Genetic Parameter Estimates for Milk Yield and Lactation Length in Buffalo

The objective of this study was to estimate genetic parameters for milk yield at 244 days and lactation length in graded buffalo cows at the El Cangre Cattle Genetic Enterprise. Data were gathered from 2575 lactations, 1377 buffalo cows, 37 milking units and between 2002-2009 calving years. It was employed the Restricted Maximum Likelihood method (REML) for estimating (co) variance components with multi trait model. Average of milk yield at 244 days and lactation length were 864 kg and 240 days, respectively. Heritability was 0.15 for milk yield and 0.13 for lactation length. Genetic correlation between these traits was 0.63. It was concluded that it is necessary to intensify selection and to increase control of the information of the genetic herds to obtain high precision in the estimates and therefore, obtain bigger genetic progress in of this species in our country.

Accumulated productivity and its genetic association with reproductive traits in females Brahman

Objective. Assessment of genetic parameters for accumulative productivity trait (ACP) and genetic correlations with age at first calving (AFC), between calving interval of first and second parity (BCI1) and longevity (LONG). Materials and methods. 8584 Brahman female records were used with an animal model in multi-trait analysis with restricted maximum likelihood method, implemented using the WOMBAT software. The models considered the fixed effects of contemporary group, parity and weaning weight of first calf covariate, the only random effect was the genetic additive direct. Weaning weight (P240) was included to reduce the effect of selection on the estimation of variance components. Results. The heritability estimates were 0.3 +/- 0.04, 0.11 +/- 0.03, 0.07 +/- 0.03 and 0.24 +/- 0.04 for AFC, BCI1, LONG and ACP respectively. Correlations between ACP and the other features were moderate to high and favorable. Conclusions. ACP can be included in breeding programs for Brahman, and used as selection criteria for its moderate heritability and genetic correlation with reproductive traits.

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

The objectives of the present study were to characterize and define homogenous production environments of composite beef cattle in Brazil in terms of climatic and geographic variables using multivariate exploratory techniques and to use them to assess the presence of G x E for birth weight (BW) and weaning weight (WW). Data from animals born between 1995 and 2008 on 36 farms located in 27 municipalities of the Brazilian states were used. Fifteen years of climate observations (mean minimum and maximum annual temperature and mean annual rainfall) and geographic (latitude, longitude and altitude) data were obtained for each municipality where the farms were located for characterization of the production environments. Hierarchical and nonhierarchical cluster analysis was used to group farms located in regions with similar environmental variables into clusters. Six clusters of farms were formed. The effect of sire-cluster interaction was tested by single-trait analysis using deviance information criterion (DIC). Genetic parameters were estimated by multi-trait analysis considering the same trait to be different in each cluster. According to the values of DIC, the inclusion of sire-cluster effect did not improve the fit of the genetic evaluation model for BW and WW. Estimates of genetic correlations among clusters ranged from -0.02 to 0.92. The low genetic correlation among the most studied regions permits us to suggest that a separate genetic evaluation for some regions should be undertaken. (C) 2012 Elsevier B.V. All rights reserved.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

The humankind genome: from genetic diversity to the origin of human diseases

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease’s etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

Molecular genetic causes of columnar growth in apple (Malus x domestica)

The columnar growth habit of apple is interesting from an economic point of view as the pillar-like trees require little space and labor. Genetic engineering could be used to speed up breeding for columnar trees with high fruit quality and disease resistance. For this purpose, this study dealt with the molecular causes of this interesting phenotype. The original bud sport mutation that led to the columnar growth habit was found to be a novel nested insertion of a Gypsy-44 LTR retrotransposon on chromosome 10 at 18.79 Mb. This subsequently causes tissue-specific differential expression of nearby downstream genes, particularly of a gene encoding a 2OG-Fe(II) oxygenase of unknown function (dmr6-like) that is strongly upregulated in developing aerial tissues of columnar trees. The tissue-specificity of the differential expression suggests involvement of cis-regulatory regions and/or tissue-specific epigenetic markers whose influence on gene expression is altered due to the retrotransposon insertion. This eventually leads to changes in genes associated with stress and defense reactions, cell wall and cell membrane metabolism as well as phytohormone biosynthesis and signaling, which act together to cause the typical phenotype characteristics of columnar trees such as short internodes and the absence of long lateral branches. In future, transformation experiments introducing Gypsy-44 into non-columnar varieties or excising Gypsy-44 from columnar varieties would provide proof for our hypotheses. However, since site-specific transformation of a nested retrotransposon is a (too) ambitious objective, silencing of the Gypsy-44 transcripts or the nearby genes would also provide helpful clues.

