Dataset Information

High resolution estimates of relative gene abundance with quantitative ratiometric regression PCR (qRR-PCR).

ABSTRACT: Quantification of the relative abundance of genetic traits has broad applications for biomarker discovery, diagnostics, and assessing gene expression in biological research. Relative quantification of genes is traditionally done with the 2^-ΔΔCT method using quantitative real-time polymerase chain reaction (qPCR) data, which is often limited in resolution beyond orders of magnitude difference. The latest techniques for quantification of nucleic acids employ digital PCR or microarrays which involve lengthy sample preparation and complex instrumentation. In this work, we describe a quantitative ratiometric regression PCR (qRR-PCR) method for computing relative abundance of genetic traits in a sample with high resolution from a single duplexed real-time quantitative PCR assay. Instead of comparing the individual cycle threshold (Ct) values as is done for the 2^-ΔΔCT method, our qRR-PCR algorithm leverages the innate relationship of co-amplified PCR targets to measure their relative quantities using characteristic curves derived from the normalized ratios of qPCR fluorescence curves. We demonstrate the utility of this technique for discriminating the fractional abundance of mixed alleles with resolution below 5%.

SUBMITTER: Trick AY

PROVIDER: S-EPMC8627783 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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High resolution estimates of relative gene abundance with quantitative ratiometric regression PCR (qRR-PCR).

Trick Alexander Y AY Chen Fan-En FE Schares Justin A JA Freml Blake E BE Lor Pa P Yun Yue Y Wang Tza-Huei TH

The Analyst 20211025 21

Quantification of the relative abundance of genetic traits has broad applications for biomarker discovery, diagnostics, and assessing gene expression in biological research. Relative quantification of genes is traditionally done with the 2<sup>-ΔΔCT</sup> method using quantitative real-time polymerase chain reaction (qPCR) data, which is often limited in resolution beyond orders of magnitude difference. The latest techniques for quantification of nucleic acids employ digital PCR or microarrays w ...[more]

PMID: 34605831

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Project description:UnlabelledHigh-throughput sequencing (HTS) is revolutionizing environmental surveys of microbial diversity in the three domains of life by providing detailed information on which taxa are present in microbial assemblages. However, it is still unclear how the relative abundance of specific taxa gathered by HTS correlates with cell abundances. Here, we quantified the relative cell abundance of 6 picoeukaryotic taxa in 13 planktonic samples from 6 European coastal sites using epifluorescence microscopy on tyramide signal amplification-fluorescence in situ hybridization preparations. These relative abundance values were then compared with HTS data obtained in three separate molecular surveys: 454 sequencing of the V4 region of the 18S ribosomal DNA (rDNA) using DNA and RNA extracts (DNA-V4 and cDNA-V4) and Illumina sequencing of the V9 region (cDNA-V9). The microscopic and molecular signals were generally correlated, indicating that a relative increase in specific 18S rDNA was the result of a large proportion of cells in the given taxa. Despite these positive correlations, the slopes often deviated from 1, precluding a direct translation of sequences to cells. Our data highlighted clear differences depending on the nucleic acid template or the 18S rDNA region targeted. Thus, the molecular signal obtained using cDNA templates was always closer to relative cell abundances, while the V4 and V9 regions gave better results depending on the taxa. Our data support the quantitative use of HTS data but warn about considering it as a direct proxy of cell abundances.ImportanceDirect studies on marine picoeukaryotes by epifluorescence microscopy are problematic due to the lack of morphological features and due to the limited number and poor resolution of specific phylogenetic probes used in fluorescence in situ hybridization (FISH) routines. As a consequence, there is an increasing use of molecular methods, including high-throughput sequencing (HTS), to study marine microbial diversity. HTS can provide a detailed picture of the taxa present in a community and can reveal diversity not evident using other methods, but it is still unclear what the meaning of the sequence abundance in a given taxon is. Our aim is to investigate the correspondence between the relative HTS signal and relative cell abundances in selected picoeukaryotic taxa. Environmental sequencing provides reasonable estimates of the relative abundance of specific taxa. Better results are obtained when using RNA extracts as the templates, while the region of 18S ribosomal DNA had different influences depending on the taxa assayed.

Project description:The nodule-forming actinobacterial genus Frankia can generally be divided into 4 taxonomic clusters, with clusters 1, 2, and 3 representing nitrogen-fixing strains of different host infection groups and cluster 4 representing atypical, generally non-nitrogen-fixing strains. Recently, quantitative PCR (qPCR)-based quantification methods have been developed for frankiae of clusters 1 and 3; however, similar approaches for clusters 2 and 4 were missing. We amended a database of partial 23S rRNA gene sequences of Frankia strains belonging to clusters 1 and 3 with sequences of frankiae representing clusters 2 and 4. The alignment allowed us to design primers and probes for the specific detection and quantification of these Frankia clusters by either Sybr Green- or TaqMan-based qPCR. Analyses of frankiae in different soils, all obtained from the same region in Illinois, USA, provided similar results, independent of the qPCR method applied, with abundance estimates of 10 × 105 to 15 × 105 cells (g soil)-1 depending on the soil. Diversity was higher in prairie soils (native, restored, and cultivated), with frankiae of all 4 clusters detected and those of cluster 4 dominating, while diversity in soils under Alnus glutinosa, a host plant for cluster 1 frankiae, or Betula nigra, a related nonhost plant, was restricted to cluster 1 and 3 frankiae and generally members of subgroup 1b were dominating. These results indicate that vegetation affects the basic composition of frankiae in soils, with higher diversity in prairie soils compared to much more restricted diversity under some host and nonhost trees.IMPORTANCE Root nodule formation by the actinobacterium Frankia is host plant specific and largely, but not exclusively, correlates with assignments of strains to specific clusters within the genus. Due to the lack of adequate detection and quantification tools, studies on Frankia have been limited to clusters 1 and 3 and generally excluded clusters 2 and 4. We have developed tools for the detection and quantification of clusters 2 and 4, which can now be used in combination with those developed for clusters 1 and 3 to retrieve information on the ecology of all clusters delineated within the genus Frankia Our initial results indicate that vegetation affects the basic composition of frankiae in soils, with higher diversity in prairie soils compared to much more restricted diversity under some host and nonhost trees.

Dataset Information

High resolution estimates of relative gene abundance with quantitative ratiometric regression PCR (qRR-PCR).

Publications

High resolution estimates of relative gene abundance with quantitative ratiometric regression PCR (qRR-PCR).

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