scholarly journals Prediction of Genetic Contributions and Generation Intervals in Populations With Overlapping Generations Under Selection

Genetics ◽  
1999 ◽  
Vol 151 (3) ◽  
pp. 1197-1210 ◽  
Author(s):  
Piter Bijma ◽  
John A Woolliams
Keyword(s):  
Gene Flow ◽  
Overlapping Generations ◽  
Selective Advantage ◽  
Turnover Time ◽  
Breeding Value ◽  
Age Classes ◽  
Generation Interval ◽  
Young Parents ◽  
Genetic Contributions

Abstract A method to predict long-term genetic contributions of ancestors to future generations is studied in detail for a population with overlapping generations under mass or sib index selection. An existing method provides insight into the mechanisms determining the flow of genes through selected populations, and takes account of selection by modeling the long-term genetic contribution as a linear regression on breeding value. Total genetic contributions of age classes are modeled using a modified gene flow approach and long-term predictions are obtained assuming equilibrium genetic parameters. Generation interval was defined as the time in which genetic contributions sum to unity, which is equal to the turnover time of genes. Accurate predictions of long-term genetic contributions of individual animals, as well as total contributions of age classes were obtained. Due to selection, offspring of young parents had an above-average breeding value. Long-term genetic contributions of youngest age classes were therefore higher than expected from the age class distribution of parents, and generation interval was shorter than the average age of parents at birth of their offspring. Due to an increased selective advantage of offspring of young parents, generation interval decreased with increasing heritability and selection intensity. The method was compared to conventional gene flow and showed more accurate predictions of long-term genetic contributions.

scholarly journals Expected Genetic Contributions and Their Impact on Gene Flow and Genetic Gain

Genetics ◽  
1999 ◽  
Vol 153 (2) ◽  
pp. 1009-1020 ◽  
Author(s):  
J A Woolliams ◽  
P Bijma ◽  
B Villanueva
Keyword(s):  
Gene Flow ◽  
Genetic Gain ◽  
Overlapping Generations ◽  
Predictive Accuracy ◽  
Index Theory ◽  
Previous Theory ◽  
Selection Indices ◽  
Breeding Groups ◽  
Genetic Contributions

Abstract Long-term genetic contributions (ri) measure lasting gene flow from an individual i. By accounting for linkage disequilibrium generated by selection both within and between breeding groups (categories), assuming the infinitesimal model, a general formula was derived for the expected contribution of ancestor i in category q (μi(q)), given its selective advantages (si(q)). Results were applied to overlapping generations and to a variety of modes of inheritance and selection indices. Genetic gain was related to the covariance between ri and the Mendelian sampling deviation (ai), thereby linking gain to pedigree development. When si(q) includes ai, gain was related to E[μi(q)ai], decomposing it into components attributable to within and between families, within each category, for each element of si(q). The formula for μi(q) was consistent with previous index theory for predicting gain in discrete generations. For overlapping generations, accurate predictions of gene flow were obtained among and within categories in contrast to previous theory that gave qualitative errors among categories and no predictions within. The generation interval was defined as the period for which μi(q), summed over all ancestors born in that period, equaled 1. Predictive accuracy was supported by simulation results for gain and contributions with sib-indices, BLUP selection, and selection with imprinted variation.

Genetic contributions of Finnish Ayrshire bulls over four generations

1995 ◽  
Vol 61 (2) ◽  
pp. 177-187 ◽  
Author(s):  
J. A. Woolliams ◽  
E. A. Mäntysaari
Keyword(s):  
Gene Flow ◽  
Genetic Relationship ◽  
Artificial Insemination ◽  
Pedigree Information ◽  
Generation Interval ◽  
New Information ◽  
Genetic Contributions ◽  
Additive Genetic Relationship

