Genotyping marker density reduction is not an effective approach in long-term prediction-based breeding of cross-pollinated crops

Reductions of genotyping marker density have been extensively evaluated as potential strategies to reduce the genotyping costs of genomic selection (GS). Low-density marker panels are appealing in GS because they entail lower multicollinearity and computational time-consumption and allow more individuals to be genotyped for the same cost. However, statistical models used in GS are usually evaluated with empirical data, using "static" training sets and populations. This may be adequate for making predictions during a breeding program's initial cycles, but not for the long term. Moreover, to the best of our knowledge, no GS models consider the effect of dominance, which is particularly important for breeding outcomes in cross-pollinated crops. Hence, dominance effects are an important and unexplored issue in GS for long-term programs involving allogamous species. To address it, we employed two approaches: analysis of empirical maize datasets and simulations of long-term breeding applying phenotypic and genomic recurrent selection (intrapopulation and reciprocal schemes). In both schemes, we simulated twenty breeding cycles and assessed the effect of marker density reduction on the population mean, the best crosses, additive variance, selective accuracy, and response to selection with models (additive, additive-dominant, general (GCA), and specific combining ability (SCA)). Our results indicate that marker reduction based on linkage disequilibrium levels provides useful predictions only within a cycle, as accuracy significantly decreases over cycles. In the long-term, high-marker density provides the best responses to selection. The model to be used depends on the breeding scheme: additive for intrapopulation and additive-dominant or SCA for reciprocal.

Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing

Background Genome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density while being cost-efficient. The number of genomic fragments created through restriction enzyme digestion and the sequencing library setup must match to achieve sufficient sequencing coverage per locus. Here, we present a workflow based on published information and computational and experimental procedures to investigate and streamline the applicability of RRS. Results In an iterative process genome size estimates, restriction enzymes and size selection windows were tested and scaled in six classes of Antarctic animals (Ostracoda, Malacostraca, Bivalvia, Asteroidea, Actinopterygii, Aves). Achieving high marker density would be expensive in amphipods, the malacostracan target taxon, due to the large genome size. We propose alternative approaches such as mitogenome or target capture sequencing for this group. Pilot libraries were sequenced for all other target taxa. Ostracods, bivalves, sea stars, and fish showed overall good coverage and marker numbers for downstream population genomic analyses. In contrast, the bird test library produced low coverage and few polymorphic loci, likely due to degraded DNA. Conclusions Prior testing and optimization are important to identify which groups are amenable for RRS and where alternative methods may currently offer better cost-benefit ratios. The steps outlined here are easy to follow for other non-model taxa with little genomic resources, thus stimulating efficient resource use for the many pressing research questions in molecular ecology.

Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing

Genome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density while being cost-efficient. The number of genomic fragments created through restriction enzyme digestion and the sequencing library setup must match to achieve sufficient sequencing coverage per locus. Here, we present a workflow based on published information and computational and experimental procedures to investigate and streamline the applicability of RRS. In an iterative process genome size estimates, restriction enzymes and size selection windows were tested and scaled in six classes of Antarctic animals (Ostracoda, Malacostraca, Bivalvia, Asteroidea, Actinopterygii, Aves). Achieving high marker density would be expensive in amphipods, the malacostracan target taxon, due to the large genome size. We propose alternative approaches such as mitogenome or target capture sequencing for this group. Pilot libraries were sequenced for all other target taxa. Ostracods, bivalves, sea stars, and fish showed overall good coverage and marker numbers for downstream population genomic analyses. In contrast, the bird test library produced low coverage and few polymorphic loci, likely due to degraded DNA. Prior testing and optimization are important to identify which groups are amenable for RRS and where alternative methods may currently offer better cost-benefit ratios. The steps outlined here are easy to follow for other non-model taxa with little genomic resources, thus stimulating efficient resource use for the many pressing research questions in molecular ecology.

High-throughput sequencing techniques to flax genetics and breeding

Flax (Lnum usitatssimum L.) is an important oil and fiber crop. Using modern methods for flax breeding allows accelerating the introduction of some desired genes into the genotypes of future varieties. Today, an important condition for their creation is the development of research, that is based on next-generation sequencing (NGS). This review summarizes the results obtained using NGS sequencing in flax research. To date, a linkage map with a high marker density has been obtained for L. usitatssimum, which is already being used for a more efficient search for quantitative traits loci. Comparative studies of transcriptomes and miRNomes of flax under stress and in control conditions elucidated molecular-genetic mechanisms of abiotic and biotic stress responses. The very accurate model for genomic selection of flax resistant to pasmo was constructed. Based on NGS-sequencing also some details of the genus Linum evolution were clarified. The knowledge systematized in the review can be useful for researchers working in flax breeding and whereas fundamental interest for understanding the phylogenetic relationships within the genus Linum, the ontogenesis, and the mechanisms of the response of flax plants to various stress factors.

An EST-SSR based genetic linkage map and identification of QTLs for anthracnose disease resistance in water yam (Dioscorea alata L.)

Water yam (Dioscorea alata L.) is one of the most important food yams with wide geographical distribution in tropics. One of the major constraints to water yam production is anthracnose disease caused by a fungus, Colletotrichum gloesporioides (Penz.). There are no economically feasible solutions as chemical sprays or cultural practices, such as crop rotation are seldom convenient for smallholder farmers for sustainable control of the disease. Breeding for development of durable genetic resistant varieties is known to offer lasting solution to control endemic disease threats to crop production. However, breeding for resistance to anthracnose has been slow considering the biological constraints related to the heterozygous and vegetative propagation of the crop. The development of saturated linkage maps with high marker density, such as SSRs, followed by identification of QTLs can accelerate the speed and precision of resistance breeding in water yam. A total of 380 EST-SSRs were used to generate a saturated linkage map. About 60.19% of SSRs showed Mendelian segregation pattern, however, it had no effect on the construction of linkage map. All 380 EST-SSRs were mapped into 20 linkage groups covering a total length of 2559.66 cM, which agrees with the diploid nature (2n = 2x = 20) of the parents used in the cross. Majority of the markers were mapped on linkage group 1 comprising of 97 EST-SSRs. This is the first genetic linkage map of water yam constructed using EST-SSRs. QTL localization was based on phenotypic data collected over a 3-year period of inoculating the mapping population with the most virulent strain of C. gloeosporoides from West Africa. Using the mean permutation value of LOD scores as threshold value for declaring a putative QTL on all linkage groups, one QTL was consistently observed on linkage group (LG) 14 in all the three years and average score data. This QTL was found at position interval of 71.12 – 84.76 cM explaining 68.94% of the total phenotypic variation in the average score data. The high marker density allowed identification of QTLs and association for anthracnose disease, which could be validated in other mapping populations and used in marker-assisted breeding in D. alata improvement programmes.