G1 Genotype Research Articles

Virus-like Particles vaccine based on co-expression of G5 Porcine rotavirus VP2-VP6-VP7 induces a powerful immune protective response in mice

Porcine rotavirus (PoRV), a member of the Reoviridae family, constitutes a principal etiological agent of acute diarrhea in piglets younger than eight weeks of age, and it is associated with considerable morbidity and mortality within the swine industry. The G5 genotype rotavirus strain currently predominates in circulation. To develop a safe and effective porcine rotavirus vaccine, we generated an insect cell-baculovirus expression system, and successfully expressed these three viral proteins and assembled them into virus-like particles (VLPs) co-displaying VP2, VP6, and VP7. Transmission electron microscopy (TEM) analysis revealed that the VP2-VP6-VP7 VLPs exhibited a "wheeled" morphology resembling that of native rotavirus particles, with an estimated diameter of approximately 65nm. To evaluate the immunogenicity and protective efficacy of these VP2-VP6-VP7 VLPs, we immunized BALB/C mice with four escalating doses of the VLPs, ranging from 5 to 40μg of VLP protein per dose. ELISA-based assessments of PoRV-specific antibodies and T cell cytokines, including IL-4, IL-2, and IFN-γ, demonstrate that immunization with VP2-VP6-VP7 VLPs can effectively elicit both humoral and cellular immune responses in mice, resulting in a notable induction of neutralizing antibodies. On days 4, 6, 8, and 10 post-infection (dpi), the VLP-vaccinated group exhibited significantly reduced levels of PoRV RNA copy numbers when compared to the PBS controls. Histological examination of the duodenum, ileum, and kidneys revealed that VP2-VP6-VP7 VLPs provided effective protection against PoRV induced intestinal injury. Collectively, these findings indicate that the VLPs generated in this study possess strong immunogenicity and suggest the considerable promise of the VLP-based vaccine candidate in the prevention and containment of Porcine Rotavirus infections.

Selection of rice genotypes based on agronomic traits and commercial grain quality

The study aimed to select rice genotypes based on agronomic traits and commercial grain quality. The study was carried out in the 2014/15 and 2015/16 harvests in eight growing environments, located in the state of Rio Grande do Sul, Brazil. Fourteen rice genotypes were sown in each environment. The experiment was conducted in a randomized block design with four replications. The following agronomic traits were evaluated: number of days to flowering and grain yield as well as commercial grain quality traits: percentage of whole grains and percentage of chalky area in the grains. AMMI, GGE and MGIDI methodologies were used to select the best performing genotypes. Using the AMMI, GGE and MGDI methods, genotypes G9 and G1 performed close to the ideal ideotype for the number of days to grain flowering, yield and quality.

Continuing evolution of H5N1 highly pathogenic avian influenza viruses of clade 2.3.2.1a G2 genotype in domestic poultry of Bangladesh during 2018–2021

ABSTRACT We characterized 15 H5N1 HPAI viruses from different small- and medium-scale poultry flocks across Bangladesh during 2018–2021 based on their complete genome sequences. The antigenic relatedness of H5N1 HPAI viruses from different timepoints was analysed. During 2020–2021, 42.11% of the flocks tested positive for at least one of the respiratory infections, with 15.79% showing influenza A virus, of which 8.77% tested positive for HPAIV H5N1. Co-infections with two to four pathogens were detected in 15.8% of flocks. Phylogeny and gene constellation analyses based on complete genome sequences of 15 HPAI viruses revealed the continuing circulation of H5 clade 2.3.2.1a genotype G2 viruses. In the HA protein of the study isolates, functionally meaningful mutations caused the loss of an N-linked glycosylation site (T156A), a modified antigenic site A (S141P), and a mutation in the receptor binding pocket (E193R/K). Consequently, antigenic analysis revealed a significant loss of cross-reactivity between viruses from different host species and periods. Most viruses displayed oseltamivir resistance markers at positions V96, I97, S227, and N275 (N1 numbering) of the NA protein. In addition, for the PB2, M1, and NS1 proteins, significant mutations were noticed that have been associated with polymerase activity and increased virulence for mammals in all study isolates. These results highlight the need for intensified genomic surveillance of HPAI circulating in poultry in Bangladesh and for establishing appropriate control measures to decrease the circulation of these viruses in poultry in the country.

