Phenotypic Data Research Articles

Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions

Accurate genomic predictions of breeding values for traits included in the selection indexes are paramount for optimizing genetic progress in populations under selection. The size of the reference populations is a major factor influencing the accuracy of genomic predictions, which is even more important for lowly-heritable traits such as fertility and reproduction indicators. Combining data from different geographical regions or countries can be beneficial for genomic prediction of these lowly heritable traits. Therefore, the objectives of this study were to: 1) evaluate the benefits of performing across-regional genomic evaluations for reproduction traits in Chinese Holstein cattle; and, 2) assess the feasibility of validating genomic predictions across environments based on reaction norm models (RNM) and the Linear Regression (LR) method after accounting for genotype-by-environment interactions. Phenotypic records from 194,574 cows collected across 47 farms located in 2 regions of China were used for this study. The reference and validation populations were defined based on birth year for applying the LR validation method. The traits evaluated included: interval from first to last insemination (IFL), conception rate at the first insemination (CR_f), and number of inseminations (NS) recorded in heifers and first-parity cows. The results indicated that combining data from different regions resulted in greater genomic prediction accuracies compared with using data from single regions, with increases ranging from 2.74% to 93.81%. This improvement was particularly notable for the region with the least amount of available data, where the increases ranged from 26.49% to 93.81%. Furthermore, the predictive abilities could be validated for all studied traits based on the LR method across different environments when fitting RNM. The prediction accuracies and bias of genomic breeding values based on RNM were better than regular single-trait animal models in extreme climatic conditions for IFL and NS, whereas limited increases in predictive abilities were observed for CR_f. Across-regional genomic prediction by RNM can account for genotype-by-environment interactions, potentially increase the accuracy of genomic prediction, and predict the performances of individuals in the environments with limited phenotypic data available.

POLR3B is associated with a developmental and epileptic encephalopathy with myoclonic-atonic seizures and ataxia.

POLR3B encodes the second largest subunit of RNA polymerase III, which is essential for transcription of small non-coding RNAs. Biallelic pathogenic variants in POLR3B are associated with an inherited hypomyelinating leukodystrophy. Recently, de novo heterozygous variants in POLR3B were reported in six individuals with ataxia, spasticity, and demyelinating peripheral neuropathy. Three of these individuals had epileptic seizures. The aim of this article is to precisely define the epilepsy phenotype associated with de novo heterozygous POLR3B variants. We used online gene-matching tools to identify 13 patients with de novo POLR3B variants. We systematically collected genotype and phenotype data from clinicians using two standardized proformas. All 13 patients had novel POLR3B variants. Twelve of 13 variants were classified as pathogenic or likely pathogenic as per American College of Medical Genetics (ACMG) criteria. Patients presented with generalized myoclonic, myoclonic-atonic, atypical absence, or tonic-clonic seizures between the ages of six months and 4 years. Epilepsy was classified as epilepsy with myoclonic-atonic seizures (EMAtS) in seven patients and "probable EMAtS" in two more. Seizures were treatment resistant in all cases. Three patients became seizure-free. All patients had some degree of developmental delay or intellectual disability. In most cases developmental delay was apparent before the onset of seizures. Three of 13 cases were reported to have developmental stagnation or regression in association with seizure onset. Treatments for epilepsy that were reported by clinicians to be effective were: sodium valproate, which was effective in five of nine patients (5/9) who tried it; rufinamide (2/3); and ketogenic diet (2/3). Additional features were ataxia/incoordination (8/13); microcephaly (7/13); peripheral neuropathy (4/13), and spasticity/hypertonia (6/13). POLR3B is a novel genetic developmental and epileptic encephalopathy (DEE) in which EMAtS is the predominant epilepsy phenotype. Ataxia, neuropathy, and hypertonia may be variously observed in these patients.

Facilitating integrative and personalized oncology omics analysis with UCSCXenaShiny.

