Different Genes are Recruited During Convergent Evolution of Pregnancy and the Placenta.

The repeated evolution of the same traits in distantly related groups (convergent evolution) raises a key question in evolutionary biology: do the same genes underpin convergent phenotypes? Here, we explore one such trait, viviparity (live birth), which, qualitative studies suggest, may indeed have evolved via genetic convergence. There are >150 independent origins of live birth in vertebrates, providing a uniquely powerful system to test the mechanisms underpinning convergence in morphology, physiology, and/or gene recruitment during pregnancy. We compared transcriptomic data from eight vertebrates (lizards, mammals, sharks) that gestate embryos within the uterus. Since many previous studies detected qualitative similarities in gene use during independent origins of pregnancy, we expected to find significant overlap in gene use in viviparous taxa. However, we found no more overlap in uterine gene expression associated with viviparity than we would expect by chance alone. Each viviparous lineage exhibits the same core set of uterine physiological functions. Yet, contrary to prevailing assumptions about this trait, we find that none of the same genes are differentially expressed in all viviparous lineages, or even in all viviparous amniote lineages. Therefore, across distantly related vertebrates, different genes have been recruited to support the morphological and physiological changes required for successful pregnancy. We conclude that redundancies in gene function have enabled the repeated evolution of viviparity through recruitment of different genes from genomic "toolboxes", which are uniquely constrained by the ancestries of each lineage.

Linking Branch Lengths across Sets of Loci Provides the Highest Statistical Support for Phylogenetic Inference.

Evolution leaves heterogeneous patterns of nucleotide variation across the genome, with different loci subject to varying degrees of mutation, selection, and drift. In phylogenetics, the potential impacts of partitioning sequence data for the assignment of substitution models are well appreciated. In contrast, the treatment of branch lengths has received far less attention. In this study, we examined the effects of linking and unlinking branch-length parameters across loci or subsets of loci. By analyzing a range of empirical data sets, we find consistent support for a model in which branch lengths are proportionate between subsets of loci: gene trees share the same pattern of branch lengths, but form subsets that vary in their overall tree lengths. These models had substantially better statistical support than models that assume identical branch lengths across gene trees, or those in which genes form subsets with distinct branch-length patterns. We show using simulations and empirical data that the complexity of the branch-length model with the highest support depends on the length of the sequence alignment and on the numbers of taxa and loci in the data set. Our findings suggest that models in which branch lengths are proportionate between subsets have the highest statistical support under the conditions that are most commonly seen in practice. The results of our study have implications for model selection, computational efficiency, and experimental design in phylogenomics.

Accounting for Uncertainty in the Evolutionary Timescale of Green Plants Through Clock-Partitioning and Fossil Calibration Strategies.

Establishing an accurate evolutionary timescale for green plants (Viridiplantae) is essential to understanding their interaction and coevolution with the Earth's climate and the many organisms that rely on green plants. Despite being the focus of numerous studies, the timing of the origin of green plants and the divergence of major clades within this group remain highly controversial. Here, we infer the evolutionary timescale of green plants by analyzing 81 protein-coding genes from 99 chloroplast genomes, using a core set of 21 fossil calibrations. We test the sensitivity of our divergence-time estimates to various components of Bayesian molecular dating, including the tree topology, clock models, clock-partitioning schemes, rate priors, and fossil calibrations. We find that the choice of clock model affects date estimation and that the independent-rates model provides a better fit to the data than the autocorrelated-rates model. Varying the rate prior and tree topology had little impact on age estimates, with far greater differences observed among calibration choices and clock-partitioning schemes. Our analyses yield date estimates ranging from the Paleoproterozoic to Mesoproterozoic for crown-group green plants, and from the Ediacaran to Middle Ordovician for crown-group land plants. We present divergence-time estimates of the major groups of green plants that take into account various sources of uncertainty. Our proposed timeline lays the foundation for further investigations into how green plants shaped the global climate and ecosystems, and how embryophytes became dominant in terrestrial environments.

