Genotypic Differentiation Research Articles

Multimodal MRI and 1H-MRS for Preoperative Stratification of High-Risk Molecular Subtype in Adult-Type Diffuse Gliomas

Isocitrate dehydrogenase (IDH) and O6-methylguanine-DNA methyltransferase (MGMT) genes are critical molecular markers in determining treatment options and predicting the prognosis of adult-type diffuse gliomas. Objectives: this study aimed to investigate whether multimodal MRI enables the differentiation of genotypes in adult-type diffuse gliomas. Methods: a total of 116 adult-type diffuse glioma patients (61 males, 51.5 (37, 62) years old) who underwent multimodal MRI before surgery were retrospectively analysed. Multimodal MRI included conventional MRI, proton magnetic resonance spectroscopy (1H-MRS), and diffusion tensor imaging (DTI). Conventional visual features, N-acetyl-aspartate (NAA)/Creatine (Cr), Choline (Cho)/Cr, Cho/NAA, fractional anisotropy (FA), mean diffusivity (MD), and diffusion histogram parameters were extracted on the whole tumour. Multimodal MRI parameters of IDH-mutant and IDH-wildtype gliomas were compared using the Mann–Whitney U test, Student’s t-test, or Pearson chi-square tests. Logistic regression was used to select the MRI parameters to predict IDH-mutant gliomas. Furthermore, multimodal MRI parameters were selected to establish models for predicting MGMT methylation in the IDH-wildtype gliomas. The performance of models was evaluated by the receiver operating characteristics curve. Results: a total of 56 patients with IDH-mutant gliomas and 60 patients with IDH-wildtype glioblastomas (GBM) (37 with methylated MGMT and 17 with unmethylated MGMT) were diagnosed by 2021 WHO classification criteria. The enhancement degree (OR = 4.298, p < 0.001), necrosis/cyst (OR = 5.381, p = 0.011), NAA/Cr (OR = 0.497, p = 0.037), FA-Skewness (OR = 0.497, p = 0.033), MD-Skewness (OR = 1.849, p = 0.035), FAmean (OR = 1.924, p = 0.049) were independent factors for the multimodal combined prediction model in predicting IDH-mutant gliomas. The combined modal based on conventional MRI, 1H-MRS, DTI parameters, and histogram performed best in predicting IDH-wildtype status (AUC = 0.890). However, only NAA/Cr (OR = 0.17, p = 0.043) and FA (OR = 0.38, p = 0.015) were associated with MGMT methylated in IDH-wildtype GBM. The combination of NAA/Cr and FA-Median is more accurate for predicting MGMT methylation levels than using these elements alone (AUC, 0.847 vs. 0.695/0.684). Conclusions: multimodal MRI based on conventional MRI, 1H-MRS, and DTI can provide compound imaging markers for stratified individual diagnosis of IDH mutant and MGMT promoter methylation in adult-type diffuse gliomas.

Genosensor based on polypyrrole and dendrimer-coated gold nanoparticles for human papillomavirus detection

Human Papillomavirus (HPV) is an often asymptomatic widespread sexually transmitted infection responsible for causing various health issues. Low-risk HPV primarily causes genital warts. High-risk HPV types are associated with several cancers, including cervical, anal, and oropharyngeal cancers, posing significant health risks. In this work, we developed an electrochemical biosensor for the detection and differentiation of HPV genotypes based on electropolymerized polypyrrole (PPy) and PAMAM dendrimer-coated gold nanoparticles (PAMAM-AuNPs) for the immobilization of a DNA probe for detecting different HPV genotypes. Electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and atomic force microscopy (AFM) were used to characterize the biosensor. AFM analysis revealed varied topographic surfaces associated with the increased peaks concerning the biosensor and against patient samples. Electrochemical responses indicated that the genosensor could detect HPV using plasmid (HPV 6, 16, 18, 31, and 33) and cDNA samples (HPV 6, 18, and 31) from infected patients. Different electrochemical profiles were obtained between high-risk and low-risk genotypes. The sensor presented an excellent analytical performance, presenting a lower LOD of 0.04 pg.µL−1 and 0.34 pg.µL−1 for plasmidial and cDNA samples, respectively. Electrochemical analysis pointed out the ability of the developed genosensor platform to differentiate the HPV genotypes. The proposed biosensor is a promising tool for detecting and monitoring HPV and related diseases such as cervical cancer.