The continuous generation of multi-omics and phenotype data is propelling advancements in precision oncology. UCSCXenaShiny was developed as an interactive tool for exploring thousands of cancer datasets available on UCSC Xena. However, its capacity for comprehensive and personalized pan-cancer data analysis is being challenged by the growing demands. Here, we introduce UCSCXenaShiny v2, a milestone update through a variety of improvements. Firstly, by integrating multidimensional data and implementing adaptable sample settings, we create a suite of robust TPC (TCGA, PCAWG, CCLE) analysis pipelines. These pipelines empower users to conduct in-depth analyses of correlation, comparison, and survival in three modes: Individual, Pan-cancer and Batch screen. Additionally, the tool includes download interfaces that enable users to access diverse data and outcomes, several features also facilitate the joint analysis of drug sensitivity and multi-omics of cancer cell lines. UCSCXenaShiny v2 is an open-source R package and a web application, freely accessible at https://github.com/openbiox/UCSCXenaShiny .

Roseobacter weihaiensis sp. nov., a cellulose-degrading bacterium isolated from intestinal content of Nipponacmea schrenckii collected from golden beach in Weihai, China.

A Gram-staining-negative, dark pink, rod-shaped, amastigote and cellulose-degrading strain, designated H9T, was isolated from intestinal contents of Nipponacmea schrenckii. The isolate was able to grow at 4-42°C (optimum, 25°C), at pH 6.5-9.0 (optimum, pH 7.0), and with 0.0-11.0% (w/v) NaCl (optimum, 3.0-5.0%). Phylogenetic analysis of the 16S rRNA gene sequence suggested that isolate H9T belongs to the genus Roseobacter, neighboring Roseobacter insulae YSTF-M11T, Roseobacter cerasinus AI77T and Roseobacter ponti MM-7T, and the pairwise sequence showed the highest similarity of 99.1% to Roseobacter insulae YSTF-M11T. The major fatty acid was summed feature 8 (C18:1ω7c and/or C18:1ω6c; 81.08%). The predominant respiratory quinone was Q-10. The polar lipids consisted of phosphatidylcholine, phosphatidylglycerol, an unknown lipid, and a small amount of an unknown phospholipid. The genome of strain H9T was 5,351,685bp in length, and the DNA G + C content was 59.8%. The average amino acid identity (AAI), average nucleotide identity (ANI), and digital DNA hybridization (dDDH) values between strain H9T and closely related strains were 63.4-76.8%, 74.7-78.8%, and 13.4-19.7%, respectively. On the basis of the phenotypic, chemical taxonomic, and phylogenetic data, it is suggested that strain H9T should represent a novel species in the genus Roseobacter, for which the name Roseobacter weihaiensis sp. nov.is proposed. The type strain is H9T (= KCTC 82507T = MCCC 1K04354T).

Tracing post-domestication historical events and screening pre-breeding germplasm from large gene pools in wheat in the absence of phenotype data.

Wheat, particularly common wheat (Triticum aestivum L.), is a major crop accounting for 25% of the world cereal production and thriving indiverse ecogeographic regions. Its adaptation to diverse environments arises from its three distinct genomes adapted to different environments and post-domestication anthropogenic interventions. In search of key genomic regions revealing historic events and breeding significance to common wheat, we performed genome scan and genome-environment association (GEA) analyses using high-marker density genotype datasets. Whole-genome scans revealed highly differentiated regions on chromosomes 2A, 3B, and 4A. In-depth analyses corroborated our previous prediction of the 4A differentiated region signifying the separation between Spelt/Macha and other wheat types. Individual chromosome scans captured key introgressions, includingone from T. timopheevii and one fromThinopyrum ponticum on 2B and 3D, respectively, as well as known genes such as Vrn-A1 on 5A. GEA highlighted loci linked to latitude-induced environmental variations, influencing traits such as photoperiodism and responses to abiotic stress. Variation at theVrn-A1 locus on 5A assigned accessions to two haplotypes (6% and 94%). Further analysis on Vrn-A1 coding gene revealed four subgroups of the major haplotype, while the minor haplotype remained undifferentiated. Analyses at differentiated loci mostly dichotomized the population, illustrating the possibility of isolating pre-breeding materials with desirable traits from large gene pools in the absence of phenotype data. Given the current availability of broad genetic data, the genome-scan-GEA hybrid can be anefficient and cost-effective approach for pinpointing environmentally resilient pre-breeding germplasm from vast gene pools, including gene banks regardless of trait characterization.