Simple and reliable protocol for identifying talented junior players in team sports using small-sided games.

We designed and tested a protocol for measuring the performance of individuals in small-sided soccer games. We tested our protocol on three different groups of youth players from elite Brazilian football academies. Players in each group played a series of 3v3 games, in which individuals were randomly assigned into new teams and against new opponents for each game. We calculated each individual's average individual goals scored, goals scored by teammates, goals conceded, and net team goals per game. Our protocol was consistent across days and repeatable across groups, with intraclass correlation coefficients (ICCs) of 0.57-0.69 for average net goals per game across testing days. Players could achieve high success by scoring goals or ensuring their team concede few goals. We also calculated the first and second dimension of a principal component analysis based on each player's number of goals scored, goals scored by teammates, and number of goals conceded per game. Players that were overall high performers had higher PC1 scores, while PC2 scores represented the type of contribution made by a player to overall performance. Positive PC2 values were indicative of high number of individual goals while negative values were associated with more goals from teammates and fewer conceded goals. Our design allows coaches and scouts to easily collect a robust metric of individual performance using randomly designed, small-sided games. We also provide simulations that allow one to apply our methodology for individual talent identification to other small-sided games in any team sport.

Increased diversification rates are coupled with higher rates of climate space exploration in Australian Acacia (Caesalpinioideae).

Australia is an excellent setting to explore relationships between climate change and diversification dynamics. Aridification since the Eocene has resulted in spectacular radiations within one or more Australian biomes. Acacia is the largest plant genus on the Australian continent, with around 1000 species, and is present in all biomes. We investigated the macroevolutionary dynamics of Acacia within climate space. We analysed phylogenetic and climatic data for 503 Acacia species to estimate a time-calibrated phylogeny and central climatic tendencies for BioClim layers from 132 000 herbarium specimens. Diversification rate heterogeneity and rates of climate space exploration were tested. We inferred two diversification rate increases, both associated with significantly higher rates of climate space exploration. Observed spikes in climate disparity within the Pleistocene correspond with onset of Pleistocene glacial-interglacial cycling. Positive time dependency in environmental disparity applies in the basal grade of Acacia, though climate space exploration rates were lower. Incongruence between rates of climate space exploration and disparity suggests different Acacia lineages have experienced different macroevolutionary processes. The second diversification rate increase is associated with a south-east Australian mesic lineage, suggesting adaptations to progressively aridifying environments and ability to transition into mesic environments contributed to Acacia's dominance across Australia.

Emergence of an evolutionary innovation: Gene expression differences associated with the transition between oviparity and viviparity.

Our understanding of the evolution of complex biological traits is greatly advanced by examining taxa with intermediate phenotypes. The transition from oviparity (egg-laying) to viviparity (live-bearing) has occurred independently in many animal lineages, but there are few phenotypic intermediates. The lizard Saiphos equalis exhibits bimodal reproduction, with some viviparous populations, and other oviparous populations with long egg-retention, a rare trait where most of embryonic development occurs inside the mother prior to late ovipositioning. We posit that oviparous S. equalis represent an intermediate form between "true" oviparity and viviparity. We used transcriptomics to compare uterine gene expression in these two phenotypes, and provide a molecular model for the genetic control and evolution of reproductive mode. Many genes are differentially expressed throughout the reproductive cycle of both phenotypes, which have clearly different gene expression profiles overall. The differentially expressed genes within oviparous and viviparous individuals have broadly similar biological functions putatively important for sustaining embryos, including uterine remodelling, respiratory gas and water exchange, and immune regulation. These functional similarities indicate either that long egg-retention is an exaptation for viviparity, or might reflect parallel evolution of similar gravidity-related changes in gene expression in long egg-retention oviparity. In contrast, gene expression changes across the reproductive cycle of long egg-retaining oviparous S. equalis are dramatically different from those of "true" oviparous skinks (such as Lampropholis guichenoti), supporting our assertion that oviparous S. equalis exhibit an intermediate phenotype between "true" oviparity and viviparity.

