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Key message Utilizing a high-density integrated genetic linkage map of hexaploid sweetpotato, we discovered a major dominant QTL for root-knot nematode (RKN) resistance and modeled its effects. This discovery is useful for development of a modern sweetpotato breeding program that utilizes marker-assisted selection and genomic selection approaches for faster genetic gain of RKN resistance. Abstract The root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) causes significant storage root quality reduction and yields losses in cultivated sweetpotato [Ipomoea batatas (L.) Lam.]. In this study, resistance to RKN was examined in a mapping population consisting of 244 progenies derived from a cross (TB) between ‘Tanzania,’ a predominant African landrace cultivar with resistance to RKN, and ‘Beauregard,’ an RKN susceptible major cultivar in the USA. We performed quantitative trait loci (QTL) analysis using a random-effect QTL mapping model on the TB genetic map. An RKN bioassay incorporating potted cuttings of each genotype was conducted in the greenhouse and replicated five times over a period of 10 weeks. For each replication, each genotype was inoculated with ca. 20,000 RKN eggs, and root-knot galls were counted ~62 days after inoculation. Resistance to RKN in the progeny was highly skewed toward the resistant parent, exhibiting medium to high levels of resistance. We identified one major QTL on linkage group 7, dominant in nature, which explained 58.3% of the phenotypic variation in RKN counts. This work represents a significant step forward in our understanding of the genetic architecture of RKN resistance and sets the stage for future utilization of genomics-assisted breeding in sweetpotato breeding programs.

There are many challenges involved with the genetic analyses of autopolyploid species, such as the tetraploid potato, Solanum tuberosum (2n = 4x = 48). The development of new analytical methods has made it valuable to re-analyze an F1 population (n = 156) derived from a cross involving ‘Atlantic’, a widely grown chipping variety in the USA. A fully integrated genetic map with 4285 single nucleotide polymorphisms, spanning 1630 cM, was constructed with MAPpoly software. We observed that bivalent configurations were the most abundant ones (51.0~72.4% depending on parent and linkage group), though multivalent configurations were also observed (2.2~39.2%). Seven traits were evaluated over four years (2006–8 and 2014) and quantitative trait loci (QTL) mapping was carried out using QTLpoly software. Based on a multiple-QTL model approach, we detected 21 QTL for 15 out of 27 trait-year combination phenotypes. A hotspot on linkage group 5 was identified with co-located QTL for maturity, plant yield, specific gravity, and internal heat necrosis resistance evaluated over different years. Additional QTL for specific gravity and dry matter were detected with maturity-corrected phenotypes. Among the genes around QTL peaks, we found those on chromosome 5 that have been previously implicated in maturity (StCDF1) and tuber formation (POTH1). These analyses have the potential to provide insights into the biology and breeding of tetraploid potato and other autopolyploid species.

Key message Polypoid crop breeders can balance resources between density and sequencing depth, dosage information and fewer highly informative SNPs recommended, non-additive models and QTL advantages on prediction dependent on trait architecture. Abstract The autopolyploid nature of potato and sweetpotato ensures a wide range of meiotic configurations and linkage phases leading to complex gene-action and pose problems in genotype data quality and genomic selection analyses. We used a 315-progeny biparental F1 population of hexaploid sweetpotato and a diversity panel of 380 tetraploid potato, genotyped using different platforms to answer the following questions: (i) do polyploid crop breeders need to invest more for additional sequencing depth? (ii) how many markers are required to make selection decisions? (iii) does considering non-additive genetic effects improve predictive ability (PA)? (iv) does considering dosage or quantitative trait loci (QTL) offer significant improvement to PA? Our results show that only a small number of highly informative single nucleotide polymorphisms (SNPs; ≤ 1000) are adequate for prediction in the type of populations we analyzed. We also show that considering dosage information and models considering only additive effects had the best PA for most traits, while the comparative advantage of considering non-additive genetic effects and including known QTL in the predictive model depended on trait architecture. We conclude that genomic selection can help accelerate the rate of genetic gains in potato and sweetpotato. However, application of genomic selection should be considered as part of optimizing the entire breeding program. Additionally, since the predictions in the current study are based on single populations, further studies on the effects of haplotype structure and inheritance on PA should be studied in actual multi-generation breeding populations.

