Rice Root Genetic Architecture: Meta-analysis from a Drought QTL Database

During the last 10 years, a large number of quantitative trait loci (QTLs) controlling rice root morphological parameters have been detected in several mapping populations by teams interested in improving drought resistance in rice. Compiling these data could be extremely helpful in identifying candidate genes by positioning consensus QTLs with more precision through meta-QTL analysis. We extracted information from 24 published papers on QTLs controlling 29 root parameters including root number, maximum root length, root thickness, root/shoot ratio, and root penetration index. A web-accessible database of 675 root QTLs detected in 12 populations was constructed. This database includes also all QTLs for drought resistance traits in rice published between 1995 and 2007. The physical position on the pseudo-chromosomes of the markers flanking each QTL was determined. An overview of the number of root QTLs in 5-Mb segments covering the whole genome revealed the existence of “hot spots,” The 32 trait × chromosome combinations comprising six or more QTLs were subjected to a meta-QTL analysis using the software package MetaQTL. The method enabled us both to determine the likely number of true QTLs in these areas using an Akaike information criterion and to estimate their position. The meta-QTL confidence intervals were notably reduced and, for the smallest ones, encompassed only a few genes.     

Identification of Rice QTLs for Important Agronomic Traits with Long-Kernel CSSL-Z741 and Three SSSLs

Rice kernel shape affects kernel quality (appearance) and yield (1000-kernel weight) and therefore is an important agronomic trait, but its inheritance is complicated. We identified a long-kernel rice chromosome segment substitution line (CSSL), Z741, derived from Nipponbare as a recipient and Xihui 18 as a donor parent. Z741 has six substitution segments distributed on rice chromosomes 3, 6, 7, 8 and 12 with an average replacement length of 5.82 Mb. Analysis of a secondary F₂ population from a cross between Nipponbare and Z741 identified 20 QTLs for important agronomic traits. The kernel length of Z741 is controlled by a major QTL (qKL3) and a minor QTL (qKL7). Candidate gene prediction and sequencing indicated that qKL3 may be an allele of OsPPKL1, which encodes a protein phosphatase implicated in brassinosteroid signaling, and qKL7 is an unreported QTL. Finally, we validated eight QTLs (qKL3, qKL7, qRLW3-1, qRLW7, qPH3-1, qKWT3, qKWT7 and qNPB6) using three selected single- segment substitution lines (SSSLs), S1, S2 and S3. Also, we detected five QTLs (qKL6, qKW3, qKW7, qKW6 and qRLW6) in S1, S2 and S3, which were not found in the Nipponbare/Z741 F₂ population. However, qNPB3, qNPB7 and qPL3 QTLs were not validated by the three SSSLs in 2019, suggesting that minor QTLs are susceptible to environmental factors. These results lay the foundation for studying the biodiversity of kernal length and molecular breeding of different kernel types.     

QTL mapping rolling,stomatal conductance and dimension traits of excised leaves in the Bala × Azucena recombinant inbred population of rice

The identification of markers linked to genes contributing to drought resistance promises opportunities to breed high yielding rice varieties for drought prone areas. Several studies using different mapping populations have previously identified quantitative trait loci (QTLs) for traits theoretically related to drought resistance. A mapping population of 176 F₆ recombinant inbred lines (RILs) derived from two upland rice varieties with contrasting aboveground drought avoidance traits (Bala and Azucena) with a linkage map of 157 markers was used to map QTLs for aboveground leaf morphological and physiological traits related to drought avoidance. Plants were grown for 6 weeks under controlled environmental conditions with three replications. Leaves were excised and placed on a balance. The rate of leaf rolling and water loss was recorded, after which leaf area, dry weight and specific leaf area were characterized. A simple method of estimating time to stomatal closure was employed. A total of 13 QTLs were detected for leaf morphological traits, three for initial transpiration and four for the proportion of water loss required to reach a specific advanced state of leaf rolling. No QTLs were detected for time of stomatal closure or speed of leaf rolling, nor for either water loss or transpiration at stomatal closure despite clear parental differences and moderate heritabilities in most of these traits. The co-location of QTLs for traits measured here and for drought avoidance previously reported from field experiments on chromosome 1, 3 and 5 link the genetics of drought resistance to leaf dimensions and physiology. However, a physiological explanation for a QTL for drought avoidance on chromosome 7 remains elusive.     

Land classification for choice of tree species on farm lands in the Attock District of Punjab,Pakistan

In Pakistan, particularly in Punjab Province, it is difficult for agrofarmers to combine their indigenous knowledge and modern scientific methods to evaluate existing traditional farming systems and forestry practices. This requires an evaluation of indigenous soil classification in simple terms along with knowledge of the local flora, especially trees. This study focuses on land suitability classification for trees in the Attock District of Punjab, Pakistan. A survey was conducted which included interviews of local agrofarmers as well as standard soil analyses including both chemical and physical determinations of local soil types. An evalu- ation of soil types for cultivation of various crops was carried out given its total extent, component soil series and their proportions, spotting characteristics of each soil series and their major limitations/hazards for trees/crops. These would lead to the identification of various tree species according to soil characteristics. Then, according to the soil types and species, a land suitability map was obtained for the choice of tree species by using geographic information system (GIS) software. Land suitability classification will help local agroforesters/agrofarmers in matching suitable agricultural trees/crops properly for different soils in the area.