Dataset Information

Root Hair Sizer: an algorithm for high throughput recovery of different root hair and root developmental parameters.

ABSTRACT: Background:The root is an important organ for water and nutrient uptake, and soil anchorage. It is equipped with root hairs (RHs) which are elongated structures increasing the exchange surface with the soil. RHs are also studied as a model for plant cellular development, as they represent a single cell with specific and highly regulated polarized elongation. For these reasons, it is useful to be able to accurately quantify RH length employing standardized procedures. Methods commonly employed rely on manual steps and are therefore time consuming and prone to errors, restricting analysis to a short segment of the root tip. Few partially automated methods have been reported to increase measurement efficiency. However, none of the reported methods allow an accurate and standardized definition of the position along the root for RH length measurement, making data comparison difficult. Results:We developed an image analysis algorithm that semi-automatically detects RHs and measures their length along the whole differentiation zone of roots. This method, implemented as a simple automated script in ImageJ/Fiji software that we termed Root Hair Sizer, slides a rectangular window along a binarized and straightened image of root tips to estimate the maximal RH length in a given measuring interval. This measure is not affected by heavily bent RHs and any bald spots. RH length data along the root are then modelled with a sigmoidal curve, generating several biologically significant parameters such as RH length, positioning of the root differentiation zone and, under certain conditions, RH growth rate. Conclusions:Image analysis with Root Hair Sizer and subsequent sigmoidal modelling of RH length data provide a simple and efficient way to characterize RH growth in different conditions, equally suitable to small and large scale phenotyping experiments.

SUBMITTER: Guichard M

PROVIDER: S-EPMC6724272 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Root Hair Sizer: an algorithm for high throughput recovery of different root hair and root developmental parameters.

Guichard Marjorie M Allain Jean-Marc JM Wolfe Bianchi Michele M Frachisse Jean-Marie JM

Plant methods 20190904

<h4>Background</h4>The root is an important organ for water and nutrient uptake, and soil anchorage. It is equipped with root hairs (RHs) which are elongated structures increasing the exchange surface with the soil. RHs are also studied as a model for plant cellular development, as they represent a single cell with specific and highly regulated polarized elongation. For these reasons, it is useful to be able to accurately quantify RH length employing standardized procedures. Methods commonly emp ...[more]

PMID: 31507646

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Project description:A single cell RNA sequencing atlas of the Arabidopsis root distinguishes cells both by developmental fate and time, revealing defining expression features that depict a complex cascade of developmental progressions from stem cell through differentiation supported by mirroring waves of transcription factor expression. Methods: mRNA profiles of 6-day-old wild-type (WT) and shortroot-knockout Arabidopsis thaliana roots were generated by deep sequencing of single cell (all) and bulk RNA libraries (wild type only), in duplicate (bulk & wild-type single cell) and singlicate (shr-3), using Illumina NextSeq. The sequence reads that passed quality filters were analyzed at the transcript level. Single Cell libraries were processed and analysed using Cell Ranger, STAR, Seurat. Bulk libraries were processed using Trimmomatic, STAR, HTSeq and DEseq2. Results: For Single Cell - Using an optimized data analysis workflow, we mapped ~87k sequence reads per wild-type cell to the Arabidopsis genome (TAIR10) and identified a median of 4,276 genes and 14,758 transcripts per cell. In total, transcripts for 16,975 genes were detected (RPM ≥1) from wild-type cells. After correction for read depth, this represents ~90% of genes detected by bulk RNA-seq of protoplasted root tissue. Bulk RNA-seq data identified genes induced by protplasting of the Arabidopsis root which could be discounted from single cell analysis. The global gene expression profiles of pooled scRNA-seq and bulk RNA-seq are highly correlated (r = 0.9) indicating that plant scRNA-seq is highly sensitive. Conclusions: Our high-resolution single cell RNA sequencing atlas of the Arabidopsis root captures precise temporal information for all major cell types, revealing new regulators and defining features foreach. Developmental trajectories derived from pseudotime analysis depict a finely resolved cascade of developmental progressions between stem cell and final differentiation supported by mirroring waves of transcription factor expression.

Project description:BACKGROUND: MicroRNAs (miRNAs) are ubiquitous components of endogenous plant transcriptome. miRNAs are small, single-stranded and ~21 nt long RNAs which regulate gene expression at the post-transcriptional level and are known to play essential roles in various aspects of plant development and growth. Previously, a number of miRNAs have been identified in potato through in silico analysis and deep sequencing approach. However, identification of miRNAs through deep sequencing approach was limited to a few tissue types and developmental stages. This study reports the identification and characterization of potato miRNAs in three different vegetative tissues and four stages of tuber development by high throughput sequencing. RESULTS: Small RNA libraries were constructed from leaf, stem, root and four early developmental stages of tuberization and subjected to deep sequencing, followed by bioinformatics analysis. A total of 89 conserved miRNAs (belonging to 33 families), 147 potato-specific miRNAs (with star sequence) and 112 candidate potato-specific miRNAs (without star sequence) were identified. The digital expression profiling based on TPM (Transcripts Per Million) and qRT-PCR analysis of conserved and potato-specific miRNAs revealed that some of the miRNAs showed tissue specific expression (leaf, stem and root) while a few demonstrated tuberization stage-specific expressions. Targets were predicted for identified conserved and potato-specific miRNAs, and predicted targets of four conserved miRNAs, miR160, miR164, miR172 and miR171, which are ARF16 (Auxin Response Factor 16), NAM (NO APICAL MERISTEM), RAP1 (Relative to APETALA2 1) and HAM (HAIRY MERISTEM) respectively, were experimentally validated using 5' RLM-RACE (RNA ligase mediated rapid amplification of cDNA ends). Gene ontology (GO) analysis for potato-specific miRNAs was also performed to predict their potential biological functions. CONCLUSIONS: We report a comprehensive study of potato miRNAs at genome-wide level by high-throughput sequencing and demonstrate that these miRNAs have tissue and/or developmental stage-specific expression profile. Also, predicted targets of conserved miRNAs were experimentally confirmed for the first time in potato. Our findings indicate the existence of extensive and complex small RNA population in this crop and suggest their important role in pathways involved in diverse biological processes, including tuber development.

Dataset Information

Root Hair Sizer: an algorithm for high throughput recovery of different root hair and root developmental parameters.

Publications

Root Hair Sizer: an algorithm for high throughput recovery of different root hair and root developmental parameters.

Similar Datasets

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