Zhang Ya-Wen, Wen Yang-Jun, Dunwell Jim M, Zhang Yuan-Ming
Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
Comput Struct Biotechnol J. 2019 Dec 9;18:59-65. doi: 10.1016/j.csbj.2019.11.005. eCollection 2020.
The methodologies and software packages for mapping quantitative trait loci (QTLs) in bi-parental segregation populations are well established. However, it is still difficult to detect small-effect and linked QTLs. To address this issue, we proposed a genome-wide composite interval mapping (GCIM) in bi-parental segregation populations. To popularize this method, we developed an R package. This program with two versions (Graphical User Interface: QTL.gCIMapping.GUI v2.0 and code: QTL.gCIMapping v3.2) can be used to identify QTLs for quantitative traits in recombinant inbred lines, doubled haploid lines, backcross and F populations. To save running time, fread function was used to read the dataset, parallel operation was used in parameter estimation, and conditional probability calculation was implemented by C++. Once one input file with *.csv or *.txt formats is uploaded into the package, one or two output files and one figure can be obtained. The input file with the ICIM and win QTL cartographer formats is available as well. Real data analysis for 1000-grain weight in rice showed that the GCIM detects the maximum previously reported QTLs and genes, and has the minimum AIC value in the stepwise regression of all the identified QTLs for this trait; using stepwise regression and empirical Bayesian analyses, there are some false QTLs around the previously reported QTLs and genes from the CIM method. The above software packages on Windows, Mac and Linux can be downloaded from https://cran.r-project.org/web/packages/ or https://bigd.big.ac.cn/biocode/tools/7078/releases/27 in order to identify all kinds of omics QTLs.
用于在双亲分离群体中定位数量性状基因座（QTL）的方法和软件包已经很成熟。然而，检测小效应和连锁QTL仍然很困难。为了解决这个问题，我们提出了一种在双亲分离群体中的全基因组复合区间定位（GCIM）方法。为了推广这种方法，我们开发了一个R包。这个程序有两个版本（图形用户界面：QTL.gCIMapping.GUI v2.0和代码：QTL.gCIMapping v3.2），可用于鉴定重组自交系、加倍单倍体系、回交群体和F群体中数量性状的QTL。为了节省运行时间，使用fread函数读取数据集，在参数估计中使用并行操作，并通过C++实现条件概率计算。一旦将一个*.csv或*.txt格式的输入文件上传到该包中，就可以获得一个或两个输出文件和一个图。也可以使用具有ICIM和win QTL cartographer格式的输入文件。对水稻千粒重的实际数据分析表明，GCIM检测到的先前报道的QTL和基因最多，并且在该性状所有已鉴定QTL的逐步回归中AIC值最小；使用逐步回归和经验贝叶斯分析，CIM方法在先前报道的QTL和基因周围存在一些假QTL。上述软件包可在Windows、Mac和Linux系统上从https://cran.r-project.org/web/packages/ 或https://bigd.big.ac.cn/biocode/tools/7078/releases/27下载，以便鉴定各种组学QTL。
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