Publications by authors named "Jan Lassen"

15 Publications

  • Page 1 of 1

Stability Assessment of the Rumen Bacterial and Archaeal Communities in Dairy Cows Within a Single Lactation and Its Association With Host Phenotype.

Front Microbiol 2021 6;12:636223. Epub 2021 Apr 6.

Department of Animal Science, Faculty of Science and Technology, Aarhus University, Aarhus, Denmark.

Better characterization of changes in the rumen microbiota in dairy cows over the lactation period is crucial for understanding how microbial factors may potentially be interacting with host phenotypes. In the present study, we characterized the rumen bacterial and archaeal community composition of 60 lactating Holstein dairy cows (33 multiparous and 27 primiparous), sampled twice within the same lactation with a 122 days interval. Firmicutes and Bacteroidetes dominated the rumen bacterial community and showed no difference in relative abundance between samplings. Two less abundant bacterial phyla (SR1 and Proteobacteria) and an archaeal order (Methanosarcinales), on the other hand, decreased significantly from the mid-lactation to the late-lactation period. Moreover, between-sampling stability assessment of individual operational taxonomic units (OTUs), evaluated by concordance correlation coefficient (C-value) analysis, revealed the majority of the bacterial OTUs (6,187 out of 6,363) and all the 79 archaeal OTUs to be unstable over the investigated lactation period. The remaining 176 stable bacterial OTUs were mainly assigned to , unclassified Prevotellaceae, and unclassified Bacteroidales. Milk phenotype-based screening analysis detected 32 bacterial OTUs, mainly assigned to unclassified Bacteroidetes and Lachnospiraceae, associated with milk fat percentage, and 6 OTUs, assigned to and unclassified Ruminococcaceae, associated with milk protein percentage. These OTUs were only observed in the multiparous cows. None of the archaeal OTUs was observed to be associated with the investigated phenotypic parameters, including methane production. Co-occurrence analysis of the rumen bacterial and archaeal communities revealed to be positively correlated with the archaeal genus (Pearson = 0.76) and unclassified Methanomassiliicoccaceae (Pearson = 0.64); , on the other hand, was negatively correlated with (Pearson = -0.56). In conclusion, the rumen bacterial and archaeal communities of dairy cows displayed distinct stability at different taxonomic levels. Moreover, specific members of the rumen bacterial community were observed to be associated with milk phenotype parameters, however, only in multiparous cows, indicating that dairy cow parity could be one of the driving factors for host-microbe interactions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fmicb.2021.636223DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076905PMC
April 2021

Effects of Incorporating Dry Matter Intake and Residual Feed Intake into a Selection Index for Dairy Cattle Using Deterministic Modeling.

Animals (Basel) 2021 Apr 17;11(4). Epub 2021 Apr 17.

Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada.

The inclusion of feed efficiency in the breeding goal for dairy cattle has been discussed for many years. The effects of incorporating feed efficiency into a selection index were assessed by indirect selection (dry matter intake) and direct selection (residual feed intake) using deterministic modeling. Both traits were investigated in three ways: (1) restricting the trait genetic gain to zero, (2) applying negative selection pressure, and (3) applying positive selection pressure. Changes in response to selection from economic and genetic gain perspectives were used to evaluate the impact of including feed efficiency with direct or indirect selection in an index. Improving feed efficiency through direct selection on residual feed intake was the best scenario analyzed, with the highest overall economic response including favorable responses to selection for production and feed efficiency. Over time, the response to selection is cumulative, with the potential for animals to reduce consumption by 0.16 kg to 2.7 kg of dry matter per day while maintaining production. As the selection pressure increased on residual feed intake, the response to selection for production, health, and fertility traits and body condition score became increasingly less favorable. This work provides insight into the potential long-term effects of selecting for feed efficiency as residual feed intake.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/ani11041157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072614PMC
April 2021

Bayesian modeling reveals host genetics associated with rumen microbiota jointly influence methane emission in dairy cows.

