Novel strategies for genomic prediction of untested single-cross maize hybrids using unbalanced historical data.

KEY MESSAGE: Weighted outperformed unweighted genomic prediction using an unbalanced dataset representative of a commercial breeding program. Moreover, the use of the two cycles preceding predictions as training set achieved optimal prediction ability. Predicting the performance of untested single-cross hybrids through genomic prediction (GP) is highly desirable to increase genetic gain. Here, we evaluate the predictive ability (PA) of novel genomic strategies to predict single-cross maize hybrids using an unbalanced historical dataset of a tropical breeding program. Field data comprised 949 single-cross hybrids evaluated from 2006 to 2013, representing eight breeding cycles. Hybrid genotypes were inferred based on their parents' genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GP analyses were fitted using genomic best linear unbiased prediction via a stage-wise approach, considering two distinct cross-validation schemes. Results highlight the importance of taking into account the uncertainty regarding the adjusted means at each step of a stage-wise analysis, due to the highly unbalanced data structure and the expected heterogeneity of variances across years and locations of a commercial breeding program. Further, an increase in the size of the training set was not always advantageous even in the same breeding program. The use of the two cycles preceding predictions achieved optimal PA of untested single-cross hybrids in a forward prediction scenario, which could be used to replace the first step of field screening. Finally, in addition to the practical and theoretical results applied to maize hybrid breeding programs, the stage-wise analysis performed in this study may be applied to any crop historical unbalanced data.

A molecular linkage map for Drosophila mediopunctata confirms synteny with Drosophila melanogaster and suggests a region that controls the variation in the number of abdominal spots.

The classic approach to gene discovery relies on the construction of linkage maps. We report the first molecular-based linkage map for Drosophila mediopunctata, a neotropical species of the tripunctata group. Eight hundred F(2) individuals were genotyped at 49 microsatellite loci, resulting in a map that is ≈450 centimorgans long. Five linkage groups were detected, and the species' chromosomes were identified through cross-references to BLASTn searches and Müller elements. Strong synteny was observed when compared with the Drosophila melanogaster chromosome arms, but little conservation in the gene order was seen. The incorporation of morphological data corresponding to the number of central abdominal spots on the map was consistent with the expected location of a genomic region responsible for the phenotype on the second chromosome.

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data.

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.

Studying the genetic basis of drought tolerance in sorghum by managed stress trials and adjustments for phenological and plant height differences.

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.

Precision of distances and ordering of microsatellite markers in consensus linkage maps of chromosomes 1, 3 and 4 from two reciprocal chicken populations using bootstrap sampling.

Some factors complicate comparisons between linkage maps from different studies. This problem can be resolved if measures of precision, such as confidence intervals and frequency distributions, are associated with markers. We examined the precision of distances and ordering of microsatellite markers in the consensus linkage maps of chromosomes 1, 3 and 4 from two F(2) reciprocal Brazilian chicken populations, using bootstrap sampling. Single and consensus maps were constructed. The consensus map was compared with the International Consensus Linkage Map and with the whole genome sequence. Some loci showed segregation distortion and missing data, but this did not affect the analyses negatively. Several inversions and position shifts were detected, based on 95% confidence intervals and frequency distributions of loci. Some discrepancies in distances between loci and in ordering were due to chance, whereas others could be attributed to other effects, including reciprocal crosses, sampling error of the founder animals from the two populations, F(2) population structure, number of and distance between microsatellite markers, number of informative meioses, loci segregation patterns, and sex. In the Brazilian consensus GGA1, locus LEI1038 was in a position closer to the true genome sequence than in the International Consensus Map, whereas for GGA3 and GGA4, no such differences were found. Extending these analyses to the remaining chromosomes should facilitate comparisons and the integration of several available genetic maps, allowing meta-analyses for map construction and quantitative trait loci (QTL) mapping. The precision of the estimates of QTL positions and their effects would be increased with such information.

Evaluation of algorithms used to order markers on genetic maps.

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.

OneMap: software for genetic mapping in outcrossing species.

OneMap is an environment for constructing linkage maps of outcrossing plant species, using full-sib families derived from two outbred parents. The analyses are performed using a novel methodology based on the maximum likelihood approach for simultaneous estimation of linkage and linkage phases (Wu et al. 2002), which has been successfully applied to sugarcane (Garcia et al. 2006). It is implemented as a set of functions for the freely distributed software R, and handles pairwise marker analysis, marker ordering and map refinement. The software is freely available at http://www.ciagri.usp.br/ approximately aafgarci/OneMap/.

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.

Analysis of genetic similarity detected by AFLP and coefficient of parentage among genotypes of sugar cane ( Saccharum spp.).

Despite the economical importance of sugar cane, until the present-date no studies have been carried out to determine the correlation of the molecular-based genetic similarity (GS) and the coefficient of parentage ( f)-estimates generated for cultivars. A comprehensive knowledge of the amount of genetic diversity in parental cultivars, could improve the effectiveness of breeding programmes. In this study, amplified fragment length polymorphism (AFLP) and pedigree data were used to investigate the genetic relationship in a group of 79 cultivars (interspecific hybrids), used as parents in one of the Brazilian breeding programmes, and four species of Saccharum ( Saccharum sinense, Saccharum barberi and two of Saccharum officinarum). The objectives of this study were to assess the level of genetic similarity among the sugar-cane cultivars and to investigate the correlation between the AFLP-based GS and f, based on pedigree information. Twenty one primer combinations were used to obtain the AFLP molecular markers, generating a total of 2,331 bands, of which 1,121 were polymorphic, with a polymorphism rate, on average, of 50% per primer combination. GSs were determined using Jaccard's similarity coefficient, and a final dendrogram was constructed using an unweighted pair-group method using arithmetic average (UPGMA). AFLP-based GS ranged from 0.28 to 0.89, with a mean of 0.47, whereas f ranged from 0 to 0.503, with a mean of 0.057. Cluster analysis using GS divided the genotypes into related subgroups suggesting that there is important genetic relationship among the cultivars. AFLP-based GS and f were significantly correlated ( r= 0.42, P< 0.001), thus the significance of this r value suggests that the AFLP data may help to more-accurately quantify the degree of relationship among sugar-cane cultivars.

