Quantitative genetic basis of floral design in a natural plant population

AbstractThe amount of genetic variation of floral traits and the degree to which they are genetically correlated are important parameters for the study of plant evolution. Estimates of these parameters can reveal the effect of historical selection relative to neutral processes such as mutation and drift, and allow us to predict the short-term evolutionary trajectory of a population under various selective regimes. Here, we assess the heritability and genetic correlation of the floral design of a native N. American tetraploid plant, Silene stellata (Caryophyllaceae), in a natural population. Specifically, we use a linear mixed model to estimate the genetic parameters based on a genealogy reconstructed from highly variable molecular markers. Overall, we found significant heritabilities in five out of nine studied traits. The level of heritability was intermediate (0.027 – 0.441). Interestingly, the floral trait showing the highest level of genetic variation was previously shown to be under strong sexually conflicting selection, which may serve as a mechanism for maintaining the observed genetic variation. Additionally, we also found prevalent positive genetic correlations between floral traits. Our results suggest that S. stellata is capable of responding to phenotypic selection on its floral design, while the abundant positive genetic correlations could also constrain the evolutionary trajectories to certain directions. Furthermore, this study demonstrates the utility and feasibility of marker-based approaches for estimating genetic parameters in natural populations.

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Analysis of Genetic Parameters for Reproductive Traits in Crossbred Dairy Cattle Maintained at Holetta Agricultural Research Center.

Asian Journal of Dairy and Food Research ◽

10.18805/ajdfr.dr-146 ◽

2020 ◽

Vol 39 (01) ◽

Author(s):

Kefale Getahun ◽

Million Tadesse ◽

Direba Hundie

Keyword(s):

Dairy Cattle ◽

Genetic Parameters ◽

Mixed Model ◽

Linear Mixed Model ◽

Agricultural Research ◽

Genetic Correlations ◽

Reproductive Traits ◽

Breeding Value ◽

Research Center ◽

Phenotypic Correlation

This study was aimed to generate information on variance components and the resulting genetic parameters (heritability, repeatability, genetic and phenotypic correlations and genetic trends) of some economic traits of Borena and its crosses with Holstein Friesian dairy cattle maintained at Holetta agricultural research center dairy farm. Traits studied were age at first service (AFS), age at first calving (AFC), calving interval (CI), days open (DO) and number of service per conception (NSC). Overall, 11331 dairy cattle reproductive performance records were used for the study. WOMBAT, which is a software package for quantitative genetic analysis of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters were employed and obtained. Heritability values of reproductive traits were from very low (0.071, 0.082 and 0.012) for CI, DO and NSC to moderate (0.3 and 0.22) for AFC and AFS traits. Repeatability estimate for CI, DO and NSC were low (0.17, 0.17 and 0.129). Strong and positive genetic correlation (0.98) was appeared between AFS and AFC traits. Negative genetic correlations were observed between AFS and DO (-0.001), AFC and DO (-0.05), AFS and NSC (-0.022), AFC and NSC (-0.29) and CI and NSC (-0.31). AFS were negative phenotypic correlation with CI, DO and NSC. Similarly, AFC was negative phenotypic correlation with CI and DO. Low phenotypic correlation was observed between AFC and NSC, CI and DO, CI and NSC and, DO and NSC. Strong and positive phenotypic correlation was appeared between AFS and AFC. The regression coefficient of mean breeding value for NSC, CI, DO, AFC and AFS on year of birth were -0.0066x+13.25 times/year, -1.19x+2387.4 days/year, -1.23x+2445.6 days/year, 0.2x-410 months/year and 0.48x-980 months/year, respectively.

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Genetic Parameters and Genotype-by-Environment Interactions in Regional Progeny Tests of Pinus taeda L. in the Southern USA

Forest Science ◽

10.1093/forsci/fxaa035 ◽

2020 ◽

Author(s):

Edwin Lauer ◽

Andrew Sims ◽

Steven McKeand ◽

Fikret Isik

Keyword(s):

