Multi-Species Genomics-Enabled Selection for Improving Agroecosystems Across Space and Time

Plant breeding has been central to global increases in crop yields. Breeding deserves praise for helping to establish better food security, but also shares the responsibility of unintended consequences. Much work has been done describing alternative agricultural systems that seek to alleviate these externalities, however, breeding methods and breeding programs have largely not focused on these systems. Here we explore breeding and selection strategies that better align with these more diverse spatial and temporal agricultural systems.

Download Full-text

Generalizable approaches for genomic prediction of metabolites in plants

10.1101/2021.11.24.469870 ◽

2021 ◽

Author(s):

Lauren J Brzozowski ◽

Malachy T Campbell ◽

Haixiao Hu ◽

Melanie Caffe ◽

Lucia Guterrez ◽

...

Keyword(s):

Plant Breeding ◽

Genomic Prediction ◽

Prediction Accuracy ◽

Group Model ◽

Plant Metabolites ◽

Plant Populations ◽

Breeding Programs ◽

Breeding Lines ◽

Consistent Model ◽

Selection For

Plant metabolites are important for plant breeders to improve nutrition and agronomic performance, yet integrating selection for metabolomic traits is limited by phenotyping expense and limited genetic characterization, especially of uncommon metabolites. As such, developing biologically-based and generalizable genomic selection methods for metabolites that are transferable across plant populations would benefit plant breeding programs. We tested genomic prediction accuracy for more than 600 metabolites measured by GC-MS and LC-MS in oat (Avena sativa L.) seed. Using a discovery germplasm panel, we conducted metabolite GWAS (mGWAS) and selected loci to use in multi-kernel models that encompassed metabolome-wide mGWAS results, or mGWAS from specific metabolite structures or biosynthetic pathways. Metabolite kernels developed from LC-MS metabolites in the discovery panel improved prediction accuracy of LC-MS metabolite traits in the validation panel, consisting of more advanced breeding lines. No approach, however, improved prediction accuracy for GC-MS metabolites. We tested if similar metabolites had consistent model ranks and found that, while different metrics of similarity had different results, using annotation-free methods to group metabolites led to consistent within-group model rankings. Overall, testing biological rationales for developing kernels for genomic prediction across populations, contributes to developing frameworks for plant breeding for metabolite traits.

Download Full-text

Food Security Impacted by Declining U.S. Plant‐Breeding Programs

CSA News ◽

10.1002/csan.20277 ◽

2020 ◽

Vol 65 (10) ◽

pp. 16-16

Keyword(s):

Food Security ◽

Plant Breeding ◽

Breeding Programs

Download Full-text

Variation within and between F2-derived families for grain yield and barley malting quality

Australian Journal of Agricultural Research ◽

10.1071/ar00041 ◽

2001 ◽

Vol 52 (1) ◽

pp. 85 ◽

Cited By ~ 1

Author(s):

M. Q. Lu ◽

L. O'Brien ◽

I. M. Stuart

Keyword(s):

Genetic Variation ◽

Grain Yield ◽

Near Infrared ◽

Malting Quality ◽

Breeding Programs ◽

Breeding Lines ◽

Selection Strategies ◽

Infrared Transmittance ◽

Selection For ◽

F2 Generation

Variation within and between F2-derived families for grain yield and malting quality was investigated using F4 breeding lines derived from F2 families of 4 barley crosses. The variation between F2-derived families was greater than within F2-derived families for grain yield and all malting quality attributes. Superior segregates almost exclusively came from the best performing families. The greater similarity of lines eventually drawn from an F2-derived family has significant implications for selection strategies in barley breeding programs as it facilitates the early discard of F2-derived families. To maximise the exploitation of genetic variation as early as possible, selection for malting quality could start in the F2 generation using near infrared transmittance (NIT) spectroscopy and for grain yield in the F3 generation.

