The Bovine Pangenome Consortium: democratizing production and accessibility of genome assemblies for global cattle breeds and other bovine species

Long read and preliminary pangenome analyses reveal breed-specific structural variations and novel sequences in Holstein and Jersey cattle

INTRODUCTION

Most SV studies in livestock rely on short-read sequencing, posing challenges in accurately characterizing large genomic variants due to their limited read length.

OBJECTIVES

Our goal is to reveal structural variation and novel sequences specific to Holstein and Jersey cattle breeds using long-read and pan-genome analyses.

METHODS

We sequenced 20 Holsteins and 8 Jersey cattle using PacBio HiFi to 20×, and integrated five read-based and one assembly-based SV caller to determine SVs.

RESULTS

We assembled the 28 genomes averaging 3.25 Gb with a contig N50 of 69.36 Mb and using the ARS-UCD1.2 reference, we acquired Holstein/Jersey SV catalogs with 74,068/54,689 events spanning 202/135 Mb (7.43 %/4.97 % of the genome). SVs were enriched in less conserved, non-coding, and non-regulatory regions. Comparing Holsteins with differing feed efficiency (FE), SVs unique to high FE were linked to energy metabolism and olfactory receptors, while those specific to low FE were associated with material transport. We constructed Holstein/Jersey pangenome graphs with 148,598/105,875 nodes and 208,891/147,990 edges, representing 47,028/37,137 biallelic and multi-allelic events, and 63.75/42.34 Mb of novel sequence. We observed SV count saturation with 20 Holsteins, while adding Jerseys significantly increased the SV count, highlighting breed-specific SV events.

CONCLUSION

Our long-read data and SV catalogs are valuable resources, revealing that the cattle genome is more complex than previously thought.

Taurine pangenome uncovers a segmental duplication upstream of KIT associated with depigmentation in white-headed cattle

Cattle have been selectively bred for coat color, spotting, and depigmentation patterns. The assumed autosomal dominant inherited genetic variants underlying the characteristic white head of Fleckvieh, Simmental, and Hereford cattle have not been identified yet, although the contribution of structural variation upstream of the KIT gene has been proposed. Here, we construct a graph pangenome from 24 haplotype assemblies representing seven taurine cattle breeds to identify and characterize the white-head-associated locus for the first time based on long-read sequencing data and pangenome analyses. We introduce a pangenome-wide association mapping approach that examines assembly path similarities within the graph to reveal an association between two most likely serial alleles of a complex structural variant (SV) 66 kb upstream of KIT and facial depigmentation. The complex SV contains a variable number of tandemly duplicated 14.3 kb repeats, consisting of LTRs, LINEs, and other repetitive elements, leading to misleading alignments of short and long reads when using a linear reference. We align 250 short-read sequencing samples spanning 15 cattle breeds to the pangenome graph, further validating that the alleles of the SV segregate with head depigmentation. We estimate an increased count of repeats in Hereford relative to Simmental and other white-headed cattle breeds from the graph alignment coverage, suggesting a large under-assembly in the current Hereford-based cattle reference genome, which had fewer copies. Our work shows that exploiting assembly path similarities within graph pangenomes can reveal trait-associated complex SVs.

Notable challenges posed by long-read sequencing for the study of transcriptional diversity and genome annotation

Long-read sequencing (LRS) technologies have revolutionized transcriptomic research by enabling the comprehensive sequencing of full-length transcripts. Using these technologies, researchers have reported tens of thousands of novel transcripts, even in well-annotated genomes, while developing new algorithms and experimental approaches to handle the noisy data. The Long-read RNA-seq Genome Annotation Assessment Project community effort benchmarked LRS methods in transcriptomics and validated many novel, lowly expressed, often times sample-specific transcripts identified by long reads. These molecules represent deviations of the major transcriptional program that were overlooked by short-read sequencing methods but are now captured by the full-length, single-molecule approach. This Perspective discusses the challenges and opportunities associated with LRS' capacity to unravel this fraction of the transcriptome, in terms of both transcriptome biology and genome annotation. For transcriptome biology, we need to develop novel experimental and computational methods to effectively differentiate technology errors from rare but real molecules. For genome annotation, we must agree on the strategy to capture molecular variability while still defining reference annotations that are useful for the genomics community.

