Prediction of crossover recombination using parental genomes.

Meiotic recombination is a crucial cellular process, being one of the major drivers of evolution and adaptation of species. In plant breeding, crossing is used to introduce genetic variation among individuals and populations. While different approaches to predict recombination rates for different species have been developed, they fail to estimate the outcome of crossings between two specific accessions. This paper builds on the hypothesis that chromosomal recombination correlates positively to a measure of sequence identity. It presents a model that uses sequence identity, combined with other features derived from a genome alignment (including the number of variants, inversions, absent bases, and CentO sequences) to predict local chromosomal recombination in rice. Model performance is validated in an inter-subspecific indica x japonica cross, using 212 recombinant inbred lines. Across chromosomes, an average correlation of about 0.8 between experimental and prediction rates is achieved. The proposed model, a characterization of the variation of the recombination rates along the chromosomes, can enable breeding programs to increase the chances of creating novel allele combinations and, more generally, to introduce new varieties with a collection of desirable traits. It can be part of a modern panel of tools that breeders can use to reduce costs and execution times of crossing experiments

Sparse non-negative matrix factorization for retrieving genomes across metagenomes

International audienceThe development of massively parallel sequencing technologies enables to sequence DNA at high-throughput and low cost, fueling the rise of metagenomics which is the study of complex microbial communities sequenced in their natural environment. A metagenomic dataset consists of billions of unordered small fragments of genomes (reads), originating from hundreds or thousands of different organisms. The de novo reconstruction of individual genomes from metagenomes is practically challenging, both because of the complexity of the problem (sequence assembly is NP-hard) and the large data volumes. The clustering of sequences into biologically meaningful partitions (e.g. strains), known as binning, is a key step with most computational tools performing read assembly as a pre-processing. However, metagenome assembly (and even more cross-assembly) is computationally intensive, requiring terabytes of memory; it is also error-prone (yielding artefacts like chimeric contigs) and discards vast amounts of information in the form of unassembled reads (up to 50% for highly diverse metagenomes). Here we show how online learning methods for sparse non-negative matrix factorization can recover relative abundances of genomes across multiple metagenomes and support assembly-free read binning by using abundance covariation signals derived from the occurrence of unique k-mers (subsequences of size k) across samples. The combinatorial explosion of k-mers is controlled by indexing them using locality sensitive hashing, and sparse coding and dictionary learning techniques are used to decompose the k-mer abundance covariation signal into genome-resolved components in latent space

Fermentative Spirochaetes mediate necromass recycling in anoxic hydrocarbon-contaminated habitats

International audienceSpirochaetes are frequently detected in anoxic hydrocarbon- and organohalide-polluted groundwater, but their role in such ecosystems has remained unclear. To address this, we studied a sulfate-reducing, naphthalene-degrading enrichment culture, mainly comprising the sulfate reducer Desulfobacterium N47 and the rod-shaped Spirochete Rectinema cohabitans HM. Genome sequencing and proteome analysis suggested that the Spirochete is an obligate fermenter that catabolizes proteins and carbohydrates, resulting in acetate, ethanol, and molecular hydrogen (H$_2$) production. Physiological experiments inferred that hydrogen is an important link between the two bacteria in the enrichment culture, with H$_2$ derived from fermentation by R. cohabitans used as reductant for sulfate reduction by Desulfobacterium N47. Differential proteomics and physiological experiments showed that R. cohabitans utilizes biomass (proteins and carbohydrates) released from dead cells of Desulfobacterium N47. Further comparative and community genome analyses indicated that other Rectinema phylotypes are widespread in contaminated environments and may perform a hydrogenogenic fermentative lifestyle similar to R. cohabitans. Together, these findings indicate that environmental Spirochaetes scavenge detrital biomass and in turn drive necromass recycling at anoxic hydrocarbon-contaminated sites and potentially other habitats