Towards a treaty instrument on marine genetic resources

Marine genetic resources other than fish and mammals are of increasing commercial interest and importance in genetic engineering, but fail being properly addressed in the law of the sea and in international economic law. The paper analyses the implication of the United Nations Convention on the Law of the Sea, the Convention on Biodiversity, the WTO Agreement on Trade Related Aspects of Intellectual Property Rights and related instruments under the auspices of WIPO. The paper argues that the triangle of these agreements does not adequately address marine genetic resources in particular in the high seas. Neither concerns of protecting biodiversity nor of access and benefit sharing find appropriate answers commensurate to the commercial potential of marine genetic resources. The paper suggests developing an instrument inspired by, and comparable to, the mechanisms developed by the International Treaty on Plant Genetic Resources for Food and Agriculture. The instrument would grant facilitated access to marine genetic resources and offer a more detailed set of rules with respect to the sharing of benefits resulting from their use, thereby addressing the existing legal gaps in a comprehensive way.

Proceedings of the Eighteenth Annual Biochemical Engineering Symposium

The eighteenth annual biochemical engineering symposium was held during April 22–23, 1988 at the YMCA of the Rockies conference center in Estes Park, Colorado, under the sponsorship of the University of Colorado. Previous symposia in this series have been hosted by Kansas State University (1st, 3rd, 5th, 9th, 12th, 16th), University of Nebraska-Lincoln (2nd, 4th), Iowa State University (6th, 7th, l0th, 13th, 17th), University of Missouri–Columbia (8th, 14th), and Colorado State University (11th, 15th). Next year's symposium is scheduled to be held at the University of Missouri-Columbia. The symposia are devoted to talks by students about their ongoing research. Because final publication usually takes place elsewhere, the papers included in the proceedings are brief, and often cover work in progress. ContentsApplications of mass spectrometers in biochemical engineeringJohn P. McDonald, Ayush Gupta, and Lourdes Taladriz, Kansas State University Enzymatic hydrolysis of corn gluten proteinsJulie Hardwick; Iowa State University Improved Acetone-Butanol Fermentation AnalysisZ. Buday; Colorado State University On-Line State Identification for Batch FermentationD. A. Gee and W. F. Ramirez; University of Colorado Role of Spargers in Air-Lift ReactorsPeter U. Sohn and Rakesh K. Bajpai; University of Missouri–Columbia The Interaction of Microcarriers and Turbulence within an Airlift FermenterG. Travis Jones; Kansas State University Oxygen Diffusion in the Inter-Fiber Gel/Cell Matrix of NMR-Compatible Hollow Fiber Bio-ReactorsS. L. Hanson, B. E. Dale, and R. J. Gillies; Colorado State University Characterization of Ca-alginate Gel Beads FormationHorngtwu Su, Rakesh K. Bajpai, and George W. Preckshot; University of Missouri–Columbia Metabolic Effects of Chloramphenicol Resistance in the Recombinant Host/Vector System: E. coli RRl [pBR329]William E. Bentley, Dana C. Andersen, Dhinakar S. Kompala, and Robert H. Davis; University of Colorado Genetic Engineering of Beta-Galactosidase to Aid in Fermentation Product Recovery by Polyelectrolyte PrecipitationD. E. Parker, C. E. Glatz, J. Zhao, C. F. Ford, S. M. Gendel, and M. A. Rougvie; Iowa State University Biodegradation of Organic Compounds in SoilLourdes Taladriz, L. E. Erickson, and L. T. Fan; Kansas State University Effect of Dilution, pH and Nutrient Composition on the Biodegradation of Metalworking FluidsAyush Gupta, L. E. Erickson, and L. T. Fan; Kansas State University Dissolved Hydrogen Correlation with Redox Potential in Acetone-Butanol FermentationXiangdong Zhou; Colorado State University Modeling of Ensiling Fermentation of Sweet SorghumA. K. Hilaly; Colorado State University