Paternally-biased gene expression follows kin-selected predictions in female honey bee embryos.

The Kinship Theory of Genomic Imprinting (KTGI) posits that, in species where females mate with multiple males, there is selection for a male to enhance the reproductive success of his offspring at the expense of other males and his mating partner. Reciprocal crosses between honey bee subspecies show parent-of-origin effects for reproductive traits, suggesting that males modify the expression of genes related to female function in their female offspring. This effect is likely to be greater in the Cape honey bee (Apis mellifera capensis), because a male's daughters have the unique ability to produce female offspring that can develop into reproductive workers or the next queen without mating. We generated reciprocal crosses between Capensis and another subspecies and used RNA-seq to identify transcripts that are over- or underexpressed in the embryos, depending on the parental origin of the gene. As predicted, 21 genes showed expression bias towards the Capensis father's allele in colonies with a Capensis father, with no such bias in the reciprocal cross. A further six genes showed a consistent bias towards expression of the father's allele across all eight colonies examined, regardless of the direction of the cross. Consistent with predictions of the KTGI, six of the 21 genes are associated with female reproduction. No gene consistently showed overexpression of the maternal allele.

Plastome sequences and exploration of tree-space help to resolve the phylogeny of riceflowers (Thymelaeaceae: Pimelea).

Data sets comprising small numbers of genetic markers are not always able to resolve phylogenetic relationships. This has frequently been the case in molecular systematic studies of plants, with many analyses being based on sequence data from only two or three chloroplast genes. An example of this comes from the riceflowers Pimelea Banks & Sol. ex Gaertn. (Thymelaeaceae), a large genus of flowering plants predominantly distributed in Australia. Despite the considerable morphological variation in the genus, low sequence divergence in chloroplast markers has led to the phylogeny of Pimelea remaining largely uncertain. In this study, we resolve the backbone of the phylogeny of Pimelea in comprehensive Bayesian and maximum-likelihood analyses of plastome sequences from 41 taxa. However, some relationships received only moderate to poor support, and the Pimelea clade contained extremely short internal branches. By using topology-clustering analyses, we demonstrate that conflicting phylogenetic signals can be found across the trees estimated from individual chloroplast protein-coding genes. A relaxed-clock dating analysis reveals that Pimelea arose in the mid-Miocene, with most divergences within the genus occurring during a subsequent rapid diversification. Our new phylogenetic estimate offers better resolution and is more strongly supported than previous estimates, providing a platform for future taxonomic revisions of both Pimelea and the broader subfamily. Our study has demonstrated the substantial improvements in phylogenetic resolution that can be achieved using plastome-scale data sets in plant molecular systematics.

Evaluating the Impact of Genomic Data and Priors on Bayesian Estimates of the Angiosperm Evolutionary Timescale.

The evolutionary timescale of angiosperms has long been a key question in biology. Molecular estimates of this timescale have shown considerable variation, being influenced by differences in taxon sampling, gene sampling, fossil calibrations, evolutionary models, and choices of priors. Here, we analyze a data set comprising 76 protein-coding genes from the chloroplast genomes of 195 taxa spanning 86 families, including novel genome sequences for 11 taxa, to evaluate the impact of models, priors, and gene sampling on Bayesian estimates of the angiosperm evolutionary timescale. Using a Bayesian relaxed molecular-clock method, with a core set of 35 minimum and two maximum fossil constraints, we estimated that crown angiosperms arose 221 (251-192) Ma during the Triassic. Based on a range of additional sensitivity and subsampling analyses, we found that our date estimates were generally robust to large changes in the parameters of the birth-death tree prior and of the model of rate variation across branches. We found an exception to this when we implemented fossil calibrations in the form of highly informative gamma priors rather than as uniform priors on node ages. Under all other calibration schemes, including trials of seven maximum age constraints, we consistently found that the earliest divergences of angiosperm clades substantially predate the oldest fossils that can be assigned unequivocally to their crown group. Overall, our results and experiments with genome-scale data suggest that reliable estimates of the angiosperm crown age will require increased taxon sampling, significant methodological changes, and new information from the fossil record. [Angiospermae, chloroplast, genome, molecular dating, Triassic.].

