ABSTRACT
Recent advances in next generation sequencing have created opportunities to directly identify genetic loci and candidate genes for abiotic stress responses in plants. With the objective of identifying candidate genes within the previously identified QTL-hotspots, the whole genomes of two divergent cultivars for salt responses, namely At 354 and Bg 352, were re-sequenced using Illumina Hiseq 2500 100PE platform and mapped to Nipponbare and R498 genomes. The sequencing results revealed approximately 2.4 million SNPs and 0.2 million InDels with reference to Nipponbare while 1.3 million and 0.07 million with reference to R498 in two parents. In total, 32,914 genes were reported across all rice chromosomes of this study. Gene mining within QTL hotspots revealed 1236 genes, out of which 106 genes were related to abiotic stress. In addition, 27 abiotic stress-related genes were identified in non-QTL regions. Altogether, 32 genes were identified as potential genes containing polymorphic non-synonymous SNPs or InDels between two parents. Out of 10 genes detected with InDels, tolerant haplotypes of Os01g0581400, Os10g0107000, Os11g0655900, Os12g0622500, and Os12g0624200 were found in the known salinity tolerant donor varieties. Our findings on different haplotypes would be useful in developing resilient rice varieties for abiotic stress by haplotype-based breeding studies.
ABSTRACT
BACKGROUND: Infectious disease is the leading cause of death worldwide, and diagnosis of polymicrobial and fungal infections is increasingly challenging in the clinical setting. Conventionally, molecular detection is still the best method of species identification in clinical samples. However, the limitations of Sanger sequencing make diagnosis of polymicrobial infections one of the biggest hurdles in treatment. The development of massively parallel sequencing or next generation sequencing (NGS) has revolutionized the field of metagenomics, with wide application of the technology in identification of microbial communities in environmental sources, human gut and others. However, to date there has been no commercial application of this technology in infectious disease diagnostic settings. METHODS: Credence Genomics Rapid Infection Detection™ test, is a molecular based diagnostic test that uses next generation sequencing of bacterial 16S rRNA gene and fungal ITS1 gene region to provide accurate identification of species within a clinical sample. Here we present a study comparing 16S and ITS1 metagenomic identification against conventional culture for clinical samples. Using culture results as gold standard, a comparison was conducted using patient specimens from a clinical microbiology lab. RESULTS: Metagenomics based results show a 91.8% concordance rate for culture positive specimens and 52.8% concordance rate with culture negative samples. 10.3% of specimens were also positive for fungal species which was not investigated by culture. Specificity and sensitivity for metagenomics analysis is 91.8 and 52.7% respectively. CONCLUSION: 16S based metagenomic identification of bacterial species within a clinical specimen is on par with conventional culture based techniques and when coupled with clinical information can lead to an accurate diagnostic tool for infectious disease diagnosis.