Genomic prediction methods based on multiple markers have potential to include nonadditive effects in prediction and analysis of complex traits. However, most developments assume a Hardy-Weinberg ...equilibrium (HWE). Statistical approaches for genomic selection that account for dominance and epistasis in a general context, without assuming HWE (
, crosses or homozygous lines), are therefore needed. Our method expands the natural and orthogonal interactions (NOIA) approach, which builds incidence matrices based on genotypic (not allelic) frequencies, to include genome-wide epistasis for an arbitrary number of interacting loci in a genomic evaluation context. This results in an orthogonal partition of the variances, which is not warranted otherwise. We also present the partition of variance as a function of genotypic values and frequencies following Cockerham's orthogonal contrast approach. Then we prove for the first time that, even not in HWE, the multiple-loci NOIA method is equivalent to construct epistatic genomic relationship matrices for higher-order interactions using Hadamard products of additive and dominant genomic orthogonal relationships. A standardization based on the trace of the relationship matrices is, however, needed. We illustrate these results with two simulated F
(not in HWE) populations, either in linkage equilibrium (LE), or in linkage disequilibrium (LD) and divergent selection, and pure biological dominant pairwise epistasis. In the LE case, correct and orthogonal estimates of variances were obtained using NOIA genomic relationships but not if relationships were constructed assuming HWE. For the LD simulation, differences were smaller, due to the smaller deviation of the F
from HWE. Wrongly assuming HWE to build genomic relationships and estimate variance components yields biased estimates, inflates the total genetic variance, and the estimates are not empirically orthogonal. The NOIA method to build genomic relationships, coupled with the use of Hadamard products for epistatic terms, allows the obtaining of correct estimates in populations either in HWE or not in HWE, and extends to any order of epistatic interactions.
Estimation of non-additive genetic effects in animal breeding is important because it increases the accuracy of breeding value prediction and the value of mate allocation procedures. With the advent ...of genomic selection these ideas should be revisited. The objective of this study was to quantify the efficiency of including dominance effects and practising mating allocation under a whole-genome evaluation scenario. Four strategies of selection, carried out during five generations, were compared by simulation techniques. In the first scenario (MS), individuals were selected based on their own phenotypic information. In the second (GSA), they were selected based on the prediction generated by the Bayes A method of whole-genome evaluation under an additive model. In the third (GSD), the model was expanded to include dominance effects. These three scenarios used random mating to construct future generations, whereas in the fourth one (GSD + MA), matings were optimized by simulated annealing. The advantage of GSD over GSA ranges from 9 to 14% of the expected response and, in addition, using mate allocation (GSD + MA) provides an additional response ranging from 6% to 22%. However, mate selection can improve the expected genetic response over random mating only in the first generation of selection. Furthermore, the efficiency of genomic selection is eroded after a few generations of selection, thus, a continued collection of phenotypic data and re-evaluation will be required.
In the last decade, genomic selection has become a standard in the genetic evaluation of livestock populations. However, most procedures for the implementation of genomic selection only consider the ...additive effects associated with SNP (Single Nucleotide Polymorphism) markers used to calculate the prediction of the breeding values of candidates for selection. Nevertheless, the availability of estimates of non-additive effects is of interest because: (i) they contribute to an increase in the accuracy of the prediction of breeding values and the genetic response; (ii) they allow the definition of mate allocation procedures between candidates for selection; and (iii) they can be used to enhance non-additive genetic variation through the definition of appropriate crossbreeding or purebred breeding schemes. This study presents a review of methods for the incorporation of non-additive genetic effects into genomic selection procedures and their potential applications in the prediction of future performance, mate allocation, crossbreeding, and purebred selection. The work concludes with a brief outline of some ideas for future lines of that may help the standard inclusion of non-additive effects in genomic selection.
Blastocystis sp. is among the most frequent intestinal protists identified in humans globally. However, characterization of Blastocystis subtype diversity in humans is ongoing. We report here the ...identification of novel Blastocystis subtype ST41 in a Colombian patient undergoing colorectal cancer screening involving colonoscopy and fecal testing (microscopy, culture, PCR). The full‐length ssu rRNA gene sequence of the protist was generated using MinION long‐read sequencing technology. The validity of the novel subtype was confirmed via phylogenetic and pairwise distance analyses of the full‐length ST41 sequence and all other valid subtypes. The study provides reference material essential for conducting subsequent experimental studies.
