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BMC Genomics

Open Access

The porcine translational research database: a manually curated, genomics and proteomics-based research resource

BMC Genomics201718:643

https://doi.org/10.1186/s12864-017-4009-7

Received: 12 October 2016

Accepted: 2 August 2017

Published: 22 August 2017

Abstract

Background

The use of swine in biomedical research has increased dramatically in the last decade. Diverse genomic- and proteomic databases have been developed to facilitate research using human and rodent models. Current porcine gene databases, however, lack the robust annotation to study pig models that are relevant to human studies and for comparative evaluation with rodent models. Furthermore, they contain a significant number of errors due to their primary reliance on machine-based annotation. To address these deficiencies, a comprehensive literature-based survey was conducted to identify certain selected genes that have demonstrated function in humans, mice or pigs.

Results

The process identified 13,054 candidate human, bovine, mouse or rat genes/proteins used to select potential porcine homologs by searching multiple online sources of porcine gene information. The data in the Porcine Translational Research Database ((http://www.ars.usda.gov/Services/docs.htm?docid=6065) is supported by >5800 references, and contains 65 data fields for each entry, including >9700 full length (5′ and 3′) unambiguous pig sequences, >2400 real time PCR assays and reactivity information on >1700 antibodies. It also contains gene and/or protein expression data for >2200 genes and identifies and corrects 8187 errors (gene duplications artifacts, mis-assemblies, mis-annotations, and incorrect species assignments) for 5337 porcine genes.

Conclusions

This database is the largest manually curated database for any single veterinary species and is unique among porcine gene databases in regard to linking gene expression to gene function, identifying related gene pathways, and connecting data with other porcine gene databases. This database provides the first comprehensive description of three major Super-families or functionally related groups of proteins (Cluster of Differentiation (CD) Marker genes, Solute Carrier Superfamily, ATP binding Cassette Superfamily), and a comparative description of porcine microRNAs.

Keywords

PorcineDatabaseComparative genomics

Background

Swine are an important models for human anatomy, nutrition, metabolism and immunology [13]. Their organs are anatomically and histologically similar to humans as are their sensory innervation and blood supply [4]. Pigs are naturally susceptible to infection with organisms that are closely related or identical to those species infecting humans including helminths (Ascaris, Taenia, Trichuris, Trichinella, Shistosoma, Strongyloides), bacteria (Campylobacter, Chlamydia, Eschericia coli, Helicobacter, Neisseria, Mycoplasma, Salmonella), protozoans (Toxoplasma) and viri (Coronavirus, Hepatitis E, Influenza, Nipah, Reovirus, Rotavirus) [2, 5, 6]. The last 10 years has seen a boon in the development of genetically modified pig as models for human cardiovascular and lung disease, neurodegenerative and musculoskeletal disorders [7, 8] and cancer [9]. There is also a robust effort to develop pigs as sources for organs and tissues for human xenotransplantation [10].

Despite these potential strengths as a model, the lack of an annotated database for porcine gene and protein expression data is a limiting factor for translating findings in one species to another. Multiple online databases exist for the storage and retrieval of diverse bovine, rodent or human biomedical data [1119]. Other databases exist for Zebrafish (ZFIN, [20]), C. elegans (WormBase, [21]), and Drosophila melanogaster (Flybase, [22]). Databases that encompass multispecies analysis such as Homologene and/or that rely on manual annotation such as InnateDb [23] include bovine but not porcine genes. Several porcine genome companion databases exist; however they lack robust manual annotation and are somewhat limited in scope or are infrequently updated [1619]. Agbase, a large, multispecies functional analysis database allows the user to search 51,489 porcine genes based on 12 criteria including gene and protein names (UniProt) and Gene Ontology (GO) annotations. Furthermore, databases can contain a significant number of errors due to their primary reliance on machine-based annotation [24]. For example, the SUS-BAR database [19] is designed to identify protein orthologs based upon data that includes annotations from the machine-annotated NCBI genome. NCBI has recently begun to include GO annotations into curated entries for non-human and rodent species but most of these are indirect and often based on observations made in other species. As swine are an important model for comparative human studies, there is a critical need to have a centralized, manually-curated source of information for biomedical research. To address these needs, we created the Porcine Translational Research Database.

Construction and Content

To generate content of immunological relevance, broad-based literature searches were conducted using the following terms: apoptosis, B cell development or activation, CD markers, chemokines, chemokine receptors, cytokines, cytokine receptors, dendritic cells, type 1 IFN induced genes, inflammation, nuclear factor kappa-light-chain-enhancer of activated B cells (NFκ-B) signaling pathway, toll receptor signaling pathway, T cell development or activation, Th1 cell development and Th2 cell development. In addition, immunologically related genes associated with the susceptibility to or pathology of allergy, asthma, arthritis, atherosclerosis and inflammation were included. In addition, The Gene Ontology consortium’s community annotation wikis for immunology, cardiovascular disease and muscle biology were searched (http://wiki.geneontology.org/index.php/Main_Page). The Jackson Laboratory database of knockout mouse phenotypes was searched for genes leading to defects in immune or metabolic phenotypes when over or under expressed. These genes include the vast majority of genes that are related to immunity and inflammation [2, 3, 25, 26]. For additional metabolically related genes, genes involved in the transport or metabolism of macronutrients, trace vitamins and minerals were searched. Other genes, associated with the susceptibility to or pathology of atherosclerosis, diabetes, and obesity, were identified. This process identified 13,054 candidate human, bovine, mouse or rat genes/proteins of interest used to select potential porcine orthologs by searching various online sources of porcine gene information. One to one orthology of protein coding genes were determined by protein structure similarity (best reciprocal BLAST hits) and the presence of a corresponding gene in the syntenic region of the human and or mouse genome. No 1:1 orthology could be established for members of some gene families including the Leukocyte Immunoglobulin-like Receptor (LILR) Killer Cell immunoglobulin-like Receptor (KIR), Carcinoembryonic antigen-related cell adhesion molecule (CEACAM) and Cytochrome P450 superfamilies. One to one porcine orthologs of human genes utilize the approved HGNC Name according to the International Society for Animal Genetics (ISAG) publishing guidelines. We defined pseudogenes by the criteria used by Ensembl and ENSCODE; namely the presence of one or more stop codons in the open reading frame that disrupt the protein structure, and (usually) a lack of intron structure at the genome level [27]. Pseudogenes are further classified into Processed, Duplicated, Unitary or Polymorphic categories [27].

