1
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Yang B, Zhou X, Liu S. Tracing the genealogy origin of geographic populations based on genomic variation and deep learning. Mol Phylogenet Evol 2024; 198:108142. [PMID: 38964594 DOI: 10.1016/j.ympev.2024.108142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 05/30/2024] [Accepted: 07/01/2024] [Indexed: 07/06/2024]
Abstract
Assigning a query individual animal or plant to its derived population is a prime task in diverse applications related to organismal genealogy. Such endeavors have conventionally relied on short DNA sequences under a phylogenetic framework. These methods naturally show constraints when the inferred population sources are ambiguously phylogenetically structured, a scenario demanding substantially more informative genetic signals. Recent advances in cost-effective production of whole-genome sequences and artificial intelligence have created an unprecedented opportunity to trace the population origin for essentially any given individual, as long as the genome reference data are comprehensive and standardized. Here, we developed a convolutional neural network method to identify population origins using genomic SNPs. Three empirical datasets (an Asian honeybee, a red fire ant, and a chicken datasets) and two simulated populations are used for the proof of concepts. The performance tests indicate that our method can accurately identify the genealogy origin of query individuals, with success rates ranging from 93 % to 100 %. We further showed that the accuracy of the model can be significantly increased by refining the informative sites through FST filtering. Our method is robust to configurations related to batch sizes and epochs, whereas model learning benefits from the setting of a proper preset learning rate. Moreover, we explained the importance score of key sites for algorithm interpretability and credibility, which has been largely ignored. We anticipate that by coupling genomics and deep learning, our method will see broad potential in conservation and management applications that involve natural resources, invasive pests and weeds, and illegal trades of wildlife products.
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Affiliation(s)
- Bing Yang
- Department of Entomology, China Agricultural University, Beijing 100193, China
| | - Xin Zhou
- Department of Entomology, China Agricultural University, Beijing 100193, China.
| | - Shanlin Liu
- Department of Entomology, China Agricultural University, Beijing 100193, China; Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.
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2
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Grzegorczyk J, Gurgul A, Oczkowicz M, Szmatoła T, Fornal A, Bugno-Poniewierska M. Single Nucleotide Polymorphism Discovery and Genetic Differentiation Analysis of Geese Bred in Poland, Using Genotyping-by-Sequencing (GBS). Genes (Basel) 2021; 12:genes12071074. [PMID: 34356090 PMCID: PMC8307914 DOI: 10.3390/genes12071074] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/06/2021] [Accepted: 07/12/2021] [Indexed: 11/25/2022] Open
Abstract
Poland is the largest European producer of goose, while goose breeding has become an essential and still increasing branch of the poultry industry. The most frequently bred goose is the White Kołuda® breed, constituting 95% of the country’s population, whereas geese of regional varieties are bred in smaller, conservation flocks. However, a goose’s genetic diversity is inaccurately explored, mainly because the advantages of the most commonly used tools are strongly limited in non-model organisms. One of the most accurate used markers for population genetics is single nucleotide polymorphisms (SNP). A highly efficient strategy for genome-wide SNP detection is genotyping-by-sequencing (GBS), which has been already widely applied in many organisms. This study attempts to use GBS in 12 conservative goose breeds and the White Kołuda® breed maintained in Poland. The GBS method allowed for the detection of 3833 common raw SNPs. Nevertheless, after filtering for read depth and alleles characters, we obtained the final markers panel used for a differentiation analysis that comprised 791 SNPs. These variants were located within 11 different genes, and one of the most diversified variants was associated with the EDAR gene, which is especially interesting as it participates in the plumage development, which plays a crucial role in goose breeding.
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Affiliation(s)
- Joanna Grzegorczyk
- Department of Molecular Biology of Animals, National Research Institute of Animal Production, Balice n., 32-083 Kraków, Poland; (J.G.); (T.S.); (A.F.)
| | - Artur Gurgul
- Center for Experimental and Innovative Medicine, University of Agriculture in Kraków, Al. Mickiewicza 24-28, 30-059 Kraków, Poland;
| | - Maria Oczkowicz
- Department of Molecular Biology of Animals, National Research Institute of Animal Production, Balice n., 32-083 Kraków, Poland; (J.G.); (T.S.); (A.F.)
- Correspondence:
| | - Tomasz Szmatoła
- Department of Molecular Biology of Animals, National Research Institute of Animal Production, Balice n., 32-083 Kraków, Poland; (J.G.); (T.S.); (A.F.)