Deciphering the genetic basis of salinity tolerance in a diverse panel of cultivated and wild soybean accessions by genome-wide association mapping

Key messageIn a genome-wide association study involving 269 cultivated and wild soybean accessions, potential salt tolerance donors were identified along with significant markers and candidate genes, such as GmKUP6 and GmWRKY33.Salt stress remains a significant challenge in agricultural systems, notably impacting soybean productivity worldwide. A comprehensive genome-wide association study (GWAS) was conducted to elucidate the genetic underpinnings of salt tolerance and identify novel source of salt tolerance among soybean genotypes. A diverse panel comprising 269 wild and cultivated soybean accessions was subjected to saline stress under controlled greenhouse conditions. Phenotypic data revealed that salt tolerance of soybean germplasm accessions was heavily compromised by the accumulation of sodium and chloride, as indicated by highly significant positive correlations of leaf scorching score with leaf sodium/chloride content. The GWAS analysis, leveraging a dataset of 32,832 SNPs, unveiled 32 significant marker-trait associations (MTAs) across seven traits associated with salt tolerance. These markers explained a substantial portion of the phenotypic variation, ranging from 14 to 52%. Notably, 11 markers surpassed Bonferroni’s correction threshold, exhibiting highly significant associations with the respective traits. Gene Ontology enrichment analysis conducted within a 100 Kb range of the identified MTAs highlighted candidate genes such as potassium transporter 6 (GmKUP6), cation hydrogen exchanger (GmCHX15), and GmWRKY33. Expression levels of GmKUP6 and GmWRKY33 significantly varied between salt-tolerant and salt-susceptible soybean accessions under salt stress. The genetic markers and candidate genes identified in this study hold promise for developing soybean varieties resilient to salinity stress, thereby mitigating its adverse effects.

Exploring AMR and virulence in Klebsiella pneumoniae isolated from humans and pet animals: A complement of phenotype by WGS-derived profiles in a One Health study in Egypt

Klebsiella pneumoniae is a ubiquitous nosocomial pathogen associated with various types of infections in hospitalized patients and different animal species. In the current study, 49 Klebsiella strains isolated from humans, dogs, and cats were investigated using NGS technology. MALDI-TOF failed to identify newly discovered K. variicola and K. quasipneumoniae isolates correctly. MLST analysis revealed different sequence types among K. pneumoniae isolates, and the most frequent STs were ST29, ST219, and ST37. Three ST23 that are generally known as hypervirulent type were identified but they lacked major discriminatory determinants for hypervirulent K. pneumoniae (hvKp). K. pneumoniae isolates showed high diversity, and several isolates from humans and animals were assigned to the same ST and were almost identical. Isolates from humans exhibited more pronounced resistance patterns compared to the animal isolates. High levels of resistance were observed for piperacillin, trimethoprim/sulfamethoxazole, and cephalosporins, and resistance to carbapenem compounds was only found in isolates of human origin. Three strains of human origin were extensively drug-resistant (XDR). A diverse range of resistance genes primarily confer resistance to beta-lactams., phenicol/quinolone, aminoglycoside, macrolide, sulfonamides, and fosfomycin were identified in silico. However, there were inconsistencies between the phenotypic characterization of isolates and the set of resistance genes detected in silico in this set of Klebsiella isolates. Further research using a larger number of isolates from various sources is necessary to fully comprehend the relationship between the presence of antimicrobial resistance determinants and phenotypic data. It is also necessary to monitor the spread of K. pneumoniae from a One Health perspective in Egypt.

Whole genome sequencing analysis identifies sex differences of familial pattern contributing to phenotypic diversity in autism

BackgroundWhole-genome sequencing (WGS) analyses have found higher genetic burden in autistic females compared to males, supporting higher liability threshold in females. However, genomic evidence of sex differences has been limited to European ancestry to date and little is known about how genetic variation leads to autism-related traits within families across sex.MethodsTo address this gap, we present WGS data of Korean autism families (n = 2255) and a Korean general population sample (n = 2500), the largest WGS data of East Asian ancestry. We analyzed sex differences in genetic burden and compared with cohorts of European ancestry (n = 15,839). Further, with extensively collected family-wise Korean autism phenotype data (n = 3730), we investigated sex differences in phenotypic scores and gene-phenotype associations within family.ResultsWe observed robust female enrichment of de novo protein-truncating variants in autistic individuals across cohorts. However, sex differences in polygenic burden varied across cohorts and we found that the differential proportion of comorbid intellectual disability and severe autism symptoms mainly drove these variations. In siblings, males of autistic females exhibited the most severe social communication deficits. Female siblings exhibited lower phenotypic severity despite the higher polygenic burden than male siblings. Mothers also showed higher tolerance for polygenic burden than fathers, supporting higher liability threshold in females.ConclusionsOur findings indicate that genetic liability in autism is both sex- and phenotype-dependent, expanding the current understanding of autism’s genetic complexity. Our work further suggests that family-based assessments of sex differences can help unravel underlying sex-differential liability in autism.