Genetic Variation ◽

Pinus Taeda ◽

Genetic Parameters ◽

Genetic Correlations ◽

Breeding Program ◽

Model Fit ◽

Genotype By Environment Interactions ◽

Genotype By Environment ◽

Progeny Tests ◽

Pinus Taeda L

Abstract Genetic parameters were estimated using a five-series multienvironment trial of Pinus taeda L. in the southern USA. There were 324 half-sib families planted in five test series across 37 locations. A set of six variance/covariance matrices for the genotype-by-environment (G × E) effect for tree height and diameter were compared on the basis of model fit. In single-series analysis, extended factor analytical models provided generally superior model fit to simpler models for both traits; however, in the combined-series analysis, diameter was optimally modeled using simpler variance/covariance structures. A three-way compound term for modeling G × E interactions among and within series yielded substantial improvements in terms of model fit and standard errors of predictions. Heritability of family means ranged between 0.63 and 0.90 for both height and diameter. Average additive genetic correlations among sites were 0.70 and 0.61 for height and diameter, respectively, suggesting the presence of some G × E interaction. Pairs of sites with the lowest additive genetic correlations were located at opposite ends of the latitude range. Latent factor regression revealed a small number of parents with large factor scores that changed ranks significantly between southern and northern environments. Study Implications Multienvironmental progeny tests of loblolly pine (Pinus taeda L.) were established over 10 years in the southern United States to understand the genetic variation for the traits of economic importance. There was substantial genetic variation between open-pollinated families, suggesting that family selection would be efficient in the breeding program. Genotype-by-environment interactions were negligible among sites in the deployment region but became larger between sites at the extremes of the distribution. The data from these trials are invaluable in informing the breeding program about the genetic merit of selection candidates and their potential interaction with the environment. These results can be used to guide deployment decisions in the southern USA, helping landowners match germplasm with geography to achieve optimal financial returns and conservation outcomes.

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Genetic parameters of traits at the juvenile stage of different assai palm tree progenies

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2018000700005 ◽

2018 ◽

Vol 53 (7) ◽

pp. 815-823

Author(s):

Patricia Cardoso Andrade Navegantes ◽

Maria do Socorro Padilha de Oliveira ◽

José Airton Rodrigues Nunes

Keyword(s):

Genetic Parameters ◽

Mixed Model ◽

Genetic Correlations ◽

Fruit Production ◽

Leaf Sheath ◽

Juvenile Stage ◽

Palm Tree ◽

Euterpe Oleracea ◽

Mixed Model Approach ◽

Randomized Design

Abstract: The objective of this work was to estimate genetic parameters of traits at the juvenile stage of different assai palm (Euterpe oleracea) tree progenies, as well as to select among and within the most promising for fruit production. A total of 34 half-sib and 16 full-sib progenies were evaluated in a completely randomized design with eight replicates and one plant per plot. Nine traits were measured in five harvests, and the data were analyzed using the mixed model approach. The genetic variance was significant for most of the traits. Progeny-mean heritabilities showed moderate magnitudes, ranging from 51% for number of dead leaves to 59% for leaf sheath length. In general, the genetic correlations were positive and had magnitudes varying from moderate to very high. The genetic gains were more expressive for the traits plant height, leaf sheath length, and girth circumference. The full-sib progenies P33, P37, and P42 are promising for fruit production.

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Categorical Visual Score Traits of a Nellore Beef Cattle Population

Journal of Agricultural Science ◽

10.5539/jas.v9n8p63 ◽

2017 ◽

Vol 9 (8) ◽

pp. 63

Author(s):

Jairo Azevedo Junior ◽

Juliana Petrini ◽

Gerson Barreto Mourão ◽

José Bento Sterman Ferraz

Keyword(s):

Variance Components ◽

Mixed Model ◽

Linear Mixed Model ◽

Genetic Correlations ◽

Estimation Method ◽

Analysis Data ◽

Suitable Model ◽

Linear Distribution ◽

Tropical Regions ◽

Trait Analysis

Variance components and genetic parameters of economically relevant traits in livestock, whether continuous or categorical, can be estimated by methods computationally available providing support for the selection and mating of animals in breeding programs. The objectives of this paper were to obtain and compare the variance components estimates for visual traits under continuous or categorical distribution in single-trait analysis and their correlations with continuous productive traits in two-trait analysis. Data of conformation (CONF), precocity of fat deposition (PREC) and muscling (MUSC) visual scores evaluated at 18 months of age as well as the weight at 18 months of age (YW) were collected from animals born from 2000 to 2012, in Nellore cattle herds raised in Southeastern and Central Western tropical regions of Brazil. Methods III of Henderson, Restricted Maximum Likelihood (REML), Bayesian Inference and generalized linear mixed model (GLMM) were tested. Variance components obtained from single-trait analysis were similar to those obtained from two-trait analysis. The estimates of heritability (h2) for the visual scores ranged from 0.1081 to 0.2190. Heritability estimates for traits evaluated by visual scores have moderate to high magnitude justifying the inclusion of visual scores as selection criteria in animal breeding and the selection of animals with higher scores for mating. High genetic correlations between yearling weight and morphological traits were verified. For visual scores of conformation, precocity and muscling, the most suitable model based on one-trait or two-trait analyses considered an animal model, a linear distribution of the data and the estimation method of the components of (co)variance based on Bayesian methodology.

