Genomics for food safety and sustainable animal production

There is a growing concern in society about the safety of animal-derived food, the health and welfare of farm animals and the sustainability of current animal production systems. Along farm animal, breeding genomics may contribute to a solution for these concerns. The use of genomic analysis tools, to achieve genetic progress in typical out-bred populations of farm animals, seems to be more difficult compared to 'model' organisms or plants. However, identification of positional candidate genes may be accelerated by linkage disequilibrium (LD) mapping. Recording of sustainable traits requires a large financial and logistic input and the economic advantages for the market are not as clear as for traditional selection traits. Examples show that the major genes causing variability for similar traits in different species are rarely the same. Therefore, for breeding purposes genomic analysis of the species of interest is needed. The fundamental knowledge obtained on the genetic architecture of complex traits will open new perspectives for the use of DNA tests in selection schemes. For food safety and traceability, DNA-based techniques evolve for monitoring and early warning systems.     

Genetic analysis of differentiation among breeding ponds reveals a candidate gene for local adaptation in Rana arvalis

One of the main questions in evolutionary and conservation biology is how geographical and environmental features of the landscape shape neutral and adaptive genetic variation in natural populations. The identification of genomic polymorphisms that account for adaptive variation can aid in finding candidate loci for local adaptation. Consequently, a comparison of spatial patterns in neutral markers and loci under selection may help disentangle the effects of gene flow, genetic drift and selection at the landscape scale. Many amphibians breed in wetlands, which differ in environmental conditions and in the degree of isolation, enhancing the potential for local adaptation. We used microsatellite markers to measure genetic differentiation among 17 local populations of Rana arvalis breeding in a network of wetlands. We found that locus RC08604 deviated from neutral expectations, suggesting that it is a good candidate for directional selection. We used a genetic network analysis to show that the allele distribution in this locus is correlated with habitat characteristics, whereas this was not the case at neutral markers that displayed a different allele distribution and population network in the study area. The graph approach illustrated the genomic heterogeneity (neutral loci vs. the candidate locus for directional selection) of gene exchange and genetic divergence among populations under directional selection. Limited gene flow between wetlands was only observed at the candidate genomic region under directional selection. RC08604 is partially located inside an up‐regulated thyroid‐hormone receptor (TRβ) gene coordinating the expression of other genes during metamorphosis and appears to be linked with variation in larval life‐history traits found among R. arvalis populations. We suggest that directional selection on genes coding larval life‐history traits is strong enough to maintain the divergence in these genomic regions, reducing the effective recombination of locally adapted alleles but not in other regions of the genome. Integrating this knowledge into conservation plans at the landscape scale will improve the design of management strategies to preserve adaptive genetic diversity in wetland networks.     

Genome-wide identification of runs of homozygosity islands and associated genes in local dairy cattle breeds

Runs of homozygosity (ROH) are widely used as predictors of whole-genome inbreeding levels in cattle. They identify regions that have an unfavorable effect on a phenotype when homozygous, but also identify the genes associated with traits of economic interest present in these regions. Here, the distribution of ROH islands and enriched genes within these regions in four dairy cattle breeds were investigated. Cinisara (71), Modicana (72), Reggiana (168) and Italian Holstein (96) individuals were genotyped using the 50K v2 Illumina BeadChip. The genomic regions most commonly associated with ROHs were identified by selecting the top 1% of the single nucleotide polymorphisms (SNPs) most commonly observed in the ROH of each breed. In total, 11 genomic regions were identified in Cinisara and Italian Holstein, and eight in Modicana and Reggiana, indicating an increased ROH frequency level. Generally, ROH islands differed between breeds. The most homozygous region (>45% of individuals with ROH) was found in Modicana on chromosome 6 within a quantitative trail locus affecting milk fat and protein concentrations. We identified between 126 and 347 genes within ROH islands, which are involved in multiple signaling and signal transduction pathways in a wide variety of biological processes. The gene ontology enrichment provided information on possible molecular functions, biological processes and cellular components under selection related to milk production, reproduction, immune response and resistance/susceptibility to infection and diseases. Thus, scanning the genome for ROH could be an alternative strategy to detect genomic regions and genes related to important economic traits.     