- Center for Experimental and Innovative Medicine, University of Agriculture in Kraków, Al. Mickiewicza 24-28, 30-059 Kraków, Poland;
| | - Agnieszka Fornal
- Department of Molecular Biology of Animals, National Research Institute of Animal Production, Balice n., 32-083 Kraków, Poland; (J.G.); (T.S.); (A.F.)
| | - Monika Bugno-Poniewierska
- Department of Animal Reproduction, Faculty Anatomy and Genomics of Animal Breeding and Biology, Agricultural University in Cracow, Al. Mickiewicza 24-28, 30-059 Kraków, Poland;
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3
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Species-diagnostic SNP markers for the black basses (Micropterus spp.): a new tool for black bass conservation and management. CONSERV GENET RESOUR 2019. [DOI: 10.1007/s12686-019-01109-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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4
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Kim JS, Wang AR, Kim MJ, Lee KH, Kim I. Single-nucleotide polymorphism markers in mitochondrial genomes for identifying Varroa destructor-resistant and -susceptible strains of Apis mellifera (Hymenoptera: Apidae). Mitochondrial DNA A DNA Mapp Seq Anal 2019; 30:477-489. [PMID: 30691316 DOI: 10.1080/24701394.2018.1551385] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Mitogenome sequences have a high potential for possessing single-nucleotide polymorphisms (SNPs) that can be used to identify different strains of an organism bred based on maternal lines. The European honey bee, Apis mellifera ligustica (Hymenoptera: Apidae), with a high-hygienic behaviour (HHB) against the external parasitic mite Varroa destructor has been bred for several years in Korea. To distinguish this strain from low-hygienic behaviour (LHB) strains, the complete mitogenome of the two strains were sequenced using next-generation sequencing techniques to detect SNPs. The two mitogenomes with lengths of 16,449 and 16,426 base pairs (bp) in the HHB and LHB strains, respectively, contained a typical set of genes (13 protein-coding genes, 2 rRNA genes, and 22 tRNA genes, plus one non-coding region), exhibited similar-nucleotide compositions, and had an identical gene arrangement compared to other available A. mellifera mitogenomes. The major differences between the HHB and LHB strains included the length of the intergenic spacer sequences located at the COIII and trnG junction (88 vs. 70 bp) and ND4 and ND4L junction (45 vs. 33 bp) and the presence or absence of a duplicated sequence block (CTTTTTTAAAAAAATAAAAA) in the A + T-rich region. Comparison of the mitogenome sequences from the two strains of A. m. ligustica revealed 23 SNPs in 11 protein-coding genes which were confirmed by sequencing of 10 randomly selected individuals from each strain, indicating the usefulness of these SNP markers for identifying the HHB strain of A. m. ligustica. Therefore, mitogenome sequences are a promising genome source for detecting SNP markers, particularly those in inbred female lines.
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Affiliation(s)
- Jong Seok Kim
- a Department of Applied Biology, College of Agriculture & Life Sciences , Chonnam National University , Gwangju , Republic of Korea
| | - Ah Rha Wang
- a Department of Applied Biology, College of Agriculture & Life Sciences , Chonnam National University , Gwangju , Republic of Korea
| | - Min Jee Kim
- a Department of Applied Biology, College of Agriculture & Life Sciences , Chonnam National University , Gwangju , Republic of Korea
| | - Keon Hee Lee
- a Department of Applied Biology, College of Agriculture & Life Sciences , Chonnam National University , Gwangju , Republic of Korea
| | - Iksoo Kim
- a Department of Applied Biology, College of Agriculture & Life Sciences , Chonnam National University , Gwangju , Republic of Korea
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5
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Zhao H, Fuller A, Thongda W, Mohammed H, Abernathy J, Beck B, Peatman E. SNP panel development for genetic management of wild and domesticated white bass (Morone chrysops). Anim Genet 2018; 50:92-96. [PMID: 30426519 DOI: 10.1111/age.12747] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/12/2018] [Indexed: 02/03/2023]
Abstract
White bass (Morone chrysops), striped bass and their interspecific hybrid are important game fishes, whereas the hybrid striped bass is an important aquaculture species in the US. Numerous state, federal and private hatcheries, therefore, rear these species for stocking purposes as well as for food fish. Although striped bass populations (both wild and domesticated) have been extensively evaluated, relatively little effort has been directed toward the study and improvement of white bass. In this study, we developed SNP resources to examine the genetic relationships among a long-term domesticated white bass line and five potential founder stocks for selective breeding collected from drainages in Arkansas, Texas and Alabama. Using genotyping-by-sequencing, we generated 13 872 genome-wide SNP loci across the six populations. Stringent filtering of SNP-calling parameters identified 426 informative SNP loci. Population genetic and structure analyses using these loci revealed only moderate genetic differentiation between populations (global Fst = 0.083) and indicated two major genetic clusters. A final 57-SNP assay was successfully designed and validated using the MassARRAY system. The developed SNP panel assigned 96 additional genotyped individuals to their population of origin with 100% accuracy. The SNP resources developed in this study should facilitate ongoing efforts in selective breeding and conservation of white bass.
