Analysis of genome-wide linkage disequilibrium in the highly polyploid sugarcane

Molecular evaluation and phenotypic screening of brown and orange rust in Saccharum germplasm

Brazil is the largest global producer of sugarcane and plays a significant role-supplier of sugar and bioethanol. However, diseases such as brown and orange rust cause substantial yield reductions and economic losses, due decrease photosynthesis and biomass in susceptible cultivars. Molecular markers associated with resistance genes, such as Bru1 (brown rust) and G1 (orange rust), could aid in predicting resistant genotypes. In this study, we sought to associate the phenotypic response of 300 sugarcane accessions with the genotypic response of Bru1 and G1 markers. The field trials were conducted in a randomized block design, and five six-month-old plants per plot were evaluated under natural disease conditions. Genotypic information about the presence or absence of Bru1 (haplotype 1) and G1 gene was obtained after extraction of genomic DNA and conventional PCR. Of the total accessions evaluated, 60.3% (181) showed resistance to brown rust in the field, and of these, 70.7% (128) had the Bru1 gene present. Considering the field-resistant accessions obtained from Brazilian breeding programs (116), the Bru1 was present in 77,6% of these accessions. While alternative resistance sources may exist, Bru1 likely confers enduring genetic resistance in current Brazilian cultivars. Regarding the phenotypic reaction to orange rust, the majority of accessions, 96.3% (288), were field resistant, and of these, 52.7% (152) carried the G1 marker. Although less efficient for predicting resistance when compared to Bru1, the G1 marker could be part of a quantitative approach when new orange rust resistance genes are described. Therefore, these findings showed the importance of Bru1 molecular markers for the early selection of resistant genotypes to brown rust by genetic breeding programs.

Genetic diversity and population structure of sugarcane introgressed hybrids by SSR markers

One hundred and seventy two introgressed hybrids from four different introgression groups and in three nobilized stages (F1, BC1,and BC2) involving two genera viz., Sugarcane (Saccharum spp) and Erianthusl (E.arundinaceus),and Coimbatore (Commercials) clones were studied for yield and quality traits, and as well with 30 SSR markers (simple sequence repeats) for diversity and population structure. The yield and quality components of the introgressed hybrids from improved S. spontaneum, improved S. robustum, S. barberi (Pathri) and E. arundinaceus (IK-76-76) showed significant variation. The traits viz., cane height, single cane weight and cane yield showed the highest level of phenotypic and genotypic variation. 456 polymorphic alleles in all with values ranging from 6 (SMC 863-GC) to 24 (NKS 43) with an average of 15 alleles per primer were studied. Polymorphism information content (PIC) generated by 30 SSR primers varied from 0.57 (NKS 1) to 0.94 (NKS 34) and the highest average PIC (0.93) was observed in hybrids of S. spontaneum (SSH). The highest number of observed and effective alleles, and Shannon's index were also registered by introgressed hybrids of SSH and the lowest variability was observed with hybrids of Co canes x S. barberi. SSR-based population genetic measures identified three mating groups involving improved S.officinarum, improved S.robustum and Coimbatore canes with maximum variability. Structure analysis identified 51 introgressed hybrids with abundant genetic variation and low gene flow as a new germplasm source for future sugarcane breeding programmes. Fifty-nine rare alleles were detected, and structure analysis revealed a low degree of admixture between the generated hybrids. Low gene flow estimates from group I (Nm: 1.052, where mostly F1 and BC1 hybrids were grouped together) explained that the maximum variability from parental clones was inherited until the BC1 generation, and high values of Nm in group III also indicated that most of the wild alleles were fixed in the BC1 population. Structure and cluster analysis (PCoA, UPGMA) explained that the grouping of introgressed hybrids is highly correlated to different stages of nobilization. UPGMA and PCoA methods grouped the individuals into three major clusters, with a clear differentiation of F1 and backcross hybrids grouped under different internal sub-clusters. The occurrence of wide genetic variability in the population and elite hybrids with a unique genetic base can be exploited in breeding programmes to develop trait specific donors for genetic enhancement and to mitigate climate change.

Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies

Mate-allocation strategies in breeding programs can improve progeny performance by harnessing non-additive genetic effects. These approaches prioritise predicted progeny merit over parental breeding value, making them particularly appealing for clonally propagated crops such as sugarcane. We conducted a comparative analysis of mate-allocation strategies, exploring utilising non-additive and heterozygosity effects to maximise clonal performance with schemes that solely consider additive effects to optimise breeding value. Using phenotypic and genotypic data from a population of 2,909 clones evaluated in final assessment trials of Australian sugarcane breeding programs, we focused on three important traits: tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and Fibre. By simulating families from all possible crosses (1,225) with 50 progenies each, we predicted the breeding and clonal values of progeny using two models: GBLUP (considering additive effects only) and extended-GBLUP (incorporating additive, non-additive, and heterozygosity effects). Integer linear programming was used to identify the optimal mate-allocation among selected parents. Compared to breeding value-based approaches, mate-allocation strategies based on clonal performance yielded substantial improvements, with predicted progeny values increasing by 57% for TCH, 12% for CCS, and 16% for fibre. Our simulation study highlights the effectiveness of mate-allocation approaches that exploit non-additive and heterozygosity effects, resulting in superior clonal performance. However, there was a notable decline in additive gain, particularly for TCH, likely due to significant epistatic effects. When selecting crosses based on clonal performance for TCH, the inbreeding coefficient of progeny was significantly lower compared to random mating, underscoring the advantages of leveraging non-additive and heterozygosity effects in mitigating inbreeding depression. Thus, mate-allocation strategies are recommended in clonally propagated crops to enhance clonal performance and reduce the negative impacts of inbreeding.

Genome-Wide Association Study Unravels Quantitative Trait Loci and Genes Associated with Yield-Related Traits in Sugarcane

Sugarcane, a major sugar and energy crop worldwide faces an increasing demand for higher yields. Identifying yield-related markers and candidate genes is valuable for breeding high-yield varieties using molecular techniques. In this work, seven yield-related traits were evaluated in a diversity panel of 159 genotypes, derived from Tripidium arundinaceum, Saccharum spontaneum, and modern sugarcane genotypes. All traits exhibited significant genetic variance with high heritability and high correlations. Genetic diversity analysis reveals a genomic decay of 23 kb and an average single nucleotide polymorphism (SNP) number of 25,429 per genotype. These 159 genotypes were divided into 4 subgroups. Genome-wide association analysis identified 47 SNPs associated with brix, spanning 36 quantitative trait loci (QTLs), and 138 SNPs for other traits across 104 QTLs, covering all 32 chromosomes. Interestingly, 12 stable QTLs associated with yield-related traits were identified, which contained 35 candidate genes. This work provides markers and candidate genes for marker-assisted breeding to improve sugarcane yields.

