The Strawberry DNA Testing Handbook

The availability of strawberry (Fragaria ×ananassa) genomic resources has increased dramatically in recent years. Some of these resources are readily applicable to strawberry breeding programs for use in DNA-informed breeding. Information about these tests and how to interpret them is dispersed through numerous manuscripts or in the laboratories that use them routinely. To assist breeders in identifying tests available to their breeding program and in implementing them in their program, a compendium of strawberry DNA tests was created. This compendium is available for download from the Genome Database for Rosaceae (https://www.rosaceae.org/organism/Fragaria/x-ananassa?pane=resource-4). This resource will be updated continually as old tests are modified and new tests are created.

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ForageGrassBase: Molecular resource for the forage grass Festuca pratensis Huds

10.1101/674390 ◽

2019 ◽

Author(s):

Jeevan Karloss Antony Samy ◽

Odd Arne Rognli ◽

Mallikarjuna Rao Kovi

Keyword(s):

Draft Genome ◽

Forage Yield ◽

Grass Species ◽

Comparative Genomic ◽

Festuca Pratensis ◽

Forage Grass ◽

Forage Grasses ◽

Genome Database ◽

Genomic Resources ◽

Link Type

AbstractBackgroundMeadow fescue (Festuca pratensis Huds.) is one of the most important forage grasses in temperate regions. F. pratensis is a diploid (2n =14) outbreeding species that belongs to the genus Festuca. Together with Lolium, they are the most important genera of forage grasses in temperate regions. F. pratensis has good winter survival, with high quality dry matter yields and persistency, and is suitable both for frequent-cutting conservation regimes and for grazing. It is a significant component of species-rich permanent pastures in the temperate regions, ensuring high forage yield under harsh climatic conditions where other productive forage grass species are unable to grow. However, genomic resources for F. Pratensis is not available so far.ResultsThe draft genome sequences of two F. pratensis genotypes “HF7/2” and “B14/16” are reported in this study. Here, using the draft genome, functional annotation datasets of two F. pratensis cultivars, we have constructed the F. pratensis genome database http://foragegrass.org/, the first open-access platform to provide comprehensive genomic resources related to this forage grass species. The current version of this database provides the most up-to-date draft genome sequence along with structural and functional annotations for genes using Genome Browser (GBrowse). In addition, we have integrated comparative genomic tracks for F. pratensis genomes by mapping F.pratensis genome to the barley, rice, Brachypodium and maize genomes. We have integrated homologus search tool BLAST also for the users to analyze their data. Combined, GBrowse, BLAST and downloadble data gives an user friendly access to F. pratensis genomic resouces. All data in the database were manually curated.ConclusionTo our knowledge, ForageGrassBase is the first genome database dedicated to forage grasses. It provides valuable resources for a range of research fields related to F. pratensis and other forage crop species, as well as for plant research communities in general. The genome database can be accessed at http://foragegrass.org. In the near future, we will expand the ForageGrassBase by adding genomic tools for other forage grass species, as soon as their genomes become available.

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Matoa (Pometia Pinata Foster): Local Fruit Papua and Strategy Development

Beccariana Botanical Research Bulletin ◽

10.30862/bbrp.v7i1.276 ◽

2010 ◽

Vol 7 (1) ◽

Author(s):

Julius D. Nugroho

Keyword(s):

Genetic Resources ◽

Fruit Tree ◽

Breeding Program ◽

Strategy Development ◽

Local Market ◽

Font Size ◽

Breeding Programs ◽

Irian Jaya ◽

Forest Exploitation ◽

Program Strategy

Matoa (Pometia pinnata) is a local fruit of  Papua (formerly called Irian Jaya) which has high potensial to develop as comercial fruit. Highly significant genetic resources of matoa potentially for breeding program in Papua are being threatened as a result of cutting down trees for fruit harvesting and of forest exploitation for timber. Besides the loss of genetic resources facing now, other major problems should be consider for conservation and domestication of this fruit tree species i.e. lack of silviculture and agronomy knowledge for further breeding programs; matoa production only for local market; and inadequate government policy for matoa breeding program. Strategy developed for matoa conservation and domestication should also concern about time limited due to the fast loss of genetic poll. This paper provides a general overview of strategy for conservation and domestication of Pometia pinnata with special reference to Papua.

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Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing

Sensors ◽

10.3390/s21123971 ◽

2021 ◽

Vol 21 (12) ◽

pp. 3971

Author(s):

Gabriel Silva de Oliveira ◽

José Marcato Junior ◽

Caio Polidoro ◽

Lucas Prado Osco ◽

Henrique Siqueira ◽

...