The Farm Animal Genotype-Tissue Expression (FarmGTEx) Project

Genetic mutation and drift, coupled with natural and human-mediated selection and migration, have produced a wide variety of genotypes and phenotypes in farmed animals. We here introduce the Farm Animal Genotype-Tissue Expression (FarmGTEx) Project, which aims to elucidate the genetic determinants of gene expression across 16 terrestrial and aquatic domestic species under diverse biological and environmental contexts. For each species, we aim to collect multiomics data, particularly genomics and transcriptomics, from 50 tissues of 1,000 healthy adults and 200 additional animals representing a specific context. This Perspective provides an overview of the priorities of FarmGTEx and advocates for coordinated strategies of data analysis and resource-sharing initiatives. FarmGTEx aims to serve as a platform for investigating context-specific regulatory effects, which will deepen our understanding of molecular mechanisms underlying complex phenotypes. The knowledge and insights provided by FarmGTEx will contribute to improving sustainable agriculture-based food systems, comparative biology and eventual human biomedicine.

Genetic advancements and future directions in ruminant livestock breeding: from reference genomes to multiomics innovations

Ruminant livestock provide a rich source of products, such as meat, milk, and wool, and play a critical role in global food security and nutrition. Over the past few decades, genomic studies of ruminant livestock have provided valuable insights into their domestication and the genetic basis of economically important traits, facilitating the breeding of elite varieties. In this review, we summarize the main advancements for domestic ruminants in reference genome assemblies, population genomics, and the identification of functional genes or variants for phenotypic traits. These traits include meat and carcass quality, reproduction, milk production, feed efficiency, wool and cashmere yield, horn development, tail type, coat color, environmental adaptation, and disease resistance. Functional genomic research is entering a new era with the advancements of graphical pangenomics and telomere-to-telomere (T2T) gap-free genome assembly. These advancements promise to improve our understanding of domestication and the molecular mechanisms underlying economically important traits in ruminant livestock. Finally, we provide new perspectives and future directions for genomic research on ruminant genomes. We suggest how ever-increasing multiomics datasets will facilitate future studies and molecular breeding in livestock, including the potential to uncover novel genetic mechanisms underlying phenotypic traits, to enable more accurate genomic prediction models, and to accelerate genetic improvement programs.

Pangenome graph mitigates heterozygosity overestimation from mapping bias: a case study in Chinese indigenous pigs

BACKGROUND

Breeds genetically distant from the reference genome often show considerable differences in DNA fragments, making it difficult to achieve accurate mappings. The genetic differences between pig reference genome (Sscrofa11.1) and Chinese indigenous pigs may lead to mapping bias and affect subsequent analyses.

RESULTS

Our analysis revealed that pangenome exhibited superior mapping accuracy to the Sscrofa11.1, reducing false-positive mappings by 1.4% and erroneous mappings by 0.8%. Furthermore, the pangenome yielded more accurate genotypes of SNP (F1: 0.9660 vs. 0.9607) and INDEL (F1: 0.9226 vs. 0.9222) compared to Sscrofa11.1. In real sequencing data, the inconsistent SNPs called from the pangenome exhibited lower genome heterozygosity compared to those identified by the Sscrofa11.1, including observed heterozygosity and nucleotide diversity. The same reduction of heterozygosity overestimation was also found in the chicken pangenome.

CONCLUSIONS

This study quantifies the mapping bias of Sscrofa11.1 in Chinese indigenous pigs, demonstrating that mapping bias can lead to an overestimation of heterozygosity in Chinese indigenous pig breeds. The adoption of a pig pangenome mitigates this bias and provides a more accurate representation of genetic diversity in these populations.

