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Keywords: genomic selection; breeding; plant breeding; animal breeding; dairy breeding; selection gain EN genomic selection breeding plant breeding animal breeding dairy breeding selection gain 1 6 6 11/24/21 20211119 NES 211119 Introduction Within the last 20 years, after the landmark paper by Meuwissen et al. ([26]), genomic selection (GS) has been widely incorporated in plant and animal breeding (Crossa et al., [12]; Hickey et al., [20]). Conclusion Dairy Cattle Breeding Compared to Plant Breeding Genomic selection was adopted in dairy cattle breeding almost instantly after genotyping costs dropped below the anticipated break-even point, presumably because the routine use of pedigree-based predictions, and a culture of centrally processing data of fragmented production units, had already been established (Schaeffer, [30]; Wiggans et al., [33]). Animal breeding, genomic selection, breeding, plant breeding, dairy breeding, selection gain Genomic Selection in Dairy Cattle Breeding Dairy cattle breeding provided good conditions for the introduction of GS. [Extracted from the article]

For the identification of germplasm bank accessions providing beneficial alleles for quantitative traits, we see the accession passport data as central information. In the case of a simple genetic architecture such as an identified major effect gene, the novel allele can be introgressed by marker assisted backcrossing (MABC) or can be approached by gene editing. Keywords: genetic resources; germplasm bank collections; predictive breeding; genomic selection; pre-breeding EN genetic resources germplasm bank collections predictive breeding genomic selection pre-breeding 1 4 4 07/05/21 20210701 NES 210701 Introduction Favorable variation from genetic resources is anticipated to play a key role in the adaptation of crops to the increasingly unfavorable production conditions resulting from climate change (FAO, [3]). Second, predictions can accelerate the pre-breeding (or "germplasm enhancement") process by helping to target the desired alleles for transfer to an elite germplasm background, saving resources and time. [Extracted from the article]

The use of temperate maize (Zea mays L.) inbreds with expired Plant Variety Protection in tropical maize breeding programs could enhance the combining ability for grain yield among tropical heterotic groups. We used DNA markers from the DArTseq genotyping‐by‐sequencing platform to investigate the genetic structure of lines with expired U.S. Plant Variety Protection (ex‐PVP) relative to the International Maize and Wheat Improvement Center's (CIMMYT's) maize heterotic groups. Neighbor‐joining cluster analysis revealed two major groups: CIMMYT and ex‐PVP. The CIMMYT lines clustered according to their pedigree relationships and adaptation, but not according to their heterotic groups. In contrast, ex‐PVP lines clustered according to the Stiff Stalk Synthetic (BSSS) and non‐Stiff Stalk Synthetic (NSSS) heterotic groups, except for a few lines that were considered to be mixed. The genetic divergence, estimated as Wright's fixation index (FST), between BSSS and NSSS (FST =.053, P <.01) was four times as large as the divergence between CIMMYT Tuxpeño and non‐Tuxpeño heterotic groups (FST =.013, P =.068). Estimates of genetic divergence marginally favored breeding with BSSS in Tuxpeño and NSSS in non‐Tuxpeño. However, CIMMYT breeders may still exploit the ex‐PVP heterotic structure fully only by ensuring that the temperate heterotic groups are placed on opposite sides of the Tuxpeño and non‐Tuxpeño heterotic pattern. We also showed how estimates of admixture from model‐based clustering could be used to avoid ex‐PVP lines of mixed heterotic background when selecting lines to maximize the genetic divergence and combining ability of CIMMYT heterotic groups. [ABSTRACT FROM AUTHOR]

Another opinion contribution was provided by Gholami et al. who compared the adoption of GS across different breeding institutions, in more detail dairy cattle breeding and public and private plant breeding programs. Keywords: genomic selection (GS); plant breeding; selection gain; breeding schemes; genotype-by-environment interaction EN genomic selection (GS) plant breeding selection gain breeding schemes genotype-by-environment interaction 1 3 3 05/31/22 20220527 NES 220527 Genomic selection (GS) has been one of the most prominent Research Topics in breeding science in the last two decades after the milestone paper by Meuwissen et al. ([1]). Plant breeding, selection gain, genotype-by-environment interaction, genomic selection (GS), breeding schemes. [Extracted from the article]

Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding. [ABSTRACT FROM AUTHOR]

Patterns of genomic divergence between hybridizing taxa can be heterogeneous along the genome. Both differential introgression and local adaptation may contribute to this pattern. Here, we analysed two teosinte subspecies, Zea mays ssp. parviglumis and ssp. mexicana, to test whether their divergence has occurred in the face of gene flow and to infer which environmental variables have been important drivers of their ecological differentiation. We generated 9,780 DArTseqTM SNPs for 47 populations, and used an additional data set containing 33,454 MaizeSNP50 SNPs for 49 populations. With these data, we inferred features of demographic history and performed genome wide scans to determine the number of outlier SNPs associated with climate and soil variables. The two data sets indicate that divergence has occurred or been maintained despite continuous gene flow and/or secondary contact. Most of the significant SNP associations were to temperature and to phosphorus concentration in the soil. A large proportion of these candidate SNPs were located in regions of high differentiation that had been identified previously as putative inversions. We therefore propose that genomic differentiation in teosintes has occurred by a process of adaptive divergence, with putative inversions contributing to reduced gene flow between locally adapted populations. [ABSTRACT FROM AUTHOR]