Proceedings of the 22nd Annual Biochemical Engineering Symposium

This is the twenty-second of a series of symposia devoted to talks and posters by students about their biochemical engineering research. The first, third, fifth, ninth, twelfth, sixteenth, and twenti~th were hosted by Kansas State University, the second and fourth by the University of Nebraska- Lincoln, the sixth, seventh, tenth, thirteenth, seventeenth, and twenty-second by Iowa State University, the eighth, fourteenth, and nineteenth by the University of Missouri-Columbia, the eleventh, fifteenth, and twenty-first by Colorado State University, and the eighteenth by the University of Colorado. Next year's symposium will be at the University of Oklahoma. Symposium proceedings are edited and issued by faculty of the host institution. Because final publication usually takes place in refereed journals, articles included here are brief and often cover work in progress. ContentsC. A. Baldwin, J.P. McDonald, and L. E. Erickson, Kansas State University. Effect of Hydrocarbon Phase on Kinetic and Transport Limitations for Bioremediation of Microporous Soil J. C. Wang, S. K. Banerji, and Rakesh Bajpai, University of Missouri-Columbia. Migration of PCP in Soil-Columns in Presence of a Second Organic Phase Cheng-Hsien Hsu and Roger G. Harrison, University of Oklahoma. Bacterial Leaching of Zinc and Copper from Mining Wastes James A. Searles, Paul Todd, and Dhinakar S. Kompala, University of Colorado. Suspension Culture of Chinese Hamster Ovary Cells Utilizing Inclined Sedimentation Ron Beyerinck and Eric H. Dunlop, Colorado State University. The Effect of Feed Zone Turbulence as Measured by Laser Doppler Velocimetry on Baker's Yeast Metabolism in a Chemostat Paul Li-Hong Yeh, GraceY. Sun, Gary A. Weisman, and Rakesh Bajpai, University of Missouri-Columbia. Effect of Medium Constituents upon Membrane Composition of Insect Cells R. Shane Gold, M. M. Meagher, R. Hutkins, and T. Conway, University of Nebraska-Lincoin. Ethanol Tolerance and Carbohydrate Metabolism in Lactobacilli John Sargantanis and M. N. Karim, Colorado State University. Application of Kalman Filter and Adaptive Control in Solid Substrate Fermentation D. Vrana, M. Meagher, and R. Hutkins, University of Nebraska-Lincoln. Product Recovery Optimization in the ABE Fermentation Kalyan R. Tadikonda and Robert H. Davis, University of Colorado. Cell Separations Using Targeted Monoclonal Antibodies Against Surface Proteins Meng H. Heng and Charles E. Glatz, Iowa State University. Charged Fusion for Selective Recovery of B-Galactosidase from Cell Extract Using Hollow Fiber Ion-Exchange Membrane Adsorption Hsiu-Mei Chen, Peter J. Reilly, and Clark Ford, Iowa State University. Site-Directed Mutagenesis to Enhance Thermostability of Glucoamylase from Aspergillus: A Rational Approach P. Tuitemwong, L. E. Erickson, and D. Y. C. Fung, Kansas State University. Applications of Enzymatic Hydrolysis and Fermentation on the Reduction of Flatulent Sugars in the Rapid Hydration Hydrothermal Cooked Soy Milk Sanjeev Redkar and Robert H. Davis, University of Colorado. Crossflow Microfiltration of Yeast Suspensions Linda Henk and James C. Linden, Colorado State University, and Irving C. Anderson, Iowa State University. Evaluation of Sorghum Ensilage as an Ethanol Feedstock Marc Lipovitch and James C. Linden, Colorado State University. Stability and Biomass Feedstock Pretreatability for Simultaneous Saccharification and Fermentation Ali Demirci, Anthony L. Pometto Ill, and Kenneth E. Johnson, Iowa State University. Application of Biofilm Reactors in Lactic Acid Fermentation Michael K. Dowd, Peter I. Reilly, and WalterS. Trahanovsky, Iowa State University. Low Molecular-Weight Organic Composition of Ethanol Stillage from Corn Craig E. Forney, Meng H. Heng, John R. Luther, Mark Q. Niederauer, and Charles E. Glatz, Iowa State University. Enhancement of Protein Separation Using Genetic Engineering J. F. Shimp, J. C. Tracy, E. Lee, L. C. Davis, and L. E. Erickson, Kansas State University. Modeling Contaminant Transport, Biodegradation and Uptake by Plants in the Rhizosphere Xiaoqing Yang, L. E. Erickson, and L. T. Fan, Kansas State University. Modeling of Dispersive-Convective Characteristics in Bioremediation of Contaminated Soil Jan Johansson and Rakesh Bajpai, University of Missouri-Columbia. Fouling of Membranes J. M. Wang, S. K. Banerji, and R. K. Bajpai, University of Missouri-Columbia. Migration of Sodium-Pentachorophenol (Na-PCP) in Unsaturated and Saturated Soil-Columns J. Sweeney and M. Meagher, University of Nebraska-Lincoln. The Purification of Alpha-D-Glucuronidase from Trichoderma reesei

Plant genetic resources: What can they contribute toward increased crop productivity?

