PEDE (Pig EST Data Explorer) has been expanded into Pig Expression Data Explorer, including 10 147 porcine full-length cDNA sequences

Uenishi, Hirohide; Eguchi-Ogawa, Tomoko; Shinkai, Hiroki; Okumura, Naohiko; Suzuki, Kohei; Toki, Daisuke; Hamasima, Noriyuki; Awata, Takashi

doi:10.1093/nar/gkl954

Cited by 62 publications

(45 citation statements)

References 14 publications

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“…In Table 2 we summarize the current status of development of EST projections for the major farm animal species, the largest being the chicken with almost 350,000 ESTs. Many databases and tools based on the web have been set up to meet the EST annotation and data management requirements of multiple highthroughput EST sequencing projects for cattle (Kumar et al 2004) sheep (Caprera et al 2007), chicken (Abdrakhmanov et al 2000;Chen et al 2005;Carre et al 2006;Park et al 2006) and pig (Kumar et al 2004;Chen et al 2005;Uenishi et al 2007). They have become an important resource for livestock genetic research.…”

Section: Est Sequencingmentioning

confidence: 99%

Advanced technologies for genomic analysis in farm animals and its application for QTL mapping

Gao

Feng

et al. 2008

Genetica

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Rapid progress in farm animal breeding has been made in the last few decades. Advanced technologies for genomic analysis in molecular genetics have led to the identification of genes or markers associated with genes that affect economic traits. Molecular markers, large-insert libraries and RH panels have been used to build the genetic linkage maps, physical maps and comparative maps in different farm animals. Moreover, EST sequencing, genome sequencing and SNPs maps are helping us to understand how genomes function in various organisms and further areas will be studied by DNA microarray technologies and proteomics methods. Because most economically important traits in farm animals are controlled by multiple genes and the environment, the main goal of genome research in farm animals is to map and characterize genes determining QTL. There are two main strategies to identify trait loci, candidate gene association tests and genome scan approaches. In recent years, some new concepts, such as RNAi, miRNA and eQTL, have been introduced into farm animal research, especially for QTL mapping and finding QTN. Several genes that influence important traits have already been identified or are close to being identified, and some of them have been applied in farm animal breeding programs by marker-assisted selection.

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Section: Est Sequencingmentioning

confidence: 99%

Advanced technologies for genomic analysis in farm animals and its application for QTL mapping

Gao

Feng

et al. 2008

Genetica

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“…Regarding technological aspects related to drycured high-quality products and the meat industry, an adequate layer of fat is required for the seasoning process of PDO products, such as dry-cured hams (Bosi & Russo 2004;Candek-Potokar & Skrlep 2012). During the last decade, pig transcriptomic data have been obtained initially by expressed sequence tag sequencing (Mikawa et al 2004;Uenishi et al 2004Uenishi et al , 2007Chen et al 2006;Gorodkin et al 2007) and microarrays (Hornshøj et al 2007;Ferraz et al 2008;Moon et al 2009), which allowed the comparison of gene expression levels in several pig tissues. More recently, the RNA-seq approach was used to compare the transcription profile of different pig fat tissues or different pig breeds (Chen et al 2011;Li et al 2012;Corominas et al 2013;Jiang et al 2013;Zhou et al 2013;Sodhi et al, 2014;Toedebusch et al 2014;Wang et al 2014).…”

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confidence: 99%

Transcriptional profiling of subcutaneous adipose tissue in Italian Large White pigs divergent for backfat thickness

Zambonelli¹,

Gaffo

Zappaterra³

et al. 2016

Animal Genetics

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Fat deposition is a widely studied trait in pigs because of its implications with animal growth efficiency, technological and nutritional characteristics of meat products, but the global framework of the biological and molecular processes regulating fat deposition in pigs is still incomplete. This study describes the backfat tissue transcription profile in Italian Large White pigs and reports genes differentially expressed between fat and lean animals according to RNA-seq data. The backfat transcription profile was characterised by the expression of 23 483 genes, of which 54.1% were represented by known genes. Of 63 418 expressed transcripts, about 80% were non-previously annotated isoforms. By comparing the expression level of fat vs. lean pigs, we detected 86 robust differentially expressed transcripts, 72 more highly expressed (e.g. ACP5, BCL2A1, CCR1, CD163, CD1A, EGR2, ENPP1, GPNMB, INHBB, LYZ, MSR1, OLR1, PIK3AP1, PLIN2, SPP1, SLC11A1, STC1) and 14 lower expressed (e.g. ADSSL1, CDO1, DNAJB1, HSPA1A, HSPA1B, HSPA2, HSPB8, IGFBP5, OLFML3) in fat pigs. The main functional categories enriched in differentially expressed genes were immune system process, response to stimulus, cell activation and skeletal system development, for the overexpressed genes, and unfolded protein binding and stress response, for the underexpressed genes, which included five heat shock proteins. Adipose tissue alterations and impaired stress response are linked to inflammation and, in turn, to adipose tissue secretory activity, similar to what is observed in human obesity. Our results provide the opportunity to identify biomarkers of carcass fat traits to improve the pig production chain and to identify genetic factors that regulate the observed differential expression.

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“…The ΔlsgB mutant exhibited significantly attenuated invasion of both PIEC and PK15 cells; however, unexpectedly; we observed a prominent and significant increase in the adhesion of the ΔlsgB mutant to both cell types. Deletion of lsgB led to the exposure of the penultimate galactose of LOS; therefore, we tested whether these cell types have differences in the expression of the galactose binding domains or receptors, such as the galactose binding lectin domain (GalR) of the adhesion G protein-coupled receptor [44,45], but the results did not suggest any difference on the expression of GalR1 or GalR2 in response to these strains. However notably, our adhesion inhibition assays showed that addition of galactose significantly blocked adhesion of the ΔlsgB mutant in a dose-dependent manner, while adhesion of the wild-type strain was completely unaffected, revealing that it is the terminal galactose residue, which is exposed after the removal of sialic acid by lsgB deletion (see Figure 3(d)), that mediates the high level of adhesion.…”

Section: Discussionmentioning

confidence: 99%

Haemophilus parasuis α-2,3-sialyltransferase-mediated lipooligosaccharide sialylation contributes to bacterial pathogenicity

et al. 2018

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Bacterial lipooligosaccharide (LOS) is an important virulence-associated factor, and its sialylation largely confers its ability to mediate cell adhesion, invasion, inflammation, and immune evasion. Here, we investigated the function of the Haemophilus parasuis α-2,3-sialyltransferase gene, lsgB, which determines the terminal sialylation of LOS, by generating a lsgB deletion mutant as well as a complementation strain. Our data indicate a direct effect of lsgB on LOS sialylation and reveal important roles of lsgB in promoting the pathogenicity of H. parasuis, including adhesion to and invasion of porcine cells in vitro, bacterial load and survival in vivo, as well as a contribution to serum resistance. These observations highlight the function of lsgB in mediating LOS sialylation and more importantly its role in H. parasuis infection. These findings provide a more profound understanding of the pathogenic mechanism of this disease-causing bacterium.

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PEDE (Pig EST Data Explorer) has been expanded into Pig Expression Data Explorer, including 10 147 porcine full-length cDNA sequences

Cited by 62 publications

References 14 publications

Advanced technologies for genomic analysis in farm animals and its application for QTL mapping

Advanced technologies for genomic analysis in farm animals and its application for QTL mapping

Transcriptional profiling of subcutaneous adipose tissue in Italian Large White pigs divergent for backfat thickness

Haemophilus parasuis α-2,3-sialyltransferase-mediated lipooligosaccharide sialylation contributes to bacterial pathogenicity

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