Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance

Yu, Guangning; Cui, Yanru; Jiao, Yang; Zhou, Kai; Wang, Xin; WenyanYang,; Xu, Yong; Yang, Kun; Zhang, Xuecai; Li, Pengcheng; Yang, Zefeng; Yang, Xu; Xu, Chenwu

doi:10.1016/j.cj.2022.09.004

Cited by 14 publications

(9 citation statements)

References 39 publications

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“…CRISPR-Cas9 allows researchers to introduce targeted mutations, insertions, or deletions in plant genomes, facilitating gene knockout, gene replacement, or gene editing. Genome editing offers unprecedented opportunities for crop improvement by enabling precise modification of genes associated with agronomical important traits, leading to the development of tailored crop varieties with enhanced performance and resilience [30].…”

Section: Genome Editing Technologiesmentioning

confidence: 99%

“…Genomic selection strategies facilitate the breeding of nutrient-rich varieties by prioritizing individuals with desirable nutritional traits based on their genomic profiles. [35,36] Moreover, understanding the genetic basis of phytochemical compounds such as antioxidants, vitamins, and secondary metabolites enables breeders to develop crops with enhanced functional properties and therapeutic benefits. Through targeted manipulation of metabolic pathways and gene regulatory networks, genomic approaches offer unprecedented opportunities for improving the nutritional quality and health-promoting attributes of crop plants.…”

Section: Improving Nutritional and Phytochemical Profilesmentioning

confidence: 99%

“…Unlike traditional phenotypic selection, which relies on observed performance, GS integrates genome-wide marker data with phenotypic information to estimate the genetic merit of individuals for target traits [40]. Using statistical models and machine learning algorithms, GS enables breeders to predict the performance of untested individuals based on their genomic profile.…”

Section: Genomic Selection Strategiesmentioning

confidence: 99%

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Genomic Approaches for Enhancing Yield and Quality Traits in Mustard (Brassica spp.): A Review of Breeding Strategies

Sunagar,

Pandey

2024

JABB

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Mustard, a vital oilseed crop, plays a significant role in global agriculture due to its versatile applications in food, feed, and biofuel industries. However, meeting the increasing demands for yield and quality traits poses a substantial challenge to mustard breeders. In response, genomic approaches have emerged as powerful tools to expedite mustard breeding programs by unraveling the genetic basis of key agronomic traits. This review provides a comprehensive overview of genomic strategies aimed at enhancing yield and quality traits in mustard. Beginning with an exploration of traditional breeding methods and their limitations, we delve into the advancements in genomics, including next-generation sequencing technologies, marker-assisted selection (MAS), and genome editing techniques. We discuss how these tools are leveraged to identify yield-related genes, quantitative trait loci (QTLs), and markers for efficient trait selection. Furthermore, we examine genomic approaches for improving oil content, nutritional profiles, and phytochemical composition, crucial for enhancing mustard quality. Case studies demonstrating the successful integration of genomics into breeding programs are highlighted, along with discussions on challenges such as regulatory concerns and technical hurdles. Finally, we outline future directions and the potential of genomic approaches to revolutionize mustard breeding, paving the way for sustainable crop improvement. This study offers valuable insights into the application of genomics in mustard breeding and underscores its importance in addressing the evolving needs of agriculture in the 21st century.

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Section: Genome Editing Technologiesmentioning

confidence: 99%

Section: Improving Nutritional and Phytochemical Profilesmentioning

confidence: 99%

Section: Genomic Selection Strategiesmentioning

confidence: 99%

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Genomic Approaches for Enhancing Yield and Quality Traits in Mustard (Brassica spp.): A Review of Breeding Strategies

Sunagar,

Pandey

2024

JABB

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“…Pendekatan GS pada kelapa sawit terkini telah menggunakan marka SNP dengan keunggulan dalam hal kerapatan marka dan akurasi yang lebih baik (Cros et al, 2017;Kwong et al, 2017a;Kwong et al, 2017b;Nyouma et al, 2020). Pada kelapa sawit, kerapatan marka untuk mendapatkan tingkat akurasi prediksi yang baik tergolong relatif lebih rendah (±500 SNP) (Cros et al, 2017) jika dibandingkan dengan kerapatan marka pada tanaman menyerbuk silang lainnya, misalnya tanaman jagung (Yu et al, 2023).…”

