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Abstract Background The Citrus reticulata Blanco peels have been widely adopted as functional food or nutraceuticals for thousands of years. In our study, two polysaccharides from the C. reticulata Blanco peels were obtained and named as CRP-WA and CRP-02A, respectively. After characterization by monosaccharide composition, methylation and NMR, chemical structures of CRP-WA and CRP-02A were elucidated. Results As a result, CRP-WA with Mw of 32.8 kDa was an arabinogalactan polysaccharide composed of (β1 → 3) (β1 → 3,6)-D-Galp, (β1 → 4)-D-Manp and (β1 → 4)-D-Glcp units in the backbone. The CRP-02A with Mw of 70.5 kDa was an arabinogalacturonan type pectin formed by (α1 → 4) (α1 → 3,4)-D-GalpA units in the backbone. Moreover, the surface morphologies and rheological properties of CRP-WA and CRP-02A were quite different from each other. Both of these two polysaccharides possessed good antioxidant activities and immunoregulatory effects on RAW 264.7 cells, in which CRP-02A behaved remarkable antioxidant feature, whereas CRP-WA showed relatively high immunoregulatory activity. Conclusion Our study will provide fundamental information for C. reticulata Blanco-based nutritional foods development. Graphical Abstract

Conventional genomic selection models trait individually, neglecting complex trait interactions. Multi-trait models address this by considering genetic correlations, thus improving breeding value accuracy. Despite their theoretical benefits, quantifying these models’ breeding advantages across genetic backgrounds is essential. This study evaluates the benefits of multi-trait models under varying population sizes and three levels of genetic correlations (low, medium, high) using simulations based on 50 K chip data from 5000 individuals. In equal heritability scenarios, the multi-trait GBLUP model consistently outperforms single-trait models, with breeding advantages increasing with heritability. For example, with a reference population of 4500, improvements range from 0.3% to 4.1%. Notably, trait combinations with low heritability are insensitive to changes in genetic correlation, with gains remaining ≤ 0.1% across different genetic correlations under low heritability conditions. In differing heritability scenarios, the multi-trait model’s benefits vary, particularly enhancing low-heritability traits when paired with high-heritability ones. Additionally, modeling time increases as genetic correlation decreases. The results of this study indicate that multi-trait models improve breeding accuracy but require more modeling time and place higher demands on algorithms and software. We recommend breeding strategies tailored to different phenotypes and genetic backgrounds to balance efficiency and accuracy.

Abstract Background Dominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena play a major role in quantitative genetics. However, most genome-wide association studies (GWAS) assume alleles act additively. Results We systematically investigate both dominance—here representing any non-additive within-locus interaction—and additivity across 574 physiological and gene expression traits in three mammalian stocks: F2 intercross pigs, rat heterogeneous stock, and mice heterogeneous stock. Dominance accounts for about one quarter of heritable variance across all physiological traits in all species. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable as additive QTLs, we identify 154, 64, and 62 novel dominance QTLs in pigs, rats, and mice respectively that are undetectable as additive QTLs. Similarly, even though most cis-acting expression QTLs are additive, gene expression exhibits a large fraction of dominance variance, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, thousands of eQTLs are associated with alternatively spliced isoforms with complex additive and dominant architectures in heterogeneous stock rats, suggesting a possible mechanism for dominance. Conclusions Although heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality.