A Genome-Wide Association Study and Genomic Prediction for Fiber and Sucrose Contents in a Mapping Population of LCP 85-384 Sugarcane

Sugarcane (Saccharum spp. hybrids) is an economically important crop for both sugar and biofuel industries. Fiber and sucrose contents are the two most critical quantitative traits in sugarcane breeding that require multiple-year and multiple-location evaluations. Marker-assisted selection (MAS) could significantly reduce the time and cost of developing new sugarcane varieties. The objectives of this study were to conduct a genome-wide association study (GWAS) to identify DNA markers associated with fiber and sucrose contents and to perform genomic prediction (GP) for the two traits. Fiber and sucrose data were collected from 237 self-pollinated progenies of LCP 85-384, the most popular Louisiana sugarcane cultivar from 1999 to 2007. The GWAS was performed using 1310 polymorphic DNA marker alleles with three models of TASSEL 5, single marker regression (SMR), general linear model (GLM) and mixed linear model (MLM), and the fixed and random model circulating probability unification (FarmCPU) of R package. The results showed that 13 and 9 markers were associated with fiber and sucrose contents, respectively. The GP was performed by cross-prediction with five models, ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB) and Bayesian least absolute shrinkage and selection operator (BL). The accuracy of GP varied from 55.8% to 58.9% for fiber content and 54.6% to 57.2% for sucrose content. Upon validation, these markers can be applied in MAS and genomic selection (GS) to select superior sugarcane with good fiber and high sucrose contents.

An autopolyploid-suitable polyBSA-seq strategy for screening candidate genetic markers linked to leaf blight resistance in sugarcane

An autopolyploid-suitable polyBSA-seq strategy was developed for screening candidate genetic markers linked to leaf blight resistance in sugarcane. Due to the complex genome architecture, the quantitative trait loci mappings and linkage marker selections for agronomic traits of autopolyploid crops were mainly limited to the time-consuming and cost intensive construction of genetic maps. To map resistance-linked markers for sugarcane leaf blight (SLB) caused by Stagonospora tainanensis, the autopolyploid-suitable bulk-segregant analysis based on the sequencing (polyBSA-seq) strategy was successfully applied for the first time. Resistant- and susceptible-bulks (R- and S-bulks) constructed from the extreme-phenotypic sugarcane F₁ lines of YT93-159 × ROC22 were deep sequenced with 195.0 × for bulks and 74.4 × for parents. Informative single-dose variants (ISDVs) present as one copy in one parent and null in the other parent were detected based on the genome sequence of LA Purple, an autooctoploid Saccharum officinarum, to screen candidate linkage markers (CLMs). The proportion of the number of short reads harboring ISDVs in the total short reads covering a given genomic position was defined as ISDV index and the ISDVs with indices met the threshold set in this study (0.04-0.14) were selected as CLMs. In total, three resistance- and one susceptibility-related CLMs for SLB resistance were identified by the polyBSA-seq. Among them, two markers on chromosome 10 were less than 300 Kb apart. Furthermore, the RNA-seq was used to calculate the expression level of genes within 1.0 Mb from the aforementioned four CLMs, which demonstrated that twelve genes were differentially expressed between resistant and susceptible clones, including a receptor-like kinase and an ethylene-responsive transcription factor. This is the first reported polyBSA-seq in autopolyploid sugarcane, which specifically tailored for the fast selection of the CLMs and causal genes associated with important agronomic traits.

A linkage disequilibrium-based approach to position unmapped SNPs in crop species

BACKGROUND

High-density SNP arrays are now available for a wide range of crop species. Despite the development of many tools for generating genetic maps, the genome position of many SNPs from these arrays is unknown. Here we propose a linkage disequilibrium (LD)-based algorithm to allocate unassigned SNPs to chromosome regions from sparse genetic maps. This algorithm was tested on sugarcane, wheat, and barley data sets. We calculated the algorithm's efficiency by masking SNPs with known locations, then assigning their position to the map with the algorithm, and finally comparing the assigned and true positions.

RESULTS

In the 20-fold cross-validation, the mean proportion of masked mapped SNPs that were placed by the algorithm to a chromosome was 89.53, 94.25, and 97.23% for sugarcane, wheat, and barley, respectively. Of the markers that were placed in the genome, 98.73, 96.45 and 98.53% of the SNPs were positioned on the correct chromosome. The mean correlations between known and new estimated SNP positions were 0.97, 0.98, and 0.97 for sugarcane, wheat, and barley. The LD-based algorithm was used to assign 5920 out of 21,251 unpositioned markers to the current Q208 sugarcane genetic map, representing the highest density genetic map for this species to date.

CONCLUSIONS

Our LD-based approach can be used to accurately assign unpositioned SNPs to existing genetic maps, improving genome-wide association studies and genomic prediction in crop species with fragmented and incomplete genome assemblies. This approach will facilitate genomic-assisted breeding for many orphan crops that lack genetic and genomic resources.

Genome-wide approaches for the identification of markers and genes associated with sugarcane yellow leaf virus resistance

Sugarcane yellow leaf (SCYL), caused by the sugarcane yellow leaf virus (SCYLV) is a major disease affecting sugarcane, a leading sugar and energy crop. Despite damages caused by SCYLV, the genetic base of resistance to this virus remains largely unknown. Several methodologies have arisen to identify molecular markers associated with SCYLV resistance, which are crucial for marker-assisted selection and understanding response mechanisms to this virus. We investigated the genetic base of SCYLV resistance using dominant and codominant markers and genotypes of interest for sugarcane breeding. A sugarcane panel inoculated with SCYLV was analyzed for SCYL symptoms, and viral titer was estimated by RT-qPCR. This panel was genotyped with 662 dominant markers and 70,888 SNPs and indels with allele proportion information. We used polyploid-adapted genome-wide association analyses and machine-learning algorithms coupled with feature selection methods to establish marker-trait associations. While each approach identified unique marker sets associated with phenotypes, convergences were observed between them and demonstrated their complementarity. Lastly, we annotated these markers, identifying genes encoding emblematic participants in virus resistance mechanisms and previously unreported candidates involved in viral responses. Our approach could accelerate sugarcane breeding targeting SCYLV resistance and facilitate studies on biological processes leading to this trait.

Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects

Non-additive genetic effects seem to play a substantial role in the expression of complex traits in sugarcane. Including non-additive effects in genomic prediction models significantly improves the prediction accuracy of clonal performance. In the recent decade, genetic progress has been slow in sugarcane. One reason might be that non-additive genetic effects contribute substantially to complex traits. Dense marker information provides the opportunity to exploit non-additive effects in genomic prediction. In this study, a series of genomic best linear unbiased prediction (GBLUP) models that account for additive and non-additive effects were assessed to improve the accuracy of clonal prediction. The reproducible kernel Hilbert space model, which captures non-additive genetic effects, was also tested. The models were compared using 3,006 genotyped elite clones measured for cane per hectare (TCH), commercial cane sugar (CCS), and Fibre content. Three forward prediction scenarios were considered to investigate the robustness of genomic prediction. By using a pseudo-diploid parameterization, we found significant non-additive effects that accounted for almost two-thirds of the total genetic variance for TCH. Average heterozygosity also had a major impact on TCH, indicating that directional dominance may be an important source of phenotypic variation for this trait. The extended-GBLUP model improved the prediction accuracies by at least 17% for TCH, but no improvement was observed for CCS and Fibre. Our results imply that non-additive genetic variance is important for complex traits in sugarcane, although further work is required to better understand the variance component partitioning in a highly polyploid context. Genomics-based breeding will likely benefit from exploiting non-additive genetic effects, especially in designing crossing schemes. These findings can help to improve clonal prediction, enabling a more accurate identification of variety candidates for the sugarcane industry.

Pairwise linkage disequilibrium estimation for polyploids

Many tasks in statistical genetics involve pairwise estimation of linkage disequilibrium (LD). The study of LD in diploids is mature. However, in polyploids, the field lacks a comprehensive characterization of LD. Polyploids also exhibit greater levels of genotype uncertainty than diploids, yet no methods currently exist to estimate LD in polyploids in the presence of such genotype uncertainty. Furthermore, most LD estimation methods do not quantify the level of uncertainty in their LD estimates. Our study contains three major contributions. (i) We characterize haplotypic and composite measures of LD in polyploids. These composite measures of LD turn out to be functions of common statistical measures of association. (ii) We derive procedures to estimate haplotypic and composite LD in polyploids in the presence of genotype uncertainty. We do this by estimating LD directly from genotype likelihoods, which may be obtained from many genotyping platforms. (iii) We derive standard errors of all LD estimators that we discuss. We validate our methods on both real and simulated data. Our methods are implemented in the R package ldsep, available on the Comprehensive R Archive Network https://cran.r-project.org/package=ldsep.

Computational characterization of double reduction in autotetraploid natural populations

Population genetic theory has been well developed for diploid species, but its extension to study genetic diversity, variation and evolution in autopolyploids, a class of polyploids derived from the genome doubling of a single ancestral species, requires the incorporation of multisomic inheritance. Double reduction, which is characteristic of autopolyploidy, has long been believed to shape the evolutionary consequence of organisms in changing environments. Here, we develop a computational model for testing and estimating double reduction and its genomic distribution in autotetraploids. The model is implemented with the expectation-maximization (EM) algorithm to dissect unobservable allelic recombinations among multiple chromosomes, enabling the simultaneous estimation of allele frequencies and double reduction in natural populations. The framework fills an important gap in the population genetic theory of autopolyploids.

Applying Molecular Phenotyping Tools to Explore Sugarcane Carbon Potential

Sugarcane (Saccharum spp.), a C₄ grass, has a peculiar feature: it accumulates, gradient-wise, large amounts of carbon (C) as sucrose in its culms through a complex pathway. Apart from being a sustainable crop concerning C efficiency and bioenergetic yield per hectare, sugarcane is used as feedstock for producing ethanol, sugar, high-value compounds, and products (e.g., polymers and succinate), and bioelectricity, earning the title of the world's leading biomass crop. Commercial cultivars, hybrids bearing high levels of polyploidy, and aneuploidy, are selected from a large number of crosses among suitable parental genotypes followed by the cloning of superior individuals among the progeny. Traditionally, these classical breeding strategies have been favoring the selection of cultivars with high sucrose content and resistance to environmental stresses. A current paradigm change in sugarcane breeding programs aims to alter the balance of C partitioning as a means to provide more plasticity in the sustainable use of this biomass for metabolic engineering and green chemistry. The recently available sugarcane genetic assemblies powered by data science provide exciting perspectives to increase biomass, as the current sugarcane yield is roughly 20% of its predicted potential. Nowadays, several molecular phenotyping tools can be applied to meet the predicted sugarcane C potential, mainly targeting two competing pathways: sucrose production/storage and biomass accumulation. Here we discuss how molecular phenotyping can be a powerful tool to assist breeding programs and which strategies could be adopted depending on the desired final products. We also tackle the advances in genetic markers and mapping as well as how functional genomics and genetic transformation might be able to improve yield and saccharification rates. Finally, we review how "omics" advances are promising to speed up plant breeding and reach the unexplored potential of sugarcane in terms of sucrose and biomass production.

Candidate gene association of gene expression data in sugarcane contrasting for sucrose content

Association mapping of gene expression data, generated from transcriptome and proteome studies, provides a means of understanding the functional significance and trait association potential of candidate genes. In this study, we applied candidate gene association mapping to validate sugarcane genes, using data from the starch and sucrose metabolism pathway, transcriptome, and proteome. We performed multiplex PCR targeted amplicon sequencing of 109 candidate genes, using NGS technology. A range of statistical models, both single-locus and multi-locus, were compared for minimization of false positives in association mapping of four sugar-related traits with different heritability. The Fixed and random model Circulating Probability Unification model effectively suppressed false positives for both low- and high-heritability traits. We identified favorable alleles of the candidate genes involved in signalling and transcriptional regulation. The results will support genetic improvement of sugarcane and may help clarify the genetic architecture of sugar-related traits.

