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Sundaramurthi, Jagadish Chandrabose

Publications and source records attributed to Sundaramurthi, Jagadish Chandrabose.

Correction to ‘Genomes OnLine Database (GOLD) v.8: overview and updates’

In the originally published online version of this manuscript, there were two co-authors missing from the author list: Tanja Woyke (https://orcid.org/0000-0002-9485-5637) and Emiley Eloe-Fadrosh (https://orcid.org/0000-0002-8162-1276). The list should now read: ‘Supratim Mukherjee, Dimitri Stamatis, Jon Bertsch, Galina Ovchinnikova, Jagadish Chandrabose Sundaramurthi, Janey Lee, Mahathi Kandimalla, Tanja Woyke, Emiley A. Eloe-Fardosh, I-Min A. Chen, Nikos C. Kyrpides and T.B.K. Reddy’. The emendation is outlined only in this correction notice to preserve the version of record.

99 GENERAL AND MISCELLANEOUS↗

Correction to ‘Twenty-five years of Genomes OnLine Database (GOLD): data updates and new features in v.9’

In the originally published online version of this manuscript, there were two co-authors missing from the author list: Tanja Woyke (https://orcid.org/0000-0002-9485-5637) and Emiley Eloe-Fadrosh (https://orcid.org/0000-0002-8162-1276). The author list should read: ‘Supratim Mukherjee, Dimitri Stamatis, Cindy Tianqing Li, Galina Ovchinnikova, Jon Bertsch, Jagadish Chandrabose Sundaramurthi, Mahathi Kandimalla, Paul A. Nicolopoulos, Alessandro Favognano, Tanja Woyke, Emiley A. Eloe-Fardosh, I-Min A. Chen, Nikos C. Kyrpides and T.B.K. Reddy’. This emendation is outlined only in this correction notice to preserve the version of record.

99 GENERAL AND MISCELLANEOUS↗

An expectation–maximization framework for comprehensive prediction of isoform-specific functions

Advances in RNA sequencing technologies have achieved an unprecedented accuracy in the quantification of mRNA isoforms, but our knowledge of isoform-specific functions has lagged behind. There is a need to understand the functional consequences of differential splicing, which could be supported by the generation of accurate and comprehensive isoform-specific gene ontology annotations. We present isoform interpretation, a method that uses expectation–maximization to infer isoform-specific functions based on the relationship between sequence and functional isoform similarity. We predicted isoform-specific functional annotations for 85 617 isoforms of 17 900 protein-coding human genes spanning a range of 17 430 distinct gene ontology terms. Comparison with a gold-standard corpus of manually annotated human isoform functions showed that isoform interpretation significantly outperforms state-of-the-art competing methods. We provide experimental evidence that functionally related isoforms predicted by isoform interpretation show a higher degree of domain sharing and expression correlation than functionally related genes. We also show that isoform sequence similarity correlates better with inferred isoform function than with gene-level function.

59 BASIC BIOLOGICAL SCIENCES↗

Twenty-five years of Genomes OnLine Database (GOLD): data updates and new features in v.9

We report the Genomes OnLine Database (GOLD) (https://gold.jgi.doe.gov/) at the Department of Energy Joint Genome Institute (DOE-JGI) continues to maintain its role as one of the flagship genomic metadata repositories of the world. The ever-increasing number of projects and metadata are freely available to the user community world-wide. GOLD’s metadata is consumed by scientists and remains an important source for large-scale comparative genomics analysis initiatives. Encouraged by this active user engagement and growth, GOLD has continued to add new components and capabilities. The new features such as a public Application Programming Interface (API) and Ecosystem landing page as well as the growth of different entities in this current GOLD v.9 edition are described in detail in this manuscript.

