Determination of genetic associations between indels in 11 candidate genes and milk composition traits in Chinese Holstein population

Genome-Wide Analysis of Milk Production Traits and Selection Signatures in Serbian Holstein-Friesian Cattle

To improve the genomic evaluation of milk-related traits in Holstein-Friesian (HF) cattle it is essential to identify the associated candidate genes. Novel SNP-based analyses, such as the genetic mapping of inherited diseases, GWAS, and genomic selection, have led to a new era of research. The aim of this study was to analyze the association of each individual SNP in Serbian HF cattle with milk production traits and inbreeding levels. The SNP 60 K chip Axiom Bovine BovMDv3 was deployed for the genotyping of 334 HF cows. The obtained genomic results, together with the collected phenotypic data, were used for a GWAS. Moreover, the identification of ROH segments was performed and served for inbreeding coefficient evaluation and ROH island detection. Using a GWAS, a polymorphism, rs110619097 (located in the intron of the CTNNA3 gene), was detected to be significantly (p < 0.01) associated with the milk protein concentration in the first lactation (adjusted to 305 days). The average genomic inbreeding value (FROH) was 0.079. ROH islands were discovered in proximity to genes associated with milk production traits and genomic regions under selection pressure for other economically important traits of dairy cattle. The findings of this pilot study provide useful information for a better understanding of the genetic architecture of milk production traits in Serbian HF dairy cows and can be used to improve lactation performances in Serbian HF cattle breeding programs.

Genomic Regions and Candidate Genes Associated with Milk Production Traits in Holstein and Its Crossbred Cattle: A Review

Genome-wide association studies (GWAS) are a powerful tool for identifying genomic regions and causative genes associated with economically important traits in dairy cattle, particularly complex traits, such as milk production. This is possible due to advances in next-generation sequencing technology. This review summarized information on identified candidate genes and genomic regions associated with milk production traits in Holstein and its crossbreds from various regions of the world. Milk production traits are important in dairy cattle breeding programs because of their direct economic impact on the industry and their close relationship with nutritional requirements. GWAS has been used in a large number of studies to identify genomic regions and candidate genes associated with milk production traits in dairy cattle. Many genomic regions and candidate genes have already been identified in Holstein and its crossbreds. Genes and single nucleotide polymorphisms (SNPs) that significantly affect milk yield (MY) were found in all autosomal chromosomes except chromosomes 27 and 29. Half of the reported SNPs associated with fat yield and fat percentage were found on chromosome 14. However, a large number of significant SNPs for protein yield (PY) and protein percentage were found on chromosomes 1, 5, and 20. Approximately 155 SNPs with significant influence on multiple milk production traits have been identified. Several promising candidate genes, including diacylglycerol O-acyltransferase 1, plectin, Rho GTPase activating protein 39, protein phosphatase 1 regulatory subunit 16A, and sphingomyelin phosphodiesterase 5 were found to have pleiotropic effects on all five milk production traits. Thus, to improve milk production traits it is of practical relevance to focus on significant SNPs and pleiotropic genes frequently found to affect multiple milk production traits.

Non-Synonymous Variants in Fat QTL Genes among High- and Low-Milk-Yielding Indigenous Breeds

The effect of breed on milk components-fat, protein, lactose, and water-has been observed to be significant. As fat is one of the major price-determining factors for milk, exploring the variations in fat QTLs across breeds would shed light on the variable fat content in their milk. Here, on whole-genome sequencing, 25 differentially expressed hub or bottleneck fat QTLs were explored for variations across indigenous breeds. Out of these, 20 genes were identified as having nonsynonymous substitutions. A fixed SNP pattern in high-milk-yielding breeds in comparison to low-milk-yielding breeds was identified in the genes GHR, TLR4, LPIN1, CACNA1C, ZBTB16, ITGA1, ANK1, and NTG5E and, vice versa, in the genes MFGE8, FGF2, TLR4, LPIN1, NUP98, PTK2, ZTB16, DDIT3, and NT5E. The identified SNPs were ratified by pyrosequencing to prove that key differences exist in fat QTLs between the high- and low-milk-yielding breeds.

