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17 Pág. Departamento de ​Mejora Genética Animal (INIA), The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations., This research was financed by the METALGEN project (RTA2015-00022-C03) from the national plan for research, development, and innovation 2013–2020 and the Department of Economic Development and Competitiveness (Madrid, Spain).

To better understand heavy metal tolerance in Chlamydomonas acidophila, an extremophilic green alga, we assembled its transcriptome and measured transcriptomic expression before and after Cd exposure in this and the neutrophilic model microalga Chlamydomonas reinhardtii. Genes possibly related to heavy metal tolerance and detoxification were identified and analyzed as potential key innovations that enable this species to live in an extremely acid habitat with high levels of heavy metals. In addition we provide a data set of single orthologous genes from eight green algal species as a valuable resource for comparative studies including eukaryotic extremophiles. Our results based on differential gene expression, detection of unique genes and analyses of codon usage all indicate that there are important genetic differences in C. acidophila compared to C. reinhardtii. Several efflux family proteins were identified as candidate key genes for adaptation to acid environments. This study suggests for the first time that exposure to cadmium strongly increases transposon expression in green algae, and that oil biosynthesis genes are induced in Chlamydomonas under heavy metal stress. Finally, the comparison of the transcriptomes of several acidophilic and non-acidophilic algae showed that the Chlamydomonas genus is polyphyletic and that acidophilic algae have distinctive aminoacid usage patterns.