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. Thus, guaranteeing a statistically robust marker order requires that maps include only a carefully selected subset of SNPs. RESULTS: In this context, the SeSAM software allows automatic genetic map construction using seriation and placement approaches, to produce (1) a high-robustness framework map which includes as many markers as possible while keeping the order robustness beyond a given statistical threshold, and (2) a high-density total map including the framework plus almost all polymorphic markers. During this process, care is taken to limit the impact of genotyping errors and of missing data on mapping quality. SeSAM can be used with a wide range of biparental populations including from outcrossing species for which phases are inferred on-the-fly by maximum-likelihood during map elongation. The package also includes functions to simulate data sets, convert data formats, detect putative genotyping errors, visualize data and map quality (including graphical genotypes), and merge several maps into a consensus. SeSAM is also suitable for interactive map construction, by providing lower-level functions for 2-point and multipoint EM analyses. The software is implemented in a R package including functions in C++. CONCLUSIONS: SeSAM is a fully automatic linkage mapping software designed to (1) produce a framework map as robust as desired by optimizing the selection of a subset of markers, and (2) produce a high-density map including almost all polymorphic markers. The software can be used with a wide range of biparental mapping populations including cases from outcrossing. SeSAM is freely available under a GNU GPL v3 license and works on Linux, Windows, and macOS platforms. It can be downloaded together with its user-manual and quick-start tutorial from ForgeMIA (SeSAM project) at https://forgemia.inra.fr/gqe-acep/sesam/-/releases.

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. While current methods accurately identify species core parts, they miss many accessory genes or split them into small gene groups that remain unassociated to core clusters. RESULTS: We introduce MSPminer, a computationally efficient software tool that reconstitutes Metagenomic Species Pan-genomes (MSPs) by binning co-abundant genes across metagenomic samples. MSPminer relies on a new robust measure of proportionality coupled with an empirical classifier to group and distinguish not only species core genes but accessory genes also. Applied to a large scale metagenomic dataset, MSPminer successfully delineates in a few hours the gene repertoires of 1661 microbial species with similar specificity and higher sensitivity than existing tools. The taxonomic annotation of MSPs reveals microorganisms hitherto unknown and brings coherence in the nomenclature of the species of the human gut microbiota. The provided MSPs can be readily used for taxonomic profiling and biomarkers discovery in human gut metagenomic samples. In addition, MSPminer can be applied on gene count tables from other ecosystems to perform similar analyses. AVAILABILITY AND IMPLEMENTATION: The binary is freely available for non-commercial users at www.enterome.com/downloads. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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. With the possibility to consider a multi-allelic context, OptiMAS opens new prospects to assemble favorable alleles issued from diverse parents and further accelerate genetic gain.

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). A subset of the healthy controls comprised the age-matched siblings of patients whose HLA-B27 status was known. Changes in gut microbiota composition were assessed based on species diversity, enterotypes, and taxonomic and functional differences. RESULTS: Dysbiosis was confirmed in SpA patients as compared to healthy controls. The restriction of microbiota diversity was detected in patients with the most active disease, and the abundance of several bacterial species was correlated with Bath Ankylosing Spondylitis Disease Activity Index score. Among healthy controls, significant differences in microbiota composition were also detected between the HLA-B27-positive and the HLA-B27-negative siblings of SpA patients. We highlighted a decreased abundance of several species of bacteria in SpA patients, especially those bacteria belonging to the Clostridiales order. Among the few species of bacteria showing increased abundance, Ruminococcus gnavus was one of the top differentiating species. CONCLUSION: These findings reveal that genetic background and level of disease activity are likely to influence the composition of the gut microbiota of patients with SpA. It may be appropriate for further research on chronic arthritis to focus on these key parameters.

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. For each chromosome, we exclude at a 98% significance level the hypothesis that a single pathway underlies the formation of all crossovers, pointing to the coexistence of two types of crossing-over in maize, as was previously demonstrated in other organisms. We estimate the proportion of crossovers coming from the noninterfering pathway to range from 6 to 23% depending on the chromosome, with a cell average of approximately 15%. The mean number of noninterfering crossovers per chromosome is significantly correlated with the length of the synaptonemal complex. We also quantify the intensity of interference. Finally, we develop inference tools that allow one to tackle, without much loss of power, complex crossover interference models such as the beam film. The lack of a likelihood function in such models had prevented their use for parameter estimation. This advance will allow more realistic mechanisms of crossover formation to be modeled in the future.

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. In several organisms including yeast, tomato, Arabidopsis, and mouse, it is believed that crossovers form via at least two pathways, one interfering, the other not. RESULTS: We have developed a software package--"CODA", for CrossOver Distribution Analyzer--which allows one to quantitatively characterize crossover patterns by fitting interference models to experimental data. Two families of interfering models are provided: the "gamma" model and the "beam-film" model. The user can specify single or two-pathways modeling, and the software package infers the model's parameters and their confidence intervals. CODA can handle data produced from measurements on bivalents or gametes, in the form of continuous crossover positions or marker genotyping. We illustrate the possibilities on data from Wheat, corn and mouse. CONCLUSIONS: CODA extends the kind of crossover data that could be analyzed so far to include gametic data (rather than only bivalents/tetrads) when using two-pathways modeling. It will also enable users to perform analyses based on the beam-film model. CODA implements that model's complex physics and mathematics, and uses a summary statistic to overcomes the lack of a computable likelihood which has hampered its use till now.

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 0.80 and 0.75 for MD and TR respectively), while engraftment capacity of defrosted NaCl transplants most diverged (Spearman correlations around 0.63). Engraftment of members of the family Lachnospiraceae and Ruminoccocaceae was the most challenging in all groups of mice, being improved with MD and TR transplants compared to NaCl, but still lower than with the fresh preparation. Improvement of engraftment of this important group in maintaining health represents a challenge that could benefit from further research on fecal microbiota transplant manufacturing.

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. By investigating multi-allelic context and diverse pedigree structure, OptiMAS enables to assemble favorable alleles issued from diverse parents and further accelerate genetic gain.

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. Within this framework, we fit the two-pathway model to the data and compare crossover interference strength between chromosomes and then along chromosomes. We find that the interfering pathway has markedly higher interference strength nu in female than in male meiosis and also that male meiosis has a higher proportion p of noninterfering crossovers. Furthermore, we test for possible intrachromosomal variations of nu and p. Our conclusion is that there are clear differences between left and right arms as well as between central and peripheral regions. Finally, statistical tests unveil a genome-wide picture of small-scale heterogeneities, pointing to the existence of hot regions in the genome where crossovers form preferentially without interference.