QTL Detection and Elite Alleles Mining for Stigma Traits in Oryza sativa by Association Mapping

Stigma traits are very important for hybrid seed production in Oryza sativa, which is a self-pollinated crop; however, the genetic mechanism controlling the traits is poorly understood. In this study, we investigated the phenotypic data of 227 accessions across two years and assessed their genotypic variation with 249 simple sequence repeat (SSR) markers. By combining phenotypic and genotypic data, a genome-wide association (GWA) map was generated. Large phenotypic variations in stigma length (STL), stigma brush-shaped part length (SBPL) and stigma non-brush-shaped part length (SNBPL) were found. Significant positive correlations were identified among stigma traits. In total, 2,072 alleles were detected among 227 accessions, with an average of 8.3 alleles per SSR locus. GWA mapping detected 6 quantitative trait loci (QTLs) for the STL, 2 QTLs for the SBPL and 7 QTLs for the SNBPL. Eleven, 5, and 12 elite alleles were found for the STL, SBPL and SNBPL, respectively. Optimal cross designs were predicted for improving the target traits. The detected genetic variation in stigma traits and QTLs provides helpful information for cloning candidate STL genes and breeding rice cultivars with longer STLs in the future

Fine mapming and candidate gene analysis of <i>qSTL3</i>.

<p>(A) Primary mapping of <i>qSTL3</i>. The <i>qSTL3</i> was mapped between the SSR markers RM3766 and RM5639 based on 220 plants randomly selected from the SSSL14/Nipponbare F₂ population. (B) Physical mapping of <i>qSTL3</i>. The <i>qSTL3</i> was positioned between the SSR markers RM14680 and RM5639 based on 3,407 plants from the SSSL14/Nipponbare F₂ population. (C) High-resolution mapping of <i>qSTL3</i>. The <i>qSTL3</i> was narrowed down to a 19.8-kb region between the markers RM14680 and LQ17 on the BAC clones OSJNBb0081I10 and OSJNBa0019J12 using a total of 7,917 plants from the SSSL14/Nipponbare F₂ population. (D) Candidate region of the <i>qSTL3</i> locus and the annotated genes in the Rice Annotation Project Database (RAP-DB, <a href="http://rapdb.dna.affrc.go.jp/" target="_blank">http://rapdb.dna.affrc.go.jp/</a>). (E) The structure of the <i>LOC_Os03g14850</i> gene and variation sites. The <i>orange bar</i> indicates the exon.</p

Fine Mapping and Candidate Gene Analysis of <i>qSTL3</i>, a Stigma Length-Conditioning Locus in Rice (<i>Oryza sativa </i>L.)

<div><p>The efficiency of hybrid seed production can be improved by increasing the percentage of exserted stigma, which is closely related to the stigma length in rice. In the chromosome segment substitute line (CSSL) population derived from Nipponbare (recipient) and Kasalath (donor), a single CSSL (SSSL14) was found to show a longer stigma length than that of Nipponbare. The difference in stigma length between Nipponbare and SSSL14 was controlled by one locus (<i>qSTL3</i>). Using 7,917 individuals from the SSSL14/Nipponbare F₂ population, the <i>qSTL3</i> locus was delimited to a 19.8-kb region in the middle of the short arm of chromosome 3. Within the 19.8-kb chromosome region, three annotated genes (<i>LOC_Os03g14850</i>, <i>LOC_Os03g14860</i> and <i>LOC_Os03g14880</i>) were found in the rice genome annotation database. According to gene sequence alignments in <i>LOC_Os03g14850</i>, a transition of G (Nipponbare) to A (Kasalath) was detected at the 474-bp site in CDS. The transition created a stop codon, leading to a deletion of 28 amino acids in the deduced peptide sequence in Kasalath. A T-DNA insertion mutant (05Z11CN28) of <i>LOC_Os03g14850 </i>showed a longer stigma length than that of wild type (Zhonghua 11), validating that <i>LOC_Os03g14850 </i>is the gene controlling stigma length. However, the Kasalath allele of <i>LOC_Os03g14850 </i>is unique because all of the alleles were the same as that of Nipponbare at the 474-bp site in the CDS of <i>LOC_Os03g14850 </i>among the investigated accessions with different stigma lengths. A gene-specific InDel marker LQ30 was developed for improving stigma length during rice hybrid breeding by marker-assisted selection.</p></div

T-DNA insertion mutant analysis of <i>LOC_Os03g14850</i>.

<p>(A) <i>LOC_Os03g14850</i> gene structure and T-DNA insertion site. White boxes, thin lines and gray boxes represent exons, introns and UTRs, respectively. LB and RB represent the left and right border of the T-DNA, respectively. P1 and P2 represent the gene-specific PCR primers flanking the T-DNA insertion site and P3 represents the vector border primer. (B) PCR genotyping results. W and M indicate the wild type and homozygous mutant, respectively. (C) Real time quantitative RT-PCR result of <i>LOC_Os03g14850</i> in wild type and the homozygous mutant. The target gene was <i>LOC_Os03g14850</i>. The <i>18S rRNA</i> gene was the control. (D) Stigma phenotype of wild type and mutant. <i>Bar</i> = 1 mm. (E-I) Comparison of the stigma length, grain length, grain width, grain thickness, plant height and days to heading of wild type and mutant. A <i>t</i> test was performed between wild type and mutant. All data are given as the mean ± SD.</p

Genotypic and phenotypic performance of the parents.

