An integrative GWAS, Transcriptomic, and domestication analysis Uncovers Multi-Layered genetic architecture of kernel rate in maize testcross hybrids.

Authors

Xuehang Xiong, Haiyang Duan, Dong Ding, Jihua Tang, Xuehai Zhang

Published in

Journal of advanced research. Nov 02, 2026. Epub Nov 02, 2026.

Abstract

Improving yield efficiency in maize (Zea mays L.) is increasingly important under high-density production systems, where gains from total biomass accumulation are approaching physiological limits. Kernel Rate (KR), or shelling percentage, captures reproductive biomass partitioning within the ear but remains less well characterized genetically than absolute yield components.
Here, we evaluated KR together with ear weight (EW), cob weight (CW), and kernel weight (KW) in two testcross populations generated with Mo17 and Zheng58 and assessed across six year-by-location environments. KR was highly heritable, showed only weak correlations with EW, and was consistently negatively correlated with CW, supporting its use as an index of relative kernel-to-cob biomass allocation.
To investigate the genetic basis of this variation, we applied an integrative analytical framework combining testcross-based genome-wide association studies (GWAS), comparative parental-line transcriptomic comparisons associated with extreme F₁ testcross performance, and population genomic signals from domestication scans. Rather than identifying a single set of causal genes, this approach revealed limited overlap among data layers, indicating that yield efficiency is shaped by multiple, context-dependent genetic contributions.
GWAS identified multiple trait-associated loci with limited overlap across environments and tester backgrounds; two CW associations also met FDR_BH < 0.05. Parental-line PCA showed partial but incomplete differentiation between high- and low-performance groups. PERMANOVA attributed 18.8-23.4 % of transcriptomic variation to group membership, with significant differences for CW and KW and weaker evidence for EW and KR. Integration of association, expression, and evolutionary evidence prioritized representative candidates including FDPS3, PFK/FBPase, and Zm00001d038275.
These results support a multi-layered and context-dependent genetic basis of biomass partitioning in maize testcross hybrids. The integrative framework provides biologically informed candidate priorities for functional validation and breeding across additional testers and environments.

PMID:
42971351
Bibliographic data and abstract were imported from PubMed on 03 Nov 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.