Whole-genome resequencing reveals genetic diversity and selection characteristics of dairy goat

The dairy goat is one of the earliest dairy livestock species, which plays an important role in the economic development, especially for developing countries. With the development of agricultural civilization, dairy goats have been widely distributed across the world. However, few studies have been conducted on the specific characteristics of dairy goat. In this study, we collected the whole-genome data of 89 goat individuals by sequencing 48 goats and employing 41 publicly available goats, including five dairy goat breeds (Saanen, Nubian, Alpine, Toggenburg, and Guanzhong dairy goat; n = 24, 15, 11, 6, 6), and three goat breeds (Guishan goat, Longlin goat, Yunshang Black goat; n = 6, 15, 6). Through compared the genomes of dairy goat and non-dairy goat to analyze genetic diversity and selection characteristics of dairy goat. The results show that the eight goats could be divided into three subgroups of European, African, and Chinese indigenous goat populations, and we also found that Australian Nubian, Toggenburg, and Australian Alpine had the highest linkage disequilibrium, the lowest level of nucleotide diversity, and a higher inbreeding coefficient, indicating that they were strongly artificially selected. In addition, we identified several candidate genes related to the specificity of dairy goat, particularly genes associated with milk production traits (GHR, DGAT2, ELF5, GLYCAM1, ACSBG2, ACSS2), reproduction traits (TSHR, TSHB, PTGS2, ESR2), immunity traits (JAK1, POU2F2, LRRC66). Our results provide not only insights into the evolutionary history and breed characteristics of dairy goat, but also valuable information for the implementation and improvement of dairy goat cross breeding program.

Full-length transcriptome analysis of Zanthoxylum nitidum (Roxb.) DC

Zanthoxylum nitidum (Roxb.) DC. (Z. nitidum) is a type of Chinese Dao-di herb, also called Liangmianzhen, which is widely used to treat arthralgia, rheumatic arthralgia, and stomach pain. However, genomic resources for Z. nitidum are still scarce. This study provides transcriptomic resources for Z. nitidum by applying single-molecule real-time (SMRT) sequencing technology. In total, 456,109 circular consensus sequencing (CCS) reads were generated with a mean length of 2,216 bp from Z. nitidum roots, old stems, young branches, leaves, flowers, and fruits. Of these total reads, 353,932 were full-length nonchimeric (FLNC) reads with an average length of 1,996 bp. A total of 16,163 transcripts with a mean length of 1,171 bp were acquired. Of these transcripts, 14,231 (88%) were successfully annotated using public databases. Across all the 16,163 transcripts, we identified 6,255 long non-coding RNAs (lncRNAs) and 22,780 simple sequence repeats (SSRs). Furthermore, 3,482 transcription factors were identified. Among the SSR loci, 1-3 nucleotide repeats were dominant, occupying 99.36% of the total SSR loci, with mono-, di-, and tri-nucleotide repeats accounting for 61.80%, 19.89%, and 5.02% of the total SSR loci, respectively. A total of 36 out of 100 randomly selected primer pairs were verified to be positive, 20 of which showed polymorphism. These findings enrich the genetic resources available for facilitating future studies and research on relevant topics such as population genetics in Z. nitidum.

Weighted Single-Step Genome-Wide Association Study Uncovers Known and Novel Candidate Genomic Regions for Milk Production Traits and Somatic Cell Score in Valle del Belice Dairy Sheep

Simple Summary

Milk production is the most economically crucial dairy sheep trait and constitutes the major genetic enhancement purpose via selective breeding. Also, mastitis is one of the most frequently encountered diseases, having a significant impact on animal welfare, milk yield, and quality. The aim of this study was to identify genomic region(s) associated with the milk production traits and somatic cell score (SCS) in Valle del Belice sheep using single-step genome-wide association (ssGWA) and genotyping data from medium density SNP panels. We identified several genomic regions (OAR1, OAR2, OAR3, OAR4, OAR6, OAR9, and OAR25) and candidate genes implicated in milk production traits and SCS. Our findings offer new insights into the genetic basis of milk production traits and SCS in dairy sheep.

