Qin Yan | Search bioRxiv

bioRxiv2015

A mechanistic model of linkage analysis in allohexaploids

Despite their pivotal role in agriculture and biological research, polyploids, a group of organisms with more than two sets of chromosomes, are very difficult to study. Increasing studies have used high-density genetic linkage maps to investigate the genome structure and function of polyploids and to identify genes underlying polyploid traits. However, although models for linkage analysis have been well established for diploids, with some essential modifications for tetraploids, no models have been available thus far for polyploids at higher ploidy levels. The linkage analysis of polyploids typically requires knowledge about their meiotic mechanisms, depending on the origin of polyplody. Here we describe a computational modeling framework for linkage analysis in allohexaploids by integrating their preferential chromosomal-pairing meiotic feature into a mixture model setting. The framework, implemented with the EM algorithm, allows the simultaneous estimates of preferential pairing factors and the recombination fraction. We investigated statistical properties of the framework through extensive computer simulation and validated its usefulness and utility by analyzing a real data from a full-sib family of allohexaploid persimmon. Our attempt in linkage analysis of allohexaploids by incorporating their meiotic mechanism lays a foundation for allohexaploid genetic mapping and also provides a new horizon to explore allohexaploid parental kinship.

Genetics↗

bioRxiv2015

Single molecule targeted sequencing for cancer gene mutation detection

With the rapid decline cost of sequencing, it is now clinically affordable to examine multiple genes in a single disease-targeted test using next generation sequencing. Current targeted sequencing methods require a separate step of targeted capture enrichment during sample preparation before sequencing, and the library preparation process is labor intensive and time consuming. Here, we introduced an amplification-free Single Molecule Targeted Sequencing (SMTS) technology, which combined targeted capture and sequencing in one step. We demonstrated that this technology can detect low-frequency mutations of cancer genes. SMTS has several advantages, namely that it requires little sample preparation and avoids biases and errors introduced by PCR reaction. SMTS can be applied in cancer gene mutation detection, inherited condition screening and noninvasive prenatal diagnosis.

Genomics↗