Summary Livestock production both contributes to and is affected by climate change. In addition to the physiological effects of higher temperatures on individual animals, the consequences of climate change are likely to include increased risk that geographically restricted rare breed populations will be badly affected by disturbances. Indirect effects may be felt via ecosystem changes that alter the distribution of animal diseases or affect the supply of feed. Breeding goals may have to be adjusted to account for higher temperatures, lower quality diets and greater disease challenge. Species and breeds that are well adapted to such conditions may become more widely used. Climate change mitigation strategies, in combination with ever increasing demand for food, may also have an impact on breed and species utilization, driving a shift towards monogastrics and breeds that are efficient converters of feed into meat, milk and eggs. This may lead to the neglect of the adaptation potential of local breeds in developing countries. Given the potential for significant future changes in production conditions and in the objectives of livestock production, it is essential that the value provided by animal genetic diversity is secured. This requires better characterization of breeds, production environments and associated knowledge; the compilation of more complete breed inventories; improved mechanisms to monitor and respond to threats to genetic diversity; more effective in situ and ex situ conservation measures; genetic improvement programmes targeting adaptive traits in high-output and performance traits in locally adapted breeds; increased support for developing countries in their management of animal genetic resources; and wider access to genetic resources and associated knowledge.
To gain insight into the number of loci of large effect that underlie variation in cattle, a quantitative trait locus (QTL) scan for 14 economically important traits was performed in two commercial Angus populations using 390 microsatellites, 11 single nucleotide polymorphisms (SNPs) and one duplication loci. The first population comprised 1769 registered Angus bulls born between 1955 and 2003, with Expected Progeny Differences computed by the American Angus Association. The second comprised 38 half-sib families containing 1622 steers with six post-natal growth and carcass phenotypes. Linkage analysis was performed by half-sib least squares regression with GRIDQTL or Bayesian Markov chain Monte Carlo analysis of complex pedigrees with LOKI. Of the 673 detected QTL, only 118 have previously been reported, reflecting both the conservative approach to QTL reporting in the literature, and the more liberal approach taken in this study. From 33 to 71% of the genetic variance and 35 to 56% of the phenotypic variance in each trait was explained by the detected QTL. To analyse the effects of 11 SNPs and one duplication locus within candidate genes on each trait, a single marker analysis was performed by fitting an additive allele substitution model in both mapping populations. There were 53 associations detected between the SNP/duplication loci and traits with -log10P(nominal) >= 4.0, where each association explained 0.92% to 4.4% of the genetic variance and 0.01% to 1.86% of the phenotypic variance. Of these associations, only six SNP/duplication loci were located within 8 cM of a QTL peak for the trait, with two being located at the QTL peak: SST_DG156121:c.362A>G for ribeye muscle area and TG_X05380:c.422C>T for calving ease. Strong associations between several SNP/duplication loci and trait variation were obtained in the absence of any detected linked QTL. However, we reject the causality of several commercialized DNA tests, including an association between TG_X05380:c.422C>T and marbling in Angus cattle.
Heat tolerance is a complex and economically important trait for catfish genetic breeding programs. With global climate change, it is becoming an increasingly important trait. To better understand the molecular basis of heat stress, a genome‐wide association study ( GWAS ) was carried out using the 250 K catfish SNP array with interspecific backcross progenies, which derived from crossing female channel catfish with male F1 hybrid catfish (female channel catfish × male blue catfish). Three significant associated SNP s were detected by performing an EMMAX approach for GWAS . The SNP located on linkage group 14 explained 12.1% of phenotypical variation. The other two SNP s, located on linkage group 16, explained 11.3 and 11.5% of phenotypical variation respectively. A total of 14 genes with heat stress related functions were detected within the significant associated regions. Among them, five genes— TRAF 2 , FBXW 5 , ANAPC 2 , UBR 1 and KLHL 29— have known functions in the protein degradation process through the ubiquitination pathway. Other genes related to heat stress include genes involved in protein biosynthesis ( PRPF 4 and SYNCRIP ), protein folding ( DNAJC25 ), molecule and iron transport ( SLC 25A46 and CLIC 5 ), cytoskeletal reorganization ( COL 12A1 ) and energy metabolism ( COX 7A2 , PLCB 1 and PLCB 4 ) processes. The results provide fundamental information about genes and pathways that is useful for further investigation into the molecular mechanisms of heat stress. The associated SNP s could be promising candidates for selecting heat‐tolerant catfish lines after validating their effects on larger and various catfish populations.
