Key message
Genetic mapping, genomic profiling and bioinformatic approaches were used to identify putative resistance genes for ear rots and low mycotoxin contamination in maize. Genomic selection ...seems to have good perspectives.
Maize is globally an indispensable crop for humans and livestock. About 30% of yield is lost by fungal diseases with Gibberella, Fusarium and Aspergillus ear rots (ERs) having a high economic impact in most maize-growing regions of the world. They reduce not only yield, but also contaminate grains with mycotoxins like deoxynivalenol, zearalenone, fumonisins and aflatoxins, respectively. These mycotoxins pose serious health problems to humans and animals. A number of studies have been conducted to dissect the genetic architecture of resistance to these three major ear rots over the past decade. The review concentrates on studies carried out to locate quantitative trait loci (QTL) and candidate genes (CG) on the maize genome as well as the application of genomic selection in maize for resistance against
Fusarium graminearum
,
Fusarium verticillioides
and
Aspergillus flavus
. QTL studies by linkage or genome-wide association mapping, omic technologies (genomics, proteomics, transcriptomics and metabolomics) and bioinformatics are the methods used in the current studies to propose resistance genes against ear rot pathogens. Though a number of QTL and CG are reported, only a few specific genes were found to directly confer ER resistance in maize. A combination of two or more gene identification methods would provide a more powerful and reliable tool. Genomic selection seems to be promising for ER resistance breeding, but there are only a limited number of studies in this area. A strategy that can accurately validate and predict genotypes with major effect QTL and CG for selection will be worthwhile for practical breeding against ERs and mycotoxin contamination in maize.
Protein kinases are major players in various signal transduction pathways. Understanding the molecular mechanisms behind plant responses to biotic and abiotic stresses has become critical for ...developing and breeding climate‐resilient crops. In this review, we summarize recent progress on understanding plant drought, salt, and cold stress responses, with a focus on signal perception and transduction by different protein kinases, especially sucrose nonfermenting1 (SNF1)‐related protein kinases (SnRKs), mitogen‐activated protein kinase (MAPK) cascades, calcium‐dependent protein kinases (CDPKs/CPKs), and receptor‐like kinases (RLKs). We also discuss future challenges in these research fields.
This review summarizes the main progresses on signal perception and transduction mediated by different protein kinases in plant responses to drought, salt, and cold stress, and discusses some future challenges in these research fields.
Key message
We clarify the influence of the genotypes of the heading date genes
Hd1
,
Ghd7
,
DTH8
, and
PRR37
and their combinations on yield-related traits and the functional differences between ...different haplotypes.
Heading date is a key agronomic trait in rice (
Oryza sativa
L.) that determines yield and adaptability to different latitudes.
Heading date 1
(
Hd1
),
Grain number, plant height, and heading date 7
(
Ghd7
),
Days to heading on chromosome 8
(
DTH8
), and
PSEUDO-RESPONSE REGULATOR 37
(
PRR37
) are core rice genes controlling photoperiod sensitivity, and these genes have many haplotypes in rice cultivars. However, the effects of different haplotypes at these genes on yield-related traits in diverse rice materials remain poorly characterized. In this study, we knocked out
Hd1
,
Ghd7
,
DTH8
, or
PRR37
, alone or together, in
indica
and
japonica
varieties and systematically investigated the agronomic traits of each knockout line.
Ghd7
and
PRR37
increased the number of spikelets and improved yield, and this effect was enhanced with the
Ghd7 DTH8
or
Ghd7 PRR37
combination, but
Hd1
negatively affected yield. We also identified a new weak functional
Ghd7
allele containing a mutation that interferes with splicing. Furthermore, we determined that the promotion or inhibition of heading date by different
PRR37
haplotypes is related to
PRR37
expression levels, day length, and the genetic background. For rice breeding, a combination of functional alleles of
Ghd7
and
DTH8
or
Ghd7
and
PRR37
in the
hd1
background can be used to increase yield. Our study clarifies the effects of heading date genes on yield-related traits and the functional differences among their different haplotypes, providing valuable information to identify and exploit elite haplotypes for heading date genes to breed high-yielding rice varieties.
Key message
Mating designs determine the realized additive genetic variance in a population sample. Deflated or inflated variances can lead to reduced or overly optimistic assessment of future ...selection gains.
The additive genetic variance
V
A
inherent to a breeding population is a major determinant of short- and long-term genetic gain. When estimated from experimental data, it is not only the additive variances at individual loci (QTL) but also covariances between QTL pairs that contribute to estimates of
V
A
. Thus, estimates of
V
A
depend on the genetic structure of the data source and vary between population samples. Here, we provide a theoretical framework for calculating the expectation and variance of
V
A
from genotypic data of a given population sample. In addition, we simulated breeding populations derived from different numbers of parents (
P
= 2, 4, 8, 16) and crossed according to three different mating designs (disjoint, factorial and half-diallel crosses). We calculated the variance of
V
A
and of the parameter
b
reflecting the covariance component in
V
A
,
standardized by the genic variance. Our results show that mating designs resulting in large biparental families derived from few disjoint crosses carry a high risk of generating progenies exhibiting strong covariances between QTL pairs on different chromosomes. We discuss the consequences of the resulting deflated or inflated
V
A
estimates for phenotypic and genome-based selection as well as for applying the usefulness criterion in selection. We show that already one round of recombination can effectively break negative and positive covariances between QTL pairs induced by the mating design. We suggest to obtain reliable estimates of
V
A
and its components in a population sample by applying statistical methods differing in their treatment of QTL covariances.