Sequence generation

Genbank (non-redundant, expressed sequences tag, high throughput genomic sequence, trace archive databases and whole genome shotgun contigs databases) was searched by discontiguous Megablast using default settings (word size = 11), using reference sequence accession numbers to human, bovine, mouse or rat genes/proteins of interest. A similar search was conducted in the following databases using the human or bovine reference sequence; NIH Intramural Sequencing Center (NISC) Comparative Vertebrate Sequencing Project [28]; National Center for Biotechnology Information (NCBI), Sus scrofa Genome Assembly releases 102 to 105 and Ensembl v10.2 releases 83 to 89. For genes that were determined to be missing from build 10.2 (Additional file 1) (and for the mis-assembled or duplicated gene artifacts (Additional file 1), we also constructed templates from de novo assemblies derived from Illumina 80 bp reads of the pig alveolar macrophage transcriptome (Dawson, unpublished results) using the de novo assembly algorithm of CLC Genomics Workbench using word size of 20 and a bubble size of 50. When necessary, predicted templates (from bovine or human sequences) were supplemented with porcine expressed sequence tag (EST) assemblies, single ESTs and portions of the published Tibetan (Bioproject # PRJNA291130), Wuzhishan (Bioproject # PRJNA144099), Goettingen (Bioproject # PRJNA291011) [29], Jinhua, Meishan, Bamei, Large White, Berkshire, Hampshire, Pietrain, Landrace, Rongshang and Duroc (Bioproject # PRJNA309108) porcine genomes [30]. ESTs were assembled using CAP3 (http://doua.prabi.fr/software/cap3). RNASeq reads were then mapped to these predicted templates in order to derive the full-length consensus sequence (unambiguous 6X coverage) using CLC Genome Workbench 7.0 (QIAGEN Bioinformatics, Redwood City CA). The following settings were used. Mismatch cost =2, Insertion cost = 3, Deletion cost = 3, similarity fraction = 0.95, length fraction = 0.95. Nucleotide sequences were translated using the ExPASy translate tool (http://web.expasy.org/translate/). A total of 1279 of these sequences have been deposited to the transcriptome shotgun assembly sequence database under Bioproject PRJNA80971 and the short read archive under project SRP013743). In silico-derived full-length RNA sequences are provided for an additional 3391 genes. This process/pipeline is summarized in Fig. 1. A summary of these sequences is provided in Table 1.
Fig. 1

Porcine Translation Research Database (PTR) Construction Flowchart

Table 1

Current Database Statistics (07/12/2017)

Parameter

Metric

Number of Entries

13,054

Number of Full-Length RNA Sequences (5′ and 3′ Representation)

9720

  Number of Genes with Full-Length RNA Sequences

9165

  Dawson Lab Full Length Submissions to Genbank

1351

  Percent of Genome in Database with RNA Sequences

41.7

  Number of Protein Coding Genes with Full-Length RNA Sequences

7805

 Number of Protein Coding Gene Splice Variants

667

 Number of Genes in Database with Full-Length Protein Sequences

8099

  Percent of Genome in Database with Protein Sequences

42.6

  Percent of Proteins in Database with Full-Length RNA Sequences

0.964

 Number of Unigene Numbers Assigned

10,232

  Unigene/Gene

1.45

  Percentage of Entries with a Unigene Assignment

0.770

  Entries with a Unigene Assignment

7056

  Entries without a Unigene Assignment

2109

 Number of NCBI Loci Represented

9967

  NCBI Loci/Gene

1.088

  Percentage of Entries with a NCBI loci Assignment

0.824

  Entries with a NCBI loci Assignment

7549

  Entries without a NCBI loci Assignment

1616

Sequence analysis

We randomly chose 268 of these mRNA for comparison of the 5′, 3′ and ORF length comparison to the corresponding human mRNA. Data are presented in Additional file 4. For the 1041 protein-coding genes missing from the genome, we entered the gene symbols into the DAVID version 6.8 (https://david.ncifcrf.gov) to assess overrepresentation of groups of gene with related function. The functional data were limited to human. Nine hundred and fifty six genes out of 1041 genes were recognized and 955 had functional annotations, of the unrecognized gene 41 are pig or artiodactyl specific genes. Data on functional enrichment of genes with a multiple comparison adjustment (Benjamini) value of >0.05 are presented in Table 3. We chose the 60 largest proteins of extreme size (>3000 amino acids) to compare the status (number of loci and completeness) in the NCBI and Ensembl build 10.2 genome. Because exon preservation is usually well conserved and there is fragmentation of certain areas of the porcine genome, the number of exons for the corresponding human gene was used for comparison. Lastly, we determined the chromosomal location of 1307 duplicated gene artifacts (2889 loci, Additional file 2) to identify problematic regions. Data are expressed as duplication per megabase (number of bases derived from the NCBI genome build (http://www.ncbi.nlm.nih.gov/genome?term=sus%20scrofa) and are presented in Fig. 2.
Fig. 2

Chromosomal Locations of 1307 Duplicated Gene Artifacts (2889 Loci)

Database implementation

The currently described database was constructed in the Filemaker Po Advanced v14.0 program (Filemaker Inc., Santa Clara, CA). The layout is illustrated in the sample database entry for the cytokine IL10 (Fig. 3 panels A–D). It was deployed using the Filemaker Server Advanced v14.0 program (Filemaker Inc., Santa Clara, CA). External access to the database has been successfully tested using Chrome, Internet Explorer and Safari browsers. Other areas of the database were populated from existing published or our own unpublished data. Each publication is manually reviewed and data (antibodies, real-time PCR assays, RNA or protein expression data, functional data) is abstracted and entered into the database, along with the Pubmed ID, in the appropriate field. We have developed Taqman real-time PCR assays for 1867 of these genes making them cross reactive for as many species as possible (1067 are partially or fully human gene cross reactive). This is to ensure that comparable areas of the gene are being analyzed as well as for economic reasons. We also conducted a literature survey to determine the sequence of porcine SYBR green PCR assays. Tissue-specific gene expression summaries, using these assays, are provided for these and other studies (i.e., those using microarray and RNASeq), and a comprehensive search of catalog and published literature to identify antibodies to the corresponding proteins. Last, the “Notes Field” in the database was populated with information such as types of errors discovered, degree of 5′ and 3′ UTR conservation, degree of positive selection pressure in various species, and intron status. When the gene (sequence) is present in the genome but not annotated as a gene, we annotate the gene in the Notes field as “Not an identified gene in Ensembl build 10.2.” or “not an identified gene in NCBI build 10.2”.
Fig. 3

ad Sample Database Entry

Fig. 4

Hemicentin (a) and Titin (b) Assembly Blasts

Fig. 5

Analysis of MicroRNA Sequence Origin and Species Similarity. These 3 sources of information for our 1047 MicroRNA sequences have a significant amount of overlap (a) and include 81 that we have predicted based upon their presence in other species and other unfinished porcine genomes. Of these sequences, 454 are unique to pigs, 318 are shared among the four species (b), 55 are shared between humans and pigs but not mice and cows and 25 are shared between mice and pigs but not humans and cows