Estimating the number and assignment of clock models in analyses of multigene datasets.

MOTIVATION: Molecular-clock methods can be used to estimate evolutionary rates and timescales from DNA sequence data. However, different genes can display different patterns of rate variation across lineages, calling for the employment of multiple clock models. Selecting the optimal clock-partitioning scheme for a multigene dataset can be computationally demanding, but clustering methods provide a feasible alternative. We investigated the performance of different clustering methods using data from chloroplast genomes and data generated by simulation. RESULTS: Our results show that mixture models provide a useful alternative to traditional partitioning algorithms. We found only a small number of distinct patterns of among-lineage rate variation among chloroplast genes, which were consistent across taxonomic scales. This suggests that the evolution of chloroplast genes has been governed by a small number of genomic pacemakers. Our study also demonstrates that clustering methods provide an efficient means of identifying clock-partitioning schemes for genome-scale datasets. AVAILABILITY AND IMPLEMENTATION: The code and data sets used in this study are available online at https://github.com/sebastianduchene/pacemaker_clustering_methods CONTACT: sebastian.duchene@sydney.edu.au SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Biogeographic calibrations for the molecular clock.

Molecular estimates of evolutionary timescales have an important role in a range of biological studies. Such estimates can be made using methods based on molecular clocks, including models that are able to account for rate variation across lineages. All clock models share a dependence on calibrations, which enable estimates to be given in absolute time units. There are many available methods for incorporating fossil calibrations, but geological and climatic data can also provide useful calibrations for molecular clocks. However, a number of strong assumptions need to be made when using these biogeographic calibrations, leading to wide variation in their reliability and precision. In this review, we describe the nature of biogeographic calibrations and the assumptions that they involve. We present an overview of the different geological and climatic events that can provide informative calibrations, and explain how such temporal information can be incorporated into dating analyses.

Molecular systematics and biogeography of Logania R.Br. (Loganiaceae).

The angiosperm genus Logania R.Br. (Loganiaceae) is endemic to the mainland of Australia. A recent genetic study challenged the monophyly of Logania, suggesting that its two sections, Logania sect. Logania and Logania sect. Stomandra, do not group together. Additionally, the genus has a disjunct distribution, with a gap at the Nullarbor Plain in southern Australia. Therefore, Logania is a favourable candidate to gain insight into phylogenetic relationships and how these might intersect with Earth-history events. Our phylogenetic analyses of DNA sequences of two chloroplast markers (petD and rps16) showed that Logania sect. Logania and L. sect. Stomandra were each resolved as monophyletic, but the genus (as currently circumscribed) was not. Based on our Bayesian estimates of divergence times, the disjunct distributions within Logania sect. Stomandra could have been caused by flooding of the Eucla Basin. However, this biogeographical process cannot account for the distribution of Logania sect. Logania, with long-distance dispersal and establishment seeming more likely.

Human cytomegalovirus (CMV) dysregulates neurodevelopmental pathways in cerebral organoids.

Human cytomegalovirus (CMV) infection is the leading non-genetic aetiology of congenital malformation in developed countries, causing significant fetal neurological injury. This study investigated potential CMV pathogenetic mechanisms of fetal neural malformation using in vitro human cerebral organoids. Cerebral organoids were permissive to CMV replication, and infection dysregulated cellular pluripotency and differentiation pathways. Aberrant expression of dual-specificity tyrosine phosphorylation-regulated kinases (DYRK), sonic hedgehog (SHH), pluripotency, neurodegeneration, axon guidance, hippo signalling and dopaminergic synapse pathways were observed in CMV-infected organoids using immunofluorescence and RNA-sequencing. Infection with CMV resulted in dysregulation of 236 Autism Spectrum Disorder (ASD)-related genes (p = 1.57E-05) and pathways. This notable observation suggests potential links between congenital CMV infection and ASD. Using DisGeNET databases, 103 diseases related to neural malformation or mental disorders were enriched in CMV-infected organoids. Cytomegalovirus infection-related dysregulation of key cerebral cellular pathways potentially provides important, modifiable pathogenetic mechanisms for congenital CMV-induced neural malformation and ASD.

