Optimized breeding strategies for multiple trait integration: II. Process efficiency in event pyramiding and trait fixation

Multiple trait integration (MTI) is a multi-step process of converting an elite variety/hybrid for value-added traits (e.g. transgenic events) through backcross breeding. From a breeding standpoint, MTI involves four steps: single event introgression, event pyramiding, trait fixation, and version testing. This study explores the feasibility of marker-aided backcross conversion of a target maize hybrid for 15 transgenic events in the light of the overall goal of MTI of recovering equivalent performance in the finished hybrid conversion along with reliable expression of the value-added traits. Using the results to optimize single event introgression (Peng et al. Optimized breeding strategies for multiple trait integration: I. Minimizing linkage drag in single event introgression. Mol Breed, 2013) which produced single event conversions of recurrent parents (RPs) with ≤8 cM of residual non-recurrent parent (NRP) germplasm with ~1 cM of NRP germplasm in the 20 cM regions flanking the event, this study focused on optimizing process efficiency in the second and third steps in MTI: event pyramiding and trait fixation. Using computer simulation and probability theory, we aimed to (1) fit an optimal breeding strategy for pyramiding of eight events into the female RP and seven in the male RP, and (2) identify optimal breeding strategies for trait fixation to create a ‘finished’ conversion of each RP homozygous for all events. In addition, next-generation seed needs were taken into account for a practical approach to process efficiency. Building on work by Ishii and Yonezawa (Optimization of the marker-based procedures for pyramiding genes from multiple donor lines: I. Schedule of crossing between the donor lines. Crop Sci 47:537–546, 2007a), a symmetric crossing schedule for event pyramiding was devised for stacking eight (seven) events in a given RP. Options for trait fixation breeding strategies considered selfing and doubled haploid approaches to achieve homozygosity as well as seed chipping and tissue sampling approaches to facilitate genotyping. With selfing approaches, two generations of selfing rather than one for trait fixation (i.e. ‘F2 enrichment’ as per Bonnett et al. in Strategies for efficient implementation of molecular markers in wheat breeding. Mol Breed 15:75–85, 2005) were utilized to eliminate bottlenecking due to extremely low frequencies of desired genotypes in the population. The efficiency indicators such as total number of plants grown across generations, total number of marker data points, total number of generations, number of seeds sampled by seed chipping, number of plants requiring tissue sampling, and number of pollinations (i.e. selfing and crossing) were considered in comparisons of breeding strategies. A breeding strategy involving seed chipping and a two-generation selfing approach (SC + SELF) was determined to be the most efficient breeding strategy in terms of time to market and resource requirements. Doubled haploidy may have limited utility in trait fixation for MTI under the defined breeding scenario. This outcome paves the way for optimizing the last step in the MTI process, version testing, which involves hybridization of female and male RP conversions to create versions of the converted hybrid for performance evaluation and possible commercial release.     

A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. I. Methodology

A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single markers was implemented via Markov Chain Monte Carlo (MCMC) algorithms for parameter estimation and hypothesis testing. Parameter estimators were marginal posterior means computed using a Gibbs sampler with data augmentation. Variables sampled included the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage, and the parameters (allele frequency, QTL substitution effect, recombination rate, polygenic and residual variances). Several MCMC algorithms were derived for computing Bayesian tests of linkage, which consisted of the marginal posterior probability of linkage and the marginal likelihood of the QTL variance associated with the marker.     

Therapeutic strategies in multiple sclerosis. I. Immunotherapy

This review first addresses several general aspects of the immunotherapy of multiple sclerosis. Next, two approved immunomodulatory treatments, interferon-beta and copolymer-1 (glatiramer acetate), are reviewed in more detail. Finally, other immunosuppressive therapies and experimental strategies are briefly discussed.     

Detecting adaptive trait introgression between Iris fulva and I. brevicaulis in highly selective field conditions

The idea that natural hybridization has served as an important force in evolutionary and adaptive diversification has gained considerable momentum in recent years. By combining genome analyses with a highly selective field experiment, we provide evidence for adaptive trait introgression between two naturally hybridizing Louisiana Iris species, flood-tolerant Iris fulva and dry-adapted I. brevicaulis. We planted reciprocal backcross (BC1) hybrids along with pure-species plants into natural settings that, due to a flooding event, favored I. fulva. As expected, I. fulva plants survived at much higher rates than I. brevicaulis plants. Backcross hybrids toward I. fulva (BCIF) also survived at significantly higher rates than the reciprocal backcross toward I. brevicaulis (BCIB). Survivorship of BCIB hybrids was strongly influenced by the presence of a number of introgressed I. fulva alleles located throughout the genome, while survivorship in the reciprocal BCIF hybrids was heavily influenced by two epistatically acting QTL of opposite effects. These results demonstrate the potential for adaptive trait introgression between these two species and may help to explain patterns of genetic variation observed in naturally occurring hybrid zones.     

