Large-scale composite hypothesis testing procedure for omics data analyses.

Composite hypothesis testing using summary statistics is a well-established approach for assessing the effect of a single marker or gene across multiple traits or omics levels. Numerous procedures have been developed for this task and have been successfully applied to identify complex patterns of association between traits, conditions, or phenotypes. However, existing methods often struggle with scalability in large datasets or fail to account for dependencies between traits or omics levels, limiting their ability to control false positives effectively.

Global compositional and functional states of the human gut microbiome in health and disease.

The human gut microbiota is of increasing interest, with metagenomics a key tool for analyzing bacterial diversity and functionality in health and disease. Despite increasing efforts to expand microbial gene catalogs and an increasing number of metagenome-assembled genomes, there have been few pan-metagenomic association studies and in-depth functional analyses across different geographies and diseases. Here, we explored 6014 human gut metagenome samples across 19 countries and 23 diseases by performing compositional, functional cluster, and integrative analyses.

SeSAM: software for automatic construction of order-robust linkage maps.

Background: Genotyping and sequencing technologies produce increasingly large numbers of genetic markers with potentially high rates of missing or erroneous data. Therefore, the construction of linkage maps is more and more complex. Moreover, the size of segregating populations remains constrained by cost issues and is less and less commensurate with the numbers of SNPs available.

Both Disease Activity and HLA-B27 Status Are Associated With Gut Microbiome Dysbiosis in Spondyloarthritis Patients.

Objective: Gut microbiome dysbiosis has previously been reported in spondyloarthritis (SpA) patients and could be critically involved in the pathogenesis of this disorder. The objectives of this study were to further characterize the microbiota structure in SpA patients and to investigate the relationship between dysbiosis and disease activity in light of the putative influence of the genetic background.

Methods: Shotgun sequencing was performed on fecal DNA isolated from stool samples from 2 groups of adult volunteers: SpA patients (n = 102) and healthy controls (n = 63).

High engraftment capacity of frozen ready-to-use human fecal microbiota transplants assessed in germ-free mice.

The number of indications for fecal microbiota transplantation is expected to rise, thus increasing the needs for production of readily available frozen or freeze-dried transplants. Using shotgun metagenomics, we investigated the capacity of two novel human fecal microbiota transplants prepared in maltodextrin-trehalose solutions (abbreviated MD and TR for maltodextrin:trehalose, 3:1, w/w, and trehalose:maltodextrin 3:1, w/w, respectively), to colonize a germ-free born mouse model. Gavage with frozen-thawed MD or TR suspensions gave the taxonomic profiles of mouse feces that best resembled those obtained with the fresh inoculum (Spearman correlations based on relative abundances of metagenomic species around 0.

MSPminer: abundance-based reconstitution of microbial pan-genomes from shotgun metagenomic data.

Motivation: Analysis toolkits for shotgun metagenomic data achieve strain-level characterization of complex microbial communities by capturing intra-species gene content variation. Yet, these tools are hampered by the extent of reference genomes that are far from covering all microbial variability, as many species are still not sequenced or have only few strains available. Binning co-abundant genes obtained from de novo assembly is a powerful reference-free technique to discover and reconstitute gene repertoire of microbial species.

OptiMAS: a decision support tool to conduct marker-assisted selection programs.

Ongoing major advances in plant genotyping and phenotyping lead to a better understanding of genetic architecture of agronomical traits. In this context, it is important to develop decision support tools to help breeders in implementing marker-assisted selection (MAS) projects to assemble new allele combinations. Algorithms have been developed within an interactive graphical interface to (a) trace parental QTL alleles throughout selection generations, (b) propose strategies to select the best plants based on estimated molecular scores, and (c) efficiently intermate them depending on the expected value of their progenies.

Hot regions of noninterfering crossovers coexist with a nonuniformly interfering pathway in Arabidopsis thaliana.

In most organisms that have been studied, crossovers formed during meiosis exhibit interference: nearby crossovers are rare. Here we provide an in-depth study of crossover interference in Arabidopsis thaliana, examining crossovers genome-wide in >1500 backcrosses for both male and female meiosis. This unique data set allows us to take a two-pathway modeling approach based on superposing a fraction p of noninterfering crossovers and a fraction (1 - p) of interfering crossovers generated using the gamma model characterized by its interference strength nu.

OptiMAS: a decision support tool for marker-assisted assembly of diverse alleles.

Current advances in plant genotyping lead to major progress in the knowledge of genetic architecture of traits of interest. It is increasingly important to develop decision support tools to help breeders and geneticists to conduct marker-assisted selection methods to assemble favorable alleles that are discovered. Algorithms have been implemented, within an interactive graphical interface, to 1) trace parental alleles throughout generations, 2) propose strategies to select the best plants based on estimated molecular scores, and 3) efficiently intermate them depending on the expected value of their progenies.

CODA (crossover distribution analyzer): quantitative characterization of crossover position patterns along chromosomes.

Background: During meiosis, homologous chromosomes exchange segments via the formation of crossovers. This phenomenon is highly regulated; in particular, crossovers are distributed heterogeneously along the physical map and rarely arise in close proximity, a property referred to as "interference". Crossover positions form patterns that give clues about how crossovers are formed.

Two types of meiotic crossovers coexist in maize.

We apply modeling approaches to investigate the distribution of late recombination nodules in maize (Zea mays). Such nodules indicate crossover positions along the synaptonemal complex. High-quality nodule data were analyzed using two different interference models: the "statistical" gamma model and the "mechanical" beam film model.