Comparative gene mapping workshop: progress in agriculturally important animals

Following the successful Comparative Mapping Workshop held at Fraser Island, Australia in 1995, HUGO organized a second workshop of 41 invited participants, held at Toulouse, France on May 3 and 4, 1999. The aim of the conference was to focus on recent developments in genome mapping in a variety of vertebrate species, with particular emphasis on progress in farm animals (cattle, pigs, chickens, sheep, horses, goats, and deer). In addition, representatives from important experimental mammalian and vertebrate organisms (e.g. mice, rats, dogs, fugu, and marsupials) also participated in the meeting. After a rapid overview of developments in the construction and comparison of genome maps in a wide variety of species, discussion focused on how comparative genomics will play a vital role in the genetic dissection of multigenic traits and the characterization of agriculturally important loci in agricultural species. Acceleration of gene discovery with heterologous ESTs (Expressed Sequence Tags) or collections of ESTs was discussed. Recent developments in the construction of cDNA libraries and the efficiency of tools such as whole genome radiation hybrids (RH) and large fragment clone libraries (YACs and in particular BACs) were discussed. Proposed criteria to improve the identification of homologous genes between species and recommendations for nomenclatures were identified. Particular emphasis was placed on how the integration of biological databases could help the scientific community. Received: 13 July 1999 / Accepted: 20 September 1999     

Optimal designs for linkage disequilibrium mapping and candidate gene association tests in livestock populations

Simulation was used to evaluate the performance of different selective genotyping strategies when using linkage disequilibrium across large half-sib families to position a QTL within a previously defined genomic region. Strategies examined included standard selective genotyping and different approaches of discordant and concordant sib selection applied to arbitrary or selected families. Strategies were compared as a function of effect and frequency of QTL alleles, heritability, and phenotypic expression of the trait. Large half-sib families were simulated for 100 generations and 2% of the population was genotyped in the final generation. Simple ANOVA was applied and the marker with the greatest F-value was considered the most likely QTL position. For traits with continuous phenotypes, genotyping the most divergent pairs of half-sibs from all families was the best strategy in general, but standard selective genotyping was somewhat more precise when heritability was low. When the phenotype was distributed in ordered categories, discordant sib selection was the optimal approach for positioning QTL for traits with high heritability and concordant sib selection was the best approach when genetic effects were small. Genotyping of a few selected sibs from many families was generally more efficient than genotyping many individuals from a few highly selected sires.     

Comparative mapping in farm animals.

This paper summarises the current status of comparative mapping in farm animals. For most of the major farm animal species, a wide range of genomic tools are now available to create high-resolution genetic and physical maps of the genome. For many farm animals, the use of radiation hybrid panels and sequence data from expressed sequence tag (EST) projects has accelerated the development of high-resolution comparative maps, with human--the model species for farm animals. These tools and comparative maps are being used to map and identify the genes at the loci for simple and complex traits. The development of detailed physical maps in farm animals based on radiation hybrid panels and bacterial artificial chromosome (BAC) contigs provides a direct link between the 'information-poor' maps of farm animals and the 'information-rich' genomes of human and other model organisms.     

A comparison of bivariate and univariate QTL mapping in livestock populations

This study presents a multivariate, variance component-based QTL mapping model implemented via restricted maximum likelihood (REML). The method was applied to investigate bivariate and univariate QTL mapping analyses, using simulated data. Specifically, we report results on the statistical power to detect a QTL and on the precision of parameter estimates using univariate and bivariate approaches. The model and methodology were also applied to study the effectiveness of partitioning the overall genetic correlation between two traits into a component due to many genes of small effect, and one due to the QTL. It is shown that when the QTL has a pleiotropic effect on two traits, a bivariate analysis leads to a higher statistical power of detecting the QTL and to a more precise estimate of the QTL''s map position, in particular in the case when the QTL has a small effect on the trait. The increase in power is most marked in cases where the contributions of the QTL and of the polygenic components to the genetic correlation have opposite signs. The bivariate REML analysis can successfully partition the two components contributing to the genetic correlation between traits.     