Utility

To date, we have generated 9720 full-length transcripts representing 9165 genes (Table 1). They include 1354 genes missing from Ensembl build 10.2 (Table 2 and Additional file 1) and 1400 genes that have been sequenced at least two times (gene duplicated artifacts shown in Table 2 and Additional file 2 that were annotated as separate genes in either Ensembl or NCBI builds. Functional enrichment analysis of 1041 protein-coding genes that are missing from the genome reveals that genes that are annotated as cytokines (24, p = 0.0053) and transcription factors (68) (particularly Homeodomain-like transcription factors (34, p = 0.032) and CENP-B/Helix-turn-helix (HTH) domains (6, p = 0.035) are significantly overrepresented (Table 3). Of note, the great majority of the Interleukin 1 Superfamily (IL1F10, IL1RN, IL36A, IL36B, IL36G, IL36RN, IL37) members are significantly (p = 0.0073) overrepresented. Data analysis that do not account for these genes risk missing assessment of important genes involved in inflammation and development.
Table 2

Number and Types of Errors Located in Publically-available Porcine Databases

Parameter

Metric

Number of Errors

8187

Number of Entries with Errors

5337

Number of Genes not identified in Ensembl Build 10.2.

1354

   Missing from Genome

1019

   Present but not Annotated

335

Artifactually Duplicated Loci

1400

Truncated proteins

2291

Elongated proteins

199

Table 3

Functional Annotations for 1041 Protein-Coding Genes that are Missing from Ensembl build 10.2

Category

Term

#

P Value

Benjamini

GOTERM MF DIRECT

Nucleic acid binding transcription factor activity

68

2.6E-3

3.0E-1

GOTERM MF DIRECT

Interleukin-1 receptor binding

7

1.8E-5

7.4E-3

GOTERM MF DIRECT

Cytokine activity

24

1.9E-5

5.2E-3

INTERPRO

Ly-6 antigen / uPA receptor -like

9

2.2E-6

2.9E-3

INTERPRO

Homeodomain-like

34

9.9E-5

3.2E-2

INTERPRO

DNA binding HTH domain, Psq-type

6

2.5E-4

6.2E-2

PFAM

CENP-B N-terminal DNA-binding domain

6

9.8E-5

3.5E-2

GOTERM BP

RNA biosynthetic process

241

4.5E-5

4.7E-2

Based upon gene number estimates from other closely related species such as human and cow, we estimated that our database has a coverage rate of approximately 42% of the porcine genome. These represent sequences found in 10,232 Unigene entries (1.45 per gene), 9967 NCBI loci (5756 are single loci that are not duplicated gene artifacts or split into multiple loci, and 1793 genes have multiple (4211) loci. A total of 2109 and 1616 of the genes have no assigned Unigene number or NCBI loci, respectively. In addition to GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, literature-based functional annotations (derived from more than 5500 references) are provided for these sequences. We have also discovered a relatively large number (178) of porcine or artiodactyl-specific paralogs (Additional file 3) for 104 protein or non-protein coding porcine genes. For genes with multiple paralogs, genes are named in the order of phylogenetic distance of the parent human or bovine gene. Some of these genes are expressed pseudogenes. Some of these genes have been previously discussed (i.e., CD36, IL1B [25, 31]) or will be discussed in the following sections.

The transcripts we have generated for protein-coding genes include, on average, 70.5% of the corresponding 5′ and 3′ ends (each) of the human sequence (Additional file 4). The ORF is 99.4% conserved on a nucleotide count basis. These percentages indicate the fidelity of our procedure. We discovered extensive gene truncation (incomplete ORF) and gene duplicated artifacts (genes sequenced more than once) among the machine annotated versions of these genes. These problems are common among 1st drafts of other genomes [32, 33]. Gene duplicated artifacts appear most frequently for chromosomes 12, 2 and 3, and less frequently for chromosomes X, 11, 13, and 1 (Fig. 2). The most frequent areas should be targeted for re-sequencing or reassembly. Analysis of the 60 largest porcine proteins in the database shows that gene fragmentation and truncation roughly correlate with protein size and number of exons (Table 4). Figure 4 shows BLAST search results from two extremely large proteins, hemicentin (HMCN1, panel a) and titin (TTN, panel b) that have 9 loci assignments each, in the current NCBI build. Surprisingly, these proteins are not represented in Ensembl build 10.2 as annotated genes. Overall, of the 60 largest porcine proteins, only 6 and 10 are represented as single full-length sequences of the correct size in Ensembl and Genbank, respectively. We have deposited 12 de novo assemblies in the TSA archive and have provided in silico predicted RNA and protein sequences for 37 of these genes.
Table 4

Extensive Gene Fragmentation/Truncation Frequently Occurs Among Proteins of Extreme Size

Protein

Accession

# of Exons

Nucleotides

Amino Acids

NCBI Loci

Ensembl Loci

TTN

Predicted

312

103,020

33,921

9

0

SYNE1

Predicted

152

27,499

8798

3

3

OBSCN

Predicted

106

26,424

8755

5

2

MACF1

Predicted

141

23,519

7353

1 (truncated)

1 (truncated)

SYNE2

Predicted

116

21,767

6911

1

1

MUC6

Predicted

33

19,628

5692

1 (truncated)

1 (truncated)

MDN1

Predicted

102

17,684

5600

2

2

KMT2D

Predicted

56

17,324

5584

0

1 (truncated)

HMCN1

Predicted

107

17,839

5519

9

8

RNF213

Predicted

72

17,574

5245

4

3

UBR4

JAA53804.1

106

15,865

5182

4

4

RYR1

NP_001001534.1

106

15,384

5035

3

1 (truncated)

FAT4

Predicted

18

17,651

4983

4

1 (elongated)

RYR2

Predicted

107

16,588

4967

1 (truncated)

1 (truncated)

KMT2C

Predicted

64

15,669

4960

4

3

RYR3

Predicted

107

15,574

4870

8

1 (truncated)

BIRC6

Predicted

78

15,159

4861

2

1 (truncated)

HERC1

XP_001927286.4

80

15,199

4859

2

2

HERC2

JAG69485.1

98

15,070

4847

2

2

DNHD1

XP_013844910.1

41

16,014

4737

1

1 (truncated)