For both undivided and subdivided populations, the consensus method to maintain genetic diversity is the Optimal Contribution (OC) method. For subdivided populations, this method determines the ...optimal contribution of each candidate to each subpopulation to maximize global genetic diversity (which implicitly optimizes migration between subpopulations) while balancing the relative levels of coancestry between and within subpopulations. Inbreeding can be controlled by increasing the weight given to within-subpopulation coancestry (λ). Here we extend the original OC method for subdivided populations that used pedigree-based coancestry matrices, to the use of more accurate genomic matrices. Global levels of genetic diversity, measured as expected heterozygosity and allelic diversity, their distributions within and between subpopulations, and the migration pattern between subpopulations, were evaluated via stochastic simulations. The temporal trajectory of allele frequencies was also investigated. The genomic matrices investigated were (i) the matrix based on deviations of the observed number of alleles shared by two individuals from the expected number under Hardy-Weinberg equilibrium; and (ii) a matrix based on a genomic relationship matrix. The matrix based on deviations led to higher global and within-subpopulation expected heterozygosities, lower inbreeding and similar allelic diversity than the second genomic and pedigree-based matrices when a relatively high weight was given to the within-subpopulation coancestries (λ ≥ 5). Under this scenario, allele frequencies moved only slightly away from the initial frequencies. Therefore, the recommended strategy is to use the former matrix in the OC methodology giving a high weight to the within-subpopulation coancestry.
Availability of fixed nitrogen is a pivotal driver on primary productivity in the oceans, thus the identification of key processes triggering nitrogen losses from these ecosystems is of major ...importance as they affect ecosystems function and consequently global biogeochemical cycles. Denitrification and anaerobic ammonium oxidation coupled to nitrite reduction (Anammox) are the only identified marine sinks for fixed nitrogen. The present study provides evidence indicating that anaerobic ammonium oxidation coupled to the reduction of sulfate, the most abundant electron acceptor present in the oceans, prevails in marine sediments. Tracer analysis with
15
N-ammonium revealed that this microbial process, here introduced as Sulfammox, accounts for up to 5 μg
15
N
2
produced g
−1
day
−1
in sediments collected from the eastern tropical North Pacific coast. Raman and X-ray diffraction spectroscopies revealed that elemental sulfur and sphalerite (ZnFeS) were produced, besides free sulfide, during the course of Sulfammox. Anaerobic ammonium oxidation linked to Fe(III) reduction (Feammox) was also observed in the same marine sediments accounting for up to 2 μg
15
N
2
produced g
−1
day
−1
. Taxonomic characterization, based on 16S rRNA gene sequencing, of marine sediments performing the Sulfammox and Feammox processes revealed the microbial members potentially involved. These novel nitrogen sinks may significantly fuel nitrogen loss in marine environments. These findings suggest that the interconnections among the oceanic biogeochemical cycles of N, S and Fe are much more complex than previously considered.
The availability of genome-wide marker data allows estimation of inbreeding coefficients (F, the probability of identity-by-descent, IBD) and, in turn, estimation of the rate of inbreeding depression ...(ΔID). We investigated, by computer simulations, the accuracy of the most popular estimators of inbreeding based on molecular markers when computing F and ΔID in populations under random mating, equalization of parental contributions, and artificially selected populations. We assessed estimators described by Li and Horvitz (F
and F
), VanRaden (F
and F
), Yang and colleagues (F
and F
), marker homozygosity (F
), runs of homozygosity (F
) and estimates based on pedigree (F
) in comparison with estimates obtained from IBD measures (F
).
If the allele frequencies of a base population taken as a reference for the computation of inbreeding are known, all estimators based on marker allele frequencies are highly correlated with F
and provide accurate estimates of the mean ΔID. If base population allele frequencies are unknown and current frequencies are used in the estimations, the largest correlation with F
is generally obtained by F
and the best estimator of ΔID is F
. The estimators F
and F
have the poorest performance in most scenarios. The assumption that base population allele frequencies are equal to 0.5 results in very biased estimates of the average inbreeding coefficient but they are highly correlated with F
and give relatively good estimates of ΔID. Estimates obtained directly from marker homozygosity (F
) substantially overestimated ΔID. Estimates based on runs of homozygosity (F
) provide accurate estimates of inbreeding and ΔID. Finally, estimates based on pedigree (F
) show a lower correlation with F
than molecular estimators but provide rather accurate estimates of ΔID. An analysis of data from a pig population supports the main findings of the simulations.
When base population allele frequencies are known, all marker-allele frequency-based estimators of inbreeding coefficients generally show a high correlation with F
and provide good estimates of ΔID. When base population allele frequencies are unknown, F
is the marker frequency-based estimator that is most correlated with F
, and F
provides the most accurate estimates of ΔID. Estimates from F
are also very precise in most scenarios. The estimators F
and F
have the poorest performances.
