4.3 Article

Accuracies of genomic predictions for disease resistance of striped catfish to Edwardsiella ictaluri using artificial intelligence algorithms

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Fisheries

Genetic correlations between challenge tested susceptibility to bacillary necrosis, caused by Edwardsiella ictaluri, and growth performance tested survival and harvest body weight in Mekong striped catfish (Pangasianodon hypophthalmus)

Khoi Dinh Pham et al.

Summary: The study found a weak genetic correlation between susceptibility to bacillary necrosis and growth and survival in Mekong striped catfish, as well as a moderate favorable genetic correlation between growth and survival. To continue challenge testing in Vietnam, a strong genetic relationship needs to be established between bacillary necrosis and survival under a natural disease outbreak, requiring another field test.

JOURNAL OF FISH DISEASES (2021)

Article Fisheries

Genomic prediction of growth traits in scallops using convolutional neural networks

Xinghai Zhu et al.

Summary: Deep learning neural networks, specifically convolutional neural networks, have shown promising performance in genomic prediction of complex traits in a Bay scallop population. CNNs outperformed linear models and multilayer perceptron neural networks on shell height, shell width, and total weight prediction accuracy. However, further optimization of CNN structures is needed for improved accuracy in scallop genomic prediction.

AQUACULTURE (2021)

Review Biotechnology & Applied Microbiology

A review of deep learning applications for genomic selection

Osval Antonio Montesinos-Lopez et al.

Summary: Deep learning methods have been widely applied in genomic selection, showing potential to capture nonlinear patterns and improve prediction accuracy. However, their advantages compared to traditional genomic prediction methods are not significantly clear, and the key to utilizing DL lies in having an adequate amount of high-quality training data.

BMC GENOMICS (2021)

Article Fisheries

Genetic analysis of resistance in Mekong striped catfish (Pangasianodon hypophthalmus) to bacillary necrosis caused by Edwardsiella ictaluri

Khoi Dinh Pham et al.

Summary: This study aimed to analyze four cohabitation challenge-test experiments with Mekong striped catfish against the bacterium E. ictaluri using genetic analysis, finding heritability estimates in two different cross-sectional models.

JOURNAL OF FISH DISEASES (2021)

Article Fisheries

Genomic selection using a subset of SNPs identified by genome-wide association analysis for disease resistance traits in aquaculture species

Zheng Luo et al.

Summary: In this study, a strategy for genomic selection (GS) using a subset of markers selected by genome wide association studies (GWAS) was proposed. Results showed that using GWAS-selected SNPs improved prediction accuracy compared to using total SNPs, with the BayesB model outperforming the GBLUP model. Optimal SNP numbers for GS varied for different traits and species.

AQUACULTURE (2021)

Article Engineering, Marine

Genome-Wide Marker Analysis for Traits of Economic Importance in Asian Seabass Lates calcarifer

Nguyen Hong Nguyen et al.

Summary: The study aimed to assess the genomic prediction accuracy for growth traits in Asian seabass and found high prediction accuracies for growth traits but low for survival traits. It also attempted to identify markers associated with body weight and found moderate SNP heritability, with no significant associations detected for other traits.

JOURNAL OF MARINE SCIENCE AND ENGINEERING (2021)

Article Fisheries

Predicting for disease resistance in aquaculture species using machine learning models

Christos Palaiokostas

Summary: The study tested the efficiency of various machine learning models in predicting disease resistance and found that XGB performed the best in most datasets, with a slight advantage over GBLUP-MCMC. SVM and RF models also provided predictions close to XGB and GBLUP-MCMC. Adaboost yielded slightly lower predictions, while DT consistently performed poorly in predictions compared to GBLUP-MCMC.

AQUACULTURE REPORTS (2021)

Article Fisheries

Data imputation and machine learning improve association analysis and genomic prediction for resistance to fish photobacteriosis in the gilthead sea bream

Luca Bargelloni et al.

