Development and mapping of SNP assays in allotetraploid cotton

A narrow germplasm base and a complex allotetraploid genome have made the discovery of single nucleotide polymorphism (SNP) markers difficult in cotton (Gossypiumhirsutum). To generate sequence for SNP discovery, we conducted a genome reduction experiment (EcoRI, BafI double digest, followed by adapter ligation, biotin–streptavidin purification, and agarose gel separation) on two accessions of G. hirsutum and two accessions of G. barbadense. From the genome reduction experiment, a total of 2.04 million genomic sequence reads were assembled into contigs with an N50 of 508 bp and analyzed for SNPs. A previously generated assembly of expressed sequence tags (ESTs) provided an additional source for SNP discovery. Using highly conservative parameters (minimum coverage of 8× at each SNP and 20% minor allele frequency), a total of 11,834 and 1,679 non-genic SNPs were identified between accessions of G. hirsutum and G. barbadense in genome reduction assemblies, respectively. An additional 4,327 genic SNPs were also identified between accessions of G. hirsutum in the EST assembly. KBioscience KASPar assays were designed for a portion of the intra-specific G. hirsutum SNPs. From 704 non-genic and 348 genic markers developed, a total of 367 (267 non-genic, 100 genic) mapped in a segregating F2 population (Acala Maxxa × TX2094) using the Fluidigm EP1 system. A G. hirsutum genetic linkage map of 1,688 cM was constructed based entirely on these new SNP markers. Of the genic-based SNPs, we were able to identify within which genome (‘A’ or ‘D’) each SNP resided using diploid species sequence data. Genetic maps generated by these newly identified markers are being used to locate quantitative, economically important regions within the cotton genome

MT-Toolbox: improved amplicon sequencing using molecule tags

Abstract Background Short oligonucleotides can be used as markers to tag and track DNA sequences. For example, barcoding techniques (i.e. Multiplex Identifiers or Indexing) use short oligonucleotides to distinguish between reads from different DNA samples pooled for high-throughput sequencing. A similar technique called molecule tagging uses the same principles but is applied to individual DNA template molecules. Each template molecule is tagged with a unique oligonucleotide prior to polymerase chain reaction. The resulting amplicon sequences can be traced back to their original templates by their oligonucleotide tag. Consensus building from sequences sharing the same tag enables inference of original template molecules thereby reducing effects of sequencing error and polymerase chain reaction bias. Several independent groups have developed similar protocols for molecule tagging; however, user-friendly software for build consensus sequences from molecule tagged reads is not readily available or is highly specific for a particular protocol. Results MT-Toolbox recognizes oligonucleotide tags in amplicons and infers the correct template sequence. On a set of molecule tagged test reads, MT-Toolbox generates sequences having on average 0.00047 errors per base. MT-Toolbox includes a graphical user interface, command line interface, and options for speed and accuracy maximization. It can be run in serial on a standard personal computer or in parallel on a Load Sharing Facility based cluster system. An optional plugin provides features for common 16S metagenome profiling analysis such as chimera filtering, building operational taxonomic units, contaminant removal, and taxonomy assignments. Conclusions MT-Toolbox provides an accessible, user-friendly environment for analysis of molecule tagged reads thereby reducing technical errors and polymerase chain reaction bias. These improvements reduce noise and allow for greater precision in single amplicon sequencing experiments

Alterations in airway microbiota in patients with PaO₂/FiO₂ ratio ≤ 300 after burn and inhalation injury

<div><p>Background</p><p>Injury to the airways after smoke inhalation is a major mortality risk factor in victims of burn injuries, resulting in a 15–45% increase in patient deaths. Damage to the airways by smoke may induce acute respiratory distress syndrome (ARDS), which is partly characterized by hypoxemia in the airways. While ARDS has been associated with bacterial infection, the impact of hypoxemia on airway microbiota is unknown. Our objective was to identify differences in microbiota within the airways of burn patients who develop hypoxemia early after inhalation injury and those that do not using next-generation sequencing of bacterial 16S rRNA genes.</p><p>Results</p><p>DNA was extracted from therapeutic bronchial washings of 48 patients performed within 72 hours of hospitalization for burn and inhalation injury at the North Carolina Jaycee Burn Center. DNA was prepared for sequencing using a novel molecule tagging method and sequenced on the Illumina MiSeq platform. Bacterial species were identified using the MTToolbox pipeline. Patients with hypoxemia, as indicated by a PaO₂/FiO₂ ratio ≤ 300, had a 30% increase in abundance of <i>Streptococcaceae</i> and <i>Enterobacteriaceae</i> and 84% increase in <i>Staphylococcaceae</i> as compared to patients with a PaO₂/FiO₂ ratio > 300. Wilcoxon rank-sum test identified significant enrichment in abundance of OTUs identified as <i>Prevotella melaninogenica (p</i> = 0.042), <i>Corynebacterium</i> (<i>p</i> = 0.037) and <i>Mogibacterium</i> (<i>p</i> = 0.048). Linear discriminant effect size analysis (LefSe) confirmed significant enrichment of <i>Prevotella melaninognica</i> among patients with a PaO₂/FiO₂ ratio ≤ 300 (<i>p</i><0.05). These results could not be explained by differences in antibiotic treatment.</p><p>Conclusions</p><p>The airway microbiota following burn and inhalation injury is altered in patients with a PaO₂/FiO₂ ratio ≤ 300 early after injury. Enrichment of specific taxa in patients with a PaO₂/FiO₂ ratio ≤ 300 may indicate airway environment and patient changes that favor these microbes. Longitudinal studies are necessary to identify stably colonizing taxa that play roles in hypoxemia and ARDS pathogenesis.</p></div

Patient clinical characteristics.

<p>Patient clinical characteristics.</p

OTU level detection differences.

<p>OTU level detection differences.</p

Percent abundance of OTUs with significant enrichment detected by LEfSe.

<p>Of the three taxa LEfSe identified as significantly enriched in patients with hypoxemia, <i>Staphylococcus</i> had the highest percent increase in abundance. However, <i>Prevotella melaninogenica</i> was more consistently present among patients with hypoxemia, resulting in its higher ranking over <i>Staphylococcus spp</i>. (A) Bacterial abundances for taxa identified as significantly enriched by LEfSe are displayed per patient. The X axis is labeled with each patient’s PaO₂/FiO₂ ratio and the Y axis displays relative abundance of the taxa. (B) The range of abundances of the three significantly enriched taxa are split by patient hypoxemia status along the X axis. (n = 48).</p

Increased detection of unique facultative anaerobic taxa.

<p>(A) Unique facultative anaerobic OTUs were detected significantly more frequently than obligate aerobes or anaerobes among all patients. (B) No significant difference was found between number of unique facultative anaerobic OTUs when the data was split by patient PaO₂/FiO₂ ratio. OTUs were identified as facultative anaerobes, obligate anaerobes, or obligate aerobes among all patients. OTUs were quantified and normalized to the molecule tag count and averaged by bacterial aerobic or anaerobic capability. One-way ANOVA detected a significant difference among the mean taxa of facultative anaerobes (<i>p</i> = 0.029). (n = 48)</p