AbstractThe long-term genetic contributions were calculated for 219 Finnish Ayrshire bulls born between 1958 and 1964 to 707 Finnish Ayrshire bulls made available for artificial insemination and born between 1986 and 1988. Three strategies were employed:(i) using all known pedigree information; (ii) ignoring information on the dam of females; (iii) only using information on sires. Expected contributions were calculated using gene flow matrices.The contributions from strategies 1, 2 and 3 were only 0.6 (1 and 2) or 0.7 (strategy 3) of those expected. The causes of this shortfall for strategies 2 and 3 were identified as (i) the use of an imported sire and (ii) generation skipping. For strategy 1, 0.2 of the expected pathways remained unaccounted for and were ascribed to missing pedigree information.Of the 219 ancestors, only 86 made positive contributions to the descendants. Only 10 ancestors made contributions more than the average, and one bull accounted for 0.3 of all pathways traced on strategy 2. There was general agreement in the relative contributions of individual bulls when assessed using the three strategies.The rate of inbreeding (ΔF) estimated by regression from 1974 to 1988 and using known pedigrees was 0.0018 per year and the average coefficients of additive genetic relationship among cohorts was increasing by 0.0030 per year. AF was estimated using the contributions calculated by strategies 1, 2 and 3 to be 0.0147, 0.0151 and 0.0125 per generation respectively. These were converted into rates per year by assuming a generation interval of 6.5 years taken from both published and new information on generation intervals in the Finnish Ayrshire population. This gave annual rates of 0.0023, 0.0023 and 0.0019. The estimates from strategy 3 were obtained without the use of any pedigree information pertaining to dams.

scholarly journals Predicting Rates of Inbreeding in Populations Undergoing Selection

Genetics ◽  
2000 ◽  
Vol 154 (4) ◽  
pp. 1851-1864 ◽  
Author(s):  
John A Woolliams ◽  
Piter Bijma
Keyword(s):  
Overlapping Generations ◽  
Linear Models ◽  
Selection Process ◽  
Correction Term ◽  
Random Mating ◽  
Nonrandom Mating ◽  
Selection Processes ◽  
Genetic Contributions ◽  
The Relationship

AbstractTractable forms of predicting rates of inbreeding (ΔF) in selected populations with general indices, nonrandom mating, and overlapping generations were developed, with the principal results assuming a period of equilibrium in the selection process. An existing theorem concerning the relationship between squared long-term genetic contributions and rates of inbreeding was extended to nonrandom mating and to overlapping generations. ΔF was shown to be ~¼(1 − ω) times the expected sum of squared lifetime contributions, where ω is the deviation from Hardy-Weinberg proportions. This relationship cannot be used for prediction since it is based upon observed quantities. Therefore, the relationship was further developed to express ΔF in terms of expected long-term contributions that are conditional on a set of selective advantages that relate the selection processes in two consecutive generations and are predictable quantities. With random mating, if selected family sizes are assumed to be independent Poisson variables then the expected long-term contribution could be substituted for the observed, providing ¼ (since ω = 0) was increased to ½. Established theory was used to provide a correction term to account for deviations from the Poisson assumptions. The equations were successfully applied, using simple linear models, to the problem of predicting ΔF with sib indices in discrete generations since previously published solutions had proved complex.

scholarly journals Selective advantage of implementing optimal contributions selection and timescales for the convergence of long-term genetic contributions

2018 ◽  
Vol 50 (1) ◽  
Author(s):  
David M. Howard ◽  
Ricardo Pong-Wong ◽  
Pieter W. Knap ◽  
Valentin D. Kremer ◽  
John A. Woolliams
Keyword(s):  
Selective Advantage ◽  
Genetic Contributions

scholarly journals Climate induced wolf prey selection in Yellowstone National Park, 1995-2015

2016 ◽  
Author(s):  
Douglas W Smith ◽  
Matthew Metz ◽  
Chris Wilmers ◽  
Daniel Stahler ◽  
Chris Geremia
Keyword(s):  
Yellowstone National Park ◽  
National Park ◽  
Prey Selection ◽  
Selective Advantage ◽  
Late Winter ◽  
Age Classes ◽  
Predator Prey ◽  
Wolf Predation ◽  
Management Objectives

Prey selection by wolves has been a fundamental and long-term topic of interest for wolf-prey studies. Virtually all studies conclude the selectivity of wolf predation and typically identify what made an individual vulnerable. Vulnerability, however, varies for multiple reasons and emerging research is discovering climate induced effects on prey forage altering condition and selective advantage of migration. We present data from a twenty year study of wolf-elk predation in Yellowstone National Park (YNP) which found bull elk killed more frequently in early winter after years with less snowfall compared to years with normal snowfall. Snowfall impacted summer forage, which impacted bull elk condition going into the autumn rut, which weakened elk prematurely post-rut causing them to be selected by wolves in early rather than late winter, and possibly caused more bulls to be killed overall. Bull elk ratios have declined over the last 20 years (from 40-60 to 10-15 bulls/100 cows; lower outside YNP), which has led to calls for a reduced human harvest on bulls which has been met with significant resistance. Understanding the interaction between climate, forage and wolf predation on bull elk (and other sex/age classes) will help guide management decisions and potentially sustain hunting of bulls in the long term as well as protect natural management objectives within YNP. Results will be of widespread value as they may suggest changing predator-prey dynamics across North America by making some otherwise healthy prey vulnerable to predation.