Summary: This study identified eight novel genetic loci for resistance to photobacteriosis in gilthead sea bream and revealed a highly polygenic genetic architecture. Machine learning methods, particularly linear bagging, showed higher prediction performance compared to Bayesian regression approaches, indicating that exploring these methods in parallel could increase the chances of highly effective genomic prediction.

AQUACULTURE REPORTS (2021)

Article Agriculture, Dairy & Animal Science

Bayesian genomic models boost prediction accuracy for survival to Streptococcus agalactiae infection in Nile tilapia (Oreochromus nilioticus)

Rajesh Joshi et al.

Summary: This study demonstrates the potential of genomic selection for survival to S. agalactiae infection in Nile tilapia. Bayesian genomic models were found to significantly boost prediction accuracy compared to pedigree-based and GBLUP models.

GENETICS SELECTION EVOLUTION (2021)

Article Fisheries

Case study development of a challenge test against Edwardsiella ictaluri in Mekong striped catfish (Pangasianodon hypophthalmus), for use in breeding: Estimates of the genetic correlation between susceptibilities in replicated tanks

Khoi Dinh Pham et al.

Summary: The challenge tests for bacillary necrosis in Mekong striped catfish suggested pre-acclimatization, cohabitant and bacteria addition methods. Results indicated that focus should be on bacteria density, timing of bacteria addition, and selecting genetic traits for resistance. Replicated tank tests showed consistent resistance trait in the same experiment.

JOURNAL OF FISH DISEASES (2021)

Article Biochemical Research Methods

AlphaFamlmpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data

Andrew Whalen et al.

BIOINFORMATICS (2020)

Article Plant Sciences

Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species

Laura M. Zingaretti et al.

FRONTIERS IN PLANT SCIENCE (2020)

Review Genetics & Heredity

Harnessing genomics to fast-track genetic improvement in aquaculture

Ross D. Houston et al.

NATURE REVIEWS GENETICS (2020)

Article Engineering, Marine

Population Genomic Analyses of Wild and Farmed Striped Catfish Pangasianodon Hypophthalmus in the Lower Mekong River

Nguyen Thanh Vu et al.

JOURNAL OF MARINE SCIENCE AND ENGINEERING (2020)

Article Agriculture, Dairy & Animal Science

Multi-omics-data-assisted genomic feature markers preselection improves the accuracy of genomic prediction

Shaopan Ye et al.

JOURNAL OF ANIMAL SCIENCE AND BIOTECHNOLOGY (2020)

Article Multidisciplinary Sciences

GMStool: GWAS-based marker selection tool for genomic prediction from genomic data

Seongmun Jeong et al.

SCIENTIFIC REPORTS (2020)

Article Biotechnology & Applied Microbiology

KAML: improving genomic prediction accuracy of complex traits using machine learning determined parameters

Lilin Yin et al.

GENOME BIOLOGY (2020)

Article Genetics & Heredity

New Deep Learning Genomic-Based Prediction Model for Multiple Traits with Binary, Ordinal, and Continuous Phenotypes

Osval A. Montesinos-Lopez et al.

G3-GENES GENOMES GENETICS (2019)

Article Biotechnology & Applied Microbiology

Predicting male fertility in dairy cattle using markers with large effect and functional annotation data

Juan Pablo Nani et al.

BMC GENOMICS (2019)

Article Agriculture, Dairy & Animal Science

Effect of selection and selective genotyping for creation of reference on bias and accuracy of genomic prediction

Gopal R. Gowane et al.

JOURNAL OF ANIMAL BREEDING AND GENETICS (2019)

Review Genetics & Heredity

A Guide on Deep Learning for Complex Trait Genomic Prediction

Miguel Perez-Enciso et al.

Article Agriculture, Dairy & Animal Science

Using imputed whole-genome sequence data to improve the accuracy of genomic prediction for parasite resistance in Australian sheep

Mohammad Al Kalaldeh et al.