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Genetic Analysis of Yield and Quality Traits in Switchgrass Based on Population Crosses

Agronomy ◽

10.3390/agronomy11112220 ◽

2021 ◽

Vol 11 (11) ◽

pp. 2220

Author(s):

Serge Edmé ◽

Rob Mitchell

Keyword(s):

Genetic Variation ◽

Combining Ability ◽

Dry Matter ◽

Mixed Model ◽

Linear Mixed Model ◽

Ethanol Yield ◽

Lignin Content ◽

Block Design ◽

Likelihood Method ◽

Single Pair

Obtaining greater genetic gains, particularly for biomass yield, requires a good understanding of the gene action governing the inheritance of traits with economic importance in switchgrass (Panicum virgatum L.). Individual genotypes from three different accessions were crossed in single-pair matings with reciprocals to assess the relative importance of additive to nonadditive genetic variation and the potential of using inter-ecotypic crosses to improve dry matter yield (DMY), in vitro dry matter digestibility (IVDMD), lignin content (ADL and KL), and ethanol yield (ETOH). Crosses and four reference populations were planted in a randomized complete block design with eight replications of single family-rows plots, with five-plants each and 1 m spacings. A linear mixed model was applied as per the restricted maximum likelihood method, integrated with a pedigree tracing back to the original founders of these parental populations, and augmented with the designation of four genetic groups. Variation due to SCA (specific combining ability) was predominant for all traits, contributing from 20% to 57% of the total phenotypic variation and with Baker’s ratios (GCA/SCA) varying from 0.003 to 0.67. Heritability values calculated at the fullsib-family mean level were moderate to very high. Variation due to GCA (general combining ability) was detected with a lesser significance for DMY and ETOH. A reciprocal GCA effect was present in the form of maternal inheritance for DMY, suggesting the use of the highest biomass-yielding parent as female in inter-ecotypic breeding. Selecting and deploying fullsib families, deploying clonal hybrids, and adopting an introgression breeding approach are all possibilities available to switchgrass breeders to exploit the complementary genes from this germplasm and capitalize on the non-additive genetic variation present in these crosses.

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Predictors of virus prevalence and diversity across a wild bumblebee community

10.1101/2021.01.06.425554 ◽

2021 ◽

Author(s):

David J. Pascall ◽

Matthew C. Tinsley ◽

Bethany L. Clark ◽

Darren J. Obbard ◽

Lena Wilfert

Keyword(s):

Mixed Model ◽

Linear Mixed Model ◽

Natural Populations ◽

Ecological Factors ◽

Positive Association ◽

Population Declines ◽

Fitness Effects ◽

Wild Host ◽

Generalised Linear Mixed Model ◽

Paralysis Virus

AbstractViruses are a key regulator of natural populations. Despite this, we have limited knowledge of the diversity and ecology of viruses that lack obvious fitness effects on their host. This is even the case in wild host populations that provide ecosystem services, where small fitness effects may have major ecological and financial impacts in aggregate. One such group of hosts are the bumblebees, which have a major role in the pollination of food crops and have suffered population declines and range contractions in recent decades. In this study, we used a multivariate generalised linear mixed model to investigate the ecological factors that determine the prevalence of four recently discovered bumblebee viruses (Mayfield virus 1, Mayfield virus 2, River Liunaeg virus and Loch Morlich virus), and two previously known viruses that infect both wild bumblebees and managed honeybees (Acute bee paralysis virus and Slow bee paralysis virus). We show that the recently discovered bumblebee viruses were more genetically diverse than the viruses shared with honeybees, potentially due to spillover dynamics of shared viruses. We found evidence for ecological drivers of prevalence in our samples, with relatively weak evidence for a positive effect of precipitation on the prevalence of River Luinaeg virus. Coinfection is potentially important in shaping prevalence: we found a strong positive association between River Liunaeg virus and Loch Morlich virus presence after controlling for host species, location and other relevant ecological variables. This study represents a first step in the description of predictors of bumblebee infection in the wild not driven by spillover from honeybees.

