Genetic insights into the crude protein and fiber content of ramie leaves

Li, Yong; Zeng, Zheng; Yang, Xiai; Zhu, Siyuan; Liu, Touming; Wang, Yanzhou

doi:10.3389/fpls.2022.969820

Cited by 4 publications

(3 citation statements)

References 35 publications

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“…Recent research has illuminated the genetic framework that determine the levels of crude protein and fiber content in ramie (Boehmeria nivea (L.) Gaud. ), identifying the QTLs and candidate genes that could be utilized to improve the forage quality via markerassisted selection strategies [15]. Additionally, the genetic loci associated with crude protein content and fiber composition were identified in alfalfa, highlighting the complex genetic mechanisms that influence these traits that are integral to forage quality [16].…”

Section: Quantitative Trait Loci (Qtl) Mappingmentioning

confidence: 99%

Advances in Molecular Breeding of Forage Crops: Technologies, Applications and Prospects

Chen

2024

Agriculture

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Molecular breeding has revolutionized the improvement of forage crops by offering precise tools to enhance the yield, quality, and environmental resilience. This review provides a comprehensive overview of the current technologies, applications, and future directions in the field of forage crop molecular breeding. Technological advancements in the field, including Quantitative Trait Loci (QTL) mapping, Genome-Wide Association Studies (GWASs), genomic selection (GS), and genome-editing tools such as CRISPR-Cas9, have significantly advanced the identification and incorporation of beneficial traits into forage species. These approaches have dramatically shortened the breeding cycles and increased the efficiency of developing cultivars with improved yield, disease resistance, stress tolerance, and nutritional profiles. The implementation of these technologies has led to notable successes, as demonstrated by case studies on various forage crops, showcasing enhanced forage quality and adaptability to challenging environmental conditions. Furthermore, the integration of high-throughput phenotyping with advanced bioinformatics tools has streamlined the management of large-scale genomic data, facilitating more precise selection and breeding decisions. Looking ahead, this review explores the potential of emerging technologies, such as the application of artificial intelligence in predictive breeding, along with the associated ethical and regulatory considerations. While we stand to gain benefit from these innovations, the future of molecular breeding in forage crops must also confront the challenges posed by climate change and the imperative of sustainable agricultural practices. This review concludes by emphasizing the transformative impact of molecular breeding on the improvement of forage crop and the critical need for ongoing research and collaboration to fully realize its potential.

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Section: Quantitative Trait Loci (Qtl) Mappingmentioning

confidence: 99%

Advances in Molecular Breeding of Forage Crops: Technologies, Applications and Prospects

Chen

2024

Agriculture

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“…ISSN 2616-5880 Vol. 4) It is assumed that the data are representative and accurately reflect the relationship between surface weathering and weathering.…”

Section: Assumptionsmentioning

confidence: 99%

“…Based on the data and requirements, Spielman's correlation analysis [3], chi-square test, descriptive statistics [4], and control variables were used in this question. In this paper, the type, decoration, and color of glass are categorical variables, so Spearman's correlation analysis [5] and chi-square test were used to analyze the relationship; when studying the type of glass, the variation pattern of other chemical components should be studied by using control variables and descriptive statistics.…”

Section: Model Preparationmentioning

confidence: 99%

Prediction of the chemical composition content of ancient glass artifacts before weathering

2023

AJMC

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In this paper, the surface weathering, type, decoration, color and content of each chemical component of glass artifacts were studied and analyzed, and a K-means clustering model was established, using Spearman correlation analysis, chi-square test, and. It was solved to classify the glass types and analyze the change pattern of chemical composition of glass artifacts, and a better fitting effect was obtained. This paper characterized the problem as a prediction class, firstly, assigned values to four categorical variables: surface weathering, type, decoration and color of glass artifacts, and then used spss to perform Spearman correlation and chi-square test analysis to pre-process the data and eliminate invalid data. Then, it used descriptive statistical analysis to find that most of the chemical components of high potassium glass showed a decreasing trend after weathering, and most of the chemical components of lead-barium glass showed an increasing trend after weathering; finally, used Matlab matrix to derive a linear mapping relationship based on the changes of chemical components before and after weathering, and finally predicted the chemical components of glass artifacts before weathering.

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Genomic variation and candidate genes dissect quality and yield traits in Boehmeria nivea (L.) Gaudich

Shi,

Huang,

Chen

et al. 2024

Cellulose

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Ramie is a perennial and traditional Chinese cellulose ber crop and accessible for harvesting three times within one year in some region of China. Besides, ramie can also be used in medicine, feed and material industries. The genetic basis over quality-and yield-related traits in ramie is poorly understood and insu cient owing to the lack of assessment in different environments. A core collection comprising 319 accessions with 25.31-fold coverage resequencing depth for evaluating population structure and genomic variation. Combined with linkage mapping method detecting favorable variation and candidate genes associated with yield and quality related traits.We obtained approximately 3.49 million high quality single nucleotide polymorphisms (SNPs), 2,089,798 insertions and deletions (Indels) and 88,087 structure variation (SV) in whole genome. None distinct population structure was found in ramie population based on geographical distribution. Some loci and genes were detected to relate to three yield traits and ber neness. A pleiotropic genes encoding NAC domain containing protein (BnNAC29), was identi ed signi cantly correlated with stem diameter and bark thickness. The variation of large-fragment deletion and indels in two candidate genes may responsible for the two traits. Moreover, we also detected pleiotropic loci and candidate genes for plant height and stem diameter. Our study provides new insights into the genetic architecture of ramie yield and ber quality. The identi ed loci and candidate genes are expected to facilitate genomics-based breeding for higher ber yield and quality improvement in ramie.

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Genetic insights into the crude protein and fiber content of ramie leaves

Cited by 4 publications

References 35 publications

Advances in Molecular Breeding of Forage Crops: Technologies, Applications and Prospects

Advances in Molecular Breeding of Forage Crops: Technologies, Applications and Prospects

Prediction of the chemical composition content of ancient glass artifacts before weathering

Genomic variation and candidate genes dissect quality and yield traits in Boehmeria nivea (L.) Gaudich

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