Mining the Wheat Grain Proteome

Bread wheat is the most widely cultivated crop worldwide, used in the production of food products and a feed source for animals. Selection tools that can be applied early in the breeding cycle are needed to accelerate genetic gain for increased wheat production while maintaining or improving grain quality if demand from human population growth is to be fulfilled. Proteomics screening assays of wheat flour can assist breeders to select the best performing breeding lines and discard the worst lines. In this study, we optimised a robust LC–MS shotgun quantitative proteomics method to screen thousands of wheat genotypes. Using 6 cultivars and 4 replicates, we tested 3 resuspension ratios (50, 25, and 17 µL/mg), 2 extraction buffers (with urea or guanidine-hydrochloride), 3 sets of proteases (chymotrypsin, Glu-C, and trypsin/Lys-C), and multiple LC settings. Protein identifications by LC–MS/MS were used to select the best parameters. A total 8738 wheat proteins were identified. The best method was validated on an independent set of 96 cultivars and peptides quantities were normalised using sample weights, an internal standard, and quality controls. Data mining tools found particularly useful to explore the flour proteome are presented (UniProt Retrieve/ID mapping tool, KEGG, AgriGO, REVIGO, and Pathway Tools).

Improvement of genomic prediction in advanced wheat breeding lines by including additive-by-additive epistasis

Key message Including additive and additive-by-additive epistasis in a NOIA parametrization did not yield orthogonal partitioning of genetic variances, nevertheless, it improved predictive ability in a leave-one-out cross-validation for wheat grain yield. Abstract Additive-by-additive epistasis is the principal non-additive genetic effect in inbred wheat lines and is potentially useful for developing cultivars based on total genetic merit; nevertheless, its practical benefits have been highly debated. In this article, we aimed to (i) evaluate the performance of models including additive and additive-by-additive epistatic effects for variance components (VC) estimation of grain yield in a wheat-breeding population, and (ii) to investigate whether including additive-by-additive epistasis in genomic prediction enhance wheat grain yield predictive ability (PA). In total, 2060 sixth-generation (F6) lines from Nordic Seed A/S breeding company were phenotyped in 21 year-location combinations in Denmark, and genotyped using a 15 K-Illumina-BeadChip. Three models were used to estimate VC and heritability at plot level: (i) “I-model” (baseline), (ii) “I + GA-model”, extending I-model with an additive genomic effect, and (iii) “I + GA + GAA-model”, extending I + GA-model with an additive-by-additive genomic effects. The I + GA-model and I + GA + GAA-model were based on the Natural and Orthogonal Interactions Approach (NOIA) parametrization. The I + GA + GAA-model failed to achieve orthogonal partition of genetic variances, as revealed by a change in estimated additive variance of I + GA-model when epistasis was included in the I + GA + GAA-model. The PA was studied using leave-one-line-out and leave-one-breeding-cycle-out cross-validations. The I + GA + GAA-model increased PA significantly (16.5%) compared to the I + GA-model in leave-one-line-out cross-validation. However, the improvement due to including epistasis was not observed in leave-one-breeding-cycle-out cross-validation. We conclude that epistatic models can be useful to enhance predictions of total genetic merit. However, even though we used the NOIA parameterization, the variance partition into orthogonal genetic effects was not possible.

