Partitioning additive genetic variance into genomic and remaining polygenic components for complex traits in dairy cattle

ABSTRACT: BACKGROUND: Low cost genotyping of individuals using high density genomic markers were recently introduced as genomic selection in genetic improvement programs in dairy cattle. Most implementations of genomic selection only use marker information, in the models used for prediction of genetic merit. However, in other species it has been shown that only a fraction of the total genetic variance can be explained by markers. Using 5217 bulls in the Nordic Holstein population that were genotyped and had genetic evaluations based on progeny, we partitioned the total additive genetic variance into a genomic component explained by markers and a remaining component explained by familial relationships. The traits analyzed were production and fitness related traits in dairy cattle. Furthermore, we estimated the genomic variance that can be attributed to individual chromosomes and we illustrate methods that can predict the amount of additive genetic variance that can be explained by sets of markers with different density. RESULTS: The amount of additive genetic variance that can be explained by markers was estimated by an analysis of the matrix of genomic relationships. For the traits in the analysis, most of the additive genetic variance can be explained by 44 K informative SNP markers. The same amount of variance can be attributed to individual chromosomes but surprisingly the relation between chromosomal variance and chromosome length was weak. In models including both genomic (marker) and familial (pedigree) effects most (on average 77.2%) of total additive genetic variance was explained by genomic effects while the remaining was explained by familial relationships. CONCLUSIONS: Most of the additive genetic variance for the traits in the Nordic Holstein population can be explained using 44 K informative SNP markers. By analyzing the genomic relationship matrix it is possible to predict the amount of additive genetic variance that can be explained by a reduced (or increased) set of markers. For the population analyzed the improvement of genomic prediction by increasing marker density beyond 44 K is limited.     

An association study using AFLP markers and application to a beef cattle breeding population

Using amplified fragment length polymorphism (AFLP) fingerprinting, selective genotyping was performed to determine if this method was effective for selecting superior breeding stock. Forty-eight cows with extreme genetic merit for beef marbling score (BMS) were selected from a population of Japanese Black cattle (n = 4462), including 25 with the highest for predicted breeding value (PBV) and 23 with the lowest. Sixteen AFLP fragments were selected for further analysis based on fragment frequency differences between the high and low groups. A linear discriminant analysis using these AFLP fragments was applied in order to derive a discriminant function that classified the cows into high and low groups. Seven of the 16 fragments were included in the resulting function and the discriminant scores (general genetic values, GGV) of the 48 cows were calculated using the function. These cows were clearly separated into high and low groups by GGV with a correlation ratio of 0.91 (discriminative error of 2.1%). The same function was then applied to 121 additional cows that were randomly selected from the original population. A significant regression coefficient of GGV on BMS-PBV (R2 = 0.45) was obtained, which indicates that the GGV can be used as a selection criterion for BMS in this population. These results suggest that AFLP fingerprinting can be used for animal breeding without identifying the underlying genes affecting the trait of interest.     

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

Background

The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle.

Methods

Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models.

Results and discussion

On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence.

Conclusions

For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.     

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k₁ (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k₁ and α. QTLs within genomic regions mapped for k₁ are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k₁ were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k₁ did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.     

Evaluation of bull fertility in dairy and beef cattle using cow field data

A successful outcome to a given service is a combination of both male and female fertility. Despite this, most national evaluations for fertility are generally confined to female fertility with evaluations for male fertility commonly undertaken by individual breeding organisations and generally not made public. The objective of this study was to define a pertinent male fertility trait for seasonal calving production systems, and to develop a multiple regression mixed model that may be used to evaluate male fertility at a national level. The data included in the study after editing consisted of 361,412 artificial inseminations from 206,683 cow-lactations (134,911 cows) in 2,843 commercial dairy and beef herds. Fixed effects associated with whether a successful pregnancy ensued (pregnant = 1) or not (pregnant = 0) from a given service were year by month of service, day of the week, days since calving, cow parity, level of calving difficulty experienced, whether or not the previous calving was associated with perinatal mortality, and age of the service bull at the date of insemination. Non-additive genetic effects such as heterosis and recombination loss as well as inbreeding level of the service bull, dam or mating were not associated with a successful pregnancy; there was no difference in pregnancy rate between fresh or frozen semen. Random effects included in the model were the additive genetic effect of the cow, as well as a within lactation and across lactation permanent environmental effect of the cow; pedigree group effects based on cow breed were also included via the relationship matrix. Temporal differences in the AI technician and service bull were also included as random effects. A difference in five percentage units in male fertility was evident between the average effects of different dairy and beef breeds. The correlation between raw pregnancy rates for bulls with more than 100 services (n = 431) and service bull solutions from the mixed model analysis was 0.66. The correlation between the raw pregnancy rates of 288 technicians with more than 100 services and their respective solutions from the mixed model was 0.35. These low to moderate correlations suggest considerable re-ranking among both service bulls and technicians and suggest possibly a benefit of using a statistical model to better estimate the performance of both service bulls and technicians.     

