Article
Genetics & Heredity
Jiabo Wang, Zhiwu Zhang
Summary: Genome-wide association study (GWAS) and genomic prediction/selection (GP/GS) are two essential tasks in genomic research. GAPIT, a widely-used integrated tool, has recently introduced multi-locus test methods to enhance statistical power and prediction accuracy.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2021)
Article
Agronomy
Brian R. Rice, Alexander E. Lipka
Summary: Genomic selection is a powerful tool for maize breeding, with the potential to increase genetic gains and improve accuracy of breeding value predictions through advancements in GS models.
MOLECULAR BREEDING
(2021)
Article
Biotechnology & Applied Microbiology
Federico Casale, Delphine Van Inghelandt, Marius Weisweiler, Jinquan Li, Benjamin Stich
Summary: Meiotic recombination is crucial for adaptation and breeding in sexually reproducing eukaryotes. This study assessed recombination rate variation in cultivated barley, highlighting differences in general and specific recombination effects. The research demonstrated the potential of genomic selection to predict recombination rate and manipulate it through natural variation.
PLANT BIOTECHNOLOGY JOURNAL
(2022)
Review
Agronomy
Leon Muntean, Andreea Ona, Ioana Berindean, Ionut Racz, Sorin Muntean
Summary: Maize will continue to expand and diversify as an industrial resource and a feed and fuel crop, and genomics tools are essential for precise, fast, and efficient crop breeding in the face of climate challenges. Furthermore, genomic tools have the potential to accelerate the process of de novo domestication of maize.
Article
Plant Sciences
Pengzun Ni, Mahlet Teka Anche, Yanye Ruan, Dongdong Dang, Nicolas Morales, Lingyue Li, Meiling Liu, Shu Wang, Kelly R. Robbins
Summary: This study investigates the genetic correlations between the dry-down rate of grain and other related traits using multi-trait genomic prediction models. The results show moderate-to-high genetic correlations between the traits and demonstrate that the use of multi-trait genomic prediction models can substantially improve prediction accuracy.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Forestry
Geoffrey Haristoy, Laurent Bouffier, Luis Fontes, Luis Leal, Jorge A. P. Paiva, Joao-Pedro Pina, Jean-Marc Gion
Summary: Genomic selection is a promising method for accelerating forest tree breeding, but there is limited research on multi-generational breeding programs in forest tree species. In this study, a subset of the Eucalyptus globulus breeding population was analyzed, and pedigree errors were corrected using marker-based relationship coefficients. Pseudo-phenotypes derived from field trials were used to estimate breeding values, and accuracy of genomic prediction models was evaluated through cross-validation. The study showed promising results for the Eucalyptus breeding program of Altri Florestal.
TREE GENETICS & GENOMES
(2023)
Review
Plant Sciences
Roberto Fritsche-Neto, Giovanni Galli, Karina Lima Reis Borges, Germano Costa-Neto, Filipe Couto Alves, Felipe Sabadin, Danilo Hottis Lyra, Pedro Patric Pinho Morais, Luciano Rogerio Braatz de Andrade, Italo Granato, Jose Crossa
Summary: The study discusses the importance of genomic prediction in tropical maize breeding and emphasizes on improving prediction accuracy under low budget and small-scale conditions. By exploring strategies such as germplasm characterization, mating design practices, and modeling of genotype-environment interaction, the accuracy of predicting tropical maize hybrids can be enhanced.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Plant Sciences
Yoseph Beyene, Manje Gowda, Paulino Perez-Rodriguez, Michael Olsen, Kelly R. Robbins, Juan Burgueno, Boddupalli M. Prasanna, Jose Crossa
Summary: The study aimed to evaluate genomic selection prediction scenarios for grain yield and agronomic traits of tropical maize, based on multi-year empirical data for designing a GS-based strategy at the early stages of the breeding pipeline. By combining multiple years of data for training, the prediction accuracy can be increased, leading to significant resource savings in maize breeding programs.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Plant Sciences
Guilherme Ferreira Simiqueli, Rafael Tassinari Resende, Elizabete Keiko Takahashi, Joao Edesio de Sousa, Dario Grattapaglia
Summary: This study assessed the realized predictive ability for volume growth at harvest age by genomic selection (GS) in hybrid Eucalyptus. It found that the predictive ability of GS improved when the direct parents of selection candidates were used in training, and that pure species data resulted in higher predictive abilities than hybrid data.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Genetics & Heredity
Sirjan Sapkota, Jon Lucas Boatwright, Neeraj Kumar, Matthew Myers, Alex Cox, Arlyn Ackerman, William Caughman, Zachary W. Brenton, Richard E. Boyles, Stephen Kresovich
Summary: Hybrid breeding in sorghum utilizes the CMS system for seed production and harnesses heterosis. Genomic prediction of parental lines and hybrids is based on genotype data to save time and cost. Through genotyping and phenotypic data collection, high accuracy prediction for agronomic traits in sorghum can be achieved. Optimal training population design for genomic selection is essential for maximizing prediction accuracies.