ISME J 2020 08 4;14(8):2019-2033. Epub 2020 May 4.

Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.

Reducing methane emissions from livestock production is of great importance for the sustainable management of the Earth's environment. Rumen microbiota play an important role in producing biogenic methane. However, knowledge of how host genetics influences variation in ruminal microbiota and their joint effects on methane emission is limited. We analyzed data from 750 dairy cows, using a Bayesian model to simultaneously assess the impact of host genetics and microbiota on host methane emission. We estimated that host genetics and microbiota explained 24% and 7%, respectively, of variation in host methane levels. In this Bayesian model, one bacterial genus explained up to 1.6% of the total microbiota variance. Further analysis was performed by a mixed linear model to estimate variance explained by host genomics in abundances of microbial genera and operational taxonomic units (OTU). Highest estimates were observed for a bacterial OTU with 33%, for an archaeal OTU with 26%, and for a microbial genus with 41% heritability. However, after multiple testing correction for the number of genera and OTUs modeled, none of the effects remained significant. We also used a mixed linear model to test effects of individual host genetic markers on microbial genera and OTUs. In this analysis, genetic markers inside host genes ABS4 and DNAJC10 were found associated with microbiota composition. We show that a Bayesian model can be utilized to model complex structure and relationship between microbiota simultaneously and their interaction with host genetics on methane emission. The host genome explains a significant fraction of between-individual variation in microbial abundance. Individual microbial taxonomic groups each only explain a small amount of variation in methane emissions. The identification of genes and genetic markers suggests that it is possible to design strategies for breeding cows with desired microbiota composition associated with phenotypes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41396-020-0663-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7368015PMC
August 2020

Predictive ability of host genetics and rumen microbiome for subclinical ketosis.

J Dairy Sci 2020 May 18;103(5):4557-4569. Epub 2020 Mar 18.

Center for Quantitative Genetics and Genomics, Aarhus University, DK-8830 Tjele, Denmark.

Subclinical metabolic disorders such as ketosis cause substantial economic losses for dairy farmers in addition to the serious welfare issues they pose for dairy cows. Major hurdles in genetic improvement against metabolic disorders such as ketosis include difficulties in large-scale phenotype recording and low heritability of traits. Milk concentrations of ketone bodies, such as acetone and β-hydroxybutyric acid (BHB), might be useful indicators to select cows for low susceptibility to ketosis. However, heritability estimates reported for milk BHB and acetone in several dairy cattle breeds were low. The rumen microbial community has been reported to play a significant role in host energy homeostasis and metabolic and physiologic adaptations. The current study aims at investigating the effects of cows' genome and rumen microbial composition on concentrations of acetone and BHB in milk, and identifying specific rumen microbial taxa associated with variation in milk acetone and BHB concentrations. We determined the concentrations of acetone and BHB in milk using nuclear magnetic resonance spectroscopy on morning milk samples collected from 277 Danish Holstein cows. Imputed high-density genotype data were available for these cows. Using genomic and microbial prediction models with a 10-fold resampling strategy, we found that rumen microbial composition explains a larger proportion of the variation in milk concentrations of acetone and BHB than do host genetics. Moreover, we identified associations between milk acetone and BHB with some specific bacterial and archaeal operational taxonomic units previously reported to have low to moderate heritability, presenting an opportunity for genetic improvement. However, higher covariation between specific microbial taxa and milk acetone and BHB concentrations might not necessarily indicate a causal relationship; therefore further validation is needed before considering implementation in selection programs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2019-17824DOI Listing
May 2020

Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle.

Animals (Basel) 2019 Oct 21;9(10). Epub 2019 Oct 21.

Agri-Food and Biosciences Institute, Hillsborough, Co. Down BT26 6DR, UK.

