256 research outputs found

    The Formworker

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    Timescales of glacial isostatic adjustment in Greenland: is transient rheology required?

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    The possibility of a transient rheological response to ice age loading, first discussed in the literature of the 1980s, has received renewed attention. Transient behaviour across centennial to millennial timescales has been invoked to reconcile apparently contradictory inferences of steady-state (Maxwell) viscosity based on two distinct data sets from Greenland: Holocene sea-level curves and Global Navigation Satellite System (GNSS) derived modern crustal uplift data. To revisit this issue, we first compute depth-dependent Fréchet kernels using 1-D Maxwell viscoelastic Earth models and demonstrate that the mantle resolving power of the two Greenland data sets is highly distinct, reflecting the differing spatial scale of the associated surface loading: the sea-level records are sensitive to viscosity structure across the entire upper mantle while uplift rates associated with post-1000 CE fluctuations of the Greenland Ice Sheet have a dominant sensitivity to shallow asthenosphere viscosity. Guided by these results, we present forward models which demonstrate that a moderate low viscosity zone beneath the lithosphere in Maxwell Earth models provides a simple route to simultaneously reconciling both data sets by significantly increasing predictions of present-day uplift rates in Greenland whilst having negligible impact on predictions of Holocene relative sea-level curves from the region. Our analysis does not rule out the possibility of transient deformation, but it suggests that it is not required to simultaneously explain these two data sets. A definitive demonstration of transient behaviour requires that one account for the resolving power of the data sets in modelling the glacial isostatic adjustment process

    EORNA, a barley gene and transcript abundance database

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    A high-quality, barley gene reference transcript dataset (BaRTv1.0), was used to quantify gene and transcript abundances from 22 RNA-seq experiments, covering 843 separate samples. Using the abundance data we developed a Barley Expression Database (EORNA*) to underpin a visualisation tool that displays comparative gene and transcript abundance data on demand as transcripts per million (TPM) across all samples and all the genes. EORNA provides gene and transcript models for all of the transcripts contained in BaRTV1.0, and these can be conveniently identified through either BaRT or HORVU gene names, or by direct BLAST of query sequences. Browsing the quantification data reveals cultivar, tissue and condition specific gene expression and shows changes in the proportions of individual transcripts that have arisen via alternative splicing. TPM values can be easily extracted to allow users to determine the statistical significance of observed transcript abundance variation among samples or perform meta analyses on multiple RNA-seq experiments. * Eòrna is the Scottish Gaelic word for Barley.</p

    An ultra-high density genetic linkage map of perennial ryegrass (Lolium perenne) using genotyping by sequencing (GBS) based on a reference shotgun genome assembly

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    Background and Aims High density genetic linkage maps that are extensively anchored to assembled genome sequences of the organism in question are extremely useful in gene discovery. To facilitate this process in perennial ryegrass (Lolium perenne L.), a high density single nucleotide polymorphism (SNP)- and presence/absence variant (PAV)-based genetic linkage map has been developed in an F(2) mapping population that has been used as a reference population in numerous studies. To provide a reference sequence to which to align genotyping by sequencing (GBS) reads, a shotgun assembly of one of the grandparents of the population, a tenth-generation inbred line, was created using Illumina-based sequencing. Methods The assembly was based on paired-end Illumina reads, scaffolded by mate pair and long jumping distance reads in the range of 3–40 kb, with >200-fold initial genome coverage. A total of 169 individuals from an F(2) mapping population were used to construct PstI-based GBS libraries tagged with unique 4–9 nucleotide barcodes, resulting in 284 million reads, with approx. 1·6 million reads per individual. A bioinformatics pipeline was employed to identify both SNPs and PAVs. A core genetic map was generated using high confidence SNPs, to which lower confidence SNPs and PAVs were subsequently fitted in a straightforward binning approach. Key Results The assembly comprises 424 750 scaffolds, covering 1·11 Gbp of the 2·5 Gbp perennial ryegrass genome, with a scaffold N50 of 25 212 bp and a contig N50 of 3790 bp. It is available for download, and access to a genome browser has been provided. Comparison of the assembly with available transcript and gene model data sets for perennial ryegrass indicates that approx. 570 Mbp of the gene-rich portion of the genome has been captured. An ultra-high density genetic linkage map with 3092 SNPs and 7260 PAVs was developed, anchoring just over 200 Mb of the reference assembly. Conclusions The combined genetic map and assembly, combined with another recently released genome assembly, represent a significant resource for the perennial ryegrass genetics community

    A Genome Assembly of the Barley 'Transformation Reference' Cultivar Golden Promise

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    Barley (Hordeum vulgare) is one of the most important crops worldwide and is also considered a research model for the large-genome small grain temperate cereals. Despite genomic resources improving all the time, they are limited for the cv. Golden Promise, the most efficient genotype for genetic transformation. We have developed a barley cv. Golden Promise reference assembly integrating Illumina paired-end reads, long mate-pair reads, Dovetail Chicago in vitro proximity ligation libraries and chromosome conformation capture sequencing (Hi-C) libraries into a contiguous reference assembly. The assembled genome of 7 chromosomes and 4.13Gb in size, has a super-scaffold N50 after Chicago libraries of 4.14Mb and contains only 2.2% gaps. Using BUSCO (benchmarking universal single copy orthologous genes) as evaluation the genome assembly contains 95.2% of complete and single copy genes from the plant database. A high-quality Golden Promise reference assembly will be useful and utilized by the whole barley research community but will prove particularly useful for CRISPR-Cas9 experiments

    The dynamics of transcript abundance during cellularization of developing barley endosperm

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    Within the cereal grain, the endosperm and its nutrient reserves are critical for successful germination and in the context of grain utilization. The identification of molecular determinants of early endosperm development, particularly regulators of cell division and cell wall deposition, would help predict end-use properties such as yield, quality, and nutritional value. Custom microarray data have been generated using RNA isolated from developing barley grain endosperm 3 d to 8 d after pollination (DAP). Comparisons of transcript abundance over time revealed 47 gene expression modules that can be clustered into 10 broad groups. Superimposing these modules upon cytological data allowed patterns of transcript abundance to be linked with key stages of early grain development. Here, attention was focused on how the datasets could be mined to explore and define the processes of cell wall biosynthesis, remodeling, and degradation. Using a combination of spatial molecular network and gene ontology enrichment analyses, it is shown that genes involved in cell wall metabolism are found in multiple modules, but cluster into two main groups that exhibit peak expression at 3 DAP to 4 DAP and 5 DAP to 8 DAP. The presence of transcription factor genes in these modules allowed candidate genes for the control of wall metabolism during early barley grain development to be identified. The data are publicly available through a dedicated web interface (https://ics.hutton.ac.uk/barseed/), where they can be used to interrogate co- and differential expression for any other genes, groups of genes, or transcription factors expressed during early endosperm development.Runxuan Zhang, Matthew R. Tucker, Rachel A Burton, Neil J. Shirley, Alan Little, Jenny Morris, Linda Milne, Kelly Houston, Pete E. Hedley, Robbie Waugh, and Geoffrey B. Finche
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