Construction of a 10,000-marker ultradense genetic recombination map of potato: providing a framework for accelerated gene isolation and a genomewide physical map

An ultradense genetic linkage map with >10,000 AFLP loci was constructed from a heterozygous diploid potato population. To our knowledge, this is the densest meiotic recombination map ever constructed. A fast marker-ordering algorithm was used, based on the minimization of the total number of recombination events within a given marker order in combination with genotyping error-detection software. This resulted in "skeleton bin maps," which can be viewed as the most parsimonious marker order. The unit of distance is not expressed in centimorgans but in "bins." A bin is a position on the genetic map with a unique segregation pattern that is separated from adjacent bins by a single recombination event. Putative centromeres were identified by a strong clustering of markers, probably due to cold spots for recombination. Conversely, recombination hot spots resulted in large intervals of up to 15 cM without markers. The current level of marker saturation suggests that marker density is proportional to physical distance and independent of recombination frequency. Most chromatids (92%) recombined once or never, suggesting strong chiasma interference. Absolute chiasma interference within a chromosome arm could not be demonstrated. Two examples of contig construction and map-based cloning have demonstrated that the marker spacing was in accordance with the expected physical distance: approximately one marker per BAC length. Currently, the markers are used for genetic anchoring of a physical map of potato to deliver a sequence-ready minimal tiling path of BAC contigs of specific chromosomal regions for the potato genome sequencing consortium (http://www.potatogenome.net).     

Genetic Mapping and Genomic Selection Using Recombination Breakpoint Data

The correct models for quantitative trait locus mapping are the ones that simultaneously include all significant genetic effects. Such models are difficult to handle for high marker density. Improving statistical methods for high-dimensional data appears to have reached a plateau. Alternative approaches must be explored to break the bottleneck of genomic data analysis. The fact that all markers are located in a few chromosomes of the genome leads to linkage disequilibrium among markers. This suggests that dimension reduction can also be achieved through data manipulation. High-density markers are used to infer recombination breakpoints, which then facilitate construction of bins. The bins are treated as new synthetic markers. The number of bins is always a manageable number, on the order of a few thousand. Using the bin data of a recombinant inbred line population of rice, we demonstrated genetic mapping, using all bins in a simultaneous manner. To facilitate genomic selection, we developed a method to create user-defined (artificial) bins, in which breakpoints are allowed within bins. Using eight traits of rice, we showed that artificial bin data analysis often improves the predictability compared with natural bin data analysis. Of the eight traits, three showed high predictability, two had intermediate predictability, and two had low predictability. A binary trait with a known gene had predictability near perfect. Genetic mapping using bin data points to a new direction of genomic data analysis.     

The development of a bin mapping population and the selective mapping of 103 markers in the diploid Fragaria reference map.

We have identified a set of plants (the bin set) to permit "selective" or "bin" mapping using the diploid strawberry mapping population FV x FN, derived from the F2 cross F. vesca 815 x F. nubicola 601, which has been used to develop the Fragaria reference map. The bin set consists of 8 plants: the F. vesca 815 parent, the F1 hybrid individual, and 6 seedlings of the F2 population. This bin set divides the 578 cM of the diploid Fragaria genome into 46 bins, the largest mapping bin being 26 cM in length and the average bin size being 12.6 cM. To validate the FV x FN bin set, we used it to locate 103 loci into bins on the FV x FN map. These loci comprised 61 previously described SSRs, 38 new SSRs developed in this investigation from Fragaria x ananassa genomic DNA, EST and gene sequences, and 4 ripening-related genes developed for Prunus. The 103 markers were located to bins on all 7 linkage groups of the Fragaria map and a new mapping bin was identified with the novel markers, demonstrating that the map covers the majority of the diploid Fragaria genome and that the 6 bin-set seedlings selected were appropriate for bin mapping using this progeny.     

A high-resolution map of the H1 locus harbouring resistance to the potato cyst nematode Globodera rostochiensis

