Detecting macroevolutionary genotype-phenotype associations using error-corrected rates of protein convergence.

On macroevolutionary timescales, extensive mutations and phylogenetic uncertainty mask the signals of genotype-phenotype associations underlying convergent evolution. To overcome this problem, we extended the widely used framework of non-synonymous to synonymous substitution rate ratios and developed the novel metric ωC, which measures the error-corrected convergence rate of protein evolution. While ωC distinguishes natural selection from genetic noise and phylogenetic errors in simulation and real examples, its accuracy allows an exploratory genome-wide search of adaptive molecular convergence without phenotypic hypothesis or candidate genes. Using gene expression data, we explored over 20 million branch combinations in vertebrate genes and identified the joint convergence of expression patterns and protein sequences with amino acid substitutions in functionally important sites, providing hypotheses on undiscovered phenotypes. We further extended our method with a heuristic algorithm to detect highly repetitive convergence among computationally non-trivial higher-order phylogenetic combinations. Our approach allows bidirectional searches for genotype-phenotype associations, even in lineages that diverged for hundreds of millions of years.

Phylodynamics of a regional SARS-CoV-2 rapid spreading event in Colorado in late 2020.

Since the initial reported discovery of SARS-CoV-2 in late 2019, genomic surveillance has been an important tool to understand its transmission and evolution. Here, we sought to describe the underlying regional phylodynamics before and during a rapid spreading event that was documented by surveillance protocols of the United States Air Force Academy (USAFA) in late October-November of 2020. We used replicate long-read sequencing on Colorado SARS-CoV-2 genomes collected July through November 2020 at the University of Colorado Anschutz Medical campus in Aurora and the United States Air Force Academy in Colorado Springs. Replicate sequencing allowed rigorous validation of variation and placement in a phylogenetic relatedness network. We focus on describing the phylodynamics of a lineage that likely originated in the local Colorado Springs community and expanded rapidly over the course of two months in an outbreak within the well-controlled environment of the United States Air Force Academy. Divergence estimates from sampling dates indicate that the SARS-CoV-2 lineage associated with this rapid expansion event originated in late October 2020. These results are in agreement with transmission pathways inferred by the United States Air Force Academy, and provide a window into the evolutionary process and transmission dynamics of a potentially dangerous but ultimately contained variant.

Integrating genomic and epidemiologic data to accelerate progress toward schistosomiasis elimination.

The global community has adopted ambitious goals to eliminate schistosomiasis as a public health problem, and new tools are needed to achieve them. Mass drug administration programs, for example, have reduced the burden of schistosomiasis, but the identification of hotspots of persistent and reemergent transmission threaten progress toward elimination and underscore the need to couple treatment with interventions that reduce transmission. Recent advances in DNA sequencing technologies make whole-genome sequencing a valuable and increasingly feasible option for population-based studies of complex parasites such as schistosomes. Here, we focus on leveraging genomic data to tailor interventions to distinct social and ecological circumstances. We consider two priority questions that can be addressed by integrating epidemiological, ecological, and genomic information: (1) how often do non-human host species contribute to human schistosome infection? and (2) what is the importance of locally acquired versus imported infections in driving transmission at different stages of elimination? These questions address processes that can undermine control programs, especially those that rely heavily on treatment with praziquantel. Until recently, these questions were difficult to answer with sufficient precision to inform public health decision-making. We review the literature related to these questions and discuss how whole-genome approaches can identify the geographic and taxonomic sources of infection, and how such information can inform context-specific efforts that advance schistosomiasis control efforts and minimize the risk of reemergence.

A genomic can of worms for schistosome host-specificity.

Understanding the genetic underpinnings of schistosome host preferences is critical. Luo et al. recently identified genes associated with intermediate and definitive host-switching based on a new chromosome-level genome for Schistosoma japonicum, population genetic comparisons, and follow-up experiments. This represents a guide to fully map-selected schistosome genes using population genetics.

Prospects for genomic surveillance for selection in schistosome parasites.