Genotypic differentiation and evolutionary dynamics of puumala orthohantavirus (PUUV)

Genotypic differentiation and evolutionary dynamics of puumala orthohantavirus (PUUV)

Microfluid biosensor for detection of hpv in patient scraping samples: Determining E6 and E7 oncogenes

E6 and E7 oncogenes are pivotal in the carcinogenic transformation in HPV infections and efficient diagnostic methods can ensure the detection and differentiation of HPV genotype. This study describes the development and validation of an electrochemical, label-free genosensor coupled with a microfluidic system for detecting the E6 and E7 oncogenes in cervical scraping samples. The nanostructuring employed was based on a cysteine and graphene quantum dots layer that provides functional groups, surface area, and interesting electrochemical properties. Biorecognition tests with cervical scraping samples showed differentiation in the voltammetric response. Low-risk HPV exhibited a lower biorecognition response, reflected in ΔI% values of 82.33 % ± 0.29 for HPV06 and 80.65 % ± 0.68 for HPV11 at a dilution of 1:100. Meanwhile, high-risk, HPV16 and HPV18, demonstrated ΔI% values of 96.65 % ± 1.27 and 93 % ± 0.026, respectively, at the same dilution. Therefore, the biorecognition intensity followed the order: HPV16 >HPV18 >HPV06 >HPV11. The limit of detection and the limit of quantification of E6E7 microfluidic LOC−Genosensor was 26 fM, and 79.6 fM. Consequently, the E6E7 biosensor is a valuable alternative for clinical HPV diagnosis, capable of detecting the potential for oncogenic progression even in the early stages of infection.

Genomic, morphological and physiological data support fast ecotypic differentiation and incipient speciation in an alpine diving beetle.

An intricate interplay between evolutionary and demographic processes has frequently resulted in complex patterns of genetic and phenotypic diversity in alpine lineages, posing serious challenges to species delimitation and biodiversity conservation planning. Here we integrate genomic data, geometric morphometric analyses and thermal tolerance experiments to explore the role of Pleistocene climatic changes and adaptation to alpine environments on patterns of genomic and phenotypic variation in diving beetles from the taxonomically complex Agabus bipustulatus species group. Genetic structure and phylogenomic analyses revealed the presence of three geographically cohesive lineages, two representing trans-Palearctic and Iberian populations of the elevation-generalist A. bipustulatus and another corresponding to the strictly-alpine A. nevadensis, a narrow-range endemic taxon from the Sierra Nevada mountain range in southeastern Iberia. The best-supported model of lineage divergence, along with the existence of pervasive genetic introgression and admixture in secondary contact zones, is consistent with a scenario of population isolation and connectivity linked to Quaternary climatic oscillations. Our results suggest that A. nevadensis is an alpine ecotype of A. bipustulatus, whose genotypic, morphological and physiological differentiation likely resulted from an interplay between population isolation and local altitudinal adaptation. Remarkably, within the Iberian Peninsula, such ecotypic differentiation is unique to Sierra Nevada populations and has not been replicated in other alpine populations of A. bipustulatus. Collectively, our study supports fast ecotypic differentiation and incipient speciation processes within the study complex and points to Pleistocene glaciations and local adaptation along elevational gradients as key drivers of biodiversity generation in alpine environments.

Gilvirhabdus luticola gen. nov., sp. nov., a mesophilic and halophilic bacterium isolated from tidal flat sediment.