Genetic architecture of species differences in annual sunflowers: implications for adaptive trait introgression.

Genetic architecture may profoundly influence the ability of adaptive traits to spread between species via introgressive hybridization. Here, we examine the genomic location of quantitative trait loci (QTL) associated with pollen sterility and morphological traits distinguishing two annual sunflowers, Helianthus annuus and H. debilis ssp. cucumerifolius. These species are of particular interest since they hybridize naturally, and the form of H. annuus in Texas (called ssp. texanus) is thought to have arisen through introgression. Analysis of 226 BC(1) progeny from a cross between H. annuus and H. debilis revealed 56 QTL for 15 morphological traits and 2 QTL for pollen sterility. Four morphological QTL are tightly linked (<10 cM) to one or more sterility factors and 7 are closely allied with underrepresented and presumably negatively selected chromosomal blocks. Although these 11 QTL seem unlikely to move between the species, no barrier to introgression was detected for the remaining 45 morphological QTL. In fact, due to widespread pleiotropy (or tight linkage), the introgression of just three small chromosomal blocks appears sufficient to largely recover the phenotype of ssp. texanus. Subsequent work will test for the occurrence and fitness consequences of the identified QTL in natural populations of ssp. texanus.     

Hereditary spastic paraplegia: LOD-score considerations for confirmation of linkage in a heterogeneous trait.

Hereditary spastic paraplegia (HSP) is a degenerative disorder of the motor system, defined by progressive weakness and spasticity of the lower limbs. HSP may be inherited as an autosomal dominant (AD), autosomal recessive, or an X-linked trait. AD HSP is genetically heterogeneous, and three loci have been identified so far: SPG3 maps to chromosome 14q, SPG4 to 2p, and SPG4a to 15q. We have undertaken linkage analysis with 21 uncomplicated AD families to the three AD HSP loci. We report significant linkage for three of our families to the SPG4 locus and exclude several families by multipoint linkage. We used linkage information from several different research teams to evaluate the statistical probability of linkage to the SPG4 locus for uncomplicated AD HSP families and established the critical LOD-score value necessary for confirmation of linkage to the SPG4 locus from Bayesian statistics. In addition, we calculated the empirical P-values for the LOD scores obtained with all families with computer simulation methods. Power to detect significant linkage, as well as type I error probabilities, were evaluated. This combined analytical approach permitted conclusive linkage analyses on small to medium-size families, under the restrictions of genetic heterogeneity.     

Heterogeneity for multiple disease loci in linkage analysis.

Many mendelian traits show heterogeneity; that is, the disease phenotype in different families may be caused by genes at different locations. In linkage analysis, this admixture type of heterogeneity (locus heterogeneity) has often been accommodated with one of the HOMOG programs, which thus far have been restricted to at most two disease gene locations. Here, an extension to an arbitrary number of disease locations is described. It has been implemented in a computer program, HOMOGM. This approach is also suitable as an approximation to the situation of complex traits, in which multiple disease genes may occur in the same family.     

Variance components models for gene-environment interaction in quantitative trait locus linkage analysis.

Gene-environment interaction (G x E) is likely to be a common and important source of variation for complex behavioral traits. Gene-environment interaction, or genetic control of sensitivity to the environment, can be incorporated into variance components twin and sib-pair analyses by partitioning genetic effects into a mean part, which is independent of the environment, and a part that is a linear function of the environment. An approach described in a companion paper (Purcell, 2002) is applied to sib-pair variance components linkage analysis in two ways: allowing for quantitative trait locus by environment interaction and utilizing information on any residual interactions detected prior to analysis. As well as elucidating environmental pathways, consideration of G x E in quantitative and molecular studies will potentially direct and enhance gene-mapping efforts.     

A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. II. A simulation study

A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single markers was implemented via Markov Chain Monte Carlo (MCMC) algorithms for parameter estimation and hypothesis testing. Parameters were estimated by marginal posterior means computed with a Gibbs sampler with data augmentation. Variables sampled included the augmented data (marker-QTL genotypes, polygenic effects), the event of linkage or nonlinkage, and the parameters (allele frequencies, QTL substitution effect, recombination rate, polygenic and residual variances). The analysis was evaluated empirically via application to simulated granddaughter designs consisting of 2000 sons, 20 related sires and their ancestors. Results obtained in this study and preliminary work on multiple linked markers and multiple QTLs support the usefulness of the Bayesian method for the statistical mapping of QTLs.     

