Transcriptome analysis of genetic mechanism of growth curve inflection point using a pig model

Animal growth curves play an important role for animal breeders to optimize feeding and management strategies (De Lange et al., 2001 [1]; Brossard et al., 2009 [2]; Strathe et al., 2010 [3]). However, the genetic mechanism of the phenotypic difference between the inflection point and noninflection p...

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Main Authors: Linyuan Shen, Shunhua Zhang, Li Zhu
Format: Article
Language:English
Published: Elsevier 2015-12-01
Series:Genomics Data
Online Access:http://www.sciencedirect.com/science/article/pii/S2213596015300192
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spelling doaj-7170962679c64bad9130418e1f1470142020-11-25T02:08:30ZengElsevierGenomics Data2213-59602015-12-016C14915010.1016/j.gdata.2015.08.024Transcriptome analysis of genetic mechanism of growth curve inflection point using a pig modelLinyuan ShenShunhua ZhangLi ZhuAnimal growth curves play an important role for animal breeders to optimize feeding and management strategies (De Lange et al., 2001 [1]; Brossard et al., 2009 [2]; Strathe et al., 2010 [3]). However, the genetic mechanism of the phenotypic difference between the inflection point and noninflection points of the growth curve remains unclear. Here, we report the differentially expressed gene pattern in pig longissimus dorsi among three typical time points of the growth curve, inflection point (IP), before inflection point (BIP) and after inflection point (AIP). The whole genome RNA-seq data was deposited at GenBank under the accession number PRJNA2284587. The RNA-seq libraries generated 117 million reads of 5.89 gigabases in length. Totals of 21,331, 20,996 and 20,139 expressed transcripts were identified in IP, UIP and AIP, respectively. Furthermore, we identified 757 differentially expressed genes (DEGs) between IP and UIP, and 271 DEGs between AIP and IP. Function enrichment analysis of DEGs found that the highly expressed genes in IP were mainly enriched in energy metabolism, global transcriptional activity and bone development intensity. This study contributes to reveal the genetic mechanism of growth curve inflection point.http://www.sciencedirect.com/science/article/pii/S2213596015300192
collection DOAJ
language English
format Article
sources DOAJ
author Linyuan Shen
Shunhua Zhang
Li Zhu
spellingShingle Linyuan Shen
Shunhua Zhang
Li Zhu
Transcriptome analysis of genetic mechanism of growth curve inflection point using a pig model
Genomics Data
author_facet Linyuan Shen
Shunhua Zhang
Li Zhu
author_sort Linyuan Shen
title Transcriptome analysis of genetic mechanism of growth curve inflection point using a pig model
title_short Transcriptome analysis of genetic mechanism of growth curve inflection point using a pig model
title_full Transcriptome analysis of genetic mechanism of growth curve inflection point using a pig model
title_fullStr Transcriptome analysis of genetic mechanism of growth curve inflection point using a pig model
title_full_unstemmed Transcriptome analysis of genetic mechanism of growth curve inflection point using a pig model
title_sort transcriptome analysis of genetic mechanism of growth curve inflection point using a pig model
publisher Elsevier
series Genomics Data
issn 2213-5960
publishDate 2015-12-01
description Animal growth curves play an important role for animal breeders to optimize feeding and management strategies (De Lange et al., 2001 [1]; Brossard et al., 2009 [2]; Strathe et al., 2010 [3]). However, the genetic mechanism of the phenotypic difference between the inflection point and noninflection points of the growth curve remains unclear. Here, we report the differentially expressed gene pattern in pig longissimus dorsi among three typical time points of the growth curve, inflection point (IP), before inflection point (BIP) and after inflection point (AIP). The whole genome RNA-seq data was deposited at GenBank under the accession number PRJNA2284587. The RNA-seq libraries generated 117 million reads of 5.89 gigabases in length. Totals of 21,331, 20,996 and 20,139 expressed transcripts were identified in IP, UIP and AIP, respectively. Furthermore, we identified 757 differentially expressed genes (DEGs) between IP and UIP, and 271 DEGs between AIP and IP. Function enrichment analysis of DEGs found that the highly expressed genes in IP were mainly enriched in energy metabolism, global transcriptional activity and bone development intensity. This study contributes to reveal the genetic mechanism of growth curve inflection point.
url http://www.sciencedirect.com/science/article/pii/S2213596015300192
work_keys_str_mv AT linyuanshen transcriptomeanalysisofgeneticmechanismofgrowthcurveinflectionpointusingapigmodel
AT shunhuazhang transcriptomeanalysisofgeneticmechanismofgrowthcurveinflectionpointusingapigmodel
AT lizhu transcriptomeanalysisofgeneticmechanismofgrowthcurveinflectionpointusingapigmodel
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