Genetics and Genomics to Enhance the Welfare, Production Efficiency, and Disease Resistance of Farmed Fish and Shellfish Species

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Aquatic Animals".

Deadline for manuscript submissions: closed (20 June 2024) | Viewed by 934

Special Issue Editors


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Guest Editor
The Roslin Institute, The University of Edinburgh, South Bridge, Edinburgh EH8 9YL, UK
Interests: aquaculture genomics; animal genetics and breeding; genomic selection; disease resistance traits; farmed fish; ruminants

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Guest Editor
Department of Comparative Biomedicine and Food Science, University of Padova, Viale dell’Università, 16, 35020 Legnaro, PD, Italy
Interests: aquaculture genomics; disease genomics; genome-wide association studies; genomic prediction; aquaculture breeding

Special Issue Information

Dear Colleagues,

With the rapidly increasing human population, the demand for high-quality animal protein is expected to increase dramatically. Fish and shellfish are important sources of this protein for human food and nutritional security. With the declining catch from wild fisheries, aquaculture provides a sustainable and environmentally clean source of protein for this growing human population. Like the other agricultural productive sectors, aquaculture industries are facing several challenges, including the need for faster-growing, feed-efficient, disease-resistant, and climate-change-resilient strains. Selective breeding is a major strategy to improve traits that are characterized by diverse phenotypes and partly controlled by genetics. The currently available genetic and genomic tools are powerful tools that support selective breeding for different traits of interest for various aquaculture species. Additionally, genomics can also be utilized to assess and monitor genetic diversity and inbreeding levels in aquaculture populations, thus enabling breeders to maximize their diversity while minimizing inbreeding rates in the populations and limiting the potential negative influence of inbreeding depression in aquaculture populations.

The purpose of this issue is to demonstrate that the use of genetic or genomic tools can be useful to improve production efficiency and disease resistance in farmed fish and shellfish species. In this issue, we encourage the submission of papers covering the genetic characterization of traits such as the growth performance and disease resistance of fish and shellfish species, with a particular emphasis on identifying the genetic or genomic background of those important traits, detecting epigenomic signatures underlying phenotypic differences, and providing evidence of the application of genomic and genetic tools to evaluate and select candidate breeders.

Dr. Robert Mukiibi
Dr. Sara Faggion
Guest Editors

Manuscript Submission Information

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Keywords

  • aquaculture genomics
  • disease genomics
  • genome-wide association studies
  • genomic prediction
  • aquaculture breeding
  • population genomics
  • transcriptomics
  • epigenetics
  • fish and shellfish

Published Papers (2 papers)