Partners in Expert Working Group WG2 of the COST Action METHAGENE have used several methods for measuring methane output by individual dairy cattle under various environmental conditions. Methods included respiration chambers, the sulphur hexafluoride (SF) tracer technique, breath sampling during milking or feeding, the GreenFeed system, and the laser methane detector. The aim of the current study was to review and compare the suitability of methods for large-scale measurements of methane output by individual animals, which may be combined with other databases for genetic evaluations. Accuracy, precision and correlation between methods were assessed. Accuracy and precision are important, but data from different sources can be weighted or adjusted when combined if they are suitably correlated with the 'true' value. All methods showed high correlations with respiration chambers. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite higher numbers of animals and in most cases simultaneous repeated measures per cow per method. Lower correlations could be due to increased variability and imprecision of alternative methods, or maybe different aspects of methane emission are captured using different methods. Results confirm that there is sufficient correlation between methods for measurements from all methods to be combined for international genetic studies and provide a much-needed framework for comparing genetic correlations between methods should these become available.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/ani9100837DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826463PMC
October 2019

Impact of the rumen microbiome on milk fatty acid composition of Holstein cattle.

Genet Sel Evol 2019 May 29;51(1):23. Epub 2019 May 29.

Department of Food Science, Aarhus University, Blichers Alle 20, P.O. Box 50, 8830, Tjele, Denmark.

Background: Fatty acids (FA) in bovine milk derive through body mobilization, de novo synthesis or from the feed via the blood stream. To be able to digest feedstuff, the cow depends on its rumen microbiome. The relative abundance of the microbes has been shown to differ between cows. To date, there is little information on the impact of the microbiome on the formation of specific milk FA. Therefore, in this study, our aim was to investigate the impact of the rumen bacterial microbiome on milk FA composition. Furthermore, we evaluated the predictive value of the rumen microbiome and the host genetics on the composition of individual FA in milk.

Results: Our results show that the proportion of variance explained by the rumen bacteria composition (termed microbiability or [Formula: see text]) was generally smaller than that of the genetic component (heritability), and that rumen bacteria influenced most C15:0, C17:0, C18:2 n-6, C18:3 n-3 and CLA cis-9, trans-11 with estimated [Formula: see text] ranging from 0.26 to 0.42. For C6:0, C8:0, C10:0, C12:0, C16:0, C16:1 cis-9 and C18:1 cis-9, the variance explained by the rumen bacteria component was close to 0. In general, both the rumen microbiome and the host genetics had little value for predicting FA phenotype. Compared to genetic information only, adding rumen bacteria information resulted in a significant improvement of the predictive value for C15:0 from 0.22 to 0.38 (P = 9.50e-07) and C18:3 n-3 from 0 to 0.29 (P = 8.81e-18).

Conclusions: The rumen microbiome has a pronounced influence on the content of odd chain FA and polyunsaturated C18 FA, and to a lesser extent, on the content of the short- and medium-chain FA in the milk of Holstein cattle. The accuracy of prediction of FA phenotypes in milk based on information from either the animal's genotypes or rumen bacteria composition was very low.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12711-019-0464-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542034PMC
May 2019

Enteric methane emission from Jersey cows during the spring transition from indoor feeding to grazing.

J Dairy Sci 2019 Jul 15;102(7):6319-6329. Epub 2019 May 15.

QGG-MBG, Dept. Molecular Biology and Genetics, Aarhus University, AU-Foulum, DK-8830 Tjele, Denmark.

