James Breen

Megabase Level Sequencing Reveals Contrasted Organization and Evolution Patterns of the Wheat Gene and Transposable Element Spaces

This article describes the molecular analysis of large contiguous sequences produced from the bread wheat genome. It provides novel insights into the number, distribution, and density of genes along chromosome 3B and reveals an unexpectedly high amount of noncollinear genes compared to model grass genomes. To improve our understanding of the organization and evolution of the wheat (Triticum aestivum) genome, we sequenced and annotated 13-Mb contigs (18.2 Mb) originating from different regions of its largest chromosome, 3B (1 Gb), and produced a 2x chromosome survey by shotgun Illumina/Solexa sequencing. All regions carried genes irrespective of their chromosomal location. However, gene distribution was not random, with 75% of them clustered into small islands containing three genes on average. A twofold increase of gene density was observed toward the telomeres likely due to high tandem and interchromosomal duplication events. A total of 3222 transposable elements were identified, including 800 new families. Most of them are complete but showed a highly nested structure spread over distances as large as 200 kb. A succession of amplification waves involving different transposable element families led to contrasted sequence compositions between the proximal and distal regions. Finally, with an estimate of 50,000 genes per diploid genome, our data suggest that wheat may have a higher gene number than other cereals. Indeed, comparisons with rice (Oryza sativa) and Brachypodium revealed that a high number of additional noncollinear genes are interspersed within a highly conserved ancestral grass gene backbone, supporting the idea of an accelerated evolution in the Triticeae lineages.

An accurate DNA marker assay for stem rust resistance gene Sr2 in wheat

The stem rust resistance gene Sr2 has provided broad-spectrum protection against stem rust (Pucciniagraminis Pers. f. sp. tritici) since its wide spread deployment in wheat from the 1940s. Because Sr2 confers partial resistance which is difficult to select under field conditions, a DNA marker is desirable that accurately predicts Sr2 in diverse wheat germplasm. Using DNA sequence derived from the vicinity of the Sr2 locus, we developed a cleaved amplified polymorphic sequence (CAPS) marker that is associated with the presence or absence of the gene in 115 of 122 (95%) diverse wheat lines. The marker genotype predicted the absence of the gene in 100% of lines which were considered to lack Sr2. Discrepancies were observed in lines that were predicted to carry Sr2 but failed to show the CAPS marker. Given the high level of accuracy observed, the marker provides breeders with a selection tool for one of the most important disease resistance genes of wheat.

The maize disease resistance gene Htn1 against northern corn leaf blight encodes a wall-associated receptor-like kinase

Significance Northern corn leaf blight (NCLB) is one of the most devastating fungal diseases of maize. The Htn1 disease resistance gene confers quantitative field resistance against most NCLB isolates. Here we show that Htn1 encodes a putative wall-associated receptor-like kinase (RLK). RLKs act as important components of the first tier of the plant innate immune system by perceiving pathogen- or host-derived elicitors on the cell surface. RLKs are often associated with resistance to nonadapted pathogens and are a component of nonhost resistance. Our work demonstrates that the Htn1-RLK plays an important role in host resistance against adapted fungal pathogens. Northern corn leaf blight (NCLB) caused by the hemibiotrophic fungus Exserohilum turcicum is an important foliar disease of maize that is mainly controlled by growing resistant maize cultivars. The Htn1 locus confers quantitative and partial NCLB resistance by delaying the onset of lesion formation. Htn1 represents an important source of genetic resistance that was originally introduced from a Mexican landrace into modern maize breeding lines in the 1970s. Using a high-resolution map-based cloning approach, we delimited Htn1 to a 131.7-kb physical interval on chromosome 8 that contained three candidate genes encoding two wall-associated receptor-like kinases (ZmWAK-RLK1 and ZmWAK-RLK2) and one wall-associated receptor-like protein (ZmWAK-RLP1). TILLING (targeting induced local lesions in genomes) mutants in ZmWAK-RLK1 were more susceptible to NCLB than wild-type plants, both in greenhouse experiments and in the field. ZmWAK-RLK1 contains a nonarginine-aspartate (non-RD) kinase domain, typically found in plant innate immune receptors. Sequence comparison showed that the extracellular domain of ZmWAK-RLK1 is highly diverse between different maize genotypes. Furthermore, an alternative splice variant resulting in a truncated protein was present at higher frequency in the susceptible parents of the mapping populations compared with in the resistant parents. Hence, the quantitative Htn1 disease resistance in maize is encoded by an unusual innate immune receptor with an extracellular wall-associated kinase domain. These results further highlight the importance of this protein family in resistance to adapted pathogens.

