ABSTRACT. Single nucleotide polymorphism in microRNAs (miRNA) may influence their target gene selection and regulation efficiency, leading to animal phenotypic variation. The aim of this study was to evaluate the possible effect of single nucleotide polymorphisms in the miRNA-1757 gene precursor region (pre-mir-1757) on economicrelated traits in chicken. Genotyping was performed using Sequenom MassArray ® iPLEX GOLD System. Association analysis was performed using SPSS19.0. The data showed that the G/C polymorphism was significantly correlated with semi-evisceration weight, evisceration weight, carcass weight, body weight at 10 weeks of age, shank length at 4 weeks of age, pectoral angle at 8 weeks of age, and body slanting length and pelvis breadth at 12 weeks of age (P < 0.05), and led to the alteration of the RNA secondary structure of pre-mir-1757. Our results provide useful information for further annotation studies of miRNA function.
44The lifetime of G. biloba is very long, and its growth is relatively slow. However, 45 little is known about growth-related genes in this species. We combined mRNA 46 sequencing (RNA-Seq) with bulked segregant analysis (BSA) to fine map significant 47 agronomic trait genes by developing polymorphism molecular markers at the 48 transcriptome level. RNA-Seq data provides BSA with genotype information in RNA 49 Pool to screen out linked genes (low in false positives) after data analysis, and the 50 efficiency of development and verification of the linked polymorphism marker is 51 greatly improved. This combined approach (named BSR) has been applied to plant 52 transcriptome sequencing in sunflower, corn, wheat, and Arabidopsis thaliana. In this 53 study, transcriptome sequencing of high growth (GD) and low growth (BD) samples 54 of G. biloba half-sib families was performed. After assembling the clean reads, 601 55 differential expression genes were detected and 513 of them were assigned functional 56 annotations. Single nucleotide polymorphism (SNP) analysis identified SNPs 57 associated with 119 genes in the GD and BD groups; 58 of these genes were 58annotated. This study provides molecular level data that could be used for seed 59 selection of high growth G.biloba half-sib families for future breeding programs. 60
ABSTRACT. With the rapid development of next-generation highthroughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.
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