Principal Component Analysis in rice (Oryza sativa L.) varieties for three seasons in Annamalai Nagar, an east coast region of Tamil Nadu

Principal component analysis (PCA) was used to assess genetic variability and identify key yield-contributing traits among 50 rice genotypes evaluated over three seasons under saline conditions. The study aimed to select promising donor lines for developing salt-tolerant, high-yielding cultivars suitable for coastal regions. PCA identified three principal components (PCs) that explained 73.19%, 70.34%, and 64.81% of the total genetic variation in seasons 1, 2 and 3, respectively. Key plant attributes, such as grain yield per plant, panicle grain density, total tiller number, and productive tiller count, showed significant positive associations with PC1 across various growth stages, underscoring their crucial role in explaining the genetic diversity among the genotypes. Plant height, panicle length, and hundred-grain weight also emerged as major contributors to variation. The PCA biplots consistently demonstrated positive correlations between grain yield and traits like panicle length, hundred-grain weight, and tillering ability. In contrast, days to 50% flowering exhibited a negative association with yield. Genotypes G10, G49, G36, G41, G9, G4, G22, and G21 displayed favourable combinations of grain yield per plant, identifying them as potential donor lines for breeding programs aimed at improving rice yield and associated agronomic traits. This comprehensive PCA analysis highlights the effectiveness of the approach in capturing genotypic diversity and guiding the selection of promising germplasm for targeted trait improvement in rice.

Assessing the population structure and genetic diversity of wheat germplasm with the iPBS-retrotransposons marker system

Context Wheat (Triticum aestivum L.) is an important crop that provides food to millions of people all over the world. Currently, wheat production is limited due to various biotic and abiotic stresses resulting from uneven patterns of climate change. Therefore, it is very important to develop climate-resilient wheat cultivars. Crop genetic diversity allows the scientific community to identify genetic variations that can be utilised in the development of improved cultivars. Aims This study planned to characterise the wheat germplasm with the iPBS-retrotransposons marker system. Methods A total of 30 iPBS-retrotransposons markers were screened and among these, the 12 most polymorphic markers were selected for further analysis. Key results Molecular characterisation yielded a total of 170 bands, of which 143 were polymorphic. A substantial level of genetic diversity was observed (mean effective number of alleles: 1.37, Shannon’s information index: 0.23, gene diversity: 0.35). Maximum genetic distance was observed in G9 and G60 genotypes. Analysis of molecular variance revealed that most genetic variation (95%) occurred within the populations. The model-based structure algorithm divided the studied germplasm into three populations based on their collection regions. Similarly, the neighbour-joining analysis also divided 70 tested wheat genotypes into three populations, whereas principal coordinate analysis divided the evaluated germplasm into four populations. Conclusions This study confirms the iPBS-retrotransposons as an ideal marker for the genetic diversity assessment studies for any crop, especially for wheat. Implications The results presented here will be helpful for the scientific community in the marker-assisted breeding of wheat.

Salinity Studies in Quinoa (Quinoa Chenipodoum Willd) from Haditha Desert, Western of Iraq

