Whole genome comparisons reveal panmixia among fall armyworm (Spodoptera frugiperda) from diverse locations

Background: The fall armyworm (Spodoptera frugiperda (J.E. Smith)) is a highly polyphagous agricultural pest with long-distance migratory behavior threatening food security worldwide. This pest has a host range of > 80 plant species, but two host strains are recognized based on their association with corn (C-strain) or rice and smaller grasses (R-strain). The population genomics of the United States (USA) fall armyworm remains poorly characterized to date despite its agricultural threat. Results: In this study, the population structure and genetic diversity in 55 S. frugiperda samples from Argentina, Brazil, Kenya, Puerto Rico and USA were surveyed to further our understanding of whole genome nuclear diversity. Comparisons at the genomic level suggest a panmictic S. frugiperda population, with only a minor reduction in gene flow between the two overwintering populations in the continental USA, also corresponding to distinct host strains at the mitochondrial level. Two maternal lines were detected from analysis of mitochondrial genomes. We found members from the Eastern Hemisphere interspersed within both continental USA overwintering subpopulations, suggesting multiple individuals were likely introduced to Africa. Conclusions: Our research is the largest diverse collection of United States S. frugiperda whole genome sequences characterized to date, covering eight continental states and a USA territory (Puerto Rico). The genomic resources presented provide foundational information to understand gene flow at the whole genome level among S. frugiperda populations. Based on the genomic similarities found between host strains and laboratory vs. field samples, our findings validate the experimental use of laboratory strains and the host strain differentiation based on mitochondria and sex-linked genetic markers extends to minor genome wide differences with some exceptions showing mixture between host strains is likely occurring in field populations.Fil: Schlum, Katrina A.. University of Tennessee; Estados UnidosFil: Lamour, Kurt. University of Tennessee; Estados UnidosFil: Placidi de Bortoli, Caroline. University of Tennessee; Estados UnidosFil: Banerjee, Rahul. University of Tennessee; Estados UnidosFil: Meagher, Robert. United States Department Of Agriculture. Center For Medical Agric And Vet Entomology; Estados UnidosFil: Pereira, Eliseu. Universidade Federal de Viçosa; BrasilFil: Murúa, María Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Tecnología Agroindustrial del Noroeste Argentino. Provincia de Tucumán. Ministerio de Desarrollo Productivo. Estación Experimental Agroindustrial "Obispo Colombres" (p). Instituto de Tecnología Agroindustrial del Noroeste Argentino; ArgentinaFil: Sword, Gregory A.. Texas A&M University; Estados UnidosFil: Tessnow, Ashley E.. Texas A&M University; Estados UnidosFil: Viteri Dillon, Diego. Universidad de Puerto Rico; Puerto RicoFil: Linares Ramirez, Angela M.. Universidad de Puerto Rico; Puerto RicoFil: Akutse, Komivi S.. International Centre Of Insect Physiology And Ecology; KeniaFil: Schmidt Jeffris, Rebecca. United States Department Of Agriculture. Center For Medical Agric And Vet Entomology; Estados UnidosFil: Huang, Fangneng. State University of Louisiana; Estados UnidosFil: Reisig, Dominic. North Carolina State University; Estados UnidosFil: Emrich, Scott J.. University of Tennessee; Estados UnidosFil: Jurat Fuentes, Juan Luis. University of Tennessee; Estados Unido

Air transport patterns at 925 mb (approximately 762 m AGL) for all months of the year.

Graphics provided by the International Research Institute for Climate and Society, Columbia University, https://iri.columbia.edu. (TIF)</p

Bar graphs showing the frequencies of the COIB variants.