Increased inbreeding is an inevitable consequence of selection in livestock populations. The analysis of high‐density single nucleotide polymorphisms ( SNPs ) facilitates the identification of long and uninterrupted runs of homozygosity ( ROH ) that can be used to identify chromosomal regions that are identical by descent. In this work, the distribution of ROH of different lengths in five Italian cattle breeds is described. A total of 4095 bulls from five cattle breeds (2093 Italian Holstein, 749 Italian Brown, 364 Piedmontese, 410 Marchigiana and 479 Italian Simmental) were genotyped at 54K SNP loci. ROH were identified and used to estimate molecular inbreeding coefficients ( F ROH ), which were compared with inbreeding coefficients estimated from pedigree information ( F PED ) and using the genomic relationship matrix ( F GRM ). The average number of ROH per animal ranged from 54 ± 7.2 in Piedmontese to 94.6 ± 11.6 in Italian Brown. The highest number of short ROH (related to ancient consanguinity) was found in Piedmontese, followed by Simmental. The Italian Brown and Holstein had a higher proportion of longer ROH distributed across the whole genome, revealing recent inbreeding. The F PED were moderately correlated with F ROH > 1 Mb (0.662, 0.700 and 0.669 in Italian Brown, Italian Holstein and Italian Simmental respectively) but poorly correlated with F GRM (0.134, 0.128 and 0.448 for Italian Brown, Italian Holstein and Italian Simmental respectively). The inclusion of ROH > 8 Mb in the inbreeding calculation improved the correlation of F ROH with F PED and F GRM . ROH are a direct measure of autozygosity at the DNA level and can overcome approximations and errors resulting from incomplete pedigree data. In populations with high linkage disequilibrium ( LD ) and recent inbreeding (e.g. Italian Holstein and Italian Brown), a medium‐density marker panel, such as the one used here, may provide a good estimate of inbreeding. However, in populations with low LD and ancient inbreeding, marker density would have to be increased to identify short ROH that are identical by descent more precisely.
Summary This study presents a second generation of linkage disequilibrium (LD) map statistics for the whole genome of the Holstein-Friesian population, which has a four times higher resolution compared with that of the maps available so far. We used DNA samples of 810 German Holstein-Friesian cattle genotyped by the Illumina Bovine SNP50K BeadChip to analyse LD structure. A panel of 40 854 (75.6%) markers was included in the final analysis. The pairwise r2 statistic of SNPs up to 5 Mb apart across the genome was estimated. A mean value of r2 = 0.30 ± 0.32 was observed in pairwise distances of <25 kb and it dropped to 0.20 ± 0.24 at 50-75 kb, which is nearly the average inter-marker space in this study. The proportion of SNPs in useful LD (r2 ≥ 0.25) was 26% for the distance of 50 and 75 kb between SNPs. We found a lower level of LD for SNP pairs at the distance ≤100 kb than previously thought. Analysis revealed 712 haplo-blocks spanning 4.7% of the genome and containing 8.0% of all SNPs. Mean and median block length were estimated as 164 ± 117 kb and 144 kb respectively. Allele frequencies of the SNPs have a considerable and systematic impact on the estimate of r2. It is shown that minimizing the allele frequency difference between SNPs reduces the influence of frequency on r2 estimates. Analysis of past effective population size based on the direct estimates of recombination rates from SNP data showed a decline in effective population size to Ne = 103 up to ∼4 generations ago. Systematic effects of marker density and effective population size on observed LD and haplotype structure are discussed.
In this study, we performed a new genome‐wide association study using SLAF‐seq technology. A total of 19 single nucleotide polymorphism effects involving nine different SNP markers reached 5% Bonferroni‐corrected genome‐wide significance. In addition, a 5‐Mb region spanning 72.9–77.9 Mb on GGA4, exhibiting many significant SNP effects, was identified. The LDB2 gene in this region had a very strong association with body weight. Another SNP on GGA1, located in the INTS6 gene, had the strongest association with late body weight (weeks 10–16). Some of the SNPs that reached suggestive significance level overlapped with previously reported quantitative trait locus regions.