An enriched sugarcane diversity panel for utilization in genetic improvement of sugarcane

Sugarcane crop is important for both sugar and biofuels. A world collection of sugarcane and related grasses (WCSRG) maintained at Miami, FL contains > 1,200 non-redundant clones of different species and genera within the Saccharum complex. However, linkage of undesirable alleles with useful genes in wild species has hindered its efficient utilization in sugarcane breeding. A core collection developed previously with smaller number of clones representing WCSRG did not take into account > 120 wild/exotic clones maintained at the USDA-ARS Sugarcane Research Unit in Houma, Louisiana. Moreover, the genome complexity and sub-tropical to temperate growing climate of Louisiana warrant a region-specific core collection that can be used for base-broadening breeding aimed at efficient introgression of desirable alleles. Genetic diversity of 1,485 clones within WCSRG and Louisiana (commercials, wild/exotic) using 423 SSR alleles showed an average gene diversity (h) at 0.208 among all species groups where Erianthus-like Saccharum species (ELSS), Miscanthus spp., and S. spontaneum each formed a distinct cluster, Saccharum robustum, S. officinarum, hybrid cultivars, and S. edule grouped together in a major cluster, and Saccharum sinense and S. barberi formed distinct grouping. A 309-clone diversity panel (SDP1) was developed that captured the genetic diversity based on the combination of maximum length subtree and manual selection to maximize representation of Louisiana clones and minimize import of clones from Miami. SDP1 shared 324 alleles out of the 423 alleles in the entire population of 1,485 clones and captured the genetic diversity of the entire collection with an average gene diversity (h) at 0.163. The variation within (11–17%) and among (83–89%) the populations in SDP1 were comparable with the entire population of 1,485 clones (9–15% and 85–91%, respectively). The breadth of the genetic variation of SDP1 was exemplified by the intra- and inter-specific diversity of a 190-clone mini-core collection with markers derived from known cold-responsive genes. SDP1 will facilitate genome-wide association studies for identification of trait-specific markers for use in marker-assisted breeding in Louisiana and elsewhere.

Assessing genetic diversity and population structure of sugarcane cultivars, progenitor species and genera using microsatellite (SSR) markers

Sugarcane is one among the most important commercial crops used to produce sugar, ethanol, and other byproducts, which significantly contributes in the GDP of India and many other countries around the world. Genetic diversity is a platform for any breeding program of a plant species. Estimation of the genetic variability and population structure play a vital role for conservation planning and management of plant genetic resources. Genetic variability serves as a source of noble alleles responsible for key agronomic and quality traits, which ultimately form basis for identification and selection of promising parents for breeding programs. In the present study genetic diversity and population structure of 139 accessions of the genus Saccharum, allied genera of family Poaceae and cultivars were assessed using informative microsatellite (SSR) markers. A sum of 427 alleles was produced using 61 polymorphic primers and number of alleles generated was ranged from 2 to 13 with an average of 7 alleles per locus. PIC values were ranged from 0.35 to 0.90, with a mean value of 0.66 for all the markers evaluated. Cluster analysis based on UPGMA method revealed three major clusters which were further subdivided into nine subclusters. Population structure analysis also established three subpopulations of used accession set, however there were no correlation of sub-groupings with that of place of origin. AMOVA analysis also confirmed that 83% and 17% of total variations were attributed to the within- and between-populations, correspondingly, demonstrating greater exchange of gene pool across places of origin. The principal component analysis (PCA) demonstrated the distribution of accessions in the scatter-plot was substantially dispersed, revealing rich genetic diversity among accessions of different species. The findings from this study will be useful in breeding programs for introgression of noble alleles into modern cultivars by exploiting natural genetic variation existing in sugarcane genetic resources.

Genome-wide association study of multiple yield traits in a diversity panel of polyploid sugarcane (Saccharum spp.)

Sugarcane (Saccharum spp.) is an important economic crop, contributing up to 80% of sugar and approximately 60% of biofuel globally. To meet the increased demand for sugar and biofuel supplies, it is critical to breed sugarcane cultivars with robust performance in yield traits. Therefore, dissection of causal DNA sequence variants is of great importance, as it provides genetic resources and fundamental information for crop improvement. In this study, we analyzed nine yield traits in a sugarcane diversity panel consisting of 308 accessions primarily selected from the World Collection of Sugarcane and Related Grasses. By genotyping the diversity panel via target enrichment sequencing, we identified a large number of sequence variants. Genome-wide association studies between the markers and traits were conducted, taking dosages and gene actions into consideration. In total, 217 nonredundant markers and 225 candidate genes were identified to be significantly associated with the yield traits, which can serve as a comprehensive genetic resource database for future gene identification, characterization, and selection for sugarcane improvement. We further investigated runs of homozygosity (ROH) in the sugarcane diversity panel. We characterized 282 ROHs and found that the occurrence of ROHs in the genome were nonrandom and probably under selection. The ROHs were associated with total weight and dry weight, and high ROHs resulted in a decrease in the two traits. This study suggests that genomic inbreeding has led to negative impacts on sugarcane yield.

A genome-wide association study identified loci for yield component traits in sugarcane (Saccharum spp.)

Sugarcane (Saccharum spp.) has a complex genome with variable ploidy and frequent aneuploidy, which hampers the understanding of phenotype and genotype relations. Despite this complexity, genome-wide association studies (GWAS) may be used to identify favorable alleles for target traits in core collections and then assist breeders in better managing crosses and selecting superior genotypes in breeding populations. Therefore, in the present study, we used a diversity panel of sugarcane, called the Brazilian Panel of Sugarcane Genotypes (BPSG), with the following objectives: (i) estimate, through a mixed model, the adjusted means and genetic parameters of the five yield traits evaluated over two harvest years; (ii) detect population structure, linkage disequilibrium (LD) and genetic diversity using simple sequence repeat (SSR) markers; (iii) perform GWAS analysis to identify marker-trait associations (MTAs); and iv) annotate the sequences giving rise to SSR markers that had fragments associated with target traits to search for putative candidate genes. The phenotypic data analysis showed that the broad-sense heritability values were above 0.48 and 0.49 for the first and second harvests, respectively. The set of 100 SSR markers produced 1,483 fragments, of which 99.5% were polymorphic. These SSR fragments were useful to estimate the most likely number of subpopulations, found to be four, and the LD in BPSG, which was stronger in the first 15 cM and present to a large extension (65 cM). Genetic diversity analysis showed that, in general, the clustering of accessions within the subpopulations was in accordance with the pedigree information. GWAS performed through a multilocus mixed model revealed 23 MTAs, six, three, seven, four and three for soluble solid content, stalk height, stalk number, stalk weight and cane yield traits, respectively. These MTAs may be validated in other populations to support sugarcane breeding programs with introgression of favorable alleles and marker-assisted selection.