Download Full-text

Improving Genotypic Adaptation in Crops – a Role for Breeders, Physiologists and Modellers

Experimental Agriculture ◽

10.1017/s0014479700018810 ◽

1991 ◽

Vol 27 (2) ◽

pp. 155-175 ◽

Cited By ~ 88

Author(s):

R. Shorter ◽

R. J. Lawn ◽

G. L. Hammer

Keyword(s):

Plant Breeding ◽

Biological Model ◽

Breeding Programme ◽

Breeding Methods ◽

Adaptive Traits ◽

Selection For ◽

Traditional Approaches

SummaryApproaches using breeding, physiology and modelling for evaluating adaptation of plant genotypes to target environments are discussed and methods of characterizing the target environments outlined. Traditional approaches, and their limitations, to evaluation of genotypic adaptation using statistical and classificatory techniques with a phenotypic model are discussed. It is suggested that a simple biological model is the most appropriate framework in which to integrate physiology and modelling with plant breeding. Methods by which physiology and modelling may contribute to assessment of adaptive traits and to selection for adaptation in a breeding programme are considered.

Download Full-text

Plant Breeding Integrated with Genomic-Enabled Prediction

OBM Genetics ◽

10.21926/obm.genet.2103137 ◽

2021 ◽

Vol 05 (03) ◽

pp. 1-1

Author(s):

Siamak Shirani Bidabadi ◽

◽

Parisa Sharifi ◽

S. Mohan Jain ◽

◽

...

Keyword(s):

Gene Flow ◽

Plant Breeding ◽

Genomic Prediction ◽

Crop Production ◽

Economic Benefits ◽

Plant Genome ◽

Plant Production ◽

Breeding Methods ◽

Breeding Programs ◽

Conventional Breeding

Plant breeding programs have used conventional breeding methods, such as hybridization, induced mutations, and other methods to manipulate the plant genome within the species' natural genetic boundaries to improve crop varieties. However, repeatedly using conventional breeding methods might lead to the erosion of the gene reservoir, thereby rendering crops vulnerable to environmental stresses and hampering future progress in crop production, food and nutritional security, and socio-economic benefits. Integrating innovative technologies in breeding programs to accelerate gene flow is critical for sustaining global plant production. Genomic prediction is a promising tool to assist the rapid selection of premiere genotypes and accelerate breeding gains for climate-resilient plant varieties. This review surveys the annals and principles of genomic-enabled prediction. Based on the problem that is investigated through the prediction, as well as several other factors, such as trait heritability, the relationship between the individuals to be predicted and those used to train the models for prediction, the number of markers, sample size, and the interaction between genotype and environment, different levels of accuracy have been reported. Genomic prediction might play a decisive role and facilitate gene flow from gene bank accessions to elite lines in future breeding programs.

Download Full-text

Selection for productivity and robustness traits in pigs

Animal Production Science ◽

10.1071/an15275 ◽

2015 ◽

Vol 55 (12) ◽

pp. 1437 ◽

Cited By ~ 10

Author(s):

S. Hermesch ◽

L. Li ◽

A. B. Doeschl-Wilson ◽

H. Gilbert

Keyword(s):

Feed Intake ◽

Disease Incidence ◽

Survival Rates ◽

Residual Feed Intake ◽

Production Traits ◽

Breeding Programs ◽

Selection Strategies ◽

Breeding Objectives ◽

Selection For ◽

Definition Of

Pig breeding programs worldwide continue to focus on both productivity and robustness. This selection emphasis has to be accompanied by provision of better-quality environments to pigs to improve performance and to enhance health and welfare of pigs. Definition of broader breeding objectives that include robustness traits in addition to production traits is the first step in the development of selection strategies for productivity and robustness. An approach has been presented which facilitates extension of breeding objectives. Post-weaning survival, maternal genetic effects for growth as an indicator of health status and sow mature weight are examples of robustness traits. Further, breeding objectives should be defined for commercial environments and selection indexes should account for genotype by environment interactions (GxE). Average performances of groups of pigs have been used to quantify the additive effects of multiple environmental factors on performance of pigs. For growth, GxE existed when environments differed by 60 g/day between groups of pigs. This environmental variation was observed even on well managed farms. Selection for improved health of pigs should focus on disease resistance to indirectly reduce pathogen loads on farms and on disease resilience to improve the ability of pigs to cope with infection challenges. Traits defining disease resilience may be based on performance and immune measures, disease incidence or survival rates of pigs. Residual feed intake is a trait that quantifies feed efficiency. The responses of divergent selection lines for residual feed intake to various environmental challenges were often similar or even favourable for the more efficient, low residual feed intake line. These somewhat unexpected results highlight the need to gain a better understanding of the metabolic differences between more or less productive pigs. These physiological differences lead to interactions between the genetic potential of pigs for productivity and robustness and the prevalence of specific environmental conditions.