DNAH8

XP_001924974.2

97

14,418

4729

1

1

MYCBP2

Predicted

89

15,037

4675

1 (truncated)

1 (truncated)

DYNC1H1

Predicted

78

14,323

4646

3

1 (truncated)

LRP1B

Predicted

91

16,455

4590

13

3

FAT1

Predicted

29

14,904

4588

1

1 (elongated)

APOB

Predicted

31

14,158

4573

4

4

FAT3

Predicted

33

18,857

4557

1 (truncated)

1 (elongated)

LRP1

JAA53703.1

89

14,074

4544

2

2

ABCA13

Predicted

75

15,009

4444

3

0

SACS

Predicted

12

15,381

4441

4

3

ANK3

XP_005671069.1

52

15,032

4376

1

1 (truncated)

HUWE1

Predicted

91

14,590

4373

1 (elongated)

2

VPS13D

Predicted

70

16,126

4364

3

1 (truncated)

FAT2

Predicted

31

14,579

4350

2

1 (truncated)

PKD1

NP_001233131.1

47

14,212

4305

1

1

HECTD4

Predicted

76

19,834

4271

1 (truncated)

1 (truncated)

PRKDC

Predicted

86

14,362

4135

5

2

ANK2

Predicted

55

14,520

4100

1 (truncated)

1 (truncated)

VPS13B

JAG69054.1

80

13,584

3993

3

3

KMT2A

JAG69421.1

37

16,597

3967

1 (truncated)

1 (truncated)

DNAH12

Predicted

78

11,946

3961

3

1 (truncated)

AKAP9

NP_001240753.1

55

12,489

3898

1

1

LYST

JAA53665.1

61

12,677

3798

3

1 (truncated)

MUC4

XP_005670193.1

25

11,665

3745

1

1 (truncated)

ZNF469

Predicted

3

12,517

3736

0

0

VPS13C

JAA53695.1

88

11,772

3714

3

2

ZFHX3

Predicted

11

15,821

3713

1 (truncated)

1 (truncated)

DMD

NP_001012408.1

87

13,770

3674

5

2

SMG1

JAG69152.1

64

15,532

3659

2

0

SPEN

JAG69140.1

15

12,261

3655

1 (truncated)

1 (truncated)

CUBN

Predicted

71

11,536

3620

4

2

ZFHX4

Predicted

15

14,156

3611

1 (truncated)

1 (truncated)

WDFY3

XP_005656619.1

74

14,209

3594

1

1

USP34

JAA53700.1

80

11,327

3547

3

3

UTRN

JAA53694.1

84

10,547

3432

4

5

COL6A3

XP_013840079.1

50

13,801

3199

1

1 (truncated)

VPS13A

Predicted

76

11,078

3172

2

1

CEP350

JAA53656.1

40

9910

3121

2

2

CELSR1

Predicted

38

11,081

3031

2

1 (truncated)

FRY

Predicted

66

10,455

3016

3

2

In previous studies, we extensively compared porcine, human and mouse genes related to immunity and inflammation [2, 3, 25, 26]. In the following section, we will summarize our findings for three major Superfamilies or functionally related groups of proteins (CD marker genes, Solute carrier superfamily, ATP binding cassette superfamily) or non-coding RNA (microRNA) that have complete or nearly complete representation. CD markers (accessible as a group by entering CD markers in the Annotations field) encode a heterogeneous group of cell surface proteins. The Human Leucocyte Differentiation Antigen (HLDA) workshop has designated 408 molecules (some of which are grouped within a CD) as CD markers [34]. Based upon our assembly and analysis, we could establish 1:1 orthology for 357 porcine genes to those that compose HLDA version 10. Forty-three genes are not present in the porcine genome or could not be designated as 1:1 orthologs. Of these, nine genes (CLEC4C, CLEC4M, SIGLEC7, BTN3A1, LILRA1, LAIR2, PSG1, SIRPG, TNFRSF10C, are primate-specific [3537]. KLRC2 (CD159c) is found in humans and rodents but not pigs. FCGR2C is a human-specific gene/pseudogene that belongs to a family of three low-affinity immunoglobulin gamma Fc receptors (CD32) [38]. We have determined that pigs have two member of this family that roughly corresponds to FCGR2A and FCGR2B. TNFRSF14 (CD270) is a marker for B cells, dendritic cells, monocytes, and Treg cells [39] found in humans and rodents, but not cows. Although, canine, feline, equine and ursine homologs have been identified, this gene may be a pseudogene in pigs as the putative ORF is interrupted by an endogenous retroviral sequence (H. Dawson, unpublished). FCRL2 (CD307b) is a marker for B cells in humans. Although sequences corresponding to FCRL2 have been identified in other mammals including dog and horse, no mouse ortholog has been identified [40]. This gene shows evidence of positive selection in humans [41] and is most likely a pseudogene in pigs.

Due to rapid evolution and post-speciation gene duplication, no 1:1 orthology could be established for most mouse and pig LILR or KIR family members, including LILRA4 (CD85G) and LILRB4 (CD85K) [42]. Similarly, other than CEACAM1 (CD66) and CEACAM6 (CD66C), no 1:1 orthology could be established for most pig and mouse CEACAM family members (CEACAM3 (CD66D) CEACAM5 (CD66E). CEACAM8 (CD67) may be a pseudogene as ESTs in Unigene Ssc.60435 predict a 243 amino acid protein interrupted by several stop codons. CEACAM8 and CEACAM6 were previously determined to have no direct murine orthologs [35]. Several other shared human-pig CD marker orthologs (ADGRE2 (CD312), ADGRE3 (CD313r), CD1A, CD1E, CR1 (CD35), CD58, FCGR2A (CD32), FCAR (CD89), FCRL3 (CD307c), FCRL4 (CD307d), ICAM3 (CD50), NCR2 (CD336), NCR3 (CD337) and TLR10 (CD290r) have no rodent orthologs [2, 40, 43].

A significant number of errors were discovered in genes encoding porcine orthologs of human CD markers; 25 are not present in Ensembl build 10.2, 88 of the proteins are truncated and 52 are duplicated gene artifacts. Sixty-seven full-length mRNA sequences encoding proteins, assembled from macrophage RNA-Seq reads, have been deposited in Genbank. An additional 79 in silico constructs are provided. Antibody data, gathered from publications, manufacturers or generated in house, is provided for 186 proteins including 395 monoclonal and 285 polyclonal antibodies. Additional cross reactivity for 29 proteins is expected because they are >95% similar to human proteins. Several of the CD Marker family are members of other gene families including the Solute Carrier and ATP-binding Cassette Super Family.