Two novel bacteria, MJ-SS3T and MJ-SS4, were isolated from tidal flat sediment sampled in Gochang, Republic of Korea. The isolates were Gram-stain-negative, aerobic, non-motile, rod-shaped, yellow-coloured, oxidase-positive, and catalase-positive. Strains MJ-SS3T and MJ-SS4 grew at 20-37 °C (optimum, 30 °C), at pH 6-8 (optimum, pH 7.0) and in the presence of 0-7 % (w/v) NaCl (optimum, 2.0 % NaCl). Strains MJ-SS3T and MJ-SS4 showed 99.9 % 16S rRNA gene sequence similarity. Phylogenetic analysis based on genome and 16S rRNA gene sequences indicated that strains MJ-SS3T and MJ-SS4 were affiliated with the family Flavobacteriaceae and most closely related to Formosa maritima 1494T (95.3 %), Hanstruepera flava NBU2984T (95.2 %), Yeosuana marina JLT21T (95.2 %), Meridianimaribacter flavus NH57NT (95.1 %), and Geojedonia litorea YCS-16T (95.1 %). The major respiratory quinone was menaquinone-6. The major identified polar lipids were phosphatidylethanolamine, phosphatidylglycerol, phosphatidylcholine, and amino lipids. The major cellular fatty acids of strain MJ-SS3T were iso-C15 : 1 G (24.6 %), iso-C15 : 0 (21.6 %), and iso-C17 : 0 3-OH (15.8 %). The genome length of strain MJ-SS3T is 3.1 Mbp (DNA G+C content, 32.5 mol%) and it has 2822 coding and 59 tRNA genes. The average amino acid identity and average nucleotide identity values, as well as biochemical, phylogenetic, and physiological characteristics, strongly supported the genotypic and phenotypic differentiation of strains MJ-SS3T and MJ-SS4 from other members of the family Flavobacteriaceae. Hence, strains MJ-SS3T and MJ-SS4 are considered to represent a novel species of a new genus in the family Flavobacteriaceae, for which the Gilvirhabdus luticola gen. nov., sp. nov. is proposed. The type strain is MJ-SS3T (=KCTC 102114T=KEMB 20189T=JCM 36595T), with reference strain MJ-SS4 (=KCTC 102115=KEMB 20190).

Evidence for feminized genetic males in a flea beetle using newly identified X-linked markers.

The equilibrium of sex ratios in sexually reproducing species is often disrupted by various environmental and genetic factors, including endosymbionts like Wolbachia. In this study, we explore the highly female-biased sex ratio observed in the flea beetle, Altica lythri, and its underlying mechanisms. Ancient hybridization events between Altica species have led to mitochondrial DNA introgression, resulting in distinct mitochondrial haplotypes that go along with different Wolbachia infections (HT1-wLytA1, HT1*- uninfected, HT2-wLytA2, and HT3-wLytB). Notably, beetles with some haplotypes exclusively produce female offspring, suggesting potential Wolbachia-induced phenomena such as feminization of genetic males. However, the observed female bias could also be a consequence of the ancient hybridization resulting in nuclear-cytoplasmic conflicts between introgressed mtDNA and nuclear genes. Through transcriptomic analysis and the program SEX-DETector, we established markers for genotypic sex differentiation for A. lythri, enabling genetic sexing via qPCR. Our findings suggest that feminization of genetic males is contributing to the skewed sex ratios, highlighting the intricate dynamics of sex determination and reproductive strategies in this flea beetle. This study provides valuable insights into the dynamics of genetic conflicts, endosymbionts, and sex ratios, revealing the novel phenomenon of genetic male feminization in the flea beetle A. lythri.