Download Full-text

A Problem Based Learning Exercise on Food Security: Understanding the Role of Genomic Variation and Plant Breeding

10.1534/gsaprep.2018.004 ◽

2018 ◽

Author(s):

Jolie WAX ◽

Zhu Zhuo ◽

Anna Bower ◽

Jessica Cooper ◽

Susan Gachara ◽

...

Keyword(s):

Food Security ◽

Plant Breeding ◽

Problem Based Learning ◽

Genomic Variation

Download Full-text

ESTIMASI NILAI HERITABILITAS BOBOT IKAN MAS VARIETAS PUNTEN DALAM PROGRAM SELEKSI INDIVIDU

Jurnal Riset Akuakultur ◽

10.15578/jra.11.3.2016.217-223 ◽

2016 ◽

Vol 11 (3) ◽

pp. 217

Author(s):

Estu Nugroho ◽

Budi Setyono ◽

Mochammad Su’eb ◽

Tri Heru Prihadi

Keyword(s):

Body Weight ◽

Selection Response ◽

Base Population ◽

Breeding Programs ◽

Male And Female ◽

Body Weight Trait ◽

Population Selection ◽

Selection For ◽

Weight Trait ◽

Selection Of

Program pemuliaan ikan mas varietas Punten dilakukan dengan seleksi individu terhadap karakter bobot ikan. Pembentukan populasi dasar untuk kegiatan seleksi dilakukan dengan memijahkan secara massal induk ikan mas yang terdiri atas 20 induk betina dan 21 induk jantan yang dikoleksi dari daerah Punten, Kepanjen (delapan betina dan enam jantan), Kediri (tujuh betina dan 12 jantan), Sragen (27 betina dan 10 jantan), dan Blitar (15 betina dan 11 jantan). Larva umur 10 hari dipelihara selama empat bulan. Selanjutnya dilakukan penjarangan sebesar 50% dan benih dipelihara selama 14 bulan untuk dilakukan seleksi dengan panduan hasil sampling 250 ekor individu setiap populasi. Seleksi terhadap calon induk dilakukan saat umur 18 bulan pada populasi jantan dan betina secara terpisah dengan memilih berdasarkan 10% bobot ikan yang terbaik. Calon induk yang terseleksi kemudian dipelihara hingga matang gonad, kemudian dipilih sebanyak 150 pasang dan dipijahkan secara massal. Didapatkan respons positif dari hasil seleksi berdasarkan bobot ikan, yaitu 49,89 g atau 3,66% (populasi ikan jantan) dan 168,47 g atau 11,43% (populasi ikan betina). Nilai heritabilitas untuk bobot ikan adalah 0,238 (jantan) dan 0,505 (betina).Punten carp breeding programs were carried out by individual selection for body weight trait. The base population for selection activities were conducted by mass breeding of parent consisted of 20 female and 21 male collected from area Punten, eight female and six male (Kepanjen), seven female and 12 male (Kediri), 27 female and 10 male (Sragen), 15 female and 11 male (Blitar). Larvae 10 days old reared for four moths. Then after spacing out 50% of total harvest, the offspring reared for 14 months for selection activity based on the sampling of 250 individual each population. Selection of broodstock candidates performed since 18 months age on male and female populations separately by selecting based on 10% of fish with best body weight. Candidates selected broodstocks were then maintained until mature. In oder to produce the next generation 150 pairs were sets and held for mass spawning. The results revealed that selection response were positive, 49.89 g (3.66%) for male and 168.47 (11.43%) for female. Heritability for body weight is 0.238 (male) and 0.505 (female).

Download Full-text