The present studies were conducted to determine the effect of various concentrations of NaCl salinity on germination and growth of four genotypes of Quinoa Chenopodium Willd, namely G1 (KVL-SR2), G2 (Q-21), G3 (Q-37), and G4 (Regalona), exposed to 0, 60, 120, and 300 mM NaCl. The study was conducted at the Center of Desert Research, Egypt, and the experiment was carried out in the Plant Physiology Laboratory of the Center of Desert Studies. Seeds were treated with four different levels of NaCl concentration: 0, 60, 120, and 300 mM. The experiment followed a Completely Randomized Design with three replications. The germination experiment aimed to determine the effect of NaCl salinity on seed germination percentage. Seeds were placed in autoclaved petri dishes lined with two layers of filter paper, with fifty seeds per dish. Seeds were treated with 0, 60, 120, and 300 mM NaCl solutions (5 mL). The petri dishes were kept in the laboratory at temperatures ranging from 25°C to 28°C for four weeks. Water loss from the petri dishes due to evaporation was monitored using control petri dishes, and water was added every 24 hours as needed. A pot experiment was conducted using plastic pots containing 1700 grams of fine-sieved soil. Seeds of the aforementioned genotypes were sown in 500 grams of soil, separated from the rest of the pot's soil by a polythene sheet. Plants were watered on alternate days and subjected to salinity treatment 25 days after sowing. Fifty milliliters of nutrient solution (N ratio of 6:4) were also added to the salt solution per pot. The salt solution was applied to the 1200 grams of soil in the pot, and after complete absorption, the polythene sheet separating the soil containing plantlets was removed, allowing the roots of the seedlings to grow into the saline soil in the lower half of the pot. Thinning was done after one week, maintaining five plants per pot. The plants were harvested one month after the salinity treatment. It was observed that the germination percentage decreased as the salinity level increased. G1 was tolerant, while G4 was salt-sensitive compared to the other genotypes. Plant height, number of leaves, and number of nodes per plant decreased with increasing salt concentration. G3 was least affected, followed by G2, G1, and G4. Fresh weight, dry weight, and percentage water content of the plants also significantly decreased with increased salinity. The distribution of Na+ ions in various plant parts showed a high concentration in the roots, stem, leaf blade, and leaf sheath of all genotypes. The highest concentration of Na+ ions was found in the leaf sheath of all genotypes, followed by the stem, root, and leaf blade, with high water content even under the highest salt levels. An effective partition of Na+ and Cl- ions in the leaf sheath and the transport of K+ to the physiologically important leaf blade were observed in G1, while other genotypes did not exhibit this efficiency. The specific ion effect of NaCl on the total N status of plants was most pronounced in G1, followed by G2 and G3, while G4 maintained optimal N levels in the root and leaf blade. The tolerant genotype G1 could be utilized for rehabilitation in salt-affected areas.

Genotype x environment interaction and yield stability of soybean (Glycine max l.) genotypes in multi-environment trials (METs) in Nigeria

Genotype × environment interaction (GEI) poses a critical challenge to plant breeders by complicating the identification of stable variety (ies) for performance across diverse environments. GGE biplot and AMMI analyses have been identified as the most effective and appropriate statistical techniques for identifying stable and high-performing genotypes across diverse environments. The objective of this study was to identify widely adapted and high-yielding soybean genotypes from Multi-Locational Trials (MLTs) using GGE and AMMI biplot analyses. Fifteen IITA-bred elite soybean lines and three standard checks were evaluated for stability of performance in a 3 × 6 alpha lattice design with three replications across seven locations in Nigeria. Significant (p < 0.001) differences were detected among genotypes, environments, and GEI for grain yield, which ranged between 979.8 kg ha−1 and 3645 kg ha−1 with a mean of 2324 kg ha−1. To assess the stability of genotypes, analyses were conducted using the general linear method, GGE, and the Additive Main Effect and Multiplicative Interaction (AMMI) approach, as well as WAAS and ASV rank indices. In the GGE biplot model, the first two principal components accounted for 67.4 % of the total variation, while in the AMMI model, the first two Interaction Principal Component Axes (IPCA1 and IPCA2) explained 73.20 % and 11.40 % of the variation attributed to genotype by environment interaction, respectively. GGE biplot identified G10 and G16 as the most stable and productive genotypes, while WAASB index revealed G16, G10, G9, G4 and G2 as the most adaptive, stable and productive genotypes across locations, and ASV identified G9, G13, G4, G14 and G10 as the most stable and productive.Consequently, genotypes G2, G4, G9, G10 and G16 displayed outstanding and stable grain yield performance across the test locations and are, therefore, recommended for release as new soybean varieties suitable for cultivation in the respective mega environment where they performed best. More importantly, the two genotypes are recommended for recycling as sources of high-yield and yield stability genes, and as parental lines for high-yield and stable performance for future breeding and genomic selection.