Single-nucleotide polymorphisms and copy number variations drive adaptive evolution to freezing stress in a subtropical evergreen broad-leaved tree: Hexaploid wild Camellia oleifera

Subtropical evergreen broad-leaved trees are usually vulnerable to freezing stress, while hexaploid wild Camellia oleifera shows strong freezing tolerance. As a valuable genetic resource of woody oil crop C. oleifera, wild C. oleifera can serve as a case for studying the molecular bases of adaptive evolution to freezing stress. Here, 47 wild C. oleifera from 11 natural distribution sites in China and 4 relative species of C. oleifera were selected for genome sequencing. “Min Temperature of Coldest Month” (BIO6) had the highest comprehensive contribution to wild C. oleifera distribution. The population genetic structure of wild C. oleifera could be divided into two groups: in cold winter (BIO6 ≤ 0 °C) and warm winter (BIO6 > 0 °C) areas. Wild C. oleifera in cold winter areas might have experienced stronger selection pressures and population bottlenecks with lower Ne than those in warm winter areas. 155 single-nucleotide polymorphisms (SNPs) were significantly correlated with the key bioclimatic variables (106 SNPs significantly correlated with BIO6). Twenty key SNPs and 15 key copy number variation regions (CNVRs) were found with genotype differentiation > 50% between the two groups of wild C. oleifera. Key SNPs in cis-regulatory elements might affect the expression of key genes associated with freezing tolerance, and they were also found within a CNVR suggesting interactions between them. Some key CNVRs in the exon regions were closely related to the differentially expressed genes under freezing stress. The findings suggest that rich SNPs and CNVRs in polyploid trees may contribute to the adaptive evolution to freezing stress.

Оценка крупноплодных форм подсолнечника коллекции ВИР

The purpose of the research was to study and identify among the collection samples of sunflower from the N. I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR) the most promising ones for the de-velopment of new large-seeded source material. The studies were carried out in 2022–2023 on the fields of the Don experimental station – a branch of the V.S. Pustovoit All-Russian Research Institute of Oil Crops in accordance with the methods of conducting field experiments with oil crops. In the source material nursery, 30 foreign and Russin samples of confectionery sunflower from the VIR collection were studied. Among the 30 studied numbers, only 13 had a weight of 1000 seeds above 100 g, which indicates their large-seeded size. According to the method of A.I. Mamonov on the differentiation of genotypes by the size of achenes using the indicator of the number of seeds in 1 liter, it was confirmed that all 12 samples are large-seeded. According to meanings of oil content and huskness, nine samples belong to edible type, and three – confectionary type.

Denitrificimonas halotolerans sp. nov., a novel species isolated from UASB sludge treating landfill leachate.

A Gram-stain-negative, facultative anaerobe, rod-shaped strain JX-1T was isolated from UASB sludge treating landfill leachate in Wuhan, China. The isolate is capable of growing under conditions of pH 6.0-11.0 (optimum, pH 7.0-8.0), temperature 4-42℃ (optimum, 20-30℃), 0-8.0% (w/v) NaCl (optimum, 5.0%), and ammonia nitrogen concentration of 200-5000mg/L (optimum, 500mg/L) on LB plates. The microorganism can utilize malic acid, D-galactose, L-rhamnose, inosine, and L-glutamic acid as carbon sources, but does not reduce nitrates and nitrites. The major fatty acids are C18:1ω7c/C18:1ω6c, iso-C15:0, and anteiso-C15:0. The respiratory quinones are Q9 (91.92%) and Q8 (8.08%). Polar lipids include aminolipid, aminophospholipid, diphosphatidylglycerol, glycolipid, phosphatidylethanolamine, phosphatidylglycerol, and phospholipid. Compared with other strains, strain JX-1T and Denitrificimonas caeni HY-14T have the highest values in terms of 16S rRNA gene sequence similarity (96.79%), average nucleotide identity (ANI; 76.06%), and average amino acid identity (AAI; 78.89%). Its digital DNA-DNA hybridization (dDDH) result is 20.3%. The genome of strain JX-1T, with a size of 2.78Mb and 46.12mol% G + C content, lacks genes for denitrification and dissimilatory nitrate reduction to ammonium (DNRA), but contains genes for ectoine synthesis as a secondary metabolite. The results of this polyphasic study allow genotypic and phenotypic differentiation of the analysed strain from the closest related species and confirm that the strain represents a novel species within the genus Denitrificimonas, for which the name Denitrificimonas halotolerans sp. nov. is proposed with JX-1T (= MCCC 1K08958T = KCTC 8395T) as the type strain.

