Multiplexed in situ hybridization reveals distinct lineage identities for major and minor vein initiation during maize leaf development.

Leaves of flowering plants are characterized by diverse venation patterns. Patterning begins with the selection of vein-forming procambial initial cells from within the ground meristem of a developing leaf, a process which is considered to be auxin-dependent, and continues until veins are anatomically differentiated with functional xylem and phloem. At present, the mechanisms responsible for leaf venation patterning are primarily characterized in the model eudicot Arabidopsis thaliana which displays a reticulate venation network. However, evidence suggests that vein development may proceed via a different mechanism in monocot leaves where venation patterning is parallel. Here, we employed Molecular Cartography, a multiplexed in situ hybridization technique, to analyze the spatiotemporal localization of a subset of auxin-related genes and candidate regulators of vein patterning in maize leaves. We show how different combinations of auxin influx and efflux transporters are recruited during leaf and vein specification and how major and minor vein ranks develop with distinct identities. The localization of the procambial marker PIN1a and the spatial arrangement of procambial initial cells that give rise to major and minor vein ranks further suggests that vein spacing is prepatterned across the medio-lateral leaf axis prior to accumulation of the PIN1a auxin transporter. In contrast, patterning in the adaxial-abaxial axis occurs progressively, with markers of xylem and phloem gradually becoming polarized as differentiation proceeds. Collectively, our data suggest that both lineage- and position-based mechanisms may underpin vein patterning in maize leaves.

Phi29 polymerase based random amplification of viral RNA as an alternative to random RT-PCR.

BACKGROUND: Phi29 polymerase based amplification methods provides amplified DNA with minimal changes in sequence and relative abundance for many biomedical applications. RNA virus detection using microarrays, however, can present a challenge because phi29 DNA polymerase cannot amplify RNA nor small cDNA fragments (<2000 bases) obtained by reverse transcription of certain viral RNA genomes. Therefore, ligation of cDNA fragments is necessary prior phi29 polymerase based amplification. We adapted the QuantiTect Whole Transcriptome Kit (Qiagen) to our purposes and designated the method as Whole Transcriptome Amplification (WTA). RESULTS: WTA successfully amplified cDNA from a panel of RNA viruses representing the diversity of ribovirus genome sizes. We amplified a range of genome copy numbers from 15 to 4 x 10(7) using WTA, which yielded quantities of amplified DNA as high as 1.2 microg/microl or 10(10) target copies. The amplification factor varied between 10(9) and 10(6). We also demonstrated that co-amplification occurred when viral RNA was mixed with bacterial DNA. CONCLUSION: This is the first report in the scientific literature showing that a modified WGA (WTA) approach can be successfully applied to viral genomic RNA of all sizes. Amplifying viral RNA by WTA provides considerably better sensitivity and accuracy of detection compared to random RT-PCR.

Exploring DNA quality of single cells for genome analysis with simultaneous whole-genome amplification.

Single cell genome analysis methods are powerful tools to define features of single cells and to identify differences between them. Since the DNA amount of a single cell is very limited, cellular DNA usually needs to be amplified by whole-genome amplification before being subjected to further analysis. A single nucleus only contains two haploid genomes. Thus, any DNA damage that prevents amplification results in loss of damaged DNA sites and induces an amplification bias. Therefore, the assessment of single cell DNA quality is urgently required. As of today, there is no simple method to determine the quality of a single cell DNA in a manner that will still retain the entire cellular DNA for amplification and downstream analysis. Here, we describe a method for whole-genome amplification with simultaneous quality control of single cell DNA by using a competitive spike-in DNA template.

Clonal rolling circle amplification for on-chip DNA cluster generation.

Generation of monoclonal DNA clusters on a surface is a useful method for digital nucleic acid detection applications (e.g. microarray or next-generation sequencing). To obtain sufficient copies per cluster for digital detection, the single molecule bound to the surface must be amplified. Here we describe ClonalRCA, a rolling-circle amplification (RCA) method for the generation of monoclonal DNA clusters based on forward and reverse primers immobilized on the surface. No primer in the reaction buffer is needed. Clusters formed by ClonalRCA comprise forward and reverse strands in multiple copies tethered to the surface within a cluster of micrometer size. Single stranded circular molecules are used as a target to create a cluster with about 10 000 forward and reverse strands. The DNA strands are available for oligonucleotide hybridization, primer extension and sequencing.