Organic dairy cows in Denmark are often kept indoors during the winter and outside at least part time in the summer. Consequently, their diet changes by the season. We hypothesized that grazing might affect enteric CH emissions due to changes in the nutrition, maintenance, and activity of the cows, and they might differentially respond to these factors. This study assessed the repeatability of enteric CH emission measurements for Jersey cattle in a commercial organic dairy herd in Denmark. It also evaluated the effects of a gradual transition from indoor winter feeding to outdoor spring grazing. Further, it assessed the individual-level correlations between measurements during the consecutive feeding periods (phenotype × environment, P × E) as neither pedigrees nor genotypes were available to estimate a genotype by environment effect. Ninety-six mixed-parity lactating Jersey cows were monitored for 30 d before grazing and for 24 d while grazing. The cows spent 8 to 11 h grazing each day and had free access to an in-barn automatic milking system (AMS). For each visit to the AMS, milk yield was recorded and logged along with date and time. Monitoring equipment installed in the AMS feed bins continuously measured enteric CH and CO concentrations (ppm) using a noninvasive "sniffer" method. Raw enteric CH and CO concentrations and their ratio (CH:CO) were derived from average concentrations measured during milking and per day for each cow. We used mixed models equations to estimate variance components and adjust for the fixed and random effects influencing the analyzed gas concentrations. Univariate models were used to precorrect the gas measurements for diurnal variation and to estimate the direct effect of grazing on the analyzed concentrations. A bivariate model was used to assess the correlation between the 2 periods (in-barn vs. grazing) for each gas concentration. Grazing had a weak P × E interaction for daily average CH and CO gas concentrations. Bivariate repeatability estimates for average CH and CO concentrations and CH:CO were 0.77 to 0.78, 0.73 to 0.80, and 0.26, respectively. Repeatability for CH:CO was low (0.26) but indicated some between-animal variation. In conclusion, grazing does not create significant shifts compared with indoor feeding in how animals rank for average CH and CO concentrations and CH:CO. We found no evidence that separate evaluation is needed to quantify enteric CH and CO emissions from Jersey cows during in-barn and grazing periods.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2018-15984DOI Listing
July 2019

Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows.

PLoS Genet 2018 10 12;14(10):e1007580. Epub 2018 Oct 12.

Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark.

Cattle and other ruminants produce large quantities of methane (~110 million metric tonnes per annum), which is a potent greenhouse gas affecting global climate change. Methane (CH4) is a natural by-product of gastro-enteric microbial fermentation of feedstuffs in the rumen and contributes to 6% of total CH4 emissions from anthropogenic-related sources. The extent to which the host genome and rumen microbiome influence CH4 emission is not yet well known. This study confirms individual variation in CH4 production was influenced by individual host (cow) genotype, as well as the host's rumen microbiome composition. Abundance of a small proportion of bacteria and archaea taxa were influenced to a limited extent by the host's genotype and certain taxa were associated with CH4 emissions. However, the cumulative effect of all bacteria and archaea on CH4 production was 13%, the host genetics (heritability) was 21% and the two are largely independent. This study demonstrates variation in CH4 emission is likely not modulated through cow genetic effects on the rumen microbiome. Therefore, the rumen microbiome and cow genome could be targeted independently, by breeding low methane-emitting cows and in parallel, by investigating possible strategies that target changes in the rumen microbiome to reduce CH4 emissions in the cattle industry.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pgen.1007580DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6200390PMC
October 2018

Changes in rumen bacterial and archaeal communities over the transition period in primiparous Holstein dairy cows.

J Dairy Sci 2018 Nov 29;101(11):9847-9862. Epub 2018 Aug 29.

Department of Animal Science, Aarhus University, DK-8830 Tjele, Denmark. Electronic address:

In the present study, we hypothesized that the rumen bacterial and archaeal communities would change significantly over the transition period of dairy cows, mainly as an adaptation to the classical use of low-grain prepartum and high-grain postpartum diets. Bacterial 16S rRNA gene amplicon sequencing of rumen samples from 10 primiparous Holstein dairy cows revealed no changes over the transition period in relative abundance of genera such as Ruminococcus, Butyrivibrio, Clostridium, Coprococcus, and Pseudobutyrivibrio. However, other dominant genus-level taxa, such as Prevotella, unclassified Ruminococcaceae, and unclassified Succinivibrionaceae, showed distinct changes in relative abundance from the prepartum to the postpartum period. Overall, we observed individual fluctuation patterns over the transition period for a range of bacterial taxa that, in some cases, were correlated with observed changes in the rumen short-chain fatty acids profile. Combined results from clone library and terminal-restriction fragment length polymorphism (T-RFLP) analyses, targeting the methyl-coenzyme M reductase α-subunit (mcrA) gene, revealed a methanogenic archaeal community dominated by the Methanobacteriales and Methanomassiliicoccales orders, particularly the genera Methanobrevibacter, Methanosphaera, and Methanomassiliicoccus. As observed for the bacterial community, the T-RFLP patterns showed significant shifts in methanogenic community composition over the transition period. Together, the composition of the rumen bacterial and archaeal communities exhibited changes in response to particularly the dietary changes of dairy cows over the transition period.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2017-14366DOI Listing
November 2018