Genetic analysis in autopolyploids is a very complicated subject due to the enormous number of genotypes at a locus that needs to be considered. For instance, the number of..., In developing countries, the sweetpotato, Ipomoea batatas (L.) Lam. (2n=6x=90), is an important autopolyploid species, both socially and economically. However, quantitative trait loci (QTL) mapping has remained limited due to its genetic complexity. Current fixed-effect models can fit only a single QTL and are generally hard to interpret. Here, we report the use of a random-effect model approach to map multiple QTL based on score statistics in a sweetpotato biparental population (‘Beauregard’ × ‘Tanzania’) with 315 full-sibs. Phenotypic data were collected for eight yield component traits in six environments in Peru, and jointly adjusted means were obtained using mixed-effect models. An integrated linkage map consisting of 30,684 markers distributed along 15 linkage groups (LGs) was used to obtain the genotype conditional probabilities of putative QTL at every centiMorgan position. Multiple interval mapping was performed using our R package QTLpoly and detected a total of 13 QTL, ranging from none to four QTL per trait, which explained up to 55% of the total variance. Some regions, such as those on LGs 3 and 15, were consistently detected among root number and yield traits, and provided a basis for candidate gene search. In addition, some QTL were found to affect commercial and noncommercial root traits distinctly. Further best linear unbiased predictions were decomposed into additive allele effects and were used to compute multiple QTL-based breeding values for selection. Together with quantitative genotyping and its appropriate usage in linkage analyses, this QTL mapping methodology will facilitate the use of genomic tools in sweetpotato breeding as well as in other autopolyploids.

Accurate QTL mapping in outcrossing species requires software programs which consider genetic features of these populations, such as markers with different segregation patterns and different level of information. Although the available mapping procedures to date allow inferring QTL position and effects, they are mostly not based on multilocus genetic maps. Having a QTL analysis based in such maps is crucial since they allow informative markers to propagate their information to less informative intervals of the map. We developedfullsibQTL, a novel and freely availableRpackage to perform composite interval QTL mapping considering outcrossing populations and markers with different segregation patterns. It allows to estimate QTL position, effects, segregation patterns, and linkage phase with flanking markers. Additionally, several statistical and graphical tools are implemented, for straightforward analysis and interpretations.fullsibQTLis anRopen source package withCandRsource code (GPLv3). It is multiplatform and can be installed fromhttps://github.com/augusto-garcia/fullsibQTL.

Despite the negative impact of common scab (Streptomyces spp.) on the potato industry, little is known about the genetic architecture of resistance to this bacterial disease in the crop. We evaluated a mapping population (∼150 full sibs) derived from a cross between two tetraploid potatoes (‘Atlantic’ × B1829-5) in three environments (MN11, PA11, ME12) under natural common scab pressure. Three measures to common scab reaction, namely percentage of scabby tubers and disease area and lesion indices, were found to be highly correlated (>0.76). Because of the large environmental effect, heritability values were zero for all three traits in MN11, but moderate to high in PA11 and ME12 (∼0.44 to 0.79). We identified a single quantitative trait locus (QTL) for lesion index in PA11, ME12, and joint analyses on linkage group 3, explaining ∼22 to 30% of the total variation. The identification of QTL haplotypes and candidate genes contributing to disease resistance can support genomics-assisted breeding approaches in the crop. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

There are many challenges involved with the genetic analyses of autopolyploid species, such as the tetraploid potato,Solanum tuberosum(2n= 4x= 48). The development of new analytical methods has made it valuable to re-analyze an F1 population (n= 156) derived from a cross involving ‘Atlantic’, a widely grown chipping variety in the USA. A fully integrated genetic map with 4,285 single nucleotide polymorphisms, spanning 1,630 cM, was constructed with MAPpoly software. We observed that bivalent configurations were the most abundant ones (51.0∼72.4% depending on parent and linkage group), though multivalent configurations were also observed (2.2∼39.2%). Seven traits were evaluated over four years (2006-8 and 2014) and quantitative trait loci (QTL) mapping was carried out using QTLpoly software. Based on a multiple-QTL model approach, we detected 21 QTL for 15 out of 27 trait-year combination phenotypes. A hotspot on linkage group 5 was identified as QTL for maturity, plant yield, specific gravity and internal heat necrosis resistance over different years were co-located. Additional QTL for specific gravity and dry matter were detected with maturity-corrected phenotypes. Among the genes around QTL peaks, we found those on chromosome 5 that have been previously implicated in maturity (StCDF1) and tuber formation (POTH1). These analyses have the potential to provide insights into the biology and breeding of tetraploid potato and other autopolyploid species.

There are many challenges involved with the genetic analyses of autopolyploid species, such as the tetraploid potato, Solanum tuberosum (2n = 4x = 48). The development of new analytical methods has made it valuable to re-analyze an F1 population (n = 156) derived from a cross involving ‘Atlantic’, a widely grown chipping variety in the USA. A fully integrated genetic map with 4285 single nucleotide polymorphisms, spanning 1630 cM, was constructed with MAPpoly software. We observed that bivalent configurations were the most abundant ones (51.0~72.4% depending on parent and linkage group), though multivalent configurations were also observed (2.2~39.2%). Seven traits were evaluated over four years (2006–8 and 2014) and quantitative trait loci (QTL) mapping was carried out using QTLpoly software. Based on a multiple-QTL model approach, we detected 21 QTL for 15 out of 27 trait-year combination phenotypes. A hotspot on linkage group 5 was identified with co-located QTL for maturity, plant yield, specific gravity, and internal heat necrosis resistance evaluated over different years. Additional QTL for specific gravity and dry matter were detected with maturity-corrected phenotypes. Among the genes around QTL peaks, we found those on chromosome 5 that have been previously implicated in maturity (StCDF1) and tuber formation (POTH1). These analyses have the potential to provide insights into the biology and breeding of tetraploid potato and other autopolyploid species.

