Single-Step Genomic Analysis Increases the Accuracy of Within-Family Selection in a Clonally Replicated Population of Pinus taeda L.

The use of genomic markers in forest tree breeding is expected to improve the response to selection, especially within family. To evaluate the potential improvements from genotyping, we analyzed a large Pinus taeda L. clonal population (1,831 cloned individuals) tested in multiple environments. Of the total, 723 clones from five full-sib families were genotyped using 10,337 single-nucleotide polymorphism markers. Single-step models with genomic and pedigree-based relationships produced similar heritability estimates. Breeding value predictions were greatly improved with inclusion of genomic relationships, even when clonal replication was abundant. The improvement was limited to genotyped individuals and attributable to accounting for the Mendelian sampling effect. Reducing clonal replication by omitting data indicated that genotyping improved breeding values similar to clonal replication. Genomic selection predictive ability (masking phenotypes) was greater for stem straightness (0.68) than for growth traits (0.41 to 0.44). Predictive ability for a new full-sibling family was poorer than when full-sibling relationships were present between model training and validation sets. Species that are difficult to propagate clonally can use genotyping to improve within-family selection. Clonal testing combined with genotyping can produce breeding value accuracies adequate to graft selections directly into deployment orchards without progeny testing. Study Implications Genomic markers can improve the reliability of breeding values, resulting in a more confident ranking of individuals within families. For genotyped individuals, the improvements were comparable to clonal testing. Breeding programs for species that are difficult to propagate clonally should consider genotyping to replace or supplement clonal testing as a means to improve within-family selection. For genomic prediction of breeding values without phenotypes (genomic selection), a robust genetic relationship between model training and validation sets is required. The single-step model allows genotyping a subset of the population and is a straightforward extension of well-established methods.

Effect of plot size and plant spatial arrangement on the efficiency of family selection in sugarcane

The purpose of this study was to identify the ideal sample size representing a family in its potential, to identify superior families and, in parallel, determine in which spatial arrangement they may have a better accuracy in the selection of new varieties of sugarcane. For such purpose, five families of full-sibs were evaluated, each with 360 individuals, in the randomized blocks design, with three replications in three different spacing among plants in the row (50 cm, 75 cm, and 100 cm) and 150 cm between the rows. To determine the ideal sample size, as well as the better spacing for evaluation, the bootstrap method was adopted. It was observed that 100 cm spacings provided the best average for the stalk numbers, stalk diameter and for estimated weight of stalks in the stool. The spacing of 75 cm between the plants allowed a better power of discrimination among the families for all characters evaluated. At this 75 cm spacing was also possible to identify superior families with a sample of 30 plants each plot and 3 reps in the trial. Highlights The bootstrap method was efficient to determine the ideal sample size, as well as the best spacing for evaluation. The 75-cm spacing had the highest power of discrimination among families, indicating that this spacing is the most efficient in evaluating sugarcane families for selection purposes. From all the results and considering selective accuracy as the guiding parameter for decision making, the highest values obtained considering the number of stalks and weight of stalks in the stools were found at the 75-cm spacing.

A simulation study of a honeybee breeding scheme accounting for polyandry, direct and maternal effects on colony performance

Background Efficient breeding programs are difficult to implement in honeybees due to their biological specificities (polyandry and haplo-diploidy) and complexity of the traits of interest, with performances being measured at the colony scale and resulting from the joint effects of tens of thousands of workers (called direct effects) and of the queen (called maternal effects). We implemented a Monte Carlo simulation program of a breeding plan designed specifically for Apis mellifera’s populations to assess the impact of polyandry versus monoandry on colony performance, inbreeding level and genetic gain depending on the individual selection strategy considered, i.e. complete mass selection or within-family (maternal lines) selection. We simulated several scenarios with different parameter setups by varying initial genetic variances and correlations between direct and maternal effects, the selection strategy and the polyandry level. Selection was performed on colony phenotypes. Results All scenarios showed strong increases in direct breeding values of queens after 20 years of selection. Monoandry led to significantly higher direct than maternal genetic gains, especially when a negative correlation between direct and maternal effects was simulated. However, the relative increase in these genetic gains depended also on their initial genetic variability and on the selection strategy. When polyandry was simulated, the results were very similar with either 8 or 16 drones mated to each queen. Across scenarios, polyandrous mating resulted in equivalent or higher gains in performance than monoandrous mating, but with considerably lower inbreeding rates. Mass selection conferred a ~ 20% increase in performance compared to within-family selection, but was also accompanied by a strong increase in inbreeding levels (25 to 50% higher). Conclusions Our study is the first to compare the long-term effects of polyandrous versus monoandrous mating in honeybee breeding. The latter is an emergent strategy to improve specific traits, such as resistance to varroa, which can be difficult or expensive to phenotype. However, if used during several generations in a closed population, monoandrous mating increases the inbreeding level of queens much more than polyandrous mating, which is a strong limitation of this strategy.

