Systematic differences in the response of genetic variation to pedigree and genome-based selection methods.

Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60 K SNP chip with markers spaced throughout the entire chicken genome, we compared the impact of GS and traditional BLUP (best linear unbiased prediction) selection methods applied side-by-side in three different lines of egg-laying chickens. Differences were demonstrated between methods, both at the level and genomic distribution of allele frequency changes. In all three lines, the average allele frequency changes were larger with GS, 0.056 0.064 and 0.066, compared with BLUP, 0.044, 0.045 and 0.036 for lines B1, B2 and W1, respectively. With BLUP, 35 selected regions (empirical P < 0.05) were identified across the three lines. With GS, 70 selected regions were identified. Empirical thresholds for local allele frequency changes were determined from gene dropping, and differed considerably between GS (0.167-0.198) and BLUP (0.105-0.126). Between lines, the genomic regions with large changes in allele frequencies showed limited overlap. Our results show that GS applies selection pressure much more locally than BLUP, resulting in larger allele frequency changes. With these results, novel insights into the nature of selection on quantitative traits have been gained and important questions regarding the long-term impact of GS are raised. The rapid changes to a part of the genetic architecture, while another part may not be selected, at least in the short term, require careful consideration, especially when selection occurs before phenotypes are observed.

Genome-wide association mapping including phenotypes from relatives without genotypes.

A common problem for genome-wide association analysis (GWAS) is lack of power for detection of quantitative trait loci (QTLs) and precision for fine mapping. Here, we present a statistical method, termed single-step GBLUP (ssGBLUP), which increases both power and precision without increasing genotyping costs by taking advantage of phenotypes from other related and unrelated subjects. The procedure achieves these goals by blending traditional pedigree relationships with those derived from genetic markers, and by conversion of estimated breeding values (EBVs) to marker effects and weights. Additionally, the application of mixed model approaches allow for both simple and complex analyses that involve multiple traits and confounding factors, such as environmental, epigenetic or maternal environmental effects. Efficiency of the method was examined using simulations with 15,800 subjects, of which 1500 were genotyped. Thirty QTLs were simulated across genome and assumed heritability was 0·5. Comparisons included ssGBLUP applied directly to phenotypes, BayesB and classical GWAS (CGWAS) with deregressed proofs. An average accuracy of prediction 0·89 was obtained by ssGBLUP after one iteration, which was 0·01 higher than by BayesB. Power and precision for GWAS applications were evaluated by the correlation between true QTL effects and the sum of m adjacent single nucleotide polymorphism (SNP) effects. The highest correlations were 0·82 and 0·74 for ssGBLUP and CGWAS with m=8, and 0·83 for BayesB with m=16. Standard deviations of the correlations across replicates were several times higher in BayesB than in ssGBLUP. The ssGBLUP method with marker weights is faster, more accurate and easier to implement for GWAS applications without computing pseudo-data.

Effect of different genomic relationship matrices on accuracy and scale.

Phenotypic data on BW and breast meat area were available on up to 287,614 broilers. A total of 4,113 birds were genotyped for 57,636 SNP. Data were analyzed by a single-step genomic BLUP (ssGBLUP), which accounts for all phenotypic, pedigree, and genomic information. The genomic relationship matrix (G) in ssGBLUP was constructed using either equal (0.5; GEq) or current (GC) allele frequencies, and with all SNP or with SNP with minor allele frequencies (MAF) below multiple thresholds (0.1, 0.2, 0.3, and 0.4) ignored. Additionally, a pedigree-based relationship matrix for genotyped birds (A(22)) was available. The matrices and their inverses were compared with regard to average diagonal (AvgD) and off-diagonal (AvgOff) elements. In A(22), AvgD was 1.004 and AvgOff was 0.014. In GEq, both averages decreased with the increasing thresholds for MAF, with AvgD decreasing from 1.373 to 1.020 and AvgOff decreasing from 0.722 to 0.025. In GC, AvgD was approximately 1.01 and AvgOff was 0 for all MAF. For inverses of the relationship matrices, all AvgOff were close to 0; AvgD was 2.375 in A(22), varied from 11.563 to 12.943 for GEq, and increased from 8.675 to 12.859 for GC as the threshold for MAF increased. Predictive ability with all GEq and GC was similar except that at MAF = 0.4, they declined by 0.01 for BW and improved by 0.01 for breast meat area. Compared with BLUP, EBV in the ssGBLUP were, on average, increased by up to 1 additive SD greater with GEq and decreased by 2 additive SD less with GC. Genotyped animals were biased upward with GEq and downward with GC. The biases and differences in EBV could be controlled by adding a constant to GC; they were eliminated with a constant of 0.014, which corresponds to AvgOff in A(22). Unbiased evaluation in the ssGBLUP may be obtained with GC scaled to be compatible with A(22). The reduction of SNP with small MAF has a small effect on the real accuracy, but it may falsely increase the estimated accuracies by inversion.

