both associated with increased risk of experiencing the composite outcome (bone: OR 1.65; 95% CI 1.04, 2.61; 2 phenotypes: OR 1.87; 95% CI 1.11, 3.16.Conclusion:The bone phenotype was associated with increased risk of having both radiographic and pain progression together, or radiographic progression alone, whereas the inflammatory phenotype or meniscus/cartilage phenotype each individually were not associated with either outcome. Phenotypic stratification appears to provide insights into risk for structural or composite structure plus pain progression, and therefore may be useful to consider when selecting patients for inclusion in clinical trials.References:[1]Roemer FW, Collins J, Kwoh CK, et al. MRI-based screening for structural definition of eligibility in clinical DMOAD trials: Rapid OsteoArthritis MRI Eligibility Score (ROAMES). Osteoarthritis Cartilage 2020;28(1):71-81Disclosure of Interests:Frank Roemer: None declared, Jamie Collins Consultant of: Boston Imaging Core Lab (BICL), LLC., Tuhina Neogi Grant/research support from: Pfizer/Lilly, Consultant of: Pfizer/Lilly, EMD-Merck Serono, Novartis, Michel Crema: None declared, Ali Guermazi Consultant of: AventisGalapagos, Pfizer, Roche, AstraZeneca, Merck Serono, and TissuGene
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Patel, Rushabh, Yanhui Guo, Adi Alhudhaif, Fayadh Alenezi, Sara A. Althubiti, and Kemal Polat. "Graph-Based Link Prediction between Human Phenotypes and Genes." Mathematical Problems in Engineering 2022 (March 27, 2022): 1–8. http://dx.doi.org/10.1155/2022/7111647.
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Deep phenotyping is defined as learning about genotype-phenotype associations and the history of human illness by analyzing phenotypic anomalies. It is significant to investigate the association between phenotype and genotype. Machine learning approaches are good at predicting the associations between abnormal human phenotypes and genes. A novel framework based on machine learning is proposed to estimate the links between human phenotype ontology (HPO) and genes. The Orphanet’s annotation parses the human phenotype-gene associations. An algorithm node2vec generates the embeddings for the nodes (HPO and genes). It performs node sampling on the graph using random walks and learns features on these sampled nodes for embedding. These embeddings were used downstream to predict the link between these nodes by supervised classifiers. Results show the gradient boosting decision tree model (LightGBM) has achieved an optimal AUROC of 0.904 and an AUCPR of 0.784, an optimal weighted F1 score of 0.87. LightGBM can detect more accurate interactions and links between human phenotypes and gene pairs.
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Mendoza-Cuenca, Luis, and Rogelio Macías-Ordóñez. "Foraging polymorphism in Heliconius charitonia (Lepidoptera: Nymphalidae): morphological constraints and behavioural compensation." Journal of Tropical Ecology 21, no. 4 (June 27, 2005): 407–15. http://dx.doi.org/10.1017/s0266467405002385.
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Sexes and also within sex phenotypes, frequently differ in morphological traits associated with efficiency and performance in foraging and mating behaviours. In butterflies and other flying animals, phenotypic differences in wing size and traits associated with flight are involved in flight performance and individual fitness, but explorations of links among two or more traits and intrasexual differences are scarce. Foraging patterns were studied in a population of Heliconius charitonia butterflies having three phenotypes (females and two male phenotypes) which differ in their wing morphology and reproductive behaviour. As in previous studies, intersexual differences in foraging patterns were found; more interestingly, intrasexual differences were found between alternative male mating strategies. Using morphological and behavioural data, as well as data from previous flight analyses in Heliconius butterflies, we show that intrasexual differences may be explained by the energetic demands of each phenotype. Energetic expenditure is partially related to phenotypic variability in flight morphology and efficiency, and at least in both male phenotypes, differences may also be related to the energetic demands of alternative mating strategies.
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Hrincă, G. H., and G. Vicovan. "Association of phenotypic combinations Hb/K with qualitative features of lamb pelts in the Botosani Karakul sheep." Biotehnologija u stocarstvu 27, no. 4 (2011): 1451–62. http://dx.doi.org/10.2298/bah1104451h.
