AA9int: SNP interaction pattern search using non-hierarchical additive model set.

MOTIVATION: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. RESULTS: We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. AVAILABILITY AND IMPLEMENTATION: The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns.

MOTIVATION: Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. RESULTS: We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. AVAILABILITY AND IMPLEMENTATION: The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ . CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.This study was supported by the National Cancer Institute (R01CA128813, PI: Park, JY and R21CA202417, PI: Lin, HY)

Biochar increases soil organic carbon, avocado yields and economic return over 4 years of cultivation

© 2020 Elsevier B.V. The use of biochar in avocado orchard soils has not yet been investigated in rigorous scientific experiments. We determine the effect of wood biochar on avocado growth, fruit production and economic benefit. Biochar was applied at 0%, 5%, 10% and 20% volume by volume basis. Biochar significantly improved the growth of avocado seedlings and increased fruit yield in the first three years after planting. There was an overall increase in soil carbon, fruit yield, tree diameter and height in all biochar treatments relative to the control over the seasons. Trees planted with biochar had 18–26% greater growth rates (in terms of height and stem diameter) than the control. Tree diameter was significantly greater with biochar (145.4 ± 3.3 mm) relative to the control treatment (125.0 ± 2.7 mm). Tree height was also significantly greater with biochar (3.7 ± 0.1 m) relative to the control treatment (3.4 ± 0.1 m). The fruit count from the biochar row was significantly greater (97%) in 2018. Heavy bearing trees typically have a lower yield in the subsequent year but despite this, the 2019 fruit counts were higher in aggregate for the biochar amended trees (20%) relative to the control. A cost-benefit analysis indicated that if yield surplus of fruit trees continued for three years, and assuming avocado prices remain at similar levels, then the discounted net benefit over a hectare would amount to US$8581, or US$105 per metric tonne of biochar applied

Revue médicale de Louvain

Addition of biochar produced through thermal decomposition of biomass has been seen as a strategy to improve soils and to sequester carbon (C), but wide scale implementation of the technology requires to devise innovative profitable solutions. To develop biochar utilisation with an integrated system approach, an innovative program was implemented in 2012 on a 53-ha farm in Western Australia to determine the costs and benefits of integrating biochar with animal husbandry and improvement of pastures. Biochar was mixed with molasses and fed directly to cows. The dung-biochar mixture was incorporated into the soil profile by dung beetles. We studied the changes in soil properties over 3 years. Biochar extracted from fresh dung and from the soil to a depth of 40 cm was characterised. A preliminary financial analysis of the costs and benefits of this integrated approach was also undertaken. The preliminary investigation results suggested that this strategy was effective in improving soil properties and increasing returns to the farmer. It was also concluded that the biochar adsorbed nutrients from the cow's gut and from the dung. Dung beetles could transport this nutrient-rich biochar into the soil profile. There was little evidence that the recalcitrant component of the biochar was reduced through reactions inside the gut or on/in the soil. Further research is required to quantify the long-term impact of integrating biochar and dung beetles into the rearing of cows