GENETICS SELECTION EVOLUTION (2019)

Review Fisheries

Applications of genotyping by sequencing in aquaculture breeding and genetics

Diego Robledo et al.

REVIEWS IN AQUACULTURE (2018)

Article Biochemistry & Molecular Biology

DARTR: An R package to facilitate analysis of SNP data generated from reduced representation genome sequencing

Bernd Gruber et al.

MOLECULAR ECOLOGY RESOURCES (2018)

Article Genetics & Heredity

Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits

Osval A. Montesinos-Lopez et al.

G3-GENES GENOMES GENETICS (2018)

Article Agriculture, Dairy & Animal Science

Hybrid peeling for fast and accurate calling, phasing, and imputation with sequence data of any coverage in pedigrees

Andrew Whalen et al.

GENETICS SELECTION EVOLUTION (2018)

Article Agriculture, Dairy & Animal Science

Predicting bull fertility using genomic data and biological information

Rostam Abdollahi-Arpanahi et al.

JOURNAL OF DAIRY SCIENCE (2017)

Article Genetics & Heredity

Genotype Imputation To Improve the Cost-Efficiency of Genomic Selection in Farmed Atlantic Salmon

Hsin-Yuan Tsai et al.

G3-GENES GENOMES GENETICS (2017)

Article Agriculture, Dairy & Animal Science

Accuracies of univariate and multivariate genomic prediction models in African cassava

Uche Godfrey Okeke et al.

GENETICS SELECTION EVOLUTION (2017)

Article Agriculture, Dairy & Animal Science

Selecting sequence variants to improve genomic predictions for dairy cattle

Paul M. VanRaden et al.

GENETICS SELECTION EVOLUTION (2017)

Article Agriculture, Dairy & Animal Science

Accuracy of genomic prediction using imputed whole-genome sequence data in white layers

M. Heidaritabar et al.

JOURNAL OF ANIMAL BREEDING AND GENETICS (2016)

Article Statistics & Probability

PresenceAbsence: AnRPackage for Presence Absence Analysis

Elizabeth A. Freeman et al.

Journal of Statistical Software (2015)

Article Agriculture, Dairy & Animal Science

Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle

Rianne van Binsbergen et al.

GENETICS SELECTION EVOLUTION (2015)

Article Biotechnology & Applied Microbiology

A new approach for efficient genotype imputation using information from relatives

Mehdi Sargolzaei et al.

BMC GENOMICS (2014)

Article Genetics & Heredity

Genomic Prediction in Maize Breeding Populations with Genotyping-by-Sequencing

Jose Crossa et al.

G3-GENES GENOMES GENETICS (2013)

Article Agriculture, Dairy & Animal Science

A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

John M. Hickey et al.

GENETICS SELECTION EVOLUTION (2012)

Article Multidisciplinary Sciences

A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

Robert J. Elshire et al.

PLOS ONE (2011)

Article Agriculture, Dairy & Animal Science

Genome-wide prediction of discrete traits using bayesian regressions and machine learning

Oscar Gonzalez-Recio et al.

GENETICS SELECTION EVOLUTION (2011)

Article Biotechnology & Applied Microbiology

RADSeq: next-generation population genetics

John L. Davey et al.

BRIEFINGS IN FUNCTIONAL GENOMICS (2010)

Article Agriculture, Dairy & Animal Science

Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information

I. Misztal et al.

JOURNAL OF DAIRY SCIENCE (2009)

Review Agriculture, Dairy & Animal Science

Invited review: Genomic selection in dairy cattle: Progress and challenges

B. J. Hayes et al.

JOURNAL OF DAIRY SCIENCE (2009)

Article Agriculture, Dairy & Animal Science

Efficient Methods to Compute Genomic Predictions

P. M. VanRaden

JOURNAL OF DAIRY SCIENCE (2008)

Article Genetics & Heredity

PLINK: A tool set for whole-genome association and population-based linkage analyses

Shaun Purcell et al.

AMERICAN JOURNAL OF HUMAN GENETICS (2007)