Optimized CRISPR/Cas9 strategy for homology-directed multiple targeted integration of transgenes in CHO cells

Site-specific integration has emerged as a promising strategy for precise Chinese hamster ovary (CHO) cell line engineering and predictable cell line development (CLD). CRISPR/Cas9 with the homology-directed repair (HDR) pathway enables precise integration of transgenes into target genomic sites. However, inherent recalcitrance to HDR-mediated targeted integration (TI) of transgenes results in low targeting efficiency, thus requiring a selection process to find a targeted integrant in CHO cells. Here, we explored several parameters that influence the targeting efficiency using a promoter-trap-based single- or double-knock-in (KI) monitoring system. A simple change in the donor template design by the addition of single-guide RNA recognition sequences strongly increased KI efficiency (2.9–36.0 fold), depending on integration sites and cell culture mode, compared to conventional circular donor plasmids. Furthermore, sequential and simultaneous KI strategies enabled us to obtain populations with ~1–4% of double-KI cells without additional enrichment procedures. Thus, this simple optimized strategy not only allows efficient CRISPR/Cas9-mediated TI in CHO cells but also paves the way for the applicability of multiplexed KIs in one experimental step without the need for sequential and independent CHO–CLD procedures.     

Not everything that counts can be counted: ants use multiple metrics for a single nest trait

There are claims in the literature that certain insects can count. We question the generality of these claims and suggest that summation rather than counting (sensu stricto) is a more likely explanation. We show that Temnothorax albipennis ant colonies can discriminate between potential nest sites with different numbers of entrances. However, our experiments suggest that the ants use ambient light levels within the nest cavity to assess the abundance of nest entrances rather than counting per se. Intriguingly, Weber's Law cannot explain the ants' inaccuracy. The ants also use a second metric, independent of light, to assess and discriminate against wide entrances. Thus, these ants use at least two metrics to evaluate one nest trait: the configuration of the portals to their potential homes.     

Sample-size considerations and strategies for linkage analysis in autosomal recessive disorders.

The opportunity raised by recombinant DNA technology to develop a linkage marker panel that spans the human genome requires cost-efficient strategies for its optimal utilization. Questions arise as to whether it is more cost-effective to convert a dimorphic restriction enzyme marker system into a highly polymorphic system or, instead, to increase the number of families studied, simply using the available marker alleles. The choice is highly dependent on the population available for study, and, therefore, an examination of the informational content of the various family structures is important to obtain the most informative data. To guide such decisions, we have developed tables of the average sample number of families required to detect linkage for autosomal recessive disorders under single backcross and under "fully informative" matings. The latter cross consists of a marker locus with highly polymorphic codominant alleles such that the parental marker genotypes can be uniquely distinguished. The sampling scheme considers families with unaffected parents of known mating types ascertained via affected offspring, for sibship sizes ranging from two to four and various numbers of affected individuals. The sample-size tables, calculated for various values of the recombination fractions and lod scores, may serve as a guide to a more efficient application of the restriction fragment length polymorphism technology to sequential linkage analysis.     

The coexistence of multiple receptors in a single nerve terminal provides evidence for pre-synaptic integration

Excitatory synaptic transmission is inhibited by G protein coupled receptors, including the adenosine A₁, GABA_B, and metabotropic glutamate receptor 7. These receptors are present in nerve terminals where they reduce the release of glutamate through activating signaling pathways negatively coupled to Ca²⁺ channels and adenylyl cyclase. However, it is not clear whether these receptors operate in distinct subpopulations of nerve terminals or if they are co-expressed in the same nerve terminals, despite the functional consequences that such distributions may have on synaptic transmission. Applying Ca²⁺ imaging and immunocytochemistry, we show that these three G protein coupled receptors coexist in a subpopulation of cerebrocortical nerve terminals. The three receptors share an intracellular signaling pathway through which their inhibitory responses are integrated and coactivation of these receptors produced an integrated response. Indeed, this response was highly variable, from a synergistic response at subthreshold agonist concentrations to an occluded response at high agonist concentrations. The presence of multiple receptors in a nerve terminal could be responsible for the physiological effects of neurotransmitter spillover from neighboring synapses or alternatively, the co-release of transmitters by the same nerve terminal.     

Selecting pedigrees for linkage analysis of a quantitative trait: the expected number of informative meioses.

With evidence of segregation at a major locus for a quantitative trait having been found, a logical next step is to select a subset of the pedigrees to include in a linkage study to map the major locus. Ideally this subset should include much of the linkage information in the sample but include only a fraction of the pedigrees. We previously described a strategy for selecting pedigrees for linkage analysis of a quantitative trait on the basis of a pedigree likelihood-ratio statistic. For quantitative traits controlled by a major locus with a rare dominant allele, the likelihood-ratio strategy extracted nearly all the information for linkage while typically requiring marker data on only about one-third of the pedigrees. Here, we describe a new strategy to select pedigrees for linkage analysis on the basis of the expected number of potentially informative meioses in each pedigree. We demonstrate that this informative-meioses strategy provides an efficient and more general means to select pedigrees for a linkage study of a quantitative trait.     

