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Biology subjects

Janzen, G. M.

Publications and source records attributed to Janzen, G. M..

7 recordsLinked to original sources

Sources and sinks of influenza A virus genomic diversity in swine from 2009 to 2022 in the United States

Influenza A virus (IAV) in swine in the U.S. is surveilled to monitor genetic evolution to inform intervention efforts and aid pandemic preparedness. We describe data from the U.S. Department of Agriculture National Surveillance Plan for Influenza A Virus in Pigs from 2009 to 2022. Clinical respiratory cases were subtyped followed by sequencing of hemagglutinin (HA) and neuraminidase (NA), and a subset of viruses were whole genome sequenced. Phylogenetic analysis identified geographic and temporal IAV reassortment hotspots. Regions acting as IAV genomic diversity sources or sinks were quantified, and dissemination was qualified and modeled. The dominant IAV clades were H1N2 (1B.2.1), H3N2 (1990.4.a), and H1N1 (H1-1A.3.3.3-c3). Internal genes were classified as triple-reassortant (T) or pandemic 2009 (P), and three genome constellations represented 73.5% of detections across the last two years. In some years, the distribution of IAV diversity was so narrowly distributed that it presented a statistical signal associated with local adaptation. We also demonstrated that the source of most IAV genomic diversity was in Midwest states (IL, MO, IA), and while this was correlated with swine inventory, the emergence and persistence of diversity was tied to swine transport across the U.S. The continued regional detection of unique HA, NA, and genome constellations provides support for targeted interventions to improve animal health and enhance pandemic preparedness. ImportanceVariation in the genetic diversity of influenza A virus (IAV) in swine through time and between regions impacts control efforts. This study quantified the genomic diversity of swine IAV collected from 2009-2022 at regional and national levels and modeled sources and sinks of that diversity. Seasonal patterns of IAV transmission were observed, and some locations contributed disproportionately to the emergence of genomic diversity. Minor groups of viruses had the potential to disseminate across the U.S. with animal movement. The identification of these patterns demonstrates the importance of a robust surveillance system to inform vaccine updates that reflect regional patterns of genetic diversity. We show how preemptive interventions in swine IAV diversity hubs could reduce reassortment and the emergence of novel genomic diversity, and how these efforts are likely to reduce the transmission of swine IAV within swine and between swine and humans.

microbiology↗

The utility of environmental data from traditionalvarieties for climate-adaptive maize breeding

Maintaining crop yields in the face of climate change is a major challenge facing plant breeding today. Considerable genetic variation exists in ex-situ collections of traditional crop varieties, but identifying adaptive loci and testing their agronomic performance in large populations in field trials is costly. Here, we study the utility of climate and genomic data for identifying promising traditional varieties to incorporate into maize breeding programs. To do so, we use phenotypic data from more than 4,000 traditional maize varieties grown in 13 trial environments. First, we used genotype data to predict environmental characteristics of germplasm collections to identify varieties that may be locally adapted to target environments. Second, we used environmental GWAS (envGWAS) to identify genetic loci associated with historical divergence along climatic gradients, such as the putative heat shock protein hsftf9 and the large-scale adaptive inversion Inv4m. Finally, we compared the value of environmental data and envGWAS-prioritized loci to genomic data for prioritizing traditional varieties. We find that maize yield traits are best predicted by genomic data, and that envGWAS-identified variants provide little direct predictive information over patterns of population structure. We also find that adding environment-of-origin variables does not improve yield component prediction over kinship or population structure alone, but could be a useful selection proxy in the absence of sequencing data. While our results suggest little utility of environmental data for selecting traditional varieties to incorporate in breeding programs, environmental GWAS is nonetheless a potentially powerful approach to identify individual novel loci for maize improvement, especially when coupled with high density genotyping.

evolutionary biology↗

Active surveillance for influenza A virus in swine reveals within-farm reassortment and cocirculation of distinct subtypes and genetic clades

Influenza A virus (IAV) is one of the three most frequently detected respiratory pathogens in swine. A passive IAV in swine surveillance system in the United States (U.S.) provides aggregated national metrics to quantify spatial and temporal changes in genetic diversity. However, swine production is not homogenous: production systems vary in size and management strategies that affect the transmission and evolution of IAV. To assess the impact of fine-scale variation in swine production on IAV transmission, we conducted active surveillance on sow farms and linked nurseries from 4 U.S. production systems for up to 14 monthly collections. From IAV-positive samples, we obtained 85 complete HA sequences, and of these, we successfully assembled 62 whole genomes with associated epidemiological information. To infer transmission and evolution, we conducted Bayesian phylodynamic analyses and detected six genetic clades from four HA lineages: the H1 1A classical swine, the H1 1B human-seasonal, and the H3 2010.1 and 1990.4 lineages. The 1B and H3 1990.4 strains showed evidence of transmission from sow farm to nursery. In contrast, 1A and H3 2010.1 viruses were detected in nurseries without detection in a linked sow farm. We also detected seven separate human-to- swine transmission events in the H1N1 pandemic clade (1A.3.3.2) in sow and nursery sites. Our data demonstrated that nursery sites were infected with IAV that was both linked and unlinked to the sow farm. These data suggest that control efforts may be impacted by subclinical IAV transmission in the breeding herd, the mixing of sow farm sources at the nursery, regional spread of new strains, and human-to-swine transmission. Regular surveillance activities within production systems provide the ability to match vaccine components to circulating diversity, thereby minimizing the opportunity for novel reassorted viruses to emerge and impact animal health.