Abstract Numerous factors determine information security-related actions (IS-actions) in the workplace. Attitudes toward following security rules and recommendations and attitudes toward specific IS ...actions determine intentions associated with those actions. IS research has examined the role of the instrumental aspect of attitudes. However, authors argue that attitudes toward a behavioral object are a multidimensional construct. We examined the dimensionality of attitudes toward security recommendations, hypothesized its multidimensional nature, and developed a new scale attitudes toward security recommendations (ASR scale). The results indicated the multidimensional nature of attitudes toward security recommendations supporting our hypothesis. The results revealed two dimensions corresponding to the perceived legitimacy and effectiveness of security recommendations and its perceived rigor. The new ASR scale showed good psychometric properties. This work contributes to the IS research at suggesting that attitudes are a multidimensional construct in the IS context. These findings imply that the employee’s evaluation of information security policy can be examined considering their instrumentality (security recommendations are important) and rigor (security recommendations are strict). Different effects of the dimensions of attitudes over IS-action suggest different interventions. Additionally, this study offers the ASR scale as a new instrument to capture employees’ evaluation of security recommendations.
Interactions between fish and pathogens, that may be harmless under natural conditions, often result in serious diseases in aquaculture systems. This is especially important due to the fact that the ...strains used in aquaculture are derived from wild strains that may not have had enough time to adapt to new disease pressures. The turbot is one of the most promising European aquaculture species. Furunculosis, caused by the bacterium Aeromonas salmonicida, produces important losses to turbot industry. An appealing solution is to achieve more robust broodstock, which can prevent or diminish the devastating effects of epizooties. Genomics strategies have been developed in turbot to look for candidate genes for resistance to furunculosis and a genetic map with appropriate density to screen for genomic associations has been also constructed. In the present study, a genome scan for QTL affecting resistance and survival to A. salmonicida in four turbot families was carried out. The objectives were to identify consistent QTL using different statistical approaches (linear regression and maximum likelihood) and to locate the tightest associated markers for their application in genetic breeding strategies.
Significant QTL for resistance were identified by the linear regression method in three linkage groups (LGs 4, 6 and 9) and for survival in two LGs (6 and 9). The maximum likelihood methodology identified QTL in three LGs (5, 6 and 9) for both traits. Significant association between disease traits and genotypes was detected for several markers, some of them explaining up to 17% of the phenotypic variance. We also identified candidate genes located in the detected QTL using data from previously mapped markers.
Several regions controlling resistance to A. salmonicida in turbot have been detected. The observed concordance between different statistical methods at particular linkage groups gives consistency to our results. The detected associated markers could be useful for genetic breeding strategies. A finer mapping will be necessary at the detected QTL intervals to narrow associations and around the closely associated markers to look for candidate genes through comparative genomics or positional cloning strategies. The identification of associated variants at specific genes will be essential, together with the QTL associations detected in this study, for future marker assisted selection programs.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Genomic relationship matrices are used to obtain genomic inbreeding coefficients. However, there are several methodologies to compute these matrices and there is still an unresolved debate on which ...one provides the best estimate of inbreeding. In this study, we investigated measures of inbreeding obtained from five genomic matrices, including the Nejati-Javaremi allelic relationship matrix (F
), the Li and Horvitz matrix based on excess of homozygosity (F
), and the VanRaden (methods 1, F
, and 2, F
) and Yang (F
) genomic relationship matrices. We derived expectations for each inbreeding coefficient, assuming a single locus model, and used these expectations to explain the patterns of the coefficients that were computed from thousands of single nucleotide polymorphism genotypes in a population of Iberian pigs.
Except for F
, the evaluated measures of inbreeding do not match with the original definitions of inbreeding coefficient of Wright (correlation) or Malécot (probability). When inbreeding coefficients are interpreted as indicators of variability (heterozygosity) that was gained or lost relative to a base population, both F
and F
led to sensible results but this was not the case for F
, F
and F
. When variability has increased relative to the base, F
, F
and F
can indicate that it decreased. In fact, based on F
, variability is not expected to increase. When variability has decreased, F
and F
can indicate that it has increased. Finally, these three coefficients can indicate that more variability than that present in the base population can be lost, which is also unreasonable. The patterns for these coefficients observed in the pig population were very different, following the derived expectations. As a consequence, the rate of inbreeding depression estimated based on these inbreeding coefficients differed not only in magnitude but also in sign.
Genomic inbreeding coefficients obtained from the diagonal elements of genomic matrices can lead to inconsistent results in terms of gain and loss of genetic variability and inbreeding depression estimates, and thus to misleading interpretations. Although these matrices have proven to be very efficient in increasing the accuracy of genomic predictions, they do not always provide a useful measure of inbreeding.
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