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Affiliation(s)
- H Zhao
- School of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - A Fuller
- United States Department of Agriculture, Agricultural Research Service, Harry K. Dupree Stuttgart National Aquaculture Research Center, Stuttgart, AR, 72160, USA
| | - W Thongda
- School of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - H Mohammed
- School of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.,Faculty of Veterinary Medicine, Department of Aquatic Animals Medicine and Management, Assiut University, Assiut, 71526, Egypt
| | - J Abernathy
- United States Department of Agriculture, Agricultural Research Service, Harry K. Dupree Stuttgart National Aquaculture Research Center, Stuttgart, AR, 72160, USA
| | - B Beck
- United States Department of Agriculture, Agricultural Research Service, Aquatic Animal Health Research Unit, Auburn, AL, 36832, USA
| | - E Peatman
- School of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
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6
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Matsukawa M, Tasaki M, Doi K, Ito K, Kawakita K, Tanaka T. Regional population differences of the brown planthopper (Nilaparvata lugens Stål) in Cambodia using genotyping-by-sequencing. BULLETIN OF ENTOMOLOGICAL RESEARCH 2018; 108:471-478. [PMID: 29061206 DOI: 10.1017/s0007485317000992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
The brown planthopper Nilaparvata lugens Stål (BPH) can be found year-round in tropical region and causes severe damage to rice. Although there has been documented BPH damage to rice crops in the past decade in Cambodia, the extent of this epidemic is poorly understood. Here, we examined the time variation of BPH population in the abundance of morphotypes in 13 main rice-producing provinces (86 sites) by aspirator method and in the Takeo Province (five sites) by yellow sticky trap method. At least three generations were observed during the 3-month collection period in the rainy growing season. Regarding the occurrence of BPH morphotypes, in July the macropterous adults were restricted to south Cambodia and in August all morphotypes, adults (macropterous and brachypterous) and nymphs, appeared in all sampling sites. To explain the difference of regional distribution, the genetic differentiation was analyzed in south and northwest Cambodia (three sites) by using single nucleotide polymorphisms (SNP) analysis via genotyping-by-sequencing (GBS) using next-generation sequencing. The 2455 SNPs obtained by GBS clarified the three sub-populations and they corresponded to the expected dissemination patterns. These results provide a clue to understand the differentiation and epidemic of BPH in Cambodia.
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Affiliation(s)
- M Matsukawa
- Graduate School of Bioagricultural Sciences,Nagoya University,Chikusa,Nagoya,Aichi 464-8601,Japan
| | - Mikako Tasaki
- International Cooperation Center for Agricultural Education,Nagoya University,Chikusa,Nagoya,Aichi 464-8601,Japan
| | - Kazuyuki Doi
- Graduate School of Bioagricultural Sciences,Nagoya University,Chikusa,Nagoya,Aichi 464-8601,Japan
| | - Kasumi Ito
- International Cooperation Center for Agricultural Education,Nagoya University,Chikusa,Nagoya,Aichi 464-8601,Japan
| | - Kazuhito Kawakita
- Graduate School of Bioagricultural Sciences,Nagoya University,Chikusa,Nagoya,Aichi 464-8601,Japan
| | - Toshiharu Tanaka
- International Cooperation Center for Agricultural Education,Nagoya University,Chikusa,Nagoya,Aichi 464-8601,Japan
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7
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Sefick SA, Castronova MA, Stevison LS. genotypeR
: An integrated
r
package for single nucleotide polymorphism genotype marker design and data analysis. Methods Ecol Evol 2018. [DOI: 10.1111/2041-210x.12965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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8
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Puncher GN, Cariani A, Maes GE, Van Houdt J, Herten K, Cannas R, Rodriguez-Ezpeleta N, Albaina A, Estonba A, Lutcavage M, Hanke A, Rooker J, Franks JS, Quattro JM, Basilone G, Fraile I, Laconcha U, Goñi N, Kimoto A, Macías D, Alemany F, Deguara S, Zgozi SW, Garibaldi F, Oray IK, Karakulak FS, Abid N, Santos MN, Addis P, Arrizabalaga H, Tinti F. Spatial dynamics and mixing of bluefin tuna in the Atlantic Ocean and Mediterranean Sea revealed using next-generation sequencing. Mol Ecol Resour 2018; 18:620-638. [PMID: 29405659 DOI: 10.1111/1755-0998.12764] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 01/06/2018] [Accepted: 01/19/2018] [Indexed: 01/05/2023]
Abstract
The Atlantic bluefin tuna is a highly migratory species emblematic of the challenges associated with shared fisheries management. In an effort to resolve the species' stock dynamics, a genomewide search for spatially informative single nucleotide polymorphisms (SNPs) was undertaken, by way of sequencing reduced representation libraries. An allele frequency approach to SNP discovery was used, combining the data of 555 larvae and young-of-the-year (LYOY) into pools representing major geographical areas and mapping against a newly assembled genomic reference. From a set of 184,895 candidate loci, 384 were selected for validation using 167 LYOY. A highly discriminatory genotyping panel of 95 SNPs was ultimately developed by selecting loci with the most pronounced differences between western Atlantic and Mediterranean Sea LYOY. The panel was evaluated by genotyping a different set of LYOY (n = 326), and from these, 77.8% and 82.1% were correctly assigned to western Atlantic and Mediterranean Sea origins, respectively. The panel revealed temporally persistent differentiation among LYOY from the western Atlantic and Mediterranean Sea (FST = 0.008, p = .034). The composition of six mixed feeding aggregations in the Atlantic Ocean and Mediterranean Sea was characterized using genotypes from medium (n = 184) and large (n = 48) adults, applying population assignment and mixture analyses. The results provide evidence of persistent population structuring across broad geographic areas and extensive mixing in the Atlantic Ocean, particularly in the mid-Atlantic Bight and Gulf of St. Lawrence. The genomic reference and genotyping tools presented here constitute novel resources useful for future research and conservation efforts.