Schistosomiasis is a neglected tropical disease caused by multiple parasitic Schistosoma species, and which impacts over 200 million people globally, mainly in low- and middle-income countries. Genomic surveillance to detect evidence for natural selection in schistosome populations represents an emerging and promising approach to identify and interpret schistosome responses to ongoing control efforts or other environmental factors. Here we review how genomic variation is used to detect selection, how these approaches have been applied to schistosomes, and how future studies to detect selection may be improved. We discuss the theory of genomic analyses to detect selection, identify experimental designs for such analyses, and review studies that have applied these approaches to schistosomes. We then consider the biological characteristics of schistosomes that are expected to respond to selection, particularly those that may be impacted by control programs. Examples include drug resistance, host specificity, and life history traits, and we review our current understanding of specific genes that underlie them in schistosomes. We also discuss how inherent features of schistosome reproduction and demography pose substantial challenges for effective identification of these traits and their genomic bases. We conclude by discussing how genomic surveillance for selection should be designed to improve understanding of schistosome biology, and how the parasite changes in response to selection.

Selection for cooperativity causes epistasis predominately between native contacts and enables epistasis-based structure reconstruction.

Epistasis and cooperativity of folding both result from networks of energetic interactions in proteins. Epistasis results from energetic interactions among mutants, whereas cooperativity results from energetic interactions during folding that reduce the presence of intermediate states. The two concepts seem intuitively related, but it is unknown how they are related, particularly in terms of selection. To investigate their relationship, we simulated protein evolution under selection for cooperativity and separately under selection for epistasis. Strong selection for cooperativity created strong epistasis between contacts in the native structure but weakened epistasis between nonnative contacts. In contrast, selection for epistasis increased epistasis in both native and nonnative contacts and reduced cooperativity. Because epistasis can be used to predict protein structure only if it preferentially occurs in native contacts, this result indicates that selection for cooperativity may be key for predicting structure using epistasis. To evaluate this inference, we simulated the evolution of guanine nucleotide-binding protein (GB1) with and without cooperativity. With cooperativity, strong epistatic interactions clearly map out the native GB1 structure, while allowing the presence of intermediate states (low cooperativity) obscured the structure. This indicates that using epistasis measurements to reconstruct protein structure may be inappropriate for proteins with stable intermediates.

Population genomic analyses of schistosome parasites highlight critical challenges facing endgame elimination efforts.

Schistosomiasis persists in Asian regions despite aggressive elimination measures. To identify factors enabling continued parasite transmission, we performed reduced representation genome sequencing on Schistosoma japonicum miracidia collected across multiple years from transmission hotspots in Sichuan, China. We discovered strong geographic structure, suggesting that local, rather than imported, reservoirs are key sources of persistent infections in the region. At the village level, parasites collected after referral for praziquantel treatment are closely related to local pre-treatment populations. Schistosomes within villages are also highly related, suggesting that only a few parasites from a limited number of hosts drive re-infection. The close familial relationships among miracidia from different human hosts also implicate short transmission routes among humans. At the individual host level, genetic evidence indicates that multiple humans retained infections following referral for treatment. Our findings suggest that end-game schistosomiasis control measures should focus on completely extirpating local parasite reservoirs and confirming successful treatment of infected human hosts.

SARS-CoV-2 evolution during treatment of chronic infection.

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for virus infection through the engagement of the human ACE2 protein1 and is a major antibody target. Here we show that chronic infection with SARS-CoV-2 leads to viral evolution and reduced sensitivity to neutralizing antibodies in an immunosuppressed individual treated with convalescent plasma, by generating whole-genome ultra-deep sequences for 23 time points that span 101 days and using in vitro techniques to characterize the mutations revealed by sequencing. There was little change in the overall structure of the viral population after two courses of remdesivir during the first 57 days. However, after convalescent plasma therapy, we observed large, dynamic shifts in the viral population, with the emergence of a dominant viral strain that contained a substitution (D796H) in the S2 subunit and a deletion (ΔH69/ΔV70) in the S1 N-terminal domain of the spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype were reduced in frequency, before returning during a final, unsuccessful course of convalescent plasma treatment. In vitro, the spike double mutant bearing both ΔH69/ΔV70 and D796H conferred modestly decreased sensitivity to convalescent plasma, while maintaining infectivity levels that were similar to the wild-type virus.The spike substitution mutant D796H appeared to be the main contributor to the decreased susceptibility to neutralizing antibodies, but this mutation resulted in an infectivity defect. The spike deletion mutant ΔH69/ΔV70 had a twofold higher level of infectivity than wild-type SARS-CoV-2, possibly compensating for the reduced infectivity of the D796H mutation. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy, which is associated with the emergence of viral variants that show evidence of reduced susceptibility to neutralizing antibodies in immunosuppressed individuals.