Feasibility and lessons learned on remote trial implementation from TestBoston, a fully remote, longitudinal, large-scale COVID-19 surveillance study.

Longitudinal clinical studies traditionally require in-person study visits which are well documented to pose barriers to participation and contribute challenges to enrolling representative samples. Remote trial models may reduce barriers to research engagement, improve retention, and reach a more representative cohort. As remote trials become more common following the COVID-19 pandemic, a critical evaluation of this approach is imperative to optimize this paradigm shift in research. The TestBoston study was launched to understand prevalence and risk factors for COVID-19 infection in the greater Boston area through a fully remote home-testing model. Participants (adults, within 45 miles of Boston, MA) were recruited remotely from patient registries at Brigham and Women's Hospital and the general public. Participants were provided with monthly and "on-demand" at-home SARS-CoV-2 RT-PCR and antibody testing using nasal swab and dried blood spot self-collection kits and electronic surveys to assess symptoms and risk factors for COVID-19 via an online dashboard. Between October 2020 and January 2021, we enrolled 10,289 participants reflective of Massachusetts census data. Mean age was 47 years (range 18-93), 5855 (56.9%) were assigned female sex at birth, 7181(69.8%) reported being White non-Hispanic, 952 (9.3%) Hispanic/Latinx, 925 (9.0%) Black, 889 (8.6%) Asian, and 342 (3.3%) other and/or more than one race. Lower initial enrollment among Black and Hispanic/Latinx individuals required an adaptive approach to recruitment, leveraging connections to the medical system, coupled with community partnerships to ensure a representative cohort. Longitudinal retention was higher among participants who were White non-Hispanic, older, working remotely, and with lower socioeconomic vulnerability. Implementation highlighted key differences in remote trial models as participants independently navigate study milestones, requiring a dedicated participant support team and robust technology platforms, to reduce barriers to enrollment, promote retention, and ensure scientific rigor and data quality. Remote clinical trial models offer tremendous potential to engage representative cohorts, scale biomedical research, and promote accessibility by reducing barriers common in traditional trial design. Barriers and burdens within remote trials may be experienced disproportionately across demographic groups. To maximize engagement and retention, researchers should prioritize intensive participant support, investment in technologic infrastructure and an adaptive approach to maximize engagement and retention.

Conflict and its relationship to climate variability in Sub-Saharan Africa.

Deviations in rainfall duration and timing are expected to have wide-ranging impacts for people in affected areas. One of these impacts is the potential for increased levels of conflict and accordingly, researchers are examining the relationship between climate variability and conflict. Thus far, there is a lack of consensus on the direction of this relationship. We contribute to the climate variability and conflict literature by incorporating Markov transitional probabilities into panel logit models to analyze how monthly deviations in rainfall affect the likelihood that a grid cell transitions to an above average level of conflict in Sub-Saharan Africa. To control for differences in seasons across the continent, we model this relationship for each of the regions of Sub-Saharan Africa separately - East, Central, West, and Southern. We find significant seasonal and regional effects between rainfall and the probability that a grid cell transitions from a state of peace to a state of conflict. In particular, above average rainfall is associated with a higher likelihood of transitioning into conflict during the dry season. Further, each region has specific months-primarily those associated with prime crop harvest periods-where variations in rainfall significantly influence conflict. We also find regional variations in the linkage between rainfall and conflict type related to the types of conflict that predominate in particular regions of Sub- Saharan Africa. These findings are important for policymakers because they suggest additional law enforcement and/or peacekeeping resources may be needed in times of above average rainfall. Policies that provide financial support for farmers or other sectors, such as mining, that are impacted by rainfall patterns may also be a useful strategy for conflict mitigation.

GeNets: a unified web platform for network-based genomic analyses.

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.

An improved canine genome and a comprehensive catalogue of coding genes and non-coding transcripts.

The domestic dog, Canis familiaris, is a well-established model system for mapping trait and disease loci. While the original draft sequence was of good quality, gaps were abundant particularly in promoter regions of the genome, negatively impacting the annotation and study of candidate genes. Here, we present an improved genome build, canFam3.1, which includes 85 MB of novel sequence and now covers 99.8% of the euchromatic portion of the genome. We also present multiple RNA-Sequencing data sets from 10 different canine tissues to catalog ∼175,000 expressed loci. While about 90% of the coding genes previously annotated by EnsEMBL have measurable expression in at least one sample, the number of transcript isoforms detected by our data expands the EnsEMBL annotations by a factor of four. Syntenic comparison with the human genome revealed an additional ∼3,000 loci that are characterized as protein coding in human and were also expressed in the dog, suggesting that those were previously not annotated in the EnsEMBL canine gene set. In addition to ∼20,700 high-confidence protein coding loci, we found ∼4,600 antisense transcripts overlapping exons of protein coding genes, ∼7,200 intergenic multi-exon transcripts without coding potential, likely candidates for long intergenic non-coding RNAs (lincRNAs) and ∼11,000 transcripts were reported by two different library construction methods but did not fit any of the above categories. Of the lincRNAs, about 6,000 have no annotated orthologs in human or mouse. Functional analysis of two novel transcripts with shRNA in a mouse kidney cell line altered cell morphology and motility. All in all, we provide a much-improved annotation of the canine genome and suggest regulatory functions for several of the novel non-coding transcripts.