Advancing the Indian cattle pangenome: characterizing non-reference sequences in Bos indicus

BACKGROUND

India harbors the world's largest cattle population, encompassing over 50 distinct Bos indicus breeds. This rich genetic diversity underscores the inadequacy of a single reference genome to fully capture the genomic landscape of Indian cattle. To comprehensively characterize the genomic variation within Bos indicus and, specifically, dairy breeds, we aim to identify non-reference sequences and construct a comprehensive pangenome.

RESULTS

Five representative genomes of prominent dairy breeds, including Gir, Kankrej, Tharparkar, Sahiwal, and Red Sindhi, were sequenced using 10X Genomics 'linked-read' technology. Assemblies generated from these linked-reads ranged from 2.70 Gb to 2.77 Gb, comparable to the Bos indicus Brahman reference genome. A pangenome of Bos indicus cattle was constructed by comparing the newly assembled genomes with the reference using alignment and graph-based methods, revealing 8 Mb and 17.7 Mb of novel sequence respectively. A confident set of 6,844 Non-reference Unique Insertions (NUIs) spanning 7.57 Mb was identified through both methods, representing the pangenome of Indian Bos indicus breeds. Comparative analysis with previously published pangenomes unveiled 2.8 Mb (37%) commonality with the Chinese indicine pangenome and only 1% commonality with the Bos taurus pangenome. Among these, 2,312 NUIs encompassing ~ 2 Mb, were commonly found in 98 samples of the 5 breeds and designated as Bos indicus Common Insertions (BICIs) in the population. Furthermore, 926 BICIs were identified within 682 protein-coding genes, 54 long non-coding RNAs (lncRNA), and 18 pseudogenes. These protein-coding genes were enriched for functions such as chemical synaptic transmission, cell junction organization, cell-cell adhesion, and cell morphogenesis. The protein-coding genes were found in various prominent quantitative trait locus (QTL) regions, suggesting potential roles of BICIs in traits related to milk production, reproduction, exterior, health, meat, and carcass. Notably, 63.21% of the bases within the BICIs call set contained interspersed repeats, predominantly Long Interspersed Nuclear Elements (LINEs). Additionally, 70.28% of BICIs are shared with other domesticated and wild species, highlighting their evolutionary significance.

CONCLUSIONS

This is the first report unveiling a robust set of NUIs defining the pangenome of Bos indicus breeds of India. The analyses contribute valuable insights into the genomic landscape of desi cattle breeds.

Genome assembly of wisent (Bison bonasus) uncovers a deletion that likely inactivates the THRSP gene

The wisent (Bison bonasus) is Europe's largest land mammal. We produced a HiFi read-based wisent assembly with a contig N50 value of 91 Mb containing 99.7% of the highly conserved single copy mammalian genes which improves contiguity a thousand-fold over an existing assembly. Extended runs of homozygosity in the wisent genome compromised the separation of the HiFi reads into parental-specific read sets, which resulted in inferior haplotype assemblies. A bovine super-pangenome built with assemblies from wisent, bison, gaur, yak, taurine and indicine cattle identified a 1580 bp deletion removing the protein-coding sequence of THRSP encoding thyroid hormone-responsive protein from the wisent and bison genomes. Analysis of 725 sequenced samples across the Bovinae subfamily showed that the deletion is fixed in both Bison species but absent in Bos and Bubalus. The THRSP transcript is abundant in adipose, fat, liver, muscle, and mammary gland tissue of Bos and Bubalus, but absent in bison. This indicates that the deletion likely inactivates THRSP in bison. We show that super-pangenomes can reveal potentially trait-associated variation across phylogenies, but also demonstrate that haplotype assemblies from species that went through population bottlenecks warrant scrutiny, as they may have accumulated long runs of homozygosity that complicate phasing.

Tailoring Genomic Selection for Bos taurus indicus: A Comprehensive Review of SNP Arrays and Reference Genomes

BACKGROUND

Advances in SNP arrays and reference genome assemblies have significantly transformed cattle genomics, particularly for Bos taurus indicus (Zebu cattle). Many commercial SNP arrays were originally designed for Bos taurus taurus, leading to ascertainment bias and the exclusion of crucial SNPs specific to Zebu populations. This review assesses progress in SNP array and reference genome development, with a focus on efforts tailored to Zebu populations and their impact on genomic selection and breeding efficiency.

