PMC:7253482 / 32923-34338 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"998","span":{"begin":79,"end":82},"obj":"Gene"},{"id":"999","span":{"begin":299,"end":304},"obj":"Gene"},{"id":"1000","span":{"begin":83,"end":88},"obj":"Gene"},{"id":"1001","span":{"begin":98,"end":106},"obj":"Species"},{"id":"1002","span":{"begin":172,"end":180},"obj":"Species"},{"id":"1003","span":{"begin":369,"end":375},"obj":"Species"},{"id":"1004","span":{"begin":408,"end":416},"obj":"Species"},{"id":"1005","span":{"begin":398,"end":402},"obj":"Disease"},{"id":"1010","span":{"begin":563,"end":571},"obj":"Species"},{"id":"1011","span":{"begin":1114,"end":1116},"obj":"Chemical"},{"id":"1012","span":{"begin":1117,"end":1119},"obj":"Chemical"},{"id":"1013","span":{"begin":553,"end":557},"obj":"Disease"}],"attributes":[{"id":"A998","pred":"tao:has_database_id","subj":"998","obj":"Gene:2995"},{"id":"A999","pred":"tao:has_database_id","subj":"999","obj":"Gene:43740568"},{"id":"A1000","pred":"tao:has_database_id","subj":"1000","obj":"Gene:43740568"},{"id":"A1001","pred":"tao:has_database_id","subj":"1001","obj":"Tax:694009"},{"id":"A1002","pred":"tao:has_database_id","subj":"1002","obj":"Tax:1335626"},{"id":"A1003","pred":"tao:has_database_id","subj":"1003","obj":"Tax:9606"},{"id":"A1004","pred":"tao:has_database_id","subj":"1004","obj":"Tax:1335626"},{"id":"A1005","pred":"tao:has_database_id","subj":"1005","obj":"MESH:D045169"},{"id":"A1010","pred":"tao:has_database_id","subj":"1010","obj":"Tax:1335626"},{"id":"A1011","pred":"tao:has_database_id","subj":"1011","obj":"MESH:C022306"},{"id":"A1012","pred":"tao:has_database_id","subj":"1012","obj":"MESH:D003903"},{"id":"A1013","pred":"tao:has_database_id","subj":"1013","obj":"MESH:D045169"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T169","span":{"begin":89,"end":93},"obj":"Body_part"},{"id":"T170","span":{"begin":205,"end":211},"obj":"Body_part"},{"id":"T171","span":{"begin":305,"end":309},"obj":"Body_part"},{"id":"T172","span":{"begin":1229,"end":1239},"obj":"Body_part"},{"id":"T173","span":{"begin":1297,"end":1307},"obj":"Body_part"},{"id":"T174","span":{"begin":1347,"end":1357},"obj":"Body_part"}],"attributes":[{"id":"A169","pred":"fma_id","subj":"T169","obj":"http://purl.org/sig/ont/fma/fma74402"},{"id":"A170","pred":"fma_id","subj":"T170","obj":"http://purl.org/sig/ont/fma/fma84116"},{"id":"A171","pred":"fma_id","subj":"T171","obj":"http://purl.org/sig/ont/fma/fma74402"},{"id":"A172","pred":"fma_id","subj":"T172","obj":"http://purl.org/sig/ont/fma/fma82739"},{"id":"A173","pred":"fma_id","subj":"T173","obj":"http://purl.org/sig/ont/fma/fma82739"},{"id":"A174","pred":"fma_id","subj":"T174","obj":"http://purl.org/sig/ont/fma/fma82739"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T99","span":{"begin":98,"end":106},"obj":"Disease"},{"id":"T100","span":{"begin":98,"end":102},"obj":"Disease"},{"id":"T101","span":{"begin":398,"end":402},"obj":"Disease"},{"id":"T102","span":{"begin":553,"end":557},"obj":"Disease"}],"attributes":[{"id":"A99","pred":"mondo_id","subj":"T99","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A100","pred":"mondo_id","subj":"T100","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A101","pred":"mondo_id","subj":"T101","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A102","pred":"mondo_id","subj":"T102","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T237","span":{"begin":89,"end":93},"obj":"http://purl.obolibrary.org/obo/OGG_0000000002"},{"id":"T238","span":{"begin":305,"end":309},"obj":"http://purl.obolibrary.org/obo/OGG_0000000002"},{"id":"T239","span