Summary A cattle database of candidate genes and genetic markers for milk production and mastitis has been developed to provide an integrated research tool incorporating different types of information supporting a genomic approach to study lactation, udder development and health. The database contains 943 genes and genetic markers involved in mammary gland development and function, representing candidates for further functional studies. The candidate loci were drawn on a genetic map to reveal positional overlaps. For identification of candidate loci, data from seven different research approaches were exploited: (i) gene knockouts or transgenes in mice that result in specific phenotypes associated with mammary gland (143 loci); (ii) cattle QTL for milk production (344) and mastitis related traits (71); (iii) loci with sequence variations that show specific allele-phenotype interactions associated with milk production (24) or mastitis (10) in cattle; (iv) genes with expression profiles associated with milk production (207) or mastitis (107) in cattle or mouse; (v) cattle milk protein genes that exist in different genetic variants (9); (vi) miRNAs expressed in bovine mammary gland (32) and (vii) epigenetically regulated cattle genes associated with mammary gland function (1). Fourty-four genes found by multiple independent analyses were suggested as the most promising candidates and were further in silico analysed for expression levels in lactating mammary gland, genetic variability and top biological functions in functional networks. A miRNA target search for mammary gland expressed miRNAs identified 359 putative binding sites in 3′UTRs of candidate genes.
Summary The data from the newly available 50 K SNP chip was used for tagging the genome-wide footprints of positive selection in Holstein-Friesian cattle. For this purpose, we employed the recently described Extended Haplotype Homozygosity test, which detects selection by measuring the characteristics of haplotypes within a single population. To assess formally the significance of these results, we compared the combination of frequency and the Relative Extended Haplotype Homozygosity value of each core haplotype with equally frequent haplotypes across the genome. A subset of the putative regions showing the highest significance in the genome-wide EHH tests was mapped. We annotated genes to identify possible influence they have in beneficial traits by using the Gene Ontology database. A panel of genes, including FABP3, CLPN3, SPERT, HTR2A5, ABCE1, BMP4 and PTGER2, was detected, which overlapped with the most extreme P-values. This panel comprises some interesting candidate genes and QTL, representing a broad range of economically important traits such as milk yield and composition, as well as reproductive and behavioural traits. We also report high values of linkage disequilibrium and a slower decay of haplotype homozygosity for some candidate regions harbouring major genes related to dairy quality. The results of this study provide a genome-wide map of selection footprints in the Holstein genome, and can be used to better understand the mechanisms of selection in dairy cattle breeding.
A putative functional mutation (rs109231213) near PLAG 1 ( BTA 14) associated with stature was studied in beef cattle. Data from 8199 B os taurus, B os indicus and T ropical C omposite cattle were used to test the associations between rs109231213 and various phenotypes. Further, 23 496 SNP s located on BTA 14 were tested for association with these phenotypes, both independently and fitted together with rs109231213. The C allele of rs109231213 significantly increased hip height, weight, net food intake, age at puberty in males and females and decreased IGF ‐I concentration in blood and fat depth. When rs109231213 was fitted as a fixed effect in the model, there was an overall reduction in associations between other SNP s and these traits but some SNP s remained associated ( P < 10 −4 ). Frequency of the mutant C allele of rs109231213 differed among B . indicus (0.52) , B. taurus (0.96) and T ropical C omposite (0.68). Most chromosomes carrying the C allele had the same surrounding 10 SNP haplotype, probably because the C allele was introgressed into B rahman from B . taurus cattle. A region of reduced heterozygosity surrounds the C allele; this is small in B . taurus but 20 Mb long in B rahmans, indicating recent and strong selection for the mutant allele. Thus, the C allele appears to mark a mutation that has been selected almost to fixation in the B . taurus breeds studied here and introduced into B rahman cattle during grading up and selected to a frequency of 0.52 despite its negative effects on fertility.
