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2009 Vol. 36, No. 11

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Research article
An integrated view of the correlations between genomic and phenomic variables
Dong Yang, Ying Jiang, Fuchu He
2009, 36(11): 645-651. doi: 10.1016/S1673-8527(08)60156-3
Abstract (68) HTML PDF (0)
Abstract:
Genome sequencing opened the flood gate of “-omics” studies, among which the research about correlations between genomic and phenomic variables is an important part. With the development of functional genomics and systems biology, genome-wide investigation of the correlations between many genomic and phenomic variables became possible. In this review, five genomic variables, such as evolution rate (or “age” of the gene), the length of intron and ORF (protein length) in one gene, the biases of amino acid composition and codon usage, along with the phenomic variables related to expression patterns (level and breadth) are focused on. In most cases, genes with higher mRNA/protein expression level tend to evolve slowly, have less intronic DNA, code for smaller proteins, and have higher biases of amino acid composition and codon usage. In addition, broadly expressed proteins evolve more slowly and are shorter than tissue-specific proteins. Studies in this field are helpful for deeper understanding the signatures of selection mediated by the features of gene expression and are of great significance to enrich the evolution theory.
Fine mapping quantitative trait loci affecting milk production traits on bovine chromosome 6 in a Chinese Holstein population
Gui Mei, Cengceng Yin, Xiangdong Ding, Qin Zhang
2009, 36(11): 653-660. doi: 10.1016/S1673-8527(08)60157-5
Abstract (59) HTML PDF (0)
Abstract:
To fine map the previously detected quantitative trait loci (QTLs) affecting milk production traits on bovine chromosome 6 (BTA6), 15 microsatellite markers situated within an interval of 14.3 cM spanning from BMS690 to BM4528 were selected and 918 daughters of 8 sires were genotyped. Two mapping approaches, haplotype sharing based LD mapping and single marker regression mapping, were used to analyze the data. Both approaches revealed a quantitative trait locus (QTL) with significant effects on milk yield, fat yield and protein yield located in the segment flanked by markers BMS483 and MNB209, which spans a genetic distance of 0.6 cM and a physical distance of 1.5 Mb. In addition, the single marker regression mapping also revealed a QTL affecting fat percentage and protein percentage at marker DIK2291. Our fine mapping work will facilitate the cloning of candidate genes underlying the QTLs for milk production traits.
Genome scan of pigmentation traits in Friesian-Jersey crossbred cattle
Lin Liu, Bevin Harris, Mike Keehan, Yuan Zhang
2009, 36(11): 661-666. doi: 10.1016/S1673-8527(08)60158-7
Abstract (65) HTML PDF (0)
Abstract:
Pigmentation traits expressed in animals are visual characteristics that allow us to distinguish between breeds and between strains within breed. The objective of this study was to map quantitative trait loci (QTLs) affecting the pigmentation traits in approximately 800 F2 grand daughter dairy cattle from a Holstein-Friesian and Jersey cross breed cattle. Traits analyzed included pigmentation phenotypes on the body, teat and hoop. The phenoypes were collected from digital photos or visual inspection of live animals. QTL mapping was implemented using half-sib and line-of-descent inheritance models. Our analysis initially detected a number of significant QTLs on chromosomes: 2, 6, 13, 15, 18 and 22. The significant QTLs were divided into two groups: one group influencing the pigmentation color and the other group affecting the absence or level of pigmentation. The most significant QTL peaks were observed on Bovine taurus autosome 18 (BTA18) close to melanocortin 1 receptor (MC1R) for the color traits, on BTA6 close to the receptor tyrosine kinase (KIT) and BTA22 close to microphthalmia-associated transcription factor (MITF) gene for the spotting traits. Association studies were conducted for candidate regions or genes known to affect pigmentation in dairy cattle.
