The pig pangenome provides insights into the roles of coding structural variations in genetic diversity and adaptation

Genomic insights into genetic diversity and seed coat color change in common bean composite populations

Introduction

The color of the seed coat of common bean (Phaseolus vulgaris L.) is an important trait influencing marketability and consumer preferences. An understanding of the genetic mechanisms underlying seed coat color variation can aid in breeding programs aimed at improving esthetic and agronomic traits. This study investigates the genetic diversity and molecular mechanisms associated with seed coat color change in composite bean populations through phenotypic analysis and whole genome sequencing (WGS).

Methods

Four composite populations and two standard varieties of common bean were cultivated over a two-year period and seed coat color and morphological traits were assessed. WGS was performed on 19 phenotypes and yielded 427 GB of data with an average sequencing depth of 30×. More than 8.6 million high-confidence single nucleotide polymorphisms (SNPs) were identified. Genetic diversity metrics such as nucleotide diversity (π), observed heterozygosity (Ho), expected heterozygosity (He) and allelic richness (Ar) were calculated. Population structure was analyzed using Fst, principal component analysis (PCA) and clustering. Cross-population statistics (XP-CLR and XP-EHH) were used to identify selection signals associated with seed coat color change. Gene Ontology (GO) and KEGG enrichment analyzes were performed for candidate genomic regions.

Results

Phenotypic analysis revealed significant differences in seed coat color among the four composite populations, with notable changes among years. The populations exhibited different growth habits and plant types, especially KIS_Amand and SRGB_00366, which showed the highest phenotypic diversity in seed coat color. WGS identified 8.6 million SNPs, with chromosomes 4 and 1 having the highest SNP density (11% each), while chromosomes 3 and 6 had the lowest. KIS_Amand had the highest genetic diversity (π = 0.222, Ar = 1.380) and SRGB_00189 the lowest (π = 0.067, Ar = 1.327). SRGB_00366 showed moderate genetic diversity (π = 0.173, Ar = 1.338) and INCBN_03048 showed medium diversity (π = 0.124, Ar = 1.047). The Fst values indicated a strong genetic differentiation, especially between the two standard varieties ETNA and Golden_Gate (Fst = 0.704) and the composite populations. Selective sweep analysis with XP-CLR and XP-EHH identified 118 significant regions associated with seed coat color change, with most regions located on chromosomes 4, 9, 10 and 11. Phosphatidylinositol signaling pathways were highly enriched in candidate regions, indicating that cellular transport mechanisms play a critical role in seed coat pigmentation. Key GO terms included phosphatidylinositol-biphosphate binding, exocytosis, and vesicle-mediated transport, suggesting a link between cellular transport and pigment deposition in the seed coat.

Discussion

The study demonstrates significant genetic diversity within and among common bean composite populations, with KIS_Amand and SRGB_00366 exhibiting the highest phenotypic and genetic variability. The identification of selective sweeps and the enrichment of phosphatidylinositol-related pathways provide new insights into the molecular mechanisms controlling seed coat color variation. The strong genetic differentiation between standard varieties and composite populations highlights the role of selective breeding in shaping the genetic landscape of common bean. The results suggest that variation in seed coat color is controlled by both regulatory and structural genetic changes, providing valuable information for breeding programs.

Conclusion

This study provides a detailed analysis of the genetic architecture of seed coat color variation in common bean. The identification of key genomic regions and pathways associated with seed pigmentation improves our understanding of the complex genetic interactions underlying this trait. These results provide valuable genomic resources for future breeding efforts aimed at improving seed color and other important traits in common bean.

Pangenome graphs and their applications in biodiversity genomics

Complete datasets of genetic variants are key to biodiversity genomic studies. Long-read sequencing technologies allow the routine assembly of highly contiguous, haplotype-resolved reference genomes. However, even when complete, reference genomes from a single individual may bias downstream analyses and fail to adequately represent genetic diversity within a population or species. Pangenome graphs assembled from aligned collections of high-quality genomes can overcome representation bias by integrating sequence information from multiple genomes from the same population, species or genus into a single reference. Here, we review the available tools and data structures to build, visualize and manipulate pangenome graphs while providing practical examples and discussing their applications in biodiversity and conservation genomics across the tree of life.

Construction of the porcine genome mobile element variations and investigation of its role in population diversity and gene expression

BACKGROUND

Mobile element variants (MEVs) have a significant and complex impact on genomic diversity and phenotypic traits. However, the quantity, distribution, and relationship with gene expression and complex traits of MEVs in the pig genome remain poorly understood.

