No abstract

Genome-wide association studies (GWAS) have uncovered genetic variants susceptible to brain disorders. However, due to the complex pathogenesis of these diseases and heterogeneity of the brain tissues, how and through which the genetic variants confer risk for brain abnormalities and brain disorders remain elusive, especially from a multi-omics perspective and in the context of brain regions. In this study, we integrated brain region-specific transcriptomics, proteomics, and imaging genetics data by systematically applying transcriptome- and proteome-wide association analysis, Mendelian randomization, and Bayesian colocalization methods. At both gene expression and protein abundance levels, this integrative study identified 51 associations linking 42 targets to structural alterations of 10 brain regions. Additionally, we validated the causal effects of 20 identified genes on one or more brain disorders. Our analysis further illuminated the significant enrichment of 12 targets in five main types of brain cells. Overall, this study underscored the utility of a multi-omics and region-specific approach in understanding the pathogenesis of complex brain abnormalities and brain disorders.

Northeast China is a major soybean production region in China. A representative sample of the Northeast China soybean germplasm population (NECSGP) composed of 361 accessions was evaluated for their seed protein content (SPC) in Tieling, Northeast China. This SPC varied greatly, with a mean SPC of 40.77%, ranging from 36.60 to 46.07%, but it was lower than that of the Chinese soybean landrace population (43.10%, ranging from 37.51 to 50.46%). The SPC increased slightly from 40.32–40.97% in the old maturity groups (MG, MGIII + II + I) to 40.93–41.58% in the new MGs (MG0 + 00 + 000). The restricted two-stage multi-locus genome-wide association study (RTM-GWAS) with 15,501 SNP linkage-disequilibrium block (SNPLDB) markers identified 73 SPC quantitative trait loci (QTLs) with 273 alleles, explaining 71.70% of the phenotypic variation, wherein 28 QTLs were new ones. The evolutionary changes of QTL-allele structures from old MGs to new MGs were analyzed, and 97.79% of the alleles in new MGs were inherited from the old MGs and 2.21% were new. The small amount of new positive allele emergence and possible recombination between alleles might explain the slight SPC increase in the new MGs. The prediction of recombination potentials in the SPC of all the possible crosses indicated that the mean of SPC overall crosses was 43.29% (+2.52%) and the maximum was 50.00% (+9.23%) in the SPC, and the maximum transgressive potential was 3.93%, suggesting that SPC breeding potentials do exist in the NECSGP. A total of 120 candidate genes were annotated and functionally classified into 13 categories, indicating that SPC is a complex trait conferred by a gene network.