Key message
Segmental introgression and advanced backcross lines were developed and validated as important tools for improving agronomically important traits in pepper, offering improved sensitivity ...in detecting quantitative trait loci for breeding.
Segmental introgression lines (SILs) and advanced backcross lines (ABs) can accelerate genetics and genomics research and breeding in crop plants. This study presents the development of a complete collection of SILs and ABs in pepper using
Capsicum annuum
cv. ‘CM334’ as the recipient parent and
Capsicum baccatum
‘PBC81’, which displays various agronomically important traits including powdery mildew and anthracnose resistance, as donor parent. Using embryo rescue to overcome abortion in interspecific crosses, and marker-assisted selection with genotyping-in-thousands by sequencing (GT-seq) to develop SILs and ABs containing different segments of the
C. baccatum
genome, we obtained 63 SILs and 44 ABs, covering 94.8% of the
C. baccatum
genome. We characterized them for traits including powdery mildew resistance, anthracnose resistance, anthocyanin accumulation, trichome density, plant architecture, and fruit morphology. We validated previously known loci for these traits and discovered new sources of variation and quantitative trait loci (QTLs). A total of 15 QTLs were identified, including four for anthracnose resistance with three novel loci, seven for plant architecture, and four for fruit morphology. This is the first complete collection of pepper SILs and ABs validated for agronomic traits and will enhance QTL detection and serve as valuable breeding resources. Further, these SILs and ABs will be useful for comparative genomics and to better understand the genetic mechanisms underlying important agronomic traits in pepper, ultimately leading to improved crop productivity and sustainability.
Key message
A novel leaf rust resistance locus located on a terminal segment (0–69.29 Mb) of Thinopyrum intermedium chromosome arm 7J
s
S has been introduced into wheat genome for disease resistance ...breeding.
Xiaoyan 78829, a wheat–
Thinopyrum intermedium
partial amphiploid, exhibits excellent resistance to fungal diseases in wheat. To transfer its disease resistance to common wheat (
Triticum aestivum
), we previously developed a translocation line WTT26 using chromosome engineering. Disease evaluation showed that WTT26 was nearly immune to 14 common races of leaf rust pathogen (
Puccinia triticina
) and highly resistant to Ug99 race PTKST of stem rust pathogen (
P
.
graminis
f. sp.
tritici
) at the seedling stage. It also displayed high adult plant resistance to powdery mildew (caused by
Blumeria graminis
f. sp.
tritici
). Cytogenetic and molecular marker analysis revealed that WTT26 carried a T4BS·7J
s
S chromosome translocation. Once transferred into the susceptible wheat genetic background, chromosome 7J
s
S exhibited its resistance to leaf rust, indicating that the resistance locus was located on this alien chromosome. To enhance the usefulness of this locus in wheat breeding, we further developed several new translocation lines with small
Th. intermedium
segments using irradiation and developed 124 specific markers using specific-locus amplified fragment sequencing, which increased the marker density of chromosome 7J
s
S. Furthermore, a refined physical map of chromosome 7J
s
S was constructed with 74 specific markers, and six bins were thus arranged according to the co-occurrence of markers and alien chromosome segments. Combining data from specific marker amplification and resistance evaluation, we mapped a new leaf rust resistance locus in the 0–69.29 Mb region on chromosome 7J
s
S. The translocation lines carrying the new leaf rust resistance locus and its linked markers will contribute to wheat disease-resistance breeding.
Key message
Four stable QTL for adult-plant resistance (APR) to powdery mildew were identified on chromosome arms 1DL, 2BS, 2DL, and 6BL in the widely grown Chinese wheat cultivar Bainong 64. These ...QTL had no effect on response to stripe rust or leaf rust.
Wheat powdery mildew, caused by
Blumeria graminis
f. sp.
tritici
(
Bgt
), is a devastating fungal disease. Seedlings of Chinese wheat Bainong 64 are susceptible to
Bgt
, but adult plants have maintained resistance since it was released in 1996. A population of 171 recombinant inbred lines (RILs) developed from cross Jingshuang 16/Bainong 64 (JS16/BN64) was used to dissect genetic components of powdery mildew resistance. A genetic map comprising 5383 polymorphic markers was constructed using the 15 K SNP chip and kompetitive allele-specific PCR (KASP) markers. Composite interval mapping identified four stable QTL with favorable alleles all from BN64 on chromosome arms 1DL, 2BS, 2DL, and 6BL in at least four environments. They accounted for 8.3%, 13.8%, 14.4%, and 9.0% of the total phenotypic variation explained (PVE) in maximum, respectively.