Genotyping-by-sequencing highlights patterns of genetic structure and domestication in artichoke and cardoon

Exploiting the biodiversity of crops and their wild relatives is fundamental for maintaining and increasing food security. The species Cynara cardunculus includes three taxa: the globe artichoke, one of the most important Mediterranean vegetables, the leafy cardoon, and the wild cardoon. In this study, genotyping by sequencing (GBS) was successfully applied to reveal thousands of polymorphisms in a C. cardunculus germplasm collection, including 65 globe artichoke, 9 leafy cardoon, and 21 wild cardoon samples. The collection showed a strong population structure at K = 2, separating the globe artichoke from the leafy and wild cardoon. At higher K values, further substructures were observed, in which the wild cardoon was separated from the leafy cardoon, and the latter included the Spanish wild cardoons, while the wild sample from Portugal was admixed. Moreover, subpopulations within the globe artichoke set were highlighted. Structure analysis restricted to the globe artichoke dataset pointed out genetic differentiation between the ˝Catanesi˝ typology and all the other samples (K = 2). At higher values of K, the separation of the ˝Catanesi˝ group still held true, and green headed landraces from Apulia region, Italy (˝Green Apulian˝) formed a distinct subpopulation. ˝Romaneschi˝ artichoke types fell in a variable group with admixed samples, indicating that they should not be considered as a genetically uniform typology. The results of principal component analysis and Neighbor-Joining hierarchical clustering were consistent with structure results, and in addition provided a measure of genetic relationships among individual genotypes. Both analyses attributed the wild material from Spain and Portugal to the cultivated cardoon group, supporting the idea that this might be indeed a feral form of the leafy cardoon. Different reproductive habit and possibly selective pressure led to a slower LD decay in artichoke compared to cardoon. Genotyping by sequencing has proven a reliable methodology to obtain valuable SNPs and assess population genetics in C. cardunculus.

A mosaic monoploid reference sequence for the highly complex genome of sugarcane

Sugarcane (Saccharum spp.) is a major crop for sugar and bioenergy production. Its highly polyploid, aneuploid, heterozygous, and interspecific genome poses major challenges for producing a reference sequence. We exploited colinearity with sorghum to produce a BAC-based monoploid genome sequence of sugarcane. A minimum tiling path of 4660 sugarcane BAC that best covers the gene-rich part of the sorghum genome was selected based on whole-genome profiling, sequenced, and assembled in a 382-Mb single tiling path of a high-quality sequence. A total of 25,316 protein-coding gene models are predicted, 17% of which display no colinearity with their sorghum orthologs. We show that the two species, S. officinarum and S. spontaneum, involved in modern cultivars differ by their transposable elements and by a few large chromosomal rearrangements, explaining their distinct genome size and distinct basic chromosome numbers while also suggesting that polyploidization arose in both lineages after their divergence.

Detection and validation of EST-SSR markers associated with sugar-related traits in sugarcane using linkage and association mapping

Sugar-related traits are of great importance in sugarcane breeding. In the present study, quantitative trait loci (QTL) mapping validated with association mapping was used to identify expressed sequence tag-simple sequence repeats (EST-SSRs) associated with sugar-related traits. For linkage mapping, 524 EST-SSRs, 241 Amplified Fragment Length Polymorphisms, and 10 genomic SSR markers were mapped using 283 F₁ progenies derived from an interspecific cross. Six regions were identified using Multiple QTL Mapping, and 14 unlinked markers using single marker analysis. Association analysis was performed on a set of 200 accessions, based on the mixed linear model. Validation of the EST-SSR markers using association mapping within the target QTL genomic regions identified two EST-SSR markers showing a putative relationship with uridine diphosphate (UDP) glycosyltransferase, and beta-amylase, which are associated with pol and sugar yield. These functional markers can be used for marker-assisted selection of sugarcane.

GBS-based single dosage markers for linkage and QTL mapping allow gene mining for yield-related traits in sugarcane

BACKGROUND

Sugarcane (Saccharum spp.) is predominantly an autopolyploid plant with a variable ploidy level, frequent aneuploidy and a large genome that hampers investigation of its organization. Genetic architecture studies are important for identifying genomic regions associated with traits of interest. However, due to the genetic complexity of sugarcane, the practical applications of genomic tools have been notably delayed in this crop, in contrast to other crops that have already advanced to marker-assisted selection (MAS) and genomic selection. High-throughput next-generation sequencing (NGS) technologies have opened new opportunities for discovering molecular markers, especially single nucleotide polymorphisms (SNPs) and insertion-deletion (indels), at the genome-wide level. The objectives of this study were to (i) establish a pipeline for identifying variants from genotyping-by-sequencing (GBS) data in sugarcane, (ii) construct an integrated genetic map with GBS-based markers plus target region amplification polymorphisms and microsatellites, (iii) detect QTLs related to yield component traits, and (iv) perform annotation of the sequences that originated the associated markers with mapped QTLs to search putative candidate genes.

RESULTS

We used four pseudo-references to align the GBS reads. Depending on the reference, from 3,433 to 15,906 high-quality markers were discovered, and half of them segregated as single-dose markers (SDMs) on average. In addition to 7,049 non-redundant SDMs from GBS, 629 gel-based markers were used in a subsequent linkage analysis. Of 7,678 SDMs, 993 were mapped. These markers were distributed throughout 223 linkage groups, which were clustered in 18 homo(eo)logous groups (HGs), with a cumulative map length of 3,682.04 cM and an average marker density of 3.70 cM. We performed QTL mapping of four traits and found seven QTLs. Our results suggest the presence of a stable QTL across locations. Furthermore, QTLs to soluble solid content (BRIX) and fiber content (FIB) traits had markers linked to putative candidate genes.

CONCLUSIONS

This study is the first to report the use of GBS for large-scale variant discovery and genotyping of a mapping population in sugarcane, providing several insights regarding the use of NGS data in a polyploid, non-model species. The use of GBS generated a large number of markers and still enabled ploidy and allelic dosage estimation. Moreover, we were able to identify seven QTLs, two of which had great potential for validation and future use for molecular breeding in sugarcane.

Evaluation of LD decay and various LD-decay estimators in simulated and SNP-array data of tetraploid potato

The number of SNPs required for QTL discovery is justified by the distance at which linkage disequilibrium has decayed. Simulations and real potato SNP data showed how to estimate and interpret LD decay. The magnitude of linkage disequilibrium (LD) and its decay with genetic distance determine the resolution of association mapping, and are useful for assessing the desired numbers of SNPs on arrays. To study LD and LD decay in tetraploid potato, we simulated autotetraploid genotypes and used it to explore the dependence on: (1) the number of haplotypes in the population (the amount of genetic variation) and (2) the percentage of haplotype specific SNPs (hs-SNPs). Several estimators for short-range LD were explored, such as the average r ², median r ², and other percentiles of r ² (80, 90, and 95 %). For LD decay, we looked at LD_½,90, the distance at which the short-range LD is halved when using the 90 % percentile of r ² at short range, as estimator for LD. Simulations showed that the performance of various estimators for LD decay strongly depended on the number of haplotypes, although the real value of LD decay was not influenced very much by this number. The estimator LD_½,90 was chosen to evaluate LD decay in 537 tetraploid varieties. LD_½,90 values were 1.5 Mb for varieties released before 1945 and 0.6 Mb in varieties released after 2005. LD_½,90 values within three different subpopulations ranged from 0.7 to 0.9 Mb. LD_½,90 was 2.5 Mb for introgressed regions, indicating large haplotype blocks. In pericentromeric heterochromatin, LD decay was negligible. This study demonstrates that several related factors influencing LD decay could be disentangled, that no universal approach can be suggested, and that the estimation of LD decay has to be performed with great care and knowledge of the sampled material.