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Research

18 pages, 2292 KiB  
Article
Transcriptome Analysis Reveals the Immunosuppression in Tiger Pufferfish (Takifugu rubripes) under Cryptocaryon irritans Infection
by Yong Chi, Robert Mukiibi, Hongxiang Zhang, Haien Zhang, Weidong Li, Diego Robledo, Songlin Chen and Yangzhen Li
Animals 2024, 14(14), 2058; https://doi.org/10.3390/ani14142058 (registering DOI) - 13 Jul 2024
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Abstract
The tiger pufferfish (Takifugu rubripes), also known as fugu, has recently suffered from severe C. irritans infections under aquaculture environment, yet the underlying immune mechanisms against the parasite remain poorly understood. In this study, we conducted a comprehensive transcriptome analysis of [...] Read more.
The tiger pufferfish (Takifugu rubripes), also known as fugu, has recently suffered from severe C. irritans infections under aquaculture environment, yet the underlying immune mechanisms against the parasite remain poorly understood. In this study, we conducted a comprehensive transcriptome analysis of the gill tissue from infected and uninfected fish using PacBio long-read (one pooled sample each for seriously infected and healthy individuals, respectively) and Illumina short-read (three pools for mildly infected, seriously infected, and healthy individuals, respectively) RNA sequencing technologies. After aligning sequence data to fugu’s reference genome, 47,307 and 34,413 known full-length transcripts were identified and profiled in healthy and infected fish, respectively. Similarly, we identified and profiled 1126 and 803 novel genes that were obtained from healthy and infected fish, respectively. Interestingly, we found a decrease in the number of alternative splicing (AS) events and long non-coding RNAs (lncRNAs) after infection with C. irritans, suggesting that they may be involved in the regulation of the immune response in fugu. There were 687 and 1535 differentially expressed genes (DEGs) in moderately and heavily infected fish, respectively, compared to uninfected fish. Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that immune-related DEGs in the two comparison groups were mainly enriched in cytokine-cytokine receptor interactions, ECM-receptor interactions, T-cell receptor signaling pathways, Th1 and Th2 cell differentiation, and Th17 cell differentiation pathways. Further analysis revealed that a large number of immune-related genes were downregulated in infected fish relative to uninfected ones, such as CCR7, IL7R, TNFRSF21, CD4, COL2A1, FOXP3B, and ITGA8. Our study suggests that C. irritans is potentially a highly efficient parasite that may disrupt the defense mechanisms of fugu against it. In addition, in combination of short-read RNA sequencing and previous genome-wide association analyses, we identified five key genes (NDUFB6, PRELID1, SMOX, SLC25A4, and DENND1B) that might be closely associated with C. irritans resistance. This study not only provides valuable resources of novel genic transcripts for further research, but also provides new insights into the immune mechanisms underlying C. irritans infection response in farmed fugu. Full article
16 pages, 1654 KiB  
Article
Estimation of Genetic Parameters for Growth and WSSV Resistance Traits in Litopenaeus vannamei
by Juan Sui, Kun Sun, Jie Kong, Jian Tan, Ping Dai, Jiawang Cao, Kun Luo, Sheng Luan, Qun Xing and Xianhong Meng
Animals 2024, 14(12), 1817; https://doi.org/10.3390/ani14121817 - 18 Jun 2024
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Abstract
The current study aimed to provide a precise assessment of the genetic parameters associated with growth and white spot syndrome virus (WSSV) resistance traits in Pacific white shrimp (Litopenaeus vannamei). This was achieved through a controlled WSSV challenge assay and the [...] Read more.
The current study aimed to provide a precise assessment of the genetic parameters associated with growth and white spot syndrome virus (WSSV) resistance traits in Pacific white shrimp (Litopenaeus vannamei). This was achieved through a controlled WSSV challenge assay and the analysis of phenotypic values of five traits: body weight (BW), overall length (OL), body length (BL), tail length (TL), and survival hour post-infection (HPI). The analysis included test data from a total of 1017 individuals belonging to 20 families, of which 293 individuals underwent whole-genome resequencing, resulting in 18,137,179 high-quality SNP loci being obtained. Three methods, including pedigree-based best linear unbiased prediction (pBLUP), genomic best linear unbiased prediction (GBLUP), and single-step genomic BLUP (ssGBLUP) were utilized. Compared to the pBLUP model, the heritability of growth-related traits obtained from GBLUP and ssGBLUP was lower, whereas the heritability of WSSV resistance was higher. Both the GBLUP and ssGBLUP models significantly enhanced prediction accuracy. Specifically, the GBLUP model improved the prediction accuracy of BW, OL, BL, TL, and HPI by 4.77%, 21.93%, 19.73%, 19.34%, and 63.44%, respectively. Similarly, the ssGBLUP model improved prediction accuracy by 10.07%, 25.44%, 25.72%, 19.34%, and 122.58%, respectively. The WSSV resistance trait demonstrated the most substantial enhancement using both genomic prediction models, followed by body size traits (e.g., OL, BL, and TL), with BW showing the least improvement. Furthermore, the choice of models minimally impacted the assessment of genetic and phenotypic correlations. Genetic correlations among growth traits ranged from 0.767 to 0.999 across models, indicating high levels of positive correlations. Genetic correlations between growth and WSSV resistance traits ranged from (−0.198) to (−0.019), indicating low levels of negative correlations. This study assured significant advantages of the GBLUP and ssGBLUP models over the pBLUP model in the genetic parameter estimation of growth and WSSV resistance in L. vannamei, providing a foundation for further breeding programs. Full article
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