Turning science on robust cattle into improved genetic selection decisions

More robust cattle have the potential to increase farm profitability, improve animal welfare, reduce the contribution of ruminant livestock to greenhouse gas emissions and decrease the risk of food shortages in the face of increased variability in the farm environment. Breeding is a powerful tool for changing the robustness of cattle; however, insufficient recording of breeding goal traits and selection of animals at younger ages tend to favour genetic change in productivity traits relative to robustness traits. This paper has extended a previously proposed theory of artificial evolution to demonstrate, using deterministic simulation, how choice of breeding scheme design can be used as a tool to manipulate the direction of genetic progress, whereas the breeding goal remains focussed on the factors motivating individual farm decision makers. Particular focus was placed on the transition from progeny testing or mass selection to genomic selection breeding strategies. Transition to genomic selection from a breeding strategy where candidates are selected before records from progeny being available was shown to be highly likely to favour genetic progress in robustness traits relative to productivity traits. This was shown even with modest numbers of animals available for training and when heritability for robustness traits was only slightly lower than that for productivity traits. When transitioning from progeny testing to a genomic selection strategy without progeny testing, it was shown that there is a significant risk that robustness traits could become less influential in selection relative to productivity traits. Augmentations of training populations using genotyped cows and support for industry-wide improvements in phenotypic recording of robustness traits were put forward as investment opportunities for stakeholders wishing to facilitate the application of science on robust cattle into improved genetic selection schemes.     

Genome-wide analysis in endangered populations: a case study in Barbaresca sheep

Analysis of genomic data is becoming increasingly common in the livestock industry and the findings have been an invaluable resource for effective management of breeding programs in small and endangered populations. In this paper, with the goal of highlighting the potential of genomic analysis for small and endangered populations, genome-wide levels of linkage disequilibrium, measured as the squared correlation coefficient of allele frequencies at a pair of loci, effective population size, runs of homozygosity (ROH) and genetic diversity parameters, were estimated in Barbaresca sheep using Illumina OvineSNP50K array data. Moreover, the breed’s genetic structure and its relationship with other breeds were investigated. Levels of pairwise linkage disequilibrium decreased with increasing distance between single nucleotide polymorphisms. An average correlation coefficient <0.25 was found for markers located up to 50 kb apart. Therefore, these results support the need to use denser single nucleotide polymorphism panels for high power association mapping and genomic selection efficiency in future breeding programs. The estimate of past effective population size ranged from 747 animals 250 generations ago to 28 animals five generations ago, whereas the contemporary effective population size was 25 animals. A total of 637 ROH were identified, most of which were short (67%) and ranged from 1 to 10 Mb. The genetic analyses revealed that the Barbaresca breed tended to display lower variability than other Sicilian breeds. Recent inbreeding was evident, according to the ROH analysis. All the investigated parameters showed a comparatively narrow genetic base and indicated an endangered status for Barbaresca. Multidimensional scaling, model-based clustering, measurement of population differentiation, neighbor networks and haplotype sharing distinguished Barbaresca from other breeds, showed a low level of admixture with the other breeds considered in this study, and indicated clear genetic differences compared with other breeds. Attention should be given to the conservation of Barbaresca due to its critical conservation status. In this context, genomic information may have a crucial role in management of small and endangered populations.     

Transmission of important chromosomal regions under selection revealed in rice pedigree breeding programs

Genetic analysis across a whole plant genome based on pedigree information offers considerable potential for enhancing genetic gain from plant breeding programs through quantitative trait loci (QTL) mapping and marker-assisted selection. Here, we report its application for graphically genotyping varieties used in Chinese japonica rice (Oryza sativa L.) pedigree breeding programs. We identified 34 important chromosomal regions from the founder parent that are under selection in the breeding programs, and by comparing donor genomic regions that are under selection with QTL locations of agronomic traits, we found that QTL clustered in important genomic regions, in accordance with association analyses of natural populations and other previous studies. The convergence of genomic regions under selection with QTL locations suggests that donor genomic regions harboring key genes/QTL for important agronomic traits have been selected by plant breeders since the 1950s from the founder rice plants. The results provide better understanding of the effects of selection in breeding programs on the traits of rice cultivars. They also provide potentially valuable information for enhancing rice breeding programs through screening candidate parents for targeted molecular markers, improving crop yield potential and identifying suitable genetic material for use in future breeding programs.     