Single-Cell Genome and Transcriptome Sequencing Library Construction Using Combination of MDA and Nextera Library Prep Method.

Single-cell analysis gives insights into the heterogeneity of neighboring cells within tissues or within cell populations and is increasing in importance in life science and medicine. Genome and transcriptome sequencing require orders of magnitude of more starting material than what is found in an individual cell. Handling such small quantities means that degradation, sample loss, and contamination can have a pronounced effect on sequence quality and robustness. Recent technical advances in amplification have helped mitigate these challenges. Single-cell sequencing addresses studies of rare cell types, heterogeneous samples, phenotypes associated with mosaicism or variability, and microbes that cannot be cultured. Single-cell sequencing can enable the discovery of clonal mutations, cryptic cell types, or transcriptional features that would be diluted or averaged out in bulk tissue. This unit describes the entire workflow from cells to next-generation sequencing (NGS), including cell lysis, MDA-based whole-genome and whole-transcriptome amplification, and NGS library preparation. © 2016 by John Wiley & Sons, Inc.

Parallel WGA and WTA for Comparative Genome and Transcriptome NGS Analysis Using Tiny Cell Numbers.

Genomic DNA determines how and when the transcriptome is changed by a trigger or environmental change and how cellular metabolism is influenced. Comparative genome and transcriptome analysis of the same cell sample links a defined genome with all changes in the bases, structure, or numbers of the transcriptome. However, comparative genome and transcriptome analysis using next-generation sequencing (NGS) or real-time PCR is often limited by the small amount of sample available. In mammals, the amount of DNA and RNA in a single cell is ∼10 picograms, but deep analysis of the genome and transcriptome currently requires several hundred nanograms of nucleic acids for library preparation for NGS sequencing. Consequently, accurate whole-genome amplification (WGA) and whole-transcriptome amplification (WTA) is required for such quantitative analysis. This unit describes how the genome and the transcriptome of a tiny number of cells can be amplified in a highly parallel and comparable process. Protocols for quality control of amplified DNA and application of amplified DNA for NGS are included.

Whole-Transcriptome Amplification of Single Cells for Next-Generation Sequencing.

Single-cell transcriptome analysis gives insight into the heterogeneity of neighboring cells in tissues or cell cultures. It has been shown that the variability of cells is important for biological function. However, cell variability can be an indication of disease (e.g., cancer). In order to elucidate cell variability in health and disease, single-cell transcriptomes can be analyzed by new next-generation sequencing (NGS) platforms. NGS analysis currently requires a few hundred nanograms of RNA. Consequently, accurate whole-transcriptome amplification is required to analyze the transcriptome of a single cell by NGS. This unit describes the entire workflow from cells to NGS, including cell quality testing, cell lysis, gDNA removal, whole-transcriptome amplification, and NGS library preparation. Recommendations for WTA quality control are given and optional protocols for using purified RNA for WTA and WTA purification are described.

Whole-genome amplification of single-cell genomes for next-generation sequencing.

DNA sequence analysis and genotyping of biological samples using next-generation sequencing (NGS), microarrays, or real-time PCR is often limited by the small amount of sample available. A single cell contains only one to four copies of the genomic DNA, depending on the organism (haploid or diploid organism) and the cell-cycle phase. The DNA content of a single cell ranges from a few femtograms in bacteria to picograms in mammalia. In contrast, a deep analysis of the genome currently requires a few hundred nanograms up to micrograms of genomic DNA for library formation necessary for NGS sequencing or labeling protocols (e.g., microarrays). Consequently, accurate whole-genome amplification (WGA) of single-cell DNA is required for reliable genetic analysis (e.g., NGS) and is particularly important when genomic DNA is limited. The use of single-cell WGA has enabled the analysis of genomic heterogeneity of individual cells (e.g., somatic genomic variation in tumor cells). This unit describes how the genome of single cells can be used for WGA for further genomic studies, such as NGS. Recommendations for isolation of single cells are given and common sources of errors are discussed.