The resistance gene H1 confers resistance to the potato cyst nematode Globodera rostochiensis and is located at the distal end of the long arm of chromosome V of potato. For marker enrichment of the H1 locus, a bulked segregant analysis (BSA) was carried out using 704 AFLP primer combinations. A second source of markers tightly linked to H1 is the ultra-high-density (UHD) genetic map of the potato cross SH × RH. This map has been produced with 387 AFLP primer combinations and consists of 10,365 AFLP markers in 1,118 bins (). Comparing these two methods revealed that BSA resulted in one marker/cM and the UHD map in four markers/cM in the H1 interval. Subsequently, a high-resolution genetic map of the H1 locus has been developed using a segregating F₁ SH × RH population consisting of 1,209 genotypes. Two PCR-based markers were designed at either side of the H1 gene to screen the 1,209 genotypes for recombination events. In the high-resolution genetic map, two of the four co-segregating AFLP markers could be separated from the H1 gene. Marker EM1 is located at a distance of 0.2 cM, and marker EM14 is located at a distance of 0.8 cM. The other two co-segregating markers CM1 (in coupling) and EM15 (in repulsion) could not be separated from the H1 gene.Communicated by J.G. Wenzel     

Microsatellite-based deletion bin system for the establishment of genetic-physical map relationships in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Because of polyploidy and large genome size, deletion stocks of bread wheat are an ideal material for physically allocating ESTs and genes to small chromosomal regions for targeted mapping. To enhance the utility of deletion stocks for chromosome bin mapping, we characterized a set of 84 deletion lines covering the 21 chromosomes of wheat using 725 microsatellites. We localized these microsatellite loci to 94 breakpoints in a homozygous state (88 distal deletions, 6 interstitial), and 5 in a heterozygous state representing 159 deletion bins. Chromosomes from homoeologous groups 2 and 5 were the best covered (126 and 125 microsatellites, respectively) while the coverage for group 4 was lower (80 microsatellites). We assigned at least one microsatellite in up to 92% of the bins (mean 4.97 SSR/bin). Only a few discrepancies concerning marker order were observed. The cytogenetic maps revealed small genetic distances over large physical regions around the centromeres and large genetic to physical map ratios close to the telomeres. As SSRs are the markers of choice for many genetic and breeding studies, the mapped microsatellite loci will be useful not only for deletion stock verifications but also for allocating associated QTLs to deletion bins where numerous ESTs that could be potential candidate genes are currently assigned.     

An infinitesimal model for quantitative trait genomic value prediction

We developed a marker based infinitesimal model for quantitative trait analysis. In contrast to the classical infinitesimal model, we now have new information about the segregation of every individual locus of the entire genome. Under this new model, we propose that the genetic effect of an individual locus is a function of the genome location (a continuous quantity). The overall genetic value of an individual is the weighted integral of the genetic effect function along the genome. Numerical integration is performed to find the integral, which requires partitioning the entire genome into a finite number of bins. Each bin may contain many markers. The integral is approximated by the weighted sum of all the bin effects. We now turn the problem of marker analysis into bin analysis so that the model dimension has decreased from a virtual infinity to a finite number of bins. This new approach can efficiently handle virtually unlimited number of markers without marker selection. The marker based infinitesimal model requires high linkage disequilibrium of all markers within a bin. For populations with low or no linkage disequilibrium, we develop an adaptive infinitesimal model. Both the original and the adaptive models are tested using simulated data as well as beef cattle data. The simulated data analysis shows that there is always an optimal number of bins at which the predictability of the bin model is much greater than the original marker analysis. Result of the beef cattle data analysis indicates that the bin model can increase the predictability from 10% (multiple marker analysis) to 33% (multiple bin analysis). The marker based infinitesimal model paves a way towards the solution of genetic mapping and genomic selection using the whole genome sequence data.     

ATG-anchored AFLP (ATG-AFLP) analysis in cotton

Amplified fragment length polymorphism (AFLP) marker system has had broad applications in biology. However, the anonymous AFLP markers are mainly amplified from non-coding regions, limiting their usefulness as a functional marker system. To take advantages of the traditional AFLP techniques, we propose substitution of a restriction enzyme that recognizes a restriction site containing ATG, called ATG-anchored AFLP (ATG-AFLP) analysis. In this study, we chose NsiI (recognizing ATGCAT) to replace EcoRI in combination with MseI to completely digest genomic DNA. One specific adaptor, one pre-selective primer and six selective amplification primers for the NsiI site were designed for ligation and PCR. Six NsiI and eight MseI primers generated a total of 1,780 ATG-AFLP fragments, of which 750 (42%) were polymorphic among four genotypes from two cultivated cotton species (Upland cotton, Gossypium hirsutum and Pima cotton, G. barbadense). The number of ATG-AFLP markers was sufficient to separate the four genotypes into two groups, consistent with their evolutionary and breeding history. Our results also showed that ATG-AFLP generated less number of total and polymorphic fragments per primer combination (2-3 vs. 4-5) than conventional AFLP within Upland cotton. Using a recombination inbred line (RIL) population, 62 polymorphic ATG-AFLP markers were mapped to 19 linkage groups with known chromosome anchored simple sequence repeat (SSR) markers. Of the nine ATG-AFLP fragments randomly chosen, three were found to be highly homologous to cotton cDNA sequences. An in-silico analysis of cotton and Arabidopsis cDNA confirmed that the ATG-anchored enzyme combination NsiI/MseI did generate more fragments than the EcoRI/MseI combination.     