Composite interval mapping and mixed models reveal QTL associated with performance and carcass traits on chicken chromosomes 1, 3, and 4.

Interval mapping (IM) implemented in QTL Express or GridQTL is widely used, but presents some limitations, such as restriction to a fixed model, risk of mapping two QTL when there may be only one and no discrimination of two or more QTL using both cofactors located on the same and other chromosomes. These limitations were overcome with composite interval mapping (CIM). We reported QTL associated with performance and carcass traits on chicken chromosomes 1, 3, and 4 through implementation of CIM and analysis of phenotypic data using mixed models. Thirty-four microsatellite markers were used to genotype 360 F2 chickens from crosses between males from a layer line and females from a broiler line. Sixteen QTL were mapped using CIM and 14 QTL with IM. Furthermore, of those 30 QTL, six were mapped only when CIM was used: for body weight at 35 days (first and third peaks on GGA4), body weight at 41 days (GGA1B and second peak on GGA4), and weights of back and legs (both on GGA4). Three new regions had evidence for QTL presence: one on GGA1B associated with feed intake 35-41 d at 404 cM (LEI0107-ADL0183) and two on GGA4 associated with weight of back at 163 cM (LEI0076-MCW0240) and weight gain 35-41 d, feed efficiency 35-41 d and weight of legs at 241 cM (LEI0085-MCW0174). We dissected one more linked QTL on GGA4, where three QTL for BW35 and two QTL for BW41 were mapped. Therefore, these new regions mapped here need further investigations using high-density SNP to confirm these QTL and identify candidate genes associated with those traits.

Characterization of new polymorphic functional markers for sugarcane.

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.

Development of an integrated genetic map of a sugarcane (Saccharum spp.) commercial cross, based on a maximum-likelihood approach for estimation of linkage and linkage phases.

Sugarcane (Saccharum spp.) is a clonally propagated outcrossing polyploid crop of great importance in tropical agriculture. Up to now, all sugarcane genetic maps had been developed using either full-sib progenies derived from interspecific crosses or from selfing, both approaches not directly adopted in conventional breeding. We have developed a single integrated genetic map using a population derived from a cross between two pre-commercial cultivars ('SP80-180' x 'SP80-4966') using a novel approach based on the simultaneous maximum-likelihood estimation of linkage and linkage phases method specially designed for outcrossing species. From a total of 1,118 single-dose markers (RFLP, SSR and AFLP) identified, 39% derived from a testcross configuration between the parents segregating in a 1:1 fashion, while 61% segregated 3:1, representing heterozygous markers in both parents with the same genotypes. The markers segregating 3:1 were used to establish linkage between the testcross markers. The final map comprised of 357 linked markers, including 57 RFLPs, 64 SSRs and 236 AFLPs that were assigned to 131 co-segregation groups, considering a LOD score of 5, and a recombination fraction of 37.5 cM with map distances estimated by Kosambi function. The co-segregation groups represented a total map length of 2,602.4 cM, with a marker density of 7.3 cM. When the same data were analyzed using JoinMap software, only 217 linked markers were assigned to 98 co-segregation groups, spanning 1,340 cM, with a marker density of 6.2 cM. The maximum-likelihood approach reduced the number of unlinked markers to 761 (68.0%), compared to 901 (80.5%) using JoinMap. All the co-segregation groups obtained using JoinMap were present in the map constructed based on the maximum-likelihood method. Differences on the marker order within the co-segregation groups were observed between the two maps. Based on RFLP and SSR markers, 42 of the 131 co-segregation groups were assembled into 12 putative homology groups. Overall, the simultaneous maximum-likelihood estimation of linkage and linkage phases was more efficient than the method used by JoinMap to generate an integrated genetic map of sugarcane.

Tropical maize germplasm: what can we say about its genetic diversity in the light of molecular markers?

Knowledge about genetic variability of a crop allows for more efficient and effective use of resources in plant improvement programs. The genetic variation within temperate maize has been studied extensively, but the levels and patterns of diversity in tropical maize are still not well understood. Brazilian maize germplasm represents a very important pool of genetic diversity due to many past introductions of exotic material. To improve our knowledge of the genetic diversity in tropical maize inbred lines, we fingerprinted 85 lines with 569 AFLP bands and 50 microsatellite loci. These markers revealed substantial variability among lines, with high rates of polymorphism. Cluster analysis was used to identify groups of related lines. Well-defined groups were not observed, indicating that the tropical maize studied is not as well organized as temperate maize. Three types of genetic distance measurements were applied (Jaccard's coefficient, Modified Rogers' distance and molecular coefficient of coancestry), and the values obtained with all of them indicated that the genetic similarities were small among the lines. The different coefficients did not substantially affect the results of cluster analysis, but marker types had a large effect on genetic similarity estimates. Regardless of genetic similarity coefficient used, estimates based on AFLPs were poorly correlated with those based on SSRs. Analyses using AFLP and SSR data together do not seem to be the most efficient manner of assessing variability in highly diverse materials because the result was similar to using AFLPs alone. It was seen that molecular markers can help to organize the genetic variability and expose useful diversity for breeding purposes.