AMMI and GGE biplot analysis for barley genotype yield performance and stability under multi environment condition in southern Ethiopia

AbstractBarley (Hordeum vulgare L.) is a major grain crop farmed in Ethiopia throughout the long rainy season (Meher) and the short rainy season (Belg) of the year. Barley genotypes were subjected to multi‐environment experiments in six different settings to identify stable genotypes and estimate the impact of genotype × environment interaction (GEI) on grain production. In each area, the field experiment was conducted from mid‐July to January during the primary cropping season of 2021. Three replications of a randomized complete block design were used to set up the trials. According to the additive main effects and multiplicative interaction (AMMI) study, genotype (18.19%), GEI (22.98%), and environment (58.83%) all had an impact on the major treatment sum of squares. The more variance attributed to the environments is a sign of environmental diversity. Given that the two interaction principal component analysis (IPCAs) accounted for 76.94% of the interaction sum of squares, they were sufficient for cross‐validation of the grain yield variance explained by GEI. In contrast to the GGE biplot approaches, which indicated genotypes G12, G3, and G9 as stable and high‐yielding genotypes throughout the environments, the AMMI stability value identified genotypes G3, G12, and G9 as high yielding with stable performance across environments. In general, the GGE biplot and AMMI analysis models demonstrated that genotypes G12, G3, and G9 were stable and yielded well, making G3 acceptable for cultivation in a wider range of environments and G12 and G9 suitable for release.

Analysis of genotype-by-environment interaction effect in barley genotypes using AMMI and GGE biplot methods

Genotype-by-environment interaction (GEI) analysis play a key role in any breeding program involving the development of new varieties for cultivation across various environments or in a specific region. The additive main effects and multiplicative interaction (AMMI) method and the GGE biplot are the two main statistical tools that have emerged to analyze GEI in multi-environment trials (METs). The main goal of the present study was to identify the best-performing and stable barley genotypes for the warm regions of Iran. For this purpose, 18 new advanced barley genotypes were investigated in five warm locations in Iran during two cropping seasons (2021–2023). In all experiments, test genotypes were evaluated in a randomized complete block design (RCBD) with three replications. Based on results, grain yield was significantly dependent on environments (E), genotypes (G), and GEI. The GEI effect was further divided into three principal component axes (IPCAs). The AMMI method identified genotypes G3, G9, G10, and G14 as ideal genotypes due to their low IPCA scores and high performances. In the GGE biplot analysis, the initial two PCAs accounted for 49.36 % of the total variation of grain yield, including both G and GEI effects. Based on averaged two-year data, genotypes G3, G4, G10, and G14 showed particular adaptability in the Zabol and Moghan regions. Moreover, the ranking of test environments showed good discriminatory and representative abilities for the Zabol and Moghan regions, so these environments constituted a mega-environment in Iran's warm climate. The genotype ranking indicated G3, G10 and G14 genotypes as the superior genotypes with the highest grain yield and stability in different test environments. Moreover, these results were confirmed by the results obtained by WAASB and WAASBY biplots. In conclusion, genotypes G3, G10 and G14 can be suggested for commercial usage and cultivation in various regions in Iran's warm climate.

Determination of G and P genotypes of bovine group A rotavirus with emergence of unusual G-and P-type combinations from neonatal calfdiarrhea in Kashmir, India.