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The specific production of the sheep belonging to the Botosani Karakul breed is the one of lamb pelts, characterized by various qualitative features (shape and size of hair curls, quality, lustre and colour of hair fibres), conferring nobility to this breed and which distinguish it from other sheep breeds. The present study tries an associative analysis of these traits of lamb pelts with different combinations between haemoglobin phenotypes and potassium phenotypes. The most valuable features, concerning shape and size of hair curls, as well as the quality and lustre of hair fibres are associated with combination of phenotypes Hband HK, and the weakest association of these features occur with the phenotypic combination HbBB/LK. The greyish, brown, grey, pink and white colours of the hair fibres are more associated with phenotypic combination HBB/LK, and the lowest frequencies of these colours are found in phenotype Hbassociated with phenotype HK, but this last phenotypic combination is associated to the highest degree with the black colour. The differences among the empirical distributions of qualitative features of the lamb pelts in relation to all phenotypic combinations of the haemoglobin and potassium systems are very significant, fact that recommends the use of these two biochemical genetic systems for the improvement of the Botosani Karakul breed for the lamb pelt production.
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Camacho-Escobar, M. A., L. Ramírez-Cancino, I. Lira-Torres, and V. Hernández-Sánchez. "Phenotypic characterization of the Guajolote (Meleagris gallopavo gallopavo) in Mexico." Animal Genetic Resources Information 43 (April 2008): 59–66. http://dx.doi.org/10.1017/s101423390000273x.
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SummaryThe study was conducted to investigate the phenotypic diversity of Guajolote present in small backyard poultry operations. From September 2004 to July 2006, in 54 municipalities in the coastal region of Oaxaca, Mexico 768 “guajalotes” growers were visited. Eleven different phenotypes of Guajolote, previously described as turkey varieties, have been identified. The phenotypes identified and their frequency are: Bronze (30.1%), Black (29.0%), Royal Palm (13.4%), Auburn (5.3%), Bourbon Red (5.2%), Narragancet (2.6%), Spotted (2.4%), Brown (2.2%), Slate (1.7%), White (1.5%) and Imperfect Albino (0.2%). The remainder (6.4%) were not identified as a phenotype previously described. This is the first report about the phenotypic differentiation of Guajolote in Mexico.
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Gupta, Deepti, Rini Upadhyaya, and Anjlina Bhati. "Study of prevalence of insulin resistance and other metabolic abnormalities in various phenotypes of polycystic ovary syndrome in central India." International Journal of Reproduction, Contraception, Obstetrics and Gynecology 9, no. 7 (June 25, 2020): 2978. http://dx.doi.org/10.18203/2320-1770.ijrcog20202744.
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Background: Till recent times, defining symptoms of PCOS remained a debatable topic. In 2012, National Institute of health consensus panel proposed diagnostic criteria based on phenotypes. Evidence showed higher incidence of diabetes mellitus, insulin resistance and compensatory hyperinsulinemia among women with PCOS. So, the present study was undertaken to compare the clinical, metabolic and hormonal profile among various phenotypes in women with PCOS and to find out the prevalence of insulin resistance among the PCOS phenotypes.Methods: The prospective, observational study was done on 292 women with PCOS-related infertility. These women were divided into 4 phenotypes. Ferriman-Gallwey score, HOMA-IR, OGTT, lipid parameters, hormonal parameters, mean ovarian volume and mean antral follicle counts were compared among the 4 phenotypic groups. One-way ANOVA followed by post-hoc Tukey was applied.Results: Mean weight, BMI, waist circumference, SBP, DBP and Ferriman-Gallwey score, fasting glucose, fasting insulin, OGTT (1 hour) and HOMA-IR was highest in phenotype A, while fasting glucose / insulin ratio was lowest in phenotype A. Total triglycerides, total cholesterol, LDL were higher and HDL was lowest, testosterone, mean ovarian volume and mean antral follicle count were highest and vitamin D was lowest in Phenotype A.Conclusions: Phenotype A is the group with all features of PCOS syndrome, while phenotype D is associated with milder metabolic profile. Women with phenotype A and B are at a higher risk for metabolic syndrome. Identifying various phenotypes will assist in providing appropriate treatment and prognosticating the patients with PCOS-related infertility.
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Zhou, Xue, Keijiro Nakamura, Naohiko Sahara, Masako Asami, Yasutake Toyoda, Yoshinari Enomoto, Hidehiko Hara, et al. "Exploring and Identifying Prognostic Phenotypes of Patients with Heart Failure Guided by Explainable Machine Learning." Life 12, no. 6 (May 24, 2022): 776. http://dx.doi.org/10.3390/life12060776.
