How useful is genomic data for predicting maladaptation to future climate?

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 13, 2023

Abstract Methods using genomic information to forecast potential population maladaptation climate change are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare estimates derived from two methods – Gradient Forests (GF offset ) Risk Of Non-Adaptedness (RONA) exome capture pool-seq data 35 39 populations across three conifer taxa: Douglas-fir varieties jack pine. We evaluate sensitivity these algorithms source input loci (markers selected genotype-environment associations [GEA] or those at random). validate against two-year 52-year growth mortality measured in independent transplant experiments. Overall, find that both often better predict performance than climatic geographic distances. also GF RONA models surprisingly not improved GEA candidates. Even with promising results, variation projections future climates makes it difficult identify most maladapted either method. Our work advances understanding applicability approaches, discuss recommendations for use.

Language: Английский

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Animal board invited review: Widespread adoption of genetic technologies is key to sustainable expansion of global aquaculture

animal, Journal Year: 2022, Volume and Issue: 16(10), P. 100642 - 100642

Published: Sept. 29, 2022

Language: Английский

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Genomic prediction of hybrid performance in grain sorghum (Sorghum bicolor L.)

Frontiers in Plant Science, Journal Year: 2023, Volume and Issue: 14

Published: April 25, 2023

Genomic selection is expected to improve efficiency and genetic gain in breeding programs. The objective of this study was assess the efficacy predicting performance grain sorghum hybrids using genomic information parental genotypes. One hundred two public inbred parents were genotyped genotyping-by-sequencing. Ninty-nine inbreds crossed three tester female generating a total 204 for evaluation at environments. sorted sets 77,59 68 evaluated along with commercial checks randomized complete block design replications. sequence analysis generated 66,265 SNP markers that used predict F1 resulted from crosses between parents. Both additive (partial model) dominance (full constructed tested various training population (TP) sizes cross-validation procedures. Increasing TP size 41 163 increased prediction accuracies all traits. With partial model, five-fold cross validated ranged 0.03 thousand kernel weight (TKW) 0.58 yield (GY) while it 0.06 TKW 0.67 GY full model. results suggest could become an effective tool based on

Language: Английский

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Genome-Wide Association and Genomic Prediction of Growth Traits in the European Flat Oyster (Ostrea edulis)

Frontiers in Genetics, Journal Year: 2022, Volume and Issue: 13

Published: July 15, 2022

The European flat oyster (

Language: Английский

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Genomic selection improves inner shell purpleness in triangle sail mussel Hyriopsis cumingii (Lea, 1852)

Aquaculture, Journal Year: 2023, Volume and Issue: 575, P. 739815 - 739815

Published: June 16, 2023

Language: Английский

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Genomic selection for hypoxia tolerance in large yellow croaker

Aquaculture, Journal Year: 2023, Volume and Issue: 579, P. 740212 - 740212

Published: Oct. 10, 2023

Language: Английский

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Viral nervous necrosis resistance in gilthead sea bream (Sparus aurata) at the larval stage: heritability and accuracy of genomic prediction with different training and testing settings

Genetics Selection Evolution, Journal Year: 2023, Volume and Issue: 55(1)

Published: April 3, 2023

The gilthead sea bream (Sparus aurata) has long been considered resistant to viral nervous necrosis (VNN), until recently, when significant mortalities caused by a reassortant virus (NNV) strain were reported. Selective breeding enhance resistance against NNV might be preventive action. In this study, 972 larvae subjected challenge test and the symptomatology was recorded. All experimental fish their parents genotyped using genome-wide single nucleotide polymorphism (SNP) array consisting of over 26,000 markers.Estimates pedigree-based genomic heritabilities VNN consistent with each other (0.21, highest posterior density interval at 95% (HPD95%): 0.1-0.4; 0.19, HPD95%: 0.1-0.3, respectively). association study suggested one region, i.e., in linkage group (LG) 23 that involved resistance, although it far from significance threshold. accuracies (r) predicted estimated values (EBV) provided three Bayesian regression models (Bayes B, Bayes C, Ridge Regression) on average equal 0.90 assessed set cross-validation (CV) procedures. When relationships between training testing sets minimized, accuracy decreased greatly (r = 0.53 for validation based clustering, r 0.12 leave-one-family-out approach focused challenged fish). Classification phenotype predictions or pedigree-based, all data included, EBV as classifiers moderately accurate (area under ROC curve 0.60 0.66, respectively).The estimate heritability indicates is feasible implement selective programs increased larvae/juveniles. Exploiting information offers opportunity developing prediction tools can trained phenotypes, minimal differences classification performance trait phenotype. long-term view, weakening ties animals leads accuracies, thus periodical update reference population new mandatory.

Language: Английский

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Meta-analysis of GWAS for sea lice load in Atlantic salmon

Aquaculture, Journal Year: 2024, Volume and Issue: 584, P. 740543 - 740543

Published: Jan. 4, 2024

Language: Английский

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Use of whole-genome sequence data for fine mapping and genomic prediction of sea louse resistance in Atlantic salmon

Frontiers in Genetics, Journal Year: 2024, Volume and Issue: 15

Published: April 19, 2024

Sea louse (Lepeophtheirus salmonis) infestation of Atlantic salmon (Salmo salar) is a significant challenge in aquaculture. Over the years, this parasite has developed immunity to medicinal control compounds, and non-medicinal methods have been proven be stressful, hence need study genomic architecture resistance sea lice. Thus, research used whole-genome sequence (WGS) data genetic basis trait since most using fewer SNPs did not identify quantitative loci. Mowi Genetics AS provided genotype (50 k SNPs) phenotype for after conducting lice test on 3,185 smolts belonging 191 full-sib families. The 50 SNP was imputed WGS information from 197 closely related individuals with data. challenged population were then estimate parameters, perform genome-wide association (GWAS), predict breeding values, its accuracy host heritability estimated 0.21 0.22, while prediction 0.65 0.64 array data, respectively. In addition, both any marker associated at level. We conclude that polygenic moderately heritable. predictions medium-density genotyping equally good or better than those based

Language: Английский

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Development and validation of a 40 K liquid SNP array for the mud crab (Scylla paramamosain)

Aquaculture, Journal Year: 2024, Volume and Issue: 594, P. 741394 - 741394

Published: July 28, 2024

Language: Английский

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