A total of 490 diarrhoeic samples from calves aged between 0 and 6 months were screened for the presence of different G- and P-genotypes of rotavirus circulating in bovines in the Kashmir Valley. Of the 490 diarrhoeic samples, Group A rotavirus was detected in 68 (13.87%) samples by polymerase chain reaction (PCR) followed by RNA-PAGE. Genotyping analysis revealed G10, G6, G3, P[11] and P[5] to be the predominant types. The most common types of combinations detected were G10P[11] (27.90%) and G6P[11] (20.60%). The prevalence rate of G10 and P[11] decreased from 60% to 36.76% and 100%-69.11%, respectively. Genotypes G6, G3, P[1] and P[5], which were not previously reported, were detected and unusual combinations such as G6P[11], G3P[11], G10P[5], G3P[5], G6P[1], G6P[5], G6+G8P[11] were also observed for the first time. Fluctuations in the predominant types, emergence of new types and possible genetic reassortment events suggest an unstable epidemiological situation and the need for continuous surveillance of the circulating types to ensure the suitability of the vaccination programme. The present data suggests G10, G6, P[11] and P[5] genotypes could be incorporated in the polyvalent vaccine to offer increased protection against bovine rotavirus infection in India.

Genetic and antigenic characterization of two diarrhoeicdominant rotavirus A genotypes G3P[12] and G14P[12] circulating in the global equine population.

Equine rotavirus species A (ERVA) G3P[12] and G14P[12] are two dominant genotypes that cause foal diarrhoea with a significant economic impact on the global equine industry. ERVA can also serve as a source of novel (equine-like) rotavirus species A (RVA) reassortants with zoonotic potential as those identified previously in 2013-2019 when equine G3-like RVA was responsible for worldwide outbreaks of severe gastroenteritis and hospitalizations in children. One hurdle to ERVA research is that the standard cell culture system optimized for human rotavirus replication is not efficient for isolating ERVA. Here, using an engineered cell line defective in antiviral innate immunity, we showed that both equine G3P[12] and G14P[12] strains can be rapidly isolated from diarrhoeic foals. The genome sequence analysis revealed that both G3P[12] and G14P[12] strains share the identical genotypic constellation except for VP7 and VP6 segments in which G3P[12] possessed VP7 of genotype G3 and VP6 of genotype I6 and G14P[12] had the combination of VP7 of genotype G14 and VP6 of genotype I2. Further characterization demonstrated that two ERVA genotypes have a limited cross-neutralization. The lack of an in vitro broad cross-protection between both genotypes supported the increased recent diarrhoea outbreaks due to equine G14P[12] in foals born to dams immunized with the inactivated monovalent equine G3P[12] vaccine. Finally, using the structural modelling approach, we provided the genetic basis of the antigenic divergence between ERVA G3P[12] and G14P[12] strains. The results of this study will provide a framework for further investigation of infection biology, pathogenesis and cross-protection of equine rotaviruses.

Echinococcus ortleppi infection in humans: An emerging zoonosis in Asia

Echinococcus ortleppi is the genotype G5 of Echinococcus granulosus sensu lato and is a zoonotic canine tapeworm of which larvae causes cystic diseases in domestic animals and also humans. While this species is highly endemic and widely spread in domestic animals, human infection is extremely rare and only sporadic, and thus, entire picture of human cystic echinococcosis due to infection with E. ortleppi is unclear. We have made an extensive literature review on the cases of E. ortleppi infection in humans and found a total of 19 cases from various places in the world with recent emergence in Asian countries.

Distribution of Echinococcus Granulosus G1 and G3 Genotype Among the Cattle in West-Kazakhstan Region

Distribution of Echinococcus Granulosus G1 and G3 Genotype Among the Cattle in West-Kazakhstan Region

Identifying dryland-resilient chickpea genotypes for autumn sowing, with a focus on multi-trait stability parameters and biochemical enzyme activity