Data are shown for Texas, Nebraska, Arizona, and the four states examined in Mexico. All variants had at least one specimen in the Texas collections. Vertical arrows at top of graph show the predominant variant for each CSh haplotype. The “other” category represents variants not found in the surveyed Texas collections.</p

Mediastinal paragangliomas: association with mutations in the succinate dehydrogenase genes and aggressive behavior

Extra-adrenal pheochromocytomas, otherwise known as paragangliomas (PGLs), account for about 20% of catecholamine-producing tumors. Catecholamine excess and mutations in the genes encoding succinate dehydrogenase subunits (SDHx) are frequently found in patients with PGLs. Only 2% of PGLs are found in the mediastinum, and little is known about genetic alterations in patients with mediastinal PGLs, catecholamine production by these tumors, or their clinical behavior. We hypothesized that most mediastinal PGLs are associated with germ line SDHx mutations, norepinephrine and/or dopamine excess, and aggressive behavior. The objective of this study was to characterize genetic, biochemical, and clinical data in a series of ten patients with mediastinal PGLs. All ten primary mediastinal PGL patients had germ line SDHx mutations, six in SDHB, and four in SDHD genes. Chest or back pain were the most common presenting symptoms (five patients), and catecholamines and/or their metabolites were elevated in seven patients. Additional tumors included head and neck PGLs in four patients, pheochromocytoma in one patient, and bladder PGL in another. Metastatic disease was documented in six patients (60%), and a concurrent abdominal mass was found in one patient. We conclude that mediastinal PGLs are strongly associated with SDHB and SDHD gene mutations, noradrenergic phenotype, and aggressive behavior. The present data suggest that all patients with mediastinal PGLs should be screened for SDHx gene mutations, regardless of age

Primer and probes sequences used to amplify diagnostic SNP C on the Z-chromosome of fall armyworm.

The FAM probe is specific to the R-strain while the VIC probe is specific to the C-strain. (DOCX)</p

Description of the COIB haplotypes and their distribution.

A: Molecular map of the COIB segment. Block horizontal arrows indicate primer locations for PCR and DNA sequencing. The relative locations of the mCOI1164D and mCOI1287R polymorphisms are indicated with the empirically observed nucleotides listed below. The T1164A1287 combination identifies the R-strain based on COI (RCOIB) while the other combinations define the COIB-based C-strain haplotypes that are designated CSh1-CSh4. B: Distribution of COIB haplotypes at different locations and times. Numbers in brackets indicate samples tested. C: C-strain COIB variants (CCOIB) from the TX collections. Each CSh haplotype is based on mCOI1164D and mCOI1287R, but polymorphisms at other sites also occur. The top line is the consensus sequence with dots below indicating agreement with the consensus. The locations of mCOI1164D and mCOI1287R are indicated.</p

Strain composition after sampling across a single latitude in 2021.

A: Sampling map for fall armyworm moths collected from September 7- October 26, 2021. All captures occurred within a single degree of latitude (32.7–33.7°N). Map location 1–4 represent Yuma, Arizona, Pinal, Arizona, Lubbock, Texas, and Burke, Georgia, respectively. B: Bar graph describing the frequencies of each strain as categorized by the SNP C Z-chromosome marker. The number above each column indicates the number of samples analyzed.</p

Maps related to FAW migration, agricultural activity, and seasonal wind systems.

Red oval approximates location of primary agricultural areas in southern Arizona. Horizontal dashed line approximates overwintering boundary. A: Map showing known FAW migration pathways from Texas (block arrows). Putative migration into Arizona indicated by red dashed lines. B: Air transport patterns in April at 925 mb (approximately 762 m AGL); graphics provided by the International Research Institute for Climate and Society, Columbia University, https://iri.columbia.edu [42, 43]. April approximates the beginning of the FAW migration season [7, 18]. C: Map of croplands showing agricultural activity (green). Image is courtesy of U.S. Geological Survey at https://www.usgs.gov/apps/croplands/app/map.</p

Bar graphs describing the frequencies of the strain types as categorized by the gTpi183Y marker.

The specimens from Iowa, Pennsylvania, and Argentina are from earlier studies [27, 40]. Numbers above columns indicate samples analyzed.</p