A Definitive Haplotype Map as Determined by Genotyping Duplicated Haploid Genomes Finds a Predominant Haplotype Preference at Copy-Number Variation Events

The majority of complete hydatidiform moles (CHMs) harbor duplicated haploid genomes that originate from sperm. This makes CHMs more advantageous than conventional diploid cells for determining haplotypes of SNPs and copy-number variations (CNVs), because all of the genetic variants in a CHM genome are homozygous. Here we report SNP and CNV haplotype structures determined by analysis of 100 CHMs from Japanese subjects via high-density DNA arrays. The obtained haplotype map should be useful as a reference for the haplotype structure of Asian populations. We resolved common CNV regions (merged CNV segments across the examined samples) into CNV events (clusters of CNV segments) on the basis of mutual overlap and found that the haplotype backgrounds of different CNV events within the same CNV region were predominantly similar, perhaps because of inherent structural instability.     

Inferring loss-of-heterozygosity from unpaired tumors using high-density oligonucleotide SNP arrays

Loss of heterozygosity (LOH) of chromosomal regions bearing tumor suppressors is a key event in the evolution of epithelial and mesenchymal tumors. Identification of these regions usually relies on genotyping tumor and counterpart normal DNA and noting regions where heterozygous alleles in the normal DNA become homozygous in the tumor. However, paired normal samples for tumors and cell lines are often not available. With the advent of oligonucleotide arrays that simultaneously assay thousands of single-nucleotide polymorphism (SNP) markers, genotyping can now be done at high enough resolution to allow identification of LOH events by the absence of heterozygous loci, without comparison to normal controls. Here we describe a hidden Markov model-based method to identify LOH from unpaired tumor samples, taking into account SNP intermarker distances, SNP-specific heterozygosity rates, and the haplotype structure of the human genome. When we applied the method to data genotyped on 100 K arrays, we correctly identified 99% of SNP markers as either retention or loss. We also correctly identified 81% of the regions of LOH, including 98% of regions greater than 3 megabases. By integrating copy number analysis into the method, we were able to distinguish LOH from allelic imbalance. Application of this method to data from a set of prostate samples without paired normals identified known regions of prevalent LOH. We have developed a method for analyzing high-density oligonucleotide SNP array data to accurately identify of regions of LOH and retention in tumors without the need for paired normal samples.     

Identification and validation of a core set of informative genic SSR and SNP markers for assaying functional diversity in barley

A ‘core set’ of 28 simple sequence repeat (SSR) and 28 single nucleotide polymorphism (SNP) markers for barley was developed after screening six diverse genotypes (DGs) representing six countries (Afghanistan, Pakistan, Algeria, Egypt, Jordan and Syria) with 50 SSR and 50 SNP markers derived from expressed sequence tags (ESTs). The markers of the core set are single locus with very high quality amplifications, high polymorphism information content (PIC) and are distributed across the barley genome. PIC values for the selected SSR and SNP markers ranged between 0.32–0.72 (average 0.58) and 0.28–0.50 (average 0.42), respectively. To make the SNP genotyping cost effective, CAPS (cleaved amplified polymorphic sequence) and indel assays were developed for 23 markers and the remaining 5 SNP markers were optimized for pyrosequencing. A high coefficient of correlations (r = 0.96, P < 0.005) between the genetic similarity matrices of SSR and SNP genotyping data of the core set on diverse genotypes (DGs) and their similar groupings according to the geographical distribution in both SSR and SNP phenograms with high bootstrap values underline the utility and reliability of the core set. A comparative allelic and sequence diversity for SSR and SNP markers between the DGs and six elite parental genotypes (PGs) of mapping populations showed comparable diverse nature of two germplasm sets. However, unique SNPs and indels were observed in both germplasm sets providing more datapoints for analysing haplotypes in a better way for the corresponding SNP marker. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Application of high-resolution DNA melting for genotyping and variant scanning of diploid and autotetraploid potato

The ideal marker system for tetraploid potato would be dosage-sensitive and have the ability to distinguish heterozygous genotypes with multiple haplotypes within the genomic region targeted by the marker. The objective of this study was to evaluate the utility of high-resolution DNA melting (HRM) for genotyping and polymorphism detection in diploid and tetraploid potato. Amplicon scanning, unlabelled probe, and short amplicon assays were developed for four candidate genes affecting tuber skin and flesh colour, and starch, and a marker linked to nematode resistance. Genotyping a set of 95 potato clones revealed several examples of clones with three distinct haplotypes. Combined probe and amplicon analysis identified between 29 and 44 unique genotypes for the same assays. Assays developed for four of the five target genes are suitable for marker-assisted selection in potato breeding programs. This study illustrates the use of HRM in potato genetics. Further advances in the technology and associated data analysis should make HRM a useful tool for basic and applied studies of potato.     