scholarly journals New cycle, same old mistakes? Overlapping vs. discrete generations in long-term recurrent selection

2021 ◽  
Author(s):  
Marlee R. Labroo ◽  
Jessica E. Rutkoski
Keyword(s):  
Genetic Gain ◽  
Overlapping Generations ◽  
Recurrent Selection ◽  
Phenotypic Selection ◽  
Breeding Value ◽  
Breeding Values ◽  
Truncation Selection ◽  
Breeding Cycles ◽  
Error Bias

Background: Recurrent selection is a foundational breeding method for quantitative trait improvement. It typically features rapid breeding cycles that can lead to high rates of genetic gain. In recurrent phenotypic selection, generations do not overlap, which means that breeding candidates are evaluated and considered for selection for only one cycle. With recurrent genomic selection, candidates can be evaluated based on genomic estimated breeding values indefinitely, therefore facilitating overlapping generations. Candidates with true high breeding values that were discarded in one cycle due to underestimation of breeding value could be identified and selected in subsequent cycles. The consequences of allowing generations to overlap in recurrent selection are unknown. We assessed whether maintaining overlapping and discrete generations led to differences in genetic gain for phenotypic, genomic truncation, and genomic optimum contribution recurrent selection by simulation of traits with various heritabilities and genetic architectures across fifty breeding cycles. We also assessed differences of overlapping and discrete generations in a conventional breeding scheme with multiple stages and cohorts. Results: With phenotypic selection, overlapping generations led to decreased genetic gain compared to discrete generations due to increased selection error bias. Selected individuals, which were in the upper tail of the distribution of phenotypic values, tended to also have high absolute error relative to their true breeding value compared to the overall population. Without repeated phenotyping, these erroneously outlying individuals were repeatedly selected across cycles, leading to decreased genetic gain. With genomic truncation selection, overlapping and discrete generations performed similarly as updating breeding values precluded repeatedly selecting individuals with inaccurately high estimates of breeding values in subsequent cycles. Overlapping generations did not outperform discrete generations in the presence of a positive genetic trend with genomic truncation selection, as past generations had lower mean genetic values than the current generation of selection candidates. With genomic optimum contribution selection, overlapping and discrete generations performed similarly, but overlapping generations slightly outperformed discrete generations in the long term if the targeted inbreeding rate was extremely low. Conclusions: Maintaining discrete generations in recurrent phenotypic mass selection leads to increased genetic gain, especially at low heritabilities, by preventing selection error bias. With genomic truncation selection and genomic optimum contribution selection, genetic gain does not differ between discrete and overlapping generations assuming non-genetic effects are not present. Overlapping generations may increase genetic gain in the long term with very low targeted rates of inbreeding in genomic optimum contribution selection.

scholarly journals A General Procedure for Predicting Rates of Inbreeding in Populations Undergoing Mass Selection

Genetics ◽  
2000 ◽  
Vol 154 (4) ◽  
pp. 1865-1877 ◽  
Author(s):  
Piter Bijma ◽  
Johan A M Van Arendonk ◽  
John A Woolliams
Keyword(s):  
Overlapping Generations ◽  
General Procedure ◽  
Prediction Method ◽  
Selective Advantage ◽  
Reproductive Age ◽  
Mass Selection ◽  
Older Individuals ◽  
Age Classes ◽  
Selection Intensities ◽  
Relative Errors

