In recent years, the use of genomic information in livestock species for genetic improvement, association studies and many other fields has become routine. In order to accommodate different market requirements in terms of genotyping cost, manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species: ranging from one for goats to more than ten for cattle, and the number of arrays available is increasing rapidly. However, there is limited or no effort to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. past and current assemblies) SNP information. Here we present SNPchiMp v.3, a solution to these issues for the six major livestock species (cow, pig, horse, sheep, goat and chicken). Original data was collected directly from SNP array producers and specific international genome consortia, and stored in a MySQL database. The database was then linked to an open-access web tool and to public databases. SNPchiMp v.3 ensures fast access to the database (retrieving within/across SNP array data) and the possibility of annotating SNP array data in a user-friendly fashion. This platform allows easy integration and standardization, and it is aimed at both industry and research. It also enables users to easily link the information available from the array producer with data in public databases, without the need of additional bioinformatics tools or pipelines. In recognition of the open-access use of Ensembl resources, SNPchiMp v.3 was officially credited as an Ensembl E!mpowered tool. Availability at http://bioinformatics.tecnoparco.org/SNPchimp.

In this study we carried out a genome-wide association analysis for plant and grain morphology and root architecture in a unique panel of temperate rice accessions adapted to European pedo-climatic conditions. This is the first study to assess the association of selected phenotypic traits to specific genomic regions in the narrow genetic pool of temperate japonica. A set of 391 rice accessions were GBS-genotyped yielding—after data editing—57000 polymorphic and informative SNPS, among which 54% were in genic regions. In total, 42 significant genotype-phenotype associations were detected: 21 for plant morphology traits, 11 for grain quality traits, 10 for root architecture traits. The FDR of detected associations ranged from 3 · 10⁻⁷ to 0.92 (median: 0.25). In most cases, the significant detected associations co-localised with QTLs and candidate genes controlling the phenotypic variation of single or multiple traits. The most significant associations were those for flag leaf width on chromosome 4 (FDR = 3 · 10⁻⁷) and for plant height on chromosome 6 (FDR = 0.011). We demonstrate the effectiveness and resolution of the developed platform for high-throughput phenotyping, genotyping and GWAS in detecting major QTLs for relevant traits in rice. We identified strong associations that may be used for selection in temperate irrigated rice breeding: e.g. associations for flag leaf width, plant height, root volume and length, grain length, grain width and their ratio. Our findings pave the way to successfully exploit the narrow genetic pool of European temperate rice and to pinpoint the most relevant genetic components contributing to the adaptability and high yield of this germplasm. The generated data could be of direct use in genomic-assisted breeding strategies.

Microbial communities associated with plants are greatly influenced by water availability in soil. In flooded crops, such as rice, the impact of water management on microbial dynamics is not fully understood. Here, we present a comprehensive study of the rice microbiota investigated in an experimental field located in one of the most productive areas of northern Italy. The microbiota associated with paddy soil and root was investigated using 454 pyrosequencing of 16S, ITS and 18S rRNA gene amplicons under two different water managements, upland (non-flooded, aerobic) and lowland (traditional flooding, anaerobic), at three plant development stages. Results highlighted a major role of the soil water status in shaping microbial communities, while phenological stage had low impacts. Compositional shifts in prokaryotic and fungal communities upon water management consisted in significant abundance changes of Firmicutes, Methanobacteria, Chloroflexi, Sordariomycetes, Dothideomycetes and Glomeromycotina. A vicariance in plant beneficial microbes and between saprotrophs and pathotrophs was observed between lowland and upland. Moreover, through network analysis, we demonstrated different co-abundance dynamics between lowland and upland conditions with a major impact on microbial hubs (strongly interconnected microbes) that fully shifted to aerobic microbes in the absence of flooding.

