A linkage map of sugar beet (Beta vulgaris L.)

Summary We have established a first linkage map for beets based on RFLP, isozyme and morphological markers. The population studied consisted of 96 F₂ individuals derived from an intraspecific cross. As was expected for outbreeding species, a relatively high degree of polymorphism was found within sugar beet; 47% of the DNA markers were polymorphic for the chosen population. The map consists of 115 independent chromosomal loci designated by 108 genomic DNA probes, 6 isozyme and one morphological marker. The loci cover 789 cM with an average spacing of 6.9 cM. They are dispersed over nine linkage groups corresponding to the haploid chromosome number of Beta species. Eighteen markers (15.4%) showed distorted segregation which, in most instances, can be explained by gametic selection of linked lethal loci. The application of the linkage map in sugar beet breeding is discussed.     

Investigation of altering single-nucleotide polymorphism density on the power to detect trait loci and frequency of false positive in nonparametric linkage analyses of qualitative traits

Genome-wide linkage analysis using microsatellite markers has been successful in the identification of numerous Mendelian and complex disease loci. The recent availability of high-density single-nucleotide polymorphism (SNP) maps provides a potentially more powerful option. Using the simulated and Collaborative Study on the Genetics of Alcoholism (COGA) datasets from the Genetics Analysis Workshop 14 (GAW14), we examined how altering the density of SNP marker sets impacted the overall information content, the power to detect trait loci, and the number of false positive results. For the simulated data we used SNP maps with density of 0.3 cM, 1 cM, 2 cM, and 3 cM. For the COGA data we combined the marker sets from Illumina and Affymetrix to create a map with average density of 0.25 cM and then, using a sub-sample of these markers, created maps with density of 0.3 cM, 0.6 cM, 1 cM, 2 cM, and 3 cM. For each marker set, multipoint linkage analysis using MERLIN was performed for both dominant and recessive traits derived from marker loci. Our results showed that information content increased with increased map density. For the homogeneous, completely penetrant traits we created, there was only a modest difference in ability to detect trait loci. Additionally, as map density increased there was only a slight increase in the number of false positive results when there was linkage disequilibrium (LD) between markers. The presence of LD between markers may have led to an increased number of false positive regions but no clear relationship between regions of high LD and locations of false positive linkage signals was observed.     

High-Throughput RAD-SNP Genotyping for Characterization of Sugar Beet Genotypes

High-throughput single-nucleotide polymorphism (SNP) genotyping provides a rapid way of developing resourceful sets of markers for delineating genetic structure and for understanding the basis of the taxonomic discrimination. In this paper, we present a panel of 192 SNPs for effective genotyping in sugar beet using a high-throughput marker array technology, QuantStudio 12K Flex system, coupled with Taqman OpenArray technology. The selected SNPs were evaluated for genetic diversity among a set of 150 individuals representing 15 genotypes (10 individuals each) from five cytoplasmic male steriles (CMSs), five pollinators, and five commercial varieties. We demonstrated that the proposed panel of 192 SNPs effectively differentiated the studied genotypes. A higher degree of polymorphism was observed among the CMSs as compared to pollinators and commercial varieties. PCoA and STRUCTURE analysis revealed that CMSs, pollinators, and varieties clustered into three distinct subpopulations. Our results demonstrate the utility of the identified panel of 192 SNPs coupled with TaqMan OpenArray technology as a wide set of markers for high-throughput SNP genotyping in sugar beet.     

GinMicrosatDb: a genome-wide microsatellite markers database for sesame (<Emphasis Type="Italic">Sesamum indicum</Emphasis> L.)

Molecular breeding in sesame is still at infancy due to limited number of microsatellite markers available and the low level of polymorphism exhibited by them. Therefore, whole genome sequencing was used for development of microsatellite markers so as to ensure availability of substantial number of polymorphic markers for use in marker assisted breeding programs. Whole genome sequencing of sesame variety ‘Swetha’ was done using Illumina paired-end sequencing and Roche 454 shotgun sequencing technologies (GCA_000975565.1 in GenBank). ‘GinMicrosatDb’, a genome-wide microsatellite marker database has been developed using the whole genome sequence data of sesame variety ‘Swetha’. The database consists of microsatellites localized on both linkage groups and scaffolds with their genomic co-ordinates. It provides five sets of forward and reverse primers for each of the microsatellite loci along with the flanking sequences, primer GC content, product size and melting temperature etc. The distribution of microsatellites can be viewed and selected through a genome browser as well as through a physical map. The newly identified microsatellite markers are expected to help sesame breeders in developing marker tags for traits of economic importance thereby bringing about greater efficiency in marker-assisted selection programs.     