Continued improvement in the development of the SARS-CoV-2 whole genome sequencing proficiency testing program.

Application of whole genome sequencing (WGS) has allowed monitoring of the emergence of variants of concern (VOC) of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) globally. Genomic investigation of emerging variants and surveillance of clinical progress has reduced the public health impact of infection during the COVID-19 pandemic. These steps required developing and implementing a proficiency testing program (PTP), as WGS has been incorporated into routine reference laboratory practice. In this study, we describe how the PTP evaluated the capacity and capability of one New Zealand and 14 Australian public health laboratories to perform WGS of SARS-CoV-2 in 2022. The participants' performances in characterising a specimen panel of known SARS-CoV-2 isolates in the PTP were assessed based on: (1) genome coverage, (2) Pango lineage, and (3) sequence quality, with the choice of assessment metrics refined based on a previously reported assessment conducted in 2021. The participants' performances in 2021 and 2022 were also compared after reassessing the 2021 results using the more stringent metrics adopted in 2022. We found that more participants would have failed the 2021 assessment for all survey samples and a significantly higher fail rate per sample in 2021 compared to 2022. This study highlights the importance of choosing appropriate performance metrics to reflect better the laboratories' capacity to perform SARS-CoV-2 WGS, as was done in the 2022 PTP. It also displays the need for a PTP for WGS of SARS-CoV-2 to be available to public health laboratories ongoing, with continuous refinements in the design and provision of the PTP to account for the dynamic nature of the COVID-19 pandemic as SARS-CoV-2 continues to evolve.

Shrinking in the dark: Parallel endosymbiont genome erosions are associated with repeated host transitions to an underground life.

Microbial symbioses have had profound impacts on the evolution of animals. Conversely, changes in host biology may impact the evolutionary trajectory of symbionts themselves. Blattabacterium cuenoti is present in almost all cockroach species and enables hosts to subsist on a nutrient-poor diet. To investigate if host biology has impacted Blattabacterium at the genomic level, we sequenced and analyzed 25 genomes from Australian soil-burrowing cockroaches (Blaberidae: Panesthiinae), which have undergone at least seven separate subterranean, subsocial transitions from above-ground, wood-feeding ancestors. We find at least three independent instances of genome erosion have occurred in Blattabacterium strains exclusive to Australian soil-burrowing cockroaches. These shrinkages have involved the repeated inactivation of genes involved in amino acid biosynthesis and nitrogen recycling, the core role of Blattabacterium in the host-symbiont relationship. The most drastic of these erosions have occurred in hosts thought to have transitioned underground the earliest relative to other lineages, further suggestive of a link between gene loss in Blattabacterium and the burrowing behavior of hosts. As Blattabacterium is unable to fulfill its core function in certain host lineages, these findings suggest soil-burrowing cockroaches must acquire these nutrients from novel sources. Our study represents one of the first cases, to our knowledge, of parallel host adaptations leading to concomitant parallelism in their mutualistic symbionts, further underscoring the intimate relationship between these two partners.

Clinical, Genomic, and Immunological Characterization of RSV Surge in Sydney, Australia, 2022.