The autopolyploid nature of potato and sweetpotato ensures a wide range of meiotic configurations and linkage phases leading to complex gene action and pose problems in genotype data quality and genomic selection analyses. We used a 315-progeny biparental population of hexaploid sweetpotato and a diversity panel of 380 tetraploid potato, genotyped using different platforms to answer the following questions: i) do polyploid crop breeders need to invest more for additional sequencing depth? ii) how many markers are required to make selection decisions? iii) does considering non-additive genetic effects improve predictive ability (PA)? iv) does considering dosage or quantitative trait loci (QTL) offer significant improvement to PA? Our results show that only a small number of highly informative single nucleotide polymorphisms (SNPs; ≤ 1000) are adequate for prediction, hence it is possible to get this number at the current sequencing depth from most service providers. We also show that considering dosage information and additive-effects only models had the best PA for most traits, while the comparative advantage of considering non-additive genetic effects and including known QTL in the predictive model depended on trait architecture. We conclude that genomic selection can help accelerate the rate of genetic gains in potato and sweetpotato. However, application of genomic selection should be considered as part of optimizing the entire breeding program. Additionally, since the predictions in the current study are based on single populations, further studies on the effects of haplotype structure and inheritance on PA should be studied in actual multi-generation breeding populations.Key messagePolypoid crop breeders do not need more investment for sequencing depth, dosage information and fewer highly informative SNPs recommended, non-additive models and QTL advantages on prediction dependent on trait architecture.

Plant cytogenetic studies have provided essential knowledge on chromosome behavior during meiosis, contributing to our understanding of this complex process. In this review, we describe in detail the meiotic process in auto- and allopolyploids from the onset of prophase I through pairing, recombination, and bivalent formation, highlighting recent findings on the genetic control and mode of action of specific proteins that lead to diploid-like meiosis behavior in polyploid species. During the meiosis of newly formed polyploids, related chromosomes (homologous in autopolyploids; homologous and homoeologous in allopolyploids) can combine in complex structures called multivalents. These structures occur when multiple chromosomes simultaneously pair, synapse, and recombine. We discuss the effectiveness of crossover frequency in preventing multivalent formation and favoring regular meiosis. Homoeologous recombination in particular can generate new gene (locus) combinations and phenotypes, but it may destabilize the karyotype and lead to aberrant meiotic behavior, reducing fertility. In crop species, understanding the factors that control pairing and recombination has the potential to provide plant breeders with resources to make fuller use of available chromosome variations in number and structure. We focused on wheat and oilseed rape, since there is an abundance of elucidating studies on this subject, including the molecular characterization of the Ph1 (wheat) and PrBn (oilseed rape) loci, which are known to play a crucial role in regulating meiosis. Finally, we exploited the consequences of chromosome pairing and recombination for genetic map construction in polyploids, highlighting two case studies of complex genomes: (i) modern sugarcane, which has a man-made genome harboring two subgenomes with some recombinant chromosomes; and (ii) hexaploid sweet potato, a naturally occurring polyploid. The recent inclusion of allelic dosage information has improved linkage estimation in polyploids, allowing multilocus genetic maps to be constructed.

Quantitative trait locus (QTL) mapping contributes to sugarcane (Saccharum spp.) breeding programs by providing information about the genetic effects, positioning and number of QTLs. Combined with marker-assisted selection, it can help breeders reduce the time required to develop new sugarcane varieties. We performed a QTL mapping study for important agronomic traits in sugarcane using the composite interval mapping method for outcrossed species. A new approach allowing the 1:2:1 segregation ratio and different ploidy levels for SNP markers was used to construct an integrated genetic linkage map that also includes AFLP and SSR markers. Were used 688 molecular markers with 1:1, 3:1 and 1:2:1 segregation ratios. A total of 187 individuals from a bi-parental cross (IACSP95-3018 and IACSP93-3046) were assayed across multiple harvests from two locations. The evaluated yield components included stalk diameter (SD), stalk weight (SW), stalk height (SH), fiber percentage (Fiber), sucrose content (Pol) and soluble solid content (Brix). The genetic linkage map covered 4512.6 cM and had 118 linkage groups corresponding to 16 putative homology groups. A total of 25 QTL were detected for SD (six QTL), SW (five QTL), SH (four QTL), Fiber (five QTL), Pol (two QTL) and Brix (three QTL). The percentage of phenotypic variation explained by each QTL ranged from 0.069 to 3.87 %, with a low individual effect because of the high ploidy level. The mapping model provided estimates of the segregation ratio of each mapped QTL (1:2:1, 3:1 or 1:1). Our results provide information about the genetic organization of the sugarcane genome and constitute the first step toward a better dissection of complex traits.