Breeding of medicinal and essential oil crops in VILAR: achievements and prospects

This review discusses the main methods of breeding material development, the current state, problems and prospects for medicinal and essential oil plants breeding. The relevance of this area has especially increased due to the sanctions, the resulting shortage of medicinal plants and their low quality, which does not meet the requirements of the pharmaceutical industry. To produce a stable plant raw material base, it is necessary to actively develop a breeding process to create new highly productive varieties of medicinal plants resistant to biotic and abiotic environments. In breeding with the use of modern molecular biological methods, related species and generic complexes of the All-Russian Research Institute of Medicinal and Aromatic Plants (VILAR) collection can be involved, where there is extensive original genetic material of medicinal, essential oil, rare and endangered species. In the breeding of medicinal and essential oil crops, traditional methods of individual and individual-family selection, polyploidy, chemical mutagenesis and a combination of methods to obtain original breeding material are still promising. VILAR has created more than 90 varieties of medicinal and essential oil crops, most of which have been approved for use throughout the Russian Federation.

The new spring rapeseed variety Sibiryak 60

In 2020, we submitted the spring rapeseed variety Sibiryak 60 bred at the Siberian Experimental Station (branch of V.S. Pustovoit All-Russian Research Institute of Oil Crops) to the State Commission of the Russian Federation on testing and protection of the selection achievements. We developed the variety by the method of multiple individual-family selection from the variety Avangard (All-Russian Research Institute of Rapeseed, Lipetsk). In 2012, there was identified an elite plant and further breeding work was carried out to improve the main economic traits: early maturity, productivity, oil content, resistance to lodging, seed falling and to the main pathogens. The general characteristics of the variety are high seed productivity and low content of glucosinolates in seeds. According to the results of the competitive variety trial (2018–2020), the spring rapeseed variety Sibiryak 60 exceeded the standard variety Granit in seed yield by 0.29 t/ha and in oil yield by 0.12 t/ha. In the conditions of the Krasnodar region, the variety Sibiryak 60 exceeded the standard variety Granit in seed yield by 0.31 t/ha, in the conditions of the Lipetsk region – by 0.30 t/ha. The new variety is meant to for cultivation for seeds in the Volgo-Vyatka (4), Middle Volga (7), Ural (9), West Siberian (10), and East Siberian (11) regions. The originator of the variety Sibiryak 60 is V.S. Pustovoit All-Russian Research Institute of Oil Crops.

Enrichment of the triticale gene pool by intraspecific hybridization

The aim of the research was to expand the genetic diversity of winter triticale samples by intraspecific hybridization and to obtain new valuable forms for their involvement in the selection process of creating high-yielding cultivars. The research was conducted during 2013–2020 at the sites of the Department of Genetics, Plant Breeding and Biotechnology of Uman National University of Horticulture, Ministry of Education and Science of Ukraine. As initial material for hybridization was used samples of hexaploid triticale of own breeding and varieties Rozivska 6, Ladne, Khlibodar Kharkivsky, Beta, Alkid, Souvenir, Raritet; octaploid triticale samples UA0602463 and UA0601654. Hybrid offspring were analyzed for morphological and economically valuable traits, including plant height, lodging resistance, ear length, grain weight from the main ear and 1000 grains, protein and gluten content in the grain and its quality indicators, yield, etc. In the studies used a systematic method of site placement. The rooms were arranged in blocks with a plant density of 400 thousand units/ha four times. In the course of researches hybridization of hexaploid forms of triticale of different ecological and geographical origin among themselves, and also hybridization of octaploid forms with hexaploid was carried out. In F2 populations, individual-family selection of low-stem forms with high ear grain was performed. In the absence of low-stem forms in the area of F2 hybrids, ear productivity was selected, and the population was transferred to a hybridization nursery for crossing plants with donors of low-stem genes. As a result of the conducted researches 23 highly productive forms of winter triticale were obtained, in particular, two dwarf samples (h = 58 cm), four – short-stemmed (h = 60–80 cm), one – early-ripening (vegetation period 285 days), nine – with high ear productivity. Sample 63 was selected, which significantly exceeded the group standard in terms of yield (7.01 t/ha), protein content (12.2 %) and gluten of the first quality group (25.4 %).

Prediction of Ratoon Sugarcane Family Yield and Selection Using Remote Imagery

Remote sensing techniques and the use of Unmanned Aerial Systems (UAS) have simplified the estimation of yield and plant health in many crops. Family selection in sugarcane breeding programs relies on weighed plots at harvest, which is a labor-intensive process. In this study, we utilized UAS-based remote sensing imagery of plant-cane and first ratoon crops to estimate family yields for a second ratoon crop. Multiple families from the commercial breeding program were planted in a randomized complete block design by family. Standard red, green, and blue imagery was acquired with a commercially available UAS equipped with a Red–Green–Blue (RGB) camera. Color indices using the CIELab color space model were estimated from the imagery for each plot. The cane was mechanically harvested with a sugarcane combine harvester and plot weights were obtained (kg) with a field wagon equipped with load cells. Stepwise regression, correlations, and variance inflation factors were used to identify the best multiple linear regression model to estimate the second ratoon cane yield (kg). A multiple regression model, which included family, and five different color indices produced a significant R2 of 0.88. This indicates that it is possible to make family selection predictions of cane weight without collecting plot weights. The adoption of this technology has the potential to decrease labor requirements and increase breeding efficiency.