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Identifying patient prognostic phenotypes facilitates precision medicine. This study aimed to explore phenotypes of patients with heart failure (HF) corresponding to prognostic condition (risk of mortality) and identify the phenotype of new patients by machine learning (ML). A unsupervised ML was applied to explore phenotypes of patients in a derivation dataset (n = 562) based on their medical records. Thereafter, supervised ML models were trained on the derivation dataset to classify these identified phenotypes. Then, the trained classifiers were further validated on an independent validation dataset (n = 168). Finally, Shapley additive explanations were used to interpret decision making of phenotype classification. Three patient phenotypes corresponding to stratified mortality risk (high, low, and intermediate) were identified. Kaplan–Meier survival curves among the three phenotypes had significant difference (pairwise comparison p < 0.05). Hazard ratio of all-cause mortality between patients in phenotype 1 (n = 91; high risk) and phenotype 3 (n = 329; intermediate risk) was 2.08 (95%CI 1.29–3.37, p = 0.003), and 0.26 (95%CI 0.11–0.61, p = 0.002) between phenotype 2 (n = 142; low risk) and phenotype 3. For phenotypes classification by random forest, AUCs of phenotypes 1, 2, and 3 were 0.736 ± 0.038, 0.815 ± 0.035, and 0.721 ± 0.03, respectively, slightly better than the decision tree. Then, the classifier effectively identified the phenotypes for new patients in the validation dataset with significant difference on survival curves and hazard ratios. Finally, age and creatinine clearance rate were identified as the top two most important predictors. ML could effectively identify patient prognostic phenotypes, facilitating reasonable management and treatment considering prognostic condition.
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Li, Yongjin, and Jagdish C. Patra. "Genome-wide inferring gene–phenotype relationship by walking on the heterogeneous network." Bioinformatics 26, no. 9 (March 9, 2010): 1219–24. http://dx.doi.org/10.1093/bioinformatics/btq108.
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Abstract Motivation: Clinical diseases are characterized by distinct phenotypes. To identify disease genes is to elucidate the gene–phenotype relationships. Mutations in functionally related genes may result in similar phenotypes. It is reasonable to predict disease-causing genes by integrating phenotypic data and genomic data. Some genetic diseases are genetically or phenotypically similar. They may share the common pathogenetic mechanisms. Identifying the relationship between diseases will facilitate better understanding of the pathogenetic mechanism of diseases. Results: In this article, we constructed a heterogeneous network by connecting the gene network and phenotype network using the phenotype–gene relationship information from the OMIM database. We extended the random walk with restart algorithm to the heterogeneous network. The algorithm prioritizes the genes and phenotypes simultaneously. We use leave-one-out cross-validation to evaluate the ability of finding the gene–phenotype relationship. Results showed improved performance than previous works. We also used the algorithm to disclose hidden disease associations that cannot be found by gene network or phenotype network alone. We identified 18 hidden disease associations, most of which were supported by literature evidence. Availability: The MATLAB code of the program is available at http://www3.ntu.edu.sg/home/aspatra/research/Yongjin_BI2010.zip Contact: yongjin.li@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
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Zhou, Xuan, Fangmei Qin, Han Li, Zhitao Li, Yang Liu, Zhengshan Yi, and Jing Sun. "Platelet-Derived Microparticles May Influence Phenotypic Heterogeneity in Patients with Severe Hemophilia." Blood 126, no. 23 (December 3, 2015): 4673. http://dx.doi.org/10.1182/blood.v126.23.4673.4673.
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Abstract Large heterogeneity in bleeding phenotype is observed among patients with severe hemophilia A. Some severe patients do not require regular replacement therapy, so to address the factors influencing phenotypic Heterogeneity in Patients with Severe Hemophilia A seems particularly important. We first initiate a cohort study 0f 274 patients with severe hemophilia A who were treated at the hemophilia treatment centre at Nanfang hospital, then 209 patients were enrolled and their bleedings were recorded, finally 12.9% (12/209) of the patients were found to be mild phenotypes, which annual bleeding rate(ABR)were less than 6 times. We then use Flow-cytometric analysis to detect the platelet-derived microparticles (PMPs) among patients with mild phenotypes, patients with severe phenotypes (ABR more than 24) and the normal control group, megamix beads (0.5μm; BioCytex, Marseille, France), CD42a-PE, CD42b-PE, CD41b-PE (GPIX, platelet MPs [PMPs], BD, NJ, USA) were involved, then the results showed that there was no difference in the level of PMPs between hemophliac patients and the normal control group (P=0.317), however, the level of PMPs in patients with mild phenotypes were significantly higher than patients with severe phenotypes (3.65±1.38 vs 1.13±0.64, P<0.05).These findings indicated that 12.9% were mild phenotypes in 209 patients with severe hemophilia A, moreover, the platelet-derived microparticles which may influence phenotypic heterogeneity in patients with severe haemophilia A will be further study for individual treatment. Disclosures No relevant conflicts of interest to declare.