Abstract

The objective of this study was to uncover genomic regions explaining a substantial proportion of the genetic variance in milk production traits and somatic cell score in a Valle del Belice dairy sheep. Weighted single-step genome-wide association studies (WssGWAS) were conducted for milk yield (MY), fat yield (FY), fat percentage (FAT%), protein yield (PY), protein percentage (PROT%), and somatic cell score (SCS). In addition, our aim was also to identify candidate genes within genomic regions that explained the highest proportions of genetic variance. Overall, the full pedigree consists of 5534 animals, of which 1813 ewes had milk data (15,008 records), and 481 ewes were genotyped with a 50 K single nucleotide polymorphism (SNP) array. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. We considered the top 10 genomic regions in terms of their explained genomic variants as candidate window regions for each trait. The results showed that top ranked genomic windows (1 Mb windows) explained 3.49, 4.04, 5.37, 4.09, 3.80, and 5.24% of the genetic variances for MY, FY, FAT%, PY, PROT%, and total SCS, respectively. Among the candidate genes found, some known associations were confirmed, while several novel candidate genes were also revealed, including PPARGC1A, LYPLA1, LEP, and MYH9 for MY; CACNA1C, PTPN1, ROBO2, CHRM3, and ERCC6 for FY and FAT%; PCSK5 and ANGPT1 for PY and PROT%; and IL26, IFNG, PEX26, NEGR1, LAP3, and MED28 for SCS. These findings increase our understanding of the genetic architecture of six examined traits and provide guidance for subsequent genetic improvement through genome selection.

Genome-Wide Association Study Candidate Genes on Mammary System-Related Teat-Shape Conformation Traits in Chinese Holstein Cattle

In the dairy industry, mammary system traits are economically important for dairy animals, and it is important to explain their fundamental genetic architecture in Holstein cattle. Good and stable mammary system-related teat traits are essential for producer profitability in animal fitness and in the safety of dairy production. In this study, we conducted a genome-wide association study on three traits—anterior teat position (ATP), posterior teat position (PTP), and front teat length (FTL)—in which the FarmCPU method was used for association analyses. Phenotypic data were collected from 1000 Chinese Holstein cattle, and the GeneSeek Genomic Profiler Bovine 100K single-nucleotide polymorphisms (SNP) chip was used for cattle genotyping data. After the quality control process, 984 individual cattle and 84,406 SNPs remained for GWAS work analysis. Nine SNPs were detected significantly associated with mammary-system-related teat traits after a Bonferroni correction (p < 5.92 × 10⁻⁷), and genes within a region of 200 kb upstream or downstream of these SNPs were performed bioinformatics analysis. A total of 36 gene ontology (GO) terms and 3 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched (p < 0.05), and these terms and pathways are mainly related to metabolic processes, immune response, and cellular and amino acid catabolic processes. Eleven genes including MMS22L, E2F8, CSRP3, CDH11, PEX26, HAL, TAMM41, HIVEP3, SBF2, MYO16 and STXBP6 were selected as candidate genes that might play roles in the teat traits of cows. These results identify SNPs and candidate genes that give helpful biological information for the genetic architecture of these teat traits, thus contributing to the dairy production, health, and genetic selection of Chinese Holstein cattle.

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

BACKGROUND

Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. While there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk.

RESULTS

Separate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk.

CONCLUSIONS

This study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.