Conservation and exploitation of crop wild relative species is an important component in ensuring food security and improving current agricultural output. By identifying agriculturally important characteristics that express favorable response to both biotic and abiotic stress currently unused by breeders, the incorporation of this new genetic material into genetic background stocks may help mitigate problems imposed by climate change, land degradation, and population pressure. This is particularly important in countries that will be more severely affected by the threat of reduced yields. The ability to effectively manage genetic resources col- lections and integrate unique and diverse data types is crucial in exploring, understanding, and exploiting the diversity contained within gene-banks. Providing a common interface through which experimental and background data can be disseminated to both researchers and breeders will bring focus and facilitate community building into research communities. We have taken wild barley (Hordeum spp.) and potato (Solanum spp.) collections along with wheat (Triticum spp.) and maize (Zea mays subsp. mays) and their wild relatives and incorporated this data into web-based information resources built using the Germinate platform (https://ics.hutton.ac.uk/get-germinate, accessed 4 Apr. 2017). We have tailored these to better meet the demands of researchers by developing both new data visualization tools and integration with current software such as Helium, Flapjack, and CurlyWhirly (https://ics.hutton.ac.uk/software, accessed 4 Apr. 2017) and presented the data in a common platform. While the underlying species differ, the approach taken ensures that tools are compatible across all database instances. We will describe these database instances and show that Germinate offers a common platform that will aid in the exploration and wider use of these species. [ABSTRACT FROM AUTHOR]

Through the local selection of landraces, humans have guided the adaptation of crops to a vast range of climatic and ecological conditions. This is particularly true of maize, which was domesticated in a restricted area of Mexico but now displays one of the broadest cultivated ranges worldwide. Here, we sequenced 67 genomes with an average sequencing depth of 18x to document routes of introduction, admixture and selective history of European maize and its American counterparts. To avoid the confounding effects of recent breeding, we targeted germplasm (lines) directly derived from landraces. Among our lines, we discovered 22,294,769 SNPs and between 0.9% to 4.1% residual heterozygosity. Using a segmentation method, we identified 6,978 segments of unexpectedly high rate of heterozygosity. These segments point to genes potentially involved in inbreeding depression, and to a lesser extent to the presence of structural variants. Genetic structuring and inferences of historical splits revealed 5 genetic groups and two independent European introductions, with modest bottleneck signatures. Our results further revealed admixtures between distinct sources that have contributed to the establishment of 3 groups at intermediate latitudes in North America and Europe. We combined differentiation- and diversity-based statistics to identify both genes and gene networks displaying strong signals of selection. These include genes/gene networks involved in flowering time, drought and cold tolerance, plant defense and starch properties. Overall, our results provide novel insights into the evolutionary history of European maize and highlight a major role of admixture in environmental adaptation, paralleling recent findings in humans. [ABSTRACT FROM AUTHOR]

Quality control (QC) of germplasm identity and purity is a critical component of breeding and conservation activities. SNP genotyping technologies and increased availability of markers provide the opportunity to employ genotyping as a low-cost and robust component of this QC. In the public sector available low-cost SNP QC genotyping methods have been developed from a very limited panel of markers of 1,000 to 1,500 markers without broad selection of the most informative SNPs. Selection of optimal SNPs and definition of appropriate germplasm sampling in addition to platform section impact on logistical and resource-use considerations for breeding and conservation applications when mainstreaming QC. In order to address these issues, we evaluated the selection and use of SNPs for QC applications from large DArTSeq data sets generated from CIMMYT maize inbred lines (CMLs). Two QC genotyping strategies were developed, the first is a “rapid QC”, employing a small number of SNPs to identify potential mislabeling of seed packages or plots, the second is a “broad QC”, employing a larger number of SNP, used to identify each germplasm entry and to measure heterogeneity. The optimal marker selection strategies combined the selection of markers with high minor allele frequency, sampling of clustered SNP in proportion to marker cluster distance and selecting markers that maintain a uniform genomic distribution. The rapid and broad QC SNP panels selected using this approach were further validated using blind test assessments of related re-generation samples. The influence of sampling within each line was evaluated. Sampling 192 individuals would result in close to 100% possibility of detecting a 5% contamination in the entry, and approximately a 98% probability to detect a 2% contamination of the line. These results provide a framework for the establishment of QC genotyping. A comparison of financial and time costs for use of these approaches across different platforms is discussed providing a framework for institutions involved in maize conservation and breeding to assess the resource use effectiveness of QC genotyping. Application of these research findings, in combination with existing QC approaches, will ensure the regeneration, distribution and use in breeding of true to type inbred germplasm. These findings also provide an effective approach to optimize SNP selection for QC genotyping in other species. [ABSTRACT FROM AUTHOR]