Single nucleotide polymorphism in sugar pathway and disease resistance genes in sugarcane

Single nucleotide polymorphism in sugar pathway and disease resistance genes showing genetic association with sugar content and red rot resistance would be useful in marker-assisted genetic improvement of sugarcane. Validation and genotyping of potential sequence variants in candidate genes are necessary to understand their functional significance and trait association potential. We discovered, characterized, validated and genotyped SNPs and InDels in sugar pathway and disease resistance genes of Saccharum complex and sugarcane varieties using amplicon sequencing and CAPS assays. The SNPs were abundant in the non-coding 3'UTRs than 5'UTRs and coding sequences depicting a strong bias toward C to T transition substitutions than transversions. Sequencing of cloned amplicons validated 61.6 and 45.2 % SNPs detected in silico in 21 sugar pathway and 16 disease resistance genes, respectively. Sixteen SNPs in four sugar pathway genes and 10 SNPs in nine disease resistance genes were validated through cost-effective CAPS assay. Functional and adaptive significance of SNP and protein haplotypes identified in sugar pathway and disease resistance genes was assessed by correlating their allelic variation with missense amino acid substitutions in the functional domains, alteration in protein structure models and possible modulation of catalytic enzyme activity in contrasting high and low sugar and moderately red rot resistant and highly susceptible sugarcane genotypes. A strong genetic association of five SNPs in the sugar pathway and disease resistance genes, and an InDel marker in the promoter sequence of sucrose synthase-2 gene, with sugar content and red rot resistance, was evident. The functionally relevant SNPs and InDels, detected and validated in sugar pathway and disease resistance genes, and genic CAPS markers designed, would be of immense use in marker-assisted genetic improvement of sugarcane for sugar content and disease resistance.

Genome-wide association mapping of quantitative traits in a breeding population of sugarcane

BACKGROUND

Molecular markers associated with relevant agronomic traits could significantly reduce the time and cost involved in developing new sugarcane varieties. Previous sugarcane genome-wide association analyses (GWAS) have found few molecular markers associated with relevant traits at plant-cane stage. The aim of this study was to establish an appropriate GWAS to find molecular markers associated with yield related traits consistent across harvesting seasons in a breeding population. Sugarcane clones were genotyped with DArT (Diversity Array Technology) and TRAP (Target Region Amplified Polymorphism) markers, and evaluated for cane yield (CY) and sugar content (SC) at two locations during three successive crop cycles. GWAS mapping was applied within a novel mixed-model framework accounting for population structure with Principal Component Analysis scores as random component.

RESULTS

A total of 43 markers significantly associated with CY in plant-cane, 42 in first ratoon, and 41 in second ratoon were detected. Out of these markers, 20 were associated with CY in 2 years. Additionally, 38 significant associations for SC were detected in plant-cane, 34 in first ratoon, and 47 in second ratoon. For SC, one marker-trait association was found significant for the 3 years of the study, while twelve markers presented association for 2 years. In the multi-QTL model several markers with large allelic substitution effect were found. Sequences of four DArT markers showed high similitude and e-value with coding sequences of Sorghum bicolor, confirming the high gene microlinearity between sorghum and sugarcane.

CONCLUSIONS

In contrast with other sugarcane GWAS studies reported earlier, the novel methodology to analyze multi-QTLs through successive crop cycles used in the present study allowed us to find several markers associated with relevant traits. Combining existing phenotypic trial data and genotypic DArT and TRAP marker characterizations within a GWAS approach including population structure as random covariates may prove to be highly successful. Moreover, sequences of DArT marker associated with the traits of interest were aligned in chromosomal regions where sorghum QTLs has previously been reported. This approach could be a valuable tool to assist the improvement of sugarcane and better supply sugarcane demand that has been projected for the upcoming decades.

Potential for Genetic Improvement of Sugarcane as a Source of Biomass for Biofuels

Sugarcane (Saccharum spp. hybrids) has great potential as a major feedstock for biofuel production worldwide. It is considered among the best options for producing biofuels today due to an exceptional biomass production capacity, high carbohydrate (sugar + fiber) content, and a favorable energy input/output ratio. To maximize the conversion of sugarcane biomass into biofuels, it is imperative to generate improved sugarcane varieties with better biomass degradability. However, unlike many diploid plants, where genetic tools are well developed, biotechnological improvement is hindered in sugarcane by our current limited understanding of the large and complex genome. Therefore, understanding the genetics of the key biofuel traits in sugarcane and optimization of sugarcane biomass composition will advance efficient conversion of sugarcane biomass into fermentable sugars for biofuel production. The large existing phenotypic variation in Saccharum germplasm and the availability of the current genomics technologies will allow biofuel traits to be characterized, the genetic basis of critical differences in biomass composition to be determined, and targets for improvement of sugarcane for biofuels to be established. Emerging options for genetic improvement of sugarcane for the use as a bioenergy crop are reviewed. This will better define the targets for potential genetic manipulation of sugarcane biomass composition for biofuels.

Multi-trait multi-environment quantitative trait loci mapping for a sugarcane commercial cross provides insights on the inheritance of important traits

Breeding trials typically consist of phenotypic observations for various traits evaluated in multiple environments. For sugarcane in particular, repeated measures are obtained for plant crop and one or more ratoons, such that joint analysis through mixed models for modeling heterogeneous genetic (co)variances between traits, locations and harvests is appropriate. This modeling approach also enables us to include molecular marker information, aiding in understanding the genetic architecture of quantitative traits. Our work aims at detecting QTL and QTL by environment interactions by fitting mixed models with multiple QTLs, with appropriate modeling of multi-trait multi-environment data for outcrossing species. We evaluated 100 individuals from a biparental cross at two locations and three  years for fiber content, sugar content (POL) and tonnes of cane per hectare (TCH). We detected 13 QTLs exhibiting QTL by location, QTL by harvest or the three-way interaction. Overall, 11 of the 13 effects presented some degree of pleiotropy, affecting at least two traits. Furthermore, these QTLs always affected fiber and TCH in the same direction, whereas POL was affected in the opposite way. There was no evidence in favor of the linked QTL over the pleiotropic QTL hypothesis for any detected genome position. These results provide valuable insights into the genetic basis of quantitative variation in sugarcane and the genetic relation between traits.