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Affiliation(s)
- Gregory N Puncher
- Department of Biological, Geological and Environmental Sciences/Laboratory of Genetics and Genomics of Marine Resources and Environment (GenoDREAM), University of Bologna, Ravenna, Italy.,Department of Biology, Marine Biology Research Group, Ghent University, Ghent, Belgium.,Department of Biology, University of New Brunswick, Saint John, NB, Canada
| | - Alessia Cariani
- Department of Biological, Geological and Environmental Sciences/Laboratory of Genetics and Genomics of Marine Resources and Environment (GenoDREAM), University of Bologna, Ravenna, Italy
| | - Gregory E Maes
- Centre for Sustainable Tropical Fisheries and Aquaculture, Comparative Genomics Centre, College of Science and Engineering, James Cook University, Townsville, Qld, Australia.,Centre for Human Genetics, Genomics Core, KU Leuven - UZ Leuven, Leuven, Belgium.,Laboratory of Biodiversity and Evolutionary Genomics, University of Leuven (KU Leuven), Leuven, Belgium
| | - Jeroen Van Houdt
- Centre for Human Genetics, Genomics Core, KU Leuven - UZ Leuven, Leuven, Belgium
| | - Koen Herten
- Centre for Human Genetics, Genomics Core, KU Leuven - UZ Leuven, Leuven, Belgium.,Laboratory of Biodiversity and Evolutionary Genomics, University of Leuven (KU Leuven), Leuven, Belgium
| | - Rita Cannas
- Department of Life & Environmental Sciences (DISVA), University of Cagliari, Cagliari, Italy
| | | | - Aitor Albaina
- Laboratory of Genetics Faculty of Science & Technology, Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain.,Environmental Studies Centre (CEA), Vitoria-Gasteiz City Council, Vitoria-Gasteiz, Spain
| | - Andone Estonba
- Laboratory of Genetics Faculty of Science & Technology, Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Molly Lutcavage
- School for the Environment and Large Pelagics Research Center, University of Massachusetts, Boston, Gloucester, MA, USA
| | - Alex Hanke
- Fisheries and Oceans Canada, St. Andrews Biological Station, St. Andrews, NB, Canada
| | - Jay Rooker
- Department of Marine Biology, Texas A&M University at Galveston, Galveston, TX, USA.,Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX, USA
| | - James S Franks
- Gulf Coast Research Laboratory, Center for Fisheries Research and Development, University of Southern Mississippi, Ocean Springs, MS, USA
| | - Joseph M Quattro
- Department of Biological Sciences, University of South Carolina, Columbia, SC, USA
| | - Gualtiero Basilone
- National Research Council, Institute for Marine and Coastal Environment, Detached Unit of Capo Granitola, Trapani, Italy
| | - Igaratza Fraile
- Marine Research Division, AZTI Tecnalia, Pasaia, Gipuzkoa, Spain
| | - Urtzi Laconcha
- Marine Research Division, AZTI Tecnalia, Pasaia, Gipuzkoa, Spain.,Laboratory of Genetics Faculty of Science & Technology, Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - Nicolas Goñi
- Marine Research Division, AZTI Tecnalia, Pasaia, Gipuzkoa, Spain
| | - Ai Kimoto
- National Research Institute of Far Seas Fisheries, Shizuoka, Japan
| | - David Macías
- Instituto Español de Oceanografía, Centro Oceanográfico de Baleares, Palma, Spain
| | - Francisco Alemany
- Instituto Español de Oceanografía, Centro Oceanográfico de Baleares, Palma, Spain
| | - Simeon Deguara
- Federation of Maltese Aquaculture Producers (FMAP), Valletta, Malta
| | - Salem W Zgozi
- Marine Biology Research Center, Tripoli-Tajura, Libya
| | - Fulvio Garibaldi
- Department of Earth, Environmental and Life Sciences, University of Genoa, Genova, Italy
| | - Isik K Oray
- Faculty of Fisheries, Istanbul University, Laleli-Istanbul, Turkey
| | | | - Noureddine Abid
- National Institute of Fisheries Research, Regional Centre of Tangier, Tanger, Morocco
| | | | - Piero Addis
- Department of Life & Environmental Sciences (DISVA), University of Cagliari, Cagliari, Italy
| | | | - Fausto Tinti
- Department of Biological, Geological and Environmental Sciences/Laboratory of Genetics and Genomics of Marine Resources and Environment (GenoDREAM), University of Bologna, Ravenna, Italy
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9
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Bich Vo TT. Identification and analysis of snps in population of Vietnamese catfish (pangasianodon hypophthalmus), using next generation sequencing and snp validation. ACTA ACUST UNITED AC 2018. [DOI: 10.15406/mojcrr.2018.01.00003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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10
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Peng X, Zhao L, Liu J, Guo X. Development of SNP markers for Xenocypris argentea based on transcriptomics. CONSERV GENET RESOUR 2017. [DOI: 10.1007/s12686-017-0900-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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11