Identification of RFLP markers linked to the H1 gene conferring resistance to the potato cyst nematode Globodera rostochiensis.

The H1 gene from Solanum tuberosum ssp. andigena confers high levels of resistance to the potato cyst nematode Globodera rostochiensis and is used extensively in potato breeding. Using a dihaploid segregating population, a search was conducted for linkage between this gene and markers on the potato/tomato RFLP map. A total of 60 RFLP markers covering the entire genome were screened on bulk resistant and susceptible segregants. Linkage was indicated for eight markers on chromosome 5. Individual plant analysis placed the closest marker, CD78, at a maximum map distance of 2.7 cM from H1. A molecular marker for the H1 should be useful both as a correlative screening tool for incorporation of resistance into new cultivars and as starting point for map-based cloning of this important gene.     

RFLP maps of potato and their alignment with the homoeologous tomato genome

Summary An RFLP linkage map of the potato is presented which comprises 304 loci derived from 230 DNA probes and one morphological marker (tuber skin color). The self-incompatibility locus of potato was mapped to chromosome I, which is homoeologous to tomato chromosome I. By mapping chromosome-specific tomato RFLP markers in potato and, vice versa, potato markers in tomato, the different potato and tomato RFLP maps were aligned to each other and the similarity of the potato and tomato genome was confirmed. The numbers given to the 12 potato chromosomes are now in accordance with the established tomato nomenclature. Comparisons between potato RFLP maps derived from different genetic backgrounds revealed conservation of marker order but differences in chromosome and total map length. In particular, significant reduction of map length was observed in interspecific compared to intraspecific crosses. The distribution of regions with distorted segregation ratios in the genome was analyzed for four potato parents. The most prominent distortion of recombination was found to be caused by the self-incompatibility locus.     

A high-density linkage map in <Emphasis Type="Italic">Brassica juncea</Emphasis> (Indian mustard) using AFLP and RFLP markers

A high-density genetic linkage map of Brassica juncea (2n = 36) was constructed with 996 AFLP (amplified fragment length polymorphism) and 33 RFLP (restriction fragment length polymorphism) markers using a F1-derived doubled-haploid (DH) population of 123 individuals. This mapping population was developed by crossing a well-adapted, extensively grown Indian variety Varuna and a canola quality line Heera. The two lines are highly divergent and contain a number of contrasting qualitative and quantitative traits of high agronomic value. AFLPs were generated by the use of restriction enzymes EcoRI or PstI in combination with either MseI or TaqI. Using 91 primer pairs, a total of 1,576 parental polymorphic bands were detected of which 996 were used for mapping. In addition, 33 RFLP markers, developed from genomic clones of B. napus, were added to the map. The segregation of each marker and linkage analysis was performed using the program JoinMap version 2.0. The 1,029 mapped-markers were aligned in 18 linkage groups, which is the haploid chromosome number of the species, at LOD values ranging from 5 to 8. The total map length was 1,629 cM with an average marker interval of 3.5 cM. AFLP markers generated by EcoRI were more clustered, whereas PstI markers showed more extensive distribution. A set of 26 primer pairs (9 EcoRI/ MseI, 6 EcoRI/ TaqI, 6 PstI/ MseI and 5 PstI/ TaqI) generating 385 markers were identified for AFLP-based whole-genome selection as these markers covered 96% of the genome mapped with the 91 primer pairs. The map developed in the present study could be used for dissection and the transfer of agronomically important traits and favourable QTLs from ill-adapted exotic germplasm to cultivated Indian varieties.     