Keyword(s):

Remote Sensing ◽

Dry Matter ◽

Pearson Correlation ◽

Genetic Correlations ◽

Remote Sensing Data ◽

Breeding Program ◽

Yield Traits ◽

Dry Matter Yield ◽

Breeding Programs ◽

Ground Truth Data

Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) and computer vision are crucial to increase the efficiency of forage breeding programs, to support high-throughput phenotyping (HTP), aiming to estimate parameters correlated to important traits. The main goal of this study was to propose a convolutional neural network (CNN) approach using UAV-RGB imagery to estimate dry matter yield traits in a guineagrass breeding program. For this, an experiment composed of 330 plots of full-sib families and checks conducted at Embrapa Beef Cattle, Brazil, was used. The image dataset was composed of images obtained with an RGB sensor embedded in a Phantom 4 PRO. The traits leaf dry matter yield (LDMY) and total dry matter yield (TDMY) were obtained by conventional agronomic methodology and considered as the ground-truth data. Different CNN architectures were analyzed, such as AlexNet, ResNeXt50, DarkNet53, and two networks proposed recently for related tasks named MaCNN and LF-CNN. Pretrained AlexNet and ResNeXt50 architectures were also studied. Ten-fold cross-validation was used for training and testing the model. Estimates of DMY traits by each CNN architecture were considered as new HTP traits to compare with real traits. Pearson correlation coefficient r between real and HTP traits ranged from 0.62 to 0.79 for LDMY and from 0.60 to 0.76 for TDMY; root square mean error (RSME) ranged from 286.24 to 366.93 kg·ha−1 for LDMY and from 413.07 to 506.56 kg·ha−1 for TDMY. All the CNNs generated heritable HTP traits, except LF-CNN for LDMY and AlexNet for TDMY. Genetic correlations between real and HTP traits were high but varied according to the CNN architecture. HTP trait from ResNeXt50 pretrained achieved the best results for indirect selection regardless of the dry matter trait. This demonstrates that CNNs with remote sensing data are highly promising for HTP for dry matter yield traits in forage breeding programs.

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Cultivars developed in the strawberry breeding program of Fresas Nuevos Materiales S.A.

Acta Horticulturae ◽

10.17660/actahortic.2021.1309.11 ◽

2021 ◽

pp. 69-74

Author(s):

F. Pistón ◽

J.M. Arenas ◽

A. Refoyo

Keyword(s):

Breeding Program ◽

Strawberry Breeding

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Phenotypic and molecular characterization of a set of tropical maize inbred lines from a public breeding program in Brazil

BMC Genomics ◽

10.1186/s12864-021-08127-7 ◽

2022 ◽

Vol 23 (1) ◽

Author(s):

Sirlene Viana de Faria ◽

Leandro Tonello Zuffo ◽

Wemerson Mendonça Rezende ◽

Diego Gonçalves Caixeta ◽

Hélcio Duarte Pereira ◽

...

Keyword(s):

Genetic Diversity ◽

Population Structure ◽

Inbred Lines ◽

Breeding Program ◽

Tropical Maize ◽

Maize Breeding ◽

Breeding Programs ◽

The Public ◽

Maize Inbred Lines

Abstract Background The characterization of genetic diversity and population differentiation for maize inbred lines from breeding programs is of great value in assisting breeders in maintaining and potentially increasing the rate of genetic gain. In our study, we characterized a set of 187 tropical maize inbred lines from the public breeding program of the Universidade Federal de Viçosa (UFV) in Brazil based on 18 agronomic traits and 3,083 single nucleotide polymorphisms (SNP) markers to evaluate whether this set of inbred lines represents a panel of tropical maize inbred lines for association mapping analysis and investigate the population structure and patterns of relationships among the inbred lines from UFV for better exploitation in our maize breeding program. Results Our results showed that there was large phenotypic and genotypic variation in the set of tropical maize inbred lines from the UFV maize breeding program. We also found high genetic diversity (GD = 0.34) and low pairwise kinship coefficients among the maize inbred lines (only approximately 4.00 % of the pairwise relative kinship was above 0.50) in the set of inbred lines. The LD decay distance over all ten chromosomes in the entire set of maize lines with r2 = 0.1 was 276,237 kb. Concerning the population structure, our results from the model-based STRUCTURE and principal component analysis methods distinguished the inbred lines into three subpopulations, with high consistency maintained between both results. Additionally, the clustering analysis based on phenotypic and molecular data grouped the inbred lines into 14 and 22 genetic divergence clusters, respectively. Conclusions Our results indicate that the set of tropical maize inbred lines from UFV maize breeding programs can comprise a panel of tropical maize inbred lines suitable for a genome-wide association study to dissect the variation of complex quantitative traits in maize, mainly in tropical environments. In addition, our results will be very useful for assisting us in the assignment of heterotic groups and the selection of the best parental combinations for new breeding crosses, mapping populations, mapping synthetic populations, guiding crosses that target highly heterotic and yielding hybrids, and predicting untested hybrids in the public breeding program UFV.