Modern SNP genotyping technologies allow to measure the relative abundance of different alleles for a given locus and consequently to estimate their allele dosage, opening a new road for genetic studies in autopolyploids. Despite advances in genetic linkage analysis in autotetraploids, there is a lack of statistical models to perform linkage analysis in organisms with higher ploidy levels. In this paper, we present a statistical method to estimate recombination fractions and infer linkage phases in full-sib populations of autopolyploid species with even ploidy levels in a sequence of SNP markers using hidden Markov models. Our method uses efficient two-point procedures to reduce the search space for the best linkage phase configuration and reestimate the final parameters using the maximum-likelihood of the Markov chain. To evaluate the method, and demonstrate its properties, we rely on simulations of autotetraploid, autohexaploid and autooctaploid populations and on a real tetraploid potato data set. The results demonstrate the reliability of our approach, including situations with complex linkage phase scenarios in hexaploid and octaploid populations.Author summaryIn this paper, we present a complete multilocus solution based on hidden Markov models to estimate recombination fractions and infer the linkage phase configuration in full-sib mapping populations with even ploidy levels under random chromosome segregation. We also present an efficient pairwise loci analysis to be used in cases were the multilocus analysis becomes compute-intensive.

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane. Electronic supplementary material The online version of this article (doi:10.1007/s00122-011-1748-8) contains supplementary material, which is available to authorized users.

Copaifera langsdorffii is a Neotropical tree with wide distribution in the Brazilian Atlantic rain forest and savanna. Although eight microsatellite loci (SSR) were developed in 2000 and have been widely used since then, there is yet no information about their inheritance, linkage and linkage disequilibrium (LD). Through the analysis of 28 open-pollinated (OP) progenies, the SSR loci revealed Mendelian inheritance and independent assortment. Using these progenies, young and adult trees LD was mainly detected in OP progenies. Our results show clear evidence that the eight SSR loci can be used without restriction in genetic diversity, mating system and parentage analysis.

Due to the strategic importance of sugarcane to Brazil, FAPESP, the main Sao Paulo state research funding agency, launched in 2008 the FAPESP Bioenergy Research Program (BIOEN, http://bioenfapesp.org). BIOEN aims to generate new knowledge and human resources for the improvement of the sugarcane and ethanol industry. As part of the BIOEN program, a Workshop on Sugarcane Improvement was held on March 18th and 19th 2009 in Sao Paulo, Brazil. The aim of the workshop was to explore present and future challenges for sugarcane improvement and its use as a sustainable bioenergy and biomaterial feedstock. The workshop was divided in four sections that represent important challenges for sugarcane improvement: a) gene discovery and sugarcane genomics, b) transgenics and controlled transgene expression, c) sugarcane physiology (photosynthesis, sucrose metabolism, and drought) and d) breeding and statistical genetics. This report summarizes the roadmap for the improvement of sugarcane.

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with 100 and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results.

The African species Urochloa humidicola (Rendle) Morrone & Zuloaga (syn. Brachiaria humidicola (Rendle) Schweick.) is an important perennial forage grass found throughout the tropics. This species is polyploid, ranging from tetra to nonaploid, and apomictic, which makes genetic studies challenging; therefore, the number of currently available genetic resources is limited. The genomic architecture and evolution of U. humidicola and the molecular markers linked to apomixis were investigated in a full-sib F1 population obtained by crossing the sexual accession H031 and the apomictic cultivar U. humidicola cv. BRS Tupi, both of which are hexaploid. A simple sequence repeat (SSR)-based linkage map was constructed for the species from 102 polymorphic and specific SSR markers based on simplex and double-simplex markers. The map consisted of 49 linkage groups (LGs) and had a total length of 1702.82 cM, with 89 microsatellite loci and an average map density of 10.6 cM. Eight homology groups (HGs) were formed, comprising 22 LGs, and the other LGs remained ungrouped. The locus that controls apospory (apo-locus) was mapped in LG02 and was located 19.4 cM from the locus Bh027.c.D2. In the cytological analyses of some hybrids, bi- to hexavalents at diakinesis were observed, as well as two nucleoli in some meiocytes, smaller chromosomes with preferential allocation within the first metaphase plate and asynchronous chromosome migration to the poles during anaphase. The linkage map and the meiocyte analyses confirm previous reports of hybridization and suggest an allopolyploid origin of the hexaploid U. humidicola. This is the first linkage map of an Urochloa species, and it will be useful for future quantitative trait locus (QTL) analysis after saturation of the map and for genome assembly and evolutionary studies in Urochloa spp. Moreover, the results of the apomixis mapping are consistent with previous reports and confirm the need for additional studies to search for a co-segregating marker.