The Human Genome Organization’s gene nomenclature committee (HGNC) has assigned 395 genes to the Solute Carrier Superfamily, 21 are pseudogenes and three hundred seventy four encode proteins (accessible as a group by entering Solute Carrier Superfamily in the Annotations field). These are organized into 52 subfamilies; about 25% are dedicated to nutrient transport. The porcine Solute Carrier Super family contains 398 protein-coding members and all human subfamilies are represented. Forty-two of these genes are present in other porcine genomes but missing from Ensembl build 10.2, 113 are truncated and 58 of these are duplicated gene artifacts. Sixty three full-length mRNA sequences, assembled from macrophage RNA-Seq reads, have been deposited in Genbank and an additional 159 in silico constructs are provided. Forty-two of these genes are missing from all porcine genomes or are present as pseudogenes. Among these genes are UCP1 (thermogenein), a protein involved in non-shivering thermogenesis and a pseudogene in pigs [44] and SLC52A2, a primate specific riboflavin transporter [45]. Other species-specific genes include eight primate-specific (SLC2A14, SLC22A24, SLC35E2, SLC35G3, SLC35G4, SLC35G5, SLCO1B1, SLCO1B7), one human specific (SLC22A25) gene and 14 mouse or rodent-specific genes (Slc6a20b, Slc7a12, Slc21a4, Slc22a19, Slc22a21, Slc22a22, Slc22a26, Slc22a27, Slc22a28, Slc22a29, Slc22a30, Slco1a1, Slco1b2, and Slco6b1). SLC25A18 is present in human and rodent genomes but is missing from bovine and porcine genomes. SLC25A52 is present in primate and rat genomes but not mouse. SLC9C2 is a pseudogene in mouse [46]. SLC22A31 is an expressed pseudogene in pigs and is missing in rodents. SLC22A11 is an expressed pseudogene in pigs and a non-expressed pseudogene in mouse. Lastly, SLC23A4, an intestinal nucleobase transporter [47], is a pseudogene in humans but is present in pig, cow and rodent genomes. Several porcine or artiodactyl-specific gene expansions are found in subfamilies (Additional file 3) including SLC7A3 (14 members), SLC7A13 (3 members) SLC22A6 (2 members), SLC22A10 (4 members) and SLC47A1 (2 members). The biological functions of these paralogs remain to be determined; however the parent genes are involved in amino acid (SLC7A3, SLC7A13) or dipeptide transport (SLC22A6) [48, 49].

The HGNC has assigned 51 genes to the ATP binding Cassette Superfamily, three are pseudogenes and 48 encode proteins (accessible as a group by entering ATP binding Cassette Superfamily in the Annotations field). These are organized into five subfamilies (A-G), about 20% are dedicated to nutrient (i.e., carotenoid, cholesterol and vitamin A) transport. The porcine ATP binding Cassette Family contains 57 members and all human subfamilies are represented. These include five that are missing from Ensembl build 10.2 and 18 that are duplicated gene artifacts. Five of these genes are present in other porcine genomes, but missing from Ensembl build 10.2, 21 are truncated, and 18 of these genes are duplicated gene artifacts, Eleven full-length mRNA sequences, assembled from macrophage RNA-Seq reads, have been deposited in Genbank and an additional 24 in silico constructs are provided.

An analysis of this superfamily revealed that ABCC11 has no murine ortholog [50] and ABCA8 has no direct rodent ortholog as the gene has diverged into two paralogs, Abca8a and Abca8b [51]. The ABCC4, a prostaglandin E2 transporter [52], has diverged from the parent gene into five paralogs (ABCC4L1, ABCC4L2, ABCC4L3, ABCC4L4 and ABCC4L5 (Additional file 3). ABCA10, involved in human macrophage cholesterol transport [53], is a pseudogene in rodents. It may be an expressed pseudogene in pigs as the predicted protein is half (787 amino acids) the size of human ABCA10 (1543 amino acids) and weak expression (by RNASeq) was detected in macrophages and moderated expression in intestine (H. Dawson, unpublished). ABCA17 is an expressed pseudogene is humans and pigs. Like the Solute Carrier Superfamily, most of the genes in the ATP binding Cassette Super family have not been characterized at the functional level. Nevertheless, the similarities and differences in the ATP binding Cassette and ATP binding Cassette Super families impact the suitability of rodents and pigs as models for human drug and nutrient transport and metabolism.

The exact number of microRNAs in the porcine genome is unknown. There are 4272 annotated microRNAs in the human genome (build 30). Although there are several papers describing the measurement of porcine microRNAs in various tissues or estimating the number in the porcine genome [5457] and three partially overlapping sources of porcine microRNA sequences, the exact number of porcine microRNAs is currently unknown. There are only 382, 385 and 816 (non-redundant) annotated pig miRNA sequences in Mirbase, NCBI gene build, and Ensembl build 10.2, respectively. These three sources of information have a significant amount of overlap (Fig. 5a). We have consolidated this information and provide sequence data for our own predicted sequences based on conserved sequence identity to 1900 human, mouse or bovine sequences, to provide 1033 non-redundant porcine microRNA sequences (accessible as a group by entering MicroRNA in the Annotations field). Of note, all of the sequences found in Mirbase were found in the NCBI gene build, 59 of the microRNA sequences in Ensembl were found to be duplicated artifacts, and 214 of the 1033 sequences are not present in the current Ensembl gene build (10.2). This includes 81 that we have predicted based upon their presence in other species and other unfinished porcine genomes. We discovered the following species- or genera-specific microRNA; pigs (454), humans (199), primates (111) bovine (179), mouse (76) and rodents (20). Many of the porcine-specific microRNA have arisen from biological duplication/expansion (Additional file 3). A comparison of microRNA that are present in pigs and shared among at least one of the three other species (human, cows, and mice) revealed that 318 microRNA are shared among the four species, 107 are shared between pigs, humans and cows but not mice, and 34 are shared between pigs, mice and cows but not humans (Fig. 5b). Thus, the frequency of non-conserved microRNA preservation between human and pig is nearly three times that of mouse to pig.

