Aquaculture Molecular Breeding Platform (AMBP): a comprehensive web server for genotype imputation and genetic analysis in aquaculture

Deciphering the population structure and genetic basis of growth traits from whole-genome resequencing of the leopard coral grouper ( Plectropomus leopardus)

The leopard coral grouper ( Plectropomus leopardus) is a species of significant economic importance. Although artificial cultivation of P. leopardus has thrived in recent decades, the advancement of selective breeding has been hindered by the lack of comprehensive population genomic data. In this study, we identified over 8.73 million single nucleotide polymorphisms (SNPs) through whole-genome resequencing of 326 individuals spanning six distinct groups. Furthermore, we categorized 226 individuals with high-coverage sequencing depth (≥14×) into eight clusters based on their genetic profiles and phylogenetic relationships. Notably, four of these clusters exhibited pronounced genetic differentiation compared with the other populations. To identify potentially advantageous loci for P. leopardus, we examined genomic regions exhibiting selective sweeps by analyzing the nucleotide diversity ( θπ) and fixation index ( F ST) in these four clusters. Using these high-coverage resequencing data, we successfully constructed the first haplotype reference panel specific to P. leopardus. This achievement holds promise for enabling high-quality, cost-effective imputation methods. Additionally, we combined low-coverage sequencing data with imputation techniques for a genome-wide association study, aiming to identify candidate SNP loci and genes associated with growth traits. A significant concentration of these genes was observed on chromosome 17, which is primarily involved in skeletal muscle and embryonic development and cell proliferation. Notably, our detailed investigation of growth-related SNPs across the eight clusters revealed that cluster 5 harbored the most promising candidate SNPs, showing potential for genetic selective breeding efforts. These findings provide a robust toolkit and valuable insights into the management of germplasm resources and genome-driven breeding initiatives targeting P. leopardus.

AGIDB: a versatile database for genotype imputation and variant decoding across species

The high cost of large-scale, high-coverage whole-genome sequencing has limited its application in genomics and genetics research. The common approach has been to impute whole-genome sequence variants obtained from a few individuals for a larger population of interest individually genotyped using SNP chip. An alternative involves low-coverage whole-genome sequencing (lcWGS) of all individuals in the larger population, followed by imputation to sequence resolution. To overcome limitations of processing lcWGS data and meeting specific genotype imputation requirements, we developed AGIDB (https://agidb.pro), a website comprising tools and database with an unprecedented sample size and comprehensive variant decoding for animals. AGIDB integrates whole-genome sequencing and chip data from 17 360 and 174 945 individuals, respectively, across 89 species to identify over one billion variants, totaling a massive 688.57 TB of processed data. AGIDB focuses on integrating multiple genotype imputation scenarios. It also provides user-friendly searching and data analysis modules that enable comprehensive annotation of genetic variants for specific populations. To meet a wide range of research requirements, AGIDB offers downloadable reference panels for each species in addition to its extensive dataset, variant decoding and utility tools. We hope that AGIDB will become a key foundational resource in genetics and breeding, providing robust support to researchers.

Improving the accuracy of genomic prediction for meat quality traits using whole genome sequence data in pigs

BACKGROUND

Pork quality can directly affect customer purchase tendency and meat quality traits have become valuable in modern pork production. However, genetic improvement has been slow due to high phenotyping costs. In this study, whole genome sequence (WGS) data was used to evaluate the prediction accuracy of genomic best linear unbiased prediction (GBLUP) for meat quality in large-scale crossbred commercial pigs.

RESULTS

We produced WGS data (18,695,907 SNPs and 2,106,902 INDELs exceed quality control) from 1,469 sequenced Duroc × (Landrace × Yorkshire) pigs and developed a reference panel for meat quality including meat color score, marbling score, L* (lightness), a* (redness), and b* (yellowness) of genomic prediction. The prediction accuracy was defined as the Pearson correlation coefficient between adjusted phenotypes and genomic estimated breeding values in the validation population. Using different marker density panels derived from WGS data, accuracy differed substantially among meat quality traits, varied from 0.08 to 0.47. Results showed that MultiBLUP outperform GBLUP and yielded accuracy increases ranging from 17.39% to 75%. We optimized the marker density and found medium- and high-density marker panels are beneficial for the estimation of heritability for meat quality. Moreover, we conducted genotype imputation from 50K chip to WGS level in the same population and found average concordance rate to exceed 95% and r² = 0.81.