Neanderthal behaviour, diet, and disease inferred from ancient DNA in dental calculus

Recent genomic data have revealed multiple interactions between Neanderthals and modern humans, but there is currently little genetic evidence regarding Neanderthal behaviour, diet, or disease. Here we describe the shotgun-sequencing of ancient DNA from five specimens of Neanderthal calcified dental plaque (calculus) and the characterization of regional differences in Neanderthal ecology. At Spy cave, Belgium, Neanderthal diet was heavily meat based and included woolly rhinoceros and wild sheep (mouflon), characteristic of a steppe environment. In contrast, no meat was detected in the diet of Neanderthals from El Sidrón cave, Spain, and dietary components of mushrooms, pine nuts, and moss reflected forest gathering. Differences in diet were also linked to an overall shift in the oral bacterial community (microbiota) and suggested that meat consumption contributed to substantial variation within Neanderthal microbiota. Evidence for self-medication was detected in an El Sidrón Neanderthal with a dental abscess and a chronic gastrointestinal pathogen (Enterocytozoon bieneusi). Metagenomic data from this individual also contained a nearly complete genome of the archaeal commensal Methanobrevibacter oralis (10.2× depth of coverage)—the oldest draft microbial genome generated to date, at around 48,000 years old. DNA preserved within dental calculus represents a notable source of information about the behaviour and health of ancient hominin specimens, as well as a unique system that is useful for the study of long-term microbial evolution.

A multiple resistance locus on chromosome arm 3BS in wheat confers resistance to stem rust (Sr2), leaf rust (Lr27) and powdery mildew

Sr2 is the only known durable, race non-specific adult plant stem rust resistance gene in wheat. The Sr2 gene was shown to be tightly linked to the leaf rust resistance gene Lr27 and to powdery mildew resistance. An analysis of recombinants and mutants suggests that a single gene on chromosome arm 3BS may be responsible for resistance to these three fungal pathogens. The resistance functions of the Sr2 locus are compared and contrasted with those of the adult plant resistance gene Lr34.

Germin-like proteins (GLPs) in cereal genomes: gene clustering and dynamic roles in plant defence.

The recent release of the genome sequences of a number of crop and model plant species has made it possible to define the genome organisation and functional characteristics of specific genes and gene families of agronomic importance. For instance, Sorghum bicolor, maize (Zea mays) and Brachypodium distachyon genome sequences along with the model grass species rice (Oryza sativa) enable the comparative analysis of genes involved in plant defence. Germin-like proteins (GLPs) are a small, functionally and taxonomically diverse class of cupin-domain containing proteins that have recently been shown to cluster in an area of rice chromosome 8. The genomic location of this gene cluster overlaps with a disease resistance QTL that provides defence against two rice fungal pathogens (Magnaporthe oryzae and Rhizoctonia solani). Studies showing the involvement of GLPs in basal host resistance against powdery mildew (Blumeria graminis ssp.) have also been reported in barley and wheat. In this mini-review, we compare the close proximity of GLPs in publicly available cereal crop genomes and discuss the contribution that these proteins, and their genome sequence organisation, play in plant defence.