METHODS

We reviewed the relevant literature on the development of SNP arrays, reference genome assemblies, and SNP genotyping techniques used for Zebu cattle. Emphasis was placed on SNP arrays specifically designed for Zebu breeds, evaluating their contributions to genomic evaluations and identifying limitations in prediction accuracy.

RESULTS

Recent advancements, such as GeneSeek's low- and high-density SNP panels, have aimed to reduce ascertainment bias and include key SNPs for Zebu populations by providing breed-specific panels. These panels have been instrumental in identifying genomic regions associated with economically important traits in Nellore cattle. Studies show that tailored SNP arrays and breed-specific reference genomes can enhance genetic diversity assessment and improve genomic predictions, supporting more effective breeding programs for Zebu cattle.

CONCLUSIONS

Improved SNP arrays and breed-specific reference genomes are crucial for accurate genomic selection in Zebu cattle. Future efforts should prioritize expanding de novo genome assemblies, reducing ascertainment bias, and developing cost-effective genotyping solutions tailored to Zebu populations. Targeted genomic tools will ultimately enable more efficient breeding practices and enhance genomic selection for economically important traits in B. t. indicus cattle.

Integer programming framework for pangenome-based genome inference

Affordable genotyping methods are essential in genomics. Commonly used genotyping methods primarily support single nucleotide variants and short indels but neglect structural variants. Additionally, accuracy of read alignments to a reference genome is unreliable in highly polymorphic and repetitive regions, further impacting genotyping performance. Recent works highlight the advantage of haplotype-resolved pangenome graphs in addressing these challenges. Building on these developments, we propose a rigorous alignment-free genotyping framework. Our formulation seeks a path through the pangenome graph that maximizes the matches between the path and substrings of sequencing reads (e.g., k-mers) while minimizing recombination events (haplotype switches) along the path. We prove that this problem is NP-Hard and develop efficient integer-programming solutions. We benchmarked the algorithm using downsampled short-read datasets from homozygous human cell lines with coverage ranging from 0.1× to 10×. Our algorithm accurately estimates complete major histocompatibility complex (MHC) haplotype sequences with small edit distances from the ground-truth sequences, providing a significant advantage over existing methods on low-coverage inputs. Although our algorithm is designed for haploid samples, we discuss future extensions to diploid samples.

An overview of recent technological developments in bovine genomics

Cattle are regarded as highly valuable animals because of their milk, beef, dung, fur, and ability to draft. The scientific community has tried a number of strategies to improve the genetic makeup of bovine germplasm. To ensure higher returns for the dairy and beef industries, researchers face their greatest challenge in improving commercially important traits. One of the biggest developments in the last few decades in the creation of instruments for cattle genetic improvement is the discovery of the genome. Breeding livestock is being revolutionized by genomic selection made possible by the availability of medium- and high-density single nucleotide polymorphism (SNP) arrays coupled with sophisticated statistical techniques. It is becoming easier to access high-dimensional genomic data in cattle. Continuously declining genotyping costs and an increase in services that use genomic data to increase return on investment have both made a significant contribution to this. The field of genomics has come a long way thanks to groundbreaking discoveries such as radiation-hybrid mapping, in situ hybridization, synteny analysis, somatic cell genetics, cytogenetic maps, molecular markers, association studies for quantitative trait loci, high-throughput SNP genotyping, whole-genome shotgun sequencing to whole-genome mapping, and genome editing. These advancements have had a significant positive impact on the field of cattle genomics. This manuscript aimed to review recent advances in genomic technologies for cattle breeding and future prospects in this field.