A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries.

Genome targeting methods enable cost-effective capture of specific subsets of the genome for sequencing. We present here an automated, highly scalable method for carrying out the Solution Hybrid Selection capture approach that provides a dramatic increase in scale and throughput of sequence-ready libraries produced. Significant process improvements and a series of in-process quality control checkpoints are also added. These process improvements can also be used in a manual version of the protocol.

A scalable, fully automated process for construction of sequence-ready barcoded libraries for 454.

We present an automated, high throughput library construction process for 454 technology. Sample handling errors and cross-contamination are minimized via end-to-end barcoding of plasticware, along with molecular DNA barcoding of constructs. Automation-friendly magnetic bead-based size selection and cleanup steps have been devised, eliminating major bottlenecks and significant sources of error. Using this methodology, one technician can create 96 sequence-ready 454 libraries in 2 days, a dramatic improvement over the standard method.

Creatine monohydrate and conjugated linoleic acid improve strength and body composition following resistance exercise in older adults.

Aging is associated with lower muscle mass and an increase in body fat. We examined whether creatine monohydrate (CrM) and conjugated linoleic acid (CLA) could enhance strength gains and improve body composition (i.e., increase fat-free mass (FFM); decrease body fat) following resistance exercise training in older adults (>65 y). Men (N = 19) and women (N = 20) completed six months of resistance exercise training with CrM (5g/d)+CLA (6g/d) or placebo with randomized, double blind, allocation. Outcomes included: strength and muscular endurance, functional tasks, body composition (DEXA scan), blood tests (lipids, liver function, CK, glucose, systemic inflammation markers (IL-6, C-reactive protein)), urinary markers of compliance (creatine/creatinine), oxidative stress (8-OH-2dG, 8-isoP) and bone resorption (Nu-telopeptides). Exercise training improved all measurements of functional capacity (P<0.05) and strength (P<0.001), with greater improvement for the CrM+CLA group in most measurements of muscular endurance, isokinetic knee extension strength, FFM, and lower fat mass (P<0.05). Plasma creatinine (P<0.05), but not creatinine clearance, increased for CrM+CLA, with no changes in serum CK activity or liver function tests. Together, this data confirms that supervised resistance exercise training is safe and effective for increasing strength in older adults and that a combination of CrM and CLA can enhance some of the beneficial effects of training over a six-month period. Trial Registration. ClinicalTrials.gov NCT00473902.

Human chromosome 11 DNA sequence and analysis including novel gene identification.

Chromosome 11, although average in size, is one of the most gene- and disease-rich chromosomes in the human genome. Initial gene annotation indicates an average gene density of 11.6 genes per megabase, including 1,524 protein-coding genes, some of which were identified using novel methods, and 765 pseudogenes. One-quarter of the protein-coding genes shows overlap with other genes. Of the 856 olfactory receptor genes in the human genome, more than 40% are located in 28 single- and multi-gene clusters along this chromosome. Out of the 171 disorders currently attributed to the chromosome, 86 remain for which the underlying molecular basis is not yet known, including several mendelian traits, cancer and susceptibility loci. The high-quality data presented here--nearly 134.5 million base pairs representing 99.8% coverage of the euchromatic sequence--provide scientists with a solid foundation for understanding the genetic basis of these disorders and other biological phenomena.

DNA sequence and analysis of human chromosome 18.

Chromosome 18 appears to have the lowest gene density of any human chromosome and is one of only three chromosomes for which trisomic individuals survive to term. There are also a number of genetic disorders stemming from chromosome 18 trisomy and aneuploidy. Here we report the finished sequence and gene annotation of human chromosome 18, which will allow a better understanding of the normal and disease biology of this chromosome. Despite the low density of protein-coding genes on chromosome 18, we find that the proportion of non-protein-coding sequences evolutionarily conserved among mammals is close to the genome-wide average. Extending this analysis to the entire human genome, we find that the density of conserved non-protein-coding sequences is largely uncorrelated with gene density. This has important implications for the nature and roles of non-protein-coding sequence elements.

The genome of M. acetivorans reveals extensive metabolic and physiological diversity.

Methanogenesis, the biological production of methane, plays a pivotal role in the global carbon cycle and contributes significantly to global warming. The majority of methane in nature is derived from acetate. Here we report the complete genome sequence of an acetate-utilizing methanogen, Methanosarcina acetivorans C2A. Methanosarcineae are the most metabolically diverse methanogens, thrive in a broad range of environments, and are unique among the Archaea in forming complex multicellular structures. This diversity is reflected in the genome of M. acetivorans. At 5,751,492 base pairs it is by far the largest known archaeal genome. The 4524 open reading frames code for a strikingly wide and unanticipated variety of metabolic and cellular capabilities. The presence of novel methyltransferases indicates the likelihood of undiscovered natural energy sources for methanogenesis, whereas the presence of single-subunit carbon monoxide dehydrogenases raises the possibility of nonmethanogenic growth. Although motility has not been observed in any Methanosarcineae, a flagellin gene cluster and two complete chemotaxis gene clusters were identified. The availability of genetic methods, coupled with its physiological and metabolic diversity, makes M. acetivorans a powerful model organism for the study of archaeal biology. [Sequence, data, annotations and analyses are available at http://www-genome.wi.mit.edu/.]