BackgroundChickpea is a key pulse crop grown in the spring in dryland regions. The cold resistance potential of chickpeas allows for the development of genotypes with varying sowing dates to take advantage of autumn and winter rainfall, particularly in dryland regions. In this study, we assessed grain yield, plant height, 100-seed weight, days to maturity, and days to flowering of 17 chickpea genotypes in five autumn-sown dryland regions from 2019 to 2021. Additionally, the response of selected chickpea genotypes to cold stress was examined at temperatures of -4 °C, 4 °C, and 22 °C by analyzing biochemical enzymes.ResultsMixed linear model of ANOVA revealed a significant genotype × environment interaction for all traits measured, indicating varying reactions of genotypes across test environments. This study reported low estimates of broad-sense heritability for days to flowering (0.34), days to maturity (0.13), and grain yield (0.08). Plant height and seed weight exhibited the highest heritability, with genotypic selection accuracies of 0.73 and 0.92, respectively. Moreover, partial least square regression highlighted the impactful role of rainfall during all months except of October, November, and February on grain yield and its interaction with environments in autumn-planted chickpeas. Among the genotypes studied, G9, G10, and G17 emerged as superior based on stability parameters and grain yield. In particular, genotype G9 stood out as a promising genotype for dryland regions, considering both MTSI and genotype by yield*trait aproaches. The cold assay indicated that − 4 °C is crucial for distinguishing between susceptible and resistant genotypes. The results showed the important role of the enzymes CAT and GPX in contributing to the cold tolerance of genotype G9 in autumn-sown chickpeas.ConclusionsSignificant G×E for agro-morphological traits of chickpea shows prerequisite for multi-trial analysis. Chickpea`s direct root system cause that monthly rainfall during plant establishment has no critical role in its yield interaction with dryland environment. Considering the importance of agro-morphological traits and their direct and indirect effects on grain yield, the utilization of multiple-trait stability approches is propose. Evaluation of chickpea germplasm reaction against cold stress is necessary for autumn-sowing. Finally, autumn sowing of genotype FLIP 10–128 C in dryland conditions can led to significant crop performance.

Registration of Newly Released Hull Less Food Barley (&amp;lt;i&amp;gt;HondiumVulgare L.&amp;lt;/i&amp;gt;) Variety, ‘Sena’, for High Potential Barley Growing Areas in Ethiopia

Twenty hull less barley genotypes from the local crossing program and germplasms introduced from ICARDA were evaluated in a multi-location variety trial to identify stable genotypes with high grain yield, desirable agronomic characters and good level of disease resistance. Results of combined analysis showed that genotype (G5 and G19) with pedigree name &amp;lt;i&amp;gt;TOCTE/M112/6/VMORALESCBSS04M00436T-11M-0Y-0M-3M-0AP and PENCO/CHEVRON-BAR/3/LEGACYU//PENCO/CHEVRON=BAR CBSS04Y00048S-23Y2M-0Y-0M-0Y-0AP--0TR-0TR &amp;lt;/i&amp;gt;exhibited the highest mean grain yield with good agronomic performance and good level of disease resistance across the testing environments, while genotype. Accordingly, the two varieties were promoted to variety verification trial in 2022, and genotype G5 released in 2023; this genotype was named Sena. The variety showed good physical grain quality, coupled with high grain yield of 5.2 t/ha. Sena variety is suitable to the high potential barley growing areas. This variety is characterized by early maturity, white seed color, has good physical grain quality, resistance to leaf rust and scald, moderate resistance to net blotch, moderate tolerance to barley shoot fly, lodging tolerance and good biomass yield. The variety’s demonstration and seed multiplication is underway. Therefore, cultivation of the new variety in the higher altitude areas of major barley growing environments of the country is highly recommended. Six-rowed semi hulled barley Sena was developed by Sinana Agricultural Research Center (SARC), Southeastern Oromia region, Ethiopia. If the variety is sufficiently demonstrated, scaled up and adopted by farmers, it can play significant role in increasing hull less barley production and productivity thereby increasing the income of farmers and can also be source of raw material for local market engaged in the &amp;lt;i&amp;gt;kolo&amp;lt;/i&amp;gt; production.