Genome assembly in the telomere-to-telomere era

Genome sequences largely determine the biology and encode the history of an organism, and de novo assembly - the process of reconstructing the genome sequence of an organism from sequencing reads - has been a central problem in bioinformatics for four decades. Until recently, genomes were typically assembled into fragments of a few megabases at best, but now technological advances in long-read sequencing enable the near-complete assembly of each chromosome - also known as telomere-to-telomere assembly - for many organisms. Here, we review recent progress on assembly algorithms and protocols, with a focus on how to derive near-telomere-to-telomere assemblies. We also discuss the additional developments that will be required to resolve remaining assembly gaps and to assemble non-diploid genomes.

A Comparative Full-Length Transcriptome Analysis Using Oxford Nanopore Technologies (ONT) in Four Tissues of Bovine Origin

The transcriptome complexity and splicing patterns in male and female cattle are ambiguous, presenting a substantial obstacle to genomic selection programs that seek to improve productivity, disease resistance, and reproduction in cattle. A comparative transcriptomic analysis using Oxford Nanopore Technologies (ONT) was conducted in bovine testes (TESTs), ovaries (OVAs), muscles (MUSCs), and livers (LIVs). An average of 5,144,769 full-length reads were obtained from each sample. The TESTs were found to have the greatest number of alternative polyadenylation (APA) events involved in processes such as sperm flagellum development and fertilization in male reproduction. In total, 438 differentially expressed transcripts (DETs) were identified in the LIVs in a comparison of females vs. males, and 214 DETs were identified in the MUSCs between females and males. Additionally, 14,735, 36,347, and 33,885 DETs were detected in MUSC vs. LIV, MUSC vs. TEST, and OVA vs. TEST comparisons, respectively, revealing the complexity of the TEST. Gene Set Enrichment Analysis (GSEA) showed that these DETs were mainly involved in the "spermatogenesis", "flagellated sperm motility", "spermatid development", "reproduction", "reproductive process", and "microtubule-based movement" KEGG pathways. Additional studies are necessary to further characterize the transcriptome in different cell types, developmental stages, and physiological conditions in bovines and ascertain the functions of the novel transcripts.

Single-Cell Sequencing Technology in Ruminant Livestock: Challenges and Opportunities

Advancements in single-cell sequencing have transformed the genomics field by allowing researchers to delve into the intricate cellular heterogeneity within tissues at greater resolution. While single-cell omics are more widely applied in model organisms and humans, their use in livestock species is just beginning. Studies in cattle, sheep, and goats have already leveraged single-cell and single-nuclei RNA-seq as well as single-cell and single-nuclei ATAC-seq to delineate cellular diversity in tissues, track changes in cell populations and gene expression over developmental stages, and characterize immune cell populations important for disease resistance and resilience. Although challenges exist for the use of this technology in ruminant livestock, such as the precise annotation of unique cell populations and spatial resolution of cells within a tissue, there is vast potential to enhance our understanding of the cellular and molecular mechanisms underpinning traits essential for healthy and productive livestock. This review intends to highlight the insights gained from published single-cell omics studies in cattle, sheep, and goats, particularly those with publicly accessible data. Further, this manuscript will discuss the challenges and opportunities of this technology in ruminant livestock and how it may contribute to enhanced profitability and sustainability of animal agriculture in the future.

Overcoming Limitations to Deep Learning in Domesticated Animals with TrioTrain

Variant calling across diverse species remains challenging as most bioinformatics tools default to assumptions based on human genomes. DeepVariant (DV) excels without joint genotyping while offering fewer implementation barriers. However, the growing appeal of a "universal" algorithm has magnified the unknown impacts when used with non-human genomes. Here, we use bovine genomes to assess the limits of human-genome-trained models in other species. We introduce the first multi-species DV model that achieves a lower Mendelian Inheritance Error (MIE) rate during single-sample genotyping. Our novel approach, TrioTrain, automates extending DV for species without Genome In A Bottle (GIAB) resources and uses region shuffling to mitigate barriers for SLURM-based clusters. To offset imperfect truth labels for animal genomes, we remove Mendelian discordant variants before training, where models are tuned to genotype the offspring correctly. With TrioTrain, we use cattle, yak, and bison trios to build 30 model iterations across five phases. We observe remarkable performance across phases when testing the GIAB human trios with a mean SNP F1 score >0.990. In HG002, our phase 4 bovine model identifies more variants at a lower MIE rate than DeepTrio. In bovine F1-hybrid genomes, our model substantially reduces inheritance errors with a mean MIE rate of 0.03 percent. Although constrained by imperfect labels, we find that multi-species, trio-based training produces a robust variant calling model. Our research demonstrates that exclusively training with human genomes restricts the application of deep-learning approaches for comparative genomics.