A high density RFLP linkage map of sugar beet.

A high density sugar beet RFLP map with an average distance of 1.5 cM between markers has been constructed. The map covers 621 cM and includes 413 markers distributed over the nine linkage groups of sugar beet. The map is based on two F2 populations representing two different pairs of parents. The two sets of data were integrated into a single map using 90 markers that were common to both data sets. The quality of the map was assessed in several ways. The common markers were used to investigate how often the loci had been mapped in the same order in the two F2 populations. For closely situated markers (<1.5 cM) the order specified in the map is uncertain, but for markers separated by more than 2 cM the locus order is highly reliable. The error rate of the overall process was estimated at 0.3% by independently repeating the analysis of 41 markers. The map is comparatively short, with a map length corresponding to approximately 1.4 crossovers per bivalent. Another feature of the map is a high degree of clustering of markers along the linkage groups. With the possible exception of linkage group 2, each linkage group shows one major cluster, which in most cases is situated in the centre of the linkage group. Our interpretation is that sugar beet, in comparison with most other species, has an extreme localization of recombination. Key words : sugar beet, linkage, RFLP, clustering.     

A sugar beet (Beta vulgaris L.) reference FISH karyotype for chromosome and chromosome‐arm identification,integration of genetic linkage groups and analysis of major repeat family distribution

We developed a reference karyotype for B. vulgaris which is applicable to all beet cultivars and provides a consistent numbering of chromosomes and genetic linkage groups. Linkage groups of sugar beet were assigned to physical chromosome arms by FISH (fluorescent in situ hybridization) using a set of 18 genetically anchored BAC (bacterial artificial chromosome) markers. Genetic maps of sugar beet were correlated to chromosome arms, and North–South orientation of linkage groups was established. The FISH karyotype provides a technical platform for genome studies and can be applied for numbering and identification of chromosomes in related wild beet species. The discrimination of all nine chromosomes by BAC probes enabled the study of chromosome‐specific distribution of the major repetitive components of sugar beet genome comprising pericentromeric, intercalary and subtelomeric satellites and 18S‐5.8S‐25S and 5S rRNA gene arrays. We developed a multicolor FISH procedure allowing the identification of all nine sugar beet chromosome pairs in a single hybridization using a pool of satellite DNA probes. Fiber‐FISH was applied to analyse five chromosome arms in which the furthermost genetic marker of the linkage group was mapped adjacently to terminal repetitive sequences on pachytene chromosomes. Only on two arms telomere arrays and the markers are physically linked, hence these linkage groups can be considered as terminally closed making the further identification of distal informative markers difficult. The results support genetic mapping by marker localization, the anchoring of contigs and scaffolds for the annotation of the sugar beet genome sequence and the analysis of the chromosomal distribution patterns of major families of repetitive DNA.     

Chromosomal assignment of the nine linkage groups of sugar beet (Beta vulgaris L.) using primary trisomics

 Twenty-four marker loci representing each of the nine linkage groups of sugar beet (Beta vulgaris) have been assigned to the nine primary trisomics of Butterfass (1964). Single-copy RFLP probes were hybridized with filter-bound DNA of the trisomics. The autoradiographs were scanned and analyzed by densitometric methods. Statistics on the integrated optical densities of the RFLP bands revealed a clear relationship of each linkage group to a distinct trisomic type. For the first time each of the linkage groups could unequivocally be assigned to one sugar beet chromosome. A standard nomenclature of the 9 chromosomes of sugar beet is suggested and discussed with respect to previous numbering systems. Received: 27 February 1997/Accepted: 7 March 1997     

RFLP markers for sugar beet breeding: chromosomal linkage maps and location of major genes for rhizomania resistance, monogermy and hypocotyl colour

An RFLP linkage map for the nine chromosomes of sugar beet (Beta vulgaris L. ssp. vulgaris var. altissima Doell) was constructed by using a segregating population from a cross between two plants which were heterozygous for several agronomically interesting characters. One hundred and eleven RFLP loci have been mapped to nine linkage groups using 92 genomic markers. The current RFLP map covers a total length of 540 cM. Evidence for the existence of a major gene for rhizomania resistance (Rr1) is given, together with its map position on linkage group IV in the interval between loci GS44 and GS28a. The presence of an RFLP fragment at the GS3d locus is, until now, the best molecular marker for rhizomania-resistant genotypes in segregating populations of sugar beet; GS3d is linked to Rr1 with 6.7 cM. The gene MM, controlling the polygerm/monogerm seed type, has been mapped on linkage group IX in a distal position at 4.2 cM from the locus GS7. The gene R controlling the hypocotyl colour maps to linkage group VII and does not recombine with the RFLP locus GS42. The inheritance of a group of RFLP loci revealed the possible presence of a translocation in the population used to establish the map. The data presented are discussed in relation to the possibility of using RFLP markers in sugar beet breeding.     