Embryo Rescue and Moleclar Marker-Assisted Selection of Hybrid Seedless Grape

Seedless grapes play an important role in fresh food and dry production. New varieties breeding by hybridization with seedless varieties as female parents is the most effective way to cultivate seedless varieties. However, the embryos of Seedless varieties can not develop normally, so it is difficult to obtain hybrid offspring as hybrid female parent. Moreover, grape is a perennial tree species with highly heterozygous genes, with long breeding cycle and low efficiency. In this study, embryo rescue technology was used to cultivate hybrid offspring by crossing with ‘Ruby Seedless’ as female parent and ‘Hongqitezao’ as male parent, so as to solve the problem that seedless varieties can not be female parent; and molecular technology was used to carry out assisted breeding research to solve the problems of long cycle and low efficiency. TP-M13-SSR technique was used to carry out authenticity breeding. SCAR marker SCF27-2000 was used to detect the seedless traits of hybrid plants, phenotypic traits was used to verify the results of molecular markers, and Seedless trait-related SSR markers VMC7F2, VrSD10 and P3_VvAGL11 was used to detect and verify the genotypes of individual plants with inconsistent detection results by the two methods. In this study, a total of 384 hybrid offspring were finally obtained, and the hybridization rate was 84.43%. A total of 163 fruit-bearing plants were identified, and the phenotypes of their seeds were identified. The coincidence rate of genotypic and phenotypic analyses was 93.88%. Additionally, 305 F1 plants were detected using the SCF27-2000 marker, and the abortion rate was 64.92%. We speculate that the inconsistent results were caused by parthenocarpy, SCF27 marker limitation, among other factors. Overall, this study shows that embryo rescue is an effective method for breeding seedless grape cultivars, and the application of molecular markers could facilitate the early identification of hybrid traits,and improve breeding efficiency.

Analysis of culling reasons during the breeding cycle and lifetime performance: The strategy to remove crossbred Landrace and Large White sows under tropical climate

Background and Aim: Sow culling is an important practice in commercial swine production because it is directly associated with the economic efficiency of the breeding herd. This study was conducted to analyze the reasons for sow culling and quantify the factors affecting culling in crossbred Landrace and Large White sows under tropical climate. Materials and Methods: A total of 4887 culled sows from one parent stock farm located in Ratchaburi province, Western Thailand, were examined in this study. Culling reasons were grouped into the following eight categories according to farm management: (1) Reproductive disorders, (2) old age, (3) low performance, (4) diseases, (5) lameness, (6) udder problems, (7) body condition, and (8) other illnesses. Logistic regression analysis was used to explore the relationship between culling sows and environmental factors. Effects of parity and season of culling were considered as fixed effects in a statistical model. Results: Descriptive statistics indicated the following factors accounting for sow removals: Old age (34.93%, n=1707), reproductive disorders (29.32%, n=1433), low performance (12.62%, n=617), lameness (12.56%, n=614), diseases (4.8%, n=235), body condition (4.68%, n=229), udder problems (0.79%, n=39), and other illnesses (0.26%, n=13). Parity and season of culling were also found to have a significant effect on sow culling (p<0.05). The majority of culling sows in this population were of old age and high parity. Conclusion: This study indicated that the purposeful culling of sows on this farm was within the targeted range. However, the incidence of reproductive disorders was too high and required further investigations.

Genomic Prediction of Drought Tolerance during Seedling Stage in Maize using Low-Cost Markers