Research Progress and Applications of Bovine Genome in the Tribe Bovini

Various bovine species have been domesticated and bred for thousands of years, and they provide adequate animal-derived products, including meat, milk, and leather, to meet human requirements. Despite the review studies on economic traits in cattle, the genetic basis of traits has only been partially explained by phenotype and pedigree breeding methods, due to the complexity of genomic regulation during animal development and growth. With the advent of next-generation sequencing technology, genomics projects, such as the 1000 Bull Genomes Project, Functional Annotation of Animal Genomes project, and Bovine Pangenome Consortium, have advanced bovine genomic research. These large-scale genomics projects gave us a comprehensive concept, technology, and public resources. In this review, we summarize the genomics research progress of the main bovine species during the past decade, including cattle (Bos taurus), yak (Bos grunniens), water buffalo (Bubalus bubalis), zebu (Bos indicus), and gayal (Bos frontalis). We mainly discuss the development of genome sequencing and functional annotation, focusing on how genomic analysis reveals genetic variation and its impact on phenotypes in several bovine species.

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.

DNA methylation analysis to differentiate reference, breed, and parent-of-origin effects in the bovine pangenome era

BACKGROUND

Most DNA methylation studies have used a single reference genome with little attention paid to the bias introduced due to the reference chosen. Reference genome artifacts and genetic variation, including single nucleotide polymorphisms (SNPs) and structural variants (SVs), can lead to differences in methylation sites (CpGs) between individuals of the same species. We analyzed whole-genome bisulfite sequencing data from the fetal liver of Angus (Bos taurus taurus), Brahman (Bos taurus indicus), and reciprocally crossed samples. Using reference genomes for each breed from the Bovine Pangenome Consortium, we investigated the influence of reference genome choice on the breed and parent-of-origin effects in methylome analyses.

RESULTS

Our findings revealed that ∼75% of CpG sites were shared between Angus and Brahman, ∼5% were breed specific, and ∼20% were unresolved. We demonstrated up to ∼2% quantification bias in global methylation when an incorrect reference genome was used. Furthermore, we found that SNPs impacted CpGs 13 times more than other autosomal sites (P < $5 \times {10}^{ - 324}$) and SVs contained 1.18 times (P < $5 \times {10}^{ - 324}$) more CpGs than non-SVs. We found a poor overlap between differentially methylated regions (DMRs) and differentially expressed genes (DEGs) and suggest that DMRs may be impacting enhancers that target these DEGs. DMRs overlapped with imprinted genes, of which 1, DGAT1, which is important for fat metabolism and weight gain, was found in the breed-specific and sire-of-origin comparisons.

CONCLUSIONS

This work demonstrates the need to consider reference genome effects to explore genetic and epigenetic differences accurately and identify DMRs involved in controlling certain genes.

Unmapped short reads from whole-genome sequencing indicate potential infectious pathogens in german black Pied cattle

When resequencing animal genomes, some short reads cannot be mapped to the reference genome and are usually discarded. In this study, unmapped reads from 302 German Black Pied cattle were analyzed to identify potential pathogenic DNA. These unmapped reads were assembled and blasted against NCBI's database to identify bacterial and viral sequences. The results provided evidence for the presence of pathogens. We found sequences of Bovine parvovirus 3 and Mycoplasma species. These findings emphasize the information content of unmapped reads for gaining insight into bacterial and viral infections, which is important for veterinarians and epidemiologists.