Maximum likelihood estimation of linkage disequilibrium in half-sib families

Maximum likelihood methods for the estimation of linkage disequilibrium between biallelic DNA-markers in half-sib families (half-sib method) are developed for single and multifamily situations. Monte Carlo computer simulations were carried out for a variety of scenarios regarding sire genotypes, linkage disequilibrium, recombination fraction, family size, and number of families. A double heterozygote sire was simulated with recombination fraction of 0.00, linkage disequilibrium among dams of δ=0.10, and alleles at both markers segregating at intermediate frequencies for a family size of 500. The average estimates of δ were 0.17, 0.25, and 0.10 for Excoffier and Slatkin (1995), maternal informative haplotypes, and the half-sib method, respectively. A multifamily EM algorithm was tested at intermediate frequencies by computer simulation. The range of the absolute difference between estimated and simulated δ was between 0.000 and 0.008. A cattle half-sib family was genotyped with the Illumina 50K BeadChip. There were 314,730 SNP pairs for which the sire was a homo-heterozygote with average estimates of r2 of 0.115, 0.067, and 0.111 for half-sib, Excoffier and Slatkin (1995), and maternal informative haplotypes methods, respectively. There were 208,872 SNP pairs for which the sire was double heterozygote with average estimates of r2 across the genome of 0.100, 0.267, and 0.925 for half-sib, Excoffier and Slatkin (1995), and maternal informative haplotypes methods, respectively. Genome analyses for all possible sire genotypes with 829,042 tests showed that ignoring half-sib family structure leads to upward biased estimates of linkage disequilibrium. Published inferences on population structure and evolution of cattle should be revisited after accommodating existing half-sib family structure in the estimation of linkage disequilibrium.     

Characterisation of single nucleotide polymorphisms in sugarcane ESTs

Commercial sugarcane cultivars (Saccharum spp. hybrids) are both polyploid and aneuploid with chromosome numbers in excess of 100; these chromosomes can be assigned to 8 homology groups. To determine the utility of single nucleotide polymorphisms (SNPs) as a means of improving our understanding of the complex sugarcane genome, we developed markers to a suite of SNPs identified in a list of sugarcane ESTs. Analysis of 69 EST contigs showed a median of 9 SNPs per EST and an average of 1 SNP per 50 bp of coding sequence. The quantitative presence of each base at 58 SNP loci within 19 contiguous sequence sets was accurately and reliably determined for 9 sugarcane genotypes, including both commercial cultivars and ancestral species, through the use of quantitative light emission technology in pyrophosphate sequencing. Across the 9 genotypes tested, 47 SNP loci were polymorphic and 11 monomorphic. Base frequency at individual SNP loci was found to vary approximately twofold between Australian sugarcane cultivars and more widely between cultivars and wild species. Base quantity was shown to segregate as expected in the IJ76-514 × Q165 sugarcane mapping population, indicating that SNPs that occur on one or two sugarcane chromosomes have the potential to be mapped. The use of SNP base frequencies from five of the developed markers was able to clearly distinguish all genotypes in the population. The use of SNP base frequencies from a further six markers within an EST contig was able to help establish the likely copy number of the locus in two genotypes tested. This is the first instance of a technology that has been able to provide an insight into the copy number of a specific gene locus in hybrid sugarcane. The identification of specific and numerous haplotypes/alleles present in a genotype by pyrophosphate sequencing or alternative techniques ultimately will provide the basis for identifying associations between specific alleles and phenotype and between allele dosage and phenotype in sugarcane.Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

Haplotype‐based genotyping‐by‐sequencing in oat genome research

In a de novo genotyping‐by‐sequencing (GBS) analysis of short, 64‐base tag‐level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag‐level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635‐line diversity panel were used to infer chromosome‐level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high‐resolution genome analysis and genomic selection in oats. A combined genome‐wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component‐based genome‐wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS‐derived markers facilitate genome analysis and genomic selection in oat.     

High-throughput single nucleotide polymorphism genotyping in wheat (Triticum spp.)