To feed a world population growing by up to 160 people per minute, with >90% of them in developing countries, will require an astonishing increase in food production. Forecasts call for wheat to become the most important cereal in the world, with maize close behind; together, these crops will account for ≈80% of developing countries’ cereal import requirements. Access to a range of genetic diversity is critical to the success of breeding programs. The global effort to assemble, document, and utilize these resources is enormous, and the genetic diversity in the collections is critical to the world’s fight against hunger. The introgression of genes that reduced plant height and increased disease and viral resistance in wheat provided the foundation for the “Green Revolution” and demonstrated the tremendous impact that genetic resources can have on production. Wheat hybrids and synthetics may provide the yield increases needed in the future. A wild relative of maize, Tripsacum, represents an untapped genetic resource for abiotic and biotic stress resistance and for apomixis, a trait that could provide developing world farmers access to hybrid technology. Ownership of genetic resources and genes must be resolved to ensure global access to these critical resources. The application of molecular and genetic engineering technologies enhances the use of genetic resources. The effective and complementary use of all of our technological tools and resources will be required for meeting the challenge posed by the world’s expanding demand for food.

Epigenetic engineering shows H3K4me2 is required for HJURP targeting and CENP-A assembly on a synthetic human kinetochore

Kinetochores assemble on distinct 'centrochromatin' containing the histone H3 variant CENP-A and interspersed nucleosomes dimethylated on H3K4 (H3K4me2). Little is known about how the chromatin environment at active centromeres governs centromeric structure and function. Here, we report that centrochromatin resembles K4-K36 domains found in the body of some actively transcribed housekeeping genes. By tethering the lysine-specific demethylase 1 (LSD1), we specifically depleted H3K4me2, a modification thought to have a role in transcriptional memory, from the kinetochore of a synthetic human artificial chromosome (HAC). H3K4me2 depletion caused kinetochores to suffer a rapid loss of transcription of the underlying α-satellite DNA and to no longer efficiently recruit HJURP, the CENP-A chaperone. Kinetochores depleted of H3K4me2 remained functional in the short term, but were defective in incorporation of CENP-A, and were gradually inactivated. Our data provide a functional link between the centromeric chromatin, α-satellite transcription, maintenance of CENP-A levels and kinetochore stability.

A genetic linkage map in autotetraploid lucerne adapted to northern Australia, and use of the map to identify DNA markers linked to resistance to Phytophthora medicaginis

Phytophthora root rot, caused by Phytophthora medicaginis, is a major limitation to lucerne ( Medicago sativa L.) production in Australia and North America. Quantitative trait loci (QTLs) involved in resistance to P. medicaginis were identified in a lucerne backcross population of 120 individuals. A genetic linkage map was constructed for tetraploid lucerne using 50 RAPD ( randomly amplified polymorphic DNA), 104 AFLP (amplified fragment length polymorphism) markers, and one SSR ( simple sequence repeat or microsatellite) marker, which originated from the resistant parent (W116); 13 markers remain unlinked. The linkage map contains 18 linkage groups covering 2136.5 cM, with an average distance of 15.0 cM between markers. Four of the linkage groups contained only either 2 or 3 markers. Using duplex markers and repulsion phase linkages the map condensed to 7 homology groups and 2 unassigned linkage groups. Three regions located on linkage groups 2, 14, and 18, were identified as associated with root reaction and the QTLs explained 6 - 15% of the phenotypic variation. The research also indicates that different resistance QTLs are involved in conferring resistance in different organs. Two QTLs were identified as associated with disease resistance expressed after inoculation of detached leaves. The marker, W11-2 on group 18, identified as associated with root reaction, contributed 7% of the phenotypic variation in leaf response in our population. This marker appears to be linked to a QTL encoding a resistance factor contributing to both root and leaf reaction. One other QTL, not identified as associated with root reaction, was positioned on group 1 and contributed to 6% of the variation. This genetic linkage map provides an entry point for future molecular-based improvement of lucerne in Australia, and markers linked to the QTLs we have reported should be useful for marker-assisted selection for partial resistance to P. medicaginis in lucerne.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.