Mapas genéticos são arranjos lineares que indicam a ordem e distância entre locos nos cromossomos de uma determinada espécie. Recentemente, a grande disponibilidade de marcadores moleculares tem tornado estes mapas cada vez mais saturados, sendo necessários métodos eficientes para sua construção. Uma das etapas que merece mais atenção na construção de mapas de ligação é a ordenação dos marcadores genéticos dentro de cada grupo de ligação. Tal ordenação é considerada um caso especial do clássico problema do caixeiro viajante (TSP), que consiste em escolher a melhor ordem entre todas as possíveis. Entretanto, a estratégia de busca exaustiva torna-se inviável quando o número de marcadores é grande. Nesses casos, para que esses mapas possam ser construídos uma alternativa viável é a utilização de algoritmos que forneçam soluções aproximadas. O objetivo desse trabalho foi avaliar a eficiência dos algoritmos Try (TRY), Seriation (SER), Rapid Chain Delineation (RCD), Recombination Counting and Ordering (RECORD) e Unidirectional Growth (UG), além dos critérios PARF (produto mínimo das frações de recombinação adjacentes), SARF (soma mínima das frações de recombinação adjacentes), SALOD (soma máxima dos LOD scores adjacentes) e LMHC (verossimilhança via cadeias de Markov ocultas), usados juntamente com o algoritmo de verificação de erros RIPPLE, para a construção de mapas genéticos. Para tanto, foi simulado um mapa de ligação de uma espécie vegetal hipotética, diplóide e monóica, contendo 21 marcadores com distância fixa entre eles de 3 centimorgans. Usando o método Monte Carlo, foram obtidas aleatoriamente 550 populações F2 com 100 e 400 indivíduos, além de diferentes combinações de marcadores dominantes e codominantes. Foi ainda simulada perda de 10% e 20% dos dados. Os resultados mostraram que os algoritmos TRY e SER tiveram bons resultados em todas as situações simuladas, mesmo com presença de elevado número de dados perdidos e marcadores dominantes ligados em repulsão, podendo ser então recomendado em situações práticas. Os algoritmos RECORD e UG apresentaram bons resultados na ausência de marcadores dominantes ligados em repulsão, podendo então ser recomendados em situações com poucos marcadores dominantes. Dentre todos os algoritmos, o RCD foi o que se mostrou menos eficiente. O critério LHMC, aplicado com o algoritmo RIPPLE, foi o que apresentou melhores resultados quando se deseja fazer verificações de erros na ordenação. Genetic linkage maps are linear arrangements showing the order and distance between loci in chromosomes of a particular species. Recently, the availability of molecular markers has made such maps more saturated and efficient methods are needed for their construction. One of the steps that deserves more attention in the construction of genetic linkage maps is the ordering of genetic markers within each linkage group. This ordering is considered a special case of the classic traveling salesman problem (TSP), which consists in choosing the best order among all possible ones. However, the strategy of exhaustive search becomes unfeasible when the number of markers is large. One possible alternative to construct such maps is to use algorithms that provide approximate solutions. Thus, the aim of this work was to evaluate the efficiency of algorithms Try (TRY), Seriation (SER), Rapid Chain Delineation (RCD), Recombination Counting and Ordering (RECORD) and Unidirectional Growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent lod scores) and LMHC (likelihood via hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. For doing so, a linkage map of a hypothetical diploid and monoecious plant species was simulated, containing 21 markers with fixed distance of 3 centimorgans between them. Using Monte Carlo methods, 550 F2 populations were randomly simulated with 100 and 400 individuals, together with different combinations of dominant and codominant markers. 10 % and 20 % of missing data was also included. Results showed that the algorithms TRY and SER gave good results in all situations, even with presence of a large number of missing data and dominant markers linked in repulsion phase. Thus, these can be recommended for analyzing real data. The algorithms RECORD and UG gave good results in the absence of dominant markers linked in repulsion phase and can be used in this case. Among all algorithms, RCD was the least efficient. The criterion LHMC, applied with the RIPPLE algorithm, showed the best results when the goal is to check ordering errors.

Accurate genotyping is essential for building genetic maps and performing genome assembly of polyploid species. Recent high-throughput techniques, such as Illumina GoldenGate™ and Sequenom iPLEX MassARRAY®, have made it possible to accurately estimate the relative abundances of different alleles even when the ploidy of the population is unknown. Here we describe the experimental methods for collecting these relative allele intensities and then demonstrate the practical concerns for inferring genotypes using Bayesian inference via the software package SuperMASSA.

Accurate genotyping is essential for building genetic maps and performing genome assembly of polyploid species. Recent high-throughput techniques, such as Illumina GoldenGate™ and Sequenom iPLEX MassARRAY®, have made it possible to accurately estimate the relative abundances of different alleles even when the ploidy of the population is unknown. Here we describe the experimental methods for collecting these relative allele intensities and then demonstrate the practical concerns for inferring genotypes using Bayesian inference via the software package SuperMASSA.

Many plant species of great economic value (e.g., potato, wheat, cotton, and sugarcane) are polyploids. Despite the essential roles of autopolyploid plants in human activities, our genetic understanding of these species is still poor. Recent progress in instrumentation and biochemical manipulation has led to the accumulation of an incredible amount of genomic data. In this study, we demonstrate for the first time a successful genetic analysis in a highly polyploid genome (sugarcane) by the quantitative analysis of single-nucleotide polymorphism (SNP) allelic dosage and the application of a new data analysis framework. This study provides a better understanding of autopolyploid genomic structure and is a sound basis for genetic studies. The proposed methods can be employed to analyse the genome of any autopolyploid and will permit the future development of high-quality genetic maps to assist in the assembly of reference genome sequences for polyploid species.