Section: Pemanfaatan Seleksi Genomik Pada Kelapa Sawitunclassified

Pendekatan Seleksi Genomik Dalam Mendukung Program Pemuliaan Kelapa Sawit

Rachman,

Sujadi,

Adriwan Siregar

et al. 2024

war

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Kelapa sawit merupakan salah satu tanaman penghasil minyak nabati terbesar di dunia. Produktivitas yang tinggi pada kelapa sawit tidak lepas dari peran penyediaan bahan tanaman unggul yang dilakukan melalui program pemuliaan kelapa sawit dengan skema reciprocal recurrent selection (RRS). Akan tetapi, skema tersebut memiliki kelemahan dalam hal siklus waktu yang lama dan intensitas seleksi yang rendah. Perkembangan teknologi molekuler yang masif melalui seleksi genomik dapat mengatasi permasalahan tersebut. Beberapa faktor pertimbangan yang harus diperhatikan dalam mengadopsi pendekatan seleksi genomik antara lain karakteristik dari sifat yang akan diperbaiki, tipe dan jumlah marka molekuler, ukuran dan keterkaitan populasi pelatihan dan pengujian, serta model statistik yang akan digunakan. Penelitian mengenai adopsi seleksi genomik pada kelapa sawit telah dilakukan untuk menjawab permasalahan yang ada. Pada program pemuliaan kelapa sawit, seleksi genomik berhasil memberikan efisiensi biaya yang baik (26%-65%) dan mempercepat siklus hingga 35%. Selain itu, permasalahan intensitas seleksi yang rendah pada RRS juga dapat diatasi melalui strategi pra-seleksi genomik.

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“…Thus, SNP genotyping arrays provide a high-throughput and costeffective way to analyse genetic diversity and have been widely used to generate genetic linkage maps, study evolutionary relationships, unravel functional genomics and support conservation efforts. They have also proved to be highly valuable in breeding programmes being used for marker assisted selection (MAS) (Thompson, 2014;Arruda et al, 2016), genome-wide association studies (GWAS) (McCouch et al, 2016;Negro et al, 2019;Balagué-Dobón et al, 2022;Yu et al, 2023), and the mapping of QTL (Xu et al, 2017;Stadlmeier et al, 2018). Their power and utility are evidenced by the large number of arrays available for crop species (strawberry - Verma et al, 2017;rose -Koning-Boucoiran et al, 2015;chrysanthemum -van Geest et al, 2017;potato-Vos et al, 2015;rice -Chen et al, 2014b;Kim et al, 2022;Deware et al, 2023;maize -Unterseer et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Development of a Next Generation SNP Genotyping Array for Wheat

Burridge,

Winfield,

Przewieslik-Allen

et al. 2023

Preprint

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SummaryHigh throughput genotyping arrays have provided a cost effective, reliable and interoperable system for genotyping hexaploid wheat and its related germplasm pool. Existing, highly cited arrays including our 35K Axiom Wheat Breeder’s genotyping array and the Illumina 90K iSelect array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in sequencing wheat varieties and landraces has given us access to a vast pool of SNP diversity, whilst technological improvements in array design has allowed us to fit significantly more probes onto a 384-well format Axiom array than was previously possible. Here we describe a novel High Density Axiom genotyping array, theTriticum aestivumNext Generation array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins “Core Collection”. We use a novel “minimal marker” optimisation approach to select up to six SNPs in each 1.5 MB region of the wheat genome with the highest combined varietal discrimination potential. A design iteration step allowed us to test and replace skim-sequence derived SNPs which failed to convert to reliable Axiom markers, resulting in a final design, designated TaNG1.1 with 43,372 SNPs derived from a haplotype-optimised combination of novel SNPs, DArTAG-derived and legacy wheat Axiom markers. We show that this design has an even distribution of SNPs across chromosomes and sub-genomes compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous Axiom array. We also demonstrate the improved performance of TaNG1.1 for Genome Wide Association Studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available, and the marker annotations, initial genotyping results and software used to generate the optimised marker sets are freely available.

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Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance

Cited by 14 publications

References 39 publications

Genomic Approaches for Enhancing Yield and Quality Traits in Mustard (Brassica spp.): A Review of Breeding Strategies

Genomic Approaches for Enhancing Yield and Quality Traits in Mustard (Brassica spp.): A Review of Breeding Strategies

Pendekatan Seleksi Genomik Dalam Mendukung Program Pemuliaan Kelapa Sawit

Development of a Next Generation SNP Genotyping Array for Wheat

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