Genome-wide marker-assisted selection combining all pedigree phenotypic information with genotypic data in one step: An example using broiler chickens.

Data of broiler chickens for 2 pure lines across 3 generations were used for genomic evaluation. A complete population (full data set; FDS) consisted of 183,784 and 164,246 broilers for the 2 lines. The genotyped subsets (SUB) consisted of 3,284 and 3,098 broilers with 57,636 SNP. Genotyped animals were preselected based on more than 20 traits with different index applied to each line. Three traits were analyzed: BW at 6 wk (BW6), ultrasound measurement of breast meat (BM), and leg score (LS) coded 1 = no and 2 = yes for leg defect. Some phenotypes were missing for BM. The training population consisted of the first 2 generations including all animals in FDS or only genotyped animals in SUB. The validation data set contained only genotyped animals in the third generation. Genetic evaluations were performed using 3 approaches: 1) phenotypic BLUP, 2) extending BLUP methodologies to utilize pedigree and genomic information in a single step (ssGBLUP), and 3) Bayes A. Whereas BLUP and ssGBLUP utilized all phenotypic data, Bayes A could use only those of the genotyped subset. Heritabilities were 0.17 to 0.20 for BW6, 0.30 to 0.35 for BM, and 0.09 to 0.11 for LS. The average accuracies of the validation population with BLUP for BW6, BM, and LS were 0.46, 0.30, and <0 with SUB and 0.51, 0.34, and 0.28 with FDS. With ssGBLUP, those accuracies were 0.60, 0.34, and 0.06 with SUB and 0.61, 0.40, and 0.37 with FDS, respectively. With Bayes A, the accuracies were 0.60, 0.36, and 0.09 with SUB. With SUB, Bayes A and ssGBLUP had similar accuracies. For traits of high heritability, the accuracy of Bayes A/SUB and ssGBLUP/FDS were similar, and up to 50% better than BLUP/FDS. However, with low heritability, ssGBLUP/FDS was 4 to 6 times more accurate than Bayes A/SUB and 50% better than BLUP/FDS. An optimal genomic evaluation would be multi-trait and involve all traits and records on which selection is based.

Precision genetics for complex objectives in animal agriculture.

Indirect modification of animal genomes by interspecific hybridization, cross-breeding, and selection has produced an enormous spectrum of phenotypic diversity over more than 10,000 yr of animal domestication. Using these established technologies, the farming community has successfully increased the yield and efficiency of production in most agricultural species while utilizing land resources that are often unsuitable for other agricultural purposes. Moving forward, animal well-being and agricultural sustainability are moral and economic priorities of consumers and producers alike. Therefore, these considerations will be included in any strategy designed to meet the challenges produced by global climate change and an expanding world population. Improvements in the efficiency and precision of genetic technologies will enable a timely response to meet the multifaceted food requirements of a rapidly increasing world population.

Bowman-Birk inhibitor affects pathways associated with energy metabolism in Drosophila melanogaster.

Bowman-Birk inhibitor (BBI) is toxic when fed to certain insects, including the fruit fly, Drosophila melanogaster. Dietary BBI has been demonstrated to slow growth and increase insect mortality by inhibiting the digestive enzymes trypsin and chymotrypsin, resulting in a reduced supply of amino acids. In mammals, BBI influences cellular energy metabolism. Therefore, we tested the hypothesis that dietary BBI affects energy-associated pathways in the D. melanogaster midgut. Through microarray and metabolomic analyses, we show that dietary BBI affects energy utilization pathways in the midgut cells of D. melanogaster. In addition, ultrastructure studies indicate that microvilli are significantly shortened in BBI-fed larvae. These data provide further insights into the complex cellular response of insects to dietary protease inhibitors.