Exploring genotype by environment interaction in sunflower using genotype plus genotype by environment interaction (GGE) and best linear unbiased prediction (BLUP) approaches

Sunflower is important for food, feed and ornamentals, faces rising demand for quality oil. Identifying resilient high-yielding genotypes is essential. Multi-environmental trials and integrated approaches to evaluate genotype by environment interactions (GEI) enhance accuracy and comprehensiveness of breeding programs. This study assess the representativeness and discriminative power of tested environments; classify mega-environments for genotype recommendations and evaluate how GGE and BLUP methods identify stable and superior sunflower genotypes. The experiment used a randomized complete block design with three replications across six locations for two seasons. The pooled analysis of variance for GEI on seed yield showed significant variability (p < 0.05) with mean values from 1171 to 2564 kg ha−1, indicating inconsistent genotypes performance across environments. The study identified E11, E2, and E6 as key discriminating and representative environments and grouped test locations into four mega-environments. Genotypes G6, G1, and G4 are the most desirable based on stability and seed yield. E11 and G6 are identified as ideal environment and genotype, respectively. GGE biplot and BLUP methods consistently identify stable and ideal sunflower genotypes. However, GGE stability indices differ somewhat in assessing genotypes stability possibly due to low number of genotypes, testing environment, and year in the dataset. The study confirmed that simultaneous consideration of GGE and BLUP models for GEI analysis helps to select more stable and adaptable sunflower genotypes across environments. It also clarifies GEI pattern, identifying mega-environments, and aiding genotype selection in sunflower production. However, validating these mega-environments and exploring the genetic basis of adaptability and stability remains essential.

Emergence of a novel pathogenic porcine G1P[7] rotavirus in China

Among group A rotaviruses (RVAs), the G1 genotype is the main genotype causing diarrhea in children, but it has rarely been reported in pigs. During our epidemiological investigation, we detected G1P[7] rotavirus infection in piglets across several provinces in China and then isolated a porcine G1P[7] rotavirus strain (CN1P7). Sequencing revealed that the virus constellation was G1-P[7]-I5-R1-C1-M1-A8-N1-T1-E1-H1. Phylogenetic analyses revealed that CN1P7 most likely emerged due to genetic reassortment among porcine, human, giant panda and dog rotavirus strains. In vivo experiments were conducted on two-day-old piglets, which revealed that the CN1P7 strain was pathogenic to piglets. The virus was shed through the digestive tract and respiratory tract. In addition to the intestine, the CN1P7 strain displayed extraintestinal tropisms in piglets. Histopathological analysis revealed that the lung and small intestine were the targets of CN1P7. This study is the first to explore the molecular and pathogenic characterization of a pig-origin G1P[7] rotavirus.

Optimization of CRISPR/Cas12a detection assay and its application in the detection of Echinococcus granulosus

Cystic echinococcosis, resulting from infection with Echinococcus granulosus, poses a significant challenge as a neglected tropical disease owing to the lack of any known effective treatment. Primarily affecting under-resourced, remote, and conflict-ridden regions, the disease is compounded by the limitations of current detection techniques, such as microscopy, physical imaging, ELISA, and qPCR, which are unsuitable for application in these areas. The emergence of CRISPR/Cas12a as a promising tool for nucleic acid detection, characterized by its unparalleled specificity, heightened sensitivity, and rapid detection time, offers a potential solution. In this study, we present a one-pot CRISPR/Cas12a detection method for E. granulosus (genotype G1, sheep strain) integrating recombinase polymerase amplification (RPA) with suboptimal protospacer adjacent motif (PAM) and structured CRISPR RNA (crRNA) to enhance reaction efficiency. The evaluation of the assay's performance using hydatid cyst spiked dog feces and the examination of 62 dog fecal samples collected from various regions of Western China demonstrate its efficacy. The assay permits visual observation of test results about 15 minutes under blue light and displays superior portability and reaction speed relative to qPCR, achieving a sensitivity level of 10 copies of standard plasmids of the target gene. Analytic specificity was verified against four tapeworm species (E. multilocularis, H. taeniaeformis, M. benedeni, and D. caninum) and two other helminths (T. canis and F. hepatica), with negative results also noted for Mesocestoides sp. This study presents a rapid, sensitive, and time-efficient DNA detection method for E. granulosus of hydatid cyst spiked and clinical dog feces, potential serving as an alternative tool for field detection. This novel assay is primarily used to diagnose the definitive host of E. granulosus. Further validation using a larger set of clinical fecal samples is warranted, along with additional exploration of more effective approaches for nucleic acid release.