Genome-wide linkage analysis for alcohol dependence: a comparison between single-nucleotide polymorphism and microsatellite marker assays

Both theoretical and applied studies have proven that the utility of single nucleotide polymorphism (SNP) markers in linkage analysis is more powerful and cost-effective than current microsatellite marker assays. Here we performed a whole-genome scan on 115 White, non-Hispanic families segregating for alcohol dependence, using one 10.3-cM microsatellite marker set and two SNP data sets (0.33-cM, 0.78-cM spacing). Two definitions of alcohol dependence (ALDX1 and ALDX2) were used. Our multipoint nonparametric linkage analysis found alcoholism was nominal linked to 12 genomic regions. The linkage peaks obtained by using the microsatellite marker set and the two SNP sets had a high degree of correspondence in general, but the microsatellite marker set was insufficient to detect some nominal linkage peaks. The presence of linkage disequilibrium between markers did not significantly affect the results. Across the entire genome, SNP datasets had a much higher average linkage information content (0.33 cM: 0.93, 0.78 cM: 0.91) than did microsatellite marker set (0.57). The linkage peaks obtained through two SNP datasets were very similar with some minor differences. We conclude that genome-wide linkage analysis by using approximately 5,000 SNP markers evenly distributed across the human genome is sufficient and might be more powerful than current 10-cM microsatellite marker assays.     

Genetic localization of four genes for nematode (Heterodera schachtii Schm.) resistance in sugar beet (Beta vulgaris L.)

Sugar beet (Beta vulgaris L.) is highly susceptible to the beet cyst nematode (Heterodera schachtii Schm.). Three resistance genes originating from the wild beets B. procumbens (Hs1 ^pro-1) and B. webbiana (Hs1 ^web-1, Hs2 ^web-7) have been transferred to sugar beet via species hybridization. We describe the genetic localization of the nematode resistance genes in four different sugar beet lines using segregating F₂ populations and RFLP markers from our current sugar beet linkage map. The mapping studies yielded a surprising result. Although the four parental lines carrying the wild beet translocations were not related to each other, the four genes mapped to the same locus in sugar beet independent of the original translocation event. Close linkage (0–4.6 cM) was found with marker loci at one end of linkage group IV. In two populations, RFLP loci showed segregation distortion due to gametic selection. For the first time, the non-randomness of the translocation process promoting gene transfer from the wild beet to the sugar beet is demonstrated. The data suggest that the resistance genes were incorporated into the sugar beet chromosomes by non-allelic homologous recombination. The finding that the different resistance genes are allelic will have major implications on future attempts to breed sugar beet combining the different resistance genes.     

Development of single nucleotide polymorphism markers in <Emphasis Type="Italic">Theobroma cacao</Emphasis> and comparison to simple sequence repeat markers for genotyping of Cameroon clones

Single nucleotide polymorphism (SNP) markers are increasingly being used in crop breeding programs, slowly replacing simple sequence repeats (SSR) and other markers. SNPs provide many benefits over SSRs, including ease of analysis and unambiguous results across various platforms. We have identified and mapped SNP markers in the tropical tree crop Theobroma cacao, and here we compare SNPs to SSRs for the purpose of determining off-types in clonal collections. Clones are used as parents in breeding programs and the presence of mislabeled clones (off-types) can lead to the propagation of undesired traits and limit genetic gain from selection. Screening was performed on 186 trees representing 19 Theobroma cacao clones from the Institute of Agricultural Research for Development (IRAD) breeding program in Cameroon. Our objectives were to determine the correct clone genotypes and off-types using both SSR and SNP markers. SSR markers that amplify 11 highly polymorphic loci from six linkage groups and 13 SNP markers that amplify eight loci from seven linkage groups were used to genotype the 186 trees and the results from the two different marker types were compared. The SNP assay identified 98% of the off-types found via SSR screening. SNP markers spread across multiple linkage groups may serve as a more cost-effective and reliable method for off-type identification, especially in cacao-producing countries where the equipment necessary for SSR analysis may not be available.     