":{"begin":369,"end":375},"obj":"http://purl.obolibrary.org/obo/NCBITaxon_9606"},{"id":"T240","span":{"begin":618,"end":625},"obj":"http://purl.obolibrary.org/obo/NCBITaxon_10239"},{"id":"T241","span":{"begin":736,"end":737},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T242","span":{"begin":1020,"end":1029},"obj":"http://purl.obolibrary.org/obo/UBERON_0001353"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T357","span":{"begin":477,"end":479},"obj":"Chemical"},{"id":"T358","span":{"begin":1114,"end":1116},"obj":"Chemical"},{"id":"T359","span":{"begin":1229,"end":1234},"obj":"Chemical"},{"id":"T360","span":{"begin":1235,"end":1239},"obj":"Chemical"},{"id":"T361","span":{"begin":1297,"end":1302},"obj":"Chemical"},{"id":"T362","span":{"begin":1303,"end":1307},"obj":"Chemical"},{"id":"T363","span":{"begin":1347,"end":1352},"obj":"Chemical"},{"id":"T364","span":{"begin":1353,"end":1357},"obj":"Chemical"}],"attributes":[{"id":"A357","pred":"chebi_id","subj":"T357","obj":"http://purl.obolibrary.org/obo/CHEBI_33793"},{"id":"A358","pred":"chebi_id","subj":"T358","obj":"http://purl.obolibrary.org/obo/CHEBI_33793"},{"id":"A359","pred":"chebi_id","subj":"T359","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A360","pred":"chebi_id","subj":"T360","obj":"http://purl.obolibrary.org/obo/CHEBI_37527"},{"id":"A361","pred":"chebi_id","subj":"T361","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A362","pred":"chebi_id","subj":"T362","obj":"http://purl.obolibrary.org/obo/CHEBI_37527"},{"id":"A363","pred":"chebi_id","subj":"T363","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A364","pred":"chebi_id","subj":"T364","obj":"http://purl.obolibrary.org/obo/CHEBI_37527"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-PD-IDO","denotations":[{"id":"T92","span":{"begin":618,"end":625},"obj":"http://purl.obolibrary.org/obo/NCBITaxon_10239"},{"id":"T93","span":{"begin":1224,"end":1228},"obj":"http://purl.obolibrary.org/obo/BFO_0000029"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-PD-FMA","denotations":[{"id":"T167","span":{"begin":89,"end":93},"obj":"Body_part"},{"id":"T168","span":{"begin":205,"end":211},"obj":"Body_part"},{"id":"T169","span":{"begin":305,"end":309},"obj":"Body_part"},{"id":"T170","span":{"begin":1229,"end":1239},"obj":"Body_part"},{"id":"T171","span":{"begin":1297,"end":1307},"obj":"Body_part"},{"id":"T172","span":{"begin":1347,"end":1357},"obj":"Body_part"}],"attributes":[{"id":"A172","pred":"fma_id","subj":"T172","obj":"http://purl.org/sig/ont/fma/fma82739"},{"id":"A168","pred":"fma_id","subj":"T168","obj":"http://purl.org/sig/ont/fma/fma84116"},{"id":"A169","pred":"fma_id","subj":"T169","obj":"http://purl.org/sig/ont/fma/fma74402"},{"id":"A167","pred":"fma_id","subj":"T167","obj":"http://purl.org/sig/ont/fma/fma74402"},{"id":"A170","pred":"fma_id","subj":"T170","obj":"http://purl.org/sig/ont/fma/fma82739"},{"id":"A171","pred":"fma_id","subj":"T171","obj":"http://purl.org/sig/ont/fma/fma82739"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-CHEBI","denotations":[{"id":"T251","span":{"begin":1229,"end":1234},"obj":"Chemical"},{"id":"T252","span":{"begin":1297,"end":1302},"obj":"Chemical"},{"id":"T253","span":{"begin":1347,"end":1352},"obj":"Chemical"}],"attributes":[{"id":"A252","pred":"chebi_id","subj":"T252","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A253","pred":"chebi_id","subj":"T253","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"},{"id":"A251","pred":"chebi_id","subj":"T251","obj":"http://purl.obolibrary.org/obo/CHEBI_46882"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