Prospecting sugarcane resistance to Sugarcane yellow leaf virus by genome-wide association

Using GWAS approaches, we detected independent resistant markers in sugarcane towards a vectored virus disease. Based on comparative genomics, several candidate genes potentially involved in virus/aphid/plant interactions were pinpointed. Yellow leaf of sugarcane is an emerging viral disease whose causal agent is a Polerovirus, the Sugarcane yellow leaf virus (SCYLV) transmitted by aphids. To identify quantitative trait loci controlling resistance to yellow leaf which are of direct relevance for breeding, we undertook a genome-wide association study (GWAS) on a sugarcane cultivar panel (n = 189) representative of current breeding germplasm. This panel was fingerprinted with 3,949 polymorphic markers (DArT and AFLP). The panel was phenotyped for SCYLV infection in leaves and stalks in two trials for two crop cycles, under natural disease pressure prevalent in Guadeloupe. Mixed linear models including co-factors representing population structure fixed effects and pairwise kinship random effects provided an efficient control of the risk of inflated type-I error at a genome-wide level. Six independent markers were significantly detected in association with SCYLV resistance phenotype. These markers explained individually between 9 and 14 % of the disease variation of the cultivar panel. Their frequency in the panel was relatively low (8-20 %). Among them, two markers were detected repeatedly across the GWAS exercises based on the different disease resistance parameters. These two markers could be blasted on Sorghum bicolor genome and candidate genes potentially involved in plant-aphid or plant-virus interactions were localized in the vicinity of sorghum homologs of sugarcane markers. Our results illustrate the potential of GWAS approaches to prospect among sugarcane germplasm for accessions likely bearing resistance alleles of significant effect useful in breeding programs.

Identification of agronomically important QTL in tetraploid potato cultivars using a marker-trait association analysis

Nineteen tuber quality traits in potato were phenotyped in 205 cultivars and 299 breeder clones. Association analysis using 3364 AFLP loci and 653 SSR-alleles identified QTL for these traits. Two association mapping panels were analysed for marker-trait associations to identify quantitative trait loci (QTL). The first panel comprised 205 historical and contemporary tetraploid potato cultivars that were phenotyped in field trials at two locations with two replicates (the academic panel). The second panel consisted of 299 potato cultivars and included recent breeds obtained from five Dutch potato breeding companies and reference cultivars (the industrial panel). Phenotypic data for the second panel were collected during subsequent clonal selection generations at the individual breeding companies. QTL were identified for 19 agro-morphological and quality traits. Two association mapping models were used: a baseline model without, and a more advanced model with correction for population structure and genetic relatedness. Correction for population structure and genetic relatedness was performed with a kinship matrix estimated from marker information. The detected QTL partly not only confirmed previous studies, e.g. for tuber shape and frying colour, but also new QTL were found like for after baking darkening and enzymatic browning. Pleiotropic effects could be discerned for several QTL.

Experimental assessment of the accuracy of genomic selection in sugarcane

Sugarcane cultivars are interspecific hybrids with an aneuploid, highly heterozygous polyploid genome. The complexity of the sugarcane genome is the main obstacle to the use of marker-assisted selection in sugarcane breeding. Given the promising results of recent studies of plant genomic selection, we explored the feasibility of genomic selection in this complex polyploid crop. Genetic values were predicted in two independent panels, each composed of 167 accessions representing sugarcane genetic diversity worldwide. Accessions were genotyped with 1,499 DArT markers. One panel was phenotyped in Reunion Island and the other in Guadeloupe. Ten traits concerning sugar and bagasse contents, digestibility and composition of the bagasse, plant morphology, and disease resistance were used. We used four statistical predictive models: bayesian LASSO, ridge regression, reproducing kernel Hilbert space, and partial least square regression. The accuracy of the predictions was assessed through the correlation between observed and predicted genetic values by cross validation within each panel and between the two panels. We observed equivalent accuracy among the four predictive models for a given trait, and marked differences were observed among traits. Depending on the trait concerned, within-panel cross validation yielded median correlations ranging from 0.29 to 0.62 in the Reunion Island panel and from 0.11 to 0.5 in the Guadeloupe panel. Cross validation between panels yielded correlations ranging from 0.13 for smut resistance to 0.55 for brix. This level of correlations is promising for future implementations. Our results provide the first validation of genomic selection in sugarcane.

Hidden diversity in wild Beta taxa from Portugal: insights from genome size and ploidy level estimations using flow cytometry

Crop wild relatives constitute a broad pool of potentially useful genetic resources for plant breeders. The genus Beta L. (Amaranthaceae) is an important source of crops, primarily for sugar production. Until recently, species within Section Beta were mostly cytogenetically uniform, with diploidy being prevalent. Still, with the discovery of tetraploid individuals of the wild B. macrocarpa in the Canary Islands, a large-scale study was necessary to evaluate the cytogenetic diversity within the wild Beta. For that, genome size and ploidy level of B. vulgaris subsp. maritima and B. macrocarpa from 21 populations across Portugal mainland and islands, including all know populations of the later taxon, were estimated using propidium iodide flow cytometry. This work revealed a cytogenetically diverse scenario. The analyzed populations were mostly diploid, except for one population of B. vulgaris subsp. maritima that presented both diploid and tetraploid individuals, and for two populations of B. macrocarpa where two or three cytotypes (diploids, tetraploids and/or hexaploids) were found. The nuclear DNA content of diploid individuals was estimated as 1.44±0.035 and 1.41±0.027 pg/2C for B. vulgaris subsp. maritima and B. macrocarpa, respectively. Also, leaves of both species presented variable levels of endopolyploidy. The obtained results are discussed within the context of interspecific hybridization and cryptic diversity and constitute significant data for the conservation of these wild Beta crop relatives.

Haplotype structure around Bru1 reveals a narrow genetic basis for brown rust resistance in modern sugarcane cultivars

Modern sugarcane cultivars (Saccharum spp., 2n = 100-130) are high polyploid, aneuploid and of interspecific origin. A major gene (Bru1) conferring resistance to brown rust, caused by the fungus Puccinia melanocephala, has been identified in cultivar R570. We analyzed 380 modern cultivars and breeding materials covering the worldwide diversity with 22 molecular markers genetically linked to Bru1 in R570 within a 8.2 cM segment. Our results revealed a strong LD in the Bru1 region and strong associations between most of the markers and rust resistance. Two PCR markers, that flank the Bru1-bearing segment, were found completely associated with one another and only in resistant clones representing efficient molecular diagnostic for Bru1. On this basis, Bru1 was inferred in 86 % of the 194 resistant sugarcane accessions, revealing that it constitutes the main source of brown rust resistance in modern cultivars. Bru1 PCR diagnostic markers should be particularly useful to identify cultivars with potentially alternative sources of resistance to diversify the basis of brown rust resistance in breeding programs.