Over the past few years, considerable progress has been made in high-throughput single nucleotide polymorphism (SNP) genotyping technologies, largely through the investment of the human genetics community. These technologies are well adapted to diploid species. For plant breeding purposes, it is important to determine whether these genotyping methods are adapted to polyploidy, as most major crops are former or recent polyploids. To address this problem, we tested the capacity of the multiplex technology SNPlex™ with a set of 47 wheat SNPs to genotype DNAs of 1314 lines that were organized in four 384-well plates. These lines represented different taxa of tetra- and hexaploid Triticum species and their wild diploid relatives. We observed 40 markers which gave less than 20% missing data. Different methods, based on either Sanger sequencing or the MassARRAY^® genotyping technology, were then used to validate the genotypes obtained by SNPlex™ for 11 markers. The concordance of the genotypes obtained by SNPlex™ with the results obtained by the different validation methods was 96%, except for one discarded marker. Furthermore, a mapping study on six markers showed the expected genetic positions previously described. To conclude, this study showed that high-throughput genotyping technologies developed for diploid species can be used successfully in polyploids, although there is a need for manual reading. For the first time in wheat species, a core of 39 SNPs is available that can serve as the basis for the development of a complete SNPlex™ set of 48 markers.     

Discrimination of SNP genotypes associated with complex haplotypes by high resolution melting analysis in almond: implications for improved marker efficiencies

Developed recently, high resolution melting (HRM) analysis is an efficient, accurate and inexpensive method for distinguishing DNA polymorphisms. HRM has been used to identify mutations in human genes, and to detect SNPs, INDELs and microsatellites in plants. However, its capacity to discriminate DNA variants in the context of complex haplotypes involving INDEL as well as SNP variants has not been examined until now. In this study, we genotyped an almond (Prunus dulcis (Mill.) D. A. Webb, syn. Prunus amygdalus Batsch) pseudo-testcross mapping population that showed segregation of complex haplotypes associated with CYP79D16 promoter sequence. The 175 bp region in question included a 7 bp INDEL and 3 SNPs, and manifested as three different haplotypes in the parents. Thus, with one homozygous and one heterozygous parent, two relevant genotypes were identified in the mapping population. Although the population displayed monomorphism with respect to the INDEL and one of the SNPs, HRM was sufficiently sensitive to distinguish genotypes on the basis of the two informative SNPs, and the resulting data were used to map CYP79D16 to linkage group 6 of the almond genome. Thus the capacity of HRM to resolve genotypes arising from complex haplotypes has been demonstrated, and this has important implications for the design of efficient HRM markers for various genetic applications including mapping, population studies and biodiversity analyses.     

Evaluation of Haplotype Inference Using Definitive Haplotype Data Obtained from Complete Hydatidiform Moles, and Its Significance for the Analyses of Positively Selected Regions

The haplotype map constructed by the HapMap Project is a valuable resource in the genetic studies of disease genes, population structure, and evolution. In the Project, Caucasian and African haplotypes are fairly accurately inferred, based mainly on the rules of Mendelian inheritance using the genotypes of trios. However, the Asian haplotypes are inferred from the genotypes of unrelated individuals based on population genetics, and are less accurate. Thus, the effects of this inaccuracy on downstream analyses needs to be assessed. We determined true Japanese haplotypes by genotyping 100 complete hydatidiform moles (CHM), each carrying a genome derived from a single sperm, using Affymetrix 500 K Arrays. We then assessed how inferred haplotypes can differ from true haplotypes, by phasing pseudo-individualized true haplotypes using the programs PHASE, fastPHASE, and Beagle. We found that, at various genomic regions, especially the MHC locus, the expansion of extended haplotype homozygosity (EHH), which is a measure of positive selection, is obscured when inferred Asian haplotype data is used to detect the expansion. We then mapped the genome using a new statistic, XDiHH, which directly detects the difference between the true and inferred haplotypes, in the determination of EHH expansion. We also show that the true haplotype data presented here is useful to assess and improve the accuracy of phasing of Asian genotypes.     

A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY, and invasive cleavage detected by Invader chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1-3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually.     

A sequential Monte Carlo framework for haplotype inference in CNV/SNP genotype data

Copy number variations (CNVs) are abundant in the human genome. They have been associated with complex traits in genome-wide association studies (GWAS) and expected to continue playing an important role in identifying the etiology of disease phenotypes. As a result of current high throughput whole-genome single-nucleotide polymorphism (SNP) arrays, we currently have datasets that simultaneously have integer copy numbers in CNV regions as well as SNP genotypes. At the same time, haplotypes that have been shown to offer advantages over genotypes in identifying disease traits even though available for SNP genotypes are largely not available for CNV/SNP data due to insufficient computational tools. We introduce a new framework for inferring haplotypes in CNV/SNP data using a sequential Monte Carlo sampling scheme ‘Tree-Based Deterministic Sampling CNV’ (TDSCNV). We compare our method with polyHap(v2.0), the only currently available software able to perform inference in CNV/SNP genotypes, on datasets of varying number of markers. We have found that both algorithms show similar accuracy but TDSCNV is an order of magnitude faster while scaling linearly with the number of markers and number of individuals and thus could be the method of choice for haplotype inference in such datasets. Our method is implemented in the TDSCNV package which is available for download at http://www.ee.columbia.edu/~anastas/tdscnv.     