A rice GWAS panel of 281 accessions of japonica rice was phenotypically characterized for twenty six traits related to phenology, plant and seed morphology, physiology and yield for two years in field conditions under permanent flooding (PF) and limited water (LW). A genome-wide analysis uncovered a total of 160 significant marker-trait associations (MTAs), of which 32 were LW-specific, 59 were PF-specific and 69 were in common between the two water management systems. LW-specific associations were identified for several agronomic traits including days to maturation, days from flowering to maturation, leaf traits, plant height, panicle and seed traits, hundred grain weight, yield and tillering. Significant MTAs were detected across all the 12 rice chromosomes, while clusters of effects influencing different traits under LW or in both watering conditions were respectively observed on chromosomes 4, 8 and 12 and on chromosomes 1, 3, 4, 5, 8. The analysis of genes annotated in the Nipponbare reference sequence and included in the regions associated to traits related to plant morphology, grain yield and physiological parameters allowed the identification of genes that were demonstrated to affect the respective traits. Among these, three (OsOFP2, Dlf1, OsMADS56) and seven (SUI1, Sd1, OsCOL4, Nal1, OsphyB, GW5, Ehd1) candidate genes were respectively identified to co-localize with LW-specific associations and associations in common between the two water treatments. For several LW-specific MTAs, or in common among the two treatments, positional co-localizations with previously identified QTLs for rice adaptation to water shortages were observed, a result that further supports the role of the loci identified in this work in conferring adaptation to LW. The most robust associations identified here could represent suitable targets for genomic selection approaches to improve yield-related traits under LW.

In previous studies, we identified a locus for schizophrenia on 6q23.3 and proposed the Abelson helper integration site 1 ( AHI1 ) as the candidate gene. AHI1 is expressed in the brain and plays a key role in neurodevelopment, is involved in Joubert syndrome, and has been recently associated with autism. The neurodevelopmental role of AHI1 fits with etiological hypotheses of schizophrenia. To definitively confirm our hypothesis, we searched for associations using a dense map of the region. Our strongest findings lay within the AHI1 gene: single‐nucleotide polymorphisms rs11154801 and rs7759971 showed significant associations ( P =6.23E‐06; P =0.84E‐06) and haplotypes gave P values in the 10E‐8 to 10E‐10 range. The second highest significant region maps close to AHI1 and includes the intergenic region between BC040979 and PDE7B (rs2038549 at P =9.70E‐06 and rs1475069 at P =6.97E‐06), and PDE7B and MAP7 . Using a sample of Palestinian Arab families to confirm these findings, we found isolated signals. While these results did not retain their significance after correction for multiple testing, the joint analysis across the 2 samples supports the role of AHI1 , despite the presence of heterogeneity. Given the hypothesis of positive selection of schizophrenia genes, we resequenced a 11 kb region within AHI1 in ethnically defined populations and found evidence for a selective sweep. Network analysis indicates 2 haplotype clades, with schizophrenia‐susceptibility haplotypes clustering within the major clade. In conclusion, our data support the role of AHI1 as a susceptibility gene for schizophrenia and confirm it has been subjected to positive selection, also shedding light on new possible candidate genes, MAP7 and PDE7B .—Torri, F., Akelai, A., Lupoli, S., Sironi, M., Amann‐Zalcenstein, D., Fumagalli, M., Dal Fiume, C., Ben‐Asher, E., Kanyas, K., Cagliani, R., Cozzi, P., Trombetti, G., Lievers, L. S., Salvi, E., Orro, A., Beckmann, J. S., Lancet, D., Kohn, Y., Milanesi, L., Ebstein, R. B., Lerer, B., Macciardi, F. Fine mapping of AHI1 as a schizophrenia susceptibility gene: from association to evolutionary evidence. FASEB J . 24, 3066–3082 (2010). www.fasebj.org

The human genome is a mosaic of isochores, which are long (>200 kb) DNA sequences that are fairly homogeneous in base composition and can be assigned to five families comprising 33%–59% of GC composition. Although the compartmentalized organization of the mammalian genome has been investigated for more than 40 years, no satisfactory automatic procedure for segmenting the genome into isochores is available so far. We present a critical discussion of the currently available methods and a new approach called isoSegmenter which allows segmenting the genome into isochores in a fast and completely automatic manner. This approach relies on two types of experimentally defined parameters, the compositional boundaries of isochore families and an optimal window size of 100 kb. The approach represents an improvement over the existing methods, is ideally suited for investigating long-range features of sequenced and assembled genomes, and is publicly available at https://github.com/bunop/isoSegmenter .