Generalized optimal spatial filtering using a kernel approach with application to EEG classification

Common spatial patterns (CSP) has been widely used for finding the linear spatial filters which are able to extract the discriminative brain activities between two different mental tasks. However, the CSP is difficult to capture the nonlinearly clustered structure from the non-stationary EEG signals. To relax the presumption of strictly linear patterns in the CSP, in this paper, a generalized CSP (GCSP) based on generalized singular value decomposition (GSVD) and kernel method is proposed. Our method is able to find the nonlinear spatial filters which are formulated in the feature space defined by a nonlinear mapping through kernel functions. Furthermore, in order to overcome the overfitting problem, the regularized GCSP is developed by adding the regularized parameters. The experimental results demonstrate that our method is an effective nonlinear spatial filtering method.     

Associations of the bovine major histocompatibility complex DRB3 (BoLA-DRB3) with production traits in Canadian dairy cattle

Associations of two alleles of the bovine major histocompatibility complex DRB3 gene (BoLA-DRB3) with lowered somatic cell score (SCS) and occurrence of disease (BoLA-DRB3.2* 16 and *23, respectively) have previously been documented. The objective of this study was to evaluate potential relationships between BoLA-DRB3 alleles with production traits, namely 305-day milk, milk fat and milk protein yield, in a population of Canadian dairy cattle (Holstein, n = 835 and Jersey, n = 66) over the course of two lactations. No significant associations were detected between BoLA alleles and production traits in Jerseys. In Holsteins, alleles *16 and *23 also did not show associations with production traits but allele *8 was significantly associated with increased 305-day milk, fat and protein yields in the previous lactation (the lactation prior to immunization with a gram negative core antigen vaccine), and with increased protein production in the subsequent (with reference to the time of immunization) lactation. Allele *22 was associated with decreased milk and protein yield in both previous and subsequent lactations. Therefore, it can be concluded that increasing or decreasing the frequency of BoLA alleles *16 and *23 to reduce SCS or increase resistance to mastitis in this population would not have adverse effects on production in this population, and that certain BoLA alleles (*8 and *22) are associated with altered production traits in Canadian Holsteins.     

SSR markers and seed quality traits revealed genetic diversity in durum wheat (Triticum durum Desf.)

Molecular Biology Reports - Genetic diversity and differences among durum-wheat cultivars evolved in various regions of the world are important for sustainable production in the current climate...     

Molecular markers to study genetic drift and selection in wheat populations

Studying the heterogeneity in variation of gene frequency among populations or between generations may be a possible way to detect genomic regions experiencing selection. In order to evaluate this approach, RFLP markers were used to compare the allelic frequencies in wheat populations that had been submitted to natural selection. In 1984, samples of two composite cross populations were distributed in the French network for dynamic management of genetic resources. Since then, all the sub-populations have been cultivated in the same sites with no human selection. The strong differentiation between populations found for agro-morphological traits (earliness, resistance to pathogens, ...) provided evidence of their adaptation to local conditions. The two initial populations and six derived sub-populations cultivated for 10 years in four contrasted sites were studied with RFLP markers. Differentiation between sub-populations based on RFLP diversity was highly significant. Variations on allelic frequencies of the 30 loci scored were found to be much greater than expected under genetic drift only. This led us to conclude that selection greatly influenced the evolution of the populations. Some of the loci clearly presented a higher differentiation than the others. This might indicate that they were genetically linked to other loci polymorphic in the populations and involved in adaptation. However, the effect of one selected gene on a marker, even located very close to the gene, could not be predicted with certainty. Hence, though the populations were predominantly selfing, it seems that initial linkage disequilibriums between markers and selected genes were not strong enough to control closely the evolution of allelic frequencies at the markers.     