Genomic contributions in livestock gene introgression programmes

The composition of the genome after introgression of a marker gene from a donor to a recipient breed was studied using analytical and simulation methods. Theoretical predictions of proportional genomic contributions, including donor linkage drag, from ancestors used at each generation of crossing after an introgression programme agreed closely with simulated results. The obligate drag, the donor genome surrounding the target locus that cannot be removed by subsequent selection, was also studied. It was shown that the number of backcross generations and the length of the chromosome affected proportional genomic contributions to the carrier chromosomes. Population structure had no significant effect on ancestral contributions and linkage drag but it did have an effect on the obligate drag whereby larger offspring groups resulted in smaller obligate drag. The implications for an introgression programme of the number of backcross generations, the population structure and the carrier chromosome length are discussed. The equations derived describing contributions to the genome from individuals from a given generation provide a framework to predict the genomic composition of a population after the introgression of a favourable donor allele. These ancestral contributions can be assigned a value and therefore allow the prediction of genetic lag.     

Linkage information content and efficiency of full-sib and half-sib designs for gene mapping

The accuracy of a genetic map depends on the amount of linkage information contained in the data set used for construction of the map. The amount of linkage information is related to the designs employed for linkage analysis. The purpose of this study was to provide general formulations for various genotyping schemes and family structures in order to evaluate the amount of linkage information in a data set. Linkage information content (LIC) was defined as the frequency of fully informative gametes, which are gametes from doubly heterozygous parents with known linkage phases. Depending on the design, LIC is based on two generations if the parental phases are determined statistically, or three generations if the parental phases are determined genetically. Different schemes were considered in deriving LIC: (1) genotyping of one parent or two parents, and (2) genotyping of two or three generation families. The LIC for a full-sib design was found to be generally greater than for a half-sib design but requires typing a large number of individuals when at least one locus has only two alleles. The efficiency of the full-sib design is reduced significantly if a sex-specific linkage map is sought.     

Expeditor: a pipeline for designing primers using human gene structure and livestock animal EST information

We have developed software, called Expeditor, that can be used to combine known gene structure information from human and coding sequence information from farm animal species for a streamlined primer design in target farm animal species. This software has many utilities, which include PCR-based SNP discovery for identification of genes/markers associated with economically important traits in farm animals, comparative mapping analysis, and evolution studies. The use of this software helps minimize tedious manual operations and reduces the chance of errors by more conventional approaches.     

Utilization of DNA marker-assisted selection in Korean native animals

The recent progress of DNA technologies including DNA fingerprinting (DFP) and random amplified DNA polymorphism (RAPD) analysis make it possible to identify the specific genetic traits of animals and to analyze the genetic diversity and relatedness between or within species or populations. Using those techniques, some efforts to identify and develop the specific DNA markers based on DNA polymorphism, which are related with economic traits for Korean native animals, Hanwoo (Korean native cattle), Korean native pig and Korean native chicken, have been made in Korea for recent a few years. The developed specific DNA markers successfully characterize the Korean native animals as the unique Korean genetic sources, distinctively from other imported breeds. Some of these DNA markers have been related to some important economic traits for domestic animals, for example, growth rate and marbling for Hanwoo, growth rate and back fat thickness for native pig, and growth rate, egg weight and egg productivity for native chicken. This means that those markers can be used in important marker-assisted selection (MAS) of Korean native domestic animals and further contribute to genetically improve and breed them.     

Tests of candidate genes in breed cross populations for QTL mapping in livestock

In recent years, several F₂ crosses between outbred lines of livestock have been developed to identify quantitative trait loci (QTL). These populations are valuable for further genetic analysis, including positional candidate gene loci (CGL). Analysis of CGL in F₂ populations is, however, hindered by extensive between-breed linkage disequilibrium (LD). The objectives here were to develop and evaluate three tests for CGL in simulated F₂ breed-cross populations. 1) A standard association test, based on the fixed effect of CGL genotype. This test was significant for CGL at considerable distances from the QTL. 2) A marker-assisted association test, based on a test at the CGL of the fixed effect of CGL genotype in a breed-cross QTL interval mapping model. This removed the impact of between-breed LD, but was not powerful in detecting CGL closely linked to the QTL, unless the CGL was the QTL. 3) An F-drop test, comparing F ratios for a QTL at the CGL with and without the CGL included as fixed effect. It had low power to distinguish close from distant CGL. Power to distinguish two CGL within 10 cM from the QTL was limited and little improved by including QTL effects associated with markers to remove between-breed LD, although the power was greater when one of the CGL was the causative mutation. Therefore, while we conclude that candidate gene tests in QTL mapping populations must be interpreted with caution, we now have a clearer picture of the value of candidate gene tests in these populations.     