<p>(A) Graphical genotype of SSSL14. The <i>black bar</i> indicates the fragment from Kasalath, and the remaining was derived from Nipponbare. (B) Chromosome map based on SSR markers of chromosome 3 of SSSL14. The <i>black circle</i> marks the position of the centromere. (C) Stigma morphology of Nipponbare, SSSL14 and Kasalath. <i>Bar</i> = 1 mm. The two thin lines aside the stigma of SSSL14 show the method used to measure stigma length. (D) Stigma length of Nipponbare, SSSL14 and Kasalath over two years. A, B and C were ranked by Duncan’s test at <i>P</i><0.01.</p

Prevalence and antibiotic resistance profiles of cerebrospinal fluid pathogens in children with acute bacterial meningitis in Yunnan province, China, 2012-2015

<div><p>Acute bacterial meningitis is still considered one of the most dangerous infectious diseases in children. To investigate the prevalence and antibiotic resistance profiles of cerebrospinal fluid (CSF) pathogens in children with acute bacterial meningitis in Southwest China, CSF samples from 179 meningitis patients (3 days to 12 years old) with positive culture results were collected from 2012 to 2015. Isolated pathogens were identified using the Vitek-32 system. Gram stain results were used to guide subcultures and susceptibility testing. The antimicrobial susceptibility of isolates was determined using the disc diffusion method. Of the isolates, 50.8% were Gram-positive bacteria, and 49.2% were Gram-negative bacteria. The most prevalent pathogens were <i>E</i>. <i>coli</i> (28.5%), <i>Streptococcus pneumoniae</i> (17.8%), <i>Staphylococcus epidermidis</i> (10.0%), <i>Haemophilus influenzae type b</i> (9.5%), and <i>group B streptococcus</i> (7.2%). In young infants aged ≤3 months, <i>E</i>. <i>coli</i> was the organism most frequently isolated from CSF (39/76; 51.3%), followed by <i>group B streptococcus</i> (13/76; 17.1%) and <i>Streptococcus pneumoniae</i> (8/76; 10.5%). However, in young infants aged >3 months, the most frequently isolated organism was <i>Streptococcus pneumoniae</i> (24/103; 23.3%), followed by <i>Staphylococcus epidermidis</i> (18/103; 17.5%) and <i>Haemophilus influenzae type b</i> (16/103; 15.5%). Antimicrobial susceptibility tests indicated that for <i>E</i>. <i>coli</i> isolates, the susceptibility rates to aminoglycosides ranged from 56.8% to 100.0%, among them, amikacin was identified as the most effective against <i>E</i>. <i>coli</i>. As for cephalosporins, the susceptibility rates ranged from 29.4% to 78.4%, and cefoxitin was identified as the most effective cephalosporin. In addition, the susceptibility rates of piperacillin/tazobactam and imipenem against E. coli were 86.3% and 100%. Meanwhile, the susceptibility rates of <i>Streptococcus pneumoniae</i> isolates to penicillin G, erythromycin, chloramphenicol, ceftriaxone and tetracycline were 68.8%, 0.0%, 87.5%, 81.3% and 0.0%, respectively. Gentamycin, ofloxacin, linezolid and vancomycin were identified as the most effective antibiotics for <i>Streptococcus pneumoniae</i>, each with susceptibility rates of 100%. It was notable that other emerging pathogens, such as <i>Listeria monocytogenes</i> and <i>group D streptococcus</i>, cannot be underestimated in meningitis.</p></div

Clinical manifestations of pediatric patients with acute meningitis from 2012–2015.

<p>Clinical manifestations of pediatric patients with acute meningitis from 2012–2015.</p

Seasonal variation in the number of confirmed meningitis cases was examined from 2012 to 2015.

<p>A greater number of confirmed meningitis cases occurred during 2015 than occurred during any other year. The highest number of confirmed meningitis cases occurred during February 2015. The monthly prevalence of confirmed meningitis was, for the most part, lower in 2012, except for during the month of February. It was notable that the seasonal distribution indicated that the number of positive CSF cultures decreased during the rainy season (May—October) in Southwest China.</p

Single‐cell transcriptomic atlas of distinct early immune responses induced by SARS‐CoV‐2 Proto or its variants in rhesus monkey

Abstract Immune responses induced by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection play a critical role in the pathogenesis and outcome of coronavirus disease 2019 (COVID‐19). However, the dynamic profile of immune responses postinfection by SARS‐CoV‐2 variants of concern (VOC) is not fully understood. In this study, peripheral blood mononuclear cells single‐cell sequencing was performed to determine dynamic profiles of immune response to Prototype, Alpha, Beta, and Delta in a rhesus monkey model. Overall, all strains induced dramatic changes in both cellular subpopulations and gene expression levels at 1 day postinfection (dpi), which associated function including adaptive immune response, innate immunity, and IFN response. COVID‐19‐related genes revealed different gene profiles at 1 dpi among the four SARS‐CoV‐2 strains, including genes reported in COVID‐19 patients with increased risk of autoimmune disease and rheumatic diseases. Delta‐infected animal showed inhibition of translation pathway. B cells, T cells, and monocytes showed much commonality rather than specificity among the four strains. Monocytes were the major responders to SARS‐CoV‐2 infection, and the response lasted longer in Alpha than the other strains. Thus, this study reveals the early immune responses induced by SARS‐CoV‐2 Proto or its variants in nonhuman primates, which is important information for controlling rapidly evolving viruses