A whole‐genome association study was performed for reproductive traits in commercial sows using the PorcineSNP60 BeadChip and Bayesian statistical methods. The traits included total number born (TNB), number born alive (NBA), number of stillborn (SB), number of mummified foetuses at birth (MUM) and gestation length (GL) in each of the first three parities. We report the associations of informative QTL and the genes within the QTL for each reproductive trait in different parities. These results provide evidence of gene effects having temporal impacts on reproductive traits in different parities. Many QTL identified in this study are new for pig reproductive traits. Around 48% of total genes located in the identified QTL regions were predicted to be involved in placental functions. The genomic regions containing genes important for foetal developmental (e.g. MEF2C ) and uterine functions (e.g. PLSCR4 ) were associated with TNB and NBA in the first two parities. Similarly, QTL in other foetal developmental (e.g. HNRNPD and AHR ) and placental (e.g. RELL1 and CD96 ) genes were associated with SB and MUM in different parities. The QTL with genes related to utero‐placental blood flow (e.g. VEGFA ) and hematopoiesis (e.g. MAFB ) were associated with GL differences among sows in this population. Pathway analyses using genes within QTL identified some modest underlying biological pathways, which are interesting candidates (e.g. the nucleotide metabolism pathway for SB) for pig reproductive traits in different parities. Further validation studies on large populations are warranted to improve our understanding of the complex genetic architecture for pig reproductive traits.
Antisense long non‐coding RNA s ( AS lnc RNA s) play important roles in refined regulation of animal gene expression. However, their functions and molecular mechanisms for domestic animal adipogenesis are largely unknown. Here, we found a novel AS lnc RNA transcribed from the porcine PU.1 gene (also known as SPI 1 ) by strand‐specific RT ‐ PCR . Results showed that PU.1 AS lnc RNA was expressed and generally lower than the level of PU.1 m RNA in porcine subcutaneous adipose, heart, liver, spleen, lympha, skeletal muscle and kidney tissues. We further found that the levels of PU.1 m RNA and PU.1 protein were significantly lower in subcutaneous and intermuscular adipose than in mesenteric and greater omentum adipose, whereas the levels of PU.1 AS lnc RNA showed no difference in porcine adipose tissues from four different parts of the body. During porcine adipogenesis, levels of PU.1 m RNA increased at day 2 and then gradually decreased. Meanwhile, PU.1 AS lnc RNA exhibited an expression trend similar to PU.1 m RNA but sharply decreased after day 2. Interestingly, PU.1 protein level rose during differentiation. In addition, at day 6 after differentiation, knockdown of endogenous PU.1 promoted adipogenesis, whereas knockdown of endogenous PU.1 AS lnc RNA had the opposite effect. Moreover, peroxisome proliferator‐activated receptor gamma ( PPARG ) and fatty acid synthase ( FASN ) were significantly upregulated in the PU.1 sh RNA treatment group ( P < 0.05), whereas they were downregulated in the PU.1 AS sh RNA treatment group ( P < 0.05). Adipose triglyceride lipase [ ATGL ; also known as patatin‐like phospholipase domain containing 2 ( PNPLA 2 )] and hormone‐sensitive lipase [ HSL; also known as lipase, hormone‐sensitive ( LIPE )] contrasted with PPARG and FASN . Finally, the PU.1 m RNA / PU.1 AS lnc RNA duplex was detected by an endogenous ribonuclease protection assay combined with RT ‐ PCR . Based on the above results, we suggest that PU.1 AS lnc RNA (vs. its m RNA translation) promotes adipogenesis through the formation of a sense–antisense RNA duplex with PU.1 m RNA .