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Bultemeier, Brett W., Mike D. Netherland, Jason A. Ferrell, and William T. Haller. "Differential Herbicide Response among Three Phenotypes ofCabomba caroliniana." Invasive Plant Science and Management 2, no. 4 (October 2009): 352–59. http://dx.doi.org/10.1614/ipsm-09-035.1.
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AbstractCabomba is a submersed aquatic plant native to the southeastern United States that is commonly sold worldwide through the aquarium trade. While infrequently managed in its native range, cabomba has recently been reported as invasive and tolerant to management efforts in the northern areas of the United States and in other countries. Invasive populations of cabomba are characterized by a phenotype that is bright green. In contrast, cabomba native to the southeastern United States is characterized by a red phenotype, while plants sold through the aquarium trade have intermediate characteristics of both the green and red phenotypes. The response of the three cabomba phenotypes to selected herbicides was evaluated by measuring photosynthetic response over the course of a static 144-hr exposure. Plants were exposed to the maximum recommended use-rates of 2,4-D, carfentrazone, copper, diquat, endothall (amine and dipotasium salt formulation), flumioxazin, quinclorac, triclopyr, and a combination of diquat and copper. A submersed plant species known to be sensitive to each of these herbicides was also included to compare photosynthetic response of the cabomba to a susceptible plant. The photosynthetic response of the red and green phenotypes differed following exposure to carfentrazone, diquat, 2,4-D, triclopyr, and flumioxazin. Diquat, diquat plus copper, endothall (amine salt), and flumioxazin were the only products that resulted in a greater than 50% reduction of photosynthesis in all three phenotypes of cabomba. A second experiment was conducted where all three phenotypes of cabomba were exposed to these four herbicides for 24 hr, and photosynthesis was evaluated. Following the 24-hr exposure, results further documented distinct response differences between the green and red phenotypes, with the green phenotype demonstrating a reduced sensitivity to the herbicides evaluated. Results demonstrate clear phenotypic differences in response to herbicide treatments and lack of susceptibility of cabomba to most herbicides.
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Aparna, Suresh Kumar, and Murugesan Sharmila. "Aberrant phenotypes in acute myeloid leukemia in India." International Journal of Advances in Medicine 5, no. 2 (March 21, 2018): 361. http://dx.doi.org/10.18203/2349-3933.ijam20181069.
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Background: Acute myeloid leukemia (AML) is a heterogeneous disease, associated with a high diversity of phenotypes. The study was done with the aim to study about the aberrant phenotypes in acute myeloid leukemia cases and the correlation among the aberrant phenotypes and poor prognostic factors in acute myeloid leukemia.Methods: This cross sectional study was conducted on 35 cases of newly diagnosed AML according to the selection criteria at Madras Medical College and Rajiv Gandhi Government General Hospital, Chennai for a period of 6 months. Immunophenotyping analysis by flow cytometry was done on fresh bone marrow aspirate or peripheral blood sample by applying Acute Leukemia Panel. The co-expression of different antigen markers on lymphocytes was analyzed.Results: Aberrant lymphoid markers were seen in 17 (49%) cases. 5 (14%) cases had lymphoid associated antigen expression alone. 3 (8%) cases had asynchronous antigen expression alone. 9 (27%) cases had both asynchronous antigen expression and lymphoid associated antigen expression which is of cases . In total, lymphoid associated antigen expression is seen in 41% of cases and asynchronous antigen expression in 35% of cases. CD3, CD19 (lymphoid associated antigen) and CD34+ CD15+ (asynchronous aberrant phenotype) were the most common equally expressed aberrant phenotypes, each in 7 cases. CD 3 was significantly more common in males (P=0.021) but in general there were no statistically significant association between adverse prognostic factors and aberrant phenotypic AML.Conclusions: CD19 and CD3 were the most commonly expressed lymphoid associated antigen. Most common asynchronous aberrant phenotype was CD34+CD15+. None of the aberrant phenotypic expression was not associated with poor risk factors in acute myeloid leukemia except for common expression of CD3 in males.
