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Association mapping is an alternative to mapping in a biparental population. A key to successful association mapping is to avoid spurious associations by controlling for population structure. Confirming the marker/trait association in an independent population is necessary for the implementation of the marker in other genetic studies. Two independent soybean populations consisting of advanced breeding lines representing the diversity within maturity groups 00, 0, and I were screened in multi-site, replicated field trials to discover molecular markers associated with iron deficiency chlorosis (IDC), a major yield-limiting factor in soybean. Lines with extreme phenotypes were initially screened to identify simple sequence repeat (SSR) markers putatively associated with the IDC. Marker data collected from all lines were used to control for population structure and kinship relationships. Single factor analysis of variance (SFA) and mixed linear model (MLM) analyses were used to discover marker/trait associations. The MLM analyses, which include population structure, kinship or both factors, reduced the number of markers significantly associated with IDC by 50% compared with SFA. With the MLM approach, three markers were found to be associated with IDC in the first population. Two of these markers, Satt114 and Satt239, were also found to be associated with IDC in the second confirmation population. For both populations, those lines with the tolerance allele at both these two marker loci had significantly lower IDC scores than lines with one or no tolerant alleles.

The noninfectious HIV-1 transgenic (HIV-1Tg) rat was developed as a model of AIDs-related pathology and immune dysfunction by manipulation of a noninfectious HIV-1gag-pol virus with a deleted 3-kb SphI-MscI fragment containing the 3′ -region of gag and the 5′ region of pol into F344 rats. Our previous studies revealed significant behavioral differences between HIV-1Tg and F344 control rats in their performance in the Morris water maze and responses to psychostimulants. However, the molecular mechanisms underlying these behavioral differences remain largely unknown. The primary goal of this study was to identify differentially expressed genes and enriched pathways affected by the gag-pol-deleted HIV-1 genome. Using RNA deep sequencing, we sequenced RNA transcripts in the prefrontal cortex, hippocampus, and striatum of HIV-1Tg and F344 rats. A total of 72 RNA samples were analyzed (i.e., 12 animals per group × 2 strains × 3 brain regions). Following deep-sequencing analysis of 50-bp paired-end reads of RNA-Seq, we used Bowtie/Tophat/Cufflinks suites to align these reads into transcripts based on the Rn4 rat reference genome and to measure the relative abundance of each transcript. Statistical analyses on each brain region in the two strains revealed that immune response- and neurotransmission-related pathways were altered in the HIV-1Tg rats, with brain region differences. Other neuronal survival-related pathways, including those encoding myelin proteins, growth factors, and translation regulators, were altered in the HIV-1Tg rats in a brain region-dependent manner. This study is the first deep-sequencing analysis of RNA transcripts associated the HIV-1Tg rat. Considering the functions of the pathways and brain regions examined in this study, our findings of abnormal gene expression patterns in HIV-1Tg rats suggest mechanisms underlying the deficits in learning and memory and vulnerability to drug addiction and other psychiatric disorders observed in HIV-positive patients.

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