Search

The identification of stable quantitative trait locus (QTL) for yield-related traits and tightly linked molecular markers is important for improving wheat grain yield. In the present study, six yield-related traits in a recombinant inbred line (RIL) population derived from the Zhongmai 578/Jimai 22 cross were phenotyped in five environments. The parents and 262 RILs were genotyped using the wheat 50K single nucleotide polymorphism (SNP) array. A high-density genetic map was constructed with 1 501 non-redundant bin markers, spanning 2 384.95 cM. Fifty-three QTLs for six yield-related traits were mapped on chromosomes 1D (2), 2A (9), 2B (6), 2D, 3A (2), 3B (2), 4A (5), 4D, 5B (8), 5D (2), 7A (7), 7B (3) and 7D (5), which explained 2.7–25.5% of the phenotypic variances. Among the 53 QTLs, 23 were detected in at least three environments, including seven for thousand-kernel weight (TKW), four for kernel length (KL), four for kernel width (KW), three for average grain filling rate (GFR), one for kernel number per spike (KNS) and four for plant height (PH). The stable QTLs QKl.caas-2A.1, QKl.caas-7D, QKw.caas-7D, QGfr.caas-2B.1, QGfr.caas-4A, QGfr.caas-7A and QPh.caas-2A.1 are likely to be new loci. Six QTL-rich regions on 2A, 2B, 4A, 5B, 7A and 7D, showed pleiotropic effects on various yield traits. TaSus2-2B and WAPO-A1 are potential candidate genes for the pleiotropic regions on 2B and 7A, respectively. The pleiotropic QTL on 7D for TKW, KL, KW and PH was verified in a natural population. The results of this study enrich our knowledge of the genetic basis underlying yield-related traits and provide molecular markers for high-yield wheat breeding.

Pre-harvest sprouting (PHS) is one of the serious global issues in wheat production. Identification of quantitative trait loci (QTL) and closely-linked markers is greatly helpful for wheat improvement. In the present study, a recombinant inbred line (RIL) population derived from the cross of Zhongmai 578 (ZM578)/Jimai 22 (JM22) and parents were phenotyped in five environments and genotyped by the wheat 50 K single-nucleotide polymorphism (SNP) array. Two QTL of germination index (GI), QGI.caas-3A and QGI.caas-5A, were detected, explaining 4.33%–5.58% and 4.43%–8.02% of the phenotypic variances, respectively. The resistant effect of QGI.caas-3A was contributed by JM22, whereas that of QGI.caas.5A was from ZM578. The two QTL did not correspond to any previously identified genes or genetic loci for PHS-related traits according to their locations in the Chinese Spring reference genome, indicating that they are likely to be new loci for PHS resistance. Four kompetitive allele-specific PCR (KASP) markers K_AX-109605367and K_AX-179559687 flanking QGI.caas-3A, and K_AX-111258240 and K_AX-109402944 flanking QGI.caas-5A, were developed and validated in a natural population of 100 wheat cultivars. The distribution frequency of resistance alleles at Qphs.caas-3A and Qphs.caas-5A loci were 82.7% and 57.1%, respectively, in the natural population. These findings provide new QTL and tightly linked KASP markers for improvement of PHS resistance in wheat.

Grain yield (GY) prediction for wheat based on canopy spectral reflectance can improve selection efficiency in breeding programs. Time-series spectral information from different growth stages such as flowering to maturity is considered to have high accuracy in predicting GY and combining this information from multiple growth stages could effectively improve prediction accuracy. For this, 207 wheat cultivars and breeding lines were grown in full and limited irrigation treatments, and their canopy spectral reflectance was measured at the flowering, early, middle, and late grain fill stages. The potential of temporal spectral information at multiple growth stages for GY prediction was evaluated by a new method based on stacking the multiple growth stages data. Twenty VIs derived from spectral reflectance were used as the input feature of a support vector regression (SVR) to predict GY at each growth stage. The predicted GY values at multiple growth stages were trained by multiple linear regression (MLR) to establish a second-level prediction model. Results suggested that the prediction accuracy (R2) of VIs data from single growth stages ranged from 0.60 to 0.66 and 0.35 to 0.42 in the full and limited irrigation treatments, respectively. The prediction accuracy was increased by an average of 0.06, 0.07, and 0.07 after stacking the VIs of two, three, and four growth stages, respectively, under full irrigation. Similarly, under limited irrigation, the prediction accuracy was increased by 0.03, 0.04, and 0.04 by stacking the VIs of two, three, and four growth stages, respectively. Stacking of VIs of multiple important growth stages can increase the accuracy of GY prediction and application of a stable stacking model could increase the usefulness of data obtained from different phenotyping platforms.

Abstract After the successful roll out of MenAfriVac, Nigeria has experienced sequential meningitis outbreaks attributed to meningococcus serogroup C (NmC). Zamfara State in North-western Nigeria recently was at the epicentre of the largest NmC outbreak in the 21st Century with 7,140 suspected meningitis cases and 553 deaths reported between December 2016 and May 2017. The overall attack rate was 155 per 100,000 population and children 5–14 years accounted for 47% (3,369/7,140) of suspected cases. The case fatality rate (CFR) among children 5–9 years was 10%, double that reported among adults ≥ 30 years (5%). NmC and pneumococcus accounted for 94% (172/184) and 5% (9/184) of the laboratory-confirmed cases, respectively. The sequenced NmC belonged to the ST-10217 clonal complex (CC). All serotyped pneumococci were PCV10 serotypes. The emergence of NmC ST-10217 CC outbreaks threatens the public health gains made by MenAfriVac, which calls for an urgent strategic action against meningitis outbreaks.