A Candidate Gene Association Study for Economically Important Traits in Czech Dairy Goat Breeds

Milk production is influenced by many factors, including genetic and environmental factors and their interactions. Animal health, especially udder health, is usually evaluated by the number of somatic cells. The present study described the effect of polymorphisms in the ACACA, BTN1A1, LPL, and SCD genes on the daily milk yield, fat, and protein percentages and somatic cell count. In this study, 590 White Shorthaired (WSH) and Brown Shorthaired (BSH) goats were included. SNP genotyping was performed by PCR-RFLP and multiplex PCR followed by SNaPshot minisequencing analysis. The linear mixed model with repeated measurement was used to identify the genetic associations between the studied genes/SNPs and chosen traits. All selected genes were polymorphic in the tested goat populations and showed significant associations with milk traits. Only BTN1A1 (SNP g.599 A > G) showed a significant association with the somatic cell score. After Bonferroni correction, a significant effect of LPL g.300G > A on daily milk yield and fat percentage, LPL g.185G > T on protein percentage, and LPL G50C, SCD EX3_15G > A, and SCD EX3_68A > G on fat percentage was found. The importance of environmental factors, such as the herd-year effect, month of milking, and lactation order on all milk performance indicators was confirmed.

Genome-Wide SNP Analysis for Milk Performance Traits in Indigenous Sheep: A Case Study in the Egyptian Barki Sheep

Simple Summary

The Barki sheep is one of the three main breeds in Egypt, which is spread mainly throughout the northwestern coastal zone, which has harsh conditions. Considering the harsh, semi-arid habitat of this breed, milk performance traits such as milk yield and milk composition have a very important role in the feeding of newborn lambs and affect their growth during the early stage of life. In this study, rare milk performance data and genomic information of Barki sheep were used to uncover diversified genomic regions that could explain the variability of milk yield and milk quality traits in the studied population of Barki ewes. Genome-wide analysis identified genomic regions harboring interesting candidate genes such as SLC5A8, NUB1, TBC1D1, KLF3 and ABHD5 for milk yield and PPARA and FBLN1 genes for milk quality traits. The findings offer valuable information for obtaining a better understanding of the genetics of milk performance traits and contribute to the genetic improvement of these traits in Barki sheep.

Abstract

Sheep milk yield and milk composition traits play an important role in supplying newborn lambs with essential components such as amino acids, energy, vitamins and immune antibodies and are also of interest in terms of the nutritional value of the milk for human consumption. The aim of this study was to identify genomic regions and candidate genes for milk yield and milk composition traits through genome-wide SNP analyses between high and low performing ewes of the Egyptian Barki sheep breed, which is well adapted to the harsh conditions of North-East Africa. Therefore, out of a herd of 111 ewes of the Egyptian Barki sheep breed (IBD = 0.08), ewes representing extremes in milk yield and milk quality traits (n = 25 for each group of animals) were genotyped using the Illumina OvineSNP50 V2 BeadChip. The fixation index (F_ST) for each SNP was calculated between the diversified groups. F_ST values were Z-transformed and used to identify putative SNPs for further analysis (Z(F_ST) > 10). Genome-wide SNP analysis revealed genomic regions covering promising candidate genes related to milk performance traits such as SLC5A8, NUB1, TBC1D1, KLF3 and ABHD5 for milk yield and PPARA and FBLN1 genes for milk quality trait. The results of this study may contribute to the genetic improvement of milk performance traits in Barki sheep breed and to the general understanding of the genetic contribution to variability in milk yield and quality traits.

Current Evidences and Future Perspectives for AMPK in the Regulation of Milk Production and Mammary Gland Biology

Activated protein kinase (AMP)-activated protein kinase (AMPK) senses the cellular energy status and coordinates catabolic and anabolic processes. Extensive studies have proposed that AMPK regulates energy homeostasis, cell growth, autophagy, mitochondrial biology and inflammation. The biological functions of AMPK vary in different tissues or organs. As a unique organ that produces milk, the mammary gland has recently attracted substantial research attention. This review discusses how AMPK in the mammary gland is activated by energy deprivation and heat stress via the activation of canonical and non-canonical pathways. In addition, the important downstream targets of AMPK and their functions in the mammary gland, especially during milk synthesis, are summarized in the review.