A Physical Map of the Short Arm of Wheat Chromosome 1A

Bread wheat (Triticum aestivum) has a large and highly repetitive genome which poses major technical challenges for its study. To aid map-based cloning and future genome sequencing projects, we constructed a BAC-based physical map of the short arm of wheat chromosome 1A (1AS). From the assembly of 25,918 high information content (HICF) fingerprints from a 1AS-specific BAC library, 715 physical contigs were produced that cover almost 99% of the estimated size of the chromosome arm. The 3,414 BAC clones constituting the minimum tiling path were end-sequenced. Using a gene microarray containing ∼40 K NCBI UniGene EST clusters, PCR marker screening and BAC end sequences, we arranged 160 physical contigs (97 Mb or 35.3% of the chromosome arm) in a virtual order based on synteny with Brachypodium, rice and sorghum. BAC end sequences and information from microarray hybridisation was used to anchor 3.8 Mbp of Illumina sequences from flow-sorted chromosome 1AS to BAC contigs. Comparison of genetic and synteny-based physical maps indicated that ∼50% of all genetic recombination is confined to 14% of the physical length of the chromosome arm in the distal region. The 1AS physical map provides a framework for future genetic mapping projects as well as the basis for complete sequencing of chromosome arm 1AS.

Predicting the origin of soil evidence: High throughput eukaryote sequencing and MIR spectroscopy applied to a crime scene scenario.

Soil can serve as powerful trace evidence in forensic casework, because it is highly individualistic and can be characterised using a number of techniques. Complex soil matrixes can support a vast number of organisms that can provide a site-specific signal for use in forensic soil discrimination. Previous DNA fingerprinting techniques rely on variations in fragment length to distinguish between soil profiles and focus solely on microbial communities. However, the recent development of high throughput sequencing (HTS) has the potential to provide a more detailed picture of the soil community by accessing non-culturable microorganisms and by identifying specific bacteria, fungi, and plants within soil. To demonstrate the application of HTS to forensic soil analysis, 18S ribosomal RNA profiles of six forensic mock crime scene samples were compared to those collected from seven reference locations across South Australia. Our results demonstrate the utility of non-bacterial DNA to discriminate between different sites, and were able to link a soil to a particular location. In addition, HTS complemented traditional Mid Infrared (MIR) spectroscopy soil profiling, but was able to provide statistically stronger discriminatory power at a finer scale. Through the design of an experimental case scenario, we highlight the considerations and potential limitations of this method in forensic casework. We show that HTS analysis of soil eukaryotes was robust to environmental variation, e.g. rainfall and temperature, transfer effects, storage effects and spatial variation. In addition, this study utilises novel analytical methodologies to interpret results for investigative purposes and provides prediction statistics to support soil DNA analysis for evidential stages of a case.

Wheat genome structure and function: genome sequence data and the International Wheat Genome Sequencing Consortium

Genome sequencing and the associated bioinformatics is now a widely accepted research tool for accelerating genetic research and the analysis of genome structure and function of wheat because it leverages similar work from other crops and plants. The International Wheat Genome Sequencing Consortium addresses the challenge of wheat genome structure and function and builds on the research efforts of Professor Bob McIntosh in the genetics of wheat. Currently, expressed sequence tags (ESTs; ∼500 000 to date) are the largest sequence resource for wheat genome analyses. It is estimated that the gene coverage of the wheat EST collection is ∼60%, close to that of Arabidopsis, indicating that ∼40% of wheat genes are not represented in EST collections. The physical map of the D-genome donor species Aegilops tauschii is under construction (http://wheat.pw.usda.gov/PhysicalMapping). The technologies developed in this analysis of the D genome provide a good model for the approach to the entire wheat genome, namely compiling BAC contigs, assigning these BAC contigs to addresses in a high resolution genetic map, filling in gaps to obtain the entire physical length of a chromosome, and then large-scale sequencing.

Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation

Aim: To determine whether dynamic DNA methylation changes in the human placenta can be used to predict gestational age. Materials & methods: Publicly available placental DNA methylation data from 12 studies, together with our own dataset, using Illumina Infinium Human Methylation BeadChip arrays. Results & conclusion: We developed an accurate tool for predicting gestational age of placentas using 62 CpG sites. There was a higher predicted gestational age for placentas from early onset preeclampsia cases, but not term preeclampsia, compared with their chronological age. Therefore, early onset preeclampsia is associated with placental aging. Gestational age acceleration prediction from DNA methylation array data may provide insight into the molecular mechanisms of pregnancy disorders.