RANKL, but Not R-Spondins, Is Involved in Vascular Smooth Muscle Cell Calcification through LGR4 Interaction.

Vascular calcification has a global health impact that is closely linked to bone loss. The Receptor Activator of Nuclear Factor Kappa B (RANK)/RANK ligand (RANKL)/osteoprotegerin (OPG) system, fundamental for bone metabolism, also plays an important role in vascular calcification. The Leucine-rich repeat-containing G-protein-coupled receptor 4 (LGR4), a novel receptor for RANKL, regulates bone remodeling, and it appears to be involved in vascular calcification. Besides RANKL, LGR4 interacts with R-spondins (RSPOs), which are known for their roles in bone but are less understood in vascular calcification. Studies were conducted in rats with chronic renal failure fed normal or high phosphorus diets for 18 weeks, with and without control of circulating parathormone (PTH) levels, resulting in different degrees of aortic calcification. Additionally, vascular smooth muscle cells (VSMCs) were cultured under non-calcifying (1 mM phosphate) and calcifying (3 mM phosphate) media with different concentrations of PTH. To explore the role of RANKL in VSMC calcification, increasing concentrations of soluble RANKL were added to non-calcifying and calcifying media. The effects mediated by RANKL binding to its receptor LGR4 were investigated by silencing the LGR4 receptor in VSMCs. Furthermore, the gene expression of the RANK/RANKL/OPG system and the ligands of LGR4 was assessed in human epigastric arteries obtained from kidney transplant recipients with calcification scores (Kauppila Index). Increased aortic calcium in rats coincided with elevated systolic blood pressure, upregulated Lgr4 and Rankl gene expression, downregulated Opg gene expression, and higher serum RANKL/OPG ratio without changes in Rspos gene expression. Elevated phosphate in vitro increased calcium content and expression of Rankl and Lgr4 while reducing Opg. Elevated PTH in the presence of high phosphate exacerbated the increase in calcium content. No changes in Rspos were observed under the conditions employed. The addition of soluble RANKL to VSMCs induced genotypic differentiation and calcification, partly prevented by LGR4 silencing. In the epigastric arteries of individuals presenting vascular calcification, the gene expression of RANKL was higher. While RSPOs show minimal impact on VSMC calcification, RANKL, interacting with LGR4, drives osteogenic differentiation in VSMCs, unveiling a novel mechanism beyond RANKL-RANK binding.

Phenotypic characterization and analysis of genetic diversity between commercial crossbred and indigenous chickens from three different agro-ecological zones using DArT-Seq technology.

Indigenous and were used to study genetic diversity and population structure analyses. Polymorphism information content (PIC) values ranged from 0.0 to 0.5, with 21,285 SNP markers (35%) being in the lowest PIC value range (0 to 0.15) while 13,511 (commercial chickens have developed unique adaptations to their environments, which may include nutrition, pathogens, and thermal stress. Besides, environmental pressures and artificial selection have generated significant genome-wide divergence in chickens, as those selection pressures contribute a considerable evolutionary force to phenotypic and genotypic differentiation. Herein, we determined genomic diversity of indigenous chickens from semi-deciduous rainforest (SDR), coastal savannah (CS) and Guinea savannah (GS) agro-ecological zones (AEZs) in Ghana and commercial crossbreds (CC) reared at the Kwame Nkrumah University of Science and Technology (KNUST). We generated SNP markers from 82 chickens (62 indigenous chicken ecotypes and 26 commercial crossbred ecotype) using DArT-Seq technology. A total of 85,396 SNP markers were generated and after filtering the data, 58,353 markers 21%) were in the highest PIC value range (0.45 to 0.50). The CC were more genetically diverse than the indigenous birds, with the highest expected heterozygosity value of 0.220. Between the commercial crossbreds population and the indigenous ecotypes, pairwise FST values were estimated to be 0.105 between CS, 0.096 between SDF, and 0.133 between GS. Furthermore, PCA analysis showed that the CC, SDF and GS chickens clustered together and are genetically distant from the commercial crossbred. We herein show that chickens from the AEZs studied can be considered as one population. However, due the abundance of agro-byproducts in the SDR compared to the CS and GS, chickens from the SDR AEZ had better growth compared to their counterparts. It is suggested that the genetic diversity within the local ecotypes could form the basis for genetic improvement.

