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Sequence validation of candidates for selectively important genes in sunflower.

ABSTRACT: Analyses aimed at identifying genes that have been targeted by past selection provide a powerful means for investigating the molecular basis of adaptive differentiation. In the case of crop plants, such studies have the potential to not only shed light on important evolutionary processes, but also to identify genes of agronomic interest. In this study, we test for evidence of positive selection at the DNA sequence level in a set of candidate genes previously identified in a genome-wide scan for genotypic evidence of selection during the evolution of cultivated sunflower. In the majority of cases, we were able to confirm the effects of selection in shaping diversity at these loci. Notably, the genes that were found to be under selection via our sequence-based analyses were devoid of variation in the cultivated sunflower gene pool. This result confirms a possible strategy for streamlining the search for adaptively-important loci process by pre-screening the derived population to identify the strongest candidates before sequencing them in the ancestral population.

SUBMITTER: Chapman MA

PROVIDER: S-EPMC3753318 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Sequence validation of candidates for selectively important genes in sunflower.

Chapman Mark A MA Mandel Jennifer R JR Burke John M JM

PloS one 20130826 8

Analyses aimed at identifying genes that have been targeted by past selection provide a powerful means for investigating the molecular basis of adaptive differentiation. In the case of crop plants, such studies have the potential to not only shed light on important evolutionary processes, but also to identify genes of agronomic interest. In this study, we test for evidence of positive selection at the DNA sequence level in a set of candidate genes previously identified in a genome-wide scan for ...[more]

PMID: 23991009

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Project description:Compared with the traditional gene expression techniques of quantitative analysis, RT-qPCR is most widely used because of its low cost, time-saving, and accuracy. It is essential to introduce suitable internal reference genes as reference corrections in RT-qPCR experiments to reduce the RNA quality and reverse transcription efficiency of different samples. In our study, we chose the candidate internal reference genes of alfalfa from transcriptome sequence datasets (162 RNA-seq sequencing data) through comparative analysis. Finally, 10 candidate reference genes were selected. These candidate reference gene expressions were determined by RT-qPCR under five abiotic stresses of drought, alkali, high temperature, low temperature, and acid treatments. The stability index of these candidate genes was calculated and evaluated correspondently using specific software and different lgorithms, such as GeNorm, Normfinder, Bestkeeper, ΔCt method, and an online analysis tool RefFinder. Then the appropriate candidate genes were screened strictly; and validated by the phyA gene. GAPDH and Actin are taken as traditional reference genes on gene expression of quantitative analysis commonly used in alfalfa, Our results showed GAPDH and Actin aren't the most appropriate reference genes of alfalfa under different abiotic stresses, under alkaline stress, the optimal reference gene is UBL-2a, and the optimal combination of reference genes is MS.65,463 (some candidate reference genes haven't been annotated yet, using gene ID abbreviation number of Medicago sativa L. instead )and UBL-2a; Under drought stress, the optimal reference gene is Ms.33,066, and the optimal combination of reference genes is MS.65,463 and UBL-2a; Under high-temperature stress, the optimal reference gene is Actin, and the optimal combination of reference genes is Rer1, Actin, MS.00617, MS.74,923, UBL-2a, MS.33,066, MS.99,505, and MS.65,463; Under low-temperature stress, the optimal reference gene is Actin, and the optimal combination of reference genes is Rer1, Actin, MS.99,505, MS.073307, and UBL-2a. The optimal reference genes and their combinations need further validation under acid stress. This paper provides scientific evidence for quantitative analysis of the genes of alfalfa.

Dataset Information

Sequence validation of candidates for selectively important genes in sunflower.

Publications

Sequence validation of candidates for selectively important genes in sunflower.

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