Community structure of the metabolically active rumen bacterial and archaeal communities of dairy cows over the transition period.

PLoS One 2017 8;12(11):e0187858. Epub 2017 Nov 8.

Department of Animal Science, Aarhus University, Tjele, Denmark.

Dairy cows experience dramatic changes in host physiology from gestation to lactation period and dietary switch from high-forage prepartum diet to high-concentrate postpartum diet over the transition period (parturition +/- three weeks). Understanding the community structure and activity of the rumen microbiota and its associative patterns over the transition period may provide insight for e.g. improving animal health and production. In the present study, rumen samples from ten primiparous Holstein dairy cows were collected over seven weeks spanning the transition period. Total RNA was extracted from the rumen samples and cDNA thereof was subsequently used for characterizing the metabolically active bacterial (16S rRNA transcript amplicon sequencing) and archaeal (qPCR, T-RFLP and mcrA and 16S rRNA transcript amplicon sequencing) communities. The metabolically active bacterial community was dominated by three phyla, showing significant changes in relative abundance range over the transition period: Firmicutes (from prepartum 57% to postpartum 35%), Bacteroidetes (from prepartum 22% to postpartum 18%) and Proteobacteria (from prepartum 7% to postpartum 32%). For the archaea, qPCR analysis of 16S rRNA transcript number, revealed a significant prepartum to postpartum increase in Methanobacteriales, in accordance with an observed increase (from prepartum 80% to postpartum 89%) in relative abundance of 16S rRNA transcript amplicons allocated to this order. On the other hand, a significant prepartum to postpartum decrease (from 15% to 2%) was observed in relative abundance of Methanomassiliicoccales 16S rRNA transcripts. In contrast to qPCR analysis of the 16S rRNA transcripts, quantification of mcrA transcripts revealed no change in total abundance of metabolically active methanogens over the transition period. According to T-RFLP analysis of the mcrA transcripts, two Methanobacteriales genera, Methanobrevibacter and Methanosphaera (represented by the T-RFs 39 and 267 bp), represented more than 70% of the metabolically active methanogens, showing no significant changes over the transition period; minor T-RFs, likely to represent members of the order Methanomassiliicoccales and with a relative abundance below 5% in total, decreased significantly over the transition period. In accordance with the T-RFLP analysis, the mcrA transcript amplicon sequencing revealed Methanobacteriales to cover 99% of the total reads, dominated by the genera Methanobrevibacter (75%) and Methanosphaera (24%), whereas the Methanomassiliicoccales order covered only 0.2% of the total reads. In conclusion, the present study showed that the structure of the metabolically active bacterial and archaeal rumen communities changed over the transition period, likely in response to the dramatic changes in physiology and nutritional factors like dry matter intake and feed composition. It should be noted however that for the methanogens, the observed community changes were influenced by the analyzed gene (mcrA or 16S rRNA).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0187858PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678694PMC
November 2017

Short communication: Genetic variation in choice consistency for cows accessing automatic milking units.

J Dairy Sci 2016 Dec 5;99(12):9857-9863. Epub 2016 Oct 5.

Nordic Cattle Genetic Evaluation, SEGES, DK-8200 Aarhus N, Denmark.