Genome‐wide variability and selection signatures in Italian island cattle breeds

In the present study, a sample of 88 animals belonging to four local (Modicana, Sarda, Sardo‐Bruna and Sardo‐Modicana) and one cosmopolitan (Italian Brown Swiss) cattle breeds were genotyped with a medium density SNP beadchip and compared to investigate their genetic diversity and the existence of selection signatures. A total of 43 012 SNPs distributed across all 29 autosomal chromosomes were retained after data quality control. Basic population statistics, Wright fixation index and runs of homozygosity (ROH) analyses confirmed that the Italian Brown Swiss genome was shaped mainly by selection, as underlined by the low values of heterozygosity and minor allele frequency. As expected, local cattle exhibited a large within‐breed genetic heterogeneity. The F_ST comparison revealing the largest number of significant SNPs was Sardo‐Bruna vs. Sardo‐Modicana, whereas the smallest was observed for Italian Brown Swiss vs. Sardo‐Modicana. Modicana exhibited the largest number of detected ROHs, whereas the smallest was observed for Sardo‐Modicana. Signatures of selection were detected in genomic regions that harbor genes involved in milk production traits for Italian Brown Swiss and fitness traits for local breeds. According to the results of multi‐dimensional scaling and the admixture analysis the Sardo‐Bruna is more similar to the Sarda than to the Italian Brown Swiss breed. Moreover, the Sardo‐Modicana is genetically closer to the Modicana than to the Sarda breed. Results of the present work confirm the usefulness of single nucleotide polymorphisms in deciphering the genetic architecture of livestock breeds.     

Contrasting Levels of Variation in Neutral and Quantitative Genetic Loci on Island Populations of Moor Frogs (<Emphasis Type="Italic">Rana arvalis</Emphasis>)

Reduced levels of genetic variability and a prominent differentiation in both neutral marker genes and phenotypic traits are typical for many island populations as compared to their mainland conspecifics. However, whether genetic diversity in neutral marker genes reflects genetic variability in quantitative traits, and thus, their evolutionary potential, remains typically unclear. Moreover, the phenotypic differentiation on islands could be attributable to phenotypic plasticity, selection or drift; something which seldom has been tested. Using eight polymorphic microsatellite loci and quantitative genetic breeding experiments we conducted a detailed comparison on genetic variability and differentiation between Nordic islands (viz. Gotland, Öland and Læsø) and neighbouring mainland populations of moor frogs (Rana arvalis). As expected, the neutral variation was generally lower in island than in mainland populations. But as opposed to this, higher levels of additive genetic variation (V _A) in body size and tibia length were found on the island of Gotland as compared to the mainland population. When comparing the differentiation seen in neutral marker genes (F _ST) with the differentiation in genes coding quantitative traits (Q _ST) two different evolutionary scenarios were found: while selection might explain a smaller size of moor frogs on Gotland, the differentiation seen in tibia length could be explained by genetic drift. These results highlight the limited utility of microsatellite loci alone in inferring the causes behind an observed phenotypic differentiation, or in predicting the amount of genetic variation in ecologically important quantitative traits.     