Espécies autopoliploides são extremamente importantes na agricultura. No entanto, a estrutura complexa de seus genomas não é bem compreendida. Apesar de todos os avanços no mapeamento genético de autotetraploides, a grande maioria dos modelos utilizados para a construção de mapas em espécies autopoliploides com elevado nível de ploidia, tais como a canade- açúcar, são aproximações daqueles usados para organismos diplóides. Assim, este trabalho teve como objetivo o desenvolvimento de um novo modelo para construção de mapas genéticos em espécies autopoliploides com qualquer nível de ploidia e incluindo marcadores com todas as dosagens possíveis. Para tanto foi utilizada a tecnologia dos modelos de Markov ocultos. O modelo aqui apresentado pode ser aplicado a dados de marcadores dominantes e codominantes, com comportamento bialélico ou multialélico. O método baseia-se no cálculo das probabilidades condicionais que compõem a matriz de transição seguido da redução de sua dimensão usando uma abordagem computacional. O uso do método foi ilustrado em uma população de mapeamento de cana-de-açúcar proveniente do cruzamento entre duas variedades pré-comerciais (IACSP 95-3018 × IACSP 93-3046) e genotipadas com três tipos de marcadores: SNPs, microssatélites e AFLPs. Os resultados indicam que o novo método é muito eficiente na obtenção de mapas genéticos, mesmo em situações com níveis de ploidia altos e marcadores com altas doses, particularmente quando estes marcadores têm comportamento codominante. Também foi possível estimar a verossimilhança, as frações de recombinação e as fases de ligação usando a abordagem multiponto, a qual leva em consideração todos os marcadores do grupo de ligação analisado simultaneamente. O novo modelo aqui proposto representa um importante passo para realizar futuramente a localização de regiões genômicas associadas à variação das características quantitativas, no entendimento da arquitetura genética de tais características e na montagem de genomas de espécies autopoliploides. Autopolyploid species are extremely important in agriculture. However, the complex structure of their genomes is not well understood. Despite all advances in genetic mapping of autotetraploids, the vast majority of the models used for autopolyploid species with high ploidy level, such as sugarcane, are approximations of those used in diploid organisms. Thus, the aim of this work was to develop a new model to build genetic linkage maps in autopolyploid species with any ploidy level, including markers with all possible dosages. For doing so, hiddenMarkov model technology was used. The new model presented herein can be applied to dominant and codominantmarkers data, with biallelic or multiallelic behavior. The method is based on the calculation of conditional probabilities that comprise the transition matrix followed by a reduction of its dimension using a computer-based approach. An application of the method was illustrated with a sugarcane mapping population derived from a cross between two pre-commercial varieties (IACSP 95-3018 × IACSP 93-3046), scored with three types of markers: SNPs, microssatellite and AFLPs. The results indicate that the new method is very efficient in obtaining genetic maps, even for high ploidy levels and for markers with high dosages, particularly when these markers have codominant behavior. It was also possible to estimate the likelihood, the recombination fractions and the linkage phases between allmarkers using themultipoint approach, which takes into account all markers of the linkage group simultaneously. The new model proposed in this work represents a major step towards the location of genomic regions associated with variation in quantitative traits and its genetic architecture, and assembling autopoliploid genome sequences.

Managed environments in the form of well watered and water stressed trials were performed to study the genetic basis of grain yield and stay green in sorghum with the objective of validating previously detected QTL. As variations in phenology and plant height may influence QTL detection for the target traits, QTL for flowering time and plant height were introduced as cofactors in QTL analyses for yield and stay green. All but one of the flowering time QTL were detected near yield and stay green QTL. Similar co-localization was observed for two plant height QTL. QTL analysis for yield, using flowering time/plant height cofactors, led to yield QTL on chromosomes 2, 3, 6, 8 and 10. For stay green, QTL on chromosomes 3, 4, 8 and 10 were not related to differences in flowering time/plant height. The physical positions for markers in QTL regions projected on the sorghum genome suggest that the previously detected plant height QTL, Sb-HT9-1, and Dw2, in addition to the maturity gene, Ma5, had a major confounding impact on the expression of yield and stay green QTL. Co-localization between an apparently novel stay green QTL and a yield QTL on chromosome 3 suggests there is potential for indirect selection based on stay green to improve drought tolerance in sorghum. Our QTL study was carried out with a moderately sized population and spanned a limited geographic range, but still the results strongly emphasize the necessity of corrections for phenology in QTL mapping for drought tolerance traits in sorghum. Made available in DSpace on 2020-08-24T04:11:26Z (GMT). No. of bitstreams: 1 Studying-genetic.pdf: 478153 bytes, checksum: ed67faaaf2dbb17ce8ce6d332df279a2 (MD5) Previous issue date: 2012