59 BASIC BIOLOGICAL SCIENCES↗

Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative’s Workshop and Follow-On Activities

Microbiome samples are inherently defined by the environment in which they are found. Therefore, data that provide context and enable interpretation of measurements produced from biological samples, often referred to as metadata, are critical. Important contributions have been made in the development of community-driven metadata standards; however, these standards have not been uniformly embraced by the microbiome research community. To understand how these standards are being adopted, or the barriers to adoption, across research domains, institutions, and funding agencies, the National Microbiome Data Collaborative (NMDC) hosted a workshop in October 2019. This report provides a summary of discussions that took place throughout the workshop, as well as outcomes of the working groups initiated at the workshop.

54 ENVIRONMENTAL SCIENCES↗

Genomes OnLine Database (GOLD) v.8: overview and updates

The Genomes OnLine Database (GOLD) (https://gold.jgi.doe.gov/) is a manually curated, daily updated collection of genome projects and their metadata accumulated from around the world. The current version of the database includes over 1.17 million entries organized broadly into Studies (45 770), Organisms (387 382) or Biosamples (101 207), Sequencing Projects (355 364) and Analysis Projects (283 481). These four levels contain over 600 metadata fields, which includes 76 controlled vocabulary (CV) tables containing 3873 terms. GOLD provides an interactive web user interface for browsing and searching by a wide range of project and metadata fields. Users can enter details about their own projects in GOLD, which acts as a gatekeeper to ensure that metadata is accurately documented before submitting sequence information to the Integrated Microbial Genomes (IMG) system for analysis. In order to maintain a reference dataset for use by members of the scientific community, GOLD also imports projects from public repositories such as GenBank and SRA. Here, the current status of the database, along with recent updates and improvements are described in this manuscript.

59 BASIC BIOLOGICAL SCIENCES↗

HIV-1 transmitted drug resistance surveillance: shifting trends in study design and prevalence estimates

HIV-1 transmitted drug resistance (TDR) prevalence increased during the initial years of the antiretroviral therapy (ART) global scale-up. Few studies have examined recent trends in TDR prevalence using published genetic sequences and described the characteristics of ART-naïve persons from whom these published sequences have been obtained. We identified 125 studies published between 2014 and 2019 for which HIV-1 reverse transcriptase (RT) with or without protease from ≥50 ART-naïve adult persons were submitted to the GenBank sequence database. The population characteristics and TDR prevalence were compared to those in 122 studies published in the preceding five years between 2009 and 2013. TDR prevalence was analysed using median study-level and person-level data. The 2009 to 2013 and 2014 to 2019 studies reported sequence data from 32,866 and 41,724 ART-naïve persons respectively. Studies from the low- and middle-income country (LMIC) regions in sub-Saharan Africa, South/Southeast Asia and Latin America/Caribbean accounted for approximately two-thirds of the studies during each period. Between the two periods, the proportion of studies from sub-Saharan Africa and from South/Southeast Asia countries other than China decreased from 43% to 32% and the proportion of studies performed at sentinel sites for recent HIV-1 infection decreased from 33% to 22%. Between 2014 and 2019, median study-level TDR prevalence was 4.1% in South/Southeast Asia, 6.0% in sub-Saharan Africa, 9.1% in Latin America/Caribbean, 8.5% in Europe and 14.2% in North America. In the person-level analysis, there was an increase in overall, NNRTI and two-class NRTI/NNRTI resistance in sub-Saharan Africa; an increase in NNRTI resistance in Latin America/Caribbean, and an increase in overall, NNRTI and PI resistance in North America. Overall, NNRTI and dual NRTI/NNRTI-associated TDR prevalence was significantly higher in sub-Saharan Africa studies published between 2014 and 2019 compared with those published between 2009 and 2013. The decreasing proportion of studies from the hardest hit LMIC regions and the shift away from sentinel sites for recent infection suggests that global TDR surveillance efforts and publication of findings require renewed emphasis.

60 APPLIED LIFE SCIENCES↗

The National Microbiome Data Collaborative: Enabling Microbiome Science

To harness the potential of microbiome science across the broad range of relevant disciplines, new approaches to data infrastructure and transdisciplinary collaboration are necessary. The National Microbiome Data Collaborative (NMDC) is a new initiative to support microbiome data exploration and discovery through a collaborative integrative data science ecosystem.

Wood-Charlson, Elisha M.↗