Sugarcane improvement: how far can we go?

In recent years, efforts to improve sugarcane have focused on the development of biotechnology for this crop. It has become clear that sugarcane lacks tools for the biotechnological route of improvement and that the initial efforts in sequencing ESTs had limited impact for breeding. Until recently, the models used by breeders in statistical genetics approaches have been developed for diploid organisms, which are not ideal for a polyploid genome such as that of sugarcane. Breeding programs are dealing with decreasing yield gains. The contribution of multiple alleles to complex traits such as yield is a basic question underlining the breeding efforts that could only be addressed by the development of specific tools for this grass. However, functional genomics has progressed and gene expression profiling is leading to the definition of gene networks. The sequencing of the sugarcane genome, which is underway, will greatly contribute to numerous aspects of research on grasses. We expect that both the transgenic and the marker-assisted route for sugarcane improvement will contribute to increased sugar, stress tolerance, and higher yield and that the industry for years to come will be able to rely on sugarcane as the most productive energy crop.

Simultaneously accounting for population structure, genotype by environment interaction, and spatial variation in marker–trait associations in sugarcaneThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”

Few association mapping studies have simultaneously accounted for population structure, genotype by environment interaction (GEI), and spatial variation. In this sugarcane association mapping study we tested models accounting for these factors and identified the impact that each model component had on the list of markers declared as being significantly associated with traits. About 480 genotypes were evaluated for cane yield and sugar content at three sites and scored with DArT markers. A mixed model was applied in analysis of the data to simultaneously account for the impacts of population structure, GEI, and spatial variation within a trial. Two forms of the DArT marker data were used in the analysis: the standard discrete data (0, 1) and a continuous DArT score, which is related to the marker dosage. A large number of markers were significantly associated with cane yield and sugar content. However, failure to account for population structure, GEI, and (or) spatial variation produced both type I and type II errors, which on the one hand substantially inflated the number of significant markers identified (especially true for failing to account for GEI) and on the other hand resulted in failure to detect markers that could be associated with cane yield or sugar content (especially when failing to account for population structure). We concluded that association mapping based on trials from one site or analysis that failed to account for GEI would produce many trial-specific associated markers that would have low value in breeding programs.

Population structure and linkage disequilibrium unravelled in tetraploid potato

Association mapping is considered to be an important alternative strategy for the identification of quantitative trait loci (QTL) as compared to traditional QTL mapping. A necessary prerequisite for association analysis to succeed is detailed information regarding hidden population structure and the extent of linkage disequilibrium. A collection of 430 tetraploid potato cultivars, comprising two association panels, has been analysed with 41 AFLP(®) and 53 SSR primer combinations yielding 3364 AFLP fragments and 653 microsatellite alleles, respectively. Polymorphism information content values and detected number of alleles for the SSRs studied illustrate that commercial potato germplasm seems to be equally diverse as Latin American landrace material. Genome-wide linkage disequilibrium (LD)-reported for the first time for tetraploid potato-was observed up to approximately 5 cM using r (2) higher than 0.1 as a criterion for significant LD. Within-group LD, however, stretched on average twice as far when compared to overall LD. A Bayesian approach, a distance-based hierarchical clustering approach as well as principal coordinate analysis were adopted to enquire into population structure. Groups differing in year of market release and market segment (starch, processing industry and fresh consumption) were repeatedly detected. The observation of LD up to 5 cM is promising because the required marker density is not likely to disable the possibilities for association mapping research in tetraploid potato. Population structure appeared to be weak, but strong enough to demand careful modelling of genetic relationships in subsequent marker-trait association analyses. There seems to be a good chance that linkage-based marker-trait associations can be identified at moderate marker densities.

Inference of haplotypic phase and missing genotypes in polyploid organisms and variable copy number genomic regions

Background

The power of haplotype-based methods for association studies, identification of regions under selection, and ancestral inference, is well-established for diploid organisms. For polyploids, however, the difficulty of determining phase has limited such approaches. Polyploidy is common in plants and is also observed in animals. Partial polyploidy is sometimes observed in humans (e.g. trisomy 21; Down's syndrome), and it arises more frequently in some human tissues. Local changes in ploidy, known as copy number variations (CNV), arise throughout the genome. Here we present a method, implemented in the software polyHap, for the inference of haplotype phase and missing observations from polyploid genotypes. PolyHap allows each individual to have a different ploidy, but ploidy cannot vary over the genomic region analysed. It employs a hidden Markov model (HMM) and a sampling algorithm to infer haplotypes jointly in multiple individuals and to obtain a measure of uncertainty in its inferences.

Results

In the simulation study, we combine real haplotype data to create artificial diploid, triploid, and tetraploid genotypes, and use these to demonstrate that polyHap performs well, in terms of both switch error rate in recovering phase and imputation error rate for missing genotypes. To our knowledge, there is no comparable software for phasing a large, densely genotyped region of chromosome from triploids and tetraploids, while for diploids we found polyHap to be more accurate than fastPhase. We also compare the results of polyHap to SATlotyper on an experimentally haplotyped tetraploid dataset of 12 SNPs, and show that polyHap is more accurate.

Conclusion

With the availability of large SNP data in polyploids and CNV regions, we believe that polyHap, our proposed method for inferring haplotypic phase from genotype data, will be useful in enabling researchers analysing such data to exploit the power of haplotype-based analyses.

Diploid/polyploid syntenic shuttle mapping and haplotype-specific chromosome walking toward a rust resistance gene (Bru1) in highly polyploid sugarcane (2n approximately 12x approximately 115)

The genome of modern sugarcane cultivars is highly polyploid (approximately 12x), aneuploid, of interspecific origin, and contains 10 Gb of DNA. Its size and complexity represent a major challenge for the isolation of agronomically important genes. Here we report on the first attempt to isolate a gene from sugarcane by map-based cloning, targeting a durable major rust resistance gene (Bru1). We describe the genomic strategies that we have developed to overcome constraints associated with high polyploidy in the successive steps of map-based cloning approaches, including diploid/polyploid syntenic shuttle mapping with two model diploid species (sorghum and rice) and haplotype-specific chromosome walking. Their applications allowed us (i) to develop a high-resolution map including markers at 0.28 and 0.14 cM on both sides and 13 markers cosegregating with Bru1 and (ii) to develop a physical map of the target haplotype that still includes two gaps at this stage due to the discovery of an insertion specific to this haplotype. These approaches will pave the way for the development of future map-based cloning approaches for sugarcane and other complex polyploid species.