Gene Transcript Profiling in Desert Bighorn Sheep

Bowen, Lizabeth; Longshore, Kathleen M.; Wolff, Peregrine L.; Klinger, R; Cox, Mike; Bullock, Sarah; Waters, Shannon; Miles, A. Keith

doi:10.1002/wsb.1078

Cited by 3 publications

(2 citation statements)

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“…Furthermore, genomic approaches such as genome wide association studies can identify candidate loci associated with disease or susceptibility. Moreover, diagnostic testing can help identify genetic markers related to changes in physiologic response, and could help characterize the interplay of various stressors contributing to pneumonia outbreaks in bighorn sheep (Bowen et al, 2020). Since many integrated factors appear to influence disease outcome in bighorn sheep, combining genomics with spatial data can improve our understanding of disease risk and pathogen dynamics to simulate pathogen spread (Kozakiewicz et al, 2018).…”

Section: Future Directionsmentioning

confidence: 99%

A review of population and landscape level dynamics associated with pneumonia outbreaks in bighorn sheep with implications for land management

Paolini

Schwartz

Friggens

et al. 2023

Conservat Sci and Prac

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Wildlife conservation necessitates understanding spatiotemporal drivers that facilitate disease outbreaks. Wildlife diseases are influenced by population and landscape level factors which affects host species' persistence through time. Recurrent pneumonia outbreaks in bighorn sheep have impeded population recovery throughout the western US. Recovery efforts have included translocating animals, limiting contact with known reservoirs, removing infected individuals, and depopulating herds, but pneumonia outbreaks continue to negatively impact recovery. Here, our objective was to systematically review the current literature focused on population and landscape level drivers that can contribute to pneumonia outbreaks in bighorn sheep.We reviewed 115 studies and discovered consistent themes important to address for future conservation. One of the primary themes to advance management includes understanding how population demographics, such as age and sex cohorts, can help elucidate drivers and maintenance of pathogens associated with respiratory disease. Second, broadening knowledge of landscape level processes including population connectivity and metapopulation dynamics can inform management and recovery efforts. We identified a need for comprehensive assessments that incorporate population dynamics, landscape genomics, and population connectivity across multiple spatiotemporal scales to advance landscape management. Finally, we provide directions for future research to help managers mitigate pneumonia outbreaks and aid bighorn sheep recovery.

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Section: Future Directionsmentioning

confidence: 99%

A review of population and landscape level dynamics associated with pneumonia outbreaks in bighorn sheep with implications for land management

Paolini

Schwartz

Friggens

et al. 2023

Conservat Sci and Prac

View full text Add to dashboard Cite

show abstract

“…Gene expression is physiologically driven by intrinsic and extrinsic stimuli including toxins, pathogens, contaminants, trauma, or nutrition. As key indicators of pathophysiologic status, the earliest observable signs of health impairment are altered levels of gene transcripts, evident prior to clinical manifestation (McLoughlin et al, 2006), thus providing an early warning of potentially compromised health of individuals, populations, and ecosystems (Bowen et al, 2020b). Broad-scale identification of gene expression patterns can provide mechanistic understanding as a proxy for health (Pedersen and Babayan, 2011;Portnoy et al, 2020) that can then be extrapolated to populations.…”

mentioning

confidence: 99%

Gene expression and wildlife health: varied interpretations based on perspective

et al. 2023

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We evaluated wildlife population health from the perspective of statistical means vs. variances. We outlined the choices necessary to provide the framework for our study. These consisted of spatial and temporal boundaries (e.g., choice of sentinel species, populations, time frame), measurement techniques (molecular to population level), and appropriate statistical analyses. We chose to assess the health of 19 sea otter populations, located in the north Pacific from the Aleutian Islands, AK, to Santa Barbara, CA, and varying in population growth rates and length of occupancy. Our focal metric was gene expression (i.e., mRNA transcripts) data that we had previously generated across sea otter populations as a measure of population health. We used statistical methods with different approaches (i.e., means vs. variances) and examined the subsequent interpretive outcomes and how these influence our assessment of “health.” Interpretations based on analyses using variances versus means overlapped to some degree. In general, sea otter populations with low variation in gene expression were limited by food resources and at or near carrying capacity. In populations where the variation in gene expression was moderate or high, four out of five populations were increasing in abundance, or had been recently increasing. Where we had additional information on sources of stressors at the level of the population, we were able to draw inferences from those stressors to specific gene expression results. For example, gene expression patterns of sea otters from Western Prince William Sound were consistent with long term exposure to petroleum hydrocarbons, whereas in Kachemak Bay, patterns were consistent with exposure to algal toxins. Ultimately, determination of population or ecosystem health will be most informative when multiple metrics are examined across disciplines in the context of specific scenarios and goals.

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Using transcriptomics to predict and visualize disease status in bighorn sheep (Ovis canadensis)

Bowen

Manlove

Roug

et al. 2022

Conservation Physiology

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Increasing risk of pathogen spillover coupled with overall declines in wildlife population abundance in the Anthropocene make infectious disease a relevant concern for species conservation worldwide. While emerging molecular tools could improve our diagnostic capabilities and give insight into mechanisms underlying wildlife disease risk, they have rarely been applied in practice. Here, employing a previously reported gene transcription panel of common immune markers to track physiological changes, we present a detailed analysis over the course of both acute and chronic infection in one wildlife species where disease plays a critical role in conservation, bighorn sheep (Ovis canadensis). Differential gene transcription patterns distinguished between infection statuses over the course of acute infection and differential correlation (DC) analyses identified clear changes in gene co-transcription patterns over the early stages of infection, with transcription of four genes—TGFb, AHR, IL1b and MX1—continuing to increase even as transcription of other immune-associated genes waned. In a separate analysis, we considered the capacity of the same gene transcription panel to aid in differentiating between chronically infected animals and animals in other disease states outside of acute disease events (an immediate priority for wildlife management in this system). We found that this transcription panel was capable of accurately identifying chronically infected animals in the test dataset, though additional data will be required to determine how far this ability extends. Taken together, our results showcase the successful proof of concept and breadth of potential utilities that gene transcription might provide to wildlife disease management, from direct insight into mechanisms associated with differential disease response to improved diagnostic capacity in the field.

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Gene Transcript Profiling in Desert Bighorn Sheep

Cited by 3 publications

References 50 publications

A review of population and landscape level dynamics associated with pneumonia outbreaks in bighorn sheep with implications for land management

A review of population and landscape level dynamics associated with pneumonia outbreaks in bighorn sheep with implications for land management

Gene expression and wildlife health: varied interpretations based on perspective

Using transcriptomics to predict and visualize disease status in bighorn sheep (Ovis canadensis)

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