Genome-wide association study and genomic prediction of root system architecture traits in Sorghum (Sorghum bicolor (L.) Moench) at the seedling stage

BMC Plant Biology, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 17, 2025

Root system architecture (RSA) plays an important role in plant adaptation to drought stress. However, the genetic basis of RSA sorghum has not been adequately elucidated. This study aimed investigate bases traits through genome-wide association studies (GWAS) and determine genomic prediction (GP) accuracy landraces at seedling stage. Phenotypic data for nodal root angle (NRA), number roots (NNR), length (NRL), fresh shoot weight (FSW), dry (DSW), leaf area (LA) were collected from 160 accessions grown soil-based rhizotrons. The panel was genotyped with 5,000 single nucleotide polymorphism (SNP) markers use current GWAS GP studies. A multi-locus model, Fixed random model Circulating Probability Unification (FarmCPU), applied analysis. For GP, ridge-regression best linear unbiased (RR-BLUP) five different Bayesian models applied. total 17 SNP loci significantly associated studied identified, which nine are novel loci. Among traits, highest significant marker-trait associations (MTAs) identified on chromosomes 1, 3, 6, 7. that explain proportion phenotypic variance (PVE) include sbi32853830 (PVE = 18.2%), sbi29954292 18.1%), sbi24668980 10.8%), sbi3022983 7%), sbi29897704 6.4%) sbi29897694 5.3%) NNR, LA, SDW, NRA, NRL SFW, respectively. estimated using ranged 0.30 0.63 while it 0.35 0.60 when RR-BLUP used. observed moderate high each trait suggests selection could be a feasible approach RSA-targeted breeding. Overall, present provides insights into offers opportunity speed up breeding drought-tolerant varieties.

Language: Английский

LncRAnalyzer: Uncovering Long Non-Coding RNAs and Exploring Gene Co-expression Patterns in Sorghum Genomics

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 25, 2024

Abstract Sorghum ( bicolor L. Moench ) is a versatile crop with significant phenotypic and genetic diversity. Despite the availability of multiple re-sequenced sorghum genomes, non-coding regions remain underexplored. Long RNAs (lncRNAs), major class RNAs, low expression levels, complex patterns, can be identified using RNA-seq. However, distinguishing lncRNAs from protein-coding genes challenging due to their abundance tissue-specific expressions. This study developed an automated pipeline for identifying Novel Protein Coding Transcripts (NPCTs) RNA-seq datasets. Using dual reference genome scheme, we 8770 in BTX642 (33.35% cultivar-specific) 8869 RTX430 (30.72% cultivar-specific). Some were linked pre- post-flowering drought tolerance BTX642, respectively. The NPCTs encoded elements such as RE-1, TNT, Zinc finger (zf) protein, FAR1 related, Xylan glucosyltransferase suggesting involvement drought-specific phenotype development. Target predictions revealed both cis- trans-regulated associated peroxidase, glutathione S-transferase, MYB TFs during drought, emphasizing role tolerance. Differentially expressed leaf root tissues (p-value < 0.05, |log2fold| > 2), that most abundant regulate C2H2-GATA, DUF domain, WD-40. Downstream gene co-expression analysis showed time point-specific lncRNA interactions TFs, highlighting roles response sorghum. Our LncRAnalyzer NPCTs, integrated them into networks provided deeper insights

Language: Английский