OBJECTIVES: The 2022 seasonal respiratory syncytial virus (RSV) epidemic in Sydney, Australia saw an unprecedented number of RSV detections. We aimed to characterize genomic and immunologic factors associated with the surge in RSV cases. METHODS: Whole genome sequences of RSV were generated from 264 RSV-infected infants and linked to case-matched clinical data from the 2022 southern hemisphere RSV season. We then performed an immunologic analysis of baseline RSV-specific humoral immunity in women of childbearing age before and throughout the coronavirus disease 2019 pandemic. RESULTS: Clinical analysis revealed a high burden of disease across patients of all health backgrounds. More than one-half of RSV-related health care visits by infants resulted in hospitalization, and one-quarter required high-flow respiratory support or a higher level of care. Viral phylogenetic analyses revealed that 2022 Sydney RSV sequences were closely related to viruses that had been circulating globally since 2017, including those detected in recent US outbreaks. Nonsynonymous mutations within the palivizumab and nirsevimab binding sites were detected at low frequencies. There was no difference in baseline RSV-neutralizing antibody titers between 2020 and 2022. CONCLUSIONS: Collectively, these findings suggest that neither the emergence of a novel RSV genotype nor hypothesized immune debt was associated with the surge of RSV cases and hospitalizations in 2022. Continued genomic and immunologic surveillance is required to further understand the factors driving outbreaks of RSV globally, and to inform guidelines for the rollout and ongoing use of recently developed immunotherapeutics and vaccines.

Persistence of a Frameshifting Deletion in SARS-CoV-2 ORF7a for the Duration of a Major Outbreak.

Australia experienced widespread COVID-19 outbreaks from infection with the SARS-CoV-2 Delta variant between June 2021 and February 2022. A 17-nucleotide frameshift-inducing deletion in ORF7a rapidly became represented at the consensus level (Delta-ORF7aΔ17del) in most Australian outbreak cases. Studies from early in the COVID-19 pandemic suggest that frameshift-inducing deletions in ORF7a do not persist for long in the population; therefore, Delta-ORF7aΔ17del genomes should have disappeared early in the Australian outbreak. In this study, we conducted a retrospective analysis of global Delta genomes to characterise the dynamics of Delta-ORF7aΔ17del over time, determined the frequency of all ORF7a deletions worldwide, and compared global trends with those of the Australian Delta outbreak. We downloaded all GISAID clade GK Delta genomes and scanned them for deletions in ORF7a. For each deletion we identified, we characterised its frequency, the number of countries it was found in, and how long it persisted. Of the 4,018,216 Delta genomes identified globally, 134,751 (~3.35%) possessed an ORF7a deletion, and ORF7aΔ17del was the most common. ORF7aΔ17del was the sole deletion in 28,014 genomes, of which 27,912 (~99.6%) originated from the Australian outbreak. During the outbreak, ~87% of genomes were Delta-ORF7aΔ17del, and genomes with this deletion were sampled until the outbreak's end. These data demonstrate that, contrary to suggestions early in the COVID-19 pandemic, genomes with frameshifting deletions in ORF7a can persist over long time periods. We suggest that the proliferation of Delta-ORF7aΔ17del genomes was likely a chance founder effect. Nonetheless, the frequency of ORF7a deletions in SARS-CoV-2 genomes worldwide suggests they might have some benefit for virus transmission.

Bioinformatic investigation of discordant sequence data for SARS-CoV-2: insights for robust genomic analysis during pandemic surveillance.

