Understanding molecular mechanisms and predicting phenotypic effects of pathogenic tubulin mutations. by Thomas J Attard, Julie P I Welburn, Joseph A Marsh

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Identification and analysis of individuals who deviate from their genetically-predicted phenotype. by Gareth Hawkes, Loic Yengo, Sailaja Vedantam, Eirini Marouli, Robin N Beaumont, GIANT Consortium, Jessica Tyrrell, Michael N Weedon, Joel Hirschhorn, Timothy M Frayling, Andrew R Wood

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P025: Newborn screening predicts phenotype conversion and developmental outcome in hyperphenylalaninemia by Aaron Williams, Kristian Divin, Lindsay Burrage, Fernando Scaglia, William Craigen, Vernon Sutton, Claudia Soler-Alfonso, Kevin Glinton, Ronit Marom

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The Influence of CYP2B6, GSTP1, and SLCO1B1 Star Allele‐Predicted Phenotypes and CBR1 Genetic Variants on Effectiveness Outcomes in Patients With Hepatocellular Carcinoma Receiving Doxorubicin via Transarterial Chemoembolization by Sireen Abdul Rahim Shilbayeh, Omnia A. Abd El‐Baset, Mohammad A. Alshabeeb, Abdalrhman Hamdan Alanizi, Naglaa F. Khedr, Rehab H. Werida

“…ABSTRACT We investigated the influence of CYP2B6, GSTP1, and SLCO1B1 star allele‐predicted phenotypes and CBR1 variants on clinical outcomes in patients with HCC receiving DOX via TACE. …”
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Cohort profile: The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) study: a 2-year, European, cohort study to describe, validate and predict phenotypes of osteoarthritis using clinical, imaging and biochemical markers by Francis Berenbaum, Margreet Kloppenburg, Ida K Haugen, Paco M J Welsing, Floris P J G Lafeber, Francisco J Blanco, Ali Mobasheri, John Loughlin, Willem E van Spil, Eefje M van Helvoort, Mylène P Jansen, Marieke Loef, Jaume Bacardit, Christoph H Ladel, Anne C Bay-Jensen, Jonathan Larkin, Janneke Boere, Harrie H Weinans, Agnes Lalande, Anne C A Marijnissen

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An integrative, multi‐scale, genome‐wide model reveals the phenotypic landscape of Escherichia coli by Javier Carrera, Raissa Estrela, Jing Luo, Navneet Rai, Athanasios Tsoukalas, Ilias Tagkopoulos

“…Abstract Given the vast behavioral repertoire and biological complexity of even the simplest organisms, accurately predicting phenotypes in novel environments and unveiling their biological organization is a challenging endeavor. …”
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Genomic selection in pig breeding: comparative analysis of machine learning algorithms by Ruilin Su, Jingbo Lv, Yahui Xue, Sheng Jiang, Lei Zhou, Li Jiang, Junyan Tan, Zhencai Shen, Ping Zhong, Jianfeng Liu

“…Machine learning (ML) methods are usually used to predict phenotypic values since their advantages in processing high dimensional data. …”
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Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility. by Irene V van Blokland, Pauline Lanting, Anil P S Ori, Judith M Vonk, Robert C A Warmerdam, Johanna C Herkert, Floranne Boulogne, Annique Claringbould, Esteban A Lopera-Maya, Meike Bartels, Jouke-Jan Hottenga, Andrea Ganna, Juha Karjalainen, Lifelines COVID-19 cohort study, COVID-19 Host Genetics Initiative, Caroline Hayward, Chloe Fawns-Ritchie, Archie Campbell, David Porteous, Elizabeth T Cirulli, Kelly M Schiabor Barrett, Stephen Riffle, Alexandre Bolze, Simon White, Francisco Tanudjaja, Xueqing Wang, Jimmy M Ramirez, Yan Wei Lim, James T Lu, Nicole L Washington, Eco J C de Geus, Patrick Deelen, H Marike Boezen, Lude H Franke

“…Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. …”
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Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease by Robert Chen, Ben Omega Petrazzini, Áine Duffy, Ghislain Rocheleau, Daniel Jordan, Meena Bansal, Ron Do

“…Association testing with predicted phenotypes, which replicates more known genetic variants from GWAS than true phenotypes, identifies 16 single variants and 11 gene-level associations implicating 23 additional genes. …”
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ORF1ab codon frequency model predicts host-pathogen relationship in orthocoronavirinae by Phillip E. Davis, Joseph A. Russell

“…Predicting phenotypic properties of a virus directly from its sequence data is an attractive goal for viral epidemiology. …”
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Predicting the direction of phenotypic difference by David Gokhman, Keith D. Harris, Shai Carmi, Gili Greenbaum

“…Abstract Predicting phenotypes from genomes is a major goal in genetics, but for most complex phenotypes, predictions are largely inaccurate. …”
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Gene mutation and drug resistance of <i>M. tuberculosis</i> in the patients followed up in the city of Moscow by M. A. Krasnova, E. M. Belilovsky, S. E. Borisov, A. A. Khakhalina, Yu. D. Mikhaylova, E. Yu. Nosova