Identification of kernel iron- and zinc-rich maize inbreds and analysis of genetic diversity using microsatellite markers

Development of micronutrient enriched staple foods is an important breeding goal in view of the extensive problem of ‘hidden hunger’ caused by micronutrient malnutrition. In the present study, kernel iron (Fe) and zinc (Zn) concentrations were evaluated in a set of 31 diverse maize inbred lines in three trials at two locations – Delhi (Kharif 2007 & 2008) and Hyderabad (Rabi 2007–08). The ranges of kernel Fe and Zn concentrations were 13.95–39.31 mg/kg and 21.85–40.91 mg/kg, respectively, across the three environments. Pooled analysis revealed significant genotype × environment (G × E) interaction in the expression of both the micronutrient traits, although kernel Fe was found to be more sensitive to G × E as compared to kernel Zn. Seven inbred lines, viz., BAJIM-06-03, DQPM-6, CM212, BAJIM-06-12, DQPM-7, DQPM-2 and CM129, were found to be the most stable and promising inbred lines for kernel Zn concentration, while for kernel Fe concentration, no promising and stable genotypes could be identified. Analysis of molecular diversity in 24 selected inbred lines with phenotypic contrast for the two kernel micronutrient traits, using 50 SSR markers covering the maize genome, revealed high levels of polymorphisms (214 SSR alleles; mean PIC value?=?0.62). The phenotypically contrasting and genetically diverse maize inbred lines identified in this study could be potentially utilized in further studies on QTL analysis of kernel micronutrient traits in maize, and the stable and most promising kernel micronutrient-rich maize genotypes provide a good foundation for developing micronutrient-enriched maize varieties suitable for the Indian context.     

Assessment of genetic diversity of landraces of Dendrocalamus hamiltonii using AFLP markers and association with biochemical traits

Fermented bamboo shoots are popular traditional food items of various ethnic groups of the northeastern India, especially in Manipur State. Dendrocalamus hamiltonii is an economically important bamboo species used to produce fermented bamboo shoots. We studied genetic variability of this bamboo species in Chandel and Imphal-East (commercial production districts), using AFLP molecular markers. Each of the selected primers detected polymorphisms and 1614 (95.8%) were found to be polymorphic. Cluster analysis based on Dice similarity coefficients using UPGMA differentiated the populations into two major groups. Principal coordinate analysis based on the AFLP data clearly separated the populations according to their genetic diversity and antioxidant activity. Four primers were tested through multiple regression analysis to identify marker-trait association between AFLP data and biochemical attributes, i.e., antioxidant activity and total cyanide content. The 273 bp generated by EcoRI-AAG(Joe)/MseI-CTC showed high positive correlation with antioxidant activity (r = 0.729, P < 0.01). The 396 bp generated by EcoRI-AAC(Ned)/MseI-CTG were negatively correlated with cyanide content (r = -0.694, P < 0.01). Thus, we found association of DNA markers with antioxidant activities and total cyanide content. These results could be of use for the identification of superior genotypes with desirable traits.     

Twins. Novel uses to study complex traits and genetic diseases

The challenge faced by research into the genetic basis of complex disease is to identify genes of small relative effect against a background of substantial genetic and environmental variation. This has focused interest on a classical epidemiological design: the study of twins. Through their precise matching for age, the common family environment and background environmental variation, studying diseases in non-identical twins provides a means to enhance the power of conventional strategies to detect genetic influence through linkage and association. The unique matching of identical twins provides researchers with ways to isolate the function of individual genes involved in disease together with approaches to understanding how genes and the environment interact.     

SNP identification and allelic-specific PCR markers development for TaGW2, a gene linked to wheat kernel weight

TaGW2, an orthologous gene of rice OsGW2, has been associated with kernel width and weight of bread wheat (Triticum aestivum). Difference in TaGW2 coding sequence was not found among different wheat varieties in previous researches. In this study, we found eight exons and seven introns in TaGW2 with a full-length cDNA sequence of 1,275?bp, which contains a conserved function domain and seven splice sites that shared homology with rice OsGW2. A single T-base insertion in the eighth exon of TaGW2 on chromosome 6A was detected in a large-kernel wheat variety, Lankaodali. This insertion mutation reduces the coding protein sequence from normal 424 amino acids (~47.2?kDa) to 328 amino acids (~37.1?kDa) by truncating 96 amino acids. The result was validated by identifying histidine-tagged TaGW2 proteins encoded by both alleles of the mutant and the wild types in SDS-PAGE. Allele-specific PCR markers were developed based on the single nucleotide polymorphism (SNP) site. The SNP markers were genotyped for an F(2) segregation population from the cross of Lankaodali?×?Chinese Spring. Seed traits of F(2:3) families were evaluated in three different environments. The association analysis indicated that F(2:3) families with the mutated TaGW2 allele significantly increased kernel width (KW) and thousand-kernel weight (TKW), and slightly improved kernel length (KL). Using the SNP markers, another two varieties harbored the mutated TaGW2 allele were successfully identified from 22 additional wheat varieties, and they both have large KW and TKW. Cloning and sequencing of the gene further confirmed the functions of the mutated allele of TaGW2 in the two large kernel varieties. The results suggested that TaGW2 may negatively regulate kernel size variation, which shares the same function as OsGW2 in rice. The successful development of SNP markers provides a useful tool for improving kernel yield in wheat.     

