Alpaca fiber growth is mediated by microRNA let-7b via down-regulation of target gene FGF5

Wang, T.; Zhang, Y.; Wang, H.D.; Shen, Yanqing; Liu, N.; Cao, Jun; Yu, Xiuju; Dong, Chunhong; He, Xu

doi:10.4238/2015.october.28.38

Cited by 7 publications

(6 citation statements)

References 35 publications

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“…To further investigate potential function of genes identified in the selection signature analysis, we first focused on a gene within our top ranking admixed locus (in the direction of llama to alpaca), comprising a set of candidate genes for adaptive introgression and artificial selection (ANTXR2/PRDM8/FGF5/C4orf22; see the "Results" section) [99,100] and in particular on FGF5. Since functional variation at FGF5 (also known as the angora gene) is known to correlate with short-or longwool phenotypes in sheep and goat [101,102], we examined sequence differences in this gene in short and longwool alpaca.…”

Section: Functional Analysis Of Target Genesmentioning

confidence: 99%

Genomic analysis of the domestication and post-Spanish conquest evolution of the llama and alpaca

Fan

Guang

et al. 2020

Genome Biol

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Background: Despite their regional economic importance and being increasingly reared globally, the origins and evolution of the llama and alpaca remain poorly understood. Here we report reference genomes for the llama, and for the guanaco and vicuña (their putative wild progenitors), compare these with the published alpaca genome, and resequence seven individuals of all four species to better understand domestication and introgression between the llama and alpaca. Results: Phylogenomic analysis confirms that the llama was domesticated from the guanaco and the alpaca from the vicuña. Introgression was much higher in the alpaca genome (36%) than the llama (5%) and could be dated close to the time of the Spanish conquest, approximately 500 years ago. Introgression patterns are at their most variable on the X-chromosome of the alpaca, featuring 53 genes known to have deleterious X-linked phenotypes in humans. Strong genome-wide introgression signatures include olfactory receptor complexes into both species, hypertension resistance into alpaca, and fleece/fiber traits into llama. Genomic signatures of domestication in the llama include male reproductive traits, while in alpaca feature fleece characteristics, olfaction-related and hypoxia adaptation traits. Expression analysis of the introgressed region that is syntenic to human HSA4q21, a gene cluster previously associated with hypertension in humans under hypoxic conditions, shows a previously undocumented role for PRDM8 downregulation as a potential transcriptional regulation mechanism, analogous to that previously reported at high altitude for hypoxia-inducible factor 1α. Conclusions: The unprecedented introgression signatures within both domestic camelid genomes may reflect post-conquest changes in agriculture and the breakdown of traditional management practices.

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Section: Functional Analysis Of Target Genesmentioning

confidence: 99%

Genomic analysis of the domestication and post-Spanish conquest evolution of the llama and alpaca

Fan

Guang

et al. 2020

Genome Biol

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“…Fibroblast growth factor (FGF) 5 and transforming growth factor β receptor type I (TGFβRI) have been previously identified as target genes of let-7b. Let-7b negatively regulates its target genes by binding to the 3' end of the mRNA (29,30). FGF5 serves an important role in the transformation process during the early-mid growth period of hair follicles.…”

Section: Discussionmentioning

confidence: 99%

“…FGF5 overexpression inhibits the growth of hair length. In the hair follicle cycle period, TGFβRI is highly expressed in the hair follicle root sheath, which aids in starting and maintaining the hair follicle catagen (29,30). EDA was predicted as a target gene of let-7b (6).…”

Section: Discussionmentioning

confidence: 99%

Let-7b regulates alpaca hair growth by downregulating ectodysplasin A

et al. 2018

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Hypohidrotic ectodermal dysplasia (HED), also known as anhidrotic ectodermal dysplasia, is characterized by the clinical manifestations of less sweat or no sweat, sparse or no hair, tooth agenesis and/or abnormal tooth morphology. The characteristics of alpaca ear hair differ from the back hair. The ectodysplasin A (EDA) signaling pathway has a regulatory effect on skin development and hair growth. The aim of the present study was to study the effects of EDA on alpaca hair growth by examining the mRNA and protein expression levels of EDA in alpaca ear and back skin by reverse transcription‑quantitative polymerase chain reaction and western blot analysis, respectively. Results indicated that EDA expression was higher in the ear skin compared with the back skin. The expression levels of let‑7b in the skin of healthy alpacas varies; the difference between let‑7b expression levels of the ear and back have been reported to be >2‑fold, suggesting a role for let‑7b in the development of adult alpaca skin and hair follicles. A dual‑luciferase reporter vector was constructed to verify the targeting relationship between microRNA let‑7b and EDA, and the results revealed that EDA was a target gene of let‑7b. Alpaca skin fibroblasts were transfected with a let‑7b eukaryotic expression vector to investigate the regulatory relationship between let‑7b and EDA. The expression of EDA was decreased in the transfected group; immunocytochemical results demonstrated that the EDA protein was abundantly expressed in the fibroblast cytoplasm. EDA protein expression was weaker in the transfected cells than in the untransfected cells. These results suggested that EDA may serve a role in alpaca hair growth and is probably a target gene of let‑7b; let‑7b downregulated EDA mRNA and protein expressions, which suggested that let‑7b may regulate alpaca hair growth. These conclusions suggested that let‑7b may be associated with HED.

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“…In this experiment, a substantial language model known as Alpaca-LoRA-7B will be employed, which pretrained by Wang [4] . This model is a reproduction of the Stanford Alpaca results, utilizing OpenAI's ChatGPT data for fine-tuning 5 .…”

Section: Pre-trained Modelmentioning

confidence: 99%

Text sentiment analysis based on LLaMA models

2024

International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023)

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Large language models (LLMs) are increasingly vital across diverse applications. This study delves into the utilization of the Alpaca language model, a cost-effective and high-performing variant, for sentiment analysis. The research systematically evaluates the Alpaca model's performance across a range of datasets, with an emphasis on its ability to excel in sentiment analysis tasks across varying domains. The study sheds light on the practical utility of the Alpaca model in sentiment analysis applications, providing insights into its adaptability and effectiveness. Furthermore, this investigation extends its inquiry into the realm of consumer-grade graphics, examining how large language models perform in sentiment analysis within this context. Notably, the study uncovers that these models demonstrate proficiency in nuanced tasks with limited answer options. Moreover, the research underscores the potential for improved accuracy through the utilization of larger training datasets. In conclusion, this research showcases the Alpaca model's efficacy in sentiment analysis and advances our understanding of LLMs capabilities in this field. It underscores their potential to enhance context-aware and precise sentiment analysis solutions, offering valuable contributions to the broader landscape of natural language processing.

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Alpaca fiber growth is mediated by microRNA let-7b via down-regulation of target gene FGF5

Cited by 7 publications

References 35 publications

Genomic analysis of the domestication and post-Spanish conquest evolution of the llama and alpaca

Genomic analysis of the domestication and post-Spanish conquest evolution of the llama and alpaca

Let-7b regulates alpaca hair growth by downregulating ectodysplasin A

Text sentiment analysis based on LLaMA models

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