Expressed sequence tags (ESTs) offer the opportunity to exploit single, low-copy, conserved sequence motifs for the development of simple sequence repeats (SSRs). The authors have examined the Sugarcane Expressed Sequence Tag database for the presence of SSRs. To test the utility of EST-derived SSR markers, a total of 342 EST–SSRs, which represent a subset of over 2005 SSR-containing sequences that were located in the sugarcane EST database, could be designed from the nonredundant SSR-positive ESTs for possible use as potential genic markers. These EST–SSR markers were used to screen 18 sugarcane ( Saccharum spp.) varieties. A high proportion (65.5%) of the above EST–SSRs, which gave amplified fragments of foreseen size, detected polymorphism. The number of alleles ranged from 2 to 24 with an average of 7.55 alleles per locus, while polymorphism information content values ranged from 0.16 to 0.94, with an average of 0.73. The ability of each set of EST–SSR markers to discriminate between varieties was generally higher than the polymorphism information content analysis. When tested for functionality, 82.1% of these 224 EST–SSRs were found to be functional, showing homology to known genes. As the EST–SSRs are within the expressed portion of the genome, they are likely to be associated to a particular gene of interest, improving their utility for genetic mapping; identification of quantitative trait loci, and comparative genomics studies of sugarcane. The development of new EST–SSR markers will have important implications for the genetic analysis and exploitation of the genetic resources of sugarcane and related species and will provide a more direct estimate of functional diversity.

O objetivo deste trabalho foi avaliar a eficiência, na construção de mapas genéticos, dos algoritmos seriação e delineação rápida em cadeia, além dos critérios para avaliação de ordens: produto mínimo das frações de recombinação adjacentes, soma mínima das frações de recombinação adjacentes e soma máxima dos LOD Scores adjacentes, quando usados com o algoritmo de verificação de erros " ripple" . Foi simulado um mapa com 24 marcadores, posicionados aleatoriamente a distâncias variadas, com média 10 cM. Por meio do método Monte Carlo, foram obtidas 1.000 populações de retrocruzamento e 1.000 populações F2, com 200 indivíduos cada, e diferentes combinações de marcadores dominantes e co-dominantes (100% co-dominantes, 100% dominantes e mistura com 50% co-dominantes e 50% dominantes). Foi, também, simulada a perda de 25, 50 e 75% dos dados. Observou-se que os dois algoritmos avaliados tiveram desempenho semelhante e foram sensíveis à presença de dados perdidos e à presença de marcadores dominantes; esta última dificultou a obtenção de estimativas com boa acurácia, tanto da ordem quanto da distância. Além disso, observou-se que o algoritmo " ripple" geralmente aumenta o número de ordens corretas e pode ser combinado com os critérios soma mínima das frações de recombinação adjacentes e produto mínimo das frações de recombinação adjacentes. The objective of this work was to evaluate the efficiency for the construction of genetic linkage maps of the algorithms seriation and rapid chain delineation, as well as the criteria: product of adjacent recombination fractions, sum of adjacent recombination fractions, and sum of adjacent LOD Scores, used with the ripple algorithm. A genetic linkage map was simulated containing 24 markers with random distances between them, with an average of 10 cM. Using the Monte Carlo method, 1,000 backcross populations and 1,000 F2 populations were simulated. The populations comprised 200 individuals each, as well as different combinations of dominant and codominant markers (100% codominant, 100% dominant and mixture containing 50% codominant and 50% dominant). It were also simulated 25, 50 e 75% of missing data. It was observed that both algorithms presented similar performance, and were sensitive to the presence of dominant markers, which makes it difficult to get estimates with good accuracy for both order and distance. Moreover, the algorithm ripple, when applied with the criteria sum of adjacent recombination fractions and product of adjacent recombination fractions, increased the number of correct orders.

Quantitative trait loci (QTL) mapping is an important approach for the study of the genetic architecture of quantitative traits. For perennial species, inbred lines cannot be obtained due to inbreed depression and a long juvenile period. Instead, linkage mapping can be performed by using a full-sib progeny. This creates a complex scenario because both markers and QTL alleles can have different segregation patterns as well as different linkage phases between them. We present a two-step method for QTL mapping using full-sib progeny based on composite interval mapping (i.e., interval mapping with cofactors), considering an integrated genetic map with markers with different segregation patterns and conditional probabilities obtained by a multipoint approach. The model is based on three orthogonal contrasts to estimate the additive effect (one in each parent) and dominance effect. These estimatives are obtained using the EM algorithm. In the first step, the genome is scanned to detect QTL. After, segregation pattern and linkage phases between QTL and markers are estimated. A simulated example is presented to validate the methodology. In general, the new model is more effective than existing approaches, because it can reveal QTL present in a full-sib progeny that segregates in any pattern present and can also identify dominance effects. Also, the inclusion of cofactors provided more statistical power for QTL mapping.