Abstract Background As pre-cut and pre-packaged chilled meat becomes increasingly popular, integrating the carcass-cutting process into the pig industry chain has become a trend. Identifying quantitative trait loci (QTLs) of pork cuts would facilitate the selection of pigs with a higher overall value. However, previous studies solely focused on evaluating the phenotypic and genetic parameters of pork cuts, neglecting the investigation of QTLs influencing these traits. This study involved 17 pork cuts and 12 morphology traits from 2,012 pigs across four populations genotyped using CC1 PorcineSNP50 BeadChips. Our aim was to identify QTLs and evaluate the accuracy of genomic estimated breed values (GEBVs) for pork cuts. Results We identified 14 QTLs and 112 QTLs for 17 pork cuts by GWAS using haplotype and imputation genotypes, respectively. Specifically, we found that HMGA1, VRTN and BMP2 were associated with body length and weight. Subsequent analysis revealed that HMGA1 primarily affects the size of fore leg bones, VRTN primarily affects the number of vertebrates, and BMP2 primarily affects the length of vertebrae and the size of hind leg bones. The prediction accuracy was defined as the correlation between the adjusted phenotype and GEBVs in the validation population, divided by the square root of the trait's heritability. The prediction accuracy of GEBVs for pork cuts varied from 0.342 to 0.693. Notably, ribs, boneless picnic shoulder, tenderloin, hind leg bones, and scapula bones exhibited prediction accuracies exceeding 0.600. Employing better models, increasing marker density through genotype imputation, and pre-selecting markers significantly improved the prediction accuracy of GEBVs. Conclusions We performed the first study to dissect the genetic mechanism of pork cuts and identified a large number of significant QTLs and potential candidate genes. These findings carry significant implications for the breeding of pork cuts through marker-assisted and genomic selection. Additionally, we have constructed the first reference populations for genomic selection of pork cuts in pigs.

Abstract Background Currently, meat cut traits are integrated in pig breeding objectives to gain extra profit. However, little is known about the heritability of meat cut proportions (MCP) and their correlations with other traits. The aims of this study were to assess the heritability and genetic correlation of MCP with carcass and meat quality traits using single nucleotide polymorphism chips and conduct a genome-wide association study (GWAS) to identify candidate genes for MCP. Results Seventeen MCP, 12 carcass, and seven meat quality traits were measured in 2012 pigs from four populations (Landrace; Yorkshire; Landrace and Yorkshire hybrid pigs; Duroc, and Landrace and Yorkshire hybrid pigs). Estimates of the heritability for MCP ranged from 0.10 to 0.55, with most estimates being moderate to high and highly consistent across populations. In the combined population, the heritability estimates for the proportions of scapula bone, loin, back fat, leg bones, and boneless picnic shoulder were 0.44 ± 0.04, 0.36 ± 0.04, 0.44 ± 0.04, 0.38 ± 0.04, and 0.39 ± 0.04, respectively. Proportion of middle cuts was genetically significantly positively correlated with intramuscular fat content and backfat depth. Proportion of ribs was genetically positively correlated with carcass oblique length and straight length (0.35 ± 0.08 to 0.45 ± 0.07) and negatively correlated with backfat depth (− 0.26 ± 0.10 to − 0.45 ± 0.10). However, weak or nonsignificant genetic correlations were observed between most MCP, indicating their independence. Twenty-eight quantitative trait loci (QTL) for MCP were detected by GWAS, and 24 new candidate genes related to MCP were identified, which are involved with growth, height, and skeletal development. Most importantly, we found that the development of the bones in different parts of the body may be regulated by different genes, among which HMGA1 may be the strongest candidate gene affecting forelimb bone development. Moreover, as previously shown, VRTN is a causal gene affecting vertebra number, and BMP2 may be the strongest candidate gene affecting hindlimb bone development. Conclusions Our results indicate that breeding programs for MCP have the potential to enhance carcass composition by increasing the proportion of expensive cuts and decreasing the proportion of inexpensive cuts. Since MCP are post-slaughter traits, the QTL and candidate genes related to these traits can be used for marker-assisted and genomic selection.