“…The article describes a retrospective study of the results of microbiological and molecular genetic tests of 685 M. tuberculosis cultures isolated from 685 adult tuberculosis patients registered for dispensary follow-up in Moscow in 2014.The following was identified during the study: phenotypic drug resistance (FDR) of MTB to rifampicin, isoniazid, fluoroquinolones, kanamycin, amikacin, and capreomycin in groups of patients with different treatment history; the frequency of FDR to the above anti-tuberculosis drugs in strains with mutations being drug resistance markers; the frequency of various mutations in case of FDR of mycobacteria in the patients from different groups; the relationship of FDR or the presence of a particular mutation with various characteristics of the patients and their treatment history.The history of previous treatment was determined as statistical significance to provide the greatest influence on the spread of drug resistant MTB: patients undergoing repeated treatment had FDR more often and also a much more pronounced variety of mutations being markers of FDR to certain anti-tuberculosis drugs.The results of the study showed that the detection of genetic mutations in MBT associated with FDR was a reliable tool for predicting phenotypic resistance and should be used as the main method for selecting anti-tuberculosis drugs when compiling the etiotropic therapy regimen.…”
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A multi‐scale approach reveals that NF‐κB cRel enforces a B‐cell decision to divide by Maxim N Shokhirev, Jonathan Almaden, Jeremy Davis‐Turak, Harry A Birnbaum, Theresa M Russell, Jesse A D Vargas, Alexander Hoffmann

“…Abstract Understanding the functions of multi‐cellular organs in terms of the molecular networks within each cell is an important step in the quest to predict phenotype from genotype. B‐lymphocyte population dynamics, which are predictive of immune response and vaccine effectiveness, are determined by individual cells undergoing division or death seemingly stochastically. …”
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Block selection in multiblock partial least squares for modeling genotype-phenotype relations in Saccharomyces. by Muhammad Tahir, Bu Yude, Tahir Mehmood, Saima Bashir, Zeeshan Ashraf

“…Both proposed variants consistently outperform conventional approaches such as partial least squares and multi-block partial least squares in predicting phenotypes. These results highlight the potential of our methods for advancing data-based modeling and genotype-phenotype mapping.…”
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Complete Genome and Characterization Analysis of a <i>Bifidobacterium animalis</i> Strain Isolated from Wild Pigs (<i>Sus scrofa ussuricus</i>) by Tenggang Di, Huan Zhang, Cheng Zhang, Liming Tian, Menghan Chang, Wei Han, Ruiming Qiao, Ming Li, Shuhong Zhang, Guangli Yang

“…Although the antibiotic resistance genes were predicted, phenotypic assays demonstrated discordant resistance patterns, indicating complex regulatory networks. …”
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FCA-STNet: Spatiotemporal Growth Prediction and Phenotype Extraction from Image Sequences for Cotton Seedlings by Yiping Wan, Bo Han, Pengyu Chu, Qiang Guo, Jingjing Zhang

“…Furthermore, the majority of the predicted phenotypic traits exhibited correlations with actual measurements with coefficients above 0.8, indicating high prediction accuracy. …”
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Often in silico, rarely in vivo: characterizing endemic plant-associated microbes for system-appropriate biofertilizers by Holly Hone, Holly Hone, Holly Hone, Tongda Li, Tongda Li, Jatinder Kaur, Jatinder Kaur, Jennifer L. Wood, Timothy Sawbridge, Timothy Sawbridge, Timothy Sawbridge

“…However, key canonical genes, such as pqq operon and gcd, did not reliably predict phenotype, highlighting the limitations of in silico predictions. …”
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Adjuvant postbiotic administration improves dental caries prognosis by restoring the oral microbiota by Qing Liu, Teng Ma, Cuijiao Feng, Yalin Li, Hao Jin, Xuan Shi, Lai-Yu Kwok, Yan Shi, Tingtao Chen, Heping Zhang

“…Taxonomic and functional annotation of the microbiota revealed that postbiotics co-treatment significantly: increased the relative abundance of Pseudomonas and P. reactans, decreased the relative abundance of Prevotella shahii, and enriched the energy metabolism-related pathways. BugBase-predicted phenotypes inferred to an oral microbiota with decreased potential pathogenic bacteria and increased oxidative stress-tolerant bacteria after postbiotics intervention. …”
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Case Report: Genetic evolution of Burkholderia pseudomallei during treatment leading to antibiotic resistance and disease relapse. [version 2; peer review: 2 approved] by Ko Chang, Elizabeth A. Ashley, Claire Chewapreecha, Anousone Douangnouvong, Chantisa Keeratipusana, Terry John Evans, Koukeo Phommasone, Davanh Sengdatka, Elizabeth M. Batty, Vilayouth Phimolsarnnousith

“…Characterisation of drug-resistant mutants is required to understand mechanisms of resistance and to predict phenotypes from whole genome sequencing.…”
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Recurrent rhabdomyolysis caused by palmitoyltransferase II (CPT-2) deficiency but complete normal acylcarnitine profile: A patient presentation and review of the literature by Chih-Hsuan Lu, Chia-Feng Yang, Yun-Ru Chen, Yann-Jang Chen, Yung-Hsiu Lu, Dau-Ming Niu

“…Although the CPT-2 deficiency genotype does not entirely predict phenotype severity, it remains informative for most patients, assisting in assessing the severity linked to each genetic variant. …”
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