Evaluation of linkage disequilibrium and its effect on non-parametric multipoint linkage analysis using two high density single-nucleotide polymorphism mapping panels

Genotype data from the Illumina Linkage III SNP panel (n = 4,720 SNPs) and the Affymetrix 10 k mapping array (n = 11,120 SNPs) were used to test the effects of linkage disequilibrium (LD) between SNPs in a linkage analysis in the Collaborative Study on the Genetics of Alcoholism pedigree collection (143 pedigrees; 1,614 individuals). The average r2 between adjacent markers across the genetic map was 0.099 +/- 0.003 in the Illumina III panel and 0.17 +/- 0.003 in the Affymetrix 10 k array. In order to determine the effect of LD between marker loci in a nonparametric multipoint linkage analysis, markers in strong LD with another marker (r2 > 0.40) were removed (n = 471 loci in the Illumina panel; n = 1,804 loci in the Affymetrix panel) and the linkage analysis results were compared to the results using the entire marker sets. In all analyses using the ALDX1 phenotype, 8 linkage regions on 5 chromosomes (2, 7, 10, 11, X) were detected (peak markers p < 0.01), and the Illumina panel detected an additional region on chromosome 6. Analysis of the same pedigree set and ALDX1 phenotype using short tandem repeat markers (STRs) resulted in 3 linkage regions on 3 chromosomes (peak markers p < 0.01). These results suggest that in this pedigree set, LD between loci with spacing similar to the SNP panels tested may not significantly affect the overall detection of linkage regions in a genome scan. Moreover, since the data quality and information content are greatly improved in the SNP panels over STR genotyping methods, new linkage regions may be identified due to higher information content and data quality in a dense SNP linkage panel.     

Genome-wide association mapping of agronomic traits in sugar beet

Recent results indicate that association mapping in populations from applied plant breeding is a powerful tool to detect QTL which are of direct relevance for breeding. The focus of this study was to unravel the genetic architecture of six agronomic traits in sugar beet. To this end, we employed an association mapping approach, based on a very large population of 924 elite sugar beet lines from applied plant breeding, fingerprinted with 677 single nucleotide polymorphism (SNP) markers covering the entire genome. We show that in this population linkage disequilibrium decays within a short genetic distance and is sufficient for the detection of QTL with a large effect size. To increase the QTL detection power and the mapping resolution a much higher number of SNPs is required. We found that for QTL detection, the mixed model including only the kinship matrix performed best, even in the presence of a considerable population structure. In genome-wide scans, main effect QTL and epistatic QTL were detected for all six traits. Our full two-dimensional epistasis scan revealed that for complex traits there appear to be epistatic master regulators, loci which are involved in a large number of epistatic interactions throughout the genome.     

Multi-trait association mapping in sugar beet (<Emphasis Type="Italic">Beta vulgaris</Emphasis> L.)

Association mapping promises to overcome the limitations of linkage mapping methods. The main objective of this study was to examine the applicability of multivariate association mapping with an empirical data set of sugar beet. A total of 111 diploid sugar beet inbreds was selected from the seed parent heterotic pool to represent a broad diversity with respect to sugar content (SC). The inbreds were genotyped with 26 simple sequence repeat markers chosen according to their map positions in proximity to previously identified quantitative trait loci for SC. For SC and beet yield (BY), the genotypic variances were highly significant (P < 0.01). Based on the global test of the bivariate mixed-model approach, four markers were significantly associated with SC, BY, or both at a false discovery rate of 0.025. All four markers were significantly (P < 0.05) associated with BY but only two with SC. The identification of markers associated with SC, BY, or both indicated that association mapping can be successfully applied in a sugar beet breeding context for detection of marker-phenotype associations. Furthermore, based on our results multivariate association mapping can be recommended as a promising tool to discriminate with a high mapping resolution between pleiotropy and linkage as reasons for co-localization of marker-phenotype associations for different traits.     

Comparing the distribution of RAPD and RFLP markers in a high density linkage map of sugar beet.