Dairy cows milked in automatic milking systems (AMS) with more than 1 milking box may, as individuals, have a preference for specific milking boxes if allowed free choice. Estimates of quantitative genetic variation in behavioral traits of farmed animals have previously been reported, with estimates of heritability ranging widely. However, for the consistency of choice in dairy cows, almost no published estimates of heritability exist. The hypothesis for this study was that choice consistency is partly under additive genetic control and partly controlled by permanent environmental (animal) effects. The aims of this study were to obtain estimates of genetic and phenotypic parameters for choice consistency in dairy cows milked in AMS herds. Data were obtained from 5 commercial Danish herds (I-V) with 2 AMS milking boxes (A, B). Milking data were only from milkings where both the present and the previous milkings were coded as completed. This filter was used to fulfill a criterion of free-choice situation (713,772 milkings, 1,231 cows). The lactation was divided into 20 segments covering 15d each, from 5 to 305d in milk. Choice consistency scores were obtained as the fraction of milkings without change of box [i.e., 1.0 - µ(box change)] for each segment. Data were analyzed for one part of lactation at a time using a linear mixed model for first-parity cows alone and for all parities jointly. Choice consistency was found to be only weakly heritable (heritability=0.02 to 0.14) in first as well as in later parities, and having intermediate repeatability (repeatability coefficients=0.27 to 0.56). Heritability was especially low at early and late lactation states. These results indicate that consistency, which is itself an indication of repeated similar choices, is also repeatable as a trait observed over longer time periods. However, the genetic background seems to play a smaller role compared with that of the permanent animal effects, indicating that consistency could also be a learned behavior. We concluded that consistency in choices are quantifiable, but only under weak genetic control.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2016-11287DOI Listing
December 2016

Heritability estimates for enteric methane emissions from Holstein cattle measured using noninvasive methods.

J Dairy Sci 2016 Mar 21;99(3):1959-1967. Epub 2016 Jan 21.

Centre for Quantitative Genetic and Genomics, Department of Molecular Biology and Genetics, Faculty of Science and Technology, Aarhus University, PO Box 50, DK-8830 Tjele, Denmark.

The objective of this study was to estimate heritability of enteric methane emissions from dairy cattle. Methane (CH4) and CO2 were measured with a portable air-sampler and analyzer unit based on Fourier transform infrared detection. Data were collected on 3,121 Holstein dairy cows from 20 herds using automatic milking systems. Three CH4 phenotypes were acquired: the ratio between CH4 and CO2 in the breath of the cows (CH4_RATIO), the estimated quantified amount of CH4 (in g/d) measured over a week (CH4_GRAMSw), and CH4 intensity, defined as grams of CH4 per liter of milk produced (CH4_MILK). Fat- and protein-corrected milk (FPCM) and live weight data were also derived for the analysis. Data were analyzed using several univariate and bivariate linear animal models. The heritability of CH4_GRAMSw and CH4_MILK was 0.21 with a standard error of 0.06, and the heritability of CH4_RATIO was 0.16 with a standard error of 0.04. The 2 CH4 traits CH4_GRAMSw and CH4_RATIO were genetically highly correlated (rg=0.83) and they were strongly correlated with FPCM, meaning that, in this study, a high genetic potential for milk production will also mean a high genetic potential for CH4 production. The genetic correlation between CH4_MILK and FPCM and live weight showed similar patterns as the other CH4 phenotypes, although the correlations in general were closer to zero. The genetic correlations between the 3 CH4 phenotypes and live weight were low and only just significantly different from zero, meaning there is less indication of a genetic relationship between CH4 emission and live weight of the cow. None of the residual correlations between the ratio of CH4 and CO2, CH4 production in grams per day, FPCM, and live weight were significantly different from zero. The results from this study suggest that CH4 emission is partly under genetic control, that it is possible to decrease CH4 emission from dairy cattle through selection, and that selection for higher milk yield will lead to higher genetic merit for CH4 emission/cow per day.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2015-10012DOI Listing
March 2016

Low evolutionary potential for egg-to-adult viability in Drosophila melanogaster at high temperatures.