GENETIC DIFFERENTIATION AMONG RED COLORED BOS INDICUS SUBCONTINENT ORIGIN BREEDS USING SNP CHIP DATA

In Pakistan, Sahiwal and Cholistani cattle are considered as dairy breeds with traits of disease resistance, heat tolerance, and adaptability to high temperature. These breeds are considered two different breeds although Sahiwal is considered an off shoot of Cholistani cattle. However, these breeds have never been characterized genotypically using SNP data. Moreover, information on genotypic differentiation is unavailable for other subcontinent red colored breeds i.e., Gir, Brahman and Red Sindhi. Thus, present study was meant to investigate distinctive genetic architect if any of these red color breeds of same region of the world. Genotype data of 50K SNP Bead chip was retrieved online from Dryad database. Quality control measures were performed in Plink 1.9 software. Admixture, Principal component analysis and Multidimensional scaling were used for breeds distinction while genetic diversity was estimated using linkage disequilibrium. The genetic structure of these breeds clearly differentiated them from each other performed by admixture analysis from K =2 to K =5. Similarly, all breeds principally differentially scattered in PCA and MDS results. The study revealed different genetic structure for Cholistani and Sahiwal indicating as distinct breeds while Brahman had mixed genetic architect of other Bos indicus subcontinent breeds. The findings of the current study stress for separate genetic improvement program of Sahiwal and Cholistani cattle. Key words: Cholistani, Sahiwal, SNPs chip, Admixture, Pakistan.

Deep Learning–Augmented ECG Analysis for Screening and Genotype Prediction of Congenital Long QT Syndrome

Congenital long QT syndrome (LQTS) is associated with syncope, ventricular arrhythmias, and sudden death. Half of patients with LQTS have a normal or borderline-normal QT interval despite LQTS often being detected by QT prolongation on resting electrocardiography (ECG). To develop a deep learning-based neural network for identification of LQTS and differentiation of genotypes (LQTS1 and LQTS2) using 12-lead ECG. This diagnostic accuracy study used ECGs from patients with suspected inherited arrhythmia enrolled in the Hearts in Rhythm Organization Registry (HiRO) from August 2012 to December 2021. The internal dataset was derived at 2 sites and an external validation dataset at 4 sites within the HiRO Registry; an additional cross-sectional validation dataset was from the Montreal Heart Institute. The cohort with LQTS included probands and relatives with pathogenic or likely pathogenic variants in KCNQ1 or KCNH2 genes with normal or prolonged corrected QT (QTc) intervals. Convolutional neural network (CNN) discrimination between LQTS1, LQTS2, and negative genetic test results. The main outcomes were area under the curve (AUC), F1 scores, and sensitivity for detecting LQTS and differentiating genotypes using a CNN method compared with QTc-based detection. A total of 4521 ECGs from 990 patients (mean [SD] age, 42 [18] years; 589 [59.5%] female) were analyzed. External validation within the national registry (101 patients) demonstrated the CNN's high diagnostic capacity for LQTS detection (AUC, 0.93; 95% CI, 0.89-0.96) and genotype differentiation (AUC, 0.91; 95% CI, 0.86-0.96). This surpassed expert-measured QTc intervals in detecting LQTS (F1 score, 0.84 [95% CI, 0.78-0.90] vs 0.22 [95% CI, 0.13-0.31]; sensitivity, 0.90 [95% CI, 0.86-0.94] vs 0.36 [95% CI, 0.23-0.47]), including in patients with normal or borderline QTc intervals (F1 score, 0.70 [95% CI, 0.40-1.00]; sensitivity, 0.78 [95% CI, 0.53-0.95]). In further validation in a cross-sectional cohort (406 patients) of high-risk patients and genotype-negative controls, the CNN detected LQTS with an AUC of 0.81 (95% CI, 0.80-0.85), which was better than QTc interval-based detection (AUC, 0.74; 95% CI, 0.69-0.78). The deep learning model improved detection of congenital LQTS from resting ECGs and allowed for differentiation between the 2 most common genetic subtypes. Broader validation over an unselected general population may support application of this model to patients with suspected LQTS.