-PD-NCBITaxon","denotations":[{"id":"T205","span":{"begin":98,"end":106},"obj":"Species"},{"id":"T206","span":{"begin":98,"end":102},"obj":"Species"},{"id":"T207","span":{"begin":172,"end":180},"obj":"Species"},{"id":"T208","span":{"begin":369,"end":375},"obj":"Species"},{"id":"T209","span":{"begin":398,"end":402},"obj":"Species"},{"id":"T210","span":{"begin":408,"end":416},"obj":"Species"},{"id":"T211","span":{"begin":553,"end":557},"obj":"Species"},{"id":"T212","span":{"begin":563,"end":571},"obj":"Species"},{"id":"T213","span":{"begin":618,"end":625},"obj":"Species"},{"id":"T214","span":{"begin":738,"end":743},"obj":"Species"}],"attributes":[{"id":"A211","pred":"ncbi_taxonomy_id","subj":"T211","obj":"NCBItxid:694009"},{"id":"A207","pred":"ncbi_taxonomy_id","subj":"T207","obj":"NCBItxid:1335626"},{"id":"A210","pred":"ncbi_taxonomy_id","subj":"T210","obj":"NCBItxid:1335626"},{"id":"A212","pred":"ncbi_taxonomy_id","subj":"T212","obj":"NCBItxid:1335626"},{"id":"A206","pred":"ncbi_taxonomy_id","subj":"T206","obj":"NCBItxid:694009"},{"id":"A213","pred":"ncbi_taxonomy_id","subj":"T213","obj":"NCBItxid:10239"},{"id":"A205","pred":"ncbi_taxonomy_id","subj":"T205","obj":"NCBItxid:694009"},{"id":"A214","pred":"ncbi_taxonomy_id","subj":"T214","obj":"NCBItxid:79338"},{"id":"A208","pred":"ncbi_taxonomy_id","subj":"T208","obj":"NCBItxid:9605"},{"id":"A209","pred":"ncbi_taxonomy_id","subj":"T209","obj":"NCBItxid:694009"}],"namespaces":[{"prefix":"NCBItxid","uri":"http://purl.bioontology.org/ontology/NCBITAXON/"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-sentences","denotations":[{"id":"T196","span":{"begin":0,"end":28},"obj":"Sentence"},{"id":"T197","span":{"begin":29,"end":167},"obj":"Sentence"},{"id":"T198","span":{"begin":168,"end":249},"obj":"Sentence"},{"id":"T199","span":{"begin":250,"end":376},"obj":"Sentence"},{"id":"T200","span":{"begin":377,"end":468},"obj":"Sentence"},{"id":"T201","span":{"begin":469,"end":608},"obj":"Sentence"},{"id":"T202","span":{"begin":609,"end":776},"obj":"Sentence"},{"id":"T203","span":{"begin":777,"end":907},"obj":"Sentence"},{"id":"T204","span":{"begin":908,"end":1201},"obj":"Sentence"},{"id":"T205","span":{"begin":1202,"end":1415},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-PD-MONDO","denotations":[{"id":"T94","span":{"begin":98,"end":106},"obj":"Disease"},{"id":"T95","span":{"begin":98,"end":102},"obj":"Disease"},{"id":"T96","span":{"begin":398,"end":402},"obj":"Disease"},{"id":"T97","span":{"begin":553,"end":557},"obj":"Disease"}],"attributes":[{"id":"A95","pred":"mondo_id","subj":"T95","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A97","pred":"mondo_id","subj":"T97","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A96","pred":"mondo_id","subj":"T96","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"},{"id":"A94","pred":"mondo_id","subj":"T94","obj":"http://purl.obolibrary.org/obo/MONDO_0005091"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-Pubtator","denotations":[{"id":"998","span":{"begin":79,"end":82},"obj":"Gene"},{"id":"1000","span":{"begin":83,"end":88},"obj":"Gene"},{"id":"1001","span":{"begin":98,"end":106},"obj":"Species"},{"id":"1002","span":{"begin":172,"end":180},"obj":"Species"},{"id":"999","span":{"begin":299,"end":304},"obj":"Gene"},{"id":"1003","span":{"begin":369,"end":375},"obj":"Species"},{"id":"1005","span":{"begin":398,"end":402},"obj":"Disease"},{"id":"1004","span":{"begin":408,"end":416},"obj":"Species"},{"id":"1013","span":{"begin":553,"end":557},"obj":"Disease"},{"id":"1010","span":{"begin":563,"end":571},"obj":"Species"},{"id":