Genetic analysis of inbreeding depression in plus tree 850.55 of Pinus radiata D. Don. I. Genetic map with distorted markers

 A genetic map of Pinus radiata plus tree 850.55 was constructed using megagametophytes of S₁ seeds. The map contained 19 linkage groups, with 168 RAPD and four microsatellite markers. The total map length was 1116.7 cM (Kosambi’s function) and was estimated to cover 56% of the genome. Of the 172 markers, 59 (34%) were distorted from the expected 1 : 1 ratio in megagametophytes (P<0.05). We show that if the distortion is caused by a single viability gene or by sampling error, the estimate of recombination frequency in megagametophytes of selfed seeds would not be affected. Received: 20 April 1998 / Accepted: 13 July 1998     

Maximum-likelihood models for mapping genetic markers showing segregation distortion. 1. Backcross populations

A maximum-likelihood approach is used in order to estimate recombination fractions between markers showing segregation distortion in backcross populations. It is assumed that the distortions are induced by viability differences between gametes or zygotes due to one or more selected genes. We show that Bailey's (1949) estimate stays consistent and efficient under more general assumptions than those defined by its author. This estimate should therefore be used instead of the classical maximum-likelihood estimate. The question of detection of linkage is also discussed. We show that the order of markers on linkage groups may be affected by segregation distortion.     

Interspecific genetic linkage map, segregation distortion and genetic conversion in coffee (Coffea sp.)

An interspecific partial genetic linkage map of Coffea sp. based on 62 backcross hybrids is presented. F₁ hybrids were generated by a cross between the wild C. pseudozanguebariae and the anciently cultivated C. liberica var. dewevrei (DEW); progeny were then derived from a backcross between F₁ hybrid and DEW. The map construction consisted of a two-step strategy using 5.5 and 3.1 LOD scores revealed by simulation file. The map consisted of 181 loci: 167 amplified fragment length polymorphism (AFLP) and 13 random fragment length polymorphism (RFLP) loci. The markers were assembled into 14 linkage groups, each with 4–31 markers covering 1,144 cM. Segregation distortion was observed for 30% of all loci, in particular 3:1 and 1:3 ratios equally favouring each of the two parents. The existence of such ratios suggests genetic conversion events. This map also represents an initial step towards the detection of quantitative trait loci. Received: 4 Janaury 2000 / Accepted: 17 January 2000     

An informative linkage map of soybean reveals QTLs for flowering time, leaflet morphology and regions of segregation distortion.

A genetic linkage map covering a large region of the genome with informative markers is essential for plant genome analysis, including identification of quantitative trait loci (QTLs), map-based cloning, and construction of a physical map. We constructed a soybean genetic linkage map using 190 F2 plants derived from a single cross between the soybean varieties Misuzudaizu and Moshidou Gong 503, based on restriction-fragment-length polymorphisms (RFLPs) and simple-sequence-repeat polymorphisms (SSRPs). This linkage map has 503 markers, including 189 RFLP markers derived from expressed sequence tag (EST) clones, and consists of 20 major linkage groups that may correspond to the 20 pairs of soybean chromosomes, covering 2908.7 cM of the soybean genome in the Kosambi function. Using this linkage map, we identified 4 QTLs--FT1, FT2, FT3, and FT4--for flowering time, the QTLs for the 5 largest principal components determining leaflet shape, 6 QTLs for single leaflet area, and 18 regions of segregation distortion. All 503 analyzed markers identified were located on the map, and almost all phenotypic variations in flowering time were explained by the detected QTLs. These results indicate that this map covers a large region of the soybean genome.     