Estimation of DNA sequence diversity in bovine cytokine genes

DNA sequence variation provides the fundamental material for improving livestock through selection. In cattle, single nucleotide polymorphisms and small insertions/deletions (collectively referred to here as SNPs) have been identified in cytokine genes and scored in a reference population to determine linkage map positions. The aim of the present study was twofold: first, to estimate the SNP frequency in a reference population of beef cattle, and second, to determine cytokine haplotypes in a group of sires from commercial populations. Forty-five SNP markers in DNA segments from nine cytokine gene loci were analyzed in 26 reference parents. Comparison of all 52 haploid genomes at each PCR amplicon locus revealed an average of one SNP per 143 bp of sequence, whereas comparison of any two chromosomes identified heterozygous sites, on average, every 443 bp. The combination of these 45 SNP genotypes was sufficient to uniquely identify each of the 26 animals. The average number of haplotype alleles (4.4) per PCR amplicon (688 bp) and the percentage heterozygosity among founding parents (50%) were similar to those for microsatellite markers in the same population. For 49 sires from seven common breeds of beef cattle, SNP genotypes (1225 total) were obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) at three amplicon loci. All three of the amplicon haplotypes were correctly deduced for each sire without the use of parent or progeny genotypes. The latter allows a wide range of genetic studies in commercial populations of cattle where genotypic information from relatives may not be available. Received: 16 June 2000 / Accepted: 23 August 2000     

Genetically Based Location from Triploid Populations and Gene Ontology of a 3.3-Mb Genome Region Linked to Alternaria Brown Spot Resistance in Citrus Reveal Clusters of Resistance Genes

Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR) to map a genome region linked to Alternaria brown spot (ABS) resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids.     

SNP Haplotype Mapping in a Small ALS Family

The identification of genes for monogenic disorders has proven to be highly effective for understanding disease mechanisms, pathways and gene function in humans. Nevertheless, while thousands of Mendelian disorders have not yet been mapped there has been a trend away from studying single-gene disorders. In part, this is due to the fact that many of the remaining single-gene families are not large enough to map the disease locus to a single site in the genome. New tools and approaches are needed to allow researchers to effectively tap into this genetic gold-mine. Towards this goal, we have used haploid cell lines to experimentally validate the use of high-density single nucleotide polymorphism (SNP) arrays to define genome-wide haplotypes and candidate regions, using a small amyotrophic lateral sclerosis (ALS) family as a prototype. Specifically, we used haploid-cell lines to determine if high-density SNP arrays accurately predict haplotypes across entire chromosomes and show that haplotype information significantly enhances the genetic information in small families. Panels of haploid-cell lines were generated and a 5 centimorgan (cM) short tandem repeat polymorphism (STRP) genome scan was performed. Experimentally derived haplotypes for entire chromosomes were used to directly identify regions of the genome identical-by-descent in 5 affected individuals. Comparisons between experimentally determined and in silico haplotypes predicted from SNP arrays demonstrate that SNP analysis of diploid DNA accurately predicted chromosomal haplotypes. These methods precisely identified 12 candidate intervals, which are shared by all 5 affected individuals. Our study illustrates how genetic information can be maximized using readily available tools as a first step in mapping single-gene disorders in small families.     

Modelling survival and allele complementation in the evolution of genomes with polymorphic loci

We have simulated the evolution of sexually reproducing populations composed of individuals represented by diploid genomes. A series of eight bits formed an allele occupying one of 128 loci of one haploid genome (chromosome). The environment required a specific activity of each locus, this being the sum of the activities of both alleles located at the corresponding loci on two chromosomes. This activity is represented by the number of bits set to zero. In a constant environment the best fitted individuals were homozygous with alleles’ activities corresponding to half of the environment requirement for a locus (in diploid genome two alleles at corresponding loci produced a proper activity). Changing the environment under a relatively low recombination rate promotes generation of more polymorphic alleles. In the heterozygous loci, alleles of different activities complement each other fulfilling the environment requirements. Nevertheless, the genetic pool of populations evolves in the direction of a very restricted number of complementing haplotypes and a fast changing environment kills the population. If simulations start with all loci heterozygous, they stay heterozygous for a long time.     