Transcriptional signatures in response to wheat germ agglutinin and starvation in Drosophila melanogaster larval midgut.

One function of plant lectins such as wheat germ agglutinin is to serve as defences against herbivorous insects. The midgut is one critical site affected by dietary lectins. We observed marked cellular, structural and gene expression changes in the midguts of Drosophila melanogaster third instar larvae that were fed wheat germ agglutinin. Some of these changes were similar to those observed in the midguts of starved D. melanogaster. Dietary wheat germ agglutinin caused shortening, branching, swelling, distortion and in some cases disintegration of the midgut microvilli. Starvation was accompanied primarily by shortening of the microvilli. Microarray analyses revealed that dietary wheat germ agglutinin evoked differential expression of 61 transcripts; seven of these were also differentially expressed in starved D. melanogaster. The differentially transcribed gene clusters in wheat germ agglutinin-fed larvae were associated with (1) cytoskeleton organization; (2) digestive enzymes; (3) detoxification reactions; and (4) energy metabolism. Four possible transcription factor binding motifs were associated with the differentially expressed genes. One of these exhibited substantial similarity to MyoD, a transcription factor binding motif associated with cellular structures in mammals. These results are consistent with the hypothesis that wheat germ agglutinin caused a starvation-like effect and structural changes of midgut cells of D. melanogaster third-instar larvae.

A mixture model approach for the analysis of small exploratory microarray experiments.

The microarray is an important and powerful tool for prescreening of genes for further research. However, alternative solutions are needed to increase power in small microarray experiments. Use of traditional parametric and even non-parametric tests for such small experiments lack power and have distributional problems. A mixture model is described that is performed directly on expression differences assuming that genes in alternative treatments are expressed or not in all combinations (i) not expressed in either condition, (ii) expressed only under the first condition, (iii) expressed only under the second condition, and (iv) expressed under both conditions, giving rise to 4 possible clusters with two treatments. The approach is termed a Mean-Difference-Mixture-Model (MD-MM) method. Accuracy and power of the MD-MM was compared to other commonly used methods, using both simulations, microarray data, and quantitative real time PCR (qRT-PCR). The MD-MM was found to be generally superior to other methods in most situations. The advantage was greatest in situations where there were few replicates, poor signal to noise ratios, or non-homogenous variances.

Comparison of genomic and traditional BLUP-estimated breeding value accuracy and selection response under alternative trait and genomic parameters.

Accuracy of prediction of estimated breeding values based on genome-wide markers (GEBV) and selection based on GEBV as compared with traditional Best Linear Unbiased Prediction (BLUP) was examined for a number of alternatives, including low heritability, number of generations of training, marker density, initial distributions, and effective population size (Ne). Results show that the more the generations of data in which both genotypes and phenotypes were collected, termed training generations (TG), the better the accuracy and persistency of accuracy based on GEBV. GEBV excelled for traits of low heritability regardless of initial equilibrium conditions, as opposed to traditional marker-assisted selection, which is not useful for traits of low heritability. Effective population size is critical for populations starting in Hardy-Weinberg equilibrium but not for populations started from mutation-drift equilibrium. In comparison with traditional BLUP, GEBV can exceed the accuracy of BLUP provided enough TG are included. Unfortunately selection rapidly reduces the accuracy of GEBV. In all cases examined, classic BLUP selection exceeds what was possible for GEBV selection. Even still, GEBV could have an advantage over traditional BLUP in cases such as sex-limited traits, traits that are expensive to measure, or can only be measured on relatives. A combined approach, utilizing a mixed model with a second random effect to account for quantitative trait loci in linkage equilibrium (the polygenic effect) was suggested as a way to capitalize on both methodologies.

Changes in Drosophila melanogaster midgut proteins in response to dietary Bowman-Birk inhibitor.

The midgut proteome of Drosophila melanogaster was compared in larvae fed dietary Bowman-Birk inhibitor (BBI) vs. larvae fed a control diet. By using two-dimensional gel electrophoresis, nine differentially expressed proteins were observed, which were associated with enzymes or transport functions such as sterol carrier protein X (SCPX), ubiquitin-conjugating enzyme, endopeptidase, receptor signalling protein kinase, ATP-dependent RNA helicase and alpha-tocopherol transport. Quantitative real-time PCR verified differential expression of transcripts coding for six of the proteins observed from the proteomic analysis. BBI evidently affects expression of proteins associated with protein degradation, transport and fatty acid catabolism. We then tested the hypothesis that SCPX was critical for the Drosophila third instars' response to BBI treatment. Inhibition of SCPX caused the third instars to become more susceptible to dietary BBI.