G3-GENES GENOMES GENETICS
(2023)
Article
Plant Sciences
YunCan Liu, Man Ao, Ming Lu, Shubo Zheng, Fangbo Zhu, Yanye Ruan, Yixin Guan, Ao Zhang, Zhenhai Cui
Summary: This study reveals the influencing factors of husk tightness in maize in different environments, providing an authoritative reference method for molecular breeding of maize.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Plant Sciences
Ce Liu, Xiaoxiao Liu, Yike Han, Xi'ao Wang, Yuanyuan Ding, Huanwen Meng, Zhihui Cheng
Summary: Genomic prediction was applied in cucumber breeding, demonstrating high predictive ability of GCA models for cucumber traits. Non-additive effects significantly influenced trait prediction, with a relatively higher proportion of additive-by-additive genetic variance components.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Biotechnology & Applied Microbiology
Akio Onogi, Toshio Watanabe, Atsushi Ogino, Kazuhito Kurogi, Kenji Togashi
Summary: Genomic prediction using non-additive effects was assessed in Japanese Black cattle for phenotypic prediction, showing moderate to relatively high levels of additive-by-additive variance components. However, incorporating these effects did not improve predictive accuracy. Subsampling analysis indicated that estimation of additive-by-additive effects heavily relied on phenotype values, while the variance components were more stable against population size reduction.
Review
Genetics & Heredity
Bader Arouisse, Tom P. J. M. Theeuwen, Fred A. van Eeuwijk, Willem Kruijer
Summary: The advances in high-throughput phenotyping have led to a greater number of secondary traits being observed, posing a challenge to improving genomic prediction for the target trait. Existing methods have limitations when dealing with a large number of secondary traits, emphasizing the need for novel approaches to enhance prediction accuracy.
FRONTIERS IN GENETICS
(2021)
Article
Genetics & Heredity
Shaohua Zhu, Tingting Guo, Chao Yuan, Jianbin Liu, Jianye Li, Mei Han, Hongchang Zhao, Yi Wu, Weibo Sun, Xijun Wang, Tianxiang Wang, Jigang Liu, Christian Keambou Tiambo, Yaojing Yue, Bohui Yang
Summary: The accuracy of genomic prediction (GP) or selection (GS) depends on marker density, heritability level, and statistical models used. Increasing marker density improves GP accuracy, and different models are more suitable for traits with different heritability levels. The study highlights the importance of incorporating these factors into real data to optimize GP.
G3-GENES GENOMES GENETICS
(2021)
Article
Ecology
Kelly Swarts, Eva Bauer, Jeffrey C. Glaubitz, Tiffany Ho, Lynn Johnson, Yongxiang Li, Yu Li, Zachary Miller, Cinta Romay, Chris-Carolin Schon, Tianyu Wang, Zhiwu Zhang, Edward S. Buckler, Peter Bradbury
Summary: This study explores the biological basis of temperate adaptation in maize populations from different regions, revealing differences in predictive ability among populations. By analyzing the genetic characteristics of different maize populations in temperate and tropical regions, the study provides insights into adaptive differences in different geographical areas.
Letter
Biochemistry & Molecular Biology
Xianra Li, Tingting Guo, Guihua Bai, Zhiwu Zhang, Deven See, Juliet Marshall, Kimberly A. Garland-Campbell, Jianming Yu
Article
Plant Sciences
Lance F. Merrick, Adrienne B. Burke, Zhiwu Zhang, Arron H. Carter
Summary: This study aimed to dissect the genetic architecture of seedling emergence in wheat using one multi-trait genome-wide association study (MT-GWAS) and three single-trait GWAS (ST-GWAS) models. The ST-GWAS models identified 107 significant markers across 19 chromosomes, while the MT-GWAS identified 82 significant markers across 14 chromosomes. The FarmCPU and BLINK models were able to identify both small effect markers and large effect markers on chromosome 5A.
