The Caenorhabditis elegans genome encodes nineteen functional Argonaute proteins that use 22G-RNAs, 26G-RNAs, miRNAs or piRNAs to regulate target transcripts. Only one Argonaute is essential under normal laboratory conditions: CSR-1. While CSR-1 has been studied widely, nearly all studies have overlooked the fact that the csr-1 locus encodes two isoforms. These isoforms differ by an additional 163 amino acids present in the N-terminus of CSR-1a. Using CRISPR-Cas9 genome editing to introduce GFP::3xFLAG into the long (CSR-1a) and short (CSR-1b) isoforms, we found that CSR-1a is expressed during spermatogenesis and in several somatic tissues, including the intestine. CSR-1b is expressed constitutively in the germline. small RNA sequencing of CSR-1 complexes shows that they interact with partly overlapping sets of 22G-RNAs. Phenotypic analyses reveal that the essential functions of csr-1 described in the literature coincide with CSR-1b, while CSR-1a plays tissue specific functions. During spermatogenesis, CSR-1a integrates into an sRNA regulatory network including ALG-3, ALG-4 and WAGO-10 that is necessary for fertility at 25°C. In the intestine, CSR-1a silences immunity and pathogen-responsive genes, and its loss results in improved survival from the pathogen Pseudomonas aeruginosa. Our findings functionally distinguish the CSR-1 isoforms and highlight the importance of studying each AGO isoform independently.
SUMMARYThe C. elegans genome encodes nineteen functional Argonaute proteins that utilize 22G-RNAs, 26G-RNAs, miRNAs, or piRNAs to regulate their target transcripts. Only one of these proteins is essential under normal laboratory conditions: CSR-1. While CSR-1 has been studied in various developmental and functional contexts, nearly all studies investigating CSR-1 have overlooked the fact that the csr-1 locus encodes two isoforms. These isoforms differ by an additional 163 amino acids present in the N-terminus of CSR-1a. Using CRISPR-Cas9 genome editing to introduce GFP::3xFLAG epitopes into the long (CSR-1a) and short (CSR-1b) isoforms of CSR-1, we identified differential expression patterns for the two isoforms. CSR-1a is expressed specifically during spermatogenesis and in select somatic tissues, including the intestine. In contrast, CSR-1b, is expressed constitutively in the germline. Essential functions of csr-1 described in the literature coincide with CSR-1b. In contrast, CSR-1a plays tissue specific functions during spermatogenesis, where it integrates into a spermatogenesis sRNA regulatory network including ALG-3, ALG-4, and WAGO-10 that is necessary for male fertility. CSR-1a is also required in the intestine for the silencing of repetitive transgenes. Sequencing of small RNAs associated with each CSR-1 isoform reveals that CSR-1a engages with 22G- and 26G-RNAs, while CSR-1b interacts with only 22G-RNAs to regulate distinct groups of germline genes and regulate both sperm and oocyte-mediated fertility.
Cophylogeny is the congruence of phylogenetic relationships between two different groups of organisms due to their long‐term interaction. We investigated the use of tree shape distance measures to quantify the degree of cophylogeny. We implemented a reverse‐time simulation model of pathogen phylogenies within a fixed host tree, given cospeciation probability, host switching, and pathogen speciation rates. We used this model to evaluate 18 distance measures between host and pathogen trees including two kernel distances that we developed for labeled and unlabeled trees, which use branch lengths and accommodate different size trees. Finally, we used these measures to revisit published cophylogenetic studies, where authors described the observed associations as representing a high or low degree of cophylogeny. Our simulations demonstrated that some measures are more informative than others with respect to specific coevolution parameters especially when these did not assume extreme values. For real datasets, trees’ associations projection revealed clustering of high concordance studies suggesting that investigators are describing it in a consistent way. Our results support the hypothesis that measures can be useful for quantifying cophylogeny. This motivates their usage in the field of coevolution and supports the development of simulation‐based methods, i.e., approximate Bayesian computation, to estimate the underlying coevolutionary parameters.
Cophylogeny is the congruence of phylogenetic relationships between two different groups of organisms due to their long‐term interaction. We investigated the use of tree shape distance measures to quantify the degree of cophylogeny. We implemented a reverse‐time simulation model of pathogen phylogenies within a fixed host tree, given cospeciation probability, host switching, and pathogen speciation rates. We used this model to evaluate 18 distance measures between host and pathogen trees including two kernel distances that we developed for labeled and unlabeled trees, which use branch lengths and accommodate different size trees. Finally, we used these measures to revisit published cophylogenetic studies, where authors described the observed associations as representing a high or low degree of cophylogeny. Our simulations demonstrated that some measures are more informative than others with respect to specific coevolution parameters especially when these did not assume extreme values. For real datasets, trees’ associations projection revealed clustering of high concordance studies suggesting that investigators are describing it in a consistent way. Our results support the hypothesis that measures can be useful for quantifying cophylogeny. This motivates their usage in the field of coevolution and supports the development of simulation‐based methods, i.e., approximate Bayesian computation, to estimate the underlying coevolutionary parameters.
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