Mapping quantitative trait loci (QTL) in sheep. I. A new male framework linkage map and QTL for growth rate and body weight

A male sheep linkage map comprising 191 microsatellites was generated from a single family of 510 Awassi-Merino backcross progeny. Except for ovine chromosomes 1, 2, 10 and 17, all other chromosomes yielded a LOD score difference greater than 3.0 between the best and second-best map order. The map is on average 11% longer than the Sheep Linkage Map v4.7 male-specific map. This map was employed in quantitative trait loci (QTL) analyses on body-weight and growth-rate traits between birth and 98 weeks of age. A custom maximum likelihood program was developed to map QTL in half-sib families for non-inbred strains (QTL-MLE) and is freely available on request. The new analysis package offers the advantage of enabling QTL × fixed effect interactions to be included in the model. Fifty-four putative QTL were identified on nine chromosomes. Significant QTL with sex-specific effects (i.e. QTL × sex interaction) in the range of 0.4 to 0.7 SD were found on ovine chromosomes 1, 3, 6, 11, 21, 23, 24 and 26.     

A linkage strategy for detection of human quantitative-trait loci. I. Generalized relative risk ratios and power of sib pairs with extreme trait values.

We generalize the concept of the relative risk ratio (lambda) to the case of quantitative traits, to take into account the various trait outcomes of a relative pair. Formulas are derived to express the expected proportions of genes shared identical by descent by a sib pair, in terms of the generalized lambda's for sib pairs (lambda S), parent-offspring pairs (lambda O), and monozygotic twins (lambda M) and in terms of the recombination fraction, with the assumption of no residual correlations. If residual correlations are nonzero among relative pairs, we assume that they are the same among sib pairs, parent-offspring pairs, and monozygotic twins, and we employ a slightly different definition for the generalized lambda so that the same set of formulas still hold. The power (or, the sample size necessary) to detect quantitative-trait loci (QTLs) by use of extreme sib pairs (ESPs) is shown to be a function of the three generalized lambda's. Since lambda M can be derived by use of values of lambda S and lambda O, estimates of the latter two lambda's will suffice for the analysis of power and the necessary sample sizes of ESPs, for a QTL linkage study.     

Multipoint linkage analysis in neurofibromatosis type I: an international collaboration.

In addition to reporting, in accompanying papers, their individual analyses of mapping the neurofibromatosis type 1 (NF1) gene on chromosome 17, members of the International Consortium for NF1 Linkage contributed their data for our joint analysis to determine the exact sequence of flanking markers and to obtain precise estimates and confidence limits of the recombination fractions for the closest markers, in anticipation of clinical use. With specimens from 142 families and more than 700 affected persons, eight teams used 31 markers in the pericentric region of chromosome 17 to perform 13,838 genotypings. With the combined data, we used the computer program CRI-MAP to build the most likely sequence of loci by sequentially adding single loci to a fixed pair of loci and separately calculating the likelihood of all permutations of four consecutive loci. The best order is pter-pA10-41-EW301-centromere (p17H8)-pHHH202-NF1-EW206-EW207-EW203++ +-CRI-L581-CRI-L946-HOX2-NGFR-qter. The total genetic distance from pA10-41 to NGFR is 26 cM in males and 56 cM in females, and the overall difference in sex-specific maps is statistically significant (P = .006). The upper 99% confidence limits of the recombination fraction of the closest proximal marker, pHHH202, is 4%, and that for the closest distal marker, EW206, is 9%. These limits should decrease with the use of additional probes and the further evaluation of DNA from the six persons showing multiple recombinations within short genetic distances. Clinical application is technically feasible with currently available markers, although its appropriate use for prenatal and presymptomatic diagnosis requires further discussion and evaluation.     

A general statistical framework for mapping quantitative trait loci in nonmodel systems: issue for characterizing linkage phases

Because of uncertainty about linkage phases of founders, linkage mapping in nonmodel, outcrossing systems using molecular markers presents one of the major statistical challenges in genetic research. In this article, we devise a statistical method for mapping QTL affecting a complex trait by incorporating all possible QTL-marker linkage phases within a mapping framework. The advantage of this model is the simultaneous estimation of linkage phases and QTL location and effect parameters. These estimates are obtained through maximum-likelihood methods implemented with the EM algorithm. Extensive simulation studies are performed to investigate the statistical properties of our model. In a case study from a forest tree, this model has successfully identified a significant QTL affecting wood density. Also, the probability of the linkage phase between this QTL and its flanking markers is estimated. The implications of our model and its extension to more general circumstances are discussed.