FRONTIERS IN PLANT SCIENCE
(2022)
Review
Genetics & Heredity
Karansher S. Sandhu, Lance F. Merrick, Sindhuja Sankaran, Zhiwu Zhang, Arron H. Carter
Summary: The adoption of genomic selection and phenomics tools in plant breeding programs has significantly increased in the past decade. Genomic selection has shown potential in selecting superior genotypes with high precision and accelerating the breeding cycle, while phenomics aims to alleviate phenotyping bottlenecks and explore new large-scale phenotyping and data acquisition methods. This review discusses the lessons learned from genomic selection and phenomics in six self-pollinated crops and their implementation schemes, with a focus on rice, wheat, soybean, common bean, chickpea, and groundnut.
FRONTIERS IN GENETICS
(2022)
Article
Genetics & Heredity
Ruicai Long, Fan Zhang, Zhiwu Zhang, Mingna Li, Lin Chen, Xue Wang, Wenwen Liu, Tiejun Zhang, Long-Xi Yu, Fei He, Xueqian Jiang, Xijiang Yang, Changfu Yang, Zhen Wang, Junmei Kang, Qingchuan Yang
Summary: This study reported the chromosome-level genome sequence and genomic variation database of Zhongmu-4, a widely cultivated alfalfa cultivar in China, as well as the polymorphic genes associated with agronomic traits. The expansion of gene families and increase of repetitive elements observed in Zhongmu-4 genome may contribute to its larger genome size compared to Medicago truncatula. The population structure analysis revealed the influence of geography on the genetic divergence of alfalfa. The findings of this study will facilitate genetic research and genomics-assisted breeding for alfalfa variety improvement.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2022)
Review
Food Science & Technology
Yang Hu, Stephanie M. Sjoberg, Chunpen (James) Chen, Amber L. Hauvermale, Craig F. Morris, Stephen R. Delwiche, Ashley E. Cannon, Camille M. Steber, Zhiwu Zhang
Summary: This review examines the application, limitations, and potential alternatives to the Hagberg-Perten falling number (FN) method used in the global wheat industry. The FN test indirectly detects the presence of alpha-amylase, which is responsible for starch degradation. Low FN/high alpha-amylase in wheat grains results in poor end-product quality and significant losses for various stakeholders. The FN method has limitations such as sampling variability, high cost, labor intensiveness, destructive nature, and inability to differentiate between different causes of low FN. Seeking faster, cheaper, and more accurate alternatives can improve breeding and avoid inadvertent mixing of high- and low-FN grain, thus preserving the value of wheat grain.
COMPREHENSIVE REVIEWS IN FOOD SCIENCE AND FOOD SAFETY
(2022)
Article
Agriculture, Dairy & Animal Science
Chun-Peng J. Chen, Gota Morota, Kiho Lee, Zhiwu Zhang, Hao Cheng
Summary: Precision livestock farming in the swine industry focuses on using computer vision technology to automate monitoring pig activity, but the performance is highly dependent on the quality of imagery features and requires intensive effort in labeling ground truths for training datasets.
JOURNAL OF ANIMAL SCIENCE
(2022)
Article
Agronomy
Chenggen Chu, Shichen Wang, Jackie C. Rudd, Amir M. H. Ibrahim, Qingwu Xue, Ravindra N. Devkota, Jason A. Baker, Shannon Baker, Bryan Simoneaux, Geraldine Opena, Haixiao Dong, Xiaoxiao Liu, Kirk E. Jessup, Ming-Shun Chen, Kele Hui, Richard Metz, Charles D. Johnson, Zhiwu S. Zhang, Shuyu Liu
Summary: Using genome-wide association studies and high throughput genotyping based on sequencing techniques can improve the accuracy of predicting and selecting new varieties using imbalanced historical yield data.
