Spatiotemporal Developmental Trajectories in the Arabidopsis Root Revealed Using High-Throughput Single-Cell RNA Sequencing

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High-Throughput Multiplex Sequencing to Discover Copy Number Variants in Drosophila

Copy number variation (CNV) contributes in phenotypically relevant ways to the genetic variability of many organisms. Cost-effective genomewide methods for identifying copy number variation are necessary to elucidate the contribution that these structural variants make to the genomes of model organisms. We have developed a novel approach for the identification of copy number variation by next generation sequencing. As a proof of concept our method has been applied to map the deletions of three Drosophila deficiency strains. We demonstrate that low sequence coverage is sufficient for identifying and mapping large deletions at kilobase resolution, suggesting that data generated from high-throughput sequencing experiments are sufficient for simultaneously analyzing many strains. Genomic DNA from two Drosophila deficiency stocks was barcoded and sequenced in multiplex, and the breakpoints associated with each deletion were successfully identified. The approach we describe is immediately applicable to the systematic exploration of copy number variation in model organisms and humans.STRUCTURAL variation is known to contribute extensively to the genetic variability of humans, mammals, and many model organisms. One class of structural variant, termed copy number variation (CNV), includes deletions, duplications, insertions, and genomic rearrangements which affect the number of occurrences of a specific DNA sequence present in the genome (Redon et al. 2006). CNV is known to occur extensively in the Drosophila genome with functionally significant consequences (Bridges 1936; Dopman and Hartl 2007; Tibshirani and Wang 2008; Zhou et al. 2008). In one study of 15 Drosophila strains, as many as 10% of genes were observed to harbor CNVs (Emerson et al. 2008). Cryptic CNVs that affect the phenotype observed in a model organism have the potential to confound research on multiple levels. For example, a recent report indicates that terminal deletions on chromosome (chr) 2L are frequent among deficiency kit stocks with mutations on the second chromosome and that the associated deletion of lgl has distorted the results of several previous studies (Roegiers et al. 2009). Despite widespread existence of CNV, the biological consequences of this phenomenon remain largely unexplored due to the lack of efficient tools for detection and characterization.Until recently, comparative genomic hybridization with whole-genome tiling arrays (array-CGH) was the primary method for characterizing CNVs (Carter 2007); however, several limitations for this platform reduce its efficacy and efficiency. First, cross-hybridization and reliance on intensity scores lead to data that are difficult to interpret. Second, custom array design and optimization is labor intensive and costly. Third, array-CGH methods can only detect CNV, not other complex rearrangements such as balanced translocations and inversions. Finally, the overall cost of array-CGH methods is relatively high, particularly when high-resolution, whole-genome tiling arrays are employed.Direct sequencing using next-generation technology has several advantages that make it a potentially powerful alternative to array-CGH for identifying genomic structural variations, including deletions, duplications, and rearrangements (Campbell et al. 2008; Chiang et al. 2009). First, high-throughput sequencing methods overcome the inherent limitations of cross-hybridization and provide a digital count of sequence representation. Second, no prior knowledge or design work is necessary. Third, using paired-end sequencing it is possible to identify complex structural variations. Finally, the current cost of CNV discovery by sequencing is comparable or lower than that of array-CGH and is continuing to decline.In this report, we describe a sequencing-based strategy for high-throughput, cost-effective, genomewide characterization of structural variation at fine resolution by employing the Illumina sequencing platform. Deletions in three deficiency fly stocks were successfully characterized and the associated breakpoints were accurately determined. As we demonstrate, high-throughput sequencing provides an ideal and cost-effective platform for CNV characterization.     

Transcriptome Sequencing of Two Phenotypic Mosaic Eucalyptus Trees Reveals Large Scale Transcriptome Re-Modelling

Phenotypic mosaic trees offer an ideal system for studying differential gene expression. We have investigated two mosaic eucalypt trees from two closely related species (Eucalyptus melliodora and E. sideroxylon), which each support two types of leaves: one part of the canopy is resistant to insect herbivory and the remaining leaves are susceptible. Driving this ecological distinction are differences in plant secondary metabolites. We used these phenotypic mosaics to investigate genome wide patterns of foliar gene expression with the aim of identifying patterns of differential gene expression and the somatic mutation(s) that lead to this phenotypic mosaicism. We sequenced the mRNA pool from leaves of the resistant and susceptible ecotypes from both mosaic eucalypts using the Illumina HiSeq 2000 platform. We found large differences in pathway regulation and gene expression between the ecotypes of each mosaic. The expression of the genes in the MVA and MEP pathways is reflected by variation in leaf chemistry, however this is not the case for the terpene synthases. Apart from the terpene biosynthetic pathway, there are several other metabolic pathways that are differentially regulated between the two ecotypes, suggesting there is much more phenotypic diversity than has been described. Despite the close relationship between the two species, they show large differences in the global patterns of gene and pathway regulation.     

Next Generation Sequencing Reveals the Hidden Diversity of Zooplankton Assemblages

Background

Zooplankton play an important role in our oceans, in biogeochemical cycling and providing a food source for commercially important fish larvae. However, difficulties in correctly identifying zooplankton hinder our understanding of their roles in marine ecosystem functioning, and can prevent detection of long term changes in their community structure. The advent of massively parallel next generation sequencing technology allows DNA sequence data to be recovered directly from whole community samples. Here we assess the ability of such sequencing to quantify richness and diversity of a mixed zooplankton assemblage from a productive time series site in the Western English Channel.

Methodology/Principle Findings

Plankton net hauls (200 µm) were taken at the Western Channel Observatory station L4 in September 2010 and January 2011. These samples were analysed by microscopy and metagenetic analysis of the 18S nuclear small subunit ribosomal RNA gene using the 454 pyrosequencing platform. Following quality control a total of 419,041 sequences were obtained for all samples. The sequences clustered into 205 operational taxonomic units using a 97% similarity cut-off. Allocation of taxonomy by comparison with the National Centre for Biotechnology Information database identified 135 OTUs to species level, 11 to genus level and 1 to order, <2.5% of sequences were classified as unknowns. By comparison a skilled microscopic analyst was able to routinely enumerate only 58 taxonomic groups.

Conclusions

Metagenetics reveals a previously hidden taxonomic richness, especially for Copepoda and hard-to-identify meroplankton such as Bivalvia, Gastropoda and Polychaeta. It also reveals rare species and parasites. We conclude that Next Generation Sequencing of 18S amplicons is a powerful tool for elucidating the true diversity and species richness of zooplankton communities. While this approach allows for broad diversity assessments of plankton it may become increasingly attractive in future if sequence reference libraries of accurately identified individuals are better populated.     

High-Throughput Amplicon Sequencing Reveals Distinct Communities within a Corroding Concrete Sewer System

Microbially induced concrete corrosion (MICC) is an important problem in sewers. Here, small-subunit (SSU) rRNA gene amplicon pyrosequencing was used to characterize MICC communities. Microbial community composition differed between wall- and ceiling-associated MICC layers. Acidithiobacillus spp. were present at low abundances, and the communities were dominated by other sulfur-oxidizing-associated lineages.