bioinformatics↗

Emergence and interstate spread of highly pathogenic avian influenza A(H5N1) in dairy cattle

Highly pathogenic avian influenza (HPAI) viruses cross species barriers and have the potential to cause pandemics. In North America, HPAI A(H5N1) viruses related to the goose/Guangdong 2.3.4.4b hemagglutinin phylogenetic clade have infected wild birds, poultry, and mammals. Our genomic analysis and epidemiological investigation showed that a reassortment event in wild bird populations preceded a single wild bird-to-cattle transmission episode. The movement of asymptomatic cattle has likely played a role in the spread of HPAI within the United States dairy herd. Some molecular markers in virus populations were detected at low frequency that may lead to changes in transmission efficiency and phenotype after evolution in dairy cattle. Continued transmission of H5N1 HPAI within dairy cattle increases the risk for infection and subsequent spread of the virus to human populations.

microbiology↗

Demonstration of local adaptation of maize landraces by reciprocal transplantation

Populations are locally adapted when they exhibit higher fitness than foreign populations in their native habitat. Maize landrace adaptations to highland and lowland conditions are of interest to researchers and breeders. To determine the prevalence and strength of local adaptation in maize landraces, we performed a reciprocal transplant experiment across an elevational gradient in Mexico. We grew 120 landraces, grouped into four populations (Mexican Highland, Mexican Lowland, South American Highland, South American Lowland), in Mexican highland and lowland common gardens and collected phenotypes relevant to fitness, as well as reported highland-adaptive traits such as anthocyanin pigmentation and macrohair density. 67k DArTseq markers were generated from field specimens to allow comparison between phenotypic patterns and population genetic structure. We found phenotypic patterns consistent with local adaptation, though these patterns differ between the Mexican and South American populations. While population genetic structure largely recapitulates drift during post-domestication dispersal, landrace phenotypes reflect adaptations to native elevation. Quantitative trait QST was greater than neutral FST for many traits, signaling divergent directional selection between pairs of populations. All populations exhibited higher fitness metric values when grown at their native elevation, and Mexican landraces had higher fitness than South American landraces when grown in our Mexican sites. Highland populations expressed generally higher anthocyanin pigmentation than lowland populations, and more so in the highland site than in the lowland site. Macrohair density was largely non-plastic, and Mexican landraces and highland landraces were generally more pilose. Analysis of{delta} 13C indicated that lowland populations may have lower WUE. Each population demonstrated garden-specific correlations between highland trait expression and fitness, with stronger positive correlations in the highland site. These results give substance to the long-held presumption of local adaptation of New World maize landraces to elevation and other environmental variables across North and South America.

evolutionary biology↗

Teosinte introgression modulates phosphatidylcholine levels and induces early maize flowering time

Native Americans domesticated maize (Zea mays ssp. mays) from lowland teosinte parviglumis (Zea mays ssp.parviglumis) in the warm Mexican southwest and brought it to the highlands of Mexico and South America where it was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature and phosphorus availability, and have been suggested to influence flowering time. Here, we combined linkage mapping with genome scans to identify High PhosphatidylCholine 1 (HPC1), a gene that encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The highland maize HPC1 variant resulted in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis across HPC1 orthologs indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we showed that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from the Northern US, Canada and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time.

plant biology↗

Single-gene resolution of locally adaptive genetic variation in Mexican maize

Threats to crop production due to climate change are one of the greatest challenges facing plant breeders today. While considerable adaptive variation exists in traditional landraces, natural populations of crop wild relatives, and ex situ germplasm collections, separating adaptive alleles from linked deleterious variants that impact agronomic traits is challenging and has limited the utility of these diverse germplasm resources. Modern genome editing techniques such as CRISPR offer a potential solution by targeting specific alleles for transfer to new backgrounds, but such methods require a higher degree of precision than traditional mapping approaches can achieve. Here we present a high-resolution genome-wide association analysis to identify loci exhibiting adaptive patterns in a large panel of more than 4500 traditional maize landraces representing the breadth of genetic diversity of maize in Mexico. We evaluate associations between genotype and plant performance in 13 common gardens across a range of environments, identifying hundreds of candidate genes underlying genotype by environment interaction. We further identify genetic associations with environment across Mexico and show that such loci are associated with variation in yield and flowering time in our field trials and predict performance in independent drought trials. Our results indicate that the variation necessary to adapt crops to changing climate exists in traditional landraces that have been subject to ongoing environmental adaptation and can be identified by both phenotypic and environmental association.

evolutionary biology↗