Genomic evidence for convergent evolution of a key trait underlying divergence in island birds

Reproductive isolation can be initiated by changes in one or a few key traits that prevent random mating among individuals in a population. During the early stages of speciation, when isolation is often incomplete, there will be a heterogeneous pattern of differentiation across regions of the genome between diverging populations, with loci controlling these key traits appearing the most distinct as a result of strong diversifying selection. In this study, we used Illumina‐sequenced ddRAD tags to identify genomewide patterns of differentiation in three recently diverged island populations of the Monarcha castaneiventris flycatcher of the Solomon Islands. Populations of this species have diverged in plumage colour, and these differences in plumage colour, in turn, are used in conspecific recognition and likely important in reproductive isolation. Previous candidate gene sequencing identified point mutations in MC1R and ASIP, both known pigmentation genes, to be associated with the difference in plumage colour between islands. Here, we show that background levels of genomic differentiation based on over 70,000 SNPs are extremely low between populations of distinct plumage colour, with no loci reaching the level of differentiation found in either candidate gene. Further, we found that a phylogenetic analysis based on these SNPs produced a taxonomy wherein the two melanic populations appear to have evolved convergently, rather than from a single common ancestor, in contrast to their original classification as a single subspecies. Finally, we found evidence that the pattern of low genomic differentiation is the result of both incomplete lineage sorting and gene flow between populations.     

Genomic consequences of selection and genome-wide association mapping in soybean

Background

Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits.

Results

To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified.

Conclusions

These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1872-y) contains supplementary material, which is available to authorized users.     

Review: Opportunities and challenges for small populations of dairy cattle in the era of genomics

In modern dairy cattle breeding, genomic breeding programs have the potential to increase efficiency and genetic gain. At the same time, the requirements and the availability of genotypes and phenotypes present a challenge. The set-up of a large enough reference population for genomic prediction is problematic for numerically small breeds but also for hard to measure traits. The first part of this study is a review of the current literature on strategies to overcome the lack of reference data. One solution is the use of combined reference populations from different breeds, different countries, or different research populations. Results reveal that the level of relationship between the merged populations is the most important factor. Compiling closely related populations facilitates the accurate estimation of marker effects and thus results in high accuracies of genomic prediction. Consequently, mixed reference populations of the same breed, but from different countries are more promising than combining different breeds, especially if those are more distantly related. The use of female reference information has the potential to enlarge the reference population size. Including females is advisable for small populations and difficult traits, and maybe combined with genotyping females and imputing those that are un-genotyped.The efficient use of imputation for un-genotyped individuals requires a set of genotyped related animals and well-considered selection strategies which animals to choose for genotyping and phenotyping. Small populations have to find ways to derive additional advantages from the cost-intensive establishment of genomic breeding schemes. Possible solutions may be the use of genomic information for inbreeding control, parentage verification, within-herd selection, adjusted mating plans or conservation strategies.The second part of the paper deals with the issue of high-quality phenotypes against the background of new, difficult and hard to measure traits. The use of contracted herds for phenotyping is recommended, as additional traits, when compared to standard traits used in dairy cattle breeding can be measured at set moments in time. This can be undertaken even for the recording of health traits, thus resulting in complete contemporary groups for health traits. Future traits to be recorded and used in genomic breeding programs, at least partly will be traits for which traditional selection based on widespread phenotyping is not possible. Enabling phenotyping of sufficient numbers to enable genomic selection will rely on cooperation between scientists from different disciplines and may require multidisciplinary approaches.     

A global barley panel revealing genomic signatures of breeding in modern Australian cultivars

The future of plant cultivar improvement lies in the evaluation of genetic resources from currently available germplasm. Today’s gene pool of crop genetic diversity has been shaped during domestication and more recently by breeding. Recent efforts in plant breeding have been aimed at developing new and improved varieties from poorly adapted crops to suit local environments. However, the impact of these breeding efforts is poorly understood. Here, we assess the contributions of both historical and recent breeding efforts to local adaptation and crop improvement in a global barley panel by analysing the distribution of genetic variants with respect to geographic region or historical breeding category. By tracing the impact that breeding had on the genetic diversity of Hordeum vulgare (barley) released in Australia, where the history of barley production is relatively young, we identify 69 candidate regions within 922 genes that were under selection pressure. We also show that modern Australian barley varieties exhibit 12% higher genetic diversity than historical cultivars. Finally, field-trialling and phenotyping for agriculturally relevant traits across a diverse range of Australian environments suggests that genomic regions under strong breeding selection and their candidate genes are closely associated with key agronomic traits. In conclusion, our combined data set and germplasm collection provide a rich source of genetic diversity that can be applied to understanding and improving environmental adaptation and enhanced yields.     