Background: The limited genetic diversity of elite maize germplasms raises concerns about the potential to breed for new challenges. Initiatives have been formed over the years to identify and utilize useful diversity from landraces to overcome this issue. The aim of this study was to evaluate the proposed designs to initiate a pre-breeding program within the Seeds of Discovery (SeeD) initiative with emphasis on harnessing polygenic variation from landraces using genomic selection. We evaluated these designs with stochastic simulation to provide decision support about the effect of several design factors on the quality of resulting (pre-bridging) germplasm. The evaluated design factors were: i) the approach to initiate a pre-breeding program from the selected landraces, doubled haploids of the selected landraces, or testcrosses of the elite hybrid and selected landraces, ii) the genetic parameters of landraces and phenotypes, and iii) logistical factors related to the size and management of a pre-breeding program. Results: The results suggest a pre-breeding program should be initiated directly from landraces. Initiating from testcrosses leads to a rapid reconstruction of the elite donor genome during further improvement of the pre-bridging germplasm. The analysis of accuracy of genomic predictions across the various design factors indicate the power of genomic selection for pre-breeding programs with large genetic diversity and constrained resources for data recording. The joint effect of design factors was summarized with decision trees with easy to follow guidelines to optimize pre-breeding efforts of SeeD and similar initiatives. Conclusions: Results of this study provide guidelines for SeeD and similar initiatives on how to initiate pre-breeding programs that aim to harness polygenic variation from landraces. [ABSTRACT FROM AUTHOR]

Mexico is the primary center of origin and diversity for maize (Zea maysL.). Farmers grow the crop largely under rain-fed conditions. Mexico is at considerable risk from climate change because of predicted rising temperatures, declining rainfall, and an increase in extreme weather events. Small-scale maize farmers are particularly vulnerable because of their geographical location as well as their limited adaptive capacity. Recommended climate change adaptation strategies include farmers’ increased use of heat and drought stress-tolerant maize. Farmer adoption of improved germplasm has been disappointing because of inefficient seed input chains and farmers’ preference for landraces for culinary, agronomic, and cultural reasons. Scientists have tended to overlook the fact that maize landraces have a critical role to play in climate change adaptation. Landraces may already exist that are appropriate for predicted climates. Furthermore, within the primary gene pool of maize and its wild relatives there exists unexploited genetic diversity for novel traits and alleles that can be used for breeding new high yielding and stress-tolerant cultivars. The breeding component of adaptation strategies should focus more on improving farmers’ landraces. The desired result would be a segmented maize seed sector characterized by both (improved) landraces and improved maize varieties. The public and private sector could continue to provide farmers with improved maize varieties and different actors, including farmers themselves, would generate seed of improved landraces for sale and/or exchange. [ABSTRACT FROM AUTHOR]

The article focuses on how to control the existence of Striga hermonthica weeds. Striga's life cycle is said to be a complex type. Its life cycle coevolves with many hosts in order to comprise a series of discrete steps that are coupled with host biochemistry, namely seed germination and development of the penetrating organ. Its reproductive capacity can produce 10,000 to 200, 000 seeds per plant, which creates a big problem on how to control its rapid production. It states there are two available methods on how to control the yielding of Striga is categorized into two, such as the cultural control and seed-based technologies. A table that presents the summarized adopted methods is presented.

This paper describes AlphaSim, a software package for simulating plant and animal breeding programs. AlphaSim enables the simulation of multiple aspects of breeding programs with a high degree of flexibility. AlphaSim simulates breeding programs in a series of steps: (i) simulate haplotype sequences and pedigree; (ii) drop haplotypes into the base generation of the pedigree and select single-nucleotide polymorphism (SNP) and quantitative trait nucleotide (QTN); (iii) assign QTN effects, calculate genetic values, and simulate phenotypes; (iv) drop haplotypes into the burn-in generations; and (v) perform selection and simulate new generations. The program is flexible in terms of historical population structure and diversity, recent pedigree structure, trait architecture, and selection strategy. It integrates biotechnologies such as doubled-haploids (DHs) and gene editing and allows the user to simulate multiple traits and multiple environments, specify recombination hot spots and cold spots, specify gene jungles and deserts, perform genomic predictions, and apply optimal contribution selection. AlphaSim also includes restart functionalities, which increase its flexibility by allowing the simulation process to be paused so that the parameters can be changed or to import an externally created pedigree, trial design, or results of an analysis of previously simulated data. By combining the options, a user can simulate simple or complex breeding programs with several generations, variable population structures and variable breeding decisions over time. In conclusion, AlphaSim is a flexible and computationally efficient software package to simulate biotechnology enhanced breeding programs with the aim of performing rapid, low-cost, and objective in silico comparison of breeding technologies., (Copyright © 2016 Crop Science Society of America.)