Biology subjects

Cook, D.

Publications and source records attributed to Cook, D..

5 recordsLinked to original sources

bioRxiv2018

Domestication and temperature modulate gene expression signatures and growth in the Australasian snapper Chrysophrys auratus

ABSTRACT\n\nIdentifying genes and pathways involved in domestication is critical to understand how species change in response to human-induced selection pressures. We experimentally manipulated temperature conditions for F1-hatchery and wild Australasian snapper (Chrysophrys auratus) for 18 days and measured differences in growth, white muscle RNA transcription and haematological blood parameters. Over 2.2 Gb paired-end reads were assembled de novo for a total set of 33,017 transcripts (N50 = 2,804). We found pronounced growth and gene expression differences between wild and domesticated individuals related to global developmental and immune pathways. Temperature modulated growth responses were linked to major pathways affecting metabolism, cell regulation and signalling. This study is the first step towards gaining an understanding of the changes occurring in the early stages of domestication, and the mechanisms underlying thermal adaptation and associated growth in poikilothermic vertebrates. Our study further provides the first transcriptome resources for studying biological questions in this non-model fish species.

evolutionary biology↗

bioRxiv2018

Effector Gene Reshuffling Involves Dispensable Mini-chromosomes in the Wheat Blast Fungus

Newly emerged wheat blast disease is a serious threat to global wheat production. Wheat blast is caused by a distinct, exceptionally diverse lineage of the fungus causing rice blast disease. To understand genetic diversity in wheat-infecting strains, we report a near-finished reference genome of a recent field isolate generated using long read sequencing and a novel scaffolding approach with long-distance paired genomic sequences. The genome assemblage includes seven core chromosomes and sequences from a dispensable mini-chromosome that harbors effector genes normally found on the ends of core chromosomes in other strains. No mini-chromosomes were observed in an early field strain, and two mini-chromosomes from another field isolate each contain different effector homologous genes and core chromosome end sequences. The mini-chromosome is highly repetitive and is enriched in transposons occurring most frequently at core chromosome ends. Additionally, transposons in mini-chromosomes lack the characteristic signature for inactivation by repeat-induced point (RIP) mutation genome defenses. Our results, collectively, indicate that dispensable mini-chromosomes and non-dispensable core chromosomes undergo divergent evolutionary trajectories, and mini-chromosomes and core chromosome ends are coupled as a mobile, fast-evolving effector compartment in the wheat pathogen genome.\n\nSignificance statementThe emerging blast disease on wheat is proving even harder to control than the ancient, still-problematic rice blast disease. Potential wheat resistance identified using strains isolated soon after disease emergence are no longer effective in controlling recent aggressive field isolates from wheat in South America and South Asia. We report that recent wheat pathogens can contain one or two highly-variable conditionally-dispensable mini-chromosomes, each with an amalgamation of effector sequences that are duplicated or absent from pathogen core chromosome ends. Well-studied effectors found on different core chromosomes in rice pathogens appear side-by-side in wheat pathogen mini-chromosomes. The rice pathogen often overcomes deployed resistance genes by deleting triggering effector genes. Localization of effectors on mini-chromosomes, which are unstably transmitted during growth, would accelerate pathogen adaptation in the field.

genomics↗

bioRxiv2018

plyranges: A grammar of genomic data transformation

The Bioconductor project provides many interoperable data abstractions for analyzing high-throughput genomics experiments; however implementing a typical genomic workflow with Bioconductor requires learning these abstractions and understanding them at an integrative level. This places a large cognitive burden on the user, especially for non-programmers. To reduce this burden we have created a grammar of genomic data transformation that operates on a single, central Bioconductor data structure, GRanges, which naturally represents genomic intervals and their associated measurements. The grammar defines verbs for performing actions on and between genomic interval data through a simplified, coherent interface to existing Bioconductor infrastructure, resulting in fluent analysis workflows. We have implemented this grammar as an R/Bioconductor package called plyranges.

bioinformatics↗

bioRxiv2018

Common loci underlie natural variation in diverse toxin responses

Phenotypic complexity is caused by the contributions of environmental factors and multiple genetic loci, interacting or acting independently. Studies of yeast and Arabidopsis found that the majority of natural variation across phenotypes is attributable to independent additive quantitative trait loci (QTL). Detected loci in these organisms explain most of the estimated heritable variation. By contrast, many heritable components underlying phenotypic variation in metazoan models remain undetected. Before the relative impacts of additive and interactive variance components on metazoan phenotypic variation can be dissected, high replication and precise phenotypic measurements are required to obtain sufficient statistical power to detect loci contributing to this missing heritability. Here, we used a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to detect loci underlying responses to 16 different toxins, including heavy metals, chemotherapeutic drugs, pesticides, and neuropharmaceuticals. Using linkage mapping, we identified 82 QTL that underlie variation in responses to these toxins and predicted the relative contributions of additive loci and genetic interactions across various growth parameters. Additionally, we identified three genomic regions that impact responses to multiple classes of toxins. These QTL hotspots could represent common factors impacting toxin responses. We went further to generate near-isogenic lines and chromosome-substitution strains and then experimentally validated these QTL hotspots, implicating additive and interactive loci that underlie toxin-response variation.

genetics↗

bioRxiv2017

Long Read Annotation (LoReAn): automated eukaryotic genome annotation based on long-read cDNA sequencing

Single-molecule full-length cDNA sequencing can aid genome annotation by revealing transcript structure and alternative splice-forms, yet current annotation pipelines do not incorporate such information. Here we present LoReAn (Long Read Annotation) software, an automated annotation pipeline utilizing short- and long-read cDNA sequencing, protein evidence, and ab initio prediction to generate accurate genome annotations. Based on annotations of two fungal and two plant genomes, we show that LoReAn outperforms popular annotation pipelines by integrating single-molecule cDNA sequencing data generated from either the PacBio or MinION sequencing platforms, and correctly predicting gene structure and capturing genes missed by other annotation pipelines.

bioinformatics↗