Effect of Environmental and Anthropic Conditions on the Development of Solanum peruvianum: A Case of the Coastal Lomas, Lima-Peru

Land degradation and the effects of climate change are increasing arid lands, accelerating desertification, and leading to the loss of ecosystem services worldwide. This research focused on evaluating how human impact and environmental factors affect the development of Solanum peruvianum in its natural habitat of coastal lomas. The study was carried out in the coastal lomas of Mangomarca-Peru, where phenotypic and ecological data on the plants were collected. Information was also gathered on human impacts on the nutritional characteristics of the soils. Then, five types of organic amendments were used to improve the physical and chemical characteristics of the degraded soil, and the development and photosynthetic activity of S. peruvianum were evaluated. As a result, under the study conditions, it was found that S. peruvianum was established approximately 33.74 cm from the rocks, in a range of 300 to 650 m asl. The maximum height of the plants was 90 cm, with a stem diameter at ground level of 2 cm. S. peruvianum produced fruits between January and July, with a seed germination rate of 36% in 25 days. On the other hand, the anthropogenic impact on the soil reduced 58% of organic material (OM), 71% of nitrogen, 40% of P2O5, and 13% of K2O and increased the concentration of magnesium oxide, calcium oxide, pH, and electric conductivity (EC). The organic amendments bokashi, compost, and biochar, when mixed with the degraded soil, increased the pH, OM, N, P, and EC; however, the plants died after 25 days. On the other hand, the application of the Premix5 substrate for 100 days favored the growth of 52.84 cm and 38.29 cm in the preserved soil and 23.21 cm in the black soil mixed with blond peat, and it should be noted that the substrates presented an acid pH and EC > 0.1. Regarding photosynthetic phenotyping, S. peruvianum plants grown in their natural habitat and in Premix5 showed a higher proton flux (vH+), linear electron flow (LEF), and maximum quantum yield (Fv’/Fm’). On the contrary, they showed a lower NPQt value than plants grown in preserved and black soil mixed with blond peat.

Bacterial N-Acyl Homoserine Lactone Priming Enhances Leaf-Rust Resistance in Winter Wheat and Some Genomic Regions Are Associated with Priming Efficiency.

Leaf rust (Puccinia triticina) is a common disease that causes significant yield losses in wheat. The most frequently used methods to control leaf rust are the application of fungicides and the cultivation of resistant genotypes. However, high genetic diversity and associated adaptability of pathogen populations hamper achieving durable resistance in wheat. Emerging alternatives, such as microbial priming, may represent an effective measure to stimulate plant defense mechanisms and could serve as a means of controlling a broad range of pathogens. In this study, 175 wheat genotypes were inoculated with two bacterial strains: Ensifer meliloti strain expR+ch (producing N-acyl homoserine lactone (AHL)) or transformed E. meliloti carrying the lactonase gene attM (control). In total, 21 genotypes indicated higher resistance upon bacterial AHL priming. Subsequently, the phenotypic data of 175 genotypes combined with 9917 single-nucleotide polymorphisms (SNPs) in a genome-wide association study to identify quantitative trait loci (QTLs) and associated markers for relative infection under attM and expR+ch conditions and priming efficiency using the Genome Association and Prediction Integrated Tool (GAPIT). In total, 15 QTLs for relative infection under both conditions and priming efficiency were identified on chromosomes 1A, 1B, 2A, 3A, 3B, 3D, 6A, and 6B, which may represent targets for wheat breeding for priming and leaf-rust resistance.

Loss-of-function variants in JPH1 cause congenital myopathy with prominent facial and ocular involvement

BackgroundWeakness of facial, ocular and axial muscles is a common clinical presentation in congenital myopathies caused by pathogenic variants in genes encoding triad proteins. Abnormalities in triad structure and function...

Diverse signatures of convergent evolution in cactus-associated yeasts.

Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question. Here, we leverage a comprehensive dataset of genomic and phenotypic data from 1,049 yeast species in the subphylum Saccharomycotina (Kingdom Fungi, Phylum Ascomycota) to explore signatures of convergent evolution in cactophilic yeasts, ecological specialists associated with cacti. We inferred that the ecological association of yeasts with cacti arose independently approximately 17 times. Using a machine learning-based approach, we further found that cactophily can be predicted with 76% accuracy from both functional genomic and phenotypic data. The most informative feature for predicting cactophily was thermotolerance, which we found to be likely associated with altered evolutionary rates of genes impacting the cell envelope in several cactophilic lineages. We also identified horizontal gene transfer and duplication events of plant cell wall-degrading enzymes in distantly related cactophilic clades, suggesting that putatively adaptive traits evolved independently through disparate molecular mechanisms. Notably, we found that multiple cactophilic species and their close relatives have been reported as emerging human opportunistic pathogens, suggesting that the cactophilic lifestyle-and perhaps more generally lifestyles favoring thermotolerance-might preadapt yeasts to cause human disease. This work underscores the potential of a multifaceted approach involving high-throughput genomic and phenotypic data to shed light onto ecological adaptation and highlights how convergent evolution to wild environments could facilitate the transition to human pathogenicity.

Effects of Various Levels of Water Stress on Morpho-Physiological Traits and Spectral Reflectance of Maize at Seedling Growth Stage

Water stress (drought and waterlogging) is one highly important factor affecting food security in China. Investigating the effects of soil moisture stress on the morphological and physiological characteristics of maize seedlings is crucial for ensuring food production. The use of spectral monitoring to observe crop phenotypic traits and assess crop health has become a focal point in field crop research. However, studies exploring the contribution of crop phenotypic and physiological data to the Normalized Difference Vegetation Index (NDVI) are still limited. In this study, a 35-day pot experiment was conducted with seven soil moisture gradients: 50%, 60%, 70%, 80% (control group, CK), 90%, 100%, and 110% treatment. In order to investigate the effects of soil moisture stress on seedling phenotypes, antioxidant enzyme activities, and NDVI, an ASD FieldSpec 4 Hi-Res NG portable spectrometer was used to collect spectral data from maize (Zea mays L. B73) leaves. The contributions of maize phenotypic and physiological traits to NDVI were also examined. The results indicated that (1) the 50% and 110% treatments significantly affected maize seedling phenotypes compared to the CK group; (2) the activities of superoxide dismutase (SOD) and peroxidase (POD) in the leaves increased under water stress, while the activities of glutathione peroxidase (GSH-PX) and ascorbate peroxidase (APX) decreased; (3) soil moisture stress (drought and waterlogging) reduced photosynthetic pigments, chlorophyll content (SPAD), and NDVI, with inhibitory effects intensifying as the stress level increased; (4) Redundancy analysis showed that antioxidant enzymes explained 69.87% of the variation in seedling height, leaf area, and NDVI. Soil moisture stress, chlorophyll, and SPAD explained 58.14% of the variation in these parameters. The results demonstrated that maize seedlings were highly sensitive to soil moisture changes, and the SPAD value contributed significantly to NDVI (p < 0.01). This study provides valuable insights for future research in precision agriculture management

Needle and Branch Trait Variation Analysis and Associated SNP Loci Mining in Larix olgensis.

Needles play key roles in photosynthesis and branch growth in Larix olgensis. However, genetic variation and SNP marker mining associated with needle and branch-related traits have not been reported yet. In this study, we examined 131 samples of unrelated genotypes from L. olgensis provenance trails. We investigated phenotypic data for seven needle and one branch-related traits before whole genome resequencing (WGRS) was employed to perform a genome-wide association study (GWAS). Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci that were significantly correlated with the studied traits. We identified a total of 243,090,868 SNP loci, and among them, we discovered a total of 161 SNP loci that were significantly associated with these traits using a general linear model (GLM). Based on the GWAS results, Kompetitive Allele-Specific PCR (KASP), designed based on the DNA of population samples, were used to validate the loci associated with L. olgensis phenotypes. In total, 20 KASP markers were selected from the 161 SNPs loci, and BSBM01000635.1_4693780, BSBM01000114.1_5114757, and BSBM01000114.1_5128586 were successfully amplified, were polymorphic, and were associated with the phenotypic variation. These developed KASP markers could be used for the genetic improvement of needle and branch-related traits in L. olgensis.