Feed efficiency is an economically important trait in beef production. It can be measured as residual feed intake. This is the difference between actual feed intake recorded over a test period and the expected feed intake of an animal based on its size and growth rate. DNA‐based marker‐assisted selection would help beef breeders to accelerate genetic improvement for feed efficiency by reducing the generation interval and would obviate the high cost of measuring residual feed intake. Although numbers of quantitative trait loci and candidate genes have been identified with the advance of molecular genetics, our understanding of the physiological mechanisms and the nature of genes underlying residual feed intake is limited. The aim of the study was to use global gene expression profiling by microarray to identify genes that are differentially expressed in cattle, using lines genetically selected for low and high residual feed intake, and to uncover candidate genes for residual feed intake. A long‐oligo microarray with 24 000 probes was used to profile the liver transcriptome of 44 cattle selected for high or low residual feed intake. One hundred and sixty‐one unique genes were identified as being differentially expressed between animals with high and low residual feed intake. These genes were involved in seven gene networks affecting cellular growth and proliferation, cellular assembly and organization, cell signalling, drug metabolism, protein synthesis, lipid metabolism, and carbohydrate metabolism. Analysis of functional data using a transcriptional approach allows a better understanding of the underlying biological processes involved in residual feed intake and also allows the identification of candidate genes for marker‐assisted selection.
We evaluated 69 SNPs in genes previously related to fertility and production traits for their relationship to daughter pregnancy rate (DPR), cow conception rate (CCR) and heifer conception rate (HCR) in a separate population of Holstein cows grouped according to their predicted transmitting ability (PTA) [-1 (n=1287) and 1.5 (n=1036)] for DPR. Genotyping was performed using Sequenom MassARRAY((R)). There were a total of 39 SNPs associated with the three fertility traits. The SNPs that explained the greater proportion of the genetic variation for DPR were COQ9 (3.2%), EPAS1 (1.0%), CAST (1.0%), C7H19orf60 (1.0%) and MRPL48 (1.0%); for CCR were GOLGA4 (2.4%), COQ9 (1.8%), EPAS1 (1.1%) and MRPL48 (0.8%); and for HCR were HSD17B7 (1.0%), AP3B1 (0.8%), HSD17B12 (0.7%) and CACNA1D (0.6%). Inclusion of 39 SNPs previously associated with DPR in the genetic evaluation system increased the reliability of PTA for DPR by 0.20%. Many of the genes represented by SNPs associated with fertility are involved in steroidogenesis or are regulated by steroids. A large proportion of SNPs previously associated with genetic merit for fertility in Holstein bulls maintained their association in a separate population of cows. The inclusion of these genes in genetic evaluation can improve reliabilities of genomic estimates for fertility.
The identification of genetic variations underlying desired phenotypes is one of the main challenges of current livestock genetic research. High‐throughput transcriptome sequencing has been recognized as an efficient way to unravel the rich genetic variants across various species. The Lanzhou Fat‐Tail sheep is an endangered sheep breed in China with a notable feature of an exaggerated fat tail that also independently occurs in other sheep breeds. However, the genetic mechanism underlying this particular trait has not been fully elucidated yet. In this study, we used RNA ‐seq on tissue samples (longissimus dorsi muscle, perinephric fat and tail fat) from three sheep breeds with either fat or thin tails and characterized the genetic variation in Lanzhou Fat‐Tail sheep with the ultimate goal of identifying the causal genes and genetic networks responsible for the fat tail in this rare sheep breed. In total, 7 122 920 SNP s and 901 518 indels were detected in the nine individual sheep investigated, of which 606 952 SNP s (8.5%) and 77 633 indels (8.6%) overlapped with QTL associated with fat traits in sheep. Furthermore, we detected 26 613 specific SNP s in Lanzhou Fat‐Tail sheep and 44 SNP s located in the same genomic position reported in another sheep breed with fat tails. Interestingly, 33 SNP s are selectively distributed on a chromosome 3 region (39.58–40.91 Mb) that was reported as a strong candidate genomic region for fat deposition in tails of sheep. Our research has also suggested that three genes ( CREB 1 , WDR 92 and ETAA 1 ) may be associated with fat tail development. In summary, the resultant genetic variants data in this study provide a valuable resource for marker‐assisted selection of the trait in Lanzhou Fat‐Tail sheep populations.