Genotype by Environment Interaction and Stability Analysis for Grain Yield in White Seeded Tef [&amp;lt;i&amp;gt;Eragrostis tef&amp;lt;/i&amp;gt; (zucc.)Trotter] Genotypes in Western Oromia, Ethiopia

Tef [&amp;lt;i&amp;gt;Eragrostis tef (Zucc.) Trotter &amp;lt;/i&amp;gt;L.] is a most important cereal crop in Ethiopia in terms of production, consumption and cash. The study was carried out to investigate grain yield stability and genotype by environment interaction for 18 genotypes conducted in the potential high land areas of Western Oromia, Ethiopia for two consecutive years (2020 to 2021) using Randomized Complete Block Experimental Design with three replications. The study of variance for grain yield using the AMMI model indicated highly significant variation for genotypes, environment, and genotype-environment interactions. Environment accounted for 18.7% of the variance in grain yield, 17.9% for genotypes, and 61.5% for genotypes. The first IPCA component accounted for 47.9% of the interaction effect and revealed the two models were fit. Genotypes G15, G10, G4, G1, and G3 had the lowest AMMI stability value (ASV), indicating stability; genotypes G16, G14, G9, G7, G2, and G5 had the highest ASV value, indicating instability. From over all analysis genotype G1 and G3, showed a high mean grain yield, lowest GSI, ASV and stable compared to other genotypes in the study. As a result, G1 and G3 were identified as the best genotypes for future breeding programs and potential release in Western Oromia, Ethiopia&amp;apos;s highlands.

Response of field pea (Pisum sativum L.) genotypes for grain yield in a multi-environment trial in Southeastern Ethiopia

Field pea (Pisum sativum L.) is a key cool-season food legume grown in Ethiopia, particularly in the Southeastern Arsi Zone. Although there is potential for field pea production in the area, adopting new and improved varieties is challenging because local farmers frequently prioritize cereal crops over field peas. To tackle this issue, a study was conducted to identify and promote high-yielding, improved field pea varieties suitable for the Southeastern farming community and similar agro-ecologies. The study focused on assessing the relationship between genotype and environment as well as the stability pattern of 14 advanced field pea genotypes. The genotypes were evaluated in eight environments in two consecutive cropping seasons (2014–2015) in southeast Ethiopia. The study utilized a randomized complete block design consisting of four replications. Various parametric stability analyses were used, including joint regression, additive main effect and multiplicative interaction (AMMI), and additive main effect and multiplicative interaction stability value (ASV). The grain yield was significantly influenced by genotype, location, and their interactions. The average grain yield ranged from 2809.5 kg ha−1 to 3509.1 kg ha−1. Eberhart's stability analysis identified stable genotypes: G3, G4, and G8, while G14 was unstable. According to additive main effect and multiplicative interaction stability value (ASV) and yield stability index (YSI), genotypes G12 and G13 had very low ASV values, whereas genotype G4 had very low ASV and YSI values. The AMMI and GGE biplot graphs showed that the principal component axes (PC1) and (PC2) accounted for 64.1 % and 61.36 % of the total variation, respectively. The results indicated that genotypes responded differently to environmental conditions and that the environment also influenced genotype performance. Genotypes G4 and G3 consistently performed well and exhibited remarkable stability, making them excellent cultivars for improving field pea productivity.