Abstract Background Genomic selection is widely applied for genetic improvement in livestock crossbreeding systems to select excellent nucleus purebred (PB) animals and to improve the performance of commercial crossbred (CB) animals. Most current predictions are based solely on PB performance. Our objective was to explore the potential application of genomic selection of PB animals using genotypes of CB animals with extreme phenotypes in a three-way crossbreeding system as the reference population. Using real genotyped PB as ancestors, we simulated the production of 100,000 pigs for a Duroc x (Landrace x Yorkshire) DLY crossbreeding system. The predictive performance of breeding values of PB animals for CB performance using genotypes and phenotypes of (1) PB animals, (2) DLY animals with extreme phenotypes, and (3) random DLY animals for traits of different heritabilities ( $${h}^{2}$$ h 2 = 0.1, 0.3, and 0.5) was compared across different reference population sizes (500 to 6500) and prediction models (genomic best linear unbiased prediction (GBLUP) and Bayesian sparse linear mixed model (BSLMM)). Results Using a reference population consisting of CB animals with extreme phenotypes showed a definite predictive advantage for medium- and low-heritability traits and, in combination with the BSLMM model, significantly improved selection response for CB performance. For high-heritability traits, the predictive performance of a reference population of extreme CB phenotypes was comparable to that of PB phenotypes when the effect of the genetic correlation between PB and CB performance ( $${r}_{pc}$$ r pc ) on the accuracy obtained with a PB reference population was considered, and the former could exceed the latter if the reference size was large enough. For the selection of the first and terminal sires in a three-way crossbreeding system, prediction using extreme CB phenotypes outperformed the use of PB phenotypes, while the optimal design of the reference group for the first dam depended on the percentage of individuals from the corresponding breed that the PB reference data comprised and on the heritability of the target trait. Conclusions A commercial crossbred population is promising for the design of the reference population for genomic prediction, and selective genotyping of CB animals with extreme phenotypes has the potential for maximizing genetic improvement for CB performance in the pig industry.

Abstract Structural variations (SVs) are important DNA polymorphisms that contribute to genetic diversity and evolution in humans, animals, and plants. In this study, we present a novel swine SV dataset of 79,919 deletions, 23,638 duplications, and 9333 inversions with average sequence depths of 24.1× from 24 varieties of worldwide pig populations, encompassing 305 individuals. Genotypes of SVs, particularly deletions, can accurately group individuals based on their population identity. We showed that exon‐covering deletions were subject to negative selection. Fixation index and differential allele frequency analysis identified highly differentiated SVs between European and Asian indigenous pigs, including deletions in NR6A1 and PLAG1, which are significantly associated with vertebrate numbers and growth performances, respectively. The growth‐enhancing allele at the deletion in PLAG1 was shared by European commercial pigs and Northern Chinese indigenous pigs including Laiwu and Min pigs, suggesting potential introgression from European commercial breeds into Chinese indigenous breeds. Moreover, we uncovered highly differentiated SVs in 139 genes between domesticated pigs and wild boars in Asia, temperature and altitude adaptation‐associated SVs in 41 genes, and population‐specific SVs in 718 genes. This study provides novel insights into the role of porcine SVs in domestication, environmental adaptation, and breed formation.

Abstract Background Lentinula edodes (Berk.) is the second most productive mushroom in the world. It contains compounds effective for antiviral, antitumor, antioxidant and immune regulation. Although genomes have previously been reported for this species, a high-quality chromosome-level reference for L. edodes is unavailable. This hinders detailed investigation of population genetics, breeding history of strains and genes related to environmental stress responses. Results A high-quality chromosome-level genome was constructed. We separated a monokaryon from protoplasts of the commercial L. edodes strain L808 and assembled the genome of L. edodes using PacBio long-read and Illumina short-read sequencing, along with the high-throughput chromatin conformation capture (Hi-C) technique. We assembled a 45.87 Mb genome, and 99% of the sequences were anchored onto 10 chromosomes. The contig and scaffold N50 length were 2.17 and 4.94 Mb, respectively. Over 96% of the complete Benchmarking Universal Single-Copy Orthologs (BUSCO) were identified, and 9853 protein-coding genes were predicted. We performed population genome resequencing using 34 wild strains and 65 commercial cultivars of L. edodes originating from China, Japan, the United States and Australia. Based on whole-genome variants, we showed substantial differences in the Chinese wild population, which divided into different branches according to the main areas of their geographical distribution. We also determined the breeding history of L. edodes at the molecular level, and demonstrated that the cultivated strains in China mainly originated from wild strains from China and Northeast Asia. Phenotypic analysis showed that 99 strains exhibited differences on the Cd accumulation. Three significant loci in the of L. edodes genome were identified using the genome-wide association study (GWAS) of Cd accumulation traits. Functional genes associated with Cd accumulation traits were related to DNA ligase and aminoacyl tRNA synthetase, indicating that DNA damage repair and in vivo protein translation may be responses to Cd stress. Conclusions A high-quality chromosome-level genome and population genetic data of L. edodes provide genetic resources for functional genomic, evolutionary and artificial breeding studies for L. edodes.