RESULTS

We constructed the most comprehensive porcine MEV library based on high-depth whole genome sequencing (WGS) data from 747 pigs across 59 breeds worldwide. This database identified a total of 147,993 polymorphic MEVs, including 121,099 short interspersed nuclear elements (SINEs), 26,053 long interspersed nuclear elements (LINEs), 802 long terminal repeats (LTRs), and 39 other transposons, among which 54% are newly discovered. We found that MEVs are unevenly distributed across the genome and are strongly influenced by negative selection effects. Importantly, we identified 514, 530, and 584 candidate MEVs associated with population differentiation, domestication, and breed formation, respectively. For example, a significantly differentiated MEV is located in the ATRX intron between Asian and European pigs, whereas ATRX is also differentially expressed between Asian and European pigs in muscle tissue. In addition, we identified 4,169 expressed MEVs (eMEVs) significantly associated with gene expression and 6,914 splicing MEVs (sMEVs) associated with gene splicing based on RNA-seq data from 266 porcine liver tissues. These eMEVs and sMEVs explain 6.24% and 9.47%, respectively, of the observed cis-heritability and highlight the important role of MEVs in the regulation of gene expression. Finally, we provide a high-quality SNP-MEV reference haplotype panel to impute MEV genotypes from genome-wide SNPs. Notably, we identified a candidate MEV significantly associated with total teat number, demonstrating the functionality of this reference panel.

CONCLUSIONS

The present investigation demonstrated the importance of MEVs in pigs in terms of population diversity, gene expression and phenotypic traits, which may provide useful resources and theoretical support for pig genetics and breeding.

The goat pan-genome reveals patterns of gene loss during domestication

BACKGROUND

Unveiling genetic diversity features and understanding the genetic mechanisms of diverse goat phenotypes are pivotal in facilitating the preservation and utilization of these genetic resources. However, the total genetic diversity within a species can't be captured by the reference genome of a single individual. The pan-genome is a collection of all the DNA sequences that occur in a species, and it is expected to capture the total genomic diversity of the specific species.

RESULTS

We constructed a goat pan-genome using map-to-pan assemble based on 813 individuals, including 723 domestic goats and 90 samples from their wild relatives, which presented a broad regional and global representation. In total, 146 Mb sequences and 974 genes were identified as absent from the reference genome (ARS1.2; GCF_001704415.2). We identified 3,190 novel single nucleotide polymorphisms (SNPs) using the pan-genome analysis. These novel SNPs could properly reveal the population structure of domestic goats and their wild relatives. Presence/absence variation (PAV) analysis revealed gene loss and intense negative selection during domestication and improvement.

CONCLUSIONS

Our research highlights the importance of the goat pan-genome in capturing the missing genetic variations. It reveals the changes in genomic architecture during goat domestication and improvement, such as gene loss. This improves our understanding of the evolutionary and breeding history of goats.

Trends and Prospects in Pig Genomics and Genetics

Pork is one of the most commonly consumed meat in the world [...].

A Pilot Detection and Associate Study of Gene Presence-Absence Variation in Holstein Cattle

Presence-absence variations (PAVs) are important structural variations, wherein a genomic segment containing one or more genes is present in some individuals but absent in others. While PAVs have been extensively studied in plants, research in cattle remains limited. This study identified PAVs in 173 Holstein bulls using whole-genome sequencing data and assessed their associations with 46 economically important traits. Out of 28,772 cattle genes (from the longest transcripts), a total of 26,979 (93.77%) core genes were identified (present in all individuals), while variable genes included 928 softcore (present in 95-99% of individuals), 494 shell (present in 5-94%), and 371 cloud genes (present in <5%). Cloud genes were enriched in functions associated with hormonal and antimicrobial activities, while shell genes were enriched in immune functions. PAV-based genome-wide association studies identified associations between gene PAVs and 16 traits including milk, fat, and protein yields, as well as traits related to health and reproduction. Associations were found on multiple chromosomes, illustrating important associations on cattle chromosomes 7 and 15, involving olfactory receptor and immune-related genes, respectively. By examining the PAVs at the population level, the results of this research provided crucial insights into the genetic structures underlying the complex traits of Holstein cattle.

When Livestock Genomes Meet Third-Generation Sequencing Technology: From Opportunities to Applications

Third-generation sequencing technology has found widespread application in the genomic, transcriptomic, and epigenetic research of both human and livestock genetics. This technology offers significant advantages in the sequencing of complex genomic regions, the identification of intricate structural variations, and the production of high-quality genomes. Its attributes, including long sequencing reads, obviation of PCR amplification, and direct determination of DNA/RNA, contribute to its efficacy. This review presents a comprehensive overview of third-generation sequencing technologies, exemplified by single-molecule real-time sequencing (SMRT) and Oxford Nanopore Technology (ONT). Emphasizing the research advancements in livestock genomics, the review delves into genome assembly, structural variation detection, transcriptome sequencing, and epigenetic investigations enabled by third-generation sequencing. A comprehensive analysis is conducted on the application and potential challenges of third-generation sequencing technology for genome detection in livestock. Beyond providing valuable insights into genome structure analysis and the identification of rare genes in livestock, the review ventures into an exploration of the genetic mechanisms underpinning exemplary traits. This review not only contributes to our understanding of the genomic landscape in livestock but also provides fresh perspectives for the advancement of research in this domain.