Evidence for widespread epistatic interactions influencing Marek's disease virus viremia levels in chicken.

Marek's disease (MD), a T cell lymphoma induced by the Marek's disease virus (MDV), is the main chronic infectious disease concern threatening the poultry industry. Enhancing genetic resistance to MD in commercial poultry is an attractive method to augment MD vaccines, which is currently the control method of choice. In order to implement this control strategy through marker-assisted selection (MAS), it is necessary to identify quantitative trait loci (QTL) or genes that influence MD incidence. Previous studies have demonstrated that it is possible to identify QTL that confer MD resistance in both experimental and commercial chickens. With the advent of the chicken genome sequence and new genomic tools, and evidence that interactions are important in understanding complex traits, the line 6 x 7 F(2) experimental resource population was re-evaluated with finer resolution for epistatic interactions. The F(2) population, consisting of 272 individuals and previously genotyped with 133 genetic markers, was combined along with 576 additional single nucleotide polymorphisms (SNPs) genotyped on 80 individuals in each of the distribution tails for MD and other associated traits, and tested for the presence of main effects and two-way epistatic interactions accounting for MD incidence, viremia titers, and length of survival. Main effects were generally not significant but a large number of highly significant interactions, involving loci located throughout the genome, were identified that account for MDV viremia titers in infected birds. These results suggest that resistance to MD is highly complex and will require the incorporation of epistatic interaction analyses and functional genomic approaches to reveal the underlying genetic basis.

Genetic variation at the tumour virus B locus in commercial and laboratory chicken populations assessed by a medium-throughput or a high-throughput assay.

The tumour virus B (TVB) locus encodes cellular receptors mediating infection by three subgroups of avian leukosis virus (B, D, and E). Three major alleles, TVB*S1, TVB*S3, and TVB*R, have been described. TVB*S1 encodes a cellular receptor mediating infection of subgroups B, D, and E. TVB*S3 encodes the receptor for two subgroups, B and D, and TVB*R encodes a dysfunctional receptor that does not permit infection by any of the subgroups, B, D, or E. Genetic diversity at the TVB locus of chickens was investigated in both layer and broiler commercial pure lines and laboratory lines. Genotyping assays were developed for both medium-throughput and high-throughput analysis. Of the 36 broiler lines sampled, 14 were fixed for the susceptible allele TVB*S1. Across all broiler lines, 83% of chickens were typed as TVB*S1/*S1, 3% as TVB*R/*R, and 14% as TVB*S1/*R. In the egg-layer lines, five of the 16 tested were fixed for TVB*S1/*S1. About 44% of egg-layers were typed as TVB*S1/*S1, 15% as TVB*R/*R, with the rest segregating for two or three of the alleles. In the laboratory chickens, 60% were fixed for TVB*S1/*S1, 6% for TVB*S3/*S3, 14% for TVB*R/*R, and the rest were heterozygotes (TVB*S1/*S3 or TVB*S1/*R). All commercial pure lines examined in this study carry the TVB*S1 allele that sustains the susceptibility to avian leukosis viruses B, D, and E. More importantly, the TVB*R allele was identified in multiple populations, thus upholding the opportunities for genetic improvement through selection.

Genome-wide analysis of phenobarbital-inducible genes in Drosophila melanogaster.

An oligoarray analysis was conducted to determine the differential expression of genes due to phenobarbital exposure in Drosophila melanogaster (w(1118) strain) third instar larvae. Seventeen genes were observed to be induced with increased expression by a statistical analysis of microarrays approach with a q < or = 0.05. At q < or = 0.12, four more genes (Cyp12d1, DmGstd4, and two genes with unknown function) were found to be up-regulated, and 11 genes with unknown function were found to be down-regulated. Fifteen of these genes, Cyp4d14, Cyp6a2, Cyp6a8, Cyp12d1, Cyp6d5, Cyp6w1, CG2065, DmGstd6, DmGstd7, Amy-p/Amy-d, Ugt86Dd, GC5724, Jheh1, Jheh2 and CG11893, were verified using quantitative real time polymerase chain reaction. Some of these genes have been shown to be over-transcribed in metabolically DDT-resistant Drosophila strains.