Evolution 2015 Mar 27;69(3):803-14. Epub 2015 Feb 27.

Department of Chemistry and Bioscience, Section of Biology and Environmental Science, Aalborg University, Fredrik Bajers Vej 7H, DK-9220, Aalborg East, Denmark.

To cope with the increasing and less-predictable temperature forecasts under climate change, many terrestrial ectotherms will have to migrate or rely on adaptation through plastic or evolutionary means. Studies suggest that some ectotherms have a limited potential to change their upper thermal limits via evolutionary shifts, but research has mostly focused on adult life stages under laboratory conditions. Here we use replicate populations of Drosophila melanogaster and a nested half-sib/full-sib quantitative genetic design to estimate heritabilities and genetic variance components for egg-to-adult viability under both laboratory and seminatural field conditions, encompassing cold, benign, and hot temperatures in two separate populations. The results demonstrated temperature-specific heritabilities and additive genetic variances for egg-to-adult viability. Heritabilities and genetic variances were higher under cold and benign compared to hot temperatures when tested under controlled laboratory conditions. Tendencies toward lower evolutionary potential at higher temperatures were also observed under seminatural conditions although the results were less clear in the field setting. Overall the results suggest that ectotherms that already experience temperatures close to their upper thermal tolerance limits have a restricted capacity to adapt to higher temperatures by evolutionary means.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/evo.12617DOI Listing
March 2015

Across-country test-day model evaluations for Holstein, Nordic Red Cattle, and Jersey.

J Dairy Sci 2015 Feb 28;98(2):1296-309. Epub 2014 Nov 28.

Nordic Cattle Genetic Evaluation, DK-8200 Aarhus, Denmark.

Three random regression models were developed for routine genetic evaluation of Danish, Finnish, and Swedish dairy cattle. Data included over 169 million test-day records with milk, protein, and fat yield observations from over 8.7 million dairy cows of all breeds. Variance component analyses showed significant differences in estimates between Holstein, Nordic Red Cattle, and Jersey, but only small to moderate differences within a breed across countries. The obtained variance component estimates were used to build, for each breed, their own set of covariance functions. The covariance functions describe the animal effects on milk, protein, and fat yields of the first 3 lactations as 9 different traits, assuming the same heritabilities and a genetic correlation of unity across countries. Only 15, 27, and 7 eigenfunctions with the largest eigenvalues were used to describe additive genetic animal effects and nonhereditary animal effects across lactations and within later lactations, respectively. These reduced-rank covariance functions explained 99.0 to 99.9% of the original variances but reduced the number of animal equations to be solved by 44%. Moderate rank reduction for nonhereditary animal effects and use of one-third-smaller measurement error correlations than obtained from variance component estimation made the models more robust against extreme observations. Estimation of the genetic levels of the countries' subpopulations within a breed was found sensitive to the way the breed effects were modeled, especially for the genetically heterogeneous Nordic Red Cattle. Means to ensure that only additive genetic effects entered the estimated breeding values were to describe the crossbreeding effects by fixed and random cofactors and the calving age effect by an age × breed proportion interaction, and to model phantom parent groups as random effects. To ensure that genetic variances were the same across the 3 countries in breeding value estimation, as suggested by the variance component estimates, the applied multiplicative heterogeneous variance adjustment method had to be tailored using country-specific reference measurement error variances. Results showed the feasibility of across-country genetic evaluation of cows and sires based on original test-day phenotypes. Nevertheless, applying a thorough model validation procedure is essential throughout the model building process to obtain reliable breeding values.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2014-8307DOI Listing
February 2015

An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends.

Genet Sel Evol 2007 Jul-Aug;39(4):353-67. Epub 2007 Jul 6.

Department of Genetics and Biotechnology, Danish Institute of Agricultural Sciences, DK-8830 Tjele, Denmark.

In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/1297-9686-39-4-353DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2682816PMC
September 2007
-->