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Nunes JDRDS, Liu S, Pértille F, Perazza CA, Villela PMS, de Almeida-Val VMF, Hilsdorf AWS, Liu Z, Coutinho LL. Large-scale SNP discovery and construction of a high-density genetic map of Colossoma macropomum through genotyping-by-sequencing. Sci Rep 2017; 7:46112. [PMID: 28387238 PMCID: PMC5384230 DOI: 10.1038/srep46112] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 03/06/2017] [Indexed: 11/11/2022] Open
Abstract
Colossoma macropomum, or tambaqui, is the largest native Characiform species found in the Amazon and Orinoco river basins, yet few resources for genetic studies and the genetic improvement of tambaqui exist. In this study, we identified a large number of single-nucleotide polymorphisms (SNPs) for tambaqui and constructed a high-resolution genetic linkage map from a full-sib family of 124 individuals and their parents using the genotyping by sequencing method. In all, 68,584 SNPs were initially identified using minimum minor allele frequency (MAF) of 5%. Filtering parameters were used to select high-quality markers for linkage analysis. We selected 7,734 SNPs for linkage mapping, resulting in 27 linkage groups with a minimum logarithm of odds (LOD) of 8 and maximum recombination fraction of 0.35. The final genetic map contains 7,192 successfully mapped markers that span a total of 2,811 cM, with an average marker interval of 0.39 cM. Comparative genomic analysis between tambaqui and zebrafish revealed variable levels of genomic conservation across the 27 linkage groups which allowed for functional SNP annotations. The large-scale SNP discovery obtained here, allowed us to build a high-density linkage map in tambaqui, which will be useful to enhance genetic studies that can be applied in breeding programs.
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Affiliation(s)
- José de Ribamar da Silva Nunes
- Animal Science department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil.,The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, United States of America.,Nature and Culture Institute, Federal University of Amazon (UFAM), Benjamin Constant, Amazonas, Brazil
| | - Shikai Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, United States of America
| | - Fábio Pértille
- Animal Science department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Caio Augusto Perazza
- Unit of Biotechnology, University of Mogi das Cruzes, P.O. Box 411, 08701-970, Mogi das Cruzes, SP, Brazil
| | - Priscilla Marqui Schmidt Villela
- Animal Science department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Vera Maria Fonseca de Almeida-Val
- Brazilian National Institute for Research of the Amazon, Laboratory of Ecophysiology and Molecular Evolution, Manaus, Amazonas, Brazil.,University Nilton Lins, Aquaculture Graduate Program, Manaus, Amazonas, Brazil
| | | | - Zhanjiang Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, United States of America
| | - Luiz Lehmann Coutinho
- Animal Science department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
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12
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Construction of a High-Density Genetic Map and Quantitative Trait Locus Mapping in the Manila clam Ruditapes philippinarum. Sci Rep 2017; 7:229. [PMID: 28331182 PMCID: PMC5427961 DOI: 10.1038/s41598-017-00246-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 02/15/2017] [Indexed: 11/13/2022] Open
Abstract
Genetic linkage maps are indispensable tools in a wide range of genetic and genomic research. With the advancement of genotyping-by-sequencing (GBS) methods, the construction of a high-density linkage maps has become achievable in marine organisms lacking sufficient genomic resources, such as mollusks. In this study, high-density linkage map was constructed for an ecologically and commercially important clam species, Ruditapes philippinarum. For the consensus linkage map, a total of 9658 markers spanning 1926.98 cM were mapped to 18 sex-averaged linkage groups, with an average marker distance of 0.42 cM. Based on the high-density linkage map, ten QTLs for growth-related traits and shell color were detected. The coverage and density of the current map are sufficient for us to effectively detect QTL for segregating traits, and two QTL positions were all coincident with the closest markers. This high-density genetic linkage map reveals basic genomic architecture and will be useful for comparative genomics research, genome assembly and genetic improvement of R. philippinarum and other bivalve molluscan species.