Drought tolerance in maize is a complex and polygenic trait, especially in the seedling stage. In plant breeding, such traits can be improved by genomic selection (GS), which has become a practical and effective tool. In the present study, a natural maize population named Northeast China core population (NCCP) consisting of 379 inbred lines were genotyped with diversity arrays technology (DArT) and genotyping-by-sequencing (GBS) platforms. Target traits of seedling emergence rate (ER), seedling plant height (SPH), and grain yield (GY) were evaluated under two natural drought environments in northeast China. adequate genetic variants have been found for genomic selection, they are not stable enough between two years. Similarly, the heritability of the three traits is not stable enough, and the heritabilities in 2019 (0.88, 0.82, 0.85 for ER, SPH, GY) are higher than that in 2020 (0.65, 0.53, 0.33) and cross-two-year (0.32, 0.26, 0.33). The current research obtained two kinds of marker sets: the SilicoDArT markers were from DArT-seq, and SNPs were from the GBS and DArT-seq. In total, a number of 11,865 SilicoDArT, 7,837 DArT's SNPs, and 91,003 GBS SNPs were used for analysis after quality control. The results of phylogenetic trees showed that the population was rich in consanguinity. Genomic prediction results showed that the average prediction accuracies estimated using the DArT SNP dataset under the 2-fold cross-validation scheme were 0.27, 0.19, and 0.33, for ER, SPH, and GY, respectively. The result of SilicoDArT is close to the SNPs from DArT-seq, those were 0.26, 0.22, and 0.33. For SPH, the prediction accuracies using SilicoDArT were more than ones using DArT SNP, In some cases, alignment to the reference genome results in a loss to the prediction. The trait with lower heritability can improve the prediction accuracy using filtering of linkage disequilibrium. For the same trait, the prediction accuracy estimated with two types of DArT markers was consistently higher than those estimated with the GBS SNPs under the same genotyping cost. Our results show the prediction accuracy has been improved in some cases of controlling population structure and marker quality, even when the density of the marker is reduced. In the initial maize breeding cycle, Silicodart markers can obtain higher prediction accuracy with a lower cost. However, higher marker density platforms i.e. GBS may play a role in the following breeding cycle for the long term. The natural drought experimental station can reduce the difficulty of phenotypic identification in a water-scarce environment. The accumulation of more yearly data will help to stabilize the heritability and improve predictive accuracy in maize breeding. The experimental design and model for drought resistance also need to be further developed.

Genetic Modification and Application in Cassava, Sweetpotato and Yams

Cassava (Manihot esculenta Crantz), sweetpotato (Ipomoea batatas) and yams (Dioscorea spp.) are important root and tuber crops grown for food, feed and various industrial applications. However, their genetic gain potentials are limited by breeding and genetic bottlenecks for improvement of many desired traits. This book chapter covers the applications and potential benefits of genetic modification in breeding selected outcrossing root and tuber crops. It assesses how improvement of selected root and tuber crops through genetic modification overcomes both the high heterozygosity and serious trait separation that occurs in conventional breeding, and contributes to timely achievement of improved target traits. It also assesses the ways genetic modification improves genetic gain in the root and tuber breeding programs, conclusions and perspectives. Conscious use of complementary techniques such as genetic modification in the root and tuber breeding programs can increase the selection gain by reducing the long breeding cycle and cost, as well as reliable exploitation of the heritable variation in the desired direction.

Demographic profiles and environmental drivers of variation relate to individual breeding state in a long-lived trans-oceanic migratory seabird, the Manx shearwater

Understanding the points in a species breeding cycle when they are most vulnerable to environmental fluctuations is key to understanding interannual demography and guiding effective conservation and management. Seabirds represent one of the most threatened groups of birds in the world, and climate change and severe weather is a prominent and increasing threat to this group. We used a multi-state capture-recapture model to examine how the demographic rates of a long-lived trans-oceanic migrant seabird, the Manx shearwater Puffinus puffinus, are influenced by environmental conditions experienced at different stages of the annual breeding cycle and whether these relationships vary with an individual’s breeding state in the previous year (i.e., successful breeder, failed breeder and non-breeder). Our results imply that populations of Manx shearwaters are comprised of individuals with different demographic profiles, whereby more successful reproduction is associated with higher rates of survival and breeding propensity. However, we found that all birds experienced the same negative relationship between rates of survival and wind force during the breeding season, indicating a cost of reproduction (or central place constraint for non-breeders) during years with severe weather conditions. We also found that environmental effects differentially influence the breeding propensity of individuals in different breeding states. This suggests individual spatio-temporal variation in habitat use during the annual cycle, such that climate change could alter the frequency that individuals with different demographic profiles breed thereby driving a complex and less predictable population response. More broadly, our study highlights the importance of considering individual-level factors when examining population demography and predicting how species may respond to climate change.