Application of One Sided t-tests and a Generalized Experiment Wise Error Rate to High-Density Oligonucleotide Microarray Experiments: An Example Using Arabidopsis.

MOTIVATION: A formidable challenge in the analysis of microarray data is the identification of those genes that exhibit differential expression. The objectives of this research were to examine the utility of simple ANOVA, one sided t tests, natural log transformation, and a generalized experiment wise error rate methodology for analysis of such experiments. As a test case, we analyzed a Affymetrix GeneChip microarray experiment designed to test for the effect of a CHD3 chromatin remodeling factor, PICKLE, and an inhibitor of the plant hormone gibberellin (GA), on the expression of 8256 Arabidopsis thaliana genes. RESULTS: The GFWER(k) is defined as the probability of rejecting k or more true null hypothesis at a given p level. Computing probabilities by GFWER(k) was shown to be simple to apply and, depending on the value of k, can greatly increase power. A k value as small as 2 or 3 was concluded to be adequate for large or small experiments respectively. A one sided t-test along with GFWER(2)=.05 identified 43 genes as exhibiting PICKLE-dependent expression. Expression of all 43 genes was re-examined by qRT-PCR, of which 36 (83.7%) were confirmed to exhibit PICKLE-dependent expression.

Chronic social stress differentially regulates neuroendocrine responses in laying hens: II. Genetic basis of adrenal responses under three different social conditions.

Chicken lines were divergently selected for both high (HGPS) or low (LGPS) group productivity and survivability resulting from cannibalism and flightiness in colony cages. Each line has unique characteristics in physical indexes, domestic behavior, and physiological responsiveness to stress. The differences between the selected lines could be reflected in differing regulation of the neuroendocrine system such as the hypothalamic-pituitary-adrenal axis. Change of the adrenal function is a key initial event in response to stress in animals, which differs for this trait. Comparisons between the selected lines showed that adrenal function was stable in HGPS hens but not in LGPS hens in response to chronic social stress. Social stress-induced adrenal hypertrophy and its positive correlation with plasma corticosterone concentrations were found in the LGPS hens but not in the HGPS hens. The data demonstrated that chickens selected for variations in productivity and survivability variously altered the adrenal system in response to social stressors. The results suggest that these chicken lines could be valuable animal models for biomedical investigation of the effect of genetic-environmental interactions on the neuroendocrine function in controlling stress responses.

Social stress differentially regulates neuroendocrine responses in laying hens: I. Genetic basis of dopamine responses under three different social conditions.

Effects of genetic-environmental interactions on plasma dopamine (DA) concentrations were studied in White Leghorn chickens selected for both high (HGPS) or low (LGPS) group productivity and survivability resulting from cannibalism and flightiness. Plasma DA levels were measured from chickens in three social treatments: single-, two-, or ten-hen cages. The two-hen treatment consisted of paired chickens from three genetic lines: HGPS, LGPS and a commercial strain, Dekalb XL (DXL). In HGPS/DXL and LGPS/DXL pairs, the DXL hen was used as a standardized genetic competitor. The ten-hen treatment contained only hens from the same line, which is similar to the original selection condition. After 7 weeks housing in the social environments, LGPS hens in the ten-hen treatment had greater plasma DA concentrations than HGPS hens (P<0.05). Compared to levels in the ten-hen treatment from the same line, plasma DA concentrations in both HGPS and LGPS hens were significantly lower in the two-hen treatment (average mean, 0.09 vs. 0.15 ng/ml and 0.22 vs. 0.44 ng/ml, P<0.05, respectively), but significantly higher in the single-hen treatment (average mean, 0.44 vs. 0.15 ng/ml and 1.78 vs. 0.44 ng/ml, P<0.05 and P<0.01, respectively). In the single-hen treatment, LGPS hens had greater plasma DA levels than HGPS hens (P<0.05). The results provide evidence of genetically related differences in the regulation of chickens' plasma DA concentrations in response to social stress. These differences may magnify the behavioral and physiological differences observed in the lines under basal and challenged conditions. These results suggest that these chicken lines may provide a new model for investigating effects of DA on the control of behavioral, neural and endocrine responses to stress.