Analysis and exploration of the use of rule-based algorithms and consensus methods for the inferral of haplotypes

The difficulty of experimental determination of haplotypes from phase-unknown genotypes has stimulated the development of nonexperimental inferral methods. One well-known approach for a group of unrelated individuals involves using the trivially deducible haplotypes (those found in individuals with zero or one heterozygous sites) and a set of rules to infer the haplotypes underlying ambiguous genotypes (those with two or more heterozygous sites). Neither the manner in which this "rule-based" approach should be implemented nor the accuracy of this approach has been adequately assessed. We implemented eight variations of this approach that differed in how a reference list of haplotypes was derived and in the rules for the analysis of ambiguous genotypes. We assessed the accuracy of these variations by comparing predicted and experimentally determined haplotypes involving nine polymorphic sites in the human apolipoprotein E (APOE) locus. The eight variations resulted in substantial differences in the average number of correctly inferred haplotype pairs. More than one set of inferred haplotype pairs was found for each of the variations we analyzed, implying that the rule-based approach is not sufficient by itself for haplotype inferral, despite its appealing simplicity. Accordingly, we explored consensus methods in which multiple inferrals for a given ambiguous genotype are combined to generate a single inferral; we show that the set of these "consensus" inferrals for all ambiguous genotypes is more accurate than the typical single set of inferrals chosen at random. We also use a consensus prediction to divide ambiguous genotypes into those whose algorithmic inferral is certain or almost certain and those whose less certain inferral makes molecular inferral preferable.     

First-generation SNP/InDel markers tagging loci for pathogen resistance in the potato genome

A panel of 17 tetraploid and 11 diploid potato genotypes was screened by comparative sequence analysis of polymerase chain reaction (PCR) products for single nucleotide polymorphisms (SNPs) and insertion-deletion polymorphisms (InDels), in regions of the potato genome where genes for qualitative and/or quantitative resistance to different pathogens have been localized. Most SNP and InDel markers were derived from bacterial artificial chromosome (BAC) insertions that contain sequences similar to the family of plant genes for pathogen resistance having nucleotide-binding-site and leucine-rich-repeat domains (NBS-LRR-type genes). Forty-four such NBS-LRR-type genes containing BAC-insertions were mapped to 14 loci, which tag most known resistance quantitative trait loci (QTL) in potato. Resistance QTL not linked to known resistance-gene-like (RGL) sequences were tagged with other markers. In total, 78 genomic DNA fragments with an overall length of 31 kb were comparatively sequenced in the panel of 28 genotypes. 1498 SNPs and 127 InDels were identified, which corresponded, on average, to one SNP every 21 base pairs and one InDel every 243 base pairs. The nucleotide diversity of the tetraploid genotypes (pi = 0.72 x 10(-3)) was lower when compared with diploid genotypes (pi = 2.31 x 10(-3)). RGL sequences showed higher nucleotide diversity when compared with other sequences, suggesting evolution by divergent selection. Information on sequences, sequence similarities, SNPs and InDels is provided in a database that can be queried via the Internet.     

Validation of Genotyping-By-Sequencing Analysis in Populations of Tetraploid Alfalfa by 454 Sequencing

Genotyping-by-sequencing (GBS) is a relatively low-cost high throughput genotyping technology based on next generation sequencing and is applicable to orphan species with no reference genome. A combination of genome complexity reduction and multiplexing with DNA barcoding provides a simple and affordable way to resolve allelic variation between plant samples or populations. GBS was performed on ApeKI libraries using DNA from 48 genotypes each of two heterogeneous populations of tetraploid alfalfa (Medicago sativa spp. sativa): the synthetic cultivar Apica (ATF0) and a derived population (ATF5) obtained after five cycles of recurrent selection for superior tolerance to freezing (TF). Nearly 400 million reads were obtained from two lanes of an Illumina HiSeq 2000 sequencer and analyzed with the Universal Network-Enabled Analysis Kit (UNEAK) pipeline designed for species with no reference genome. Following the application of whole dataset-level filters, 11,694 single nucleotide polymorphism (SNP) loci were obtained. About 60% had a significant match on the Medicago truncatula syntenic genome. The accuracy of allelic ratios and genotype calls based on GBS data was directly assessed using 454 sequencing on a subset of SNP loci scored in eight plant samples. Sequencing depth in this study was not sufficient for accurate tetraploid allelic dosage, but reliable genotype calls based on diploid allelic dosage were obtained when using additional quality filtering. Principal Component Analysis of SNP loci in plant samples revealed that a small proportion (<5%) of the genetic variability assessed by GBS is able to differentiate ATF0 and ATF5. Our results confirm that analysis of GBS data using UNEAK is a reliable approach for genome-wide discovery of SNP loci in outcrossed polyploids.