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Genetic analysis of clinical mastitis during different risk periods in Finnish Ayrshire

Agricultural and Food Science ◽

10.2137/145960607782219373 ◽

2008 ◽

Vol 16 (2) ◽

pp. 115 ◽

Cited By ~ 3

Author(s):

E. NEGUSSIE ◽

I. STRANDÉN ◽

E. MÄNTYSAARI

Keyword(s):

Genetic Variation ◽

Genetic Information ◽

Genetic Parameters ◽

Genetic Correlations ◽

Clinical Mastitis ◽

Data Sets ◽

Threshold Models ◽

Early Lactation ◽

Sire Evaluation ◽

Using Data

Clinical mastitis (CM) records from first-lactation Finnish Ayrshire were analysed by linear and threshold models to assess the effects trait definition on estimates of genetic parameters and sire evaluation. The studied CM traits were defined by dividing lactation into six lactation stages (risk periods) by days (d) after calving: CM1 (-7 to 150 d), CM2 (-30 to 30 d), CM3 (-30 to 150 d), CM4 (31 to 150 d), CM5 (150 to 300 d), CM6 (-30 to 300 d). In addition, two data sets were prepared to assess the effect of excluding (Data I) or including (Data II) records of culled cows on estimates of genetic parameters. Sire variances and heritabilities were larger using Data II. When data from longer intervals was used heritabilities of CM were slightly higher than shorter intervals indicating that longer intervals tend to obscure genetic variation between animals. Of all CM traits, heritability of liability to CM with threshold-liability model was highest for CM2 (h2=0.083) implying that most of the genetic information on CM is in early lactation. In sire evaluation, a multitrait index calculated by combining CM2, CM4 and CM5 had the highest correlation with all other univariate CM trait evaluations. This and the magnitude (less than 1.0) of genetic correlations between CM traits suggest that a multitrait model considering CM from the different risk periods would be appropriate for CM sire evaluation.;

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Geographic variation in floral traits is associated with environmental and genetic differences among populations of the mixed mating species Collinsia heterophylla (Plantaginaceae)

Botany ◽

10.1139/cjb-2016-0014 ◽

2017 ◽

Vol 95 (2) ◽

pp. 121-138 ◽

Cited By ~ 7

Author(s):

Åsa Lankinen ◽

Josefin A. Madjidian ◽

Stefan Andersson

Keyword(s):

Environmental Factors ◽

Mating System ◽

Climatic Factors ◽

Environmental Influence ◽

Genetic Correlations ◽

Flower Size ◽

Floral Traits ◽

Mixed Mating ◽

Floral Trait ◽

Stigma Receptivity

Relatively few studies have investigated how geography, environmental factors, and genetics affect floral trait variation. We used mixed-mating Collinsia heterophylla Buist to explore variation in a suite of floral traits related to mating system in populations representing four geographic regions of California, USA, and relate this variation to geography, climatic factors, and local site characteristics. We evaluated the environmental vs. genetic trait variability in the greenhouse. Stage of anther–stigma contact correlated positively with temperature, stage of stigma receptivity was negatively associated with vegetation cover, and flower size differed among populations without any clear relation to environmental factors. Greenhouse data indicated heritability for stage of anther–stigma contact, flower size, and time to flowering, and positive correlations between field and greenhouse for stage of stigma receptivity and flower size; however, stage of anther–stigma contact showed a high degree of environmental influence. Stage of anther–stigma contact covaried positively with stage of stigma receptivity and flower size across maternal families, indicating genetic correlations between traits. In conclusion, phenotypic floral variation within mixed-mating C. heterophylla is mostly determined by a genetic component. Geography, environment, and genetics affect traits differently, suggesting that ecological and evolutionary processes contribute to shaping variability in mating system-related traits.

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211 Changes in genetic parameters of fitness and growth traits under genomic selection in pigs

Journal of Animal Science ◽

10.1093/jas/skz258.081 ◽

2019 ◽

Vol 97 (Supplement_3) ◽

pp. 41-41

Author(s):

Jorge Hidalgo ◽

Shogo Tsuruta ◽

Daniela Lourenco ◽

Yijian Huang ◽

Kent Gray ◽

...