Abstract Predictions of rates of inbreeding (ΔF), based on the concept of long-term genetic contributions assuming the infinitesimal model, are developed for populations with discrete or overlapping generations undergoing mass selection. Phenotypes of individuals are assumed to be recorded prior to reproductive age and to remain constant over time. The prediction method accounts for inheritance of selective advantage both within and between age classes and for changing selection intensities with age. Terms corresponding to previous methods that assume constant selection intensity with age are identified. Predictions are accurate (relative errors ≤8%), except for cases with extreme selection intensities in females in combination with high heritability. With overlapping generations ΔF reaches a maximum when parents are equally distributed over age classes, which is mainly due to selection of the same individuals in consecutive years. ΔF/year decreases much more slowly compared to ΔF/generation as the number of younger individuals increases, whereas the decrease is more similar as the number of older individuals increases. The minimum ΔF (per year or per generation) is obtained when most parents were in the later age classes, which is mainly due to an increased number of parents per generation. With overlapping generations, the relationship between heritability and ΔF is dependent on the age structure of the population.

scholarly journals Climate induced wolf prey selection in Yellowstone National Park, 1995-2015

2016 ◽  
Author(s):  
Douglas W Smith ◽  
Matthew Metz ◽  
Chris Wilmers ◽  
Daniel Stahler ◽  
Chris Geremia
Keyword(s):  
Yellowstone National Park ◽  
National Park ◽  
Prey Selection ◽  
Selective Advantage ◽  
Late Winter ◽  
Age Classes ◽  
Predator Prey ◽  
Wolf Predation ◽  
Management Objectives

Prey selection by wolves has been a fundamental and long-term topic of interest for wolf-prey studies. Virtually all studies conclude the selectivity of wolf predation and typically identify what made an individual vulnerable. Vulnerability, however, varies for multiple reasons and emerging research is discovering climate induced effects on prey forage altering condition and selective advantage of migration. We present data from a twenty year study of wolf-elk predation in Yellowstone National Park (YNP) which found bull elk killed more frequently in early winter after years with less snowfall compared to years with normal snowfall. Snowfall impacted summer forage, which impacted bull elk condition going into the autumn rut, which weakened elk prematurely post-rut causing them to be selected by wolves in early rather than late winter, and possibly caused more bulls to be killed overall. Bull elk ratios have declined over the last 20 years (from 40-60 to 10-15 bulls/100 cows; lower outside YNP), which has led to calls for a reduced human harvest on bulls which has been met with significant resistance. Understanding the interaction between climate, forage and wolf predation on bull elk (and other sex/age classes) will help guide management decisions and potentially sustain hunting of bulls in the long term as well as protect natural management objectives within YNP. Results will be of widespread value as they may suggest changing predator-prey dynamics across North America by making some otherwise healthy prey vulnerable to predation.

Anthropologic Relationships among Prehistoric Northeastern Amerindians

1980 ◽  
Vol 1 (2) ◽  
pp. 145-159
Author(s):  
Edward F. Harris ◽  
Nicholas F. Bellantoni
Keyword(s):  
New York ◽  
Gene Flow ◽  
Material Culture ◽  
New England ◽  
Cultural Barriers ◽  
Group Differences ◽  
Phenetic Analysis ◽  
Trade Relationships ◽  
Good Agreement

Archaeologically defined inter-group differences in the Northeast subarea ate assessed with a phenetic analysis of published craniometric information. Spatial distinctions in the material culture are in good agreement with those defined by the cranial metrics. The fundamental dichotomy, between the Ontario Iroquois and the eastern grouping of New York and New England, suggests a long-term dissociation between these two groups relative to their ecologic adaptations, trade relationships, trait-list associations, and natural and cultural barriers to gene flow.

Population fragmentation causes inadequate gene flow and increases extinction risk

2017 ◽  
Author(s):  
Richard Frankham ◽  
Jonathan D. Ballou ◽  
Katherine Ralls ◽  
Mark D. B. Eldridge ◽  
Michele R. Dudash ◽  
...  
Keyword(s):  
Gene Flow ◽  
Extinction Risk ◽  
Random Mating ◽  
Large Population ◽  
Isolated Population ◽  
Population Fragmentation ◽  
Single Population ◽  
Total Size ◽  
Limited Gene Flow

Most species now have fragmented distributions, often with adverse genetic consequences. The genetic impacts of population fragmentation depend critically upon gene flow among fragments and their effective sizes. Fragmentation with cessation of gene flow is highly harmful in the long term, leading to greater inbreeding, increased loss of genetic diversity, decreased likelihood of evolutionary adaptation and elevated extinction risk, when compared to a single population of the same total size. The consequences of fragmentation with limited gene flow typically lie between those for a large population with random mating and isolated population fragments with no gene flow.

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