Levels of Amyloid Beta (Aβ) Expression in the Caenorhabditis elegans Neurons Influence the Onset and Severity of Neuronally Mediated Phenotypes.

A characteristic feature of Alzheimer's disease (AD) is the formation of neuronal extracellular senile plaques composed of aggregates of fibrillar amyloid β (Aβ) peptides, with the Aβ1-42 peptide being the most abundant species. These Aβ peptides have been proposed to contribute to the pathophysiology of the disease; however, there are few tools available to test this hypothesis directly. In particular, there are no data that establish a dose-response relationship between Aβ peptide expression level and disease. We have generated a panel of transgenic Caenorhabditis elegans strains expressing the human Aβ1-42 peptide under the control of promoter regions of two pan-neuronal expressed genes, snb-1 and rgef-1. Phenotypic data show strong age-related defects in motility, subtle changes in chemotaxis, reduced median and maximum lifespan, changes in health span indicators, and impaired learning. The Aβ1-42 expression level of these strains differed as a function of promoter identity and transgene copy number, and the timing and severity of phenotypes mediated by Aβ1-42 were strongly positively correlated with expression level. The pan-neuronal expression of varying levels of human Aβ1-42 in a nematode model provides a new tool to investigate the in vivo toxicity of neuronal Aβ expression and the molecular and cellular mechanisms underlying AD progression in the absence of endogenous Aβ peptides. More importantly, it allows direct quantitative testing of the dose-response relationship between neuronal Aβ peptide expression and disease for the first time. These strains may also be used to develop screens for novel therapeutics to treat Alzheimer's disease.

The Unified Phenotype Ontology (uPheno): A framework for cross-species integrative phenomics.

Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.

A Review on Integrating Bioinformatics Tools in Modern Plant Breeding

Bioinformatics has become integral to modern plant breeding, facilitating the analysis of large-scale genomic data, identifying key genetic markers, and enabling precision breeding techniques such as genomic selection. Advances in sequencing technologies and computational tools have accelerated the pace of crop improvement, allowing for the rapid identification of genes associated with important agronomic traits, including yield, stress tolerance, and disease resistance. The integration of bioinformatics in plant breeding also presents significant challenges, particularly in terms of data management, multi-omics integration, and the interpretation and validation of complex datasets. The role of emerging trends such as pangenomics, metagenomics, and epigenomics in expanding the scope of plant breeding, as well as the increasing importance of artificial intelligence and machine learning in enhancing predictive accuracy and optimizing breeding strategies. Personalized plant breeding and precision agriculture are identified as promising approaches for tailoring crop varieties to specific environments and farming practices, driven by bioinformatics tools that enable detailed analysis of genomic and phenotypic data. Ethical considerations and data privacy issues are also addressed, emphasizing the need for transparent and equitable practices in the collection, sharing, and use of genomic data. The importance of collaborative efforts and global initiatives in advancing bioinformatics-driven plant breeding, with a focus on fostering international cooperation, building capacity in developing regions, and ensuring open access to bioinformatics resources. As the field continues to evolve, bioinformatics will play a Important role in developing sustainable agricultural systems capable of meeting the demands of a growing global population while mitigating the impacts of climate change. The current applications, challenges, and future prospects of bioinformatics in plant breeding, offering insights into the critical role of this field in shaping the future of agriculture.

Rpv10.2: A Haplotype Variant of Locus Rpv10 Enables New Combinations for Pyramiding Downy Mildew Resistance Traits in Grapevine.

In viticulture, pathogens like the oomycete Plasmopara viticola, the causal agent of downy mildew, can cause severe yield loss and require extensive application of plant protection chemicals. Breeders are generating pathogen-resistant varieties exploiting American and Asian wild Vitis germplasm as sources of resistance. Several loci mediating resistance to P. viticola have been identified in the past but may be overcome by specifically adapted strains of the pathogen. Aiming to find and characterize novel loci, a cross population with Vitis amurensis ancestry was investigated searching for resistance-correlated quantitative trait loci (QTL). As a prerequisite, a genetic map was generated by analyzing the 244 F1 individuals derived from a cross of the downy mildew susceptible Vitis vinifera cultivar 'Tigvoasa' and the resistant V. amurensis pBC1 breeding line We 90-06-12. This genetic map is based on the information from 627 molecular markers including 56 simple sequence repeats and 571 rhAmpSeq markers. A phenotypic characterization of the progeny showed a clear segregation of the resistance traits in the F1 population after an experimental inoculation of leaf discs with downy mildew. Combining genetic and phenotypic data, an analysis for QTL revealed a major locus on linkage Group 9 that correlates strongly with the resistance to downy mildew. The locus was mapped to a region of about 80 kb on the PN40024 (12x.V2) grapevine reference genome. This genomic region co-localizes with the formerly identified locus Rpv10 from the grapevine cultivar 'Solaris'. As we found different allele sizes of the locus-linked SSR markers than those characterizing the known Rpv10 locus and differences in the sequence of a candidate gene, it was regarded as a haplotype variant and named Rpv10.2.