Modeling the effect of inbreeding among founders in linkage analysis

In this paper, we present a unified mathematical model for linkage analysis that allows for inbreeding among founders in all families. The identical by descent (IBD) configuration of each pedigree is modeled as a Markov process containing two parameters; the inverse inbreeding and kinship coefficient and a rate parameter proportional to the inverse expected length of chromosome segments shared IBD by two different founder haplotypes. We use hidden Markov models and define a forward-backward algorithm for computing the conditional IBD-distribution given marker data, thereby extending the multipoint method of Lander and Green [1987. Construction of multilocus genetic maps in humans, Proc. Natl. Acad. Sci. USA 84, 2363-2367] to situations where founders are inbred. Our methodology is valid for arbitrary pedigree structures. Simulation and theoretical approximations for nonparametric linkage (NPL) analysis based on affected sib pairs reveal that NPL scores are inflated and type 1 errors increased when the inbreeding coefficient or rate parameter is underestimated. When the parents are genotyped, we present a general way of modifying the score function to drastically reduce this effect.     

Maximum-likelihood models for mapping genetic markers showing segregation distortion. 2. F2 populations

In F₂ populations, gametic and zygotic selection may affect the analysis of linkage in different ways. Therefore, specific likelihood equations have to be developed for each case, including dominant and codominant markers. The asymptotic bias of the classical estimates are derived for each case, in order to compare them with the standard errors of the suggested estimates. We discuss the utility and the efficiency of a previous model developed for dominant markers. We show that dominant markers provide very poor information in the case of segregation distortion and, therefore, should be used with circumspection. On the other hand, the estimation of recombination fractions between codominant markers is less affected by selection than is that for dominant markers. We also discuss the analysis of linkage between dominant and codominant markers.     

Genetic linkage maps of rose constructed with new microsatellite markers and locating QTL controlling flowering traits

New microsatellites markers [simple sequence repeat (SSR)] have been isolated from rose and integrated into an existing amplified fragment-length polymorphism genetic map. This new map was used to identify quantitative trait locus (QTL) controlling date of flowering and number of petals. From a rose bud expressed sequence tag (EST) database of 2,556 unigenes and a rose genomic library, 44 EST-SSRs and 20 genomic-SSR markers were developed, respectively. These new rose SSRs were used to expand genetic maps of the rose interspecific F₁ progeny. In addition, SSRs from other Rosaceae genera were also tested in the mapping progeny. Genetic maps for the two parents of the progeny were constructed using pseudo-testcross mapping strategy. The maps consist of seven linkage groups of 105 markers covering 432 cM for the maternal map and 136 markers covering 438 cM for the paternal map. Homologous relationships among linkage groups between the maternal and paternal maps were established using SSR markers. Loci controlling flowering traits were localised on genetic maps as a major gene and QTL for the number of petals and a QTL for the blooming date. New SSR markers developed in this study will provide tools for the establishment of a consensus linkage map for roses that combine traits and markers in various rose genetic maps.     

An integrative genetic linkage map of winter wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

We constructed a genetic linkage map based on a cross between two Swiss winter wheat (Triticum aestivum L.) varieties, Arina and Forno. Two-hundred and forty F₅ single-seed descent (SSD)-derived lines were analysed with 112 restriction fragment length polymorphism (RFLP) anonymous probes, 18 wheat cDNA clones coding for putative stress or defence-related proteins and 179 simple-sequence repeat (SSR) primer-pairs. The 309 markers revealed 396 segregating loci. Linkage analysis defined 27 linkage groups that could all be assigned to chromosomes or chromosome arms. The resulting genetic map comprises 380 loci and spans 3,086 cM with 1,131 cM for the A genome, 920 cM for the B genome and 1,036 cM for the D genome. Seventeen percent of the loci showed a significant (P < 0.05) deviation from a 1:1 ratio, most of them in favour of the Arina alleles. This map enabled the mapping of QTLs for resistance against several fungal diseases such as Stagonospora glume blotch, leaf rust and Fusarium head blight. It will also be very useful for wheat genetic mapping, as it combines RFLP and SSR markers that were previously located on separate maps. S. Paillard and T. Schnurbusch contributed equally to the work     

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.     

Estimating temporally variable selection intensity from ancient DNA data with the flexibility of modelling linkage and epistasis

Innovations in ancient DNA (aDNA) preparation and sequencing technologies have exponentially increased the quality and quantity of aDNA data extracted from ancient biological materials. The additional temporal component from the incoming aDNA data can provide improved power to address fundamental evolutionary questions like characterizing selection processes that shape the phenotypes and genotypes of contemporary populations or species. However, utilizing aDNA to study past selection processes still involves considerable hurdles like how to eliminate the confounding factor of genetic interactions in the inference of selection. To address this issue, we extend the approach of He et al., 2023 to infer temporally variable selection from the aDNA data in the form of genotype likelihoods with the flexibility of modelling linkage and epistasis in this work. Our posterior computation is carried out by a robust adaptive version of the particle marginal Metropolis-Hastings algorithm with a coerced acceptance rate. Our extension inherits the desirable features of He et al., 2023 such as modelling sample uncertainty resulting from the damage and fragmentation of aDNA molecules and reconstructing underlying gamete frequency trajectories of the population. We evaluate its performance through extensive simulations and show its utility with an application to the aDNA data from pigmentation loci in horses.     

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.     

Construction of a cucumber genetic linkage map with SRAP markers and location of the genes for lateral branch traits

Using SRAP (sequence-related amplified polymorphism) markers a genetic linkage map of cucumber was constructed with a population consisting of 138 F₂ individuals derived from a cross of the two cucumber lines, S06 and S52. In the survey of parental polymorphisms with 182 primer combinations, 64 polymorphism-revealing primer pairs were screened out, which generated totally 108 polymorphic bands with an average of 1.7 bands per primer pair and at most 6 bands from one primer pair. The constructed molecular linkage map included 92 loci, distributed in seven linkage groups and spanning 1164.2 cM in length with an average genetic distance of 12.6 cM between two neighboring loci. Based on this linkage map, the quantitative trait loci (QTL) for the lateral branch number (lbn) and the lateral branch average length (lbl) in cucumber were identified by QTLMapper1.6. A major QTL lbn1 located between ME11SA4B and ME5EM5 in LG2 could explain 10.63% of the total variation with its positively effecting allele from S06. A major QTL lbl1 located between DC1OD3 and DC1EM14 in LG2 could account for 10.38% of the total variation with its positively effecting allele from S₀₆.     

Construction of a cucumber genetic linkage map with SRAP markers and location of the genes for lateral branch traits

Cucumber (Cucumis sativus L. 2n = 2x = 14), thatbelongs to Cucurbitaceae family, is one of majorvegetables with a planting area second to that of to-mato in the world[1]. Due to its economical importanceplant breeders and geneticists have paid much atten-tion to the genetic study on this important vegetablecrop, but the research progress in cucumber is muchless than that in tomato. In 1990, Pierce[2] reviewed allthe reported genes of cucumber that had been geneti-cally analyzed since the 1930…     

Genetic dissection of a modern sugarcane cultivar (Saccharum spp.). I. Genome mapping with AFLP markers

Sugarcane cultivars are polyploid, aneuploid clones derived from interspecific hybridization between Saccharum officinarum and S. spontaneum. Their genome has recently started to be unravelled as a result of the development of molecular markers. We constructed an AFLP genetic map based on a selfing population of a specific cultivar, R570.Using 37 AFLP primer pairs, we detected 1,185 polymorphic markers of which 939 were simplex (segregated 3:1); these were used to construct the map. Of those 939, 887 were distributed on 120 cosegregation groups (CGs) based on linkages in coupling, while 52 remained unlinked. The cumulative length of all the groups was 5,849 cM, which is probably around one-third of the total genome length. Comparison with reference S. officinarum clones enabled us to assign 11 and 79 CGs to S. spontaneum and S. officinarum,respectively, whereas 11 CGs were probably derived from recombination between chromosomes of the two ancestral species. The patchy size of the groups, which ranges from 1 to 232 cM, illustrates the difficulty to access large portions of chromosomes, particularly those inherited from S. officinarum. Repulsion phase linkages suggested a high preferential pairing for 13 CG pairs. Out of the 120 CGs, 34 could be assigned to one of the 10 homo(eo)logy groups already defined in a previous RFLP map owing to the use of a small common marker set. The genome coverage was significantly increased in the map reported here. Implications for quantitative trait loci (QTL) research and marker-assisted breeding perspectives are discussed. Received: 31 August 2000 / Accepted: 16 October 2000