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Rubtsova, Svetlana N., Irina Y. Zhitnyak, and Natalya A. Gloushankova. "Phenotypic Plasticity of Cancer Cells Based on Remodeling of the Actin Cytoskeleton and Adhesive Structures." International Journal of Molecular Sciences 22, no. 4 (February 12, 2021): 1821. http://dx.doi.org/10.3390/ijms22041821.
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There is ample evidence that, instead of a binary switch, epithelial-mesenchymal transition (EMT) in cancer results in a flexible array of phenotypes, each one uniquely suited to a stage in the invasion-metastasis cascade. The phenotypic plasticity of epithelium-derived cancer cells gives them an edge in surviving and thriving in alien environments. This review describes in detail the actin cytoskeleton and E-cadherin-based adherens junction rearrangements that cancer cells need to implement in order to achieve the advantageous epithelial/mesenchymal phenotype and plasticity of migratory phenotypes that can arise from partial EMT.
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Maslov, Andrey A., Nailya Guskova, Ekaterina Guskova, Kristina Avanesova, Svetlana V. Belgova, Ekaterina Gornostaeva, Irina V. Tselishcheva, et al. "The rates of ABO, Rh, and Kell antigens in children with cancer." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): e22007-e22007. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e22007.
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e22007 Background: The purpose of the study was to analyze phenotypic characteristics of red blood cells by the AVBO, Rh and Kell systems in children with cancer. Methods: ABO and Rh blood groups were determined and erythrocyte antigens (D, С, с, Сw, Е, е, К, k) were typed (AutoVue Innova, USA) in blood samples of 114 children with solid tumors. Results: ABO blood groups distribution was as follows: A(II) > O(I) > B(III) > AB(IV) with A(II) prevalence. Rh(D)-positive phenotype was observed in 82 (71.9%) patients of 114: 47 (57.3%) boys and 35 (42.6%) girls. 32 (28.1%) patients of 114 were Rh(D)-negative: 15 (46.8%) boys and 17 (53.1%) girls. Only 8 (7%) children were Kell-positive, which was similar to the antigen prevalence in European population. 4 erythrocyte phenotypes were the most frequent in Rh(D)-positive patients: СсDееK− (34.1%), ССDееK− (22.0%), ccDEeK− (13.4%) and СсDЕеK− (11.0%). I.e., more than a half of children with oncopathologies (56.1%) had Kell-negative phenotypes, СсDееK− and ССDееK−. 86.4% of Rh(D)-positive patients had homozygous combinations of Rhesus antigens causing transfusion reactions - СС, сc, ЕЕ and ее. 18 (22.0%) of Rh(D)-positive patients were homozygous for the C antigen and 64 (78.0%), i.e. every third patient, had the c antigen. Children with the C antigen may be sensitized to the c antigen through blood transfusion with subsequent development of hemolytic complications. The K (Cellano) antigen was found in all children, and 93% of them had kk phenotype and 7% - Kk. The Сw (Willis) antigen was revealed only in 5 (6.0%) Rh(D)-positive patients with rare phenotypes - CwCceeK-, CwccEeK-, CwCcEEK-, CwCcEeK-. Matching a donor for patients with one of these phenotypes could pose a problem. Conclusions: Studying phenotypic characteristics of red blood cells is necessary for providing a successful blood transfusion, especially in children Kell-positive for the K antigen, in children homozygous for the C antigen with ССDееК- phenotype and in children with the Сw antigen and СwСсееК-, СwссЕеК-, СwСсЕЕК- and СwСсЕеК- phenotypes.
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Wang, Ye, Huigan Xie, Tiechui Yang, Dan Gao, and Xiwen Li. "Primary Investigation of Phenotypic Plasticity in Fritillaria cirrhosa Based on Metabolome and Transcriptome Analyses." Cells 11, no. 23 (November 30, 2022): 3844. http://dx.doi.org/10.3390/cells11233844.