Evaluation of designs for reference families for livestock linkage mapping experiments

Abstract

The development of dense linkage maps consisting of highly polymorphic loci for livestock species is technically feasible. However, linkage mapping experiments are expensive as they involve many animals and marker typings per animal. To minimize costs of developing linkage maps for livestock species, optimizing designs for mapping studies is necessary. This study provides a general framework for evaluating the efficiency of designs for reference families consisting of two‐ or three‐ generation full‐sib or half‐sib families selected from a segregating population. The influence of number of families, number of offspring per family, family structure (either half‐sib or full‐sib) and marker polymorphism is determined. Evaluation is done for two markers with a recombination rate of .20 and for a marker and a dominant single gene with a recombination rate of .20. Two evaluation criteria are used: expected maximum lod score for detection of linkage and accuracy of an estimated recombination rate defined as probability that the true recombination rate is in an interval around the estimated recombination rate. First, for several designs the contribution of reference families to expected maximum lod score and accuracy is given. Second, the required number of families in a design to obtain a certain value for the evaluation criteria is calculated when number of offspring per family, family structure and marker polymorphism are specified. The required numbers increase when designs are optimized not only for expected maximum lod score but also for accuracy. The required number of animals to map a dominant single gene is very large. Therefore, a set of reference families should be designed for strictly mapping marker loci. Examples illustrate how tabulated results can be generalized to determine the values for a wide range of designs containing two‐ or three‐generation full‐sib or half‐sib families.     

False alarms and information transmission in grouping animals

A key benefit of grouping in prey species is access to social information, including information about the presence of predators. Larger groups of prey animals respond both sooner and at greater distances from predators, increasing the likelihood that group members will successfully avoid capture. However, identifying predators in complex environments is a difficult task, and false alarms (alarm behaviours without genuine threat) appear surprisingly frequent across a range of taxa including insects, amphibians, fish, mammals, and birds. In some bird flocks, false alarms have been recorded to substantially outnumber true alarms. False alarms can be costly in terms of both the energetic costs of producing alarm behaviours as well as lost opportunity costs (e.g. abandoning a feeding patch which was in fact safe, losing sleep if an animal is resting/roosting, or losing mating opportunities). Models have shown that false alarms may be a substantial but underappreciated cost of group living, introducing an inherent risk to using social information and a vulnerability to the propagation of false information. This review will focus on false alarms, introducing a two-stage framework to categorise the different factors hypothesised to influence the propensity of animal groups to produce false alarms. A number of factors may affect false alarm rate, and this new framework splits these factors into two core processing stages: (i) individual perception and response; and (ii) group processing of predator information. In the first stage, individuals in the group monitor the environment for predator cues and respond. The factors highlighted in this stage influence the likelihood that an individual will misclassify stimuli and produce a false alarm (e.g. lower light levels can make predator identification more difficult and false alarms more common). In the second stage, alarm information from individuals is processed by the group. The factors highlighted in this stage influence the likelihood of alarm information being copied by group members and propagated through the group (e.g. some animals implement group processing mechanisms that regulate the spread of behavioural responses such as consensus decision making through the quorum response). This review follows the structure of this new framework, focussing on the causes of false alarms, factors that influence false alarm rate, the transmission of alarm information through animal groups, mechanisms to mitigate the spread of false alarms, and the consequences of false alarms.     

Genome mapping in aquatic animals: progress and future perspectives

The genome of aquatic animals is poorly understood and information from different taxonomic groups is sketchy. While there have been intensive genomic studies on some fish models, investigations on other fishes and invertebrates have been scarce. Yet there are recently some coordinated studies on genome mapping in a number of aquaculture animals of economic importance. This review summarizes information available on genome mapping of the important fish models and aquaculture animals. The future perspectives of this field of studies are discussed.     

QTL mapping in autotetraploids using SNP dosage information

Key message

Dense linkage maps derived by analysing SNP dosage in autotetraploids provide detailed information about the location of, and genetic model at, quantitative trait loci.