Comparative genetic analyses of metric traits using diallel and factorial mating designs in bread wheat

Summary For studying the inheritance of metric traits, diallel cross and factorial mating designs are commonly used. Since factorial mating design is less restrictive in crossing plans, the genetic information drawn from it was compared with that from a diallel cross. The comparison was made using graphical, genetic components and combining ability analyses for grain yield, grain weight and spike length in a field experiment of bread wheat (Triticum aestivum L.). Analyses were made on a nine parent diallel cross and a 4 × 5 factorial mating design which was sampled from the diallel cross. In general, there was a high degree of agreement between the results obtained from factorial mating design and diallel cross analyses showing thereby that the former provides almost equivalent genetic information to the latter.     

Characterization of genetic diversity and population structure in wheat using array based SNP markers

Genetic diversity is crucial for successful adaptation and sustained improvement in crops. India is bestowed with diverse agro-climatic conditions which makes it rich in wheat germplasm adapted to various niches. Germplasm repository consists of local landraces, trait specific genetic stocks including introgressions from wild relatives, exotic collections, released varieties, and improved germplasm. Characterization of genetic diversity is done using morpho-physiological characters as well as by analyzing variations at DNA level. However, there are not many reports on array based high throughput SNP markers having characteristics of genome wide coverage employed in Indian spring wheat germplasm. Amongst wheat SNP arrays, 35K Axiom Wheat Breeder’s Array has the highest SNP polymorphism efficiency suitable for genetic mapping and genetic diversity characterization. Therefore, genotyping was done using 35K in 483 wheat genotypes resulting in 14,650 quality filtered SNPs, that were distributed across the B (~?50%), A (~?39%), and D (~?10%) genomes. The total genetic distance coverage was 4477.85 cM with 3.27 SNP/cM and 0.49 cM/SNP as average marker density and average inter-marker distance, respectively. The PIC ranged from 0.09 to 0.38 with an average of 0.29 across genomes. Population structure and Principal Coordinate Analysis resulted in two subpopulations (SP1 and SP2). The analysis of molecular variance revealed the genetic variation of 2% among and 98% within subpopulations indicating high gene flow between SP1 and SP2. The subpopulation SP2 showed high level of genetic diversity based on genetic diversity indices viz. Shannon’s information index (I)?=?0.648, expected heterozygosity (He)?=?0.456 and unbiased expected heterozygosity (uHe)?=?0.456. To the best of our knowledge, this study is the first to include the largest set of Indian wheat genotypes studied exclusively for genetic diversity. These findings may serve as a potential source for the identification of uncharacterized QTL/gene using genome wide association studies and marker assisted selection in wheat breeding programs.

     

SSR-based linkage map with new markers using an intraspecific population of common wheat

Simple sequence repeats (SSRs) are valuable molecular markers in many plant species. In common wheat (Triticum aestivum L.), which is characteristic of its large genomes and alloploidy, SSRs are one of the most useful markers. To increase SSR marker sources and construct an SSR-based linkage map of appropriate density, we tried to develop new SSR markers from SSR-enriched genomic libraries and the public database. SSRs having (GA)n and (GT)n motifs were isolated from enriched libraries, and di- and tri-nucleotide repeats were mined from expressed sequence tags (ESTs) and DNA sequences of Triticum species in the public database. Of the 1,147 primer pairs designed, 842 primers gave accurate amplification products, and 478 primers showed polymorphism among the nine wheat lines examined. Using a doubled haploid (DH) population from an intraspecific cross between Kitamoe and Münstertaler (KM), we constructed an SSR-based linkage map that consisted of 464 loci: 185 loci from genomic libraries, 65 loci from the sequence database including ESTs, 213 loci from the SSR markers already reported, and 1 locus of morphological marker. Although newly developed SSR loci were distributed throughout all chromosomes, clustering of them around putative centromeric regions was found on several chromosomes. The total length of the KM map spanned 3,441 cM and corresponded to approximately 86% genome coverage. The KM map comprised of 23 linkage groups because two gaps of over 50 cM distance remained on chromosome 6A. This is a first report of SSR-based linkage map using single intraspecific population of common wheat. This mapping result suggests that it becomes possible to construct linkage maps with sufficient genome coverage using only SSR markers without RFLP markers, even in an intraspecific population of common wheat. Moreover, the new SSR markers will contribute to the enrichment of molecular marker resources in common wheat.