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13
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Casabianca S, Cornetti L, Capellacci S, Vernesi C, Penna A. Genome complexity of harmful microalgae. HARMFUL ALGAE 2017; 63:7-12. [PMID: 28366402 DOI: 10.1016/j.hal.2017.01.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Revised: 01/09/2017] [Accepted: 01/09/2017] [Indexed: 06/07/2023]
Abstract
During the past decade, next generation sequencing (NGS) technologies have provided new insights into the diversity, dynamics, and metabolic pathways of natural microbial communities. But, these new techniques face challenges related to the genome size and level of genome complexity of the species under investigation. Moreover, the coverage depth and the short-read length achieved by NGS based approaches also represent a major challenge for assembly. These factors could limit the use of these high-throughput sequencing methods for species lacking a reference genome and characterized by a high level of complexity. In the present work, the evolutionary history, mainly consisting of gene transfer events from bacteria and unicellular eukaryotes to microalgae, including harmful species, is discussed and reviewed as it relates to NGS application in microbial communities, with a particular focus on harmful algal bloom species and dinoflagellates. In the context of genetic population studies, genotyping-by-sequencing (GBS), an NGS based approach, could be used for the discovery and analysis of single nucleotide polymorphisms (SNPs). The NGS technologies are still relatively new and require further improvement. Specifically, there is a need to develop and standardize tools and approaches to handle large data sets, which have to be used for the majority of HAB species characterized by evolutionary highly dynamic genomes.
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Affiliation(s)
- Silvia Casabianca
- Department of Biomolecular Sciences, University of Urbino, Viale Trieste 296, 61121 Pesaro, Italy; CoNISMa, Italian Interuniversity Consortium on Marine Sciences, Piazzale Flaminio 9, 00196, Rome, Italy
| | - Luca Cornetti
- Institute for Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland
| | - Samuela Capellacci
- Department of Biomolecular Sciences, University of Urbino, Viale Trieste 296, 61121 Pesaro, Italy; CoNISMa, Italian Interuniversity Consortium on Marine Sciences, Piazzale Flaminio 9, 00196, Rome, Italy
| | - Cristiano Vernesi
- Department of Biodiversity and Molecular Ecology, Research and Innovation Centre, Fondazione Edmund Mach, Via E. Mach 1, San Michele all'Adige, 38010 Trento, Italy
| | - Antonella Penna
- Department of Biomolecular Sciences, University of Urbino, Viale Trieste 296, 61121 Pesaro, Italy; CoNISMa, Italian Interuniversity Consortium on Marine Sciences, Piazzale Flaminio 9, 00196, Rome, Italy.
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14
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Zhu F, Cui QQ, Hou ZC. SNP discovery and genotyping using Genotyping-by-Sequencing in Pekin ducks. Sci Rep 2016; 6:36223. [PMID: 27845353 PMCID: PMC5109183 DOI: 10.1038/srep36223] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2016] [Accepted: 10/11/2016] [Indexed: 11/09/2022] Open
Abstract
Genomic selection and genome-wide association studies need thousands to millions of SNPs. However, many non-model species do not have reference chips for detecting variation. Our goal was to develop and validate an inexpensive but effective method for detecting SNP variation. Genotyping by sequencing (GBS) can be a highly efficient strategy for genome-wide SNP detection, as an alternative to microarray chips. Here, we developed a GBS protocol for ducks and tested it to genotype 49 Pekin ducks. A total of 169,209 SNPs were identified from all animals, with a mean of 55,920 SNPs per individual. The average SNP density reached 1156 SNPs/MB. In this study, the first application of GBS to ducks, we demonstrate the power and simplicity of this method. GBS can be used for genetic studies in to provide an effective method for genome-wide SNP discovery.
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Affiliation(s)
- Feng Zhu
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, Department of Animal Genetics and Breeding, China Agricultural University, Beijing 100193, China
| | - Qian-Qian Cui
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, Department of Animal Genetics and Breeding, China Agricultural University, Beijing 100193, China
| | - Zhuo-Cheng Hou
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, Department of Animal Genetics and Breeding, China Agricultural University, Beijing 100193, China
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15
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Li R, Erpelding JE. Genetic diversity analysis of Gossypium arboreum germplasm accessions using genotyping-by-sequencing. Genetica 2016; 144:535-545. [PMID: 27604991 DOI: 10.1007/s10709-016-9921-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Accepted: 08/31/2016] [Indexed: 10/21/2022]
Abstract
The diploid cotton species Gossypium arboreum possesses many favorable agronomic traits such as drought tolerance and disease resistance, which can be utilized in the development of improved upland cotton cultivars. The USDA National Plant Germplasm System maintains more than 1600 G. arboreum accessions. Little information is available on the genetic diversity of the collection thereby limiting the utilization of this cotton species. The genetic diversity and population structure of the G. arboreum germplasm collection were assessed by genotyping-by-sequencing of 375 accessions. Using genome-wide single nucleotide polymorphism sequence data, two major clusters were inferred with 302 accessions in Cluster 1, 64 accessions in Cluster 2, and nine accessions unassigned due to their nearly equal membership to each cluster. These two clusters were further evaluated independently resulting in the identification of two sub-clusters for the 302 Cluster 1 accessions and three sub-clusters for the 64 Cluster 2 accessions. Low to moderate genetic diversity between clusters and sub-clusters were observed indicating a narrow genetic base. Cluster 2 accessions were more genetically diverse and the majority of the accessions in this cluster were landraces. In contrast, Cluster 1 is composed of varieties or breeding lines more recently added to the collection. The majority of the accessions had kinship values ranging from 0.6 to 0.8. Eight pairs of accessions were identified as potential redundancies due to their high kinship relatedness. The genetic diversity and genotype data from this study are essential to enhance germplasm utilization to identify genetically diverse accessions for the detection of quantitative trait loci associated with important traits that would benefit upland cotton improvement.