QTL Scanning for Rice Yield Using a Whole Genome SNP Array

High-throughput SNP genotyping is widely used for plant genetic studies. Recently, a RICE6K SNP array has been developed based on the Illumina Bead Array platform and Infinium SNP assay technology for genome-wide evaluation of allelic variations and breeding applications. In this study, the RICE6K SNP array was used to genotype a recombinant inbred line （RIL） population derived from the cross between the indica variety, Zhenshan 97, and the japonica variety, Xizang 2. A total of 3324 SNP markers of high quality were identified and were grouped into 1495 recombination bins in the RIL population. A high-density linkage map, consisting of the 1495 bins, was developed, covering 1591.2 cM and with average length ofl.1 cM per bin. Segregation distortions were observed in 24 regions of the 11 chromosomes in the RILs. One half of the distorted regions contained fertility genes that had been previously reported. A total of 23 QTLs were identified for yield. Seven QTLs were firstly detected in this study. The positive alleles from about half of the identified QTLs came from Zhenshan 97 and they had lower phenotypic values than Xizang 2. This indicated that favorable alleles for breeding were dispersed in both parents and pyramiding favorable alleles could develop elite lines. The size of the mapping population for QTL analysis using high throughput SNP genotyping platform is also discussed.     

A population ‘consensus’, partial linkage map of Picea abies Karst. based on RAPD markers

 We built a “consensus” partial linkage map based on RAPD markers using 48 sibships of eight megagametophytes each from a natural population of Norway spruce. A RAPD linkage map for a single individual from the same population had previously been constructed. Using 30 random decamers that had yielded 83 RAPD markers in the single-tree map, eight megagametophytes for each of the 48 sibships were screened. The linkage relationship among markers was estimated considering each family of eight megagametophytes as a progeny of a phase-unknown backcross mating between a heterozygous mother and a fictitious ‘recessive’ father. Markers were assigned to windows using LOD=2.0 and θ=0.4 as thresholds, and ordered using a criterion of interval support ≥2.0. For eight “windows” of recombination selected on the single-tree map, we investigated the consistency of marker order in the two maps. We adopted restrictive criteria for rejecting co-linearity between the two locus orders. For each window we imposed the most likely locus order obtained from one data set to the other (and vice versa), obtaining two symmetrical log-likelihood differences. We considered the hypothesis of co-linearity rejected when both symmetrical differences were significant (ΔLOD>3.0). By bootstrapping a subset of markers for each window (highly informative, ‘framework’ loci chosen on the previous single-tree map using a matrix correlation method) the sampling variability of the single-tree and population maps was estimated. As expected the population map was affected by a larger variability than the single-tree map. Heterogeneity in pairwise recombination fractions among groups of sibship revealed a (possible) alternative genomic arrangement detected within a single recombination window. Received : 4 January 1997 / Accepted : 24 January 1997     

An ultradense genetic recombination map for <Emphasis Type="Italic">Brassica napus</Emphasis>, consisting of 13551 SRAP markers

Sequence related amplified polymorphism (SRAP) was used to construct an ultradense genetic recombination map for a doubled haploid (DH) population in B. napus. A total of 1,634 primer combinations including 12 fluorescently labeled primers and 442 unlabeled ones produced 13,551 mapped SRAP markers. All these SRAPs were assembled in 1,055 bins that were placed onto 19 linkage groups. Ten of the nineteen linkage groups were assigned to the A genome and the remaining nine to the C genome on the basis of the differential SRAP PCR amplification in two DH lines of B. rapa and B. oleracea. Furthermore, all 19 linkage groups were assigned to their corresponding N1–N19 groups of B. napus by comparison with 55 SSR markers used to construct previous maps in this species. In total, 1,663 crossovers were detected, resulting in a map length span of 1604.8 cM. The marker density is 8.45 SRAPs per cM, and there could be more than one marker in 100 kb physical distance. There are four linkage groups in the A genome with more than 800 SRAP markers each, and three linkage groups in the C genome with more 1,000 SRAP markers each. Our studies suggest that a single SRAP map might be applicable to the three Brassica species, B. napus, B. oleracea and B. rapa. The use of this ultra high-density genetic recombination map in marker development and map-based gene cloning is discussed. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A comparative genetic and cytogenetic mapping of wheat chromosome 5B using introgression lines

The genetic map of chromosome 5B has been constructed by using microsatellite (SSR) analysis of 381 plants from the F2 population produced by cross of the Chinese Spring (CS) and Renan cultivars. Initially, 180 SSR markers for the common wheat 5B chromosome have been used for analysis of these cultivars. The 32 markers able to detect polymorphism between these cultivars have been located on the genetic map of chromosome 5B. Cytogenetic mapping has involved a set of CS 5B chromosome deletion lines. Totally, 51 SSR markers have been located in ten regions (deletion bins) of this chromosome by SSR analysis of these deletion lines. Five genes—TaCBFIIIc-B10, Vrn-B1, Chi-B1, Skr, and Ph1—have been integrated into the cytogenetic map of chromosome 5B using the markers either specific of or tightly linked to the genes in question. Comparison of the genetic and cytogenetic maps suggests that recombination is suppressed in the pericentromeric region of chromosome 5B, especially in the short arm segment. The 18 markers localized to deletion bins 5BL16-0.79-1.00 and 5BL18-0.66-0.79 have been used to analyze common wheat introgression lines L842, L5366-180, L73/00i, and L21-4, carrying fragments of alien genomes in the terminal region of 5B long arm. L5366-180 and L842 lines carry a fragment of the Triticum timopheevii 5GL chromosome, while L73/00i and L21-4 lines, a fragment of the Aegilops speltoides 5SL chromosome. As has been shown, the translocated fragments in these four lines are of different lengths, allowing bin 5BL18-0.66-0.79 to be divided into three shorter regions. The utility of wheat introgression lines carrying alien translocations for increasing the resolution of cytogenetic mapping is discussed.     

