Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone

CpG-creating mutations are costly in many human viruses.

Mutations can occur throughout the virus genome and may be beneficial, neutral or deleterious. We are interested in mutations that yield a C next to a G, producing CpG sites. CpG sites are rare in eukaryotic and viral genomes. For the eukaryotes, it is thought that CpG sites are rare because they are prone to mutation when methylated. In viruses, we know less about why CpG sites are rare. A previous study in HIV suggested that CpG-creating transition mutations are more costly than similar non-CpG-creating mutations. To determine if this is the case in other viruses, we analyzed the allele frequencies of CpG-creating and non-CpG-creating mutations across various strains, subtypes, and genes of viruses using existing data obtained from Genbank, HIV Databases, and Virus Pathogen Resource. Our results suggest that CpG sites are indeed costly for most viruses. By understanding the cost of CpG sites, we can obtain further insights into the evolution and adaptation of viruses

CpG-creating mutations are costly in many human viruses

Mutations can occur throughout the virus genome and may be beneficial, neutral or deleterious. We are interested in mutations that yield a C next to a G, producing CpG sites. CpG sites are rare in eukaryotic and viral genomes. For the eukaryotes, it is thought that CpG sites are rare because they are prone to mutation when methylated. In viruses, we know less about why CpG sites are rare. A previous study in HIV suggested that CpG-creating transition mutations are more costly than similar non-CpG-creating mutations. To determine if this is the case in other viruses, we analyzed the allele frequencies of CpG-creating and non-CpG-creating mutations across various strains, subtypes, and genes of viruses using existing data obtained from Genbank, HIV Databases, and Virus Pathogen Resource. Our results suggest that CpG sites are indeed costly for most viruses. By understanding the cost of CpG sites, we can obtain further insights into the evolution and adaptation of viruses.ISSN:0269-7653ISSN:1573-847

Ten simple rules for an inclusive summer coding program for non-computer-science undergraduates.

Since 2015, we have run a free 9-week summer program that provides non-computer science (CS) undergraduates at San Francisco State University (SFSU) with experience in coding and doing research. Undergraduate research experiences remain very limited at SFSU and elsewhere, so the summer program provides opportunities for many more students beyond the mentoring capacity of our university laboratories. In addition, we were concerned that many students from historically underrepresented (HU) groups may be unable to take advantage of traditional summer research programs because these programs require students to relocate or be available full time, which is not feasible for students who have family, work, or housing commitments. Our program, which is local and part-time, serves about 5 times as many students as a typical National Science Foundation (NSF) Research Experiences for Undergraduates (REU) program, on a smaller budget. Based on our experiences, we present 10 simple rules for busy faculty who want to create similar programs to engage non-CS HU undergraduates in computational research. Note that while some of the strategies we implement are based on evidence-based publications in the social sciences or education research literature, the original suggestions we make here are based on our trial-and-error experiences, rather than formal hypothesis testing

CanMars mission Science Team operational results: implications for operations and the sample selection process for Mars Sample Return (MSR)

The CanMars Mars sample return (MSR) analogue mission was conducted as a field and operational test for the Mars 2020 sample cache rover mission and was the most realistic known MSR rover analogue mission to-date. A rover — similar in scale to that of rover planned for NASA's Mars 2020 mission — was deployed to a scientifically relevant Mars-analogue sedimentary field site with remote mission operations conducted at the University of Western Ontario, Canada; the mission aim was to inform on best practices and optimal approaches for sample acquisition modeled on the Mars 2020 rover mission. The daily operational procedures of the CanMars Science Team were modeled on those of current missions (i.e., Mars Science Laboratory tactical operations), serving as a study of known operational workflows and as a testbed for new approaches. This paper reports on the operational results of CanMars with best-practice recommendations. CanMars was designed as a Mars 2020 mock mission and thus carried similar science objectives; these included (1) advancing the understanding of the habitability potential of a subaqueous sedimentary environment through identifying, characterizing, and caching drilled samples containing high organic carbon (as a proxy for preserved ancient biosignatures) and (2) advancing the understanding of the history of water at the site. The in situ science investigations needed to address these science objectives were guided by the Mars Exploration Program Analysis Group goals. Effective and efficient Science Team operational procedures were developed – and many lessons were documented – through daily tactical planning and science investigations employed to meet the sample acquisition goals. In addition to the documentation of the CanMars operational procedures, this paper provides a brief summary of the science results from CanMars with a focus on recommendations for future analogue missions and planetary sample return flight missions, providing specific value to operational procedures for the Mars 2020 rover mission

Institutional Reforms to Enhance Urban Water Infrastructure with Climate Change Uncertainty