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MoBPSweb: A web-based framework to simulate and compare breeding programs

10.1101/2020.07.08.193227 ◽

2020 ◽

Cited By ~ 1

Author(s):

T. Pook ◽

L. Büttgen ◽

A. Ganesan ◽

N.T. Ha ◽

H. Simianer

Keyword(s):

Selection Index ◽

Relevant Information ◽

Simulation Software ◽

Breeding Program ◽

Breeding Value ◽

Long Term Effects ◽

General Applicability ◽

Breeding Programs ◽

Web Based ◽

Value Estimation

ABSTRACTSelective breeding is a continued element of both crop and livestock breeding since early prehistory. In this work, we are proposing a new web-based simulation framework (“MoBPSweb”) that is combining a unified language to describe breeding programs with the simulation software MoBPS, standing for ‘Modular Breeding Program Simulator’. Thereby, MoBPSweb is providing a flexible environment to enter, simulate, evaluate and compare breeding programs. Inputs can be provided via modules ranging from a Vis.js-based flash environment for “drawing” the breeding program to a variety of modules to provide phenotype information, economic parameters and other relevant information. Similarly, results of the simulation study can be extracted and compared to other scenarios via output modules (e.g. observed phenotypes, accuracy of breeding value estimation, inbreeding rates). Usability of the framework is showcased along a toy example of a dairy cattle breeding program on farm level, with comparing scenarios differing in implemented breeding value estimation, selection index and selection intensity being considered. Comparisons are made considering both short and long-term effects of the different scenarios in terms of genomic gains, rates of inbreeding and the accuracy of the breeding value estimation. Lastly, general applicability of the MoBPSweb framework and the general potential for simulation studies for genetics and in particular in breeding are discussed.

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Genomic Selection for Any Dairy Breeding Program via Optimized Investment in Phenotyping and Genotyping

Frontiers in Genetics ◽

10.3389/fgene.2021.637017 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jana Obšteter ◽

Janez Jenko ◽

Gregor Gorjanc

Keyword(s):

Genomic Selection ◽

Genetic Gain ◽

Breeding Program ◽

Progeny Testing ◽

Initial Training ◽

Training Population ◽

Breeding Programs ◽

Use Of Resources ◽

Dairy Cattle Breeding ◽

Close Relatives

This paper evaluates the potential of maximizing genetic gain in dairy cattle breeding by optimizing investment into phenotyping and genotyping. Conventional breeding focuses on phenotyping selection candidates or their close relatives to maximize selection accuracy for breeders and quality assurance for producers. Genomic selection decoupled phenotyping and selection and through this increased genetic gain per year compared to the conventional selection. Although genomic selection is established in well-resourced breeding programs, small populations and developing countries still struggle with the implementation. The main issues include the lack of training animals and lack of financial resources. To address this, we simulated a case-study of a small dairy population with a number of scenarios with equal available resources yet varied use of resources for phenotyping and genotyping. The conventional progeny testing scenario collected 11 phenotypic records per lactation. In genomic selection scenarios, we reduced phenotyping to between 10 and 1 phenotypic records per lactation and invested the saved resources into genotyping. We tested these scenarios at different relative prices of phenotyping to genotyping and with or without an initial training population for genomic selection. Reallocating a part of phenotyping resources for repeated milk records to genotyping increased genetic gain compared to the conventional selection scenario regardless of the amount and relative cost of phenotyping, and the availability of an initial training population. Genetic gain increased by increasing genotyping, despite reduced phenotyping. High-genotyping scenarios even saved resources. Genomic selection scenarios expectedly increased accuracy for young non-phenotyped candidate males and females, but also proven females. This study shows that breeding programs should optimize investment into phenotyping and genotyping to maximize return on investment. Our results suggest that any dairy breeding program using conventional progeny testing with repeated milk records can implement genomic selection without increasing the level of investment.

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ARE TODAY’S DAIRY CATTLE BREEDING PROGRAMS SUITABLE FOR TOMORROW’S PRODUCTION REQUIREMENTS?