Development of a Core RFLP Map in Maize Using an Immortalized F(2) Population

A map derived from restriction fragment length polymorphisms (RFLPs) in maize (Zea mays L.) is presented. The map was constructed in an immortalized Tx303 X CO159 F(2) mapping population that allowed for an unlimited number of markers to be mapped and pooled F(3) seed to be distributed to other laboratories. A total of 215 markers consisting of 159 genomic clones, 16 isozymes and 35 cloned genes of defined function have been placed on 10 chromosomes. An examination of segregation data has revealed several genomic regions with aberrant segregation ratios favoring either parent or the heterozygote. Mapping of cloned genes and isozymes that have been previously mapped by functional criteria has provided 29 points of alignment with the classical maize genetic map. Screening of all mapped RFLP probes against a collection of U.S. Corn Belt germplasm using EcoRI, HindIII and EcoRV has resulted in a set of 97 core markers being defined. The designation of a set of core markers allows the maize genome to be subdivided into a series of bins which serve as the backbone for maize genetic information and database boundaries. The merits and applications of core markers and bins are discussed.     

A 2600-locus chromosome bin map of wheat homoeologous group 2 reveals interstitial gene-rich islands and colinearity with rice

The complex hexaploid wheat genome offers many challenges for genomics research. Expressed sequence tags facilitate the analysis of gene-coding regions and provide a rich source of molecular markers for mapping and comparison with model organisms. The objectives of this study were to construct a high-density EST chromosome bin map of wheat homoeologous group 2 chromosomes to determine the distribution of ESTs, construct a consensus map of group 2 ESTs, investigate synteny, examine patterns of duplication, and assess the colinearity with rice of ESTs assigned to the group 2 consensus bin map. A total of 2600 loci generated from 1110 ESTs were mapped to group 2 chromosomes by Southern hybridization onto wheat aneuploid chromosome and deletion stocks. A consensus map was constructed of 552 ESTs mapping to more than one group 2 chromosome. Regions of high gene density in distal bins and low gene density in proximal bins were found. Two interstitial gene-rich islands flanked by relatively gene-poor regions on both the short and long arms and having good synteny with rice were discovered. The map locations of two ESTs indicated the possible presence of a small pericentric inversion on chromosome 2B. Wheat chromosome group 2 was shown to share syntenous blocks with rice chromosomes 4 and 7.     

Dynamic genetic features of chromosomes revealed by comparison of soybean genetic and sequence-based physical maps

Despite the intensive soybean [Glycine max (L.) Merrill] genome studies, the high chromosome number (20) of the soybean plant relative to many other major crops has hindered the development of a high-resolution genomewide genetic map derived from a single population. Here, we report such a map, which was constructed in an F₁₅ population derived from a cross between G. max and G. soja lines using indel polymorphisms detected via a G. soja genome resequencing. By targeting novel indel markers to marker-poor regions, all marker intervals were reduced to under 6 cM on a genome scale. Comparison of the Williams 82 soybean reference genome sequence and our genetic map indicated that marker orders of 26 regions were discrepant with each other. In addition, our comparison showed seven misplaced and two absent markers in the current Williams 82 assembly and six markers placed on the scaffolds that were not incorporated into the pseudomolecules. Then, we showed that, by determining the missing sequences located at the presumed beginning points of the five major discordant segments, these observed discordant regions are mostly errors in the Williams 82 assembly. Distributions of the recombination rates along the chromosomes were similar to those of other organisms. Genotyping of indel markers and genome resequencing of the two parental lines suggested that some marker-poor chromosomal regions may represent introgression regions, which appear to be prevalent in soybean. Given the even and dense distribution of markers, our genetic map can serve as a bridge between genomics research and breeding programs.