MOLECULAR BREEDING
(2022)
Article
Plant Sciences
William Wesley Crump, Cameron Peace, Zhiwu Zhang, Per McCord
Summary: This study aims to improve fruit cracking incidence and fruit firmness in sweet cherry through DNA-informed breeding. Four stable QTLs related to fruit cracking and firmness were identified, and the ancestral sources of functional SNP haplotypes were traced.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Multidisciplinary Sciences
Yao Zhou, Zhiyang Zhang, Zhigui Bao, Hongbo Li, Yaqing Lyu, Yanjun Zan, Yaoyao Wu, Lin Cheng, Yuhan Fang, Kun Wu, Jinzhe Zhang, Hongjun Lyu, Tao Lin, Qiang Gao, Surya Saha, Lukas Mueller, Zhangjun Fei, Thomas Stadler, Shizhong Xu, Zhiwu Zhang, Doug Speed, Sanwen Huang
Summary: Constructing a graph pangenome of tomato can improve the estimation of heritability for complex traits, identify more causal structural variants, and facilitate the identification of genetic factors underlying agronomically important traits. This study advances our understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding.
Article
Plant Sciences
Fan Zhang, Junmei Kang, Ruicai Long, Mingna Li, Yan Sun, Fei He, Xueqian Jiang, Changfu Yang, Xijiang Yang, Jie Kong, Yiwen Wang, Zhen Wang, Zhiwu Zhang, Qingchuan Yang
Summary: Fall dormancy (FD) is a crucial trait for alfalfa cultivar selection. We conducted genomic prediction of FD using machine learning methods and achieved high prediction accuracy.
HORTICULTURE RESEARCH
(2023)
Article
Plant Sciences
Dongdong Dang, Yuan Guan, Hongjian Zheng, Xuecai Zhang, Ao Zhang, Hui Wang, Yanye Ruan, Li Qin
Summary: Sweet corn and waxy corn have better taste and higher nutritional value than regular maize. A genome-wide association study (GWAS) and genomic prediction analysis were conducted on plant architecture traits in sweet corn and waxy corn. Significant differences were observed between sweet corn and waxy corn for plant height, ear height, and tassel branch number.
Article
Agriculture, Multidisciplinary
Zhou Tang, Meinan Wang, Michael Schirrmann, Xianran Li, Robert Brueggeman, Sindhuja Sankaran, Arron H. Carter, Michael O. Pumphrey, Yang Hu, Xianming Chen, Zhiwu Zhang
Summary: In this study, a neural network-based image classifier called RustNet was developed to efficiently monitor wheat fields for stripe rust. The model uses deep learning to process images and videos captured from affordable devices, enabling high-throughput pheno-typing for early detection of rust and improved control efficiency.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Genetics & Heredity
Yueting Jin, Dan Li, Meiling Liu, Zhenhai Cui, Daqiu Sun, Cong Li, Ao Zhang, Huiying Cao, Yanye Ruan
Summary: By performing a genome-wide association study, we identified 19 SNPs and 76 candidate genes associated with chlorophyll content. One SNP was co-localized in chlorophyll content and area under the chlorophyll content curve. These findings provide an experimental basis for discovering candidate genes of chlorophyll content and offer new insights for cultivating high-yield and excellent maize suitable for planting environment.
Article
Mycology
Y. P. Fu, Y. T. Dai, K. W. T. Chethana, Z. H. Li, L. Sun, C. T. Li, H. L. Yu, R. H. Yang, Q. Tan, D. P. Bao, Y. J. Deng, S. X. Wang, Y. F. Wang, F. H. Tian, L. L. Qi, L. L. Shu, P. S. Jia, L. C. Chen, M. Y. Chen, Q. X. Hu, H. Tan, T. T. Song, Z. W. Zhang, G. Bonito, G. Zervakis, S. J. Xiao, K. D. Hyde, Y. Li, X. H. Yuan
Summary: This study presents high-quality genomes, transcriptomes, and re-sequencing data of edible and medicinal mushrooms, and constructs an integrated omics database (MushDB) for a better understanding of mushroom domestication. Using multi-omics data, the researchers identified potential functional genes contributing to mushroom domestication, including genes involved in starch and sucrose metabolism and mitogen-activated protein kinase signaling pathway. The function of one key gene in low temperature adaptation and cultivation environment was validated using CRISPR/Cas9 system.