A global alfalfa diversity panel reveals genomic selection signatures in Chinese varieties and genomic associations with root development

Alfalfa (Medicago sativa L.) is an important forage crop worldwide. However, little is known about the effects of breeding status and different geographical populations on alfalfa improvement. Here, we sequenced 220 alfalfa core germplasms and determined that Chinese alfalfa cultivars form an independent group, as evidenced by comparisons of F_ST values between different subgroups, suggesting that geographical origin plays an important role in group differentiation. By tracing the influence of geographical regions on the genetic diversity of alfalfa varieties in China, we identified 350 common candidate genetic regions and 548 genes under selection. We also defined 165 loci associated with 24 important traits from genome-wide association studies. Of those, 17 genomic regions closely associated with a given phenotype were under selection, with the underlying haplotypes showing significant differences between subgroups of distinct geographical origins. Based on results from expression analysis and association mapping, we propose that 6-phosphogluconolactonase (MsPGL) and a gene encoding a protein with NHL domains (MsNHL) are critical candidate genes for root growth. In conclusion, our results provide valuable information for alfalfa improvement via molecular breeding.     

Integrating genomic selection into dairy cattle breeding programmes: a review

Extensive genetic progress has been achieved in dairy cattle populations on many traits of economic importance because of efficient breeding programmes. Success of these programmes has relied on progeny testing of the best young males to accurately assess their genetic merit and hence their potential for breeding. Over the last few years, the integration of dense genomic information into statistical tools used to make selection decisions, commonly referred to as genomic selection, has enabled gains in predicting accuracy of breeding values for young animals without own performance. The possibility to select animals at an early stage allows defining new breeding strategies aimed at boosting genetic progress while reducing costs. The first objective of this article was to review methods used to model and optimize breeding schemes integrating genomic selection and to discuss their relative advantages and limitations. The second objective was to summarize the main results and perspectives on the use of genomic selection in practical breeding schemes, on the basis of the example of dairy cattle populations. Two main designs of breeding programmes integrating genomic selection were studied in dairy cattle. Genomic selection can be used either for pre-selecting males to be progeny tested or for selecting males to be used as active sires in the population. The first option produces moderate genetic gains without changing the structure of breeding programmes. The second option leads to large genetic gains, up to double those of conventional schemes because of a major reduction in the mean generation interval, but it requires greater changes in breeding programme structure. The literature suggests that genomic selection becomes more attractive when it is coupled with embryo transfer technologies to further increase selection intensity on the dam-to-sire pathway. The use of genomic information also offers new opportunities to improve preservation of genetic variation. However, recent simulation studies have shown that putting constraints on genomic inbreeding rates for defining optimal contributions of breeding animals could significantly reduce achievable genetic gain. Finally, the article summarizes the potential of genomic selection to include new traits in the breeding goal to meet societal demands regarding animal health and environmental efficiency in animal production.     

SNP genotypes reveal breed substructure,selection signatures and highly inbred regions in Piétrain pigs

The Piétrain pig originates from the Belgian village Piétrain some time between 1920 and 1950. Owing to its superior conformation, the Piétrain has spread worldwide since the 1960s. As initial population sizes were limited and close inbreeding was commonplace, the breed’s genetic diversity has been questioned. Therefore, this study examines Piétrain breed substructure, diversity and selection signatures using SNP data in comparison with Duroc, Landrace and Large White populations. Principal component analysis indicated three subpopulations, and F_ST analysis showed that US Piétrains differ most from European Piétrains. Average inbreeding based on runs of homozygosity (ROH) segments larger than 4 Mb ranged between 16.7 and 20.9%. The highest chromosomal inbreeding levels were found on SSC8 (42.7%). ROH islands were found on SSC8, SSC15 and SSC18 in all Piétrain populations, but numerous population-specific ROH islands were also detected. Moreover, a large ROH island on SSC8 (34–126 Mb) appears nearly fixed in all Piétrain populations, with a unique genotype. Chromosomal ROH patterns were similar between Piétrain populations. This study shows that Piétrain populations are genetically diverging, with at least three genetically distinct populations worldwide. Increasing genetic diversity in local Piétrain populations by introgression from other Piétrain populations seems to be only limited. Moreover, a unique 90 Mb region on SSC8 appeared largely fixed in the Piétrain breed, indicating that fixation was already present before the 1960s. We believe that strong selection and inbreeding during breed formation fixed these genomic regions in Piétrains. Finally, we hypothesize that independent coat color selection may have led to large ROH pattern similarities on SSC8 between unrelated pig breeds.     