Validation of improved automated nucleic acid extraction methods for direct detection of polioviruses for global polio eradication

Polioviruses (PV), the main causative agent of acute flaccid paralysis (AFP), are positive-sense single-stranded RNA viruses of the family Picornaviridae. As we approach polio eradication, accurate and timely detection of poliovirus in stool from AFP cases becomes vital to success for the eradication efforts. Direct detection of PV from clinical diagnostic samples using nucleic acid (NA) extraction and real-time reverse transcriptase polymerase chain reaction (rRT-PCR) instead of the current standard method of virus isolation in culture, eliminates the long turn-around time to diagnosis and the need for high viral titer amplification in laboratories. An essential component of direct detection of PV from AFP surveillance samples is the efficient extraction of NA. Potential supply chain issues and lack of vendor presence in certain areas of the world necessitates the validation of multiple NA extraction methods. Using retrospective PV-positive surveillance samples (n=104), two extraction kits were compared to the previously validated Zymo Research Quick-RNA™ Viral Kit. The Roche High Pure Viral RNA Kit, a column-based manual extraction method, and the MagMaX™ Pathogen RNA/DNA kit used in the automated Kingfisher Flex system were both non-inferior to the Zymo kit, with similar rates of PV detection in pivotal rRT-PCR assays, such as pan-poliovirus (PanPV), poliovirus serotype 2 (PV2), and wild poliovirus serotype 1 (WPV1). These important assays allow the identification and differentiation of PV genotypes and serotypes and are fundamental to the GPLN program. Validation of two additional kits provides feasible alternatives to the current piloted method of NA extraction for poliovirus rRT-PCR assays.

Deciphering the role of the morphophysiology of germination and leaves morphoanatomy for differentiation of Brazil nut genotypes

Deciphering the role of the morphophysiology of germination and leaves morphoanatomy for differentiation of Brazil nut genotypes

Development of a multiplex real-time enzymatic recombinase amplification assay for differentiation of yellow head virus genotype 1 and 2 in Penaeus vannamei

At present, eight genotypes of yellow head virus (YHV) have been identified, and the main pathogenic genotypes are yellow head virus 1 (YHV1) and gill-associated virus (GAV), which have caused mass death and serious economic losses of shrimp industry. The prevention of YHV complex infection is highly dependent on early and rapid diagnostic, however, the available molecular technologies require complex procedures or expensive equipment. In this study, a multiplex rapid detection method of YHV1 and GAV based on real-time enzymatic recombinase amplification (YHV1/GAV-ERA) was established. Primers and probes were designed to detect the conserved ORF1b gene of YHV1 and GAV. Best primers and probes were selected to effectively amplify the target gene, and the sensitivity was reached 102 copies/μL within 6.17 ± 0.49 min. While multi-nested PCR could reach the detection limit of 1.9 copies/μL and 2.1 copies/μL for YHV1 and GAV by consuming higher time and instrument cost. The YHV1/GAV-ERA can effectively amplify the target gene at 32–45 °C within 30 min, and the optimum reaction temperature is 42 °C. No cross reaction with white spot syndrome virus (WSSV), Vibrio parahaemolyticus causing acute hepatopancreatic necrosis disease (VpAHPND), Enterocytozoon hepatopenaei (EHP), infectious hypodermal and hematopoietic necrosis virus (IHHNV) and healthy shrimp DNA were observed. Additionally, the test results of YHV1/GAV-ERA were 100% consistent with the industrial standard multi-nested PCR in shrimp samples. This method can distinguish the two genotypes of YHV and get rid of the dependence on the thermal cycle instrument, and provides a feasible rapid detection method for on-site screening of pathogens.