Similarities and differences between osteoarthritis and rheumatoid arthritis: insights from Mendelian randomization and transcriptome analysis

BackgroundOsteoarthritis (OA) and rheumatoid arthritis (RA) are often difficult to distinguish in the early stage of the disease. The purpose of this study was to explore the similarities and differences between the two diseases through Mendelian randomization (MR) and transcriptome analysis.MethodsWe first performed a correlation analysis of phenotypic data from genome-wide association studies (GWAS) of OA and RA. Then, we performed functional and pathway enrichment of differentially expressed genes in OA, RA, and normal patients. The infiltration of immune cells in arthritis was analyzed according to gene expression. Finally, MR analysis was performed with inflammatory cytokines and immune cells as exposures and arthritis as the outcome. The same and different key cytokines and immune cells were obtained by the two analysis methods.ResultsGWAS indicated that there was a genetic correlation between OA and RA. The common function of OA and RA is enriched in their response to cytokines, while the difference is enriched in lymphocyte activation. T cells are the main immune cells that differentiate between OA and RA. MR analysis further revealed that OA is associated with more protective cytokines, and most of the cytokines in RA are pathogenic. In addition, CCR7 on naive CD4 + T cell was positively correlated with OA. SSC-A on CD4 + T cell was negatively correlated with RA, while HLA DR on CD33- HLA DR + was positively correlated with RA.ConclusionOur study demonstrated the similarities and differences of immune inflammation between OA and RA, allowing us to better understand these two diseases.

Taxonogenomic analysis of the Xanthomonas translucens complex leads to the descriptions of Xanthomonas cerealis sp. nov. and Xanthomonas graminis sp. nov.

The pathovar-based taxonomy of the Xanthomonas translucens group is very confusing due to an overlap of plant host ranges and level of host specificity. Here, whole-genome sequence-based parameters (digital DNA–DNA hybridization and blast-based average nucleotide identity), phylogenomic, biochemical and phenotypical data were used to taxonomically analyse the 11 known pathovars of the X. translucens complex. This polyphasic approach taxonomically assigned the 11 pathovars of X. translucens complex into three distinct species, two of which are new: X. translucens, X. cerealis sp. nov. and X. graminis sp. nov. X. translucens consists of three pathovars: pv. translucens (=pv. hordei), pv. pistaciae strain A ICMP 16316PT and pv. undulosa (=pv. secalis). X. cerealis sp. nov. encompasses the pv. cerealis strain LMG 679PT and pv. pistaciae strain B ICMP 16317PT with genome similarity of 92.7% (dDDH) and 99.0% (ANIb) suggesting taxonomically similar genotypes. The other new species, X. graminis sp. nov., consists of the remaining five designated pathovars (pv. graminis, pv. arrhenatheri, pv. poae, pv. phleipratensis and pv. phlei) with highly variable dDDH and ANIb values ranging from 74.5 to 93.0% and from 96.7 to 99.2%, respectively, an indication of a very divergent taxonomic group. Only strains of pvs. phlei and phleipratensis showed the highest genomic similarities of 93.0% (dDDH) and 99.2% (ANIb), suggesting synonymic pathovars as both infect the same plant hosts. The dDDH and ANI data were corroborated by phylogenomics clustering. The fatty acid contents were similar but the type strain of X. graminis sp. nov. exhibited 20% less C15 : 0 iso and 40% more C17 : 0 iso fatty acids than the other species. Based on phenotypic, biochemical and whole-genome sequence data, we propose two new species, Xanthomonas cerealis sp. nov. and Xanthomonas graminis sp. nov. with type strains LMG 679T (=NCPPB 1944T) and LMG 726T (=NCPPB 2700T), respectively.