Effect of Artificial Selection on Runs of Homozygosity in U.S. Holstein Cattle

The intensive selection programs for milk made possible by mass artificial insemination increased the similarity among the genomes of North American (NA) Holsteins tremendously since the 1960s. This migration of elite alleles has caused certain regions of the genome to have runs of homozygosity (ROH) occasionally spanning millions of continuous base pairs at a specific locus. In this study, genome signatures of artificial selection in NA Holsteins born between 1953 and 2008 were identified by comparing changes in ROH between three distinct groups under different selective pressure for milk production. The ROH regions were also used to estimate the inbreeding coefficients. The comparisons of genomic autozygosity between groups selected or unselected since 1964 for milk production revealed significant differences with respect to overall ROH frequency and distribution. These results indicate selection has increased overall autozygosity across the genome, whereas the autozygosity in an unselected line has not changed significantly across most of the chromosomes. In addition, ROH distribution was more variable across the genomes of selected animals in comparison to a more even ROH distribution for unselected animals. Further analysis of genome-wide autozygosity changes and the association between traits and haplotypes identified more than 40 genomic regions under selection on several chromosomes (Chr) including Chr 2, 7, 16 and 20. Many of these selection signatures corresponded to quantitative trait loci for milk, fat, and protein yield previously found in contemporary Holsteins.     

Discovery of selection-driven genetic differences of Duroc,Landrace, and Yorkshire pig breeds by EigenGWAS and Fst analyses

Pigs are one of the earliest domesticated animals and multiple breeds have been developed to meet the various demands of consumers. EigenGWAS is a novel strategy to identify candidate genes that underlying population genetic differences and to infer candidate regions under selection as well. In this study, EigenGWAS and F_st analyses were performed using the public re-sequencing data of three typical commercial pig breeds, Duroc, Landrace and Yorkshire. The intersection of genome-wide significant SNPs detected by EigenGWAS and top-ranked 1% SNPs of F_st results were treated as signals under selection. Using the data of all three breeds, 3062 signals under selection were detected and the nearby genomic regions within 300 kb upstream and downstream covered 6.54% of whole genome. Pairs of breeds were analysed along with the pathway analysis. The gene function enrichment results indicated that many candidate genes located in the genomic regions of the signals under selection were associated with biological processes related to growth, metabolism, reproduction, sensory perception, etc. Among the candidate genes, the FSHB, AHR, PTHLH, KDR and FST genes were reported to be associated with reproductive performance; the KIT, KITLG, MITF, MC1R and EDNRB genes were previously identified to affect coat colour; the RETREG1, TXNIP, BMP5, PPARD and RBP4 genes were reported to be associated with lipid metabolism and growth traits. The identified genetic differences across the three commercial breeds will advance understanding of the artificial selection history of pigs and the signals under selection will suggest potential uses in pig genomic breeding programmes.     

Combined approaches to reveal genes associated with litter size in Yunshang black goats