Abstract Background Short tandem repeats (STRs) were recently found to have significant impacts on gene expression and diseases in humans, but their roles on gene expression and complex traits in pigs remain unexplored. This study investigates the effects of STRs on gene expression in liver tissues based on the whole-genome sequences and RNA-Seq data of a discovery cohort of 260 F6 individuals and a validation population of 296 F7 individuals from a heterogeneous population generated from crosses among eight pig breeds. Results We identified 5203 and 5868 significantly expression STRs (eSTRs, FDR

Abstract Background Carcass length is very important for body size and meat production for swine, thus understanding the genetic mechanisms that underly this trait is of great significance in genetic improvement programs for pigs. Although many quantitative trait loci (QTL) have been detected in pigs, very few have been fine-mapped to the level of the causal mutations. The aim of this study was to identify potential causal single nucleotide polymorphisms (SNPs) for carcass length by integrating a genome-wide association study (GWAS) and functional assays. Results Here, we present a GWAS in a commercial Duroc × (Landrace × Yorkshire) (DLY) population that reveals a prominent association signal (P = 4.49E−07) on pig chromosome 17 for carcass length, which was further validated in two other DLY populations. Within the detected 1 Mb region, the BMP2 gene stood out as the most likely causal candidate because of its functions in bone growth and development. Whole-genome gene expression studies showed that the BMP2 gene was differentially expressed in the cartilage tissues of pigs with extreme carcass length. Then, we genotyped an additional 267 SNPs in 500 selected DLY pigs, followed by further whole-genome SNP imputation, combined with deep genome resequencing data on multiple pig breeds. Reassociation analyses using genotyped and imputed SNP data revealed that the rs320706814 SNP, located approximately 123 kb upstream of the BMP2 gene, was the strongest candidate causal mutation, with a large association with carcass length, with a ~ 4.2 cm difference in length across all three DLY populations (N = 1501; P = 3.66E−29). This SNP segregated in all parental lines of the DLY (Duroc, Large White and Landrace) and was also associated with a significant effect on body length in 299 pure Yorkshire pigs (P = 9.2E−4), which indicates that it has a major value for commercial breeding. Functional assays showed that this SNP is likely located within an enhancer and may affect the binding affinity of transcription factors, thereby regulating BMP2 gene expression. Conclusions Taken together, these results suggest that the rs320706814 SNP on pig chromosome 17 is a putative causal mutation for carcass length in the widely used DLY pigs and has great value in breeding for body size in pigs.

