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Biology subjects

Xue Gao

Publications and source records attributed to Xue Gao.

2 recordsLinked to original sources

Atp6v1b2 Plays Important Roles in the Early Development of Hearing, the Pectoral Fin, the Cardiovascular System, and the Swim Bladder of the Zebrafish, Supporting a Role for the Gene in Syndromic Hearing Loss

BackgroundThe ATP6V1B2 gene plays a critical role in the auditory system, and a mutation in this gene is one genetic cause of DDOD syndrome (Dominant deafness-onychodystrophy syndrome, MIM 124480) and ZLS (Zimmermann-Laband syndrome, MIM 135500). However, whether and how ATP6V1B2 is involved in the development of other organs remains unknown. In the present study, we explored the effect of atp6v1b2 knockdown on early zebrafish development and verified that this gene plays a role in syndromic hearing loss.\n\nMethodsThree morpholinos (two splice-blocking, one translation-blocking) and the atp6v1b2 c.1516 C>T plasmid were used to knockdown or overexpress atp6v1b2 in zebrafish after microinjection of fertilised embryos. Control and atp6v1b2 embryo morphants were evaluated 6 days post-fertilisation in terms of motility, apoptosis, pectoral fin development, and hair cell number.\n\nResultsAtp6v1b2-knockdown zebrafish exhibited decreased body length, pericardial oedema, hair cell loss, a non-inflated swim bladder, and shorter pectoral fins; the first three phenotypes were also evident in fish overexpressing the gene.\n\nConclusionsAtp6v1b2 plays important roles in the development of hearing, the pectoral fin, the cardiovascular system, and the swim bladder, thereby supporting a role for this gene in syndromic hearing loss.

Genetics

Improving the Efficiency of Genomic Selection in Chinese Simmental beef cattle

Genomic selection is an accurate and efficient method of estimating genetic merits by using high-density genome-wide single nucleotide polymorphisms (SNPs).In this study, we investigate an approach to increase the efficiency of genomic prediction by using genome-wide markers. The approach is a feature selection based on genomic best linear unbiased prediction (GBLUP),which is a statistical method used to predict breeding values using SNPs for selection in animal and plant breeding. The objective of this study is the choice of kinship matrix for genomic best linear unbiased prediction (GBLUP).The G-matrix is using the information of genome-wide dense markers. We compare three kinds of kinships based on different combinations of centring and scaling of marker genotypes. And find a suitable kinship approach that adjusts for the resource population of Chinese Simmental beef cattle. Single nucleotide polymorphism (SNPs) can be used to estimate kinship matrix and individual inbreeding coefficients more accurately. So in our research a genomic relationship matrix was developed for 1059 Chinese Simmental beef cattle using 640000 single nucleotide polymorphisms and breeding values were estimated using phenotypes about Carcass weight and Sirloin weight. The number of SNPs needed to accurately estimate a genomic relationship matrix was evaluated in this population. Another aim of this study was to optimize the selection of markers and determine the required number of SNPs for estimation of kinship in the Chinese Simmental beef cattle.\n\nWe find that the feature selection of GBLUP using Xus and the Astle and Baldings kinships model performed similarly well, and were the best-performing methods in our study. Inbreeding and kinship matrix can be estimated with high accuracy using [≥]12,000s in Chinese Simmental beef cattle.

Genomics