Plant breeding simulations with AlphaSimR

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 30, 2023

Abstract Plant breeding plays a crucial role in the development of high-performing crop varieties that meet demands society. Emerging techniques offer potential to improve precision and efficiency plant programs; however, their optimal implementation requires refinement existing programs or design new ones. Stochastic simulations are cost-effective solution for testing optimizing strategies. The aim this paper is provide an introduction stochastic simulation with software AlphaSimR students, researchers, experienced breeders. We present overview how use introductory vignette as well complete scripts self-pollinated, clonal, cross-pollinated plants, including relevant techniques, such backcrossing, speed breeding, genomic selection, index others. Our objective foundation understanding utilizing software, enabling readers adapt provided own even develop completely programs. By incorporating into education practice, next generation breeders will have valuable tool quest sustainable nutritious food sources growing population.

Language: Английский

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Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits in Urochloa ruziziensis

Frontiers in Plant Science, Journal Year: 2023, Volume and Issue: 14

Published: Dec. 12, 2023

Tropical forage grasses, particularly those belonging to the Urochloa genus, play a crucial role in cattle production and serve as main food source for animals tropical subtropical regions. The majority of these species are apomictic tetraploid, highlighting significance U. ruziziensis , sexual diploid that can be tetraploidized use interspecific crosses with species. As means support breeding programs, our study investigates feasibility genome-wide family prediction families predict agronomic traits. Fifty half-sibling were assessed green matter yield, dry regrowth capacity, leaf matter, stem across different clippings established contrasting seasons varying available water capacity. Genotyping was performed using genotyping-by-sequencing approach based on DNA samples from pools. In addition conventional genomic methods, machine learning feature selection algorithms employed reduce necessary number markers enhance predictive accuracy phenotypes. To explore regulation traits, evaluated selected tree-based approach, potentially linking regions quantitative trait loci (QTLs). multiomic genes transcriptome mapped correlated markers. A gene coexpression network modeled expression estimates diverse set genotypes, enabling comprehensive investigation molecular mechanisms associated heritabilities traits ranged 0.44 0.92. total 28,106 filtered SNPs used phenotypic measurements, achieving mean ability 0.762. By employing techniques, we could dimensionality SNP datasets, revealing potential genotype-phenotype associations. functional annotation near revealed associations auxin transport biosynthesis lignin, flavonol, folic acid. Further exploration uncovered metabolism, stress response, circadian rhythm. These represent important targets expanding understanding metabolic offer valuable insights applicable breeding. Our work represents an innovative contribution techniques forages, presenting viable marker-assisted identifying target future studies

Language: Английский

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Multiomic insights into sucrose accumulation in sugarcane

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 19, 2024

Abstract Sugarcane ( Saccharum spp.) holds significant economic importance in sugar and biofuel production. Despite extensive research, understanding highly quantitative traits, such as sucrose content, remains challenging due to the complex genomic landscape of crop. In this study, we conducted a multiomic investigation elucidate genetic architecture molecular mechanisms governing accumulation sugarcane. Using biparental cross (IACSP95-3018 × IACSP93-3046) genetically diverse collection sugarcane genotypes, evaluated soluble solids (Brix) content (POL) across various years environments. Both populations were genotyped using genotyping-by-sequencing (GBS) approach, with single nucleotide polymorphisms (SNPs) identified via bioinformatics pipelines. Genotype‒phenotype associations established combination traditional linear mixed-effect models machine learning algorithms. Furthermore, an RNA sequencing (RNA-Seq) experiment on genotypes exhibiting distinct Brix POL profiles different developmental stages. Differentially expressed genes (DEGs) potentially associated variations identified. All findings integrated through comprehensive gene coexpression network analysis. Strong correlations among characteristics observed, estimates modest high heritabilities. By leveraging broad set SNPs for both populations, several linked phenotypic variance. Our examination close these markers facilitated association DEGs contrasting levels. Through integration results network, delineated involved regulatory sugarcane, collectively contributing definition critical phenotype. constitute resource biotechnology plant breeding initiatives. our genotype‒phenotype hold promise application selection, offering valuable insights into underpinnings

Language: Английский

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Prospects of artificial intelligence for the sustainability of sugarcane production in the modern era of climate change: An overview of related global findings