Background and Objectives: Ferulic acid is a prominent bioactive compound found in wheat grains, known for its beneficial health effects, prompting significant interest from breeders and producers. The aim of this study was to identify new quantitative trait loci (QTL) to aid in the development of wheat varieties with increased ferulic acid concentration (FAC). Findings: In this study, a recombinant inbred line population, resulting from a cross between Zhongmai 578 and Jimai 22, was evaluated in five different environments. Genotyping was performed using the wheat 50 K single‐nucleotide polymorphism (SNP) array. Three stable QTL, named QFAC.caas‐2D, QFAC.caas‐3B, and QFAC.caas‐4D, were identified. These QTL explained 4.24%–7.09%, 3.7%–4.57%, and 3.20%–5.06% of the phenotypic variances, respectively. Furthermore, three SNPs closely associated with above QTL were successfully converted into kompetitive allele‐specific polymerase chain reaction (KASP) markers. Conclusions: FAC is a complex trait governed by multiple minor‐effect QTL. The successful development of KASP markers opens up avenues for marker‐assisted selection in breeding programs. Significance and Novelty: This study establishes a genetic foundation for understanding the genetic basis of FAC in wheat. The identified QTL and developed KASP markers offer valuable insights for quality breeding initiatives and the production of functional wheat‐based foods. [ABSTRACT FROM AUTHOR]

Background: Urinary tract infection (UTI) refers to any part of urinary system infection caused by the presence and growth of microorganisms anywhere in the urinary tract. The infections are commonly found in women. Staphylococcus saprophyticus may infect the urinary tract. Methods: Isolation of Staphylococcus spp was carried out using the streak plate method on Mannitol salt and Blood agar. Pure isolates were subjected to different biochemical tests for identification. Kirby bauer method was used to determine the antibiotic susceptibility profile of the isolates. Results: S. saprophyticus accounted for 27 (55.1%) of the isolates, S.aureus accounted for 14 (28.6%) of the isolates, and S. epidermidis accounted for 8 (10.2%) of the isolates. Most of the isolates were susceptible to Levofloxacin and Rifampin, while Erythromycin, Clarithromycin, Streptromycin and Amoxicillin were resisted by the isolates of the Staphylococcus species. S. saprophyticus isolates were susceptible to Levofloxacin (55.6%) and least susceptible to Norfloxacin (11.1%). S. epidermidis were more susceptible to Levofloxacin (75.0%), and resistant to Ampicillin (0.0%), while S. aureus was most susceptible to Levofloxacin (78.6%) and least to Ampicillin and erythromycin (14.3%). Age, occupation, marital status and area of domicile of the patients were found to be associated with the occurrence of Staphylococcus species in the urine of patients (P<0.5). Educational status indicated no association with the incidence of Staphylococcus species in the urine of patients (P>0.5). Conclusion: S. saprophyticus was found as the most predominant Staphylococcus species in the urine of women attending IBB specialist hospital Minna, Niger state, Nigeria. [ABSTRACT FROM AUTHOR]

Abstract BackgroundThe COVID-19 pandemic caused by SARS-CoV-2 is causing ongoing human and socioeconomic losses. ObjectiveTo know how far the virus has spread in Niger State, Nigeria, a pilot study was carried out to determine the SARS-CoV-2 seroprevalence, patterns, dynamics, and risk factors in the state. MethodsA cross-sectional study design and clustered, stratified random sampling strategy were used to select 185 test participants across the state. SARS-CoV-2 IgG and IgM rapid test kits (colloidal gold immunochromatography lateral flow system) were used to determine the presence or absence of antibodies to the virus in the blood of sampled participants across Niger State from June 26 to 30, 2020. The test kits were validated using the blood samples of some of the Nigeria Center for Disease Control–confirmed positive and negative COVID-19 cases in the state. SARS-CoV-2 IgG and IgM test results were entered into the Epi Info questionnaire administered simultaneously with each test. Epi Info was then used to calculate the arithmetic mean and percentage, odds ratio, χ2 ResultsThe seroprevalence of SARS-CoV-2 in Niger State was found to be 25.4% (47/185) and 2.2% (4/185) for the positive IgG and IgM results, respectively. Seroprevalence among age groups, genders, and occupations varied widely. The COVID-19 asymptomatic rate in the state was found to be 46.8% (22/47). The risk analyses showed that the chances of infection are almost the same for both urban and rural dwellers in the state. However, health care workers, those who experienced flulike symptoms, and those who had contact with a person who traveled out of Nigeria in the last 6 months (February to June 2020) were at double the risk of being infected with the virus. More than half (101/185, 54.6%) of the participants in this study did not practice social distancing at any time since the pandemic started. Participants’ knowledge, attitudes, and practices regarding COVID-19 are also discussed. ConclusionsThe observed Niger State SARS-CoV-2 seroprevalence and infection patterns meansuggest that the virus has widely spread, far more SARS-CoV-2 infections have occurred than the reported cases, and there is a high asymptomatic COVID-19 rate across the state.