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Affiliation(s)
- Ruijuan Li
- Crop Genetics Research Unit, USDA-ARS, 141 Experiment Station Road, PO Box 345, Stoneville, MS, 38776, USA
| | - John E Erpelding
- Crop Genetics Research Unit, USDA-ARS, 141 Experiment Station Road, PO Box 345, Stoneville, MS, 38776, USA.
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16
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Fine mapping QTL for resistance to VNN disease using a high-density linkage map in Asian seabass. Sci Rep 2016; 6:32122. [PMID: 27555039 PMCID: PMC4995370 DOI: 10.1038/srep32122] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Accepted: 08/02/2016] [Indexed: 12/30/2022] Open
Abstract
Asian seabass has suffered from viral nervous necrosis (VNN) disease. Our previous study has mapped quantitative trait loci (QTL) for resistance to VNN disease. To fine map these QTL and identify causative genes, we identified 6425 single nucleotide polymorphisms (SNPs) from 85 dead and 94 surviving individuals. Combined with 155 microsatellites, we constructed a genetic map consisting of 24 linkage groups (LGs) containing 3000 markers, with an average interval of 1.27 cM. We mapped one significant and three suggestive QTL with phenotypic variation explained (PVE) of 8.3 to 11.0%, two significant and two suggestive QTL with PVE of 7.8 to 10.9%, for resistance in three LGs and survival time in four LGs, respectively. Further analysis one QTL with the largest effect identified protocadherin alpha-C 2-like (Pcdhac2) as the possible candidate gene. Association study in 43 families with 1127 individuals revealed a 6 bp insertion-deletion was significantly associated with disease resistance. qRT-PCR showed the expression of Pcdhac2 was significantly induced in the brain, muscle and skin after nervous necrosis virus (NNV) infection. Our results could facilitate marker-assisted selection (MAS) for resistance to NNV in Asian seabass and set up the basis for functional analysis of the potential causative gene for resistance.
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17
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Pavy N, Gagnon F, Deschênes A, Boyle B, Beaulieu J, Bousquet J. Development of highly reliable in silico SNP resource and genotyping assay from exome capture and sequencing: an example from black spruce (Picea mariana). Mol Ecol Resour 2015; 16:588-98. [PMID: 26391535 DOI: 10.1111/1755-0998.12468] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2014] [Revised: 06/30/2015] [Accepted: 08/21/2015] [Indexed: 11/29/2022]
Abstract
Picea mariana is a widely distributed boreal conifer across Canada and the subject of advanced breeding programmes for which population genomics and genomic selection approaches are being developed. Targeted sequencing was achieved after capturing P. mariana exome with probes designed from the sequenced transcriptome of Picea glauca, a distant relative. A high capture efficiency of 75.9% was reached although spruce has a complex and large genome including gene sequences interspersed by some long introns. The results confirmed the relevance of using probes from congeneric species to perform successfully interspecific exome capture in the genus Picea. A bioinformatics pipeline was developed including stringent criteria that helped detect a set of 97,075 highly reliable in silico SNPs. These SNPs were distributed across 14,909 genes. Part of an Infinium iSelect array was used to estimate the rate of true positives by validating 4267 of the predicted in silico SNPs by genotyping trees from P. mariana populations. The true positive rate was 96.2% for in silico SNPs, compared to a genotyping success rate of 96.7% for a set 1115 P. mariana control SNPs recycled from previous genotyping arrays. These results indicate the high success rate of the genotyping array and the relevance of the selection criteria used to delineate the new P. mariana in silico SNP resource. Furthermore, in silico SNPs were generally of medium to high frequency in natural populations, thus providing high informative value for future population genomics applications.