Intensive artificial selection has been imposed in Yunshang black goats, the first black specialist mutton goat breed in China, with a breeding object of improving reproductive performance, which has contributed to reshaping of the genome including the characterization of SNP, ROH and haplotype. However, variation in reproductive ability exists in the present population. A WGS was implemented in two subpopulations (polytocous group, PG, and monotocous group, MG) with evident differences of litter size. Following the mapping to reference genome, and SNP calling and pruning, three approaches – GWAS, ROH analysis and detection of signatures of selection – were employed to unveil candidate genes responsible for litter size. Consequently, 12 candidate genes containing OSBPL8 with the minimum P-value were uncovered by GWAS. Differences were observed in the pattern of ROH between two subpopulations that shared similar low inbreeding coefficients. Two ROH hotspots and 12 corresponding genes emerged from ROH pool association analysis. Based on the nS_L statistic, 15 and 61 promising genes were disclosed under selection for MG and PG respectively. Of them, some promising genes participate in ovarian function (PPP2R5C, CDC25A, ESR1, RPS26 and SERPINBs), seasonal reproduction (DIO3, BTG1 and CRYM) and metabolism (OSBPL8, SLC39A5 and SERPINBs). Our study pinpointed some novel promising genes influencing litter size, provided a comprehensive insight into genetic makeup of litter size and might facilitate selective breeding in goats.     

Effectiveness of genomic prediction on milk flow traits in dairy cattle

Background

Milkability, primarily evaluated by measurements of milking speed and time, has an economic impact in milk production of dairy cattle. Recently the Italian Brown Swiss Breeders Association has included milking speed in genetic evaluations. The main objective of this study was to investigate the possibility of implementing genomic selection for milk flow traits in the Italian Brown Swiss population and thereby evaluate the potential of genomic selection for novel traits in medium-sized populations. Predicted breeding values and reliabilities based on genomic information were compared with those obtained from traditional breeding values.

Methods

Milk flow measures for total milking time, ascending time, time of plateau, descending time, average milk flow and maximum milk flow were collected on 37 213 Italian Brown Swiss cows. Breeding values for genotyped sires (n = 1351) were obtained from standard BLUP and genome-enhanced breeding value techniques utilizing two-stage and single-step methods. Reliabilities from a validation dataset were estimated and used to compare accuracies obtained from parental averages with genome-enhanced predictions.

Results

Genome-enhanced breeding values evaluated using two-stage methods had similar reliabilities with values ranging from 0.34 to 0.49 for the different traits. Across two-stage methods, the average increase in reliability from parental average was approximately 0.17 for all traits, with the exception of descending time, for which reliability increased to 0.11. Combining genomic and pedigree information in a single-step produced the largest increases in reliability over parent averages: 0.20, 0.24, 0.21, 0.14, 0.20 and 0.21 for total milking time, ascending time, time of plateau, descending time, average milk flow and maximum milk flow, respectively.

Conclusions

Using genomic models increased the accuracy of prediction compared to traditional BLUP methods. Our results show that, among the methods used to predict genome-enhanced breeding values, the single-step method was the most successful at increasing the reliability for most traits. The single-step method takes advantage of all the data available, including phenotypes from non-genotyped animals, and can easily be incorporated into current breeding evaluations.     

The Genomic Architecture of Adaptation to Larval Malnutrition Points to a Trade-off with Adult Starvation Resistance in Drosophila

Periods of nutrient shortage impose strong selection on animal populations. Experimental studies of genetic adaptation to nutrient shortage largely focus on resistance to acute starvation at adult stage; it is not clear how conclusions drawn from these studies extrapolate to other forms of nutritional stress. We studied the genomic signature of adaptation to chronic juvenile malnutrition in six populations of Drosophila melanogaster evolved for 150 generations on an extremely nutrient-poor larval diet. Comparison with control populations evolved on standard food revealed repeatable genomic differentiation between the two set of population, involving >3,000 candidate SNPs forming >100 independently evolving clusters. The candidate genomic regions were enriched in genes implicated in hormone, carbohydrate, and lipid metabolism, including some with known effects on fitness-related life-history traits. Rather than being close to fixation, a substantial fraction of candidate SNPs segregated at intermediate allele frequencies in all malnutrition-adapted populations. This, together with patterns of among-population variation in allele frequencies and estimates of Tajima’s D, suggests that the poor diet results in balancing selection on some genomic regions. Our candidate genes for tolerance to larval malnutrition showed a high overlap with genes previously implicated in acute starvation resistance. However, adaptation to larval malnutrition in our study was associated with reduced tolerance to acute adult starvation. Thus, rather than reflecting synergy, the shared genomic architecture appears to mediate an evolutionary trade-off between tolerances to these two forms of nutritional stress.