A Novel and Fast Approach for Population Structure Inference Using Kernel-PCA and Optimization (PSIKO)

Population structure is a confounding factor in Genome Wide Association Studies, increasing the rate of false positive associations. In order to correct for it, several model-based algorithms such as ADMIXTURE and STRUCTURE have been proposed. These tend to suffer from the fact that they have a considerable computational burden, limiting their applicability when used with large datasets, such as those produced by Next Generation Sequencing (NGS) techniques. To address this, non-model based approaches such as SNMF and EIGENSTRAT have been proposed, which scale better with larger data. Here we present a novel non-model based approach, PSIKO, which is based on a unique combination of linear kernel-PCA and least-squares optimization and allows for the inference of admixture coefficients, principal components, and number of founder populations of a dataset. PSIKO has been compared against existing leading methods on a variety of simulation scenarios, as well as on real biological data. We found that in addition to producing results of the same quality as other tested methods, PSIKO scales extremely well with dataset size, being considerably (up to 30 times) faster for longer sequences than even state of the art methods such as SNMF. PSIKO and accompanying manual are freely available at https://www.uea.ac.uk/computing/psiko

Development of an efficient glucosinolate extraction method

Background: Glucosinolates, anionic sulfur rich secondary metabolites, have been extensively studied because of their occurrence in the agriculturally important brassicaceae and their impact on human and animal health. There is also increasing interest in the biofumigant properties of toxic glucosinolate hydrolysis products as a method to control agricultural pests. Evaluating biofumigation potential requires rapid and accurate quantification of glucosinolates, but current commonly used methods of extraction prior to analysis involve a number of time consuming and hazardous steps; this study aimed to develop an improved method for glucosinolate extraction. Results: Three methods previously used to extract glucosinolates from brassicaceae tissues, namely extraction in cold methanol, extraction in boiling methanol, and extraction in boiling water were compared across tissue type (root, stem leaf ) and four brassicaceae species (B. juncea, S. alba, R. sativus, and E. sativa). Cold methanol extraction was shown to perform as well or better than all other tested methods for extraction of glucosinolates with the exception of glucoraphasatin in R. sativus shoots. It was also demonstrated that lyophilisation methods, routinely used during extraction to allow tissue disruption, can reduce final glucosinolate concentrations and that extracting from frozen wet tissue samples in cold 80% methanol is more effective. Conclusions: We present a simplified method for extracting glucosinolates from plant tissues which does not require the use of a freeze drier or boiling methanol, and is therefore less hazardous, and more time and cost effective. The presented method has been shown to have comparable or improved glucosinolate extraction efficiency relative to the commonly used ISO method for major glucosinolates in the Brassicaceae species studied: sinigrin and gluconasturtiin in B. juncea; sinalbin, glucotropaeolin, and gluconasturtiin in S. alba; glucoraphenin and glucoraphasatin in R. sativus; and glucosatavin, glucoerucin and glucoraphanin in E. sativa

Variation in susceptibility to microbial lignin oxidation in a set of wheat straw cultivars:influence of genetic, seasonal and environmental factors

An alkali lignin preparation from wheat straw was found to be compatible with a previously developed nitrated lignin assay for microbial lignin oxidation, allowing comparison of the susceptibility of different wheat lignins to microbial oxidation. Alkali lignin was prepared from a panel of 18 wheat varieties, and was analysed by FT-IR spectroscopy, revealing minor variations in the lignin structure. Samples of nitrated alkali lignin were assayed against five lignin degrading bacteria: Streptomyces viridosporus, Rhodococcus jostii RHA1, Pseudomonas putida mt-2, Microbacterium phyllosphaerae, and Sphingobacterium sp. T2. Up to 5-fold variation in rates of lignin oxidation were observed between different wheat varieties, and between different bacterial strain, with Sphingobacterium sp. T2 showing consistently highest absorbance changes. Testing of wheat varieties from two consecutive harvests, and from different locations, revealed that the observed variation was due to a ombination of genetic, seasonal and environmental factors, but that some wheat varieties showed consistently higher rates of oxidation. Samples of wheat straw treated with Sphingobacterium sp. T2 were analysed by FT-IR spectroscopy after 7 and 14 days? treatment, showing changes in lignin structure versus time, consistent with lignin breakdown.publishersversionPeer reviewe

Chronic Trichuris muris infection in C57BL/6 mice causes significant changes in most microbiota and metabolome:effects reversed by pathogen clearance

Trichuris species are a globally important and prevalent group of intestinal helminth parasites, in which Trichuris muris (mouse whipworm) is an ideal model for this disease. This paper describes the first ever highly controlled and comprehensive investigation into the effects of T. muris infection on the faecal microbiota of mice and the effects on the microbiota following successful clearance of the infection. Communities were profiled using DGGE, 454 pyrosequencing, and metabolomics. Changes in microbial composition occurred between 14 and 28 days post infection, resulting in significant changes in α and β- diversity. This impact was dominated by a reduction in the diversity and abundance of Bacteroidetes, specifically Prevotella and Parabacteroides. Metabolomic analysis of stool samples of infected mice at day 41 showed significant differences to uninfected controls with a significant increase in the levels of a number of essential amino acids and a reduction in breakdown of dietary plant derived carbohydrates. The significant reduction in weight gain by infected mice probably reflects these metabolic changes and the incomplete digestion of dietary polysaccharides. Following clearance of infection the intestinal microbiota underwent additional changes gradually transitioning by day 91 towards a microbiota of an uninfected animal. These data indicate that the changes in microbiota as a consequence of infection were transitory requiring the presence of the pathogen for maintenance. Interestingly this was not observed for all of the key immune cell populations associated with chronic T. muris infection. This reflects the highly regulated chronic response and potential lasting immunological consequences of dysbiosis in the microbiota. Thus infection of T. muris causes a significant and substantial impact on intestinal microbiota and digestive function of mice with affects in long term immune regulation

Analysing the genetic architecture of clubroot resistance variation in Brassica napus by associative transcriptomics

Clubroot is a destructive soil-borne pathogen of Brassicaceae that causes significant recurrent reductions in yield of cruciferous crops. Although there is some resistance in oilseed rape (a crop type of the species Brassica napus), the genetic basis of that resistance is poorly understood. In this study, we used an associative transcriptomics approach to elucidate the genetic basis of resistance to clubroot pathotype ECD 17/31/31 across a genetic diversity panel of 245 accessions of B. napus. A single nucleotide polymorphism (SNP) association analysis was performed with 256,397 SNPs distributed across the genome of B. napus and combined with transcript abundance data of 53,889 coding DNA sequence (CDS) gene models. The SNP association analysis identified two major loci (on chromosomes A2 and A3) controlling resistance and seven minor loci. Within these were a total of 86 SNP markers. Altogether, 392 genes were found in these regions. Another 21 genes were implicated as potentially involved in resistance using gene expression marker (GEM) analysis. After GO enrichment analysis and InterPro functional analysis of the identified genes, 82 candidate genes were identified as having roles in clubroot resistance. These results provide useful information for marker-assisted breeding which could lead to acceleration of pyramiding of multiple clubroot resistance genes in new varieties