The effect of thermal changes on the physiology and behavior of fish is a major research focus in the face of ongoing global warming. There is little information about the effects of temperature increase on fish in the wild. However, the consequences of temperature increase on fish in controlled laboratory conditions can provide insights into what can be expected in the wild. Triplophysa bleekeri, a high-plateau fish, exhibits high sensitivity to high temperatures, suggesting it to be a good model to investigate the impact of temperature increase on fish. In this study, we analyzed the effect of gradual temperature increase on transcriptional and metabolic levels of T. bleekeri subjected to a gradual temperature change of 0.5°C/day until temperatures of 10°C, 13°C, 16°C, and 19°C were reached. Transcriptomics results of the liver, gut, spleen, and trunk kidney showed that metabolic pathways are widely involved in the response to increased temperatures in T. bleekeri. Lipidomics results further indicated that the lipid composition was altered by increased temperatures, and three lipids (PC 14:0e/22:1, PC 18:0e/22:5, and TAG 14:3-21:2-21:2) were identified as potential biomarkers of heat stress in T. bleekeri. Moreover, a decline in unsaturated fatty acid levels was observed in T. bleekeri under high temperatures. These results suggest that high temperatures modify the metabolomic pathways. Overall, our results help improve the understanding of physiological responses in fish to increased temperatures, and provide valuable information predicting the consequences of global warming on fish.

Northern snakehead, Channa argus (C. argus), is an important economic and ecological fish species. The wild population of the species was sharply declined in the last decade. A high-quality reference genome could lay a solid foundation for the genetic and conservation studies for C. argus. In this work, we report a chromosomal genome assembly with PacBio and Hi-C technology using the albino northern snakehead, a color variety of C. argus. A 644.1-Mb genome with 24 chromosomes was obtained with a contig and scaffold N50 of 11.78 and 27.8 Mb, respectively. We inferred that C. argus diverged from A. testudineus around 85.6 million years ago. 514 expanded gene families and 214 positively selected genes were identified in the C. argus genome. The chromosome-level genome provides a valuable high-quality genomic resource for population, as well as genetic and evolutionary studies for C. argus and other species in Channidae.

Genomic selection is an approach to select elite breeding stock based on the use of dense genetic markers and that has led to the development of various models to derive a predictive equation. However, the current genomic selection software faces several issues such as low prediction accuracy, low computational efficiency, or an inability to handle large-scale sample data. We report the development of a genomic prediction model named FMixFN with four zero-mean normal distributions as the prior distributions to optimize the predictive ability and computing efficiency. The variance of the prior distributions in our model is precisely determined based on an F2 population, and genomic estimated breeding values (GEBV) can be obtained accurately and quickly in combination with an iterative conditional expectation algorithm. We demonstrated that FMixFN improves computational efficiency and predictive ability compared to other methods, such as GBLUP, SSgblup, MIX, BayesR, BayesA, and BayesB. Most importantly, FMixFN may handle large-scale sample data, and thus should be able to meet the needs of large breeding companies or combined breeding schedules. Our study developed a Bayes genomic selection model called FMixFN, which combines stable predictive ability and high computational efficiency, and is a big data-oriented genomic selection model that has potential in the future. The FMixFN method can be freely accessed at https://zenodo.org/record/5560913 (DOI: 10.5281/zenodo.5560913).

In order to reveal the genetic variation signals of Auricularia heimuer that have occurred during their domestication and to find potential functional gene families, we constructed a monokaryotic pan-genome of A. heimuer representing four cultivated strains and four wild strains. The pan-genome contained 14,089 gene families, of which 67.56% were core gene families and 31.88% were dispensable gene families. We screened substrate utilization-related genes such as the chitinase gene ahchi1 of the glycoside hydrolase (GH) 18 family and a carbohydrate-binding module (CBM)-related gene from the dispensable families of cultivated populations. The genomic difference in the ahchi1 gene between the wild and cultivated genomes was caused by a 33 kb presence/absence variation (PAV). The detection rate of the ahchi1 gene was 93.75% in the cultivated population, significantly higher than that in the wild population (17.39%), indicating that it has been selected in cultivated strains. Principal component analysis (PCA) of the polymorphic markers in fragments near the ahchi1 gene was enriched in cultivated strains, and this was caused by multiple independent instances of artificial selection. We revealed for the first time the genetic basis of the ahchi1 gene in domestication, thereby providing a foundation for elucidating the potential function of the ahchi1 gene in the breeding of A. heimuer.