Keyword(s):

Genetic Variation ◽

Genomic Selection ◽

Variance Components ◽

Genetic Parameters ◽

Growth Traits ◽

Average Daily Gain ◽

Genetic Correlations ◽

Data Set ◽

Daily Gain ◽

Over Time

Abstract Genomic selection increases intensity of selection and decreases generation interval. However, intensive selection reduces genetic variation and can strengthen undesirable genetic correlations. The purpose of this study was to investigate changes in genetic parameters of litter size (LS), number born alive (NBA), number born dead (NBD) and average daily gain (ADG) and weight at off-test (WT) in pigs over time. The data set contained 20,086 (LS), 21,230 (NBA), 21,230 (NBD), 144,717 (ADG) and 144,718 (WT) phenotypic records. Pedigree file included 369,776 animals born between 2001 and 2018, of which 39,038 were genotyped. Two trait models were evaluated (LS-ADG, LS-WT, NBA-ADG, NBA-WT, NBD-ADG and NBD-WT) using 3-year sliding subsets starting from 2010. Variance components and genetic parameters were estimated using GIBBS2F90 program. Computations were performed with (BLUP) or without (ssGBLUP) genotypes. For BLUP (ssGBLUP), the changes in heritability from 2010–2012 to 2015–2018 were 0.08 to 0.09 (0.08 to 0.06) for LS, 0.33 to 0.24 (0.37 to 0.16) for ADG, 0.11 to 0.07 (0.10 to 0.07) for NBD, and 0.32 to 0.24 (0.38 to 0.17) for WT. Differences were also observed for genetic correlations as they were -0.23 to -0.73 (-0.31 to -0.58) for LS-ADG, -0.24 to -0.74 (-0.31 to -0.50) for LS-WT, -0.33 to -0.65 (-0.41 to -0.53) for NBA-ADG, -0.35 to -0.66 (-0.42 to -0.45) for NBA-WT, 0.12 to 0.04 (0.12 to 0.16) for NBD-ADG, and 0.11 to 0.05 (0.11 to 0.22) for NBD-WT. Genomic selection in pigs reduced heritabilities and emphasized the antagonistic relationship that are under strong selection. Heritabilities estimated from ssGBLUP declined more than those by BLUP while changes in the genetic correlations were smaller and more gradual by ssGBLUP. Differences between ssGBLUP and BLUP could be caused by genomic pre-selection unaccounted for by BLUP.

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299 Genetic analysis of temperament and its correlation with production, reproduction, type, health and longevity in Chinese Holstein

Journal of Animal Science ◽

10.1093/jas/skaa278.053 ◽

2020 ◽

Vol 98 (Supplement_4) ◽

pp. 29-30

Author(s):

Yao Chang ◽

Yachun Wang

Keyword(s):

Genetic Correlation ◽

Fixed Effects ◽

Genetic Parameters ◽

Mixed Model ◽

Linear Mixed Model ◽

Threshold Model ◽

Residual Effect ◽

Additive Genetic Effect ◽

Age At First Calving ◽

Chinese Holstein

Abstract The objectives of this study were to estimate genetic parameters for temperament via three approaches and to examine associations of temperament with other economically important traits in Chinese Holstein. Records for temperament score (TS) on 6,586 lactating cows from 2015 to 2017 were obtained. Temperament assessed during rectal temperature measurements was recorded on a 3-point scale (1 = quiet; 2 = average; 3 = nervous). TS was treated as a ternary trait or a binary trait in different scenarios. The genetic parameters were estimated by: 1) a linear model using AI-REML; 2) a Generalized Linear Mixed Model (GLMM); or 3) a Bayesian threshold model via Gibbs sampling. Each record was partitioned into the fixed effects of herd-scorer and parity, an additive genetic effect and a residual effect. Then approximate genetic correlation between TS with production traits [milk yield (MY), fat and protein percentage (FP and PP)], fertility traits [age at first service (AFS), age at first calving (AFC), stillbirth (SB)], overall type, health traits [somatic cell score (SCS), udder diseases (UD) claw and leg diseases (CLD) metabolic disorders (MD)] and productive life (PL) were estimated. Estimates of heritability and accuracy of EBV for TS were listed in Table 1. Low to moderate genetic correlation between TS and above-mentioned traits were found. There was a favorable genetic correlation between TS and FP (-0.35), PP (-0.42), AFC (0.31), UD (0.58) and PL (-0.24); however, undesirable genetic correlation existed between TS and the other traits (-0.43~0.27). Current results suggested that a Bayesian threshold model can be the most recommended algorithm for analyzing temperament since it brought a relatively higher heritability and consequently EBV with higher accuracy, and selection for calmer individuals will translate into increased fat and protein yields, a lower age at first calving, better resistance to udder diseases and a longer functional longevity.

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