Social stress in laying hens: differential effect of stress on plasma dopamine concentrations and adrenal function in genetically selected chickens.

Genetic selection for high or low group productivity and survivability (HGPS, LGPS) has created two phenotypically distinct chicken lines. Each line has unique characteristics in behavioral and physiological adaptability to multiple-bird cage system. The present study was designed to examine whether these differences reflect genetic variation in the control of plasma dopamine (DA) concentrations and adrenal function in response to social stress. Chickens from the HGPS and LGPS lines were randomly assigned to single- or 10-bird cages at 17 wk of age. The 10-bird cages were the same as those used in the development of the two lines. Differences in regulation of DA concentrations and adrenal function in response to different social environments were measured between the two lines when the study was conducted at 24 wk of age. In the 10-bird cages, the HGPS line had lower levels of DA (P < 0.05) and heavier adrenal glands (AG, P < 0.05) than those of the LGPS line, but concentrations of corticosterone (CORT) from the two lines were not significantly different. In the single-bird cages, DA levels in both lines were greater than in that of their siblings in the 10-bird cages, but a greater increase was found in the LGPS line (P < 0.01 and P < 0.05, 405% vs. 293%). Likewise, both lines had lower concentrations of CORT (P < 0.05) in the single- vs. 10-bird cages, but the AG were less heavy in the LGPS line but not in HGPS line in the single-bird cages (P < 0.05). The results indicated that the two strains reacted differently in terms of their stress hormone levels in the two different environments. These differences could contribute to the behavioral and physiological differences existing between the two lines.

Social stress in laying hens: differential dopamine and corticosterone responses after intermingling different genetic strains of chickens.

White Leghorn chickens were genetically selected for high (HGPS) or low (LGPS) group productivity and survivability. The selection resulted in two genetic lines with marked opposite changes in cannibalism and flightiness when housed in multiple-colony battery cages without beak trimming. The objective of the study was to examine whether the genetic selection differentially affected the neuroendocrine system of chickens from different strains in response to social stress. Based on the previous studies, social stress was induced by randomly pairing 17-wk-old hens from three genetic lines, i.e., HGPS, LGPS, and Dekalb XL (DXL), to form three mixed-line combinations. At 24 wk of age, the concentrations of plasma dopamine (DA) and corticosterone (CORT) showed no differences in DXL hens housed with HGPS or LGPS hens (P > 0.05). However, different regulations of DA and adrenal function were found between HGPS and LGPS hens when paired with DXL hens. Compared to HGPS hens, LGPS hens had greater levels of DA and CORT (P < 0.01 and P < 0.05, respectively). In addition, under the HGPS-LGPS social treatment, the concentrations of DA but not CORT were greater in LGPS hens than in HGPS hens (P < 0.05 and P > 0.05, respectively). The results indicated genetic selection for production and survivability differentially altered DA and CORT systems in response to social stress. The data suggested, compared to LGPS hens, HGPS hens had a better coping capability to social stress, which might have been responsible for their higher productivity and survivability.

Fitness components and ecological risk of transgenic release: a model using Japanese medaka (Oryzias latipes).

Any release of transgenic organisms into nature is a concern because ecological relationships between genetically engineered organisms and other organisms (including their wild-type conspecifics) are unknown. To address this concern, we developed a method to evaluate risk in which we input estimates of fitness parameters from a founder population into a recurrence model to predict changes in transgene frequency after a simulated transgenic release. With this method, we grouped various aspects of an organism's life cycle into six net fitness components: juvenile viability, adult viability, age at sexual maturity, female fecundity, male fertility, and mating advantage. We estimated these components for wild-type and transgenic individuals using the fish, Japanese medaka (Oryzias latipes). We generalized our model's predictions using various combinations of fitness component values in addition to our experimentally derived estimates. Our model predicted that, for a wide range of parameter values, transgenes could spread in populations despite high juvenile viability costs if transgenes also have sufficiently high positive effects on other fitness components. Sensitivity analyses indicated that transgene effects on age at sexual maturity should have the greatest impact on transgene frequency, followed by juvenile viability, mating advantage, female fecundity, and male fertility, with changes in adult viability, resulting in the least impact.