The mixed linear model has been widely used in genome-wide association studies (GWAS), but its application to multi-locus GWAS analysis has not been explored and assessed. Here, we implemented a fast multi-locus random-SNP-effect EMMA (FASTmrEMMA) model for GWAS. The model is built on random single nucleotide polymorphism (SNP) effects and a new algorithm. This algorithm whitens the covariance matrix of the polygenic matrix K and environmental noise, and specifies the number of nonzero eigenvalues as one. The model first chooses all putative quantitative trait nucleotides (QTNs) with ≤ 0.005 P-values and then includes them in a multi-locus model for true QTN detection. Owing to the multi-locus feature, the Bonferroni correction is replaced by a less stringent selection criterion. Results from analyses of both simulated and real data showed that FASTmrEMMA is more powerful in QTN detection and model fit, has less bias in QTN effect estimation and requires a less running time than existing single- and multi-locus methods, such as empirical Bayes, settlement of mixed linear model under progressively exclusive relationship (SUPER), efficient mixed model association (EMMA), compressed MLM (CMLM) and enriched CMLM (ECMLM). FASTmrEMMA provides an alternative for multi-locus GWAS.

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Researchers have revealed minuscule features on the leaves of a common desert plant that allow it to collect water from moist air. © 2 0 1 6 M a c m i l l a n P u b l i s h e r s L i m i t e d. A l l r i g h t s r e s e r v e d .

1. Understanding the importance of biotic interactions in driving the distribution and abundance of species is a central goal of plant ecology. Early vascular plants likely colonized land occupied by biocrusts -photoautotrophic, surface-dwelling soil communities comprised of cyanobacteria, bryophytes, lichens and fungi -suggesting biotic interactions between biocrusts and plants have been at play for some 2,000 million years. Today, biocrusts coexist with plants in dryland ecosystems worldwide, and have been shown to both facilitate or inhibit plant species performance depending on ecological context. Yet, the factors that drive the direction and magnitude of these effects remain largely unknown.2. We conducted a meta-analysis of plant responses to biocrusts using a global dataset encompassing 1,004 studies from six continents. 3. Meta-analysis revealed there is no simple positive or negative effect of biocrusts on plants. Rather, plant responses differ by biocrust composition and plant species traits and vary across plant ontogeny. Moss-dominated biocrusts facilitated, while lichen-dominated biocrusts inhibited overall plant performance. Plant responses also varied among plant functional groups: C 4 grasses received greater benefits from biocrusts compared to C 3 grasses, and plants without N-fixing symbionts responded more positively to biocrusts than plants with N-fixing symbionts. Biocrusts decreased germination but facilitated growth of non-native plant species. S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section at the end of the article. How to cite this article: Havrilla CA, Chaudhary VB, Ferrenberg S, et al. Towards a predictive framework for biocrust mediation of plant performance: A meta-analysis. J

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If the poultry industry hopes to continue to flourish, the identification of potential quantitative trait loci (QTL) for production-related traits must be pursued This remains true despite the sequencing of the chicken genome. In view of this need, a scan of the chicken genome using 72 microsatellite markers was carried out on a meat-type x egg-type resource population measured for production and egg quality traits. Using a Bayesian analysis, potential QTL for a number of traits were identified on several chromosomes. Evidence of eight QTL regions associated with a total of eight traits (specific gravity, albumin height, Haugh score, shell shape, total number of eggs, final body weight, gain, and feed efficiency) was found. Two of these regions, one spanning the area of 263/287 cM on GAA01 and the other spanning the area of 23/28 cM on GAA02, were associated with multiple QTL.