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Phenotypic plasticity refers to the adaptability of an organism to a heterogeneous environment. In this study, the differential gene expression and compositional changes in Fritillaria cirrhosa during phenotypic plasticity were evaluated using transcriptomic and metabolomic analyses. The annotation profiles of 1696 differentially expressed genes from the transcriptome between abnormal and normal phenotypes revealed that the main annotation pathways were related to the biosynthesis of amino acids, ABC transporters, and plant–pathogen interactions. According to the metabolome, the abnormal phenotype had 36 upregulated amino acids, including tryptophan, proline, and valine, which had a 3.77-fold higher relative content than the normal phenotype. However, saccharides and vitamins were found to be deficient in the abnormal phenotypes. The combination profiles demonstrated that phenotypic plasticity may be an effective strategy for overcoming potential stress via the accumulation of amino acids and regulation of the corresponding genes and transcription factors. In conclusion, a pathogen attack on F. cirrhosa may promote the synthesis of numerous amino acids and transport them into the bulbs through ABC transporters, which may further result in phenotypic variation. Our results provide new insights into the potential mechanism of phenotypic changes.
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Patalano, Solenn, Anna Vlasova, Chris Wyatt, Philip Ewels, Francisco Camara, Pedro G. Ferreira, Claire L. Asher, et al. "Molecular signatures of plastic phenotypes in two eusocial insect species with simple societies." Proceedings of the National Academy of Sciences 112, no. 45 (October 19, 2015): 13970–75. http://dx.doi.org/10.1073/pnas.1515937112.
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Phenotypic plasticity is important in adaptation and shapes the evolution of organisms. However, we understand little about what aspects of the genome are important in facilitating plasticity. Eusocial insect societies produce plastic phenotypes from the same genome, as reproductives (queens) and nonreproductives (workers). The greatest plasticity is found in the simple eusocial insect societies in which individuals retain the ability to switch between reproductive and nonreproductive phenotypes as adults. We lack comprehensive data on the molecular basis of plastic phenotypes. Here, we sequenced genomes, microRNAs (miRNAs), and multiple transcriptomes and methylomes from individual brains in a wasp (Polistes canadensis) and an ant (Dinoponera quadriceps) that live in simple eusocial societies. In both species, we found few differences between phenotypes at the transcriptional level, with little functional specialization, and no evidence that phenotype-specific gene expression is driven by DNA methylation or miRNAs. Instead, phenotypic differentiation was defined more subtly by nonrandom transcriptional network organization, with roles in these networks for both conserved and taxon-restricted genes. The general lack of highly methylated regions or methylome patterning in both species may be an important mechanism for achieving plasticity among phenotypes during adulthood. These findings define previously unidentified hypotheses on the genomic processes that facilitate plasticity and suggest that the molecular hallmarks of social behavior are likely to differ with the level of social complexity.
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Kryzhanovska, M. M., N. Ya Holub, M. Z. Prokopiak, and H. M. Holinei. "Study of the intrapopulation polymorphism of Trifolium repens L. from Lanivtsi under the anthropogenic load of various intensity." Faktori eksperimental'noi evolucii organizmiv 29 (August 31, 2021): 185–90. http://dx.doi.org/10.7124/feeo.v29.1429.
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Aim. To study the phenotypic polymorphism of Trifolium repens L. populations growing under various anthropogenic load. Methods. The quantitative calculation of the leaves of the white clover by the presence or absence of the white leaf mark; the identification of the phenotype and genotype of the plant according to the pattern of the white leaf mark; the analysis of the phenotypic diversity and the study of the percentage of rare phenotypes; the calculation of the index of the phenotypes ratio. Results. 4 phenotypes were identified in the pasture area. The most common of them were the plants without the white mark with a frequency of 56.2 %. The plants with a full spot accounted for 27.5 %, with a spot with a gap – 15.4 %, with a central spot – 2.2 %. Heterozygous plants were absent. In the central part of the city, 7 genotypes were identified. Among these genotypes there were the significant decrease of the recessive homozygotes (by 43.6 %) and the increase of the frequency of VV (by 15.2 %) and VHVH (by 21.2 %) genotypes. Heterozygotes accounted for 1.3–3.0 %. The intrapopulation diversity in this territory was the highest (5.1) among the studied areas. In the population growing near Ternopil-Lanivtsi road, we identified 6 genotypes. The plants without spot (vv) and with the full spot (VV) were found with identical frequency of 34–35 %. The plants with a full high spot (VHVH) were about 20.4 %. Other phenotypes amounted to 10 %. Conclusions. In the populations located in ecologically polluted and anthropogenically loaded areas, the sets of alleles expand and the specific phenotypes appear under the influence of the mutation processes and natural selection. In the population without the anthropogenic load the decrease of the polymorphism and the increase of the frequency of individual genotypes (vv, VV) were observed.
