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. 2024 Dec 16:15:1499055.
doi: 10.3389/fpls.2024.1499055. eCollection 2024.

Meta-QTL mapping for wheat thousand kernel weight

Affiliations

Meta-QTL mapping for wheat thousand kernel weight

Chao Tan et al. Front Plant Sci. .

Abstract

Wheat domestication and subsequent genetic improvement have yielded cultivated species with larger seeds compared to wild ancestors. Increasing thousand kernel weight (TKW) remains a crucial goal in many wheat breeding programs. To identify genomic regions influencing TKW across diverse genetic populations, we performed a comprehensive meta-analysis of quantitative trait loci (MQTL), integrating 993 initial QTL from 120 independent mapping studies over recent decades. We refined 242 loci into 66 MQTL, with an average confidence interval (CI) 3.06 times smaller than that of the original QTL. In these 66 MQTL regions, a total of 4,913 candidate genes related to TKW were identified, involved in ubiquitination, phytohormones, G-proteins, photosynthesis, and microRNAs. Expression analysis of the candidate genes showed that 95 were specific to grain and might potentially affect TKW at different seed development stages. These findings enhance our understanding of the genetic factors associated with TKW in wheat, providing reliable MQTL and potential candidate genes for genetic improvement of this trait.

Keywords: QTL mapping; genetic populations; meta-analysis; thousand kernel weight; wheat.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Analysis of collected 993 QTL. (A) Number of initial and projected QTL in the DH, F2 and RIL population. (B) Number of QTL on each chromosome. (C) Confidence intervals of the initial QTL in the DH, F2 and RIL population. (D). Individual PVE of QTL in the DH, F2 and RIL population.
Figure 2
Figure 2
Comparison of mean CI for initial QTL and MQTL.
Figure 3
Figure 3
Distribution of the MQTL on chromosomes. (A) On the chromosome 1A, 1B, 1D, 2A, 2B, 2D, 3B, 4A, 5B, 5D, 6B, 6D, and 7A in the DH population. (B) On the chromosome 1A, 1B, 1D, 2A, 2B, 3A, 3B, 3D, 4A, 4D, 5B, 5D, 7A, and 7D in the F2 population. (C) On the chromosome 3B, 5B, and 7B in the RILpopulation. Original TKW QTLs were detected and are represented by red bars. Black bars within the chromosomes indicate marker density, and to the right of these bars is the distance in cM along with the marker names.
Figure 4
Figure 4
SNPs density in the (A). DH populations and (B) F2 populations.
Figure 5
Figure 5
(A) KEGG pathway enrichment of 95 candidate genes. (B) GO terms for 95 candidate genes underlying MQTL interval for thousand kernel weight.
Figure 6
Figure 6
Heatmap showing the differential expression levels of 95 candidate genes.

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