Differentiation of sunflower genotypes in accordance with growing conditions

Differentiation of sunflower genotypes in accordance with growing conditions

Description of Streptomyces naphthomycinicus sp. nov., an endophytic actinobacterium producing naphthomycin A and its genome insight for discovering bioactive compounds.

Endophytic actinobacteria are a group of bacteria living inside plant tissue without harmful effects, and benefit the host plant. Many can inhibit plant pathogens and promote plant growth. This study aimed to identify a strain of Streptomyces as a novel species and study its antibiotics production. An endophytic actinobacterium, strain TML10T was isolated from a surface-sterilized leaf of a Thai medicinal plant (Terminalia mucronata Craib and Hutch). As a result of a polyphasic taxonomy study, strain TML10T was identified as a member of the genus Streptomyces. Strain TML10T was an aerobic actinobacterium with well-developed substrate mycelia with loop spore chains and spiny surface. Chemotaxonomic data, including cell wall components, major menaquinones, and major fatty acids, confirmed the affiliation of strain TML10T to the genus Streptomyces. The results of the phylogenetic analysis, including physiological and biochemical studies in combination with a genome comparison study, allowed the genotypic and phenotypic differentiation of strain TML10T and the closest related type strains. The digital DNA-DNA hybridization (dDDH), Average nucleotide identity Blast (ANIb), and ANIMummer (ANIm) values between strain TML10T and the closest type strain, Streptomyces musisoli CH5-8T were 38.8%, 88.5%, and 90.8%, respectively. The name proposed for the new species is Streptomyces naphthomycinicus sp. nov. (TML10T = TBRC 15050T = NRRL B-65638T). Strain TML10T was further studied for liquid and solid-state fermentation of antibiotic production. Solid-state fermentation with cooked rice provided the best conditions for antibiotic production against methicillin-resistant Staphylococcus aureus. The elucidation of the chemical structures from this strain revealed a known antimicrobial agent, naphthomycin A. Mining the genome data of strain TML10T suggested its potential as a producer of antbiotics and other valuable compounds such as ε-Poly-L-lysine (ε-PL) and arginine deiminase. Strain TML10T contains the arcA gene encoding arginine deiminase and could degrade arginine in vitro.

Time-Series Field Phenotyping of Soybean Growth Analysis by Combining Multimodal Deep Learning and Dynamic Modeling.

The rate of soybean canopy establishment largely determines photoperiodic sensitivity, subsequently influencing yield potential. However, assessing the rate of soybean canopy development in large-scale field breeding trials is both laborious and time-consuming. High-throughput phenotyping methods based on unmanned aerial vehicle (UAV) systems can be used to monitor and quantitatively describe the development of soybean canopies for different genotypes. In this study, high-resolution and time-series raw data from field soybean populations were collected using UAVs. The RGB (red, green, and blue) and infrared images are used as inputs to construct the multimodal image segmentation model-the RGB & Infrared Feature Fusion Segmentation Network (RIFSeg-Net). Subsequently, the segment anything model was employed to extract complete individual leaves from the segmentation results obtained from RIFSeg-Net. These leaf aspect ratios facilitated the accurate categorization of soybean populations into 2 distinct varieties: oval leaf type variety and lanceolate leaf type variety. Finally, dynamic modeling was conducted to identify 5 phenotypic traits associated with the canopy development rate that differed substantially among the classified soybean varieties. The results showed that the developed multimodal image segmentation model RIFSeg-Net for extracting soybean canopy cover from UAV images outperformed traditional deep learning image segmentation networks (precision = 0.94, recall = 0.93, F1-score = 0.93). The proposed method has high practical value in the field of germplasm resource identification. This approach could lead to the use of a practical tool for further genotypic differentiation analysis and the selection of target genes.