A Review on In-vitro Haploid Production in Orchids

The aim of writing this paper is to review production of haploids in orchids in vitro. Haploids possess half number of chromosomes and do not undergo fertilization. In vitro conditions provide necessary nutrients and conditions that are required for growth of haploid plantlets. The natural breeding cycle of orchids is very slow as well as unpredictable. To reduce this time, the technique of in vitro haploid production is used. In vitro conditions can decrease or shorten the time required for juvenile period in Orchids. Haploid plants are produced from in vitro haploid culture. This technique is useful to produce homozygous pure lines and to increase the yield of a plant.

Genetic parameters of a progeny trial of Pinus greggii Engelmann ex Parlatore var. australis Donahue & López in the Mixteca Alta of Oaxaca, Mexico

Introduction: The Mixteca Alta of Oaxaca has high environmental degradation. Several species have been planted to recover vegetation cover; Pinus greggii Engelmann ex Parlatore var. australis Donahue & López has grown successfully even without selected material.Objective: To determine growth performance and genetic parameters of 90 families at early ages, for use in the selection of superior trees.Materials and methods: In San Miguel Achiutla, Oaxaca, genetic variation in growth, conformation and straightness of 90 selected open-pollinated families of P. greggii var. australiswas evaluated in a progeny trial five years after planting in two different quality sites. Additive genetic variation, heritability (h2) and genetic and phenotypic correlations were calculated.Results and discussion: h2 were superior in the more fertile site. Height, whorls, straightness and volume had greater genetic control (0.09 < h2i < 0.18). h2i of stem straightness was higher when evaluated as a whole than when divided into three sections. Genetic correlations were high and positive among growth variables (rg > 0.81; diameter vs. volume = 0.99) and low to moderate for the rest. Volume had a higher genetic correlation with other traits and higher genetic variation and heritability, so it could be used as a selection criterion for breeding cycle. Some genetic correlations differed contrastingly between sites in equal pairs of variables.Conclusion: Differences between families and heritability will allow the identification of superior individuals for germplasm sources for regional use.

Phenotyping seedlings for selection of root system architecture in alfalfa (Medicago sativa L.)

Background The root system architecture (RSA) of alfalfa (Medicago sativa L.) affects biomass production by influencing water and nutrient uptake, including nitrogen fixation. Further, roots are important for storing carbohydrates that are needed for regrowth in spring and after each harvest. Previous selection for a greater number of branched and fibrous roots significantly increased alfalfa biomass yield. However, phenotyping root systems of mature alfalfa plant is labor-intensive, time-consuming, and subject to environmental variability and human error. High-throughput and detailed phenotyping methods are needed to accelerate the development of alfalfa germplasm with distinct RSAs adapted to specific environmental conditions and for enhancing productivity in elite germplasm. In this study methods were developed for phenotyping 14-day-old alfalfa seedlings to identify measurable root traits that are highly heritable and can differentiate plants with either a branched or a tap rooted phenotype. Plants were grown in a soil-free mixture under controlled conditions, then the root systems were imaged with a flatbed scanner and measured using WinRhizo software. Results The branched root plants had a significantly greater number of tertiary roots and significantly longer tertiary roots relative to the tap rooted plants. Additionally, the branch rooted population had significantly more secondary roots > 2.5 cm relative to the tap rooted population. These two parameters distinguishing phenotypes were confirmed using two machine learning algorithms, Random Forest and Gradient Boosting Machines. Plants selected as seedlings for the branch rooted or tap rooted phenotypes were used in crossing blocks that resulted in a genetic gain of 10%, consistent with the previous selection strategy that utilized manual root scoring to phenotype 22-week-old-plants. Heritability analysis of various root architecture parameters from selected seedlings showed tertiary root length and number are highly heritable with values of 0.74 and 0.79, respectively. Conclusions The results show that seedling root phenotyping is a reliable tool that can be used for alfalfa germplasm selection and breeding. Phenotypic selection of RSA in seedlings reduced time for selection by 20 weeks, significantly accelerating the breeding cycle.