Keywords: Trifolium repens L., leaf phenotype, intrapopulation polymorphism, multiple allelism, bioindication, anthropogenic load.
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Rinkenbaugh, Amanda L., Vidya C. Sinha, Pankaj Singh, Yuan Qi, Jiansu Shao, Xiaomei Zhang, Gloria V. Echeverria, W. Fraser Symmans, Stacy L. Moulder, and Helen Piwnica-Worms. "Abstract 1595: Analysis of spatiotemporal phenotypic heterogeneity in chemoresistant triple negative breast cancer using imaging mass cytometry." Cancer Research 82, no. 12_Supplement (June 15, 2022): 1595. http://dx.doi.org/10.1158/1538-7445.am2022-1595.
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Abstract Shifts in tumor cell phenotype in response to selective pressures (i.e. changing microenvironments, drug treatments) pose one of the biggest obstacles to successful breast cancer therapies. Phenotypically diverse breast tumor and stroma subpopulations, and interactions between them that alter tumor cell biology, represent unique and spatially distinct niches. We hypothesize that localized neighborhoods of breast tumor cells possess specialized phenotypes that mediate chemoresistance and represent novel therapeutic vulnerabilities. In order to assess these potential phenotypes, we utilized imaging mass cytometry (IMC), a highly multiplexed imaging modality that allows simultaneous measurement of 30-40 antigens while retaining the spatial architecture of the cancer tissue. We constructed an IMC antibody panel that combines markers for tissue architecture, tumor and stromal cell phenotyping, and signaling pathway activation. IMC was applied to patient-derived xenograft (PDX) models of triple negative breast cancer (TNBC).Our TNBC PDX collection was established from tumors obtained before and after neoadjuvant Adriamycin and cyclophosphamide (AC). IMC analysis of 18 PDX models representing eight patients revealed that stromal cell phenotypes were generally shared between all models, but tumor cell phenotypes were largely patient-specific. While every model was comprised primarily of a few major tumor cell phenotypes, we noted that each case also harbored several minor, unique populations, suggesting that specialized neighborhoods may exist within the tumor mass. Comparison of paired PDX models showed a wide range of phenotypic responses to chemotherapy, ranging from stable tumor composition to widespread changes in tumor phenotypes. These phenotypic changes arose despite relatively consistent genomic architecture. Vimentinhi fibroblasts were present more often in post-AC models, while SMAhi fibroblasts were unchanged after treatment. Comparison of pre-/post-AC PDX pairs revealed spatially constrained MAPK activation emerged after treatment. To capture acute changes in tumor phenotype, we treated treatment-naïve PDX models with AC and evaluated tumors by IMC. As tumors regressed and then regrew, we identified novel phenotypic shifts, again including increased MAPK signaling localized to discrete neighborhoods, suggesting this property may be a common feature of chemoresistant TNBC. Analysis of adjacent cells revealed seven distinct neighborhoods, and ongoing work is aimed at determining whether these neighborhoods are altered in response to chemotherapy treatment. Taken together, our findings suggest that distinct tumor phenotypes arise following treatment. Our goal is to determine whether these unique phenotypic niches functionally contribute to chemoresistance and if disruption of these niches enhances chemosensitivity. Citation Format: Amanda L. Rinkenbaugh, Vidya C. Sinha, Pankaj Singh, Yuan Qi, Jiansu Shao, Xiaomei Zhang, Gloria V. Echeverria, W. Fraser Symmans, Stacy L. Moulder, Helen Piwnica-Worms. Analysis of spatiotemporal phenotypic heterogeneity in chemoresistant triple negative breast cancer using imaging mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1595.
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Duedu, Kwabena Obeng, Joana Qwansima Mends, Reuben Ayivor-Djanie, Priscilla Efua Essandoh, Emmanuel Mawuli Nattah, Jones Gyamfi, and Grace Semabia Kpeli. "Plasmidome AMR screening (PAMRS) workflow: a rapid screening workflow for phenotypic characterization of antibiotic resistance in plasmidomes." AAS Open Research 4 (April 21, 2021): 18. http://dx.doi.org/10.12688/aasopenres.13111.1.