Discussion

The Porcine Translational Research Database is named because of its unique utility to translate findings made in rodents to pigs and from those in pigs to humans. A comprehensive literature-based survey was conducted to identify genes that have demonstrated function in humans, mice or pigs. The resulting data in the database is documented by >6000 references. The database currently contains 65 data fields for each entry. Our efforts to improve the genome and its annotation are similar to other efforts, for example the sequencing of 12,000 genes to supplement annotation of the pig genome [32, 33, 58] and de novo assembly of multiple pig genomes to reveal 1737 protein coding genes that are missing from Ensembl build 10.2 [30]. The online Supplemental data from the latter manuscript was unavailable at the time of the preparation of this manuscript so no comparison could be made. The manual assembly of >9700 RNA sequences has direct practical implications for genomics-based analysis. The state of the current genome build (mis-annotations, duplication artifacts, and missing sequences) effectively prohibits its use for aligning RNAseq reads. We have used these sequences to compare gene expression separately from Ensembl 10.2 and have also compared the number of reads obtained from the corresponding templates in Ensembl 10.2. For the great majority of transcripts compared, as expected, our full-length sequences provided a higher level of sensitivity than the corresponding Ensembl sequences (H. Dawson unpublished).

The full 5′ and 3′ representation of each gene will also allow for characterization of regulatory regions and miRNA target sites. In our estimation, >40% of transcripts in Ensembl or NCBI genomes do not represent the full-length gene. Our efforts will also allow for further consolidation of porcine Unigene numbers. Currently, each gene is represented by from 0 to >10 Unigene assignments, and >10% of genes have more than one.

It is significant that we discovered a large number of errors (about 30% of entries) in the publicly available sequence databases (these can be accessed by searching the “Notes Field” using the word “error” (Fig. 3)). In addition to the duplication artifacts, mis-annotations and missing genes, we also encountered a number of RNA sequences in publically available archives belonging to other species. For, example, human (AHR, AF233432.1), panda (IL2, NM_001199892.1) and rat (NUDT14, ESTs in Unigene Ssc.85635) RNA sequences are annotated as porcine derived. We also found sources of contaminating DNA from completely unrelated species. For example, about 1/5 of porcine chromosome 4 clone CU076066.6 is from Zebrafish. These sequences represent 6 Zebrafish genes (LOC100003615, LOC447815, LOC108179932, LOC108183883, LOC108183971, and LOC103910681) and are annotated as porcine genes by Ensembl build 10.2 (ENSSSCG00000006223) and NCBI genomes (LOC100739857). Similarly, several NCBI loci (ASNA1L*, LOC100737282, LOC100737202, LOC100620149, LOC100737282) and one Ensembl locus (ENSSSCG00000026988) are derived from contaminating Babesia bigemina genomic DNA.

We have discovered several sources of systematic errors in the Ensmbl and NCBI gene/protein prediction or annotation pipelines. For example all selenoproteins in Ensembl are truncated because the codon (UGA) for selenocysteine is mistranslated or translated as a stop codon. We and others have identified a systematic error in the identification of another gene family, the Taste receptor, type 2 (TAS2R) Superfamily. Despite being intronless and mostly devoid of 5′ and 3′ UTR regions, Ensembl consistently fails to recognize them as genes [3]. These data illustrate the critical importance of the manual-curation process to reduce errors.

We believe that this is the largest manually curated database for any veterinary species and that the infomantics are unique among those targeting a veterinary species in regard to linking gene expression to gene function, identification of related gene pathways, and connectivity with other porcine gene databases, as well as for reagents that measure gene and protein expression. In addition, it is the largest source of centralized antibody information for the pig. Any database must be updated frequently in order to be useful. Currently the database is updated monthly and we anticipate expanding the content to include all porcine genes. There are several Super families of genes that will be the next targets of our efforts. One is the GPCR super family, the exact size of the GPCR super family is still unknown, but nearly 800 different human genes (or ~4% of the entire protein-coding genome) have been predicted to code for them. We will also continue to develop and annotate new assays. We intend to include our own prediction analysis for the promoter and 3′ UTR region of RNA for transcription factor and microRNA binding sites. Lastly, we intend to synchronize our database with the porcine “Snowball” array and porcine gene expression atlas [59].

Declarations

Funding

Supported by USDA/ARS Project Plan 1235-51,000-055-00D.

Availability and requirements

The dataset(s) supporting the conclusions of this article are included within the article, its additional file (Additional files 1, 2, 3 and 4) and within the online database (http://www.ars.usda.gov/Services/docs.htm?docid=6065).

Authors’ contributions

HDD, CC, BG and JS contributed to the content of the database. HDD and JFU wrote the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
United States Department of Agriculture, Agricultural Research Service, Beltsville Human Nutrition Research Center, Diet, Genomics and Immunology Laboratory
(2)
United States Department of Agriculture, Agricultural Research Service, Beltsville Agricultural Research Center, Molecular Plant Pathology Lab