The COVID-19 pandemic has necessitated the rapid development and implementation of whole-genome sequencing (WGS) and bioinformatic methods for managing the pandemic. However, variability in methods and capabilities between laboratories has posed challenges in ensuring data accuracy. A national working group comprising 18 laboratory scientists and bioinformaticians from Australia and New Zealand was formed to improve data concordance across public health laboratories (PHLs). One effort, presented in this study, sought to understand the impact of the methodology on consensus genome concordance and interpretation. SARS-CoV-2 WGS proficiency testing programme (PTP) data were retrospectively obtained from the 2021 Royal College of Pathologists of Australasia Quality Assurance Programmes (RCPAQAP), which included 11 participating Australian laboratories. The submitted consensus genomes and reads from eight contrived specimens were investigated, focusing on discordant sequence data and findings were presented to the working group to inform best practices. Despite using a variety of laboratory and bioinformatic methods for SARS-CoV-2 WGS, participants largely produced concordant genomes. Two participants returned five discordant sites in a high-Cτ replicate, which could be resolved with reasonable bioinformatic quality thresholds. We noted ten discrepancies in genome assessment that arose from nucleotide heterogeneity at three different sites in three cell-culture-derived control specimens. While these sites were ultimately accurate after considering the participants' bioinformatic parameters, it presented an interesting challenge for developing standards to account for intrahost single nucleotide variation (iSNV). Observed differences had little to no impact on key surveillance metrics, lineage assignment and phylogenetic clustering, while genome coverage <90 % affected both. We recommend PHLs bioinformatically generate two consensus genomes with and without ambiguity thresholds for quality control and downstream analysis, respectively, and adhere to a minimum 90 % genome coverage threshold for inclusion in surveillance interpretations. We also suggest additional PTP assessment criteria, including primer efficiency, detection of iSNVs and minimum genome coverage of 90 %. This study underscores the importance of multidisciplinary national working groups in informing guidelines in real time for bioinformatic quality acceptance criteria. It demonstrates the potential for enhancing public health responses through improved data concordance and quality control in SARS-CoV-2 genomic analysis during pandemic surveillance.

Emergence and antibody evasion of BQ, BA.2.75 and SARS-CoV-2 recombinant sub-lineages in the face of maturing antibody breadth at the population level.

BACKGROUND: The Omicron era of the COVID-19 pandemic commenced at the beginning of 2022 and whilst it started with primarily BA.1, it was latter dominated by BA.2 and the related sub-lineage BA.5. Following resolution of the global BA.5 wave, a diverse grouping of Omicron sub-lineages emerged derived from BA.2, BA.5 and recombinants thereof. Whilst emerging from distinct lineages, all shared similar changes in the Spike glycoprotein affording them an outgrowth advantage through evasion of neutralising antibodies. METHODS: Over the course of 2022, we monitored the potency and breadth of antibody neutralization responses to many emerging variants in the Australian community at three levels: (i) we tracked over 420,000 U.S. plasma donors over time through various vaccine booster roll outs and Omicron waves using sequentially collected IgG pools; (ii) we mapped the antibody response in individuals using blood from stringently curated vaccine and convalescent cohorts. (iii) finally we determine the in vitro efficacy of clinically approved therapies Evusheld and Sotrovimab. FINDINGS: In pooled IgG samples, we observed the maturation of neutralization breadth to Omicron variants over time through continuing vaccine and infection waves. Importantly, in many cases, we observed increased antibody breadth to variants that were yet to be in circulation. Determination of viral neutralization at the cohort level supported equivalent coverage across prior and emerging variants with isolates BQ.1.1, XBB.1, BR.2.1 and XBF the most evasive. Further, these emerging variants were resistant to Evusheld, whilst increasing neutralization resistance to Sotrovimab was restricted to BQ.1.1 and XBF. We conclude at this current point in time that dominant variants can evade antibodies at levels equivalent to their most evasive lineage counterparts but sustain an entry phenotype that continues to promote an additional outgrowth advantage. In Australia, BR.2.1 and XBF share this phenotype and, in contrast to global variants, are uniquely dominant in this region in the later months of 2022. INTERPRETATION: Whilst the appearance of a diverse range of omicron lineages has led to primary or partial resistance to clinically approved monoclonal antibodies, the maturation of the antibody response across both cohorts and a large donor pools importantly observes increasing breadth in the antibody neutralisation responses over time with a trajectory that covers both current and known emerging variants. FUNDING: This work was primarily supported by Australian Medical Foundation research grants MRF2005760 (SGT, GM & WDR), Medical Research Future Fund Antiviral Development Call grant (WDR), the New South Wales Health COVID-19 Research Grants Round 2 (SGT & FB) and the NSW Vaccine Infection and Immunology Collaborative (VIIM) (ALC). Variant modeling was supported by funding from SciLifeLab's Pandemic Laboratory Preparedness program to B.M. (VC-2022-0028) and by the European Union's Horizon 2020 research and innovation programme under grant agreement no. 101003653 (CoroNAb) to B.M.