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Background: Phenotypic characterization of antimicrobial resistance (AMR) in bacteria has remained the gold standard for investigation and monitoring of what resistance is present in an organism. However, the process is laborious and not attractive for screening multiple plasmids from a microbial community (plasmidomes). Instead, genomic tools are used, but a major bottle neck that presence of genes does not always translate into phenotypes. Methods: We designed the plasmidome AMR screening (PAMRS) workflow to investigate the presence of antibiotic resistant phenotypes in a plasmidome using Escherichia coli as a host organism. Plasmidomes were extracted from the faecal matter of chicken, cattle and humans using commercial plasmid extraction kits. Competent E. coli cells were transformed and evaluated using disk diffusion. Thirteen antibiotic resistant phenotypes were screened. Results: Here, we show that multiple antibiotic resistant phenotypes encoded by plasmids can be rapidly screened simultaneously using the PAMRS workflow. E. coli was able to pick up to 7, 5 or 8 resistant phenotypes from a single plasmidome from chicken, cattle or humans, respectively. Resistance to ceftazidime was the most frequently picked up phenotype in humans (52.6%) and cattle (90.5%), whereas in chickens, the most picked up resistant phenotype was resistance to co-trimoxazole, ceftriaxone and ampicillin (18.4% each). Conclusions: This workflow is a novel tool that could facilitate studies to evaluate the occurrence and expression of plasmid-encoded antibiotic resistance in microbial communities and their associated plasmid-host ranges. It could find application in the screening of plasmid-encoded virulence genes.
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Zilhão, N. R., M. C. Olthof, D. J. A. Smit, D. C. Cath, L. Ligthart, C. A. Mathews, K. Delucchi, D. I. Boomsma, and C. V. Dolan. "Heritability of tic disorders: a twin-family study." Psychological Medicine 47, no. 6 (December 15, 2016): 1085–96. http://dx.doi.org/10.1017/s0033291716002981.
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BackgroundGenetic–epidemiological studies that estimate the contributions of genetic factors to variation in tic symptoms are scarce. We estimated the extent to which genetic and environmental influences contribute to tics, employing various phenotypic definitions ranging between mild and severe symptomatology, in a large population-based adult twin-family sample.MethodIn an extended twin-family design, we analysed lifetime tic data reported by adult mono- and dizygotic twins (n = 8323) and their family members (n = 7164; parents and siblings) from 7311 families in the Netherlands Twin Register. We measured tics by the abbreviated version of the Schedule for Tourette and Other Behavioral Syndromes. Heritability was estimated by genetic structural equation modeling for four tic disorder definitions: three dichotomous and one trichotomous phenotype, characterized by increasingly strictly defined criteria.ResultsPrevalence rates of the different tic disorders in our sample varied between 0.3 and 4.5% depending on tic disorder definition. Tic frequencies decreased with increasing age. Heritability estimates varied between 0.25 and 0.37, depending on phenotypic definitions. None of the phenotypes showed evidence of assortative mating, effects of shared environment or non-additive genetic effects.ConclusionsHeritabilities of mild and severe tic phenotypes were estimated to be moderate. Overlapping confidence intervals of the heritability estimates suggest overlapping genetic liabilities between the various tic phenotypes. The most lenient phenotype (defined only by tic characteristics, excluding criteria B, C and D of DSM-IV) rendered sufficiently reliable heritability estimates. These findings have implications in phenotypic definitions for future genetic studies.
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Barthold, Stephen W. "Genetically altered mice: phenotypes, no phenotypes, and Faux phenotypes." Genetica 122, no. 1 (September 2004): 75–88. http://dx.doi.org/10.1007/s10709-004-1439-3.
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de Koning-Tijssen, M. "One gene many phenotypes, one phenotype many genes." Journal of the Neurological Sciences 405 (October 2019): 11. http://dx.doi.org/10.1016/j.jns.2019.10.028.
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Xiromerisiou, Georgia, Henry Houlden, Nikolaos Scarmeas, Maria Stamelou, Eleanna Kara, John Hardy, Andrew J. Lees, et al. "THAP1 mutations and dystonia phenotypes: Genotype phenotype correlations." Movement Disorders 27, no. 10 (August 17, 2012): 1290–94. http://dx.doi.org/10.1002/mds.25146.
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