CONCLUSIONS

Overall, estimation of heritability for meat quality traits can benefit from the use of WGS data. This study showed the superiority of using WGS data to genetically improve pork quality in genomic prediction.

Mitochondrial genomic analyses provide new insights into the "missing" atp8 and adaptive evolution of Mytilidae

Background

Mytilidae, also known as marine mussels, are widely distributed in the oceans worldwide. Members of Mytilidae show a tremendous range of ecological adaptions, from the species distributed in freshwater to those that inhabit in deep-sea. Mitochondria play an important role in energy metabolism, which might contribute to the adaptation of Mytilidae to different environments. In addition, some bivalve species are thought to lack the mitochondrial protein-coding gene ATP synthase F0 subunit 8. Increasing studies indicated that the absence of atp8 may be caused by annotation difficulties for atp8 gene is characterized by highly divergent, variable length.

Results

In this study, the complete mitochondrial genomes of three marine mussels (Xenostrobus securis, Bathymodiolus puteoserpentis, Gigantidas vrijenhoeki) were newly assembled, with the lengths of 14,972 bp, 20,482, and 17,786 bp, respectively. We annotated atp8 in the sequences that we assembled and the sequences lacking atp8. The newly annotated atp8 sequences all have one predicted transmembrane domain, a similar hydropathy profile, as well as the C-terminal region with positively charged amino acids. Furthermore, we reconstructed the phylogenetic trees and performed positive selection analysis. The results showed that the deep-sea bathymodiolines experienced more relaxed evolutionary constraints. And signatures of positive selection were detected in nad4 of Limnoperna fortunei, which may contribute to the survival and/or thriving of this species in freshwater.

Conclusions

Our analysis supported that atp8 may not be missing in the Mytilidae. And our results provided evidence that the mitochondrial genes may contribute to the adaptation of Mytilidae to different environments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08940-8.

Animal-SNPAtlas: a comprehensive SNP database for multiple animals

Single-nucleotide polymorphisms (SNPs) as the most important type of genetic variation are widely used in describing population characteristics and play vital roles in animal genetics and breeding. Large amounts of population genetic variation resources and tools have been developed in human, which provided solid support for human genetic studies. However, compared with human, the development of animal genetic variation databases was relatively slow, which limits the genetic researches in these animals. To fill this gap, we systematically identified ∼ 499 million high-quality SNPs from 4784 samples of 20 types of animals. On that basis, we annotated the functions of SNPs, constructed high-density reference panels and calculated genome-wide linkage disequilibrium (LD) matrixes. We further developed Animal-SNPAtlas, a user-friendly database (http://gong_lab.hzau.edu.cn/Animal_SNPAtlas/) which includes high-quality SNP datasets and several support tools for multiple animals. In Animal-SNPAtlas, users can search the functional annotation of SNPs, perform online genotype imputation, explore and visualize LD information, browse variant information using the genome browser and download SNP datasets for each species. With the massive SNP datasets and useful tools, Animal-SNPAtlas will be an important fundamental resource for the animal genomics, genetics and breeding community.

Fine-mapping and association analysis of candidate genes for papilla number in sea cucumber, Apostichopus japonicus

The papilla number is one of the most economically important traits of sea cucumber in the China marketing trade. However, the genetic basis for papilla number diversity in holothurians is still scarce. In the present study, we conducted genome-wide association studies (GWAS) for the trait papilla number of sea cucumbers utilizing a set of 400,186 high-quality SNPs derived from 200 sea cucumbers. Two significant trait-associated SNPs that passed Bonferroni correction (P < 1.25E-7) were located in the intergenic region near PATS1 and the genic region of EIF4G, which were reported to play a pivotal role in cell growth and proliferation. The fine-mapping regions around the top two lead SNPs provided precise causative loci/genes related to papilla formation and cellular activity, including PPP2R3C, GBP1, and BCAS3. Potential SNPs with P < 1E-4 were acquired for the following GO and KEGG enrichment analysis. Moreover, the two lead SNPs were verified in another population of sea cucumber, and the expressive detection of three potential candidate genes PATS1, PPP2R3C, and EIF4G that near or cover the two lead SNPs was conducted in papilla tissue of TG (Top papilla number group) and BG (Bottom papilla number group) by qRT-PCR. We found the significantly higher expression profile of PATS1 (3.34-fold), PPP2R3C (4.90-fold), and EIF4G (4.23-fold) in TG, implying their potential function in papilla polymorphism. The present results provide valuable information to decipher the phenotype differences of the papilla trait and will provide a scientific basis for selective breeding in sea cucumbers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-022-00139-w.