Keith J. Edwards

Bio: Keith J. Edwards is an academic researcher from University of Bristol. The author has contributed to research in topics: Population & Microsatellite. The author has an hindex of 63, co-authored 168 publications receiving 19087 citations. Previous affiliations of Keith J. Edwards include University of Sheffield & University of Hertfordshire.

A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.)

Abstract: A microsatellite consensus map was constructed by joining four independent genetic maps of bread wheat. Three of the maps were F1-derived, doubled-haploid line populations and the fourth population was ‘Synthetic’ × ‘Opata’, an F6-derived, recombinant-inbred line population. Microsatellite markers from different research groups including the Wheat Microsatellite Consortium, GWM, GDM, CFA, CFD, and BARC were used in the mapping. A sufficient number of common loci between genetic maps, ranging from 52 to 232 loci, were mapped on different populations to facilitate joining the maps. Four genetic maps were developed using MapMaker V3.0 and JoinMap V3.0. The software CMap, a comparative map viewer, was used to align the four maps and identify potential errors based on consensus. JoinMap V3.0 was used to calculate marker order and recombination distances based on the consensus of the four maps. A total of 1,235 microsatellite loci were mapped, covering 2,569 cM, giving an average interval distance of 2.2 cM. This consensus map represents the highest-density public microsatellite map of wheat and is accompanied by an allele database showing the parent allele sizes for every marker mapped. This enables users to predict allele sizes in new breeding populations and develop molecular breeding and genomics strategies.

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

Abstract: High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90,000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence-absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

Nested Retrotransposons in the Intergenic Regions of the Maize Genome

Abstract: The relative organization of genes and repetitive DNAs in complex eukaryotic genomes is not well understood. Diagnostic sequencing indicated that a 280-kilobase region containing the maize Adh1-F and u22 genes is composed primarily of retrotransposons inserted within each other. Ten retroelement families were discovered, with reiteration frequencies ranging from 10 to 30,000 copies per haploid genome. These retrotransposons accounted for more than 60 percent of the Adh1-F region and at least 50 percent of the nuclear DNA of maize. These elements were largely intact and are dispersed throughout the gene-containing regions of the maize genome.

Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models.

Abstract: The rate at which nonsynonymous single nucleotide polymorphisms (nsSNPs) are being identified in the human genome is increasing dramatically owing to advances in whole-genome/whole-exome sequencing technologies. Automated methods capable of accurately and reliably distinguishing between pathogenic and functionally neutral nsSNPs are therefore assuming ever-increasing importance. Here, we describe the Functional Analysis Through Hidden Markov Models (FATHMM) software and server: a species-independent method with optional species-specific weightings for the prediction of the functional effects of protein missense variants. Using a model weighted for human mutations, we obtained performance accuracies that outperformed traditional prediction methods (i.e., SIFT, PolyPhen, and PANTHER) on two separate benchmarks. Furthermore, in one benchmark, we achieve performance accuracies that outperform current state-of-the-art prediction methods (i.e., SNPs&GO and MutPred). We demonstrate that FATHMM can be efficiently applied to high-throughput/large-scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations. To illustrate this, we evaluated nsSNPs in wheat (Triticum spp.) to identify some of the important genetic variants responsible for the phenotypic differences introduced by intense selection during domestication. A Web-based implementation of FATHMM, including a high-throughput batch facility and a downloadable standalone package, is available at http://fathmm.biocompute.org.uk.

Analysis of the bread wheat genome using whole-genome shotgun sequencing

Abstract: Bread wheat (Triticum aestivum) is a globally important crop, accounting for 20 per cent of the calories consumed by humans. Major efforts are underway worldwide to increase wheat production by extending genetic diversity and analysing key traits, and genomic resources can accelerate progress. But so far the very large size and polyploid complexity of the bread wheat genome have been substantial barriers to genome analysis. Here we report the sequencing of its large, 17-gigabase-pair, hexaploid genome using 454 pyrosequencing, and comparison of this with the sequences of diploid ancestral and progenitor genomes. We identified between 94,000 and 96,000 genes, and assigned two-thirds to the three component genomes (A, B and D) of hexaploid wheat. High-resolution synteny maps identified many small disruptions to conserved gene order. We show that the hexaploid genome is highly dynamic, with significant loss of gene family members on polyploidization and domestication, and an abundance of gene fragments. Several classes of genes involved in energy harvesting, metabolism and growth are among expanded gene families that could be associated with crop productivity. Our analyses, coupled with the identification of extensive genetic variation, provide a resource for accelerating gene discovery and improving this major crop.