Climate change adds another layer of uncertainty to the complex issue of urban water infrastructure provision. Current institutional configurations surrounding infrastructure investments are deemed inflexible and ill-equipped to deal with climate uncertainty. This paper evaluates the regulatory and planning frameworks surrounding the urban water infrastructure provision in Victoria. Regulatory inflexibility, lack of clarity in the objectives of the water agencies and opaque supply augmentation policies constrain water businesses from making flexible infrastructure decisions. Future reforms need to focus on clarifying roles and objectives of water agencies, removing barriers to supply augmentation options including inter-sectoral transfers and a regulatory model that embeds flexibility in infrastructure decision processes

The CanMars Mars Sample Return analogue mission

The return of samples from known locations on Mars is among the highest priority goals of the international planetary science community. A possible scenario for Mars Sample Return (MSR) is a series of 3 missions: sample cache, fetch, and retrieval. The NASA Mars 2020 mission represents the first cache mission and was the focus of the CanMars analogue mission described in this paper. The major objectives for CanMars included comparing the accuracy of selecting samples remotely using rover data versus a traditional human field party, testing the efficiency of remote science operations with periodic pre-planned strategic observations (Strategic Traverse Days), assessing the utility of realistic autonomous science capabilities to the remote science team, and investigating the factors that affect the quality of sample selection decision-making in light of returned sample analysis. CanMars was conducted over two weeks in November 2015 and continued over three weeks in October and November 2016 at an analogue site near Hanksville, Utah, USA, that was unknown to the Mission Control Team located at the University of Western Ontario (Western) in London, Ontario, Canada. This operations architecture for CanMars was based on the Phoenix and Mars Exploration Rover missions together with previous analogue missions led by Western with the Mission Control Team being divided into Planning and Science sub-teams. In advance of the 2015 operations, the Science Team used satellite data, chosen to mimic datasets available from Mars-orbiting instruments, to produce a predictive geological map for the landing ellipse and a set of hypotheses for the geology and astrobiological potential of the landing site. The site was proposed to consist of a series of weakly cemented multi-coloured sedimentary rocks comprising carbonates, sulfates, and clays, and sinuous ridges with a resistant capping unit, interpreted as inverted paleochannels. Both the 2015 CanMars mission, which achieved 11 sols of operations, and the first part of the 2016 mission (sols 12–21), were conducted with the Mars Exploration Science Rover (MESR) and a series of integrated and hand-held instruments designed to mimic the payload of the Mars 2020 rover. Part 2 of the 2016 campaign (sols 22–39) was implemented without the MESR rover and was conducted exclusively by the field team as a Fast Motion Field Test (FMFT) with hand-carried instruments and with the equivalent of three sols of operations being executed in a single actual day. A total of 8 samples were cached during the 39 sols from which the Science Team prioritized 3 for “return to Earth”. Various science autonomy capabilities, based on flight-proven or near-future techniques intended for actual rover missions, were tested throughout the 2016 CanMars activities, with autonomous geological classification and targeting and autonomous pointing refinement being used extensively during the FMFT. Blind targeting, contingency sequencing, and conditional sequencing were also employed. Validation of the CanMars cache mission was achieved through various methods and approaches. The use of dedicated documentarians in mission control provided a detailed record of how and why decisions were made. Multiple separate field validation exercises employing humans using traditional geological techniques were carried out. All 8 of the selected samples plus a range of samples from the landing site region, collected out-of-simulation, have been analysed using a range of laboratory analytical techniques. A variety of lessons learned for both future analogue missions and planetary exploration missions are provided, including: dynamic collaboration between the science and planning teams as being key for mission success; the more frequent use of spectrometers and micro-imagers having remote capabilities rather than contact instruments; the utility of strategic traverse days to provide additional time for scientific discussion and meaningful interpretation of the data; the benefit of walkabout traverse strategies along with multi-sol plans with complex decisions trees to acquire a large amount of contextual data; and the availability of autonomous geological targeting, which enabled complex multi-sol plans gathering large suites of geological and geochemical survey data. Finally, the CanMars MSR activity demonstrated the utility of analogue missions in providing opportunities to engage and educate children and the public, by providing tangible hands-on linkages between current robotic missions and future human space missions. Public education and outreach was a priority for CanMars and a dedicated lead coordinated a strong presence on social media (primarily Twitter and Facebook), articles in local, regional, and national news networks, and interaction with the local community in London, Ontario. A further core objective of CanMars was to provide valuable learning opportunities to students and post-doctoral fellows in preparation for future planetary exploration missions. A learning goals survey conducted at the end of the 2016 activities had 90% of participants “somewhat agreeing” or “strongly agreeing” that participation in the mission has helped them to increase their understanding of the four learning outcomes

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic data sets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and to the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al.,2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than three-fold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone