Goodness-of-fit testing in growth curve models: A general approach based on finite differences

Mandal, Abhijit; Huang, Wen-Tao; Bhandari, Subir Kumar; Basu, Ayanendranath

doi:10.1016/j.csda.2010.09.003

Cited by 10 publications

(9 citation statements)

References 14 publications

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“…Three sigmoid growth functions were involved in our study. The equation of logistic growth curve model is W t = A/(1 + B e − kt )[ 17 ]. The second Gompertz growth curve model is defined by the equation W t = A e − Be − kt [ 17 ] .…”

Section: Methodsmentioning

confidence: 99%

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Transcriptome Analysis of Liangshan Pig Muscle Development at the Growth Curve Inflection Point and Asymptotic Stages Using Digital Gene Expression Profiling

Shen

Luo

et al. 2015

PLoS ONE

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Animal growth curves can provide essential information for animal breeders to optimize feeding and management strategies. However, the genetic mechanism underlying the phenotypic differentiation between the inflection point and asymptotic stages of the growth curve is not well characterized. Here, we employed Liangshan pigs in stages of growth at the inflection point (under inflection point: UIP) and the two asymptotic stages (before the inflection point: BIP, after the inflection point: AIP) as models to survey global gene expression in the longissimus dorsi muscle using digital gene expression (DGE) tag profiling. We found Liangshan pigs reached maximum growth rate (UIP) at 163.6 days of age and a weight of 134.6 kg. The DGE libraries generated 117 million reads of 5.89 gigabases in length. 21,331, 20,996 and 20,139 expressed transcripts were identified BIP, UIP and AIP, respectively. Among them, we identified 757 differentially expressed genes (DEGs) between BIP and UIP, and 271 DEGs between AIP and UIP. An enrichment analysis of DEGs proved the immune system was strengthened in the AIP stage. Energy metabolism rate, global transcriptional activity and bone development intensity were highest UIP. Meat from Liangshan pigs had the highest intramuscular fat content and most favorable fatty acid composition in the AIP. Three hundred eighty (27.70%) specific expression genes were highly enriched in QTL regions for growth and meat quality traits. This study completed a comprehensive analysis of diverse genetic mechanisms underlying the inflection point and asymptotic stages of growth. Our findings will serve as an important resource in the understanding of animal growth and development in indigenous pig breeds.

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Section: Methodsmentioning

confidence: 99%

“…The equation of logistic growth curve model is W t = A/(1 + B e − kt )[ 17 ]. The second Gompertz growth curve model is defined by the equation W t = A e − Be − kt [ 17 ] . The third growth curve model is the Von Bertalanffy[ 18 ], which is defined by the equation W t = A × (1 − B e − kt ) 3 .…”

Section: Methodsmentioning

confidence: 99%

Transcriptome Analysis of Liangshan Pig Muscle Development at the Growth Curve Inflection Point and Asymptotic Stages Using Digital Gene Expression Profiling

Shen

Luo

et al. 2015

PLoS ONE

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“…Three sigmoid growth functions (i.e. Logistic, Gompertz and Von Bertalanffy growth curves) were involved and nineteen time points of body weight data was measured to t the growth curve according to the methods previously described [15][16][17]. Brie y, the formulas of three growth curve models are listed as follows: y represents body weight; t represents the age of pigs.…”

Section: Growth Curve Modelmentioning

confidence: 99%

Profiling and Functional Analysis of Long Noncoding RNAs and mRNAs during Porcine Skeletal Muscle Development

Tan¹,

Gan

Shen

et al. 2020

Preprint

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BackgroundGene transcripts or mRNAs and long noncoding RNAs (lncRNAs) are differentially expressed during porcine skeletal muscle development. However, only a few studies have been conducted on skeletal muscle transcriptome in pigs based on timepoints according to the growth curve for porcine. Here, we investigated gene expression in Qingyu pigs at three different growth stages: of the inflection point with the maximum growth rate (MGI), inflection point of gradual increase stage to rapid increasing stage (GRI) and inflection point of rapid increasing stage to slowly increasing stage (RSI). Subsequently, we explored gene expression profiles during muscle development at the MGI, GRI and RSI stages by Ribo-Zero RNA sequencing. ResultsQingyu pigs reached the MGI, GRI and RSI stages at 156.40, 23.82 and 288.97 days of age with 51.73, 3.14 and 107.03 kg body weight, respectively. A total of 14,530 mRNAs and 11,970 lncRNAs were identified at the three stages, and 645, 323 differentially expressed genes (DEGs) and 696, 760 differentially expressed lncRNAs (DELs) were identified in the GRI vs. MGI, RSI vs. MGI comparisons. Functional enrichment analysis revealed that genes involved in immune system development and energy metabolism (mainly relate to amino acid, carbohydrate and lipid) were enriched at the GRI and MGI stages, respectively, whereas genes involved in energy and lipid metabolism were enriched at the RSI stage. We further characterized G1430, an abundant lncRNA. The full-length sequence (316 nt) of lncRNA G1430 was determined by rapid amplification of cDNA ends (RACE). Subcellular distribution analysis by quantitative real-time PCR (qRT-PCR) revealed that G1430 is a cytoplasmic lncRNA. Binding site prediction and dual luciferase assay showed that lncRNA G1430 directly binds to microRNA 133a (miR-133a). ConclusionThese findings indicate lncRNAs and a certain lncRNA G1430 involved in the regulatory mechanism during pig muscle development. Our findings provide the basis for further investigation of the regulatory mechanisms and molecular genetics of muscle development in pigs.

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“…For bacteria, the growth rate shows a lag phase that is followed by an exponential phase, and finally it shows a decreasing growth rate down to zero resulting in a maximum value of the number of organisms. A growth model with three parameters can describe this growth curve [12,13]: the maximum specific growth rate max μ which is defined as the tangent in the inflection point; the lag time λ , which is defined as the t-axis intercept of this tangent in the inflection point, and the asymptote A, which is the maximal value reached. The three parameters are determined from growth data by describing them by the Gompertz model.…”

Section: Growth Modelmentioning

confidence: 99%

A novel measurement method of microorganism growth by tunable diode laser-absorption spectroscopy

et al. 2015

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The objective of this work was to attain essential parameters by using a Gompertz model that employed a new approach of wavelength modulation spectroscopy (WMS) to describe the microorganism growth. The measurement method of WMS introduces noninvasive technique instead of complicated invasive microorganism operation analysis and quickly obtains the accurate real-time measurement results. By using the WMS measurement, the specific growth curve of microorganism growth clearly displayed every three minute, which has characteristics of high sensitivity, high spectral resolution, fast time response and overcomes the randomness and error operation of traditional analysis methods. The measurement value of BF and AF in the range of 1.008 to 1.043 and the lower MSE showed that Gompertz model can fit the data well and be capable of describing bacteria growth rate and lag time. The results of experiment data suggested that the specific growth rate of microorganism depends on the temperature. With the increase of temperature ranging from 25 o C to 42 o C , the lag time of bacteria growth has been shortened. And the suitable temperature of bacteria growth is about 37 o C . Judging from the growth rate of microorganisms, we can identify the microbial species, not only to improve the precision and efficiency, but also to provides a rapidly sensitive way for microbial detection. The lag time of microorganism growth also provides a great application prospect for shelf life of the food safety.

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Goodness-of-fit testing in growth curve models: A general approach based on finite differences

Cited by 10 publications

References 14 publications

Transcriptome Analysis of Liangshan Pig Muscle Development at the Growth Curve Inflection Point and Asymptotic Stages Using Digital Gene Expression Profiling

Transcriptome Analysis of Liangshan Pig Muscle Development at the Growth Curve Inflection Point and Asymptotic Stages Using Digital Gene Expression Profiling

Profiling and Functional Analysis of Long Noncoding RNAs and mRNAs during Porcine Skeletal Muscle Development

A novel measurement method of microorganism growth by tunable diode laser-absorption spectroscopy

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