Abstract

Recent developments in sequencing and genotyping technologies enable researchers to generate high-density single nucleotide polymorphism (SNP) genotype data for mapping studies. For polyploid species, the SNP genotypes are informative about allele dosage, and Hackett et al. (PLoS ONE 8:e63939, 2013) presented theory about how dosage information can be used in linkage map construction and quantitative trait locus (QTL) mapping for an F₁ population in an autotetraploid species. Here, QTL mapping using dosage information is explored for simulated phenotypic traits of moderate heritability and possibly non-additive effects. Different mapping strategies are compared, looking at additive and more complicated models, and model fitting as a single step or by iteratively re-weighted modelling. We recommend fitting an additive model without iterative re-weighting, and then exploring non-additive models for the genotype means estimated at the most likely position. We apply this strategy to re-analyse traits of high heritability from a potato population of 190 F₁ individuals: flower colour, maturity, height and resistance to late blight (Phytophthora infestans (Mont.) de Bary) and potato cyst nematode (Globodera pallida), using a map of 3839 SNPs. The approximate confidence intervals for QTL locations have been improved by the detailed linkage map, and more information about the genetic model at each QTL has been revealed. For several of the reported QTLs, candidate SNPs can be identified, and used to propose candidate trait genes. We conclude that the high marker density is informative about the genetic model at loci of large effects, but that larger populations are needed to detect smaller QTLs.     

Sustainable,efficient livestock production with high biodiversity and good welfare for animals

What is the future for livestock agriculture in the world? Consumers have concerns about sustainability but many widely used livestock production methods do not satisfy consumers'' requirements for a sustainable system. However, production can be sustainable, occurring in environments that: supply the needs of the animals resulting in good welfare, allow coexistence with a wide diversity of organisms native to the area, minimize carbon footprint and provide a fair lifestyle for the people working there. Conservation need not just involve tiny islands of natural vegetation in a barren world of agriculture, as there can be great increases in biodiversity in farmed areas. Herbivores, especially ruminants that consume materials inedible by humans, are important for human food in the future. However, their diet should not be just ground-level plants. Silvopastoral systems, pastures with shrubs and trees as well as herbage, are described which are normally more productive than pasture alone. When compared with widely used livestock production systems, silvopastoral systems can provide efficient feed conversion, higher biodiversity, enhanced connectivity between habitat patches and better animal welfare, so they can replace existing systems in many parts of the world and should be further developed.     

Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals,humans and environment in livestock farming

Anthropogenic environments such as those created by intensive farming of livestock, have been proposed to provide ideal selection pressure for the emergence of antimicrobial-resistant Escherichia coli bacteria and antimicrobial resistance genes (ARGs) and spread to humans. Here, we performed a longitudinal study in a large-scale commercial poultry farm in China, collecting E. coli isolates from both farm and slaughterhouse; targeting animals, carcasses, workers and their households and environment. By using whole-genome phylogenetic analysis and network analysis based on single nucleotide polymorphisms (SNPs), we found highly interrelated non-pathogenic and pathogenic E. coli strains with phylogenetic intermixing, and a high prevalence of shared multidrug resistance profiles amongst livestock, human and environment. Through an original data processing pipeline which combines omics, machine learning, gene sharing network and mobile genetic elements analysis, we investigated the resistance to 26 different antimicrobials and identified 361 genes associated to antimicrobial resistance (AMR) phenotypes; 58 of these were known AMR-associated genes and 35 were associated to multidrug resistance. We uncovered an extensive network of genes, correlated to AMR phenotypes, shared among livestock, humans, farm and slaughterhouse environments. We also found several human, livestock and environmental isolates sharing closely related mobile genetic elements carrying ARGs across host species and environments. In a scenario where no consensus exists on how antibiotic use in the livestock may affect antibiotic resistance in the human population, our findings provide novel insights into the broader epidemiology of antimicrobial resistance in livestock farming. Moreover, our original data analysis method has the potential to uncover AMR transmission pathways when applied to the study of other pathogens active in other anthropogenic environments characterised by complex interconnections between host species.     

Regulating gene expression in transgenic animals.

Regardless of the field of application, the raison d'etre of transgenic animals is to study gene regulation and function. With increasing frequency, mammalian genes are being isolated with no concomitant knowledge of their function. The human genome mapping initiative will undoubtedly produce a cornucopia of such genes. While the merit of taking a transgenic route to study genes of unknown function is axiomatic, the choices of strategies for gene regulation in vivo may not be fully appreciated. This review will address two main points: first, the targeted and regulated expression of genes, and second, the structural and functional ablation of genes.