The distribution of RAPD markers was compared with that of RFLP markers in a high density linkage map of sugar beet. The same mapping population of 161 F2 individuals was used to generate all the marker data. The total map comprises 160 RAPD and 248 RFLP markers covering 508 cM. Both the RAPD and the RFLP markers show a high degree of clustering over the nine linkage groups. The pattern is compatible with a strong distal localization of recombination in the sugar beet. It leads generally to one major cluster of markers in the centre of each linkage group. In regions of high marker density, dominant RAPD markers present in either linkage phase and codominant RFLP markers are subclustered relative to each other. This phenomenon is shown to be attributable to: (i) effects of the mapping procedure when dominant and codominant data are combined, (ii) effects of the mapping procedure when dominant data in both linkage phases are combined, and (iii) genuine differences in the way RAPD and RFLP markers are recruited.     

Development of single nucleotide polymorphism (SNP) markers for use in commercial maize (Zea mays L.) germplasm

The development of single nucleotide polymorphism (SNP) markers in maize offers the opportunity to utilize DNA markers in many new areas of population genetics, gene discovery, plant breeding and germplasm identification. However, the steps from sequencing and SNP discovery to SNP marker design and validation are lengthy and expensive. Access to a set of validated SNP markers is a significant advantage to maize researchers who wish to apply SNPs in scientific inquiry. We mined 1,088 loci sequenced across 60 public inbreds that have been used in maize breeding in North America and Europe. We then selected 640 SNPs using generalized marker design criteria that enable utilization with several SNP chemistries. While SNPs were found on average every 43 bases in 1,088 maize gene sequences, SNPs that were amenable to marker design were found on average every 623 bases; representing only 7% of the total SNPs discovered. We also describe the development of a 768 marker multiplex assay for use on the Illumina^® BeadArray? platform. SNP markers were mapped on the IBM2 intermated B73 × Mo17 high resolution genetic map using either the IBM2 segregating population, or segregation in multiple parent-progeny triplets. A high degree of colinearity was found with the genetic nested association map. For each SNP presented we give information on map location, polymorphism rates in different heterotic groups and performance on the Illumina^® platform.     

Comparative effectiveness of sugar beet microsatellite markers isolated from genomic libraries and GenBank ESTs to map the sugar beet genome

Sugar beet (Beta vulgaris) is an important root crop for sucrose production. A study was conducted to find a new abundant source of microsatellite (SSR) markers in order to develop marker assistance for breeding. Different sources of existing microsatellites were used and new ones were developed to compare their efficiency to reveal diversity in mapping population and mapping coverage. Forty-one microsatellite markers were isolated from a B. vulgaris ssp maritima genomic library and 201 SSRs were extracted from a B. vulgaris ssp vulgaris library. Data mining was applied on GenBank B. vulgaris expressed sequence tags (ESTs), 803 EST-SSRs were identified over 19,709 ESTs. Characteristics, polymorphism and cross-species transferability of these microsatellites were compared. Based on these markers, a high density genetic map was constructed using 92 F₂ individuals from a cross between a sugar and a table beet. The map contains 284 markers, spans over 555 cM and covers the nine chromosomes of the species with an average markers density of one marker every 2.2 cM. A set of markers for assignation to the nine chromosomes of sugar beet is provided.     

Development and validation of EST-derived SSR markers and diversity analysis in cluster bean (<Emphasis Type="Italic">Cyamopsis tetragonoloba</Emphasis>)

Cluster bean/guar (Cyamopsis tetragonoloba), has an important place in industry because of its seeds, which contain galactomannan (guar gum) rich endosperm. Guar gum, an important ingredient of many products, is purely an export oriented commodity. Development of molecular markers for this crop is essential to accelerate breeding for guar gum content in seeds. A total of 100 novel primers pairs were developed from 16,476 expressed sequence tags (ESTs) sequence of cluster bean. A total of 50 primers pairs with function annotation of gum synthesis were selected and validated on a panel of 32 genotypes. Among the 50 primers 39 primers were amplified with a total of 45 loci. The polymorphic information content (PIC) ranged from 0.00 to 0.42 with an average of 0.13. With low polymorphic simple sequence repeats (SSRs) and narrow genetic base, most of the genotypes scattered into three clusters regardless of their geographical origin. Present study showed the existence of very low genetic diversity in cluster bean. The results indicated that there is need to explore SSR markers from whole genome or alternative marker systems like SNP (single nucleotide polymorphism) markers, for effective implication of markers in cluster bean breeding.     

A large‐scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large‐scale genomic association analysis with high‐density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high‐confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult‐plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker‐assisted breeding. These results demonstrate that high‐resolution SNP‐based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker‐assisted selection in wheat disease resistance breeding.