BackgroundGenotyping-by-Sequencing (GBS) provides affordable methods for genotyping hundreds of individuals using millions of markers. However, this challenges bioinformatic procedures that must overcome possible artifacts such as the bias generated by PCR duplicates and sequencing errors. Genotyping errors lead to data that deviate from what is expected from regular meiosis. This, in turn, leads to difficulties in grouping and ordering markers resulting in inflated and incorrect linkage maps. Therefore, genotyping errors can be easily detected by linkage map quality evaluations.ResultsWe developed and used the Reads2Map workflow to build linkage maps with simulated and empirical GBS data of diploid outcrossing populations. The workflows runGATKandfreebayesfor SNP calling andupdog, polyRAD, andSuperMASSAfor genotype calling, andOneMapandGUSMapto build linkage maps. Using simulated data, we observed which genotype call software fails in identifying common errors in GBS sequencing data and proposed specific filters to better handle them. We tested whether it is possible to overcome errors in a linkage map using genotype probabilities from each software or global error rates to estimate genetic distances with an updated version ofOneMap. We also evaluated the impact of segregation distortion, contaminant samples, and haplotype-based multiallelic markers in the final linkage maps. The results showed a low impact of segregation distortion in the linkage map quality, improvements in ordering markers with haplotype-based multiallelic markers, and improved maps with expected size using reliable genotype probabilities or a global error rate of 5%.ConclusionsThe pipelines results in each scenario changed according to the data set used, indicating that optimal pipelines and parameters are dataset-dependent and cannot be generalized to all GBS data sets. The Reads2Map workflow can reproduce the analysis in other GBS empirical data sets where users can select the pipeline and parameters adapted to their data context. The Reads2MapApp shiny app provides a graphical representation of the results to facilitate their interpretation.

Background The database of sugarcane expressed sequence tags (EST) offers a great opportunity for developing molecular markers that are directly associated with important agronomic traits. The development of new EST-SSR markers represents an important tool for genetic analysis. In sugarcane breeding programs, functional markers can be used to accelerate the process and select important agronomic traits, especially in the mapping of quantitative traits loci (QTL) and plant resistant pathogens or qualitative resistance loci (QRL). The aim of this work was to develop new simple sequence repeat (SSR) markers in sugarcane using the sugarcane expressed sequence tag (SUCEST database). Findings A total of 365 EST-SSR molecular markers with trinucleotide motifs were developed and evaluated in a collection of 18 genotypes of sugarcane (15 varieties and 3 species). In total, 287 of the EST-SSRs markers amplified fragments of the expected size and were polymorphic in the analyzed sugarcane varieties. The number of alleles ranged from 2-18, with an average of 6 alleles per locus, while polymorphism information content values ranged from 0.21-0.92, with an average of 0.69. The discrimination power was high for the majority of the EST-SSRs, with an average value of 0.80. Among the markers characterized in this study some have particular interest, those that are related to bacterial defense responses, generation of precursor metabolites and energy and those involved in carbohydrate metabolic process. Conclusions These EST-SSR markers presented in this work can be efficiently used for genetic mapping studies of segregating sugarcane populations. The high Polymorphism Information Content (PIC) and Discriminant Power (DP) presented facilitate the QTL identification and marker-assisted selection due the association with functional regions of the genome became an important tool for the sugarcane breeding program.

The African species Urochloa humidicola (Rendle) Morrone & Zuloaga (syn. Brachiaria humidicola (Rendle) Schweick.) is an important perennial forage grass found throughout the tropics. This species is polyploid, ranging from tetra to nonaploid, and apomictic, which makes genetic studies challenging; therefore, the number of currently available genetic resources is limited. The genomic architecture and evolution of U. humidicola and the molecular markers linked to apomixis were investigated in a full-sib F1 population obtained by crossing the sexual accession H031 and the apomictic cultivar U. humidicola cv. BRS Tupi, both of which are hexaploid. A simple sequence repeat (SSR)-based linkage map was constructed for the species from 102 polymorphic and specific SSR markers based on simplex and double-simplex markers. The map consisted of 49 linkage groups (LGs) and had a total length of 1702.82 cM, with 89 microsatellite loci and an average map density of 10.6 cM. Eight homology groups (HGs) were formed, comprising 22 LGs, and the other LGs remained ungrouped. The locus that controls apospory (apo-locus) was mapped in LG02 and was located 19.4 cM from the locus Bh027.c.D2. In the cytological analyses of some hybrids, bi- to hexavalents at diakinesis were observed, as well as two nucleoli in some meiocytes, smaller chromosomes with preferential allocation within the first metaphase plate and asynchronous chromosome migration to the poles during anaphase. The linkage map and the meiocyte analyses confirm previous reports of hybridization and suggest an allopolyploid origin of the hexaploid U. humidicola. This is the first linkage map of an Urochloa species, and it will be useful for future quantitative trait locus (QTL) analysis after saturation of the map and for genome assembly and evolutionary studies in Urochloa spp. Moreover, the results of the apomixis mapping are consistent with previous reports and confirm the need for additional studies to search for a co-segregating marker.