Evolutionary aspects of direct or indirect selection for seed size and seed metabolites in Brassica juncea and diploid progenitor species

Integrated analysis of BSA-seq and RNA-seq identified the candidate genes for seed weight in Brassica juncea

Introduction

Brassica juncea is a major oilseed crop of Brassica. The seed weight is one of yield components in oilseed Brassica crops. Research on the genetic mechanism of seed weight is not only directly related to the yield and economic value of Brassica juncea but also can provide a theory foundation for studying other Brassica crops.

Methods

To map the genes for seed weight, the parental and F2 extreme bulks derived were constructed from the cross between the heavy-seeded accession 7981 and the light-seeded one Sichuan yellow (SY) of B. juncea, and used in bulk segregant sequencing (BSA-seq). Meanwhile, RNA-sequencing (RNA-seq) was performed for both parents at six seed development stages.

Results

Our results showed that a total of thirty five SNPs were identified in thirty two genes located on chromosomes A02 and A10, while fifty eight InDels in fifty one genes located on A01, A03, A05, A07, A09, A10, B01, B02 and B04. The 7,679 differentially expressed genes were identified in developing seeds between the parents. Furthermore, integrated analysis of BSA-seq and RNA-seq data revealed a cluster of nine genes on chromosome A10 and one gene on chromosome A05 that are putative candidate genes controlling seed weight in B. juncea.

Discussion

This study provides a new reference for research on Brassica seed weight and lays a solid foundation for the examination of seed in other Brassica crops.

Transcriptome analysis reveals cell cycle-related transcripts as key determinants of varietal differences in seed size of Brassica juncea

Brassica juncea is an important oilseed crop, widely grown as a source of edible oil. Seed size is a pivotal agricultural trait in oilseed Brassicas. However, the regulatory mechanisms underlying seed size determination are poorly understood. To elucidate the transcriptional dynamics involved in the determination of seed size in B. juncea, we performed a comparative transcriptomic analysis using developing seeds of two varieties, small-seeded Early Heera2 (EH2) and bold-seeded Pusajaikisan (PJK), at three distinct stages (15, 30 and 45 days after pollination). We detected 112,550 transcripts, of which 27,186 and 19,522 were differentially expressed in the intra-variety comparisons and inter-variety comparisons, respectively. Functional analysis using pathway, gene ontology, and transcription factor enrichment revealed that cell cycle- and cell division-related transcripts stay upregulated during later stages of seed development in the bold-seeded variety but are downregulated at the same stage in the small-seeded variety, indicating that an extended period of cell proliferation in the later stages increased seed weight in PJK as compared to EH2. Further, k-means clustering and candidate genes-based analyses unravelled candidates for employing in seed size improvement of B. juncea. In addition, candidates involved in determining seed coat color, oil content, and other seed traits were also identified.

Comparative Analysis of Seed Transcriptome and Coexpression Analysis Reveal Candidate Genes for Enhancing Seed Size/Weight in Brassica juncea

Seed size/weight is a multigenic trait that is governed by complex transcriptional regulatory pathways. An understanding of the genetic basis of seed size is of great interest in the improvement of seed yield and quality in oilseed crops. A global transcriptome analysis was performed at the initial stages of seed development in two lines of Brassica juncea, small-seeded EH-2 and large-seeded PJ. The anatomical analyses revealed significant differences in cell number and cell size in the outer layer of the seed coat between EH-2 and PJ. Pairwise comparisons at each developmental stage identified 5,974 differentially expressed genes (DEGs) between the two lines, of which 954 genes belong to different families of transcription factors. Two modules were found to be significantly correlated with an increased seed size using weighted gene coexpression network analysis. The DEG and coexpression datasets were integrated with the thousand seed weight (Tsw) quantitative trait loci (QTL) mapped earlier in the EPJ (EH-2 × PJ) doubled haploid (DH) population, which identified forty potential key components controlling seed size. The candidate genes included genes regulating the cell cycle, cell wall biogenesis/modification, solute/sugar transport, and hormone signaling. The results provide a valuable resource to widen the current understanding of regulatory mechanisms underlying seed size in B. juncea.

Meta-analysis: Congruence of genomic and phenotypic differentiation across diverse natural study systems

Linking genotype to phenotype is a primary goal for understanding the genomic underpinnings of evolution. However, little work has explored whether patterns of linked genomic and phenotypic differentiation are congruent across natural study systems and traits. Here, we investigate such patterns with a meta-analysis of studies examining population-level differentiation at subsets of loci and traits putatively responding to divergent selection. We show that across the 31 studies (88 natural population-level comparisons) we examined, there was a moderate (R 2 = 0.39) relationship between genomic differentiation (F ST ) and phenotypic differentiation (P ST ) for loci and traits putatively under selection. This quantitative relationship between P ST and F ST for loci under selection in diverse taxa provides broad context and cross-system predictions for genomic and phenotypic adaptation by natural selection in natural populations. This context may eventually allow for more precise ideas of what constitutes "strong" differentiation, predictions about the effect size of loci, comparisons of taxa evolving in nonparallel ways, and more. On the other hand, links between P ST and F ST within studies were very weak, suggesting that much work remains in linking genomic differentiation to phenotypic differentiation at specific phenotypes. We suggest that linking genotypes to specific phenotypes can be improved by correlating genomic and phenotypic differentiation across a spectrum of diverging populations within a taxon and including wide coverage of both genomes and phenomes.

R. Patiranage D, Johansen K, Schmöckel SM, Bertero D, Oakey H, Colque-Little C, Afzal I, Raubach S, Miller N, Streich J, Amby DB, Emrani N, Warmington M, Mousa MAA, Wu D, Jacobson D, Andreasen C, Jung C, Murphy K, Bazile D, Tester M, on behalf of the Quinoa Phenotyping Consortium. Quinoa Phenotyping Methodologies: An International Consensus

Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.

Genome wide association mapping and candidate gene analysis for pod shatter resistance in Brassica juncea and its progenitor species

We investigated phenotypic variations for pod shattering, pod length and number of seeds per pod in large germplasm collections of Brassica juncea (2n = 36; AABB) and its progenitor species, B. rapa (2n = 20; AA) and B. nigra (2n = 16; BB). Pod shatter resistance was measured as energy required for rupturing a mature dry pod, with a specially fabricated pendulum machine. Rupture energy (RE) ranged from 3.3 to 11.0 mJ in B. juncea. MCP 633, NR 3350 and Albeli required maximum energy to shatter a pod. It ranged from 2.5 to 7.8 mJ for B. rapa with an average of 5.5 mJ. B. nigra possessed easy to rupture pods. Correlation analysis showed strong associations among these traits in B. juncea and B. rapa. Genome wide association studies were conducted with select sets of B. juncea and B. rapa germplasm lines. Significant and annotated associations predict the role of FRUITFULL, MANNASE7, and NAC secondary wall thickening promoting factor (NST2) in the genetic regulation of shatter resistance in B. juncea. NST2 and SHP1 appeared important for pod length and seeds per pod in B. rapa. Candidate gene based association mapping also confirmed the role of SHP1 and NST2 in regulating pod shattering and related pod traits in B. rapa and B. juncea. Footprints of selection were detected in SHP1, SHP2 (B. rapa, B. nigra and B. juncea), RPL (B. rapa) and NAC (B. juncea). Our results provide insights into the genetic architecture of three pod traits. The identified genes are relevant to improving and securing crop productivity of mustard crop.