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Affiliation(s)
- Nathalie Pavy
- Canada Research Chair in Forest and Environmental Genomics, Centre for Forest Research, Université Laval, Québec, QC, G1V 0A6, Canada.,Institute of Systems and Integrative Biology, Université Laval, Québec, QC, G1V 0A6, Canada
| | - France Gagnon
- Canada Research Chair in Forest and Environmental Genomics, Centre for Forest Research, Université Laval, Québec, QC, G1V 0A6, Canada.,Institute of Systems and Integrative Biology, Université Laval, Québec, QC, G1V 0A6, Canada
| | - Astrid Deschênes
- Canada Research Chair in Forest and Environmental Genomics, Centre for Forest Research, Université Laval, Québec, QC, G1V 0A6, Canada.,Institute of Systems and Integrative Biology, Université Laval, Québec, QC, G1V 0A6, Canada
| | - Brian Boyle
- Institute of Systems and Integrative Biology, Université Laval, Québec, QC, G1V 0A6, Canada
| | - Jean Beaulieu
- Canada Research Chair in Forest and Environmental Genomics, Centre for Forest Research, Université Laval, Québec, QC, G1V 0A6, Canada.,Natural Resources Canada, Canadian Wood Fibre Centre, 1055 Rue du P.E.P.S., PO Box 10380, Station Sainte-Foy, Québec, QC, G1V 4C7, Canada
| | - Jean Bousquet
- Canada Research Chair in Forest and Environmental Genomics, Centre for Forest Research, Université Laval, Québec, QC, G1V 0A6, Canada.,Institute of Systems and Integrative Biology, Université Laval, Québec, QC, G1V 0A6, Canada
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18
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Characterization of 87 EST-SNP markers in hard clam Meretrix meretrix using high-resolution melting analysis. CONSERV GENET RESOUR 2015. [DOI: 10.1007/s12686-015-0490-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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19
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Carlson BM, Onusko SW, Gross JB. A high-density linkage map for Astyanax mexicanus using genotyping-by-sequencing technology. G3 (BETHESDA, MD.) 2014; 5:241-51. [PMID: 25520037 PMCID: PMC4321032 DOI: 10.1534/g3.114.015438] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 12/11/2014] [Indexed: 12/17/2022]
Abstract
The Mexican tetra, Astyanax mexicanus, is a unique model system consisting of cave-adapted and surface-dwelling morphotypes that diverged >1 million years (My) ago. This remarkable natural experiment has enabled powerful genetic analyses of cave adaptation. Here, we describe the application of next-generation sequencing technology to the creation of a high-density linkage map. Our map comprises more than 2200 markers populating 25 linkage groups constructed from genotypic data generated from a single genotyping-by-sequencing project. We leveraged emergent genomic and transcriptomic resources to anchor hundreds of anonymous Astyanax markers to the genome of the zebrafish (Danio rerio), the most closely related model organism to our study species. This facilitated the identification of 784 distinct connections between our linkage map and the Danio rerio genome, highlighting several regions of conserved genomic architecture between the two species despite ~150 My of divergence. Using a Mendelian cave-associated trait as a proof-of-principle, we successfully recovered the genomic position of the albinism locus near the gene Oca2. Further, our map successfully informed the positions of unplaced Astyanax genomic scaffolds within particular linkage groups. This ability to identify the relative location, orientation, and linear order of unaligned genomic scaffolds will facilitate ongoing efforts to improve on the current early draft and assemble future versions of the Astyanax physical genome. Moreover, this improved linkage map will enable higher-resolution genetic analyses and catalyze the discovery of the genetic basis for cave-associated phenotypes.
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Affiliation(s)
- Brian M Carlson
- Department of Biological Sciences, University of Cincinnati, Cincinnati, Ohio 45221
| | - Samuel W Onusko
- Department of Biological Sciences, University of Cincinnati, Cincinnati, Ohio 45221
| | - Joshua B Gross
- Department of Biological Sciences, University of Cincinnati, Cincinnati, Ohio 45221
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20
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Li C, Gowan S, Anil A, Beck BH, Thongda W, Kucuktas H, Kaltenboeck L, Peatman E. Discovery and validation of gene-linked diagnostic SNP markers for assessing hybridization between Largemouth bass (Micropterus salmoides) and Florida bass (M. floridanus). Mol Ecol Resour 2014; 15:395-404. [DOI: 10.1111/1755-0998.12308] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2014] [Revised: 07/17/2014] [Accepted: 07/18/2014] [Indexed: 11/28/2022]
Affiliation(s)
- Chao Li
- School of Fisheries; Aquaculture and Aquatic Sciences; Auburn University; Auburn AL 36849 USA
| | - Spencer Gowan
- School of Fisheries; Aquaculture and Aquatic Sciences; Auburn University; Auburn AL 36849 USA
| | - Ammu Anil
- School of Fisheries; Aquaculture and Aquatic Sciences; Auburn University; Auburn AL 36849 USA
| | - Benjamin H. Beck
- United States Department of Agriculture; Agricultural Research Service; Stuttgart National Aquaculture Research Center; Stuttgart AR 72160 USA
| | - Wilawan Thongda
- School of Fisheries; Aquaculture and Aquatic Sciences; Auburn University; Auburn AL 36849 USA
| | - Huseyin Kucuktas
- School of Fisheries; Aquaculture and Aquatic Sciences; Auburn University; Auburn AL 36849 USA
| | - Ludmilla Kaltenboeck
- School of Fisheries; Aquaculture and Aquatic Sciences; Auburn University; Auburn AL 36849 USA
| | - Eric Peatman
- School of Fisheries; Aquaculture and Aquatic Sciences; Auburn University; Auburn AL 36849 USA
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