Canadian Journal of Animal Science ◽

10.4141/cjas80-034 ◽

1980 ◽

Vol 60 (2) ◽

pp. 253-264 ◽

Cited By ~ 4

Author(s):

A. J. McALLISTER

Keyword(s):

Dairy Cattle ◽

Genetic Improvement ◽

Herd Size ◽

Breeding Program ◽

Genetic Trend ◽

Genetic Progress ◽

Breeding Programs ◽

Holstein Breed ◽

Dairy Cattle Breeding ◽

National Production

In the last decade the dairy cattle population has declined to a level of 1.9 million cows in 1978 with about 56% of these cows bred AI and nearly 20% of the population enrolled in a supervised milk recording program. The decline in cow numbers has been accompanied by an increase in herd size and production per cow. The current breeding program of the dairy industry is a composite of breeding decisions made by AI organizations, breeders who produce young bulls for sampling and all dairymen who choose the sires and dams of their replacement heifers. Estimates of genetic trend from 1958–1975 for milk production in the national milk recorded herd range from 21 to 55 kg per year for the four dairy breeds with Holsteins being 41 kg per year. Both differential use of superior proven sires and improved genetic merit of young bulls entering AI studs contribute to this genetic improvement. Various national production and marketing alternatives were examined. Selection is a major breeding tool in establishing a breeding program to meet national production requirements for milk and milk products once the selection goal is defined. AI and young sire sampling programs will continue to be the primary vehicle for genetic improvement through selection regardless of the selection goal. The current resources of milk-recorded cows bred AI is not being fully utilized to achieve maximum genetic progress possible from young sire sampling indicate that the number of young bulls sampled annually in the Holstein breed could be tripled with the existing milk-recorded and AI bred dairy cow population. Expanded milk recording and AI breeding levels could increase the potential for even further genetic improvement. The potential impact of selection for other traits, crossbreeding and the use of embryo transfer of future breeding programs is highlighted.

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POWDERY MILDEW RESISTANCE IN STRAWBERRY PROGENIES

Canadian Journal of Plant Science ◽

10.4141/cjps61-032 ◽

1961 ◽

Vol 41 (2) ◽

pp. 239-243 ◽

Cited By ~ 5

Author(s):

Hugh A. Daubeny

Keyword(s):

Powdery Mildew ◽

Powdery Mildew Resistance ◽

Breeding Program ◽

Mildew Resistance ◽

Large Numbers ◽

The Mean ◽

Strawberry Breeding ◽

Resistance Rating

The effect of various parents on the degree of powdery mildew resistance in strawberry progenies was studied. Puget Beauty parentage, compared with Siletz, Surecrop, Talisman, Magoon, or Stelemaster parentage, gave a highly significant increase in the mean resistance rating. British Sovereign parentage, compared with Northwest or Agassiz parentage, gave a significant increase in the mean resistance rating. Puget Beauty was the only parent to give relatively large numbers of seedlings immune or resistant to powdery mildew. Siletz was as resistant to the disease as Puget Beauty, but did not transmit this resistance to its progeny. Selections immune or resistant to powdery mildew will be used in the strawberry breeding program at Agassiz.

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Consistency of organoleptic and yield related traits of strawberry cultivars over time

Journal of Berry Research ◽

10.3233/jbr-200548 ◽

2020 ◽

Vol 10 (4) ◽

pp. 623-636

Author(s):

M.T. Ariza ◽

L. Miranda ◽

E. Martínez-Ferri ◽

J.J. Medina ◽

J.A. Gómez-Mora ◽

...

Keyword(s):

Fragaria X Ananassa ◽

Crop Season ◽

Breeding Programs ◽

Continuous Increase ◽

Environment Temperature ◽

New Varieties ◽

Different Characteristics ◽

Organoleptic Parameters ◽

Over Time ◽

Strawberry Cultivars

BACKGROUND: Strawberry (Fragaria x ananassa Duch.) is among the most widely consumed fruits in the world and its cultivation is increasing worldwide. This continuous increase in its cultivation acreage is concomitant with the development of new varieties by numerous breeding programs. Due to strawberry is a microclimatic crop, the behaviour of the cultivars could vary depending on many agronomical and environmental factors such as temperature or humidity. Thus, for some traits, data from a single crop season may not be enough to suspect the behaviour of a specific variety. OBJECTIVE: Generate information that allows knowing the consistency of different characteristics over time. METHODS: For four consecutive years, organoleptic and yield related traits were analysed in five strawberry cultivars. RESULTS: The overall result is a significant effect of genotype on all yield relates and organoleptic parameters studied. Our study also inferred an effect of environment, temperature and relative humidity, mainly on yield parameters. However, not all cultivars were similarly affected. CONCLUSIONS: With the information generated from this work, it will be possible to establish, based on the consistency of the cultivar trials over time, the suitability of using the results of a single season to predict the behaviour of a particular cultivar.

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