Molecular cloning, sequence characterization, polymorphism and association analysis of porcine ROPN1 gene

Assessment of Autozygosity Derived From Runs of Homozygosity in Jinhua Pigs Disclosed by Sequencing Data

Jinhua pig, a well-known Chinese indigenous breed, has evolved as a pig breed with excellent meat quality, greater disease resistance, and higher prolificacy. The reduction in the number of Jinhua pigs over the past years has raised concerns about inbreeding. Runs of homozygosity (ROH) along the genome have been applied to quantify individual autozygosity to improve the understanding of inbreeding depression and identify genes associated with traits of interest. Here, we investigated the occurrence and distribution of ROH using next-generation sequencing data to characterize autozygosity in 202 Jinhua pigs, as well as to identify the genomic regions with high ROH frequencies within individuals. The average inbreeding coefficient, based on ROH longer than 1 Mb, was 0.168 ± 0.052. In total, 18,690 ROH were identified in all individuals, among which shorter segments (1-5 Mb) predominated. Individual ROH autosome coverage ranged from 5.32 to 29.14% in the Jinhua population. On average, approximately 16.8% of the whole genome was covered by ROH segments, with the lowest coverage on SSC11 and the highest coverage on SSC17. A total of 824 SNPs (about 0.5%) and 11 ROH island regions were identified (occurring in over 45% of the samples). Genes associated with reproduction (HOXA3, HOXA7, HOXA10, and HOXA11), meat quality (MYOD1, LPIN3, and CTNNBL1), appetite (NUCB2) and disease resistance traits (MUC4, MUC13, MUC20, LMLN, ITGB5, HEG1, SLC12A8, and MYLK) were identified in ROH islands. Moreover, several quantitative trait loci for ham weight and ham fat thickness were detected. Genes in ROH islands suggested, at least partially, a selection for economic traits and environmental adaptation, and should be subject of future investigation. These findings contribute to the understanding of the effects of environmental and artificial selection in shaping the distribution of functional variants in the pig genome.

The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set

BACKGROUND

The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction.

METHODS AND FINDINGS

The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method.

CONCLUSIONS

The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes.

Gonadal transcriptomic analysis of yellow catfish (Pelteobagrus fulvidraco): identification of sex-related genes and genetic markers

Yellow catfish (Pelteobagrus fulvidraco) has been recognized as a vital freshwater aquaculture species in East and Southeast Asia. In addition to its commercial interest, it is also attracted much attention because of its value in studying sex-determination mechanisms. A comprehensive gonadal transcriptome analysis is believed to provide a resource for genome annotation, candidate gene identification, and molecular marker development. Herein, we performed a de novo assembly of yellow catfish gonad transcriptome by high-throughput Illumina sequencing. A total of 82,123 contigs were obtained, ranging from 351 to 21,268 bp, and N50 of 2,329 bp. Unigenes of 21,869 in total were identified. Of these, 229 and 1,188 genes were found to be specifically expressed in XY gonad tissue for 1 yr and 2 yr old yellow catfish, respectively; correspondingly, 51 and 40 genes were identified in XX gonad tissue at those two stages. Gene ontology and KEGG analysis were conducted and classified all contigs into different categories. A large number of unigenes involved in sex determination were identified, as well as microsatellites and SNP variants. The expression patterns of sex-related genes were then validated by quantitative real-time PCR (qRT-PCR) suggesting the high reliability of RNA-Seq results. In this study, the transcriptome of yellow catfish gonad was first sequenced, assembled, and characterized; it provides a valuable genomic resource for better understanding of yellow catfish sex determination as well as development of molecular markers, thereby assisting in the production of monosex yellow catfish for aquaculture.

Molecular characterization, tissue expression, polymorphism and association of porcine LCK gene

Lymphocyte-specific protein tyrosine kinase (LCK) is an important reproduction related gene. In this study, the full-length cDNA sequence of porcine LCK gene was cloned through the rapid amplification of cDNA ends (RACE) method. The porcine LCK gene encodes a protein of 509 amino acids which shares high homology with the LCK of nine species: giant panda (97%), dog (97%), cattle (96%), sheep (95%), rabbit (95%), human (96%), rat (94%), mouse (94%) and horse (94%). This novel porcine gene was assigned to GeneID: 100233188. The phylogenetic analysis revealed that the porcine LCK gene has a closer genetic relationship with the LCK gene of dog. This gene is structured in twelve exons and eleven introns as revealed by computer-assisted analysis. The tissue transcription profile analysis indicated that the porcine LCK gene is generally but differentially expressed in the detected tissues including large intestine, spleen, lung, muscle, fat, liver, heart, kidney and ovary. PCR-Alu I-RFLP was established to detect an A/G substitution at the position of 1127-bp of mRNA and eight pig breeds displayed obvious genotype and allele frequency differences at this mutation locus. Association of this single-nucleotide polymorphism with litter size traits was assessed in Large White (n = 100) and Landrace (n = 100) pig populations, and results demonstrated that this polymorphic locus was significantly associated with the litter size of all parities in Large White sows and Landrace sows (P < 0.01). Therefore, LCK gene could be an useful candidate gene in selection for increasing litter size in pigs. These data serve as a foundation for further insight into this novel porcine gene.