References

  1. Miller ER, Ullrey DE. The pig as a model for human nutrition. Annu Rev Nutr. 1987;7:361–82.View ArticlePubMedGoogle Scholar
  2. Dawson HD: A comparative assessment of the pig, mouse and human genomes. In: The Minipig in Biomedical Research. Boca Raton: CRC Press; 2011: 323-342.Google Scholar
  3. Groenen MA, Archibald AL, Uenishi H, Tuggle CK, Takeuchi Y, Rothschild MF, Rogel-Gaillard C, Park C, Milan D, Megens HJ, et al. Analyses of pig genomes provide insight into porcine demography and evolution. Nature. 2012;491(7424):393–8.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Roth JA, Tuggle CK. Livestock models in translational medicine. ILAR J. 2015;56(1):1–6.View ArticlePubMedGoogle Scholar
  5. Meurens F, Summerfield A, Nauwynck H, Saif L, Gerdts V. The pig: a model for human infectious diseases. Trends Microbiol. 2012;20(1):50–7.View ArticlePubMedGoogle Scholar
  6. Schautteet K, Vanrompay D. Chlamydiaceae infections in pig. Vet Res. 2011;42:29.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Holm IE, Alstrup AK, Luo Y. Genetically modified pig models for neurodegenerative disorders. J Pathol. 2016;238(2):267–87.View ArticlePubMedGoogle Scholar
  8. Selsby JT, Ross JW, Nonneman D, Hollinger K. Porcine models of muscular dystrophy. ILAR J. 2015;56(1):116–26.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Flisikowska T, Kind A, Schnieke A. Pigs as models of human cancers. Theriogenology. 2016;86(1):433–7.View ArticlePubMedGoogle Scholar
  10. Klymiuk N, Aigner B, Brem G, Wolf E. Genetic modification of pigs as organ donors for xenotransplantation. Mol Reprod Dev. 2010;77(3):209–21.PubMedGoogle Scholar
  11. Kelley J, de Bono B, Trowsdale J. IRIS: a database surveying known human immune system genes. Genomics. 2005;85(4):503–11.View ArticlePubMedGoogle Scholar
  12. Schonbach C, Koh JL, Flower DR, Brusic V. An update on the functional molecular immunology (FIMM) database. Appl Bioinforma. 2005;4(1):25–31.View ArticleGoogle Scholar
  13. Lefranc MP. IMGT, the international ImMunoGeneTics information system(R): a standardized approach for immunogenetics and immunoinformatics. Immunome Res. 2005;1(1):3.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Grimes GR, Moodie S, Beattie JS, Craigon M, Dickinson P, Forster T, Livingston AD, Mewissen M, Robertson KA, Ross AJ, et al. GPX-macrophage expression atlas: a database for expression profiles of macrophages challenged with a variety of pro-inflammatory, anti-inflammatory, benign and pathogen insults. BMC Genomics. 2005;6:178.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Korber B, LaBute M, Yusim K. Immunoinformatics comes of age. PLoS Comput Biol. 2006;2(6):e71.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Uenishi H, Eguchi T, Suzuki K, Sawazaki T, Toki D, Shinkai H, Okumura N, Hamasima N, Awata T. PEDE (pig EST data explorer): construction of a database for ESTs derived from porcine full-length cDNA libraries. Nucleic Acids Res. 2004;32(Database issue):D484–8.View ArticlePubMedPubMed CentralGoogle Scholar
  17. McCarthy FM, Wang N, Magee GB, Nanduri B, Lawrence ML, Camon EB, Barrell DG, Hill DP, Dolan ME, Williams WP, et al. AgBase: a functional genomics resource for agriculture. BMC Genomics. 2006;7(1):229.View ArticlePubMedPubMed CentralGoogle Scholar
  18. Ruan J, Guo Y, Li H, Hu Y, Song F, Huang X, Kristiensen K, Bolund L, Wang J. PigGIS: pig genomic informatics system. Nucleic Acids Res. 2007;35(Database issue):D654–7.View ArticlePubMedGoogle Scholar
  19. Piovesan D, Profiti G, Martelli PL, Fariselli P, Fontanesi L, Casadio R. SUS-BAR: a database of pig proteins with statistically validated structural and functional annotation. Database. 2013;2013:bat065.View ArticlePubMedPubMed CentralGoogle Scholar
  20. Howe DG, Bradford YM, Eagle A, Fashena D, Frazer K, Kalita P, Mani P, Martin R, Moxon ST, Paddock H, et al. The Zebrafish model organism database: new support for human disease models, mutation details, gene expression phenotypes and searching. Nucleic Acids Res. 2017;45(D1):D758–68.View ArticlePubMedGoogle Scholar
  21. Howe KL, Bolt BJ, Cain S, Chan J, Chen WJ, Davis P, Done J, Down T, Gao S, Grove C, et al. WormBase 2016: expanding to enable helminth genomic research. Nucleic Acids Res. 2016;44(D1):D774–80.View ArticlePubMedGoogle Scholar
  22. Drysdale R, FlyBase C. FlyBase : a database for the drosophila research community. Methods Mol Biol. 2008;420:45–59.View ArticlePubMedGoogle Scholar
  23. Breuer K, Foroushani AK, Laird MR, Chen C, Sribnaia A, Lo R, Winsor GL, Hancock RE, Brinkman FS, Lynn DJ. InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation. Nucleic Acids Res. 2013;41(Database issue):D1228–33.View ArticlePubMedGoogle Scholar
  24. Rhee SY, Wood V, Dolinski K, Draghici S. Use and misuse of the gene ontology annotations. Nat Rev Genet. 2008;9(7):509–15.View ArticlePubMedGoogle Scholar
  25. Dawson HD, Loveland JE, Pascal G, Gilbert JG, Uenishi H, Mann KM, Sang Y, Zhang J, Carvalho-Silva D, Hunt T, et al. Structural and functional annotation of the porcine immunome. BMC Genomics. 2013;14:332.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Dawson HD, Smith AD, Chen C, Urban JF Jr. An in-depth comparison of the porcine, murine and human inflammasomes; lessons from the porcine genome and transcriptome. Vet Microbiol. 2016;Google Scholar
  27. Pei B, Sisu C, Frankish A, Howald C, Habegger L, Mu XJ, Harte R, Balasubramanian S, Tanzer A, Diekhans M, et al. The GENCODE pseudogene resource. Genome Biol. 2012;13(9):R51.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Thomas JW, Prasad AB, Summers TJ, Lee-Lin SQ, Maduro VV, Idol JR, Ryan JF, Thomas PJ, McDowell JC, Green ED. Parallel construction of orthologous sequence-ready clone contig maps in multiple species. Genome Res. 2002;12(8):1277–85.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Heckel T, Schmucki R, Berrera M, Ringshandl S, Badi L, Steiner G, Ravon M, Kung E, Kuhn B, Kratochwil NA, et al. Functional analysis and transcriptional output of the Gottingen minipig genome. BMC Genomics. 2015;16:932.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Li M, Chen L, Tian S, Lin Y, Tang Q, Zhou X, Li D, Yeung CK, Che T, Jin L, et al. Comprehensive variation discovery and recovery of missing sequence in the pig genome using multiple de novo assemblies. Genome Res. 2016;Google Scholar