We performed a genome‐wide association study to detect markers associated with growth traits in Atlantic salmon. The analyzed traits included body weight at tagging ( BWT ) and body weight at 25 months ( BW 25M). Genotypes of 4662 animals were imputed from the 50K SNP chip to the 200K SNP chip using fimpute software. The markers were simultaneously modeled using Bayes C to identify genomic regions associated with the traits. We identified windows explaining a maximum of 3.71% and 3.61% of the genetic variance for BWT and BW 25M respectively. We found potential candidate genes located within the top ten 1‐Mb windows for BWT and BW 25M. For instance, the vitronectin ( VTN ) gene, which has been previously reported to be associated with cell growth, was found within one of the top ten 1‐Mb windows for BWT . In addition, the WNT 1‐inducible‐signaling pathway protein 3, melanocortin 2 receptor accessory protein 2, myosin light chain kinase, transforming growth factor beta receptor type 3 and myosin light chain 1 genes, which have been reported to be associated with skeletal growth in humans, growth stimulation during the larval stage in zebrafish, body weight in pigs, feed conversion in chickens and growth rate of sheep skeletal muscle respectively, were found within some of the top ten 1‐Mb windows for BW 25M. These results indicate that growth traits are most likely controlled by many variants with relatively small effects in Atlantic salmon. The genomic regions associated with the traits studied here may provide further insight into the functional regions underlying growth traits in this species.
A genome‐wide association scan for loci affecting withers height was conducted in 782 G erman W armblood stallions, which were genotyped using the I llumina E quine SNP 50 B ead C hip. A principal components approach was applied to correct for population structure. The analysis revealed a single major QTL on ECA 3 explaining ~18 per cent of the phenotypic variance, which is in concordance with recent reports from other horse populations. The LCORL / NCAPG locus represents a strong candidate gene for this QTL . This locus is among a small number that have consistently been identified to influence human height in several large meta‐analyses. Furthermore, a mutation within the NCAPG gene was found to affect growth and body frame size in cattle. Together with the results of this study in G erman W armbloods, these findings strongly indicate LCORL / NCAPG as a candidate locus for withers height in horses. Further studies are, however, needed to confirm this.
Genetic engineering in livestock has been greatly enhanced through the use of artificial programmed nucleases such as the recently emerged clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) system. We recently reported our successful application of the CRISPR/Cas9 system to engineer the goat genome through micro-injection of Cas9 mRNA and sgRNAs targeting MSTN and FGF5 in goat embryos. The phenotypes induced by edited loss-of-function mutations of MSTN remain to be evaluated extensively. We demonstrate the utility of this approach by disrupting MSTN, resulting in enhanced body weight and larger muscle fiber size in Cas9-mediated gene-modified goats. The effects of genome modifications were further characterized by H&E staining, quantitative PCR, Western blotting and immunofluorescence staining. Morphological and genetic analyses indicated the occurrence of phenotypic and genotypic modifications. We further provide sufficient evidence, including breeding data, to demonstrate the transmission of the knockout alleles through the germline. By phenotypic and genotypic characterization, we demonstrated the merit of using the CRISPR/Cas9 approach for establishing genetically modified livestock with an enhanced production trait.
The Functional Annotation of AN imal Genomes ( FAANG ) project aims, through a coordinated international effort, to provide high quality functional annotation of animal genomes with an initial focus on farmed and companion animals. A key goal of the initiative is to ensure high quality and rich supporting metadata to describe the project's animals, specimens, cell cultures and experimental assays. By defining rich sample and experimental metadata standards and promoting best practices in data descriptions, deposition and openness, FAANG champions higher quality and reusability of published datasets. FAANG has established a Data Coordination Centre, which sits at the heart of the Metadata and Data Sharing Committee. It continues to evolve the metadata standards, support submissions and, crucially, create powerful and accessible tools to support deposition and validation of metadata. FAANG conforms to the findable, accessible, interoperable, and reusable ( FAIR ) data principles, with high quality, open access and functionally interlinked data. In addition to data generated by FAANG members and specific FAANG projects, existing datasets that meet the main—or more permissive legacy—standards are incorporated into a central, focused, functional data resource portal for the entire farmed and companion animal community. Through clear and effective metadata standards, validation and conversion software, combined with promotion of best practices in metadata implementation, FAANG aims to maximise effectiveness and inter‐comparability of assay data. This supports the community to create a rich genome‐to‐phenotype resource and promotes continuing improvements in animal data standards as a whole.