Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays

Cassidy M. Hahn; Luke R. Iwanowicz; Robert S. Cornman; Patricia M. Mazik; Vicki S. Blazer

doi:10.1016/j.cbd.2016.07.001

Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays

Cassidy M. Hahn, Luke R. Iwanowicz, Robert S. Cornman, Patricia M. Mazik, Vicki S. Blazer

Ecosystem Science and Management

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest.

Original language	English (US)
Pages (from-to)	27-40
Number of pages	14
Journal	Comparative Biochemistry and Physiology - Part D: Genomics and Proteomics
Volume	20
DOIs	https://doi.org/10.1016/j.cbd.2016.07.001
State	Published - Dec 1 2016

All Science Journal Classification (ASJC) codes

Biochemistry
Physiology
Molecular Biology
Genetics

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10.1016/j.cbd.2016.07.001

Cite this

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title = "Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays",

abstract = "Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest.",

author = "Hahn, {Cassidy M.} and Iwanowicz, {Luke R.} and Cornman, {Robert S.} and Mazik, {Patricia M.} and Blazer, {Vicki S.}",

note = "Funding Information: This research was funded through a Great Lakes Restoration Initiative grant to the U.S. Fish and Wildlife Service, and by the U.S. Geological Survey's Environmental Health (Contaminant Biology), Ecosystems (Fisheries) and Cooperative Units Programs . We thank Jo Ann Banda, Steven Choy, Daniel Gefell, Zachary Jorgenson, and Jeremy Moore for fish collections; Ryan Braham, Heather Walsh, and Adam Sperry for assistance with fish collections and tissue processing; and Tim King for assistance with 454 sequencing of the smallmouth bass. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Publisher Copyright: {\textcopyright} 2016",

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N1 - Funding Information: This research was funded through a Great Lakes Restoration Initiative grant to the U.S. Fish and Wildlife Service, and by the U.S. Geological Survey's Environmental Health (Contaminant Biology), Ecosystems (Fisheries) and Cooperative Units Programs . We thank Jo Ann Banda, Steven Choy, Daniel Gefell, Zachary Jorgenson, and Jeremy Moore for fish collections; Ryan Braham, Heather Walsh, and Adam Sperry for assistance with fish collections and tissue processing; and Tim King for assistance with 454 sequencing of the smallmouth bass. Any use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Publisher Copyright: © 2016

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N2 - Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest.

AB - Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest.

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Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays

Abstract

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