QPmjbr.caas-1DL
, situated about 22 Mb from centromere, is probably a new QTL.
QPmjbr.caas-2DL
located near the end of arm 2DL and explained the largest PVE. Using genetic maps populated with KASP markers,
QPmjbr.caas-2BS
and
QPmjbr.caas-6BL
were fine mapped to a 1.8 cM genetic intervals spanning 13.6 Mb (76.0–89.6 Mb) and 1.7 cM and 4.9 Mb (659.9–664.8 Mb), respectively. The four QTL independent of stripe rust and leaf rust resistance were validated for powdery mildew resistance in another RIL population related to BN64 and a cultivar panel using representative KASP markers. Since BN64 has been a leading cultivar and an important breeding parent in China, the QTL and markers reported in this study will be useful for marker-assisted selection of APR.
Key message
Lineage-specific evolution of
RCO
was described in Brassicaceae.
BjRCO.1
and
BjRCO.2
within the complex locus regulated highly lobed-leaf formation in
Brassica juncea
.
RCO
regulates the ...formation of lobed leaves in Brassicaceae species.
RCO
originated from the duplication of
LMI1
-type sequences and evolved through gene duplication and loss within the Brassicaceae. However, the evolutionary process and diversification of
RCO
in different lineages of Brassicaceae remain unclear. Although the
RCO
locus in
B. juncea
has been associated with lobed-leaf formation, its complexity has remained largely unknown. This study involved the identification of 55
LMI1-like
genes in 16 species of Brassicaceae through syntenic analysis. We classified these
LMI1-like
genes into two types, namely
LMI1
-type and
RCO
-type, based on their phylogenetic relationship. Additionally, we proposed two independent lineage-specific evolution routes for
RCO
following the divergence of
Aethionema
. Our findings revealed that the
LMI1-like
loci responsible for lobed-leaf formation in
Brassica
species are located on the LF subgenomes. For
B. juncea
(T84-66V2), we discovered that the complex locus underwent duplication through segments of nucleic acid sequence containing
Exostosin
-
LMI1
-
RCO
(
E
-
R
-
L
), resulting in the tandem presence of two
RCO
-type and two
LMI1
-type genes on chromosome A10. As additional evidence, we successfully mapped the complex locus responsible for highly lobed-leaf formation to chromosome A10 using a
B. juncea
F
2
population, which corroborated the results of our evolutionary analysis. Furthermore, through transcriptome analysis, we clarified that
BjRCO.1
and
BjRCO.2
within the complex locus are functional genes involved in the regulation of highly lobed-leaf formation. The findings of this study offer valuable insights into the regulation of leaf morphology for the breeding of
Brassica
crops.
Key message
We detected a QTL
qHSW-16
undergone strong selection associated with seed weight and identified a novel candidate gene controlling seed weight candidate gene for this major QTL by ...qRT-PCT.
Soybean
Glycine max
(L.) Merr. provides more than half of the world’s oilseed production. To expand its germplasm resources useful for breeding increased yield and oil quality cultivars, it is necessary to resolve the diversity and evolutionary history of this crop. In this work, we resequenced 283 soybean accessions from China and obtained a large number of high-quality SNPs for investigation of the population genetics that underpin variation in seed weight and other agronomic traits. Selective signature analysis detected 78 (~ 25.0 Mb) and 39 (~ 22.60 Mb) novel putative selective signals that were selected during soybean domestication and improvement, respectively. Genome-wide association study (GWAS) identified five loci associated with seed weight. Among these QTLs,
qHSW-16
, overlapped with the improvement-selective region on chromosome 16, suggesting that this QTL may be underwent strong selection during soybean improvement. Of the 18 candidate genes in
qHSW-16
, only
SoyZH13_16G122400
showed higher expression levels in a large seed variety compared to a small seed variety during seed development. These results identify
SoyZH13_16G122400
as a novel candidate gene controlling seed weight and provide foundational insights into the molecular targets for breeding improvement of seed weight and potential seed yield in soybean.
Key Message
Predictive ability derived from gene expression and metabolic information was evaluated using genomic prediction methods based on datasets from a public maize panel.
With the rapid ...development of high throughput biological technologies, information from gene expression and metabolites has received growing attention in plant genetics and breeding. In this study, we evaluated the utility of gene expression and metabolic information for genomic prediction using data obtained from a maize diversity panel. Our results show that, when used as predictor variables, gene expression levels and metabolite abundances provided reasonable predictive abilities relative to those based on genetic markers, although these values were not as large as those with genetic markers. Integrating gene expression levels and metabolite abundances with genetic markers significantly improved predictive abilities in comparison to the benchmark genomic best linear unbiased prediction model using genome-wide markers only. Predictive abilities based on gene expression and metabolites were trait-specific and were affected by the time of measurement and tissue samples as well as the number of genes and metabolites included in the model. In general, our results suggest that, rather than being conventionally used as intermediate phenotypes, gene expression and metabolic information can be used as predictors for genomic prediction and help improve genetic gains for complex traits in breeding programs.
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