Analysis of the genome sequence of the flowering plant Arabidopsis thaliana.

Abstract: The flowering plant Arabidopsis thaliana is an important model system for identifying genes and determining their functions. Here we report the analysis of the genomic sequence of Arabidopsis. The sequenced regions cover 115.4 megabases of the 125-megabase genome and extend into centromeric regions. The evolution of Arabidopsis involved a whole-genome duplication, followed by subsequent gene loss and extensive local gene duplications, giving rise to a dynamic genome enriched by lateral gene transfer from a cyanobacterial-like ancestor of the plastid. The genome contains 25,498 genes encoding proteins from 11,000 families, similar to the functional diversity of Drosophila and Caenorhabditis elegans--the other sequenced multicellular eukaryotes. Arabidopsis has many families of new proteins but also lacks several common protein families, indicating that the sets of common proteins have undergone differential expansion and contraction in the three multicellular eukaryotes. This is the first complete genome sequence of a plant and provides the foundations for more comprehensive comparison of conserved processes in all eukaryotes, identifying a wide range of plant-specific gene functions and establishing rapid systematic ways to identify genes for crop improvement.

The Ensembl Variant Effect Predictor.

Abstract: The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

The B73 Maize Genome: Complexity, Diversity, and Dynamics

Abstract: We report an improved draft nucleotide sequence of the 2.3-gigabase genome of maize, an important crop plant and model for biological research. Over 32,000 genes were predicted, of which 99.8% were placed on reference chromosomes. Nearly 85% of the genome is composed of hundreds of families of transposable elements, dispersed nonuniformly across the genome. These were responsible for the capture and amplification of numerous gene fragments and affect the composition, sizes, and positions of centromeres. We also report on the correlation of methylation-poor regions with Mu transposon insertions and recombination, and copy number variants with insertions and/or deletions, as well as how uneven gene losses between duplicated regions were involved in returning an ancient allotetraploid to a genetically diploid state. These analyses inform and set the stage for further investigations to improve our understanding of the domestication and agricultural improvements of maize.

DNA methylation landscapes: provocative insights from epigenomics

Abstract: The genomes of many animals, plants and fungi are tagged by methylation of DNA cytosine. To understand the biological significance of this epigenetic mark it is essential to know where in the genome it is located. New techniques are making it easier to map DNA methylation patterns on a large scale and the results have already provided surprises. In particular, the conventional view that DNA methylation functions predominantly to irreversibly silence transcription is being challenged. Not only is promoter methylation often highly dynamic during development, but many organisms also seem to target DNA methylation specifically to the bodies of active genes.

Ribosomal DNA: molecular evolution and phylogenetic inference.

Abstract: Ribosomal DNA (rDNA) sequences have been aligned and compared in a number of living organisms, and this approach has provided a wealth of information about phylogenetic relationships. Studies of rDNA sequences have been used to infer phylogenetic history across a very broad spectrum, from studies among the basal lineages of life to relationships among closely related species and populations. The reasons for the systematic versatility of rDNA include the numerous rates of evolution among different regions of rDNA (both among and within genes), the presence of many copies of most rDNA sequences per genome, and the pattern of concerted evolution that occurs among repeated copies. These features facilitate the analysis of rDNA by direct RNA sequencing, DNA sequencing (either by cloning or amplification), and restriction enzyme methodologies. Constraints imposed by secondary structure of rRNA and concerted evolution need to be considered in phylogenetic analyses, but these constraints do not appear to impede seriously the usefulness of rDNA. An analysis of aligned sequences of the four nuclear and two mitochondrial rRNA genes identified regions of these genes that are likely to be useful to address phylogenetic problems over a wide range of levels of divergence. In general, the small subunit nuclear sequences appear to be best for elucidating Precambrian divergences, the large subunit nuclear sequences for Paleozoic and Mesozoic divergences, and the organellar sequences of both subunits for Cenozoic divergences. Primer sequences were designed for use in amplifying the entire nuclear rDNA array in 15 sections by use of the polymerase chain reaction; these "universal" primers complement previously described primers for the mitochondrial rRNA genes. Pairs of primers can be selected in conjunction with the analysis of divergence of the rRNA genes to address systematic problems throughout the hierarchy of life.