  31. Mathew DJ, Newsom EM, Guyton JM, Tuggle CK, Geisert RD, Lucy MC. Activation of the transcription factor nuclear factor-kappa B in uterine luminal epithelial cells by interleukin 1 Beta 2: a novel interleukin 1 expressed by the elongating pig conceptus. Biol Reprod. 2015;92(4):107.View ArticlePubMedGoogle Scholar
  32. International Human Genome Sequencing C. Finishing the euchromatic sequence of the human genome. Nature. 2004;431(7011):931–45.View ArticleGoogle Scholar
  33. Church DM, Goodstadt L, Hillier LW, Zody MC, Goldstein S, She X, Bult CJ, Agarwala R, Cherry JL, DiCuccio M, et al. Lineage-specific biology revealed by a finished genome assembly of the mouse. PLoS Biol. 2009;7(5):e1000112.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Clark G, Stockinger H, Balderas R, van Zelm MC, Zola H, Hart D, Engel P. Nomenclature of CD molecules from the tenth human Leucocyte differentiation antigen workshop. Clin Translational Immunol. 2016;5(1):e57.View ArticleGoogle Scholar
  35. Kelley J, Walter L, Trowsdale J. Comparative genomics of natural killer cell receptor gene clusters. PLoS Genet. 2005;1(2):129–39.View ArticlePubMedGoogle Scholar
  36. van Beek EM, Cochrane F, Barclay AN, van den Berg TK. Signal regulatory proteins in the immune system. J Immunol. 2005;175(12):7781–7.View ArticlePubMedGoogle Scholar
  37. Crocker PR, Paulson JC, Varki A. Siglecs and their roles in the immune system. Nat Rev Immunol. 2007;7(4):255–66.View ArticlePubMedGoogle Scholar
  38. Su K, Wu J, Edberg JC, McKenzie SE, Kimberly RP. Genomic organization of classical human low-affinity Fcgamma receptor genes. Genes Immun. 2002;3(Suppl 1):S51–6.View ArticlePubMedGoogle Scholar
  39. Tao R, Wang L, Murphy KM, Fraser CC, Hancock WW. Regulatory T cell expression of herpesvirus entry mediator suppresses the function of B and T lymphocyte attenuator-positive effector T cells. J Immunol. 2008;180(10):6649–55.View ArticlePubMedGoogle Scholar
  40. Davis RS. Fc receptor-like molecules. Annu Rev Immunol. 2007;25:525–60.View ArticlePubMedGoogle Scholar
  41. Barreiro LB, Quintana-Murci L. From evolutionary genetics to human immunology: how selection shapes host defence genes. Nat Rev Genet. 2010;11(1):17–30.View ArticlePubMedGoogle Scholar
  42. Kang X, Kim J, Deng M, John S, Chen H, Wu G, Phan H, Zhang CC. Inhibitory leukocyte immunoglobulin-like receptors: immune checkpoint proteins and tumor sustaining factors. Cell Cycle. 2016;15(1):25–40.View ArticlePubMedGoogle Scholar
  43. Jacobson AC, Weis JH. Comparative functional evolution of human and mouse CR1 and CR2. J Immunol. 2008;181(5):2953–9.View ArticlePubMedPubMed CentralGoogle Scholar
  44. Berg F, Gustafson U, Andersson L. The uncoupling protein 1 gene (UCP1) is disrupted in the pig lineage: a genetic explanation for poor thermoregulation in piglets. PLoS Genet. 2006;2(8):e129.View ArticlePubMedPubMed CentralGoogle Scholar
  45. Yonezawa A, Inui K. Novel riboflavin transporter family RFVT/SLC52: identification, nomenclature, functional characterization and genetic diseases of RFVT/SLC52. Mol Asp Med. 2013;34(2-3):693–701.View ArticleGoogle Scholar
  46. Fuster DG, Alexander RT. Traditional and emerging roles for the SLC9 Na+/H+ exchangers. Pflugers Archiv. 2014;466(1):61–76.View ArticlePubMedGoogle Scholar
  47. Yamamoto S, Inoue K, Murata T, Kamigaso S, Yasujima T, Maeda JY, Yoshida Y, Ohta KY, Yuasa H. Identification and functional characterization of the first nucleobase transporter in mammals: implication in the species difference in the intestinal absorption mechanism of nucleobases and their analogs between higher primates and other mammals. J Biol Chem. 2010;285(9):6522–31.View ArticlePubMedGoogle Scholar
  48. Ito K, Groudine M. A new member of the cationic amino acid transporter family is preferentially expressed in adult mouse brain. J Biol Chem. 1997;272(42):26780–6.View ArticlePubMedGoogle Scholar
  49. Hagos Y, Burckhardt G, Burckhardt BC. Human organic anion transporter OAT1 is not responsible for glutathione transport but mediates transport of glutamate derivatives. Am J Physiol Renal Physiol. 2013;304(4):F403–9.View ArticlePubMedGoogle Scholar
  50. Shimizu H, Taniguchi H, Hippo Y, Hayashizaki Y, Aburatani H, Ishikawa T. Characterization of the mouse Abcc12 gene and its transcript encoding an ATP-binding cassette transporter, an orthologue of human ABCC12. Gene. 2003;310:17–28.View ArticlePubMedGoogle Scholar
  51. Annilo T, Chen ZQ, Shulenin S, Dean M. Evolutionary analysis of a cluster of ATP-binding cassette (ABC) genes. Mamm Genome. 2003;14(1):7–20.View ArticlePubMedGoogle Scholar
  52. Kochel TJ, Fulton AM. Multiple drug resistance-associated protein 4 (MRP4), prostaglandin transporter (PGT), and 15-hydroxyprostaglandin dehydrogenase (15-PGDH) as determinants of PGE2 levels in cancer. Prostaglandins Other Lipid Mediators. 2015;116-117:99–103.View ArticlePubMedGoogle Scholar
  53. Wenzel JJ, Kaminski WE, Piehler A, Heimerl S, Langmann T, Schmitz G. ABCA10, a novel cholesterol-regulated ABCA6-like ABC transporter. Biochem Biophys Res Commun. 2003;306(4):1089–98.View ArticlePubMedGoogle Scholar
  54. Bao H, Kommadath A, Plastow GS, Tuggle CK, Guan le L, Stothard P. MicroRNA buffering and altered variance of gene expression in response to salmonella infection. PLoS One. 2014;9(4):e94352.View ArticlePubMedPubMed CentralGoogle Scholar
  55. Sharbati S, Friedlander MR, Sharbati J, Hoeke L, Chen W, Keller A, Stahler PF, Rajewsky N, Einspanier R. Deciphering the porcine intestinal microRNA transcriptome. BMC Genomics. 2010;11:275.View ArticlePubMedPubMed CentralGoogle Scholar
  56. Anthon C, Tafer H, Havgaard JH, Thomsen B, Hedegaard J, Seemann SE, Pundhir S, Kehr S, Bartschat S, Nielsen M, et al. Structured RNAs and synteny regions in the pig genome. BMC Genomics. 2014;15:459.View ArticlePubMedPubMed CentralGoogle Scholar
  57. Paczynska P, Grzemski A, Szydlowski M. Distribution of miRNA genes in the pig genome. BMC Genet. 2015;16:6.View ArticlePubMedPubMed CentralGoogle Scholar
  58. Uenishi H, Morozumi T, Toki D, Eguchi-Ogawa T, Rund LA, Schook LB. Large-scale sequencing based on full-length-enriched cDNA libraries in pigs: contribution to annotation of the pig genome draft sequence. BMC Genomics. 2012;13:581.View ArticlePubMedPubMed CentralGoogle Scholar
  59. Freeman TC, Ivens A, Baillie JK, Beraldi D, Barnett MW, Dorward D, Downing A, Fairbairn L, Kapetanovic R, Raza S, et al. A gene expression atlas of the domestic pig. BMC Biol. 2012;10:90.View ArticlePubMedPubMed CentralGoogle Scholar

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