Analysis of collinear regions of Oryza AA and CC genomes
Qi Feng, Tao Huang, Qiang Zhao, Jingjie Zhu, Zhixin Lin, Bin Han
2009, 36(11): 667-677. doi: 10.1016/S1673-8527(08)60159-9
Abstract (53) HTML PDF (0)
Abstract:
Comparative analyses of genome structure and sequence of closely related species have yielded insights into the evolution and function of plant genomes. A total of 103,844 BAC end sequences delegated ∼73.8 Mb of O. officinalis that belongs to the CC genome type of the rice genus Oryza were obtained and compared with the genome sequences of rice cultivar, O. sativa ssp. japonica cv. Nipponbare. We found that more than 45% ofO. officinalis genome consists of repeat sequences, which is higher than that of Nipponbare cultivar. To further investigate the evolutionary divergence of AA and CC genomes, two BAC-contigs of O. officinalis were compared with the collinear genomic regions of Nipponbare. Of 57 genes predicted in the AA genome orthologous regions, 39 had orthologs in the regions of the CC genome. Alignment of the orthologous regions indicated that the CC genome has undergone expansion in both genic and intergenic regions through primarily retroelement insertion. Particularly, the density of RNA transposable elements was 17.95% and 1.78% in O. officinalis and O. sativa, respectively. This explains why the orthologous region is about 100 kb longer in the CC genome in comparison to the AA genome.
Genetic analysis and molecular mapping of a novel gene for zebra mutation in rice (Oryza sativa L.)
Qiushi Wang, Xianchun Sang, Yinghua Ling, Fangming Zhao, Zhenglin Yang, Yunfeng Li, Guanghua He
2009, 36(11): 679-684. doi: 10.1016/S1673-8527(08)60160-5
Abstract (82) HTML PDF (0)
Abstract:
A novel zebra mutant, zebra-15, derived from the restorer line Jinhui10 (Oryza sativa L. ssp. indica) treated by EMS, displayed a distinctive zebra leaf from seedling stage to jointing stage. Its chlorophyll content decreased (55.4%) and the ratio of Chla/Chlb increased (90.2%) significantly in the yellow part of the zebra-15, compared with the wild type. Net photosynthetic rate and fluorescence kinetic parameters showed that the decrease of chlorophyll content significantly influenced the photosynthetic efficiency of the mutant. Genetic analysis of F2 segregation populations derived from the cross of Xinong1A and zebra-15 indicated that the zebra leaf trait is controlled by a single recessive nuclear gene. Ninety-eight out of four hundred and eighty pairs of SSR markers showed the diversity between the Xinong1A and the zebra-15, their F2 population was then used for gene mapping. Zebra-15 (Z-15) gene was primarily restricted on the short arm of chromosome 5 by 150 F2 recessive individuals, 19.6 cM from marker RM3322 and 6.0 cM from marker RM6082. Thirty-six SSR markers were newly designed in the restricted location, and the Z-15 was finally located between markers nSSR516 and nSSR502 with the physical region 258 kb by using 1,054 F2 recessive individuals.
A statistical procedure to assess the significance level of barriers to gene flow
Sébastien Rioux Paquette, François-Joseph Lapointe
2009, 36(11): 685-693. doi: 10.1016/S1673-8527(08)60161-7
Abstract (63) HTML PDF (0)
Abstract:
Although several methods are available to study the extent of isolation by distance (IBD) among natural populations, comparatively few exist to detect the presence of sharp genetic breaks in genetic distance datasets. In recent years, Monmonier's maximum-difference algorithm has been increasingly used by population geneticists. However, this method does not provide means to measure the statistical significance of such barriers, nor to determine their relative contribution to population differentiation with respect to IBD. Here, we propose an approach to assess the significance of genetic boundaries. The method is based on the calculation of a multiple regression from distance matrices, where binary matrices represent putative genetic barriers to test, in addition to geographic and genetic distances. Simulation results suggest that this method reliably detects the presence of genetic barriers, even in situations where IBD is also significant. We also illustrate the methodology by analyzing previously published datasets. Conclusions about the importance of genetic barriers can be misleading if one does not take into consideration their relative contribution to the overall genetic structure of species.