"1011","span":{"begin":1114,"end":1116},"obj":"Chemical"},{"id":"1012","span":{"begin":1117,"end":1119},"obj":"Chemical"}],"attributes":[{"id":"A1010","pred":"pubann:denotes","subj":"1010","obj":"Tax:1335626"},{"id":"A1001","pred":"pubann:denotes","subj":"1001","obj":"Tax:694009"},{"id":"A1013","pred":"pubann:denotes","subj":"1013","obj":"MESH:D045169"},{"id":"A999","pred":"pubann:denotes","subj":"999","obj":"Gene:43740568"},{"id":"A1003","pred":"pubann:denotes","subj":"1003","obj":"Tax:9606"},{"id":"A998","pred":"pubann:denotes","subj":"998","obj":"Gene:2995"},{"id":"A1011","pred":"pubann:denotes","subj":"1011","obj":"MESH:C022306"},{"id":"A1002","pred":"pubann:denotes","subj":"1002","obj":"Tax:1335626"},{"id":"A1005","pred":"pubann:denotes","subj":"1005","obj":"MESH:D045169"},{"id":"A1000","pred":"pubann:denotes","subj":"1000","obj":"Gene:43740568"},{"id":"A1004","pred":"pubann:denotes","subj":"1004","obj":"Tax:1335626"},{"id":"A1012","pred":"pubann:denotes","subj":"1012","obj":"MESH:D003903"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sample-UniProt","denotations":[{"id":"T6448","span":{"begin":67,"end":71},"obj":"Protein"},{"id":"T6449","span":{"begin":79,"end":82},"obj":"Protein"}],"attributes":[{"id":"A6448","pred":"uniprot_id","subj":"T6448","obj":"https://www.uniprot.org/uniprot/Q8N1N2"},{"id":"A6449","pred":"uniprot_id","subj":"T6449","obj":"https://www.uniprot.org/uniprot/P03711"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}

{"project":"LitCovid-sentences","denotations":[{"id":"T196","span":{"begin":0,"end":28},"obj":"Sentence"},{"id":"T197","span":{"begin":29,"end":167},"obj":"Sentence"},{"id":"T198","span":{"begin":168,"end":249},"obj":"Sentence"},{"id":"T199","span":{"begin":250,"end":376},"obj":"Sentence"},{"id":"T200","span":{"begin":377,"end":468},"obj":"Sentence"},{"id":"T201","span":{"begin":469,"end":608},"obj":"Sentence"},{"id":"T202","span":{"begin":609,"end":776},"obj":"Sentence"},{"id":"T203","span":{"begin":777,"end":907},"obj":"Sentence"},{"id":"T204","span":{"begin":908,"end":1201},"obj":"Sentence"},{"id":"T205","span":{"begin":1202,"end":1415},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Molecular evolution analysis\nPublicly available sequences encoding full-length GPC spike gene for SARS-CoV (3765 bp) were downloaded from GenBank and manually aligned. For MERS-CoV, we leveraged the whole genome alignment collated by Dudas et al.69. Specifically, the alignment corresponding to the spike gene was extracted (4059 bp), excluding sequences isolated from humans. Final alignments for SARS- and MERS-CoV corresponded to 70 and 100 sequences, respectively.\nFor the dN/dS analysis, we first estimated Bayesian molecular clock phylogenies for SARS- and MERS-CoV independently using BEAST v 1.8.470. For both viruses, we assumed an uncorrelated log-normal distributed molecular clock71, Bayesian Skyline coalescent prior72 and a codon-structured substitution model73. Multiple independent MCMC runs of 10–20 million steps were executed to ensure that stationarity and convergence had been achieved. Empirical distributions of time-scaled phylogenies were obtained by combining (after the removal of burnin) the posterior tree distributions from the separate runs, which were subsequently used to estimate dN/dS ratios using the renaissance counting approach74,75 implemented in BEAST v 1.8.4. We also estimated per-site amino-acid diversity, which was calculated as the average number of amino-acid difference between two sequences at an amino-acid position in all possible pairs in the sequence alignment."}