Journal of Agriculture and Food Research, Journal Year: 2024, Volume and Issue: 18, P. 101519 - 101519

Published: Nov. 15, 2024

Language: Английский

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Advances in genomic characterization ofUrochloa humidicola: exploring polyploid inheritance and apomixis

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 3, 2023

Abstract Tropical forage grasses are an important food source for animal feeding, with Urochloa humidicol a, also known as Koronivia grass, being one of the main pasture poorly drained soils in tropics. However, genetic and genomic resources this species lacking due to its complexity, including high heterozygosity, evidence segmental allopolyploidy, reproduction by apomixis. These complexities hinder application marker-assisted selection (MAS) breeding programs. Here, we developed highest-density linkage map currently available hexaploid tropical grass U. humidicola . This was constructed using a biparental F1 population generated from cross between female parent H031 (CIAT 26146), only sexual genotype species, apomictic male H016 (BRS cv. Tupi). The analysis included 4,873 single nucleotide polymorphism (SNP) markers allele dosage information. It allowed mapping apospory locus phenotype group 3, region syntenic chromosome 3 ruziziensis 1 Setaria italica We identified haplotypes all individuals, assessed meiotic configuration, estimated level preferential pairing parents during process, which revealed autopolyploid origin contrast H016, presented allopolyploid behavior analysis. results provide new information regarding organization, mode reproduction, , potential SNPs associated apomixes MAS research on polyploids grasses. Key message present SNP expose origin, aiding polyploid research.

Language: Английский

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Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits inUrochloa ruziziensis

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 26, 2023

Abstract Tropical forage grasses, especially species of the genus Urochloa , play an important role in cattle production and are main food source for animals tropical/subtropical regions. Most apomictic tetraploid, which gives special importance to U. ruziziensis a sexual diploid that can be tetraploidized use interspecific crosses with species. As means assist breeding programs, this study investigates applicability genome-wide family prediction (GWFP) half-sibling families predict growth biomass production. Machine learning feature selection algorithms were used reduce necessary number markers enhance predictive ability across phenotypes. Beyond that, investigate regulation agronomic traits, positions more considered putatively associated quantitative trait loci (QTLs), multiomic approach, genes obtained transcriptome mapped linked those markers. Furthermore, gene coexpression network was modeled, enabling investigation not only but also their coexpressed genes. The functional annotation showed mainly auxin transport biosynthesis lignin, flavonol folic acid, while DNA metabolism, stress response circadian rhythm. results provide viable marker-assisted approach tropical forages identify target regions future molecular studies on these traits.

Language: Английский

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Advances in genomic characterization of Urochloa humidicola: exploring polyploid inheritance and apomixis

Theoretical and Applied Genetics, Journal Year: 2023, Volume and Issue: 136(11)

Published: Nov. 1, 2023

Language: Английский

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Unraveling growth molecular mechanisms inPinus taedawith GWAS, machine learning, and gene coexpression networks

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: Dec. 10, 2022

Abstract Pinus taeda (loblolly pine [LP]) is a long-lived tree species and one of the most economically significant forest species. Among growth traits, volume widely considered trait in improvement programs. However, deciphering genetic variants responsible for variations conifers, such as LP, particularly challenging due to vast size intricate complexity genomes. We present comprehensive analysis focusing on markers associated with stem variation, elucidate molecular mechanisms governing high-performance phenotypes. used population 1,692 individuals phenotyped genotyped these using sequence capture probes. To conduct genome-wide associations, we utilized both association study (GWAS) machine learning (ML) approaches. The identified were found be linked genes assembled from three distinct transcriptomes. These subsequently construct gene coexpression networks, through topological evaluations, key potential regulatory roles within configurations. Using set 31,589 SNPs, defined 7 GWAS-associated SNPs 128 ML-associated markers, all which correlated multiple involved diverse biological functions. Gene revealed group 270 potentially regulation material. Key directly implicated response stress identified, inferences about their impact development elucidated. Our not only offers insights into but also elucidates subset characterized by unique features. findings significantly advance our understanding factors influencing reveal candidate future functional studies, contribute broader comprehension architecture underlying traits LP.

Language: Английский

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Identificação de contaminantes e análises